diff --git a/Eigen/src/Array/Array.h b/Eigen/src/Array/Array.h
index e9fabcc..30d5529 100644
--- a/Eigen/src/Array/Array.h
+++ b/Eigen/src/Array/Array.h
@@ -101,7 +101,7 @@
       * is called a null matrix. This constructor is the unique way to create null matrices: resizing
       * a matrix to 0 is not supported.
       *
-      * \sa resize(int,int)
+      * \sa resize(Index,Index)
       */
     EIGEN_STRONG_INLINE explicit Array() : Base()
     {
@@ -126,7 +126,7 @@
       * it is redundant to pass the dimension here, so it makes more sense to use the default
       * constructor Matrix() instead.
       */
-    EIGEN_STRONG_INLINE explicit Array(int dim)
+    EIGEN_STRONG_INLINE explicit Array(Index dim)
       : Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
     {
       Base::_check_template_params();
@@ -149,7 +149,7 @@
       * This is useful for dynamic-size matrices. For fixed-size matrices,
       * it is redundant to pass these parameters, so one should use the default constructor
       * Matrix() instead. */
-    Array(int rows, int cols);
+    Array(Index rows, Index cols);
     /** constructs an initialized 2D vector with given coefficients */
     Array(const Scalar& x, const Scalar& y);
     #endif
@@ -217,8 +217,8 @@
     void swap(ArrayBase<OtherDerived> EIGEN_REF_TO_TEMPORARY other)
     { this->_swap(other.derived()); }
 
-    inline int innerStride() const { return 1; }
-    inline int outerStride() const { return this->innerSize(); }
+    inline Index innerStride() const { return 1; }
+    inline Index outerStride() const { return this->innerSize(); }
 
     #ifdef EIGEN_ARRAY_PLUGIN
     #include EIGEN_ARRAY_PLUGIN
diff --git a/Eigen/src/Array/ArrayBase.h b/Eigen/src/Array/ArrayBase.h
index b835a57..ccbc772 100644
--- a/Eigen/src/Array/ArrayBase.h
+++ b/Eigen/src/Array/ArrayBase.h
@@ -60,8 +60,11 @@
     using ei_special_scalar_op_base<Derived,typename ei_traits<Derived>::Scalar,
                 typename NumTraits<typename ei_traits<Derived>::Scalar>::Real>::operator*;
 
+    typedef typename ei_traits<Derived>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
     typedef typename ei_traits<Derived>::Scalar Scalar;
     typedef typename ei_packet_traits<Scalar>::type PacketScalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
 
     typedef DenseBase<Derived> Base;
     using Base::RowsAtCompileTime;
@@ -88,7 +91,6 @@
     using Base::operator*=;
     using Base::operator/=;
 
-    typedef typename Base::RealScalar RealScalar;
     typedef typename Base::CoeffReturnType CoeffReturnType;
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
@@ -161,8 +163,8 @@
     ArrayBase() : Base() {}
 
   private:
-    explicit ArrayBase(int);
-    ArrayBase(int,int);
+    explicit ArrayBase(Index);
+    ArrayBase(Index,Index);
     template<typename OtherDerived> explicit ArrayBase(const ArrayBase<OtherDerived>&);
 };
 
diff --git a/Eigen/src/Array/ArrayWrapper.h b/Eigen/src/Array/ArrayWrapper.h
index 83cd8ba..98d388d 100644
--- a/Eigen/src/Array/ArrayWrapper.h
+++ b/Eigen/src/Array/ArrayWrapper.h
@@ -53,51 +53,51 @@
 
     inline ArrayWrapper(const ExpressionType& matrix) : m_expression(matrix) {}
 
-    inline int rows() const { return m_expression.rows(); }
-    inline int cols() const { return m_expression.cols(); }
-    inline int outerStride() const { return m_expression.outerStride(); }
-    inline int innerStride() const { return m_expression.innerStride(); }
+    inline Index rows() const { return m_expression.rows(); }
+    inline Index cols() const { return m_expression.cols(); }
+    inline Index outerStride() const { return m_expression.outerStride(); }
+    inline Index innerStride() const { return m_expression.innerStride(); }
 
-    inline const CoeffReturnType coeff(int row, int col) const
+    inline const CoeffReturnType coeff(Index row, Index col) const
     {
       return m_expression.coeff(row, col);
     }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return m_expression.const_cast_derived().coeffRef(row, col);
     }
 
-    inline const CoeffReturnType coeff(int index) const
+    inline const CoeffReturnType coeff(Index index) const
     {
       return m_expression.coeff(index);
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       return m_expression.const_cast_derived().coeffRef(index);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int row, int col) const
+    inline const PacketScalar packet(Index row, Index col) const
     {
       return m_expression.template packet<LoadMode>(row, col);
     }
 
     template<int LoadMode>
-    inline void writePacket(int row, int col, const PacketScalar& x)
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
     {
       m_expression.const_cast_derived().template writePacket<LoadMode>(row, col, x);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int index) const
+    inline const PacketScalar packet(Index index) const
     {
       return m_expression.template packet<LoadMode>(index);
     }
 
     template<int LoadMode>
-    inline void writePacket(int index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& x)
     {
       m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
     }
@@ -138,51 +138,51 @@
 
     inline MatrixWrapper(const ExpressionType& matrix) : m_expression(matrix) {}
 
-    inline int rows() const { return m_expression.rows(); }
-    inline int cols() const { return m_expression.cols(); }
-    inline int outerStride() const { return m_expression.outerStride(); }
-    inline int innerStride() const { return m_expression.innerStride(); }
+    inline Index rows() const { return m_expression.rows(); }
+    inline Index cols() const { return m_expression.cols(); }
+    inline Index outerStride() const { return m_expression.outerStride(); }
+    inline Index innerStride() const { return m_expression.innerStride(); }
 
-    inline const CoeffReturnType coeff(int row, int col) const
+    inline const CoeffReturnType coeff(Index row, Index col) const
     {
       return m_expression.coeff(row, col);
     }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return m_expression.const_cast_derived().coeffRef(row, col);
     }
 
-    inline const CoeffReturnType coeff(int index) const
+    inline const CoeffReturnType coeff(Index index) const
     {
       return m_expression.coeff(index);
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       return m_expression.const_cast_derived().coeffRef(index);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int row, int col) const
+    inline const PacketScalar packet(Index row, Index col) const
     {
       return m_expression.template packet<LoadMode>(row, col);
     }
 
     template<int LoadMode>
-    inline void writePacket(int row, int col, const PacketScalar& x)
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
     {
       m_expression.const_cast_derived().template writePacket<LoadMode>(row, col, x);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int index) const
+    inline const PacketScalar packet(Index index) const
     {
       return m_expression.template packet<LoadMode>(index);
     }
 
     template<int LoadMode>
-    inline void writePacket(int index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& x)
     {
       m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
     }
diff --git a/Eigen/src/Array/BooleanRedux.h b/Eigen/src/Array/BooleanRedux.h
index 9c6985a..67c29f5 100644
--- a/Eigen/src/Array/BooleanRedux.h
+++ b/Eigen/src/Array/BooleanRedux.h
@@ -97,8 +97,8 @@
      >::run(derived());
   else
   {
-    for(int j = 0; j < cols(); ++j)
-      for(int i = 0; i < rows(); ++i)
+    for(Index j = 0; j < cols(); ++j)
+      for(Index i = 0; i < rows(); ++i)
         if (!coeff(i, j)) return false;
     return true;
   }
@@ -121,8 +121,8 @@
            >::run(derived());
   else
   {
-    for(int j = 0; j < cols(); ++j)
-      for(int i = 0; i < rows(); ++i)
+    for(Index j = 0; j < cols(); ++j)
+      for(Index i = 0; i < rows(); ++i)
         if (coeff(i, j)) return true;
     return false;
   }
@@ -135,9 +135,9 @@
   * \sa all(), any()
   */
 template<typename Derived>
-inline int DenseBase<Derived>::count() const
+inline typename DenseBase<Derived>::Index DenseBase<Derived>::count() const
 {
-  return derived().template cast<bool>().template cast<int>().sum();
+  return derived().template cast<bool>().template cast<Index>().sum();
 }
 
 #endif // EIGEN_ALLANDANY_H
diff --git a/Eigen/src/Array/Random.h b/Eigen/src/Array/Random.h
index 9a81c7b..c4c482b 100644
--- a/Eigen/src/Array/Random.h
+++ b/Eigen/src/Array/Random.h
@@ -27,7 +27,8 @@
 
 template<typename Scalar> struct ei_scalar_random_op {
   EIGEN_EMPTY_STRUCT_CTOR(ei_scalar_random_op)
-  inline const Scalar operator() (int, int = 0) const { return ei_random<Scalar>(); }
+  template<typename Index>
+  inline const Scalar operator() (Index, Index = 0) const { return ei_random<Scalar>(); }
 };
 template<typename Scalar>
 struct ei_functor_traits<ei_scalar_random_op<Scalar> >
@@ -51,11 +52,11 @@
   * a temporary matrix whenever it is nested in a larger expression. This prevents unexpected
   * behavior with expressions involving random matrices.
   *
-  * \sa MatrixBase::setRandom(), MatrixBase::Random(int), MatrixBase::Random()
+  * \sa MatrixBase::setRandom(), MatrixBase::Random(Index), MatrixBase::Random()
   */
 template<typename Derived>
 inline const CwiseNullaryOp<ei_scalar_random_op<typename ei_traits<Derived>::Scalar>, Derived>
-DenseBase<Derived>::Random(int rows, int cols)
+DenseBase<Derived>::Random(Index rows, Index cols)
 {
   return NullaryExpr(rows, cols, ei_scalar_random_op<Scalar>());
 }
@@ -80,11 +81,11 @@
   * a temporary vector whenever it is nested in a larger expression. This prevents unexpected
   * behavior with expressions involving random matrices.
   *
-  * \sa MatrixBase::setRandom(), MatrixBase::Random(int,int), MatrixBase::Random()
+  * \sa MatrixBase::setRandom(), MatrixBase::Random(Index,Index), MatrixBase::Random()
   */
 template<typename Derived>
 inline const CwiseNullaryOp<ei_scalar_random_op<typename ei_traits<Derived>::Scalar>, Derived>
-DenseBase<Derived>::Random(int size)
+DenseBase<Derived>::Random(Index size)
 {
   return NullaryExpr(size, ei_scalar_random_op<Scalar>());
 }
@@ -103,7 +104,7 @@
   * a temporary matrix whenever it is nested in a larger expression. This prevents unexpected
   * behavior with expressions involving random matrices.
   *
-  * \sa MatrixBase::setRandom(), MatrixBase::Random(int,int), MatrixBase::Random(int)
+  * \sa MatrixBase::setRandom(), MatrixBase::Random(Index,Index), MatrixBase::Random(Index)
   */
 template<typename Derived>
 inline const CwiseNullaryOp<ei_scalar_random_op<typename ei_traits<Derived>::Scalar>, Derived>
@@ -119,7 +120,7 @@
   * Example: \include MatrixBase_setRandom.cpp
   * Output: \verbinclude MatrixBase_setRandom.out
   *
-  * \sa class CwiseNullaryOp, setRandom(int), setRandom(int,int)
+  * \sa class CwiseNullaryOp, setRandom(Index), setRandom(Index,Index)
   */
 template<typename Derived>
 inline Derived& DenseBase<Derived>::setRandom()
@@ -134,11 +135,11 @@
   * Example: \include Matrix_setRandom_int.cpp
   * Output: \verbinclude Matrix_setRandom_int.out
   *
-  * \sa MatrixBase::setRandom(), setRandom(int,int), class CwiseNullaryOp, MatrixBase::Random()
+  * \sa MatrixBase::setRandom(), setRandom(Index,Index), class CwiseNullaryOp, MatrixBase::Random()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-DenseStorageBase<Derived>::setRandom(int size)
+DenseStorageBase<Derived>::setRandom(Index size)
 {
   resize(size);
   return setRandom();
@@ -152,11 +153,11 @@
   * Example: \include Matrix_setRandom_int_int.cpp
   * Output: \verbinclude Matrix_setRandom_int_int.out
   *
-  * \sa MatrixBase::setRandom(), setRandom(int), class CwiseNullaryOp, MatrixBase::Random()
+  * \sa MatrixBase::setRandom(), setRandom(Index), class CwiseNullaryOp, MatrixBase::Random()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-DenseStorageBase<Derived>::setRandom(int rows, int cols)
+DenseStorageBase<Derived>::setRandom(Index rows, Index cols)
 {
   resize(rows, cols);
   return setRandom();
diff --git a/Eigen/src/Array/Replicate.h b/Eigen/src/Array/Replicate.h
index 63e4683..c60d990 100644
--- a/Eigen/src/Array/Replicate.h
+++ b/Eigen/src/Array/Replicate.h
@@ -90,28 +90,28 @@
                           THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE)
     }
 
-    inline int rows() const { return m_matrix.rows() * m_rowFactor.value(); }
-    inline int cols() const { return m_matrix.cols() * m_colFactor.value(); }
+    inline Index rows() const { return m_matrix.rows() * m_rowFactor.value(); }
+    inline Index cols() const { return m_matrix.cols() * m_colFactor.value(); }
 
-    inline Scalar coeff(int row, int col) const
+    inline Scalar coeff(Index row, Index col) const
     {
       // try to avoid using modulo; this is a pure optimization strategy
-      const int actual_row  = ei_traits<MatrixType>::RowsAtCompileTime==1 ? 0
+      const Index actual_row  = ei_traits<MatrixType>::RowsAtCompileTime==1 ? 0
                             : RowFactor==1 ? row
                             : row%m_matrix.rows();
-      const int actual_col  = ei_traits<MatrixType>::ColsAtCompileTime==1 ? 0
+      const Index actual_col  = ei_traits<MatrixType>::ColsAtCompileTime==1 ? 0
                             : ColFactor==1 ? col
                             : col%m_matrix.cols();
 
       return m_matrix.coeff(actual_row, actual_col);
     }
     template<int LoadMode>
-    inline PacketScalar packet(int row, int col) const
+    inline PacketScalar packet(Index row, Index col) const
     {
-      const int actual_row  = ei_traits<MatrixType>::RowsAtCompileTime==1 ? 0
+      const Index actual_row  = ei_traits<MatrixType>::RowsAtCompileTime==1 ? 0
                             : RowFactor==1 ? row
                             : row%m_matrix.rows();
-      const int actual_col  = ei_traits<MatrixType>::ColsAtCompileTime==1 ? 0
+      const Index actual_col  = ei_traits<MatrixType>::ColsAtCompileTime==1 ? 0
                             : ColFactor==1 ? col
                             : col%m_matrix.cols();
 
@@ -121,8 +121,8 @@
 
   protected:
     const typename MatrixType::Nested m_matrix;
-    const ei_int_if_dynamic<RowFactor> m_rowFactor;
-    const ei_int_if_dynamic<ColFactor> m_colFactor;
+    const ei_variable_if_dynamic<Index, RowFactor> m_rowFactor;
+    const ei_variable_if_dynamic<Index, ColFactor> m_colFactor;
 };
 
 /** \nonstableyet
@@ -131,7 +131,7 @@
   * Example: \include MatrixBase_replicate.cpp
   * Output: \verbinclude MatrixBase_replicate.out
   *
-  * \sa VectorwiseOp::replicate(), DenseBase::replicate(int,int), class Replicate
+  * \sa VectorwiseOp::replicate(), DenseBase::replicate(Index,Index), class Replicate
   */
 template<typename Derived>
 template<int RowFactor, int ColFactor>
@@ -151,7 +151,7 @@
   */
 template<typename Derived>
 inline const Replicate<Derived,Dynamic,Dynamic>
-DenseBase<Derived>::replicate(int rowFactor,int colFactor) const
+DenseBase<Derived>::replicate(Index rowFactor,Index colFactor) const
 {
   return Replicate<Derived,Dynamic,Dynamic>(derived(),rowFactor,colFactor);
 }
@@ -166,7 +166,7 @@
   */
 template<typename ExpressionType, int Direction>
 const typename VectorwiseOp<ExpressionType,Direction>::ReplicateReturnType
-VectorwiseOp<ExpressionType,Direction>::replicate(int factor) const
+VectorwiseOp<ExpressionType,Direction>::replicate(Index factor) const
 {
   return typename VectorwiseOp<ExpressionType,Direction>::ReplicateReturnType
           (_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1);
diff --git a/Eigen/src/Array/Reverse.h b/Eigen/src/Array/Reverse.h
index 0f56d5d..cca4251 100644
--- a/Eigen/src/Array/Reverse.h
+++ b/Eigen/src/Array/Reverse.h
@@ -103,33 +103,33 @@
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Reverse)
 
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return m_matrix.const_cast_derived().coeffRef(ReverseRow ? m_matrix.rows() - row - 1 : row,
                                                     ReverseCol ? m_matrix.cols() - col - 1 : col);
     }
 
-    inline const Scalar coeff(int row, int col) const
+    inline const Scalar coeff(Index row, Index col) const
     {
       return m_matrix.coeff(ReverseRow ? m_matrix.rows() - row - 1 : row,
                             ReverseCol ? m_matrix.cols() - col - 1 : col);
     }
 
-    inline const Scalar coeff(int index) const
+    inline const Scalar coeff(Index index) const
     {
       return m_matrix.coeff(m_matrix.size() - index - 1);
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       return m_matrix.const_cast_derived().coeffRef(m_matrix.size() - index - 1);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int row, int col) const
+    inline const PacketScalar packet(Index row, Index col) const
     {
       return reverse_packet::run(m_matrix.template packet<LoadMode>(
                                     ReverseRow ? m_matrix.rows() - row - OffsetRow : row,
@@ -137,7 +137,7 @@
     }
 
     template<int LoadMode>
-    inline void writePacket(int row, int col, const PacketScalar& x)
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
     {
       m_matrix.const_cast_derived().template writePacket<LoadMode>(
                                       ReverseRow ? m_matrix.rows() - row - OffsetRow : row,
@@ -146,13 +146,13 @@
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int index) const
+    inline const PacketScalar packet(Index index) const
     {
       return ei_preverse(m_matrix.template packet<LoadMode>( m_matrix.size() - index - PacketSize ));
     }
 
     template<int LoadMode>
-    inline void writePacket(int index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& x)
     {
       m_matrix.const_cast_derived().template writePacket<LoadMode>(m_matrix.size() - index - PacketSize, ei_preverse(x));
     }
diff --git a/Eigen/src/Array/Select.h b/Eigen/src/Array/Select.h
index 100a264..8834156 100644
--- a/Eigen/src/Array/Select.h
+++ b/Eigen/src/Array/Select.h
@@ -81,10 +81,10 @@
       ei_assert(m_condition.cols() == m_then.cols() && m_condition.cols() == m_else.cols());
     }
 
-    int rows() const { return m_condition.rows(); }
-    int cols() const { return m_condition.cols(); }
+    Index rows() const { return m_condition.rows(); }
+    Index cols() const { return m_condition.cols(); }
 
-    const Scalar coeff(int i, int j) const
+    const Scalar coeff(Index i, Index j) const
     {
       if (m_condition.coeff(i,j))
         return m_then.coeff(i,j);
@@ -92,7 +92,7 @@
         return m_else.coeff(i,j);
     }
 
-    const Scalar coeff(int i) const
+    const Scalar coeff(Index i) const
     {
       if (m_condition.coeff(i))
         return m_then.coeff(i);
diff --git a/Eigen/src/Array/VectorwiseOp.h b/Eigen/src/Array/VectorwiseOp.h
index c1f17f6..e338a91 100644
--- a/Eigen/src/Array/VectorwiseOp.h
+++ b/Eigen/src/Array/VectorwiseOp.h
@@ -89,10 +89,10 @@
     PartialReduxExpr(const MatrixType& mat, const MemberOp& func = MemberOp())
       : m_matrix(mat), m_functor(func) {}
 
-    int rows() const { return (Direction==Vertical   ? 1 : m_matrix.rows()); }
-    int cols() const { return (Direction==Horizontal ? 1 : m_matrix.cols()); }
+    Index rows() const { return (Direction==Vertical   ? 1 : m_matrix.rows()); }
+    Index cols() const { return (Direction==Horizontal ? 1 : m_matrix.cols()); }
 
-    const Scalar coeff(int i, int j) const
+    const Scalar coeff(Index i, Index j) const
     {
       if (Direction==Vertical)
         return m_functor(m_matrix.col(j));
@@ -100,7 +100,7 @@
         return m_functor(m_matrix.row(i));
     }
 
-    const Scalar coeff(int index) const
+    const Scalar coeff(Index index) const
     {
       if (Direction==Vertical)
         return m_functor(m_matrix.col(index));
@@ -177,7 +177,8 @@
 {
   public:
 
-    typedef typename ei_traits<ExpressionType>::Scalar Scalar;
+    typedef typename ExpressionType::Scalar Scalar;
+    typedef typename ExpressionType::Index Index;
     typedef typename ei_meta_if<ei_must_nest_by_value<ExpressionType>::ret,
         ExpressionType, const ExpressionType&>::ret ExpressionTypeNested;
 
@@ -209,14 +210,14 @@
     typedef typename ei_meta_if<Direction==Vertical,
                                typename ExpressionType::ColXpr,
                                typename ExpressionType::RowXpr>::ret SubVector;
-    SubVector subVector(int i)
+    SubVector subVector(Index i)
     {
       return SubVector(m_matrix.derived(),i);
     }
 
     /** \internal
       * \returns the number of subvectors in the direction \c Direction */
-    int subVectors() const
+    Index subVectors() const
     { return Direction==Vertical?m_matrix.cols():m_matrix.rows(); }
 
     template<typename OtherDerived> struct ExtendedType {
@@ -362,7 +363,7 @@
       * Output: \verbinclude PartialRedux_count.out
       *
       * \sa DenseBase::count() */
-    const PartialReduxExpr<ExpressionType, ei_member_count<int>, Direction> count() const
+    const PartialReduxExpr<ExpressionType, ei_member_count<Index>, Direction> count() const
     { return _expression(); }
 
     /** \returns a row (or column) vector expression of the product
@@ -387,7 +388,7 @@
     { return Reverse<ExpressionType, Direction>( _expression() ); }
 
     typedef Replicate<ExpressionType,Direction==Vertical?Dynamic:1,Direction==Horizontal?Dynamic:1> ReplicateReturnType;
-    const ReplicateReturnType replicate(int factor) const;
+    const ReplicateReturnType replicate(Index factor) const;
 
     /** \nonstableyet
       * \return an expression of the replication of each column (or row) of \c *this
@@ -395,11 +396,11 @@
       * Example: \include DirectionWise_replicate.cpp
       * Output: \verbinclude DirectionWise_replicate.out
       *
-      * \sa VectorwiseOp::replicate(int), DenseBase::replicate(), class Replicate
+      * \sa VectorwiseOp::replicate(Index), DenseBase::replicate(), class Replicate
       */
     // NOTE implemented here because of sunstudio's compilation errors
     template<int Factor> const Replicate<ExpressionType,(IsVertical?Factor:1),(IsHorizontal?Factor:1)>
-    replicate(int factor = Factor) const
+    replicate(Index factor = Factor) const
     {
       return Replicate<ExpressionType,Direction==Vertical?Factor:1,Direction==Horizontal?Factor:1>
           (_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1);
@@ -413,7 +414,7 @@
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
       //ei_assert((m_matrix.isNull()) == (other.isNull())); FIXME
-      for(int j=0; j<subVectors(); ++j)
+      for(Index j=0; j<subVectors(); ++j)
         subVector(j) = other;
       return const_cast<ExpressionType&>(m_matrix);
     }
@@ -423,7 +424,7 @@
     ExpressionType& operator+=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      for(int j=0; j<subVectors(); ++j)
+      for(Index j=0; j<subVectors(); ++j)
         subVector(j) += other.derived();
       return const_cast<ExpressionType&>(m_matrix);
     }
@@ -433,7 +434,7 @@
     ExpressionType& operator-=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      for(int j=0; j<subVectors(); ++j)
+      for(Index j=0; j<subVectors(); ++j)
         subVector(j) -= other.derived();
       return const_cast<ExpressionType&>(m_matrix);
     }
diff --git a/Eigen/src/Cholesky/LDLT.h b/Eigen/src/Cholesky/LDLT.h
index 206ccef..a433f8d 100644
--- a/Eigen/src/Cholesky/LDLT.h
+++ b/Eigen/src/Cholesky/LDLT.h
@@ -65,7 +65,8 @@
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef typename ei_plain_col_type<MatrixType, int>::type IntColVectorType;
+    typedef typename MatrixType::Index Index;
+    typedef typename ei_plain_col_type<MatrixType, Index>::type IntColVectorType;
     typedef Matrix<Scalar, RowsAtCompileTime, 1, Options, MaxRowsAtCompileTime, 1> TmpMatrixType;
 
     /** \brief Default Constructor.
@@ -81,7 +82,7 @@
       * according to the specified problem \a size.
       * \sa LDLT()
       */
-    LDLT(int size) : m_matrix(size, size),
+    LDLT(Index size) : m_matrix(size, size),
                      m_p(size),
                      m_transpositions(size),
                      m_temporary(size),
@@ -168,8 +169,8 @@
 
     MatrixType reconstructedMatrix() const;
 
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
 
   protected:
     /** \internal
@@ -182,7 +183,7 @@
     IntColVectorType m_p;
     IntColVectorType m_transpositions; // FIXME do we really need to store permanently the transpositions?
     TmpMatrixType m_temporary;
-    int m_sign;
+    Index m_sign;
     bool m_isInitialized;
 };
 
@@ -192,7 +193,7 @@
 LDLT<MatrixType>& LDLT<MatrixType>::compute(const MatrixType& a)
 {
   ei_assert(a.rows()==a.cols());
-  const int size = a.rows();
+  const Index size = a.rows();
 
   m_matrix = a;
 
@@ -215,10 +216,10 @@
   // have optimal alignment.
   m_temporary.resize(size);
 
-  for (int j = 0; j < size; ++j)
+  for (Index j = 0; j < size; ++j)
   {
     // Find largest diagonal element
-    int index_of_biggest_in_corner;
+    Index index_of_biggest_in_corner;
     biggest_in_corner = m_matrix.diagonal().tail(size-j).cwiseAbs()
                        .maxCoeff(&index_of_biggest_in_corner);
     index_of_biggest_in_corner += j;
@@ -236,7 +237,7 @@
     // Finish early if the matrix is not full rank.
     if(biggest_in_corner < cutoff)
     {
-      for(int i = j; i < size; i++) m_transpositions.coeffRef(i) = i;
+      for(Index i = j; i < size; i++) m_transpositions.coeffRef(i) = i;
       break;
     }
 
@@ -256,7 +257,7 @@
     RealScalar Djj = ei_real(m_matrix.coeff(j,j) -  m_matrix.row(j).head(j).dot(m_matrix.col(j).head(j)));
     m_matrix.coeffRef(j,j) = Djj;
 
-    int endSize = size - j - 1;
+    Index endSize = size - j - 1;
     if (endSize > 0) {
       m_temporary.tail(endSize).noalias() = m_matrix.block(j+1,0, endSize, j)
                                 * m_matrix.col(j).head(j).conjugate();
@@ -272,8 +273,8 @@
   }
 
   // Reverse applied swaps to get P matrix.
-  for(int k = 0; k < size; ++k) m_p.coeffRef(k) = k;
-  for(int k = size-1; k >= 0; --k) {
+  for(Index k = 0; k < size; ++k) m_p.coeffRef(k) = k;
+  for(Index k = size-1; k >= 0; --k) {
     std::swap(m_p.coeffRef(k), m_p.coeffRef(m_transpositions.coeff(k)));
   }
 
@@ -310,11 +311,11 @@
 bool LDLT<MatrixType>::solveInPlace(MatrixBase<Derived> &bAndX) const
 {
   ei_assert(m_isInitialized && "LDLT is not initialized.");
-  const int size = m_matrix.rows();
+  const Index size = m_matrix.rows();
   ei_assert(size == bAndX.rows());
 
   // z = P b
-  for(int i = 0; i < size; ++i) bAndX.row(m_transpositions.coeff(i)).swap(bAndX.row(i));
+  for(Index i = 0; i < size; ++i) bAndX.row(m_transpositions.coeff(i)).swap(bAndX.row(i));
 
   // y = L^-1 z
   //matrixL().solveInPlace(bAndX);
@@ -327,7 +328,7 @@
   m_matrix.adjoint().template triangularView<UnitUpper>().solveInPlace(bAndX);
 
   // x = P^T u
-  for (int i = size-1; i >= 0; --i) bAndX.row(m_transpositions.coeff(i)).swap(bAndX.row(i));
+  for (Index i = size-1; i >= 0; --i) bAndX.row(m_transpositions.coeff(i)).swap(bAndX.row(i));
 
   return true;
 }
@@ -339,12 +340,12 @@
 MatrixType LDLT<MatrixType>::reconstructedMatrix() const
 {
   ei_assert(m_isInitialized && "LDLT is not initialized.");
-  const int size = m_matrix.rows();
+  const Index size = m_matrix.rows();
   MatrixType res(size,size);
   res.setIdentity();
 
   // PI
-  for(int i = 0; i < size; ++i) res.row(m_transpositions.coeff(i)).swap(res.row(i));
+  for(Index i = 0; i < size; ++i) res.row(m_transpositions.coeff(i)).swap(res.row(i));
   // L^* P
   res = matrixL().adjoint() * res;
   // D(L^*P)
@@ -352,7 +353,7 @@
   // L(DL^*P)
   res = matrixL() * res;
   // P^T (LDL^*P)
-  for (int i = size-1; i >= 0; --i) res.row(m_transpositions.coeff(i)).swap(res.row(i));
+  for (Index i = size-1; i >= 0; --i) res.row(m_transpositions.coeff(i)).swap(res.row(i));
 
   return res;
 }
diff --git a/Eigen/src/Cholesky/LLT.h b/Eigen/src/Cholesky/LLT.h
index 22d0c91..29fa465 100644
--- a/Eigen/src/Cholesky/LLT.h
+++ b/Eigen/src/Cholesky/LLT.h
@@ -65,6 +65,7 @@
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
+    typedef typename MatrixType::Index Index;
 
     enum {
       PacketSize = ei_packet_traits<Scalar>::size,
@@ -88,7 +89,7 @@
       * according to the specified problem \a size.
       * \sa LLT()
       */
-    LLT(int size) : m_matrix(size, size),
+    LLT(Index size) : m_matrix(size, size),
                     m_isInitialized(false) {}
 
     LLT(const MatrixType& matrix)
@@ -149,8 +150,8 @@
 
     MatrixType reconstructedMatrix() const;
 
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
 
   protected:
     /** \internal
@@ -171,11 +172,12 @@
   {
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
     ei_assert(mat.rows()==mat.cols());
-    const int size = mat.rows();
-    for(int k = 0; k < size; ++k)
+    const Index size = mat.rows();
+    for(Index k = 0; k < size; ++k)
     {
-      int rs = size-k-1; // remaining size
+      Index rs = size-k-1; // remaining size
 
       Block<MatrixType,Dynamic,1> A21(mat,k+1,k,rs,1);
       Block<MatrixType,1,Dynamic> A10(mat,k,0,1,k);
@@ -195,19 +197,20 @@
   template<typename MatrixType>
   static bool blocked(MatrixType& m)
   {
+    typedef typename MatrixType::Index Index;
     ei_assert(m.rows()==m.cols());
-    int size = m.rows();
+    Index size = m.rows();
     if(size<32)
       return unblocked(m);
 
-    int blockSize = size/8;
+    Index blockSize = size/8;
     blockSize = (blockSize/16)*16;
-    blockSize = std::min(std::max(blockSize,8), 128);
+    blockSize = std::min(std::max(blockSize,Index(8)), Index(128));
 
-    for (int k=0; k<size; k+=blockSize)
+    for (Index k=0; k<size; k+=blockSize)
     {
-      int bs = std::min(blockSize, size-k);
-      int rs = size - k - bs;
+      Index bs = std::min(blockSize, size-k);
+      Index rs = size - k - bs;
 
       Block<MatrixType,Dynamic,Dynamic> A11(m,k,   k,   bs,bs);
       Block<MatrixType,Dynamic,Dynamic> A21(m,k+bs,k,   rs,bs);
@@ -266,7 +269,7 @@
 LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
 {
   assert(a.rows()==a.cols());
-  const int size = a.rows();
+  const Index size = a.rows();
   m_matrix.resize(size, size);
   m_matrix = a;
 
diff --git a/Eigen/src/Core/Assign.h b/Eigen/src/Core/Assign.h
index eb7bca1..494df7b 100644
--- a/Eigen/src/Core/Assign.h
+++ b/Eigen/src/Core/Assign.h
@@ -254,12 +254,13 @@
 template<typename Derived1, typename Derived2>
 struct ei_assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling>
 {
+  typedef typename Derived1::Index Index;
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    const int innerSize = dst.innerSize();
-    const int outerSize = dst.outerSize();
-    for(int outer = 0; outer < outerSize; ++outer)
-      for(int inner = 0; inner < innerSize; ++inner)
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
+      for(Index inner = 0; inner < innerSize; ++inner)
         dst.copyCoeffByOuterInner(outer, inner, src);
   }
 };
@@ -277,10 +278,11 @@
 template<typename Derived1, typename Derived2>
 struct ei_assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling>
 {
+  typedef typename Derived1::Index Index;
   EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
-    const int outerSize = dst.outerSize();
-    for(int outer = 0; outer < outerSize; ++outer)
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
       ei_assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
         ::run(dst, src, outer);
   }
@@ -293,10 +295,11 @@
 template<typename Derived1, typename Derived2>
 struct ei_assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling>
 {
+  typedef typename Derived1::Index Index;
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    const int size = dst.size();
-    for(int i = 0; i < size; ++i)
+    const Index size = dst.size();
+    for(Index i = 0; i < size; ++i)
       dst.copyCoeff(i, src);
   }
 };
@@ -318,13 +321,14 @@
 template<typename Derived1, typename Derived2>
 struct ei_assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling>
 {
+  typedef typename Derived1::Index Index;
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    const int innerSize = dst.innerSize();
-    const int outerSize = dst.outerSize();
-    const int packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
-    for(int outer = 0; outer < outerSize; ++outer)
-      for(int inner = 0; inner < innerSize; inner+=packetSize)
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    const Index packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
+    for(Index outer = 0; outer < outerSize; ++outer)
+      for(Index inner = 0; inner < innerSize; inner+=packetSize)
         dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, inner, src);
   }
 };
@@ -342,10 +346,11 @@
 template<typename Derived1, typename Derived2>
 struct ei_assign_impl<Derived1, Derived2, InnerVectorizedTraversal, InnerUnrolling>
 {
+  typedef typename Derived1::Index Index;
   EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
-    const int outerSize = dst.outerSize();
-    for(int outer = 0; outer < outerSize; ++outer)
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
       ei_assign_innervec_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
         ::run(dst, src, outer);
   }
@@ -359,7 +364,7 @@
 struct ei_unaligned_assign_impl
 {
   template <typename Derived, typename OtherDerived>
-  static EIGEN_STRONG_INLINE void run(const Derived&, OtherDerived&, int, int) {}
+  static EIGEN_STRONG_INLINE void run(const Derived&, OtherDerived&, typename Derived::Index, typename Derived::Index) {}
 };
 
 template <>
@@ -369,13 +374,13 @@
   // packet access path.
 #ifdef _MSC_VER
   template <typename Derived, typename OtherDerived>
-  static EIGEN_DONT_INLINE void run(const Derived& src, OtherDerived& dst, int start, int end)
+  static EIGEN_DONT_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
 #else
   template <typename Derived, typename OtherDerived>
-  static EIGEN_STRONG_INLINE void run(const Derived& src, OtherDerived& dst, int start, int end)
+  static EIGEN_STRONG_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
 #endif
   {
-    for (int index = start; index < end; ++index)
+    for (typename Derived::Index index = start; index < end; ++index)
       dst.copyCoeff(index, src);
   }
 };
@@ -383,17 +388,18 @@
 template<typename Derived1, typename Derived2>
 struct ei_assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling>
 {
+  typedef typename Derived1::Index Index;
   EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
-    const int size = dst.size();
-    const int packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
-    const int alignedStart = ei_assign_traits<Derived1,Derived2>::DstIsAligned ? 0
-                           : ei_first_aligned(&dst.coeffRef(0), size);
-    const int alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
+    const Index size = dst.size();
+    const Index packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
+    const Index alignedStart = ei_assign_traits<Derived1,Derived2>::DstIsAligned ? 0
+                             : ei_first_aligned(&dst.coeffRef(0), size);
+    const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
 
     ei_unaligned_assign_impl<ei_assign_traits<Derived1,Derived2>::DstIsAligned!=0>::run(src,dst,0,alignedStart);
 
-    for(int index = alignedStart; index < alignedEnd; index += packetSize)
+    for(Index index = alignedStart; index < alignedEnd; index += packetSize)
     {
       dst.template copyPacket<Derived2, Aligned, ei_assign_traits<Derived1,Derived2>::JointAlignment>(index, src);
     }
@@ -405,11 +411,12 @@
 template<typename Derived1, typename Derived2>
 struct ei_assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnrolling>
 {
+  typedef typename Derived1::Index Index;
   EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
-    const int size = Derived1::SizeAtCompileTime;
-    const int packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
-    const int alignedSize = (size/packetSize)*packetSize;
+    const Index size = Derived1::SizeAtCompileTime;
+    const Index packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
+    const Index alignedSize = (size/packetSize)*packetSize;
 
     ei_assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, alignedSize>::run(dst, src);
     ei_assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, alignedSize, size>::run(dst, src);
@@ -423,32 +430,33 @@
 template<typename Derived1, typename Derived2>
 struct ei_assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling>
 {
+  typedef typename Derived1::Index Index;
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    const int packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
-    const int packetAlignedMask = packetSize - 1;
-    const int innerSize = dst.innerSize();
-    const int outerSize = dst.outerSize();
-    const int alignedStep = (packetSize - dst.outerStride() % packetSize) & packetAlignedMask;
-    int alignedStart = ei_assign_traits<Derived1,Derived2>::DstIsAligned ? 0
-                     : ei_first_aligned(&dst.coeffRef(0,0), innerSize);
+    const Index packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
+    const Index packetAlignedMask = packetSize - 1;
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    const Index alignedStep = (packetSize - dst.outerStride() % packetSize) & packetAlignedMask;
+    Index alignedStart = ei_assign_traits<Derived1,Derived2>::DstIsAligned ? 0
+                       : ei_first_aligned(&dst.coeffRef(0,0), innerSize);
 
-    for(int outer = 0; outer < outerSize; ++outer)
+    for(Index outer = 0; outer < outerSize; ++outer)
     {
-      const int alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
+      const Index alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
       // do the non-vectorizable part of the assignment
-      for(int inner = 0; inner<alignedStart ; ++inner)
+      for(Index inner = 0; inner<alignedStart ; ++inner)
         dst.copyCoeffByOuterInner(outer, inner, src);
 
       // do the vectorizable part of the assignment
-      for(int inner = alignedStart; inner<alignedEnd; inner+=packetSize)
+      for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize)
         dst.template copyPacketByOuterInner<Derived2, Aligned, Unaligned>(outer, inner, src);
 
       // do the non-vectorizable part of the assignment
-      for(int inner = alignedEnd; inner<innerSize ; ++inner)
+      for(Index inner = alignedEnd; inner<innerSize ; ++inner)
         dst.copyCoeffByOuterInner(outer, inner, src);
 
-      alignedStart = std::min<int>((alignedStart+alignedStep)%packetSize, innerSize);
+      alignedStart = std::min<Index>((alignedStart+alignedStep)%packetSize, innerSize);
     }
   }
 };
diff --git a/Eigen/src/Core/BandMatrix.h b/Eigen/src/Core/BandMatrix.h
index 432df0b..fbe7e39 100644
--- a/Eigen/src/Core/BandMatrix.h
+++ b/Eigen/src/Core/BandMatrix.h
@@ -46,6 +46,7 @@
 struct ei_traits<BandMatrix<_Scalar,Rows,Cols,Supers,Subs,Options> >
 {
   typedef _Scalar Scalar;
+  typedef Dense StorageKind;
   enum {
     CoeffReadCost = NumTraits<Scalar>::ReadCost,
     RowsAtCompileTime = Rows,
@@ -71,6 +72,7 @@
     };
     typedef typename ei_traits<BandMatrix>::Scalar Scalar;
     typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> DenseMatrixType;
+    typedef typename DenseMatrixType::Index Index;
 
   protected:
     enum {
@@ -83,7 +85,7 @@
 
   public:
 
-    inline BandMatrix(int rows=Rows, int cols=Cols, int supers=Supers, int subs=Subs)
+    inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs)
       : m_data(1+supers+subs,cols),
         m_rows(rows), m_supers(supers), m_subs(subs)
     {
@@ -91,32 +93,32 @@
     }
 
     /** \returns the number of columns */
-    inline int rows() const { return m_rows.value(); }
+    inline Index rows() const { return m_rows.value(); }
 
     /** \returns the number of rows */
-    inline int cols() const { return m_data.cols(); }
+    inline Index cols() const { return m_data.cols(); }
 
     /** \returns the number of super diagonals */
-    inline int supers() const { return m_supers.value(); }
+    inline Index supers() const { return m_supers.value(); }
 
     /** \returns the number of sub diagonals */
-    inline int subs() const { return m_subs.value(); }
+    inline Index subs() const { return m_subs.value(); }
 
     /** \returns a vector expression of the \a i -th column,
       * only the meaningful part is returned.
       * \warning the internal storage must be column major. */
-    inline Block<DataType,Dynamic,1> col(int i)
+    inline Block<DataType,Dynamic,1> col(Index i)
     {
       EIGEN_STATIC_ASSERT((Options&RowMajor)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
-      int start = 0;
-      int len = m_data.rows();
+      Index start = 0;
+      Index len = m_data.rows();
       if (i<=supers())
       {
         start = supers()-i;
-        len = std::min(rows(),std::max(0,m_data.rows() - (supers()-i)));
+        len = std::min(rows(),std::max<Index>(0,m_data.rows() - (supers()-i)));
       }
       else if (i>=rows()-subs())
-        len = std::max(0,m_data.rows() - (i + 1 - rows() + subs()));
+        len = std::max<Index>(0,m_data.rows() - (i + 1 - rows() + subs()));
       return Block<DataType,Dynamic,1>(m_data, start, i, len, 1);
     }
 
@@ -146,30 +148,30 @@
                  BuildType>::ret Type;
     };
 
-    /** \returns a vector expression of the \a Index -th sub or super diagonal */
-    template<int Index> inline typename DiagonalIntReturnType<Index>::Type diagonal()
+    /** \returns a vector expression of the \a N -th sub or super diagonal */
+    template<int N> inline typename DiagonalIntReturnType<N>::Type diagonal()
     {
-      return typename DiagonalIntReturnType<Index>::BuildType(m_data, supers()-Index, std::max(0,Index), 1, diagonalLength(Index));
+      return typename DiagonalIntReturnType<N>::BuildType(m_data, supers()-N, std::max(0,N), 1, diagonalLength(N));
     }
 
-    /** \returns a vector expression of the \a Index -th sub or super diagonal */
-    template<int Index> inline const typename DiagonalIntReturnType<Index>::Type diagonal() const
+    /** \returns a vector expression of the \a N -th sub or super diagonal */
+    template<int N> inline const typename DiagonalIntReturnType<N>::Type diagonal() const
     {
-      return typename DiagonalIntReturnType<Index>::BuildType(m_data, supers()-Index, std::max(0,Index), 1, diagonalLength(Index));
+      return typename DiagonalIntReturnType<N>::BuildType(m_data, supers()-N, std::max(0,N), 1, diagonalLength(N));
     }
 
     /** \returns a vector expression of the \a i -th sub or super diagonal */
-    inline Block<DataType,1,Dynamic> diagonal(int i)
+    inline Block<DataType,1,Dynamic> diagonal(Index i)
     {
       ei_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers()));
-      return Block<DataType,1,Dynamic>(m_data, supers()-i, std::max(0,i), 1, diagonalLength(i));
+      return Block<DataType,1,Dynamic>(m_data, supers()-i, std::max<Index>(0,i), 1, diagonalLength(i));
     }
 
     /** \returns a vector expression of the \a i -th sub or super diagonal */
-    inline const Block<DataType,1,Dynamic> diagonal(int i) const
+    inline const Block<DataType,1,Dynamic> diagonal(Index i) const
     {
       ei_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers()));
-      return Block<DataType,1,Dynamic>(m_data, supers()-i, std::max(0,i), 1, diagonalLength(i));
+      return Block<DataType,1,Dynamic>(m_data, supers()-i, std::max<Index>(0,i), 1, diagonalLength(i));
     }
 
     template<typename Dest> inline void evalTo(Dest& dst) const
@@ -177,9 +179,9 @@
       dst.resize(rows(),cols());
       dst.setZero();
       dst.diagonal() = diagonal();
-      for (int i=1; i<=supers();++i)
+      for (Index i=1; i<=supers();++i)
         dst.diagonal(i) = diagonal(i);
-      for (int i=1; i<=subs();++i)
+      for (Index i=1; i<=subs();++i)
         dst.diagonal(-i) = diagonal(-i);
     }
 
@@ -192,13 +194,13 @@
 
   protected:
 
-    inline int diagonalLength(int i) const
+    inline Index diagonalLength(Index i) const
     { return i<0 ? std::min(cols(),rows()+i) : std::min(rows(),cols()-i); }
 
     DataType m_data;
-    ei_int_if_dynamic<Rows>   m_rows;
-    ei_int_if_dynamic<Supers> m_supers;
-    ei_int_if_dynamic<Subs>   m_subs;
+    ei_variable_if_dynamic<Index, Rows>   m_rows;
+    ei_variable_if_dynamic<Index, Supers> m_supers;
+    ei_variable_if_dynamic<Index, Subs>   m_subs;
 };
 
 /** \nonstableyet
@@ -216,8 +218,9 @@
 class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor>
 {
     typedef BandMatrix<Scalar,Size,Size,1,Options&SelfAdjoint?0:1,Options|RowMajor> Base;
+    typedef typename Base::Index Index;
   public:
-    TridiagonalMatrix(int size = Size) : Base(size,size,1,1) {}
+    TridiagonalMatrix(Index size = Size) : Base(size,size,1,1) {}
 
     inline typename Base::template DiagonalIntReturnType<1>::Type super()
     { return Base::template diagonal<1>(); }
diff --git a/Eigen/src/Core/Block.h b/Eigen/src/Core/Block.h
index 79c9dd4..bb1b8a6 100644
--- a/Eigen/src/Core/Block.h
+++ b/Eigen/src/Core/Block.h
@@ -36,7 +36,7 @@
   * \param _DirectAccessStatus \internal used for partial specialization
   *
   * This class represents an expression of either a fixed-size or dynamic-size block. It is the return
-  * type of DenseBase::block(int,int,int,int) and DenseBase::block<int,int>(int,int) and
+  * type of DenseBase::block(Index,Index,Index,Index) and DenseBase::block<int,int>(Index,Index) and
   * most of the time this is the only way it is used.
   *
   * However, if you want to directly maniputate block expressions,
@@ -55,7 +55,7 @@
   * \include class_FixedBlock.cpp
   * Output: \verbinclude class_FixedBlock.out
   *
-  * \sa DenseBase::block(int,int,int,int), DenseBase::block(int,int), class VectorBlock
+  * \sa DenseBase::block(Index,Index,Index,Index), DenseBase::block(Index,Index), class VectorBlock
   */
 template<typename XprType, int BlockRows, int BlockCols, bool HasDirectAccess>
 struct ei_traits<Block<XprType, BlockRows, BlockCols, HasDirectAccess> > : ei_traits<XprType>
@@ -110,7 +110,7 @@
 
     /** Column or Row constructor
       */
-    inline Block(const XprType& xpr, int i)
+    inline Block(const XprType& xpr, Index i)
       : m_xpr(xpr),
         // It is a row if and only if BlockRows==1 and BlockCols==XprType::ColsAtCompileTime,
         // and it is a column if and only if BlockRows==XprType::RowsAtCompileTime and BlockCols==1,
@@ -128,7 +128,7 @@
 
     /** Fixed-size constructor
       */
-    inline Block(const XprType& xpr, int startRow, int startCol)
+    inline Block(const XprType& xpr, Index startRow, Index startCol)
       : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
         m_blockRows(BlockRows), m_blockCols(BlockCols)
     {
@@ -140,8 +140,8 @@
     /** Dynamic-size constructor
       */
     inline Block(const XprType& xpr,
-          int startRow, int startCol,
-          int blockRows, int blockCols)
+          Index startRow, Index startCol,
+          Index blockRows, Index blockCols)
       : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
                           m_blockRows(blockRows), m_blockCols(blockCols)
     {
@@ -153,28 +153,28 @@
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
 
-    inline int rows() const { return m_blockRows.value(); }
-    inline int cols() const { return m_blockCols.value(); }
+    inline Index rows() const { return m_blockRows.value(); }
+    inline Index cols() const { return m_blockCols.value(); }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return m_xpr.const_cast_derived()
                .coeffRef(row + m_startRow.value(), col + m_startCol.value());
     }
 
-    inline const CoeffReturnType coeff(int row, int col) const
+    inline const CoeffReturnType coeff(Index row, Index col) const
     {
       return m_xpr.coeff(row + m_startRow.value(), col + m_startCol.value());
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       return m_xpr.const_cast_derived()
              .coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
                        m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
     }
 
-    inline const CoeffReturnType coeff(int index) const
+    inline const CoeffReturnType coeff(Index index) const
     {
       return m_xpr
              .coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
@@ -182,21 +182,21 @@
     }
 
     template<int LoadMode>
-    inline PacketScalar packet(int row, int col) const
+    inline PacketScalar packet(Index row, Index col) const
     {
       return m_xpr.template packet<Unaligned>
               (row + m_startRow.value(), col + m_startCol.value());
     }
 
     template<int LoadMode>
-    inline void writePacket(int row, int col, const PacketScalar& x)
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
     {
       m_xpr.const_cast_derived().template writePacket<Unaligned>
               (row + m_startRow.value(), col + m_startCol.value(), x);
     }
 
     template<int LoadMode>
-    inline PacketScalar packet(int index) const
+    inline PacketScalar packet(Index index) const
     {
       return m_xpr.template packet<Unaligned>
               (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
@@ -204,7 +204,7 @@
     }
 
     template<int LoadMode>
-    inline void writePacket(int index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& x)
     {
       m_xpr.const_cast_derived().template writePacket<Unaligned>
          (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
@@ -214,17 +214,17 @@
     #ifdef EIGEN_PARSED_BY_DOXYGEN
     /** \sa MapBase::data() */
     inline const Scalar* data() const;
-    inline int innerStride() const;
-    inline int outerStride() const;
+    inline Index innerStride() const;
+    inline Index outerStride() const;
     #endif
 
   protected:
 
     const typename XprType::Nested m_xpr;
-    const ei_int_if_dynamic<XprType::RowsAtCompileTime == 1 ? 0 : Dynamic> m_startRow;
-    const ei_int_if_dynamic<XprType::ColsAtCompileTime == 1 ? 0 : Dynamic> m_startCol;
-    const ei_int_if_dynamic<RowsAtCompileTime> m_blockRows;
-    const ei_int_if_dynamic<ColsAtCompileTime> m_blockCols;
+    const ei_variable_if_dynamic<Index, XprType::RowsAtCompileTime == 1 ? 0 : Dynamic> m_startRow;
+    const ei_variable_if_dynamic<Index, XprType::ColsAtCompileTime == 1 ? 0 : Dynamic> m_startCol;
+    const ei_variable_if_dynamic<Index, RowsAtCompileTime> m_blockRows;
+    const ei_variable_if_dynamic<Index, ColsAtCompileTime> m_blockCols;
 };
 
 /** \internal */
@@ -241,7 +241,7 @@
 
     /** Column or Row constructor
       */
-    inline Block(const XprType& xpr, int i)
+    inline Block(const XprType& xpr, Index i)
       : Base(&xpr.const_cast_derived().coeffRef(
               (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0,
               (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0),
@@ -257,7 +257,7 @@
 
     /** Fixed-size constructor
       */
-    inline Block(const XprType& xpr, int startRow, int startCol)
+    inline Block(const XprType& xpr, Index startRow, Index startCol)
       : Base(&xpr.const_cast_derived().coeffRef(startRow,startCol)), m_xpr(xpr)
     {
       ei_assert(startRow >= 0 && BlockRows >= 1 && startRow + BlockRows <= xpr.rows()
@@ -268,8 +268,8 @@
     /** Dynamic-size constructor
       */
     inline Block(const XprType& xpr,
-          int startRow, int startCol,
-          int blockRows, int blockCols)
+          Index startRow, Index startCol,
+          Index blockRows, Index blockCols)
       : Base(&xpr.const_cast_derived().coeffRef(startRow,startCol), blockRows, blockCols),
         m_xpr(xpr)
     {
@@ -281,7 +281,7 @@
     }
 
     /** \sa MapBase::innerStride() */
-    inline int innerStride() const
+    inline Index innerStride() const
     {
       return ei_traits<Block>::HasSameStorageOrderAsXprType
              ? m_xpr.innerStride()
@@ -289,7 +289,7 @@
     }
 
     /** \sa MapBase::outerStride() */
-    inline int outerStride() const
+    inline Index outerStride() const
     {
       return m_outerStride;
     }
@@ -302,7 +302,7 @@
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** \internal used by allowAligned() */
-    inline Block(const XprType& xpr, const Scalar* data, int blockRows, int blockCols)
+    inline Block(const XprType& xpr, const Scalar* data, Index blockRows, Index blockCols)
       : Base(data, blockRows, blockCols), m_xpr(xpr)
     {
       init();
@@ -335,19 +335,19 @@
   * when it is applied to a fixed-size matrix, it inherits a fixed maximal size,
   * which means that evaluating it does not cause a dynamic memory allocation.
   *
-  * \sa class Block, block(int,int)
+  * \sa class Block, block(Index,Index)
   */
 template<typename Derived>
 inline Block<Derived> DenseBase<Derived>
-  ::block(int startRow, int startCol, int blockRows, int blockCols)
+  ::block(Index startRow, Index startCol, Index blockRows, Index blockCols)
 {
   return Block<Derived>(derived(), startRow, startCol, blockRows, blockCols);
 }
 
-/** This is the const version of block(int,int,int,int). */
+/** This is the const version of block(Index,Index,Index,Index). */
 template<typename Derived>
 inline const Block<Derived> DenseBase<Derived>
-  ::block(int startRow, int startCol, int blockRows, int blockCols) const
+  ::block(Index startRow, Index startCol, Index blockRows, Index blockCols) const
 {
   return Block<Derived>(derived(), startRow, startCol, blockRows, blockCols);
 }
@@ -363,19 +363,19 @@
   * Example: \include MatrixBase_topRightCorner_int_int.cpp
   * Output: \verbinclude MatrixBase_topRightCorner_int_int.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 inline Block<Derived> DenseBase<Derived>
-  ::topRightCorner(int cRows, int cCols)
+  ::topRightCorner(Index cRows, Index cCols)
 {
   return Block<Derived>(derived(), 0, cols() - cCols, cRows, cCols);
 }
 
-/** This is the const version of topRightCorner(int, int).*/
+/** This is the const version of topRightCorner(Index, Index).*/
 template<typename Derived>
 inline const Block<Derived>
-DenseBase<Derived>::topRightCorner(int cRows, int cCols) const
+DenseBase<Derived>::topRightCorner(Index cRows, Index cCols) const
 {
   return Block<Derived>(derived(), 0, cols() - cCols, cRows, cCols);
 }
@@ -387,7 +387,7 @@
   * Example: \include MatrixBase_template_int_int_topRightCorner.cpp
   * Output: \verbinclude MatrixBase_template_int_int_topRightCorner.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 template<int CRows, int CCols>
@@ -417,19 +417,19 @@
   * Example: \include MatrixBase_topLeftCorner_int_int.cpp
   * Output: \verbinclude MatrixBase_topLeftCorner_int_int.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 inline Block<Derived> DenseBase<Derived>
-  ::topLeftCorner(int cRows, int cCols)
+  ::topLeftCorner(Index cRows, Index cCols)
 {
   return Block<Derived>(derived(), 0, 0, cRows, cCols);
 }
 
-/** This is the const version of topLeftCorner(int, int).*/
+/** This is the const version of topLeftCorner(Index, Index).*/
 template<typename Derived>
 inline const Block<Derived>
-DenseBase<Derived>::topLeftCorner(int cRows, int cCols) const
+DenseBase<Derived>::topLeftCorner(Index cRows, Index cCols) const
 {
   return Block<Derived>(derived(), 0, 0, cRows, cCols);
 }
@@ -441,7 +441,7 @@
   * Example: \include MatrixBase_template_int_int_topLeftCorner.cpp
   * Output: \verbinclude MatrixBase_template_int_int_topLeftCorner.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 template<int CRows, int CCols>
@@ -473,19 +473,19 @@
   * Example: \include MatrixBase_bottomRightCorner_int_int.cpp
   * Output: \verbinclude MatrixBase_bottomRightCorner_int_int.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 inline Block<Derived> DenseBase<Derived>
-  ::bottomRightCorner(int cRows, int cCols)
+  ::bottomRightCorner(Index cRows, Index cCols)
 {
   return Block<Derived>(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
 }
 
-/** This is the const version of bottomRightCorner(int, int).*/
+/** This is the const version of bottomRightCorner(Index, Index).*/
 template<typename Derived>
 inline const Block<Derived>
-DenseBase<Derived>::bottomRightCorner(int cRows, int cCols) const
+DenseBase<Derived>::bottomRightCorner(Index cRows, Index cCols) const
 {
   return Block<Derived>(derived(), rows() - cRows, cols() - cCols, cRows, cCols);
 }
@@ -497,7 +497,7 @@
   * Example: \include MatrixBase_template_int_int_bottomRightCorner.cpp
   * Output: \verbinclude MatrixBase_template_int_int_bottomRightCorner.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 template<int CRows, int CCols>
@@ -527,19 +527,19 @@
   * Example: \include MatrixBase_bottomLeftCorner_int_int.cpp
   * Output: \verbinclude MatrixBase_bottomLeftCorner_int_int.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 inline Block<Derived> DenseBase<Derived>
-  ::bottomLeftCorner(int cRows, int cCols)
+  ::bottomLeftCorner(Index cRows, Index cCols)
 {
   return Block<Derived>(derived(), rows() - cRows, 0, cRows, cCols);
 }
 
-/** This is the const version of bottomLeftCorner(int, int).*/
+/** This is the const version of bottomLeftCorner(Index, Index).*/
 template<typename Derived>
 inline const Block<Derived>
-DenseBase<Derived>::bottomLeftCorner(int cRows, int cCols) const
+DenseBase<Derived>::bottomLeftCorner(Index cRows, Index cCols) const
 {
   return Block<Derived>(derived(), rows() - cRows, 0, cRows, cCols);
 }
@@ -551,7 +551,7 @@
   * Example: \include MatrixBase_template_int_int_bottomLeftCorner.cpp
   * Output: \verbinclude MatrixBase_template_int_int_bottomLeftCorner.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 template<int CRows, int CCols>
@@ -579,19 +579,19 @@
   * Example: \include MatrixBase_topRows_int.cpp
   * Output: \verbinclude MatrixBase_topRows_int.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::RowsBlockXpr DenseBase<Derived>
-  ::topRows(int n)
+  ::topRows(Index n)
 {
   return RowsBlockXpr(derived(), 0, 0, n, cols());
 }
 
-/** This is the const version of topRows(int).*/
+/** This is the const version of topRows(Index).*/
 template<typename Derived>
 inline const typename DenseBase<Derived>::RowsBlockXpr
-DenseBase<Derived>::topRows(int n) const
+DenseBase<Derived>::topRows(Index n) const
 {
   return RowsBlockXpr(derived(), 0, 0, n, cols());
 }
@@ -603,7 +603,7 @@
   * Example: \include MatrixBase_template_int_topRows.cpp
   * Output: \verbinclude MatrixBase_template_int_topRows.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 template<int N>
@@ -633,19 +633,19 @@
   * Example: \include MatrixBase_bottomRows_int.cpp
   * Output: \verbinclude MatrixBase_bottomRows_int.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::RowsBlockXpr DenseBase<Derived>
-  ::bottomRows(int n)
+  ::bottomRows(Index n)
 {
   return RowsBlockXpr(derived(), rows() - n, 0, n, cols());
 }
 
-/** This is the const version of bottomRows(int).*/
+/** This is the const version of bottomRows(Index).*/
 template<typename Derived>
 inline const typename DenseBase<Derived>::RowsBlockXpr
-DenseBase<Derived>::bottomRows(int n) const
+DenseBase<Derived>::bottomRows(Index n) const
 {
   return RowsBlockXpr(derived(), rows() - n, 0, n, cols());
 }
@@ -657,7 +657,7 @@
   * Example: \include MatrixBase_template_int_bottomRows.cpp
   * Output: \verbinclude MatrixBase_template_int_bottomRows.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 template<int N>
@@ -687,19 +687,19 @@
   * Example: \include MatrixBase_leftCols_int.cpp
   * Output: \verbinclude MatrixBase_leftCols_int.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::ColsBlockXpr DenseBase<Derived>
-  ::leftCols(int n)
+  ::leftCols(Index n)
 {
   return ColsBlockXpr(derived(), 0, 0, rows(), n);
 }
 
-/** This is the const version of leftCols(int).*/
+/** This is the const version of leftCols(Index).*/
 template<typename Derived>
 inline const typename DenseBase<Derived>::ColsBlockXpr
-DenseBase<Derived>::leftCols(int n) const
+DenseBase<Derived>::leftCols(Index n) const
 {
   return ColsBlockXpr(derived(), 0, 0, rows(), n);
 }
@@ -711,7 +711,7 @@
   * Example: \include MatrixBase_template_int_leftCols.cpp
   * Output: \verbinclude MatrixBase_template_int_leftCols.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 template<int N>
@@ -741,19 +741,19 @@
   * Example: \include MatrixBase_rightCols_int.cpp
   * Output: \verbinclude MatrixBase_rightCols_int.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::ColsBlockXpr DenseBase<Derived>
-  ::rightCols(int n)
+  ::rightCols(Index n)
 {
   return ColsBlockXpr(derived(), 0, cols() - n, rows(), n);
 }
 
-/** This is the const version of rightCols(int).*/
+/** This is the const version of rightCols(Index).*/
 template<typename Derived>
 inline const typename DenseBase<Derived>::ColsBlockXpr
-DenseBase<Derived>::rightCols(int n) const
+DenseBase<Derived>::rightCols(Index n) const
 {
   return ColsBlockXpr(derived(), 0, cols() - n, rows(), n);
 }
@@ -765,7 +765,7 @@
   * Example: \include MatrixBase_template_int_rightCols.cpp
   * Output: \verbinclude MatrixBase_template_int_rightCols.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 template<int N>
@@ -802,21 +802,21 @@
   * \note since block is a templated member, the keyword template has to be used
   * if the matrix type is also a template parameter: \code m.template block<3,3>(1,1); \endcode
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 template<int BlockRows, int BlockCols>
 inline Block<Derived, BlockRows, BlockCols>
-DenseBase<Derived>::block(int startRow, int startCol)
+DenseBase<Derived>::block(Index startRow, Index startCol)
 {
   return Block<Derived, BlockRows, BlockCols>(derived(), startRow, startCol);
 }
 
-/** This is the const version of block<>(int, int). */
+/** This is the const version of block<>(Index, Index). */
 template<typename Derived>
 template<int BlockRows, int BlockCols>
 inline const Block<Derived, BlockRows, BlockCols>
-DenseBase<Derived>::block(int startRow, int startCol) const
+DenseBase<Derived>::block(Index startRow, Index startCol) const
 {
   return Block<Derived, BlockRows, BlockCols>(derived(), startRow, startCol);
 }
@@ -829,7 +829,7 @@
   * \sa row(), class Block */
 template<typename Derived>
 inline typename DenseBase<Derived>::ColXpr
-DenseBase<Derived>::col(int i)
+DenseBase<Derived>::col(Index i)
 {
   return ColXpr(derived(), i);
 }
@@ -837,7 +837,7 @@
 /** This is the const version of col(). */
 template<typename Derived>
 inline const typename DenseBase<Derived>::ColXpr
-DenseBase<Derived>::col(int i) const
+DenseBase<Derived>::col(Index i) const
 {
   return ColXpr(derived(), i);
 }
@@ -850,7 +850,7 @@
   * \sa col(), class Block */
 template<typename Derived>
 inline typename DenseBase<Derived>::RowXpr
-DenseBase<Derived>::row(int i)
+DenseBase<Derived>::row(Index i)
 {
   return RowXpr(derived(), i);
 }
@@ -858,7 +858,7 @@
 /** This is the const version of row(). */
 template<typename Derived>
 inline const typename DenseBase<Derived>::RowXpr
-DenseBase<Derived>::row(int i) const
+DenseBase<Derived>::row(Index i) const
 {
   return RowXpr(derived(), i);
 }
diff --git a/Eigen/src/Core/CommaInitializer.h b/Eigen/src/Core/CommaInitializer.h
index adfca4f..311c903 100644
--- a/Eigen/src/Core/CommaInitializer.h
+++ b/Eigen/src/Core/CommaInitializer.h
@@ -39,7 +39,9 @@
 template<typename XprType>
 struct CommaInitializer
 {
-  typedef typename ei_traits<XprType>::Scalar Scalar;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::Index Index;
+
   inline CommaInitializer(XprType& xpr, const Scalar& s)
     : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1)
   {
@@ -113,9 +115,9 @@
   inline XprType& finished() { return m_xpr; }
 
   XprType& m_xpr;   // target expression
-  int m_row;              // current row id
-  int m_col;              // current col id
-  int m_currentBlockRows; // current block height
+  Index m_row;              // current row id
+  Index m_col;              // current col id
+  Index m_currentBlockRows; // current block height
 };
 
 /** \anchor MatrixBaseCommaInitRef
diff --git a/Eigen/src/Core/CwiseBinaryOp.h b/Eigen/src/Core/CwiseBinaryOp.h
index e0617e3..5307775 100644
--- a/Eigen/src/Core/CwiseBinaryOp.h
+++ b/Eigen/src/Core/CwiseBinaryOp.h
@@ -123,14 +123,14 @@
       ei_assert(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols());
     }
 
-    EIGEN_STRONG_INLINE int rows() const {
+    EIGEN_STRONG_INLINE Index rows() const {
       // return the fixed size type if available to enable compile time optimizations
       if (ei_traits<typename ei_cleantype<LhsNested>::type>::RowsAtCompileTime==Dynamic)      
         return m_rhs.rows();
       else
         return m_lhs.rows();
     }
-    EIGEN_STRONG_INLINE int cols() const {
+    EIGEN_STRONG_INLINE Index cols() const {
       // return the fixed size type if available to enable compile time optimizations
       if (ei_traits<typename ei_cleantype<LhsNested>::type>::ColsAtCompileTime==Dynamic)      
         return m_rhs.cols();
@@ -161,27 +161,27 @@
     typedef typename ei_dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE( Derived )
 
-    EIGEN_STRONG_INLINE const Scalar coeff(int row, int col) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
     {
       return derived().functor()(derived().lhs().coeff(row, col),
                                  derived().rhs().coeff(row, col));
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int row, int col) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
     {
       return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(row, col),
                                           derived().rhs().template packet<LoadMode>(row, col));
     }
 
-    EIGEN_STRONG_INLINE const Scalar coeff(int index) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
     {
       return derived().functor()(derived().lhs().coeff(index),
                                  derived().rhs().coeff(index));
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int index) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
     {
       return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(index),
                                           derived().rhs().template packet<LoadMode>(index));
diff --git a/Eigen/src/Core/CwiseNullaryOp.h b/Eigen/src/Core/CwiseNullaryOp.h
index bb44703..af16432 100644
--- a/Eigen/src/Core/CwiseNullaryOp.h
+++ b/Eigen/src/Core/CwiseNullaryOp.h
@@ -63,7 +63,7 @@
     typedef typename ei_dense_xpr_base<CwiseNullaryOp>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp)
 
-    CwiseNullaryOp(int rows, int cols, const NullaryOp& func = NullaryOp())
+    CwiseNullaryOp(Index rows, Index cols, const NullaryOp& func = NullaryOp())
       : m_rows(rows), m_cols(cols), m_functor(func)
     {
       ei_assert(rows >= 0
@@ -72,34 +72,34 @@
             && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
     }
 
-    EIGEN_STRONG_INLINE int rows() const { return m_rows.value(); }
-    EIGEN_STRONG_INLINE int cols() const { return m_cols.value(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_cols.value(); }
 
-    EIGEN_STRONG_INLINE const Scalar coeff(int rows, int cols) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index rows, Index cols) const
     {
       return m_functor(rows, cols);
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int row, int col) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
     {
       return m_functor.packetOp(row, col);
     }
 
-    EIGEN_STRONG_INLINE const Scalar coeff(int index) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
     {
       return m_functor(index);
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int index) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
     {
       return m_functor.packetOp(index);
     }
 
   protected:
-    const ei_int_if_dynamic<RowsAtCompileTime> m_rows;
-    const ei_int_if_dynamic<ColsAtCompileTime> m_cols;
+    const ei_variable_if_dynamic<Index, RowsAtCompileTime> m_rows;
+    const ei_variable_if_dynamic<Index, ColsAtCompileTime> m_cols;
     const NullaryOp m_functor;
 };
 
@@ -120,7 +120,7 @@
 template<typename Derived>
 template<typename CustomNullaryOp>
 EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
-DenseBase<Derived>::NullaryExpr(int rows, int cols, const CustomNullaryOp& func)
+DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func)
 {
   return CwiseNullaryOp<CustomNullaryOp, Derived>(rows, cols, func);
 }
@@ -143,7 +143,7 @@
 template<typename Derived>
 template<typename CustomNullaryOp>
 EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
-DenseBase<Derived>::NullaryExpr(int size, const CustomNullaryOp& func)
+DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   if(RowsAtCompileTime == 1) return CwiseNullaryOp<CustomNullaryOp, Derived>(1, size, func);
@@ -182,7 +182,7 @@
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Constant(int rows, int cols, const Scalar& value)
+DenseBase<Derived>::Constant(Index rows, Index cols, const Scalar& value)
 {
   return DenseBase<Derived>::NullaryExpr(rows, cols, ei_scalar_constant_op<Scalar>(value));
 }
@@ -204,7 +204,7 @@
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Constant(int size, const Scalar& value)
+DenseBase<Derived>::Constant(Index size, const Scalar& value)
 {
   return DenseBase<Derived>::NullaryExpr(size, ei_scalar_constant_op<Scalar>(value));
 }
@@ -239,11 +239,11 @@
   * Example: \include DenseBase_LinSpaced_seq.cpp
   * Output: \verbinclude DenseBase_LinSpaced_seq.out
   *
-  * \sa setLinSpaced(const Scalar&,const Scalar&,int), LinSpaced(Scalar,Scalar,int), CwiseNullaryOp
+  * \sa setLinSpaced(const Scalar&,const Scalar&,Index), LinSpaced(Scalar,Scalar,Index), CwiseNullaryOp
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::SequentialLinSpacedReturnType
-DenseBase<Derived>::LinSpaced(Sequential_t, const Scalar& low, const Scalar& high, int size)
+DenseBase<Derived>::LinSpaced(Sequential_t, const Scalar& low, const Scalar& high, Index size)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return DenseBase<Derived>::NullaryExpr(size, ei_linspaced_op<Scalar,false>(low,high,size));
@@ -259,11 +259,11 @@
   * Example: \include DenseBase_LinSpaced.cpp
   * Output: \verbinclude DenseBase_LinSpaced.out
   *
-  * \sa setLinSpaced(const Scalar&,const Scalar&,int), LinSpaced(Sequential_t,const Scalar&,const Scalar&,int), CwiseNullaryOp
+  * \sa setLinSpaced(const Scalar&,const Scalar&,Index), LinSpaced(Sequential_t,const Scalar&,const Scalar&,Index), CwiseNullaryOp
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
-DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high, int size)
+DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high, Index size)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return DenseBase<Derived>::NullaryExpr(size, ei_linspaced_op<Scalar,true>(low,high,size));
@@ -274,8 +274,8 @@
 bool DenseBase<Derived>::isApproxToConstant
 (const Scalar& value, RealScalar prec) const
 {
-  for(int j = 0; j < cols(); ++j)
-    for(int i = 0; i < rows(); ++i)
+  for(Index j = 0; j < cols(); ++j)
+    for(Index i = 0; i < rows(); ++i)
       if(!ei_isApprox(this->coeff(i, j), value, prec))
         return false;
   return true;
@@ -303,7 +303,7 @@
 
 /** Sets all coefficients in this expression to \a value.
   *
-  * \sa fill(), setConstant(int,const Scalar&), setConstant(int,int,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes()
+  * \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& value)
@@ -318,11 +318,11 @@
   * Example: \include Matrix_setConstant_int.cpp
   * Output: \verbinclude Matrix_setConstant_int.out
   *
-  * \sa MatrixBase::setConstant(const Scalar&), setConstant(int,int,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
+  * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-DenseStorageBase<Derived>::setConstant(int size, const Scalar& value)
+DenseStorageBase<Derived>::setConstant(Index size, const Scalar& value)
 {
   resize(size);
   return setConstant(value);
@@ -336,11 +336,11 @@
   * Example: \include Matrix_setConstant_int_int.cpp
   * Output: \verbinclude Matrix_setConstant_int_int.out
   *
-  * \sa MatrixBase::setConstant(const Scalar&), setConstant(int,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
+  * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-DenseStorageBase<Derived>::setConstant(int rows, int cols, const Scalar& value)
+DenseStorageBase<Derived>::setConstant(Index rows, Index cols, const Scalar& value)
 {
   resize(rows, cols);
   return setConstant(value);
@@ -359,7 +359,7 @@
   * \sa CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low, const Scalar& high, int size)
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low, const Scalar& high, Index size)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return derived() = Derived::NullaryExpr(size, ei_linspaced_op<Scalar,false>(low,high,size));
@@ -379,11 +379,11 @@
   * Example: \include MatrixBase_zero_int_int.cpp
   * Output: \verbinclude MatrixBase_zero_int_int.out
   *
-  * \sa Zero(), Zero(int)
+  * \sa Zero(), Zero(Index)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Zero(int rows, int cols)
+DenseBase<Derived>::Zero(Index rows, Index cols)
 {
   return Constant(rows, cols, Scalar(0));
 }
@@ -402,11 +402,11 @@
   * Example: \include MatrixBase_zero_int.cpp
   * Output: \verbinclude MatrixBase_zero_int.out
   *
-  * \sa Zero(), Zero(int,int)
+  * \sa Zero(), Zero(Index,Index)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Zero(int size)
+DenseBase<Derived>::Zero(Index size)
 {
   return Constant(size, Scalar(0));
 }
@@ -419,7 +419,7 @@
   * Example: \include MatrixBase_zero.cpp
   * Output: \verbinclude MatrixBase_zero.out
   *
-  * \sa Zero(int), Zero(int,int)
+  * \sa Zero(Index), Zero(Index,Index)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
@@ -439,8 +439,8 @@
 template<typename Derived>
 bool DenseBase<Derived>::isZero(RealScalar prec) const
 {
-  for(int j = 0; j < cols(); ++j)
-    for(int i = 0; i < rows(); ++i)
+  for(Index j = 0; j < cols(); ++j)
+    for(Index i = 0; i < rows(); ++i)
       if(!ei_isMuchSmallerThan(this->coeff(i, j), static_cast<Scalar>(1), prec))
         return false;
   return true;
@@ -466,11 +466,11 @@
   * Example: \include Matrix_setZero_int.cpp
   * Output: \verbinclude Matrix_setZero_int.out
   *
-  * \sa DenseBase::setZero(), setZero(int,int), class CwiseNullaryOp, DenseBase::Zero()
+  * \sa DenseBase::setZero(), setZero(Index,Index), class CwiseNullaryOp, DenseBase::Zero()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-DenseStorageBase<Derived>::setZero(int size)
+DenseStorageBase<Derived>::setZero(Index size)
 {
   resize(size);
   return setConstant(Scalar(0));
@@ -484,11 +484,11 @@
   * Example: \include Matrix_setZero_int_int.cpp
   * Output: \verbinclude Matrix_setZero_int_int.out
   *
-  * \sa DenseBase::setZero(), setZero(int), class CwiseNullaryOp, DenseBase::Zero()
+  * \sa DenseBase::setZero(), setZero(Index), class CwiseNullaryOp, DenseBase::Zero()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-DenseStorageBase<Derived>::setZero(int rows, int cols)
+DenseStorageBase<Derived>::setZero(Index rows, Index cols)
 {
   resize(rows, cols);
   return setConstant(Scalar(0));
@@ -508,11 +508,11 @@
   * Example: \include MatrixBase_ones_int_int.cpp
   * Output: \verbinclude MatrixBase_ones_int_int.out
   *
-  * \sa Ones(), Ones(int), isOnes(), class Ones
+  * \sa Ones(), Ones(Index), isOnes(), class Ones
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Ones(int rows, int cols)
+DenseBase<Derived>::Ones(Index rows, Index cols)
 {
   return Constant(rows, cols, Scalar(1));
 }
@@ -531,11 +531,11 @@
   * Example: \include MatrixBase_ones_int.cpp
   * Output: \verbinclude MatrixBase_ones_int.out
   *
-  * \sa Ones(), Ones(int,int), isOnes(), class Ones
+  * \sa Ones(), Ones(Index,Index), isOnes(), class Ones
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Ones(int size)
+DenseBase<Derived>::Ones(Index size)
 {
   return Constant(size, Scalar(1));
 }
@@ -548,7 +548,7 @@
   * Example: \include MatrixBase_ones.cpp
   * Output: \verbinclude MatrixBase_ones.out
   *
-  * \sa Ones(int), Ones(int,int), isOnes(), class Ones
+  * \sa Ones(Index), Ones(Index,Index), isOnes(), class Ones
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
@@ -592,11 +592,11 @@
   * Example: \include Matrix_setOnes_int.cpp
   * Output: \verbinclude Matrix_setOnes_int.out
   *
-  * \sa MatrixBase::setOnes(), setOnes(int,int), class CwiseNullaryOp, MatrixBase::Ones()
+  * \sa MatrixBase::setOnes(), setOnes(Index,Index), class CwiseNullaryOp, MatrixBase::Ones()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-DenseStorageBase<Derived>::setOnes(int size)
+DenseStorageBase<Derived>::setOnes(Index size)
 {
   resize(size);
   return setConstant(Scalar(1));
@@ -610,11 +610,11 @@
   * Example: \include Matrix_setOnes_int_int.cpp
   * Output: \verbinclude Matrix_setOnes_int_int.out
   *
-  * \sa MatrixBase::setOnes(), setOnes(int), class CwiseNullaryOp, MatrixBase::Ones()
+  * \sa MatrixBase::setOnes(), setOnes(Index), class CwiseNullaryOp, MatrixBase::Ones()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-DenseStorageBase<Derived>::setOnes(int rows, int cols)
+DenseStorageBase<Derived>::setOnes(Index rows, Index cols)
 {
   resize(rows, cols);
   return setConstant(Scalar(1));
@@ -638,7 +638,7 @@
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
-MatrixBase<Derived>::Identity(int rows, int cols)
+MatrixBase<Derived>::Identity(Index rows, Index cols)
 {
   return DenseBase<Derived>::NullaryExpr(rows, cols, ei_scalar_identity_op<Scalar>());
 }
@@ -651,7 +651,7 @@
   * Example: \include MatrixBase_identity.cpp
   * Output: \verbinclude MatrixBase_identity.out
   *
-  * \sa Identity(int,int), setIdentity(), isIdentity()
+  * \sa Identity(Index,Index), setIdentity(), isIdentity()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
@@ -668,15 +668,15 @@
   * Example: \include MatrixBase_isIdentity.cpp
   * Output: \verbinclude MatrixBase_isIdentity.out
   *
-  * \sa class CwiseNullaryOp, Identity(), Identity(int,int), setIdentity()
+  * \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), setIdentity()
   */
 template<typename Derived>
 bool MatrixBase<Derived>::isIdentity
 (RealScalar prec) const
 {
-  for(int j = 0; j < cols(); ++j)
+  for(Index j = 0; j < cols(); ++j)
   {
-    for(int i = 0; i < rows(); ++i)
+    for(Index i = 0; i < rows(); ++i)
     {
       if(i == j)
       {
@@ -705,11 +705,12 @@
 template<typename Derived>
 struct ei_setIdentity_impl<Derived, true>
 {
+  typedef typename Derived::Index Index;
   static EIGEN_STRONG_INLINE Derived& run(Derived& m)
   {
     m.setZero();
-    const int size = std::min(m.rows(), m.cols());
-    for(int i = 0; i < size; ++i) m.coeffRef(i,i) = typename Derived::Scalar(1);
+    const Index size = std::min(m.rows(), m.cols());
+    for(Index i = 0; i < size; ++i) m.coeffRef(i,i) = typename Derived::Scalar(1);
     return m;
   }
 };
@@ -719,7 +720,7 @@
   * Example: \include MatrixBase_setIdentity.cpp
   * Output: \verbinclude MatrixBase_setIdentity.out
   *
-  * \sa class CwiseNullaryOp, Identity(), Identity(int,int), isIdentity()
+  * \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), isIdentity()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
@@ -738,7 +739,7 @@
   * \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(int rows, int cols)
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index cols)
 {
   derived().resize(rows, cols);
   return setIdentity();
@@ -748,10 +749,10 @@
   *
   * \only_for_vectors
   *
-  * \sa MatrixBase::Unit(int), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(int size, int i)
+EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index size, Index i)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return BasisReturnType(SquareMatrixType::Identity(size,size), i);
@@ -763,10 +764,10 @@
   *
   * This variant is for fixed-size vector only.
   *
-  * \sa MatrixBase::Unit(int,int), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index,Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(int i)
+EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index i)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return BasisReturnType(SquareMatrixType::Identity(),i);
@@ -776,7 +777,7 @@
   *
   * \only_for_vectors
   *
-  * \sa MatrixBase::Unit(int,int), MatrixBase::Unit(int), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitX()
@@ -786,7 +787,7 @@
   *
   * \only_for_vectors
   *
-  * \sa MatrixBase::Unit(int,int), MatrixBase::Unit(int), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitY()
@@ -796,7 +797,7 @@
   *
   * \only_for_vectors
   *
-  * \sa MatrixBase::Unit(int,int), MatrixBase::Unit(int), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitZ()
@@ -806,7 +807,7 @@
   *
   * \only_for_vectors
   *
-  * \sa MatrixBase::Unit(int,int), MatrixBase::Unit(int), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitW()
diff --git a/Eigen/src/Core/CwiseUnaryOp.h b/Eigen/src/Core/CwiseUnaryOp.h
index 8f95b69..da398d1 100644
--- a/Eigen/src/Core/CwiseUnaryOp.h
+++ b/Eigen/src/Core/CwiseUnaryOp.h
@@ -76,8 +76,8 @@
     inline CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
       : m_xpr(xpr), m_functor(func) {}
 
-    EIGEN_STRONG_INLINE int rows() const { return m_xpr.rows(); }
-    EIGEN_STRONG_INLINE int cols() const { return m_xpr.cols(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_xpr.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_xpr.cols(); }
 
     /** \returns the functor representing the unary operation */
     const UnaryOp& functor() const { return m_functor; }
@@ -100,32 +100,31 @@
 template<typename UnaryOp, typename XprType>
 class CwiseUnaryOpImpl<UnaryOp,XprType,Dense>
   : public ei_dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type
- {
-    typedef CwiseUnaryOp<UnaryOp, XprType> Derived;
-
+{
   public:
 
+    typedef CwiseUnaryOp<UnaryOp, XprType> Derived;
     typedef typename ei_dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
 
-    EIGEN_STRONG_INLINE const Scalar coeff(int row, int col) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
     {
       return derived().functor()(derived().nestedExpression().coeff(row, col));
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int row, int col) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
     {
       return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(row, col));
     }
 
-    EIGEN_STRONG_INLINE const Scalar coeff(int index) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
     {
       return derived().functor()(derived().nestedExpression().coeff(index));
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int index) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
     {
       return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(index));
     }
diff --git a/Eigen/src/Core/CwiseUnaryView.h b/Eigen/src/Core/CwiseUnaryView.h
index 9cdd034..11a23c6 100644
--- a/Eigen/src/Core/CwiseUnaryView.h
+++ b/Eigen/src/Core/CwiseUnaryView.h
@@ -74,8 +74,8 @@
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView)
 
-    EIGEN_STRONG_INLINE int rows() const { return m_matrix.rows(); }
-    EIGEN_STRONG_INLINE int cols() const { return m_matrix.cols(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_matrix.cols(); }
 
     /** \returns the functor representing unary operation */
     const ViewOp& functor() const { return m_functor; }
@@ -98,40 +98,39 @@
 class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
   : public ei_dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type
 {
-    typedef CwiseUnaryView<ViewOp, MatrixType> Derived;
-
   public:
 
+    typedef CwiseUnaryView<ViewOp, MatrixType> Derived;
     typedef typename ei_dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type Base;
 
-    inline int innerStride() const
+    EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
+
+    inline Index innerStride() const
     {
       return derived().nestedExpression().innerStride() * sizeof(typename ei_traits<MatrixType>::Scalar) / sizeof(Scalar);
     }
 
-    inline int outerStride() const
+    inline Index outerStride() const
     {
       return derived().nestedExpression().outerStride();
     }
 
-    EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
-
-    EIGEN_STRONG_INLINE CoeffReturnType coeff(int row, int col) const
+    EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
     {
       return derived().functor()(derived().nestedExpression().coeff(row, col));
     }
 
-    EIGEN_STRONG_INLINE CoeffReturnType coeff(int index) const
+    EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
     {
       return derived().functor()(derived().nestedExpression().coeff(index));
     }
 
-    EIGEN_STRONG_INLINE Scalar& coeffRef(int row, int col)
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
     {
       return derived().functor()(const_cast_derived().nestedExpression().coeffRef(row, col));
     }
 
-    EIGEN_STRONG_INLINE Scalar& coeffRef(int index)
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
     {
       return derived().functor()(const_cast_derived().nestedExpression().coeffRef(index));
     }
diff --git a/Eigen/src/Core/DenseBase.h b/Eigen/src/Core/DenseBase.h
index e2429be..c4b4057 100644
--- a/Eigen/src/Core/DenseBase.h
+++ b/Eigen/src/Core/DenseBase.h
@@ -50,8 +50,12 @@
 
     class InnerIterator;
 
+    typedef typename ei_traits<Derived>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
     typedef typename ei_traits<Derived>::Scalar Scalar;
     typedef typename ei_packet_traits<Scalar>::type PacketScalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
     typedef DenseCoeffsBase<Derived> Base;
     using Base::derived;
     using Base::const_cast_derived;
@@ -168,19 +172,9 @@
       OuterStrideAtCompileTime = ei_outer_stride_at_compile_time<Derived>::ret
     };
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** This is the "real scalar" type; if the \a Scalar type is already real numbers
-      * (e.g. int, float or double) then \a RealScalar is just the same as \a Scalar. If
-      * \a Scalar is \a std::complex<T> then RealScalar is \a T.
-      *
-      * \sa class NumTraits
-      */
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-#endif // not EIGEN_PARSED_BY_DOXYGEN
-
     /** \returns the number of nonzero coefficients which is in practice the number
       * of stored coefficients. */
-    inline int nonZeros() const { return size(); }
+    inline Index nonZeros() const { return size(); }
     /** \returns true if either the number of rows or the number of columns is equal to 1.
       * In other words, this function returns
       * \code rows()==1 || cols()==1 \endcode
@@ -191,7 +185,7 @@
       * \note For a vector, this returns just 1. For a matrix (non-vector), this is the major dimension
       * with respect to the storage order, i.e., the number of columns for a column-major matrix,
       * and the number of rows for a row-major matrix. */
-    int outerSize() const
+    Index outerSize() const
     {
       return IsVectorAtCompileTime ? 1
            : int(IsRowMajor) ? this->rows() : this->cols();
@@ -202,7 +196,7 @@
       * \note For a vector, this is just the size. For a matrix (non-vector), this is the minor dimension
       * with respect to the storage order, i.e., the number of rows for a column-major matrix,
       * and the number of columns for a row-major matrix. */
-    int innerSize() const
+    Index innerSize() const
     {
       return IsVectorAtCompileTime ? this->size()
            : int(IsRowMajor) ? this->cols() : this->rows();
@@ -212,7 +206,7 @@
       * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
       * nothing else.
       */
-    void resize(int size)
+    void resize(Index size)
     {
       EIGEN_ONLY_USED_FOR_DEBUG(size);
       ei_assert(size == this->size()
@@ -222,7 +216,7 @@
       * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
       * nothing else.
       */
-    void resize(int rows, int cols)
+    void resize(Index rows, Index cols)
     {
       EIGEN_ONLY_USED_FOR_DEBUG(rows); 
       EIGEN_ONLY_USED_FOR_DEBUG(cols); 
@@ -301,41 +295,41 @@
   public:
 #endif
 
-    RowXpr row(int i);
-    const RowXpr row(int i) const;
+    RowXpr row(Index i);
+    const RowXpr row(Index i) const;
 
-    ColXpr col(int i);
-    const ColXpr col(int i) const;
+    ColXpr col(Index i);
+    const ColXpr col(Index i) const;
 
-    Block<Derived> block(int startRow, int startCol, int blockRows, int blockCols);
-    const Block<Derived> block(int startRow, int startCol, int blockRows, int blockCols) const;
+    Block<Derived> block(Index startRow, Index startCol, Index blockRows, Index blockCols);
+    const Block<Derived> block(Index startRow, Index startCol, Index blockRows, Index blockCols) const;
 
-    VectorBlock<Derived> segment(int start, int size);
-    const VectorBlock<Derived> segment(int start, int size) const;
+    VectorBlock<Derived> segment(Index start, Index size);
+    const VectorBlock<Derived> segment(Index start, Index size) const;
 
-    VectorBlock<Derived> head(int size);
-    const VectorBlock<Derived> head(int size) const;
+    VectorBlock<Derived> head(Index size);
+    const VectorBlock<Derived> head(Index size) const;
 
-    VectorBlock<Derived> tail(int size);
-    const VectorBlock<Derived> tail(int size) const;
+    VectorBlock<Derived> tail(Index size);
+    const VectorBlock<Derived> tail(Index size) const;
 
-    Block<Derived>       topLeftCorner(int cRows, int cCols);
-    const Block<Derived> topLeftCorner(int cRows, int cCols) const;
-    Block<Derived>       topRightCorner(int cRows, int cCols);
-    const Block<Derived> topRightCorner(int cRows, int cCols) const;
-    Block<Derived>       bottomLeftCorner(int cRows, int cCols);
-    const Block<Derived> bottomLeftCorner(int cRows, int cCols) const;
-    Block<Derived>       bottomRightCorner(int cRows, int cCols);
-    const Block<Derived> bottomRightCorner(int cRows, int cCols) const;
+    Block<Derived>       topLeftCorner(Index cRows, Index cCols);
+    const Block<Derived> topLeftCorner(Index cRows, Index cCols) const;
+    Block<Derived>       topRightCorner(Index cRows, Index cCols);
+    const Block<Derived> topRightCorner(Index cRows, Index cCols) const;
+    Block<Derived>       bottomLeftCorner(Index cRows, Index cCols);
+    const Block<Derived> bottomLeftCorner(Index cRows, Index cCols) const;
+    Block<Derived>       bottomRightCorner(Index cRows, Index cCols);
+    const Block<Derived> bottomRightCorner(Index cRows, Index cCols) const;
 
-    RowsBlockXpr       topRows(int n);
-    const RowsBlockXpr topRows(int n) const;
-    RowsBlockXpr       bottomRows(int n);
-    const RowsBlockXpr bottomRows(int n) const;
-    ColsBlockXpr       leftCols(int n);
-    const ColsBlockXpr leftCols(int n) const;
-    ColsBlockXpr       rightCols(int n);
-    const ColsBlockXpr rightCols(int n) const;
+    RowsBlockXpr       topRows(Index n);
+    const RowsBlockXpr topRows(Index n) const;
+    RowsBlockXpr       bottomRows(Index n);
+    const RowsBlockXpr bottomRows(Index n) const;
+    ColsBlockXpr       leftCols(Index n);
+    const ColsBlockXpr leftCols(Index n) const;
+    ColsBlockXpr       rightCols(Index n);
+    const ColsBlockXpr rightCols(Index n) const;
 
     template<int CRows, int CCols> Block<Derived, CRows, CCols>       topLeftCorner();
     template<int CRows, int CCols> const Block<Derived, CRows, CCols> topLeftCorner() const;
@@ -356,9 +350,9 @@
     template<int NCols> const typename NColsBlockXpr<NCols>::Type rightCols() const;
 
     template<int BlockRows, int BlockCols>
-    Block<Derived, BlockRows, BlockCols> block(int startRow, int startCol);
+    Block<Derived, BlockRows, BlockCols> block(Index startRow, Index startCol);
     template<int BlockRows, int BlockCols>
-    const Block<Derived, BlockRows, BlockCols> block(int startRow, int startCol) const;
+    const Block<Derived, BlockRows, BlockCols> block(Index startRow, Index startCol) const;
 
     template<int Size> VectorBlock<Derived,Size> head(void);
     template<int Size> const VectorBlock<Derived,Size> head() const;
@@ -366,8 +360,8 @@
     template<int Size> VectorBlock<Derived,Size> tail();
     template<int Size> const VectorBlock<Derived,Size> tail() const;
 
-    template<int Size> VectorBlock<Derived,Size> segment(int start);
-    template<int Size> const VectorBlock<Derived,Size> segment(int start) const;
+    template<int Size> VectorBlock<Derived,Size> segment(Index start);
+    template<int Size> const VectorBlock<Derived,Size> segment(Index start) const;
 
     Diagonal<Derived,0> diagonal();
     const Diagonal<Derived,0> diagonal() const;
@@ -375,8 +369,8 @@
     template<int Index> Diagonal<Derived,Index> diagonal();
     template<int Index> const Diagonal<Derived,Index> diagonal() const;
 
-    Diagonal<Derived, Dynamic> diagonal(int index);
-    const Diagonal<Derived, Dynamic> diagonal(int index) const;
+    Diagonal<Derived, Dynamic> diagonal(Index index);
+    const Diagonal<Derived, Dynamic> diagonal(Index index) const;
 
     template<unsigned int Mode> TriangularView<Derived, Mode> part();
     template<unsigned int Mode> const TriangularView<Derived, Mode> part() const;
@@ -388,37 +382,37 @@
     template<unsigned int UpLo> const SelfAdjointView<Derived, UpLo> selfadjointView() const;
 
     static const ConstantReturnType
-    Constant(int rows, int cols, const Scalar& value);
+    Constant(Index rows, Index cols, const Scalar& value);
     static const ConstantReturnType
-    Constant(int size, const Scalar& value);
+    Constant(Index size, const Scalar& value);
     static const ConstantReturnType
     Constant(const Scalar& value);
 
     static const SequentialLinSpacedReturnType
-    LinSpaced(Sequential_t, const Scalar& low, const Scalar& high, int size);
+    LinSpaced(Sequential_t, const Scalar& low, const Scalar& high, Index size);
     static const RandomAccessLinSpacedReturnType
-    LinSpaced(const Scalar& low, const Scalar& high, int size);
+    LinSpaced(const Scalar& low, const Scalar& high, Index size);
 
     template<typename CustomNullaryOp>
     static const CwiseNullaryOp<CustomNullaryOp, Derived>
-    NullaryExpr(int rows, int cols, const CustomNullaryOp& func);
+    NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func);
     template<typename CustomNullaryOp>
     static const CwiseNullaryOp<CustomNullaryOp, Derived>
-    NullaryExpr(int size, const CustomNullaryOp& func);
+    NullaryExpr(Index size, const CustomNullaryOp& func);
     template<typename CustomNullaryOp>
     static const CwiseNullaryOp<CustomNullaryOp, Derived>
     NullaryExpr(const CustomNullaryOp& func);
 
-    static const ConstantReturnType Zero(int rows, int cols);
-    static const ConstantReturnType Zero(int size);
+    static const ConstantReturnType Zero(Index rows, Index cols);
+    static const ConstantReturnType Zero(Index size);
     static const ConstantReturnType Zero();
-    static const ConstantReturnType Ones(int rows, int cols);
-    static const ConstantReturnType Ones(int size);
+    static const ConstantReturnType Ones(Index rows, Index cols);
+    static const ConstantReturnType Ones(Index size);
     static const ConstantReturnType Ones();
 
     void fill(const Scalar& value);
     Derived& setConstant(const Scalar& value);
-    Derived& setLinSpaced(const Scalar& low, const Scalar& high, int size);
+    Derived& setLinSpaced(const Scalar& low, const Scalar& high, Index size);
     Derived& setZero();
     Derived& setOnes();
     Derived& setRandom();
@@ -471,11 +465,11 @@
     typename ei_traits<Derived>::Scalar minCoeff() const;
     typename ei_traits<Derived>::Scalar maxCoeff() const;
 
-    typename ei_traits<Derived>::Scalar minCoeff(int* row, int* col) const;
-    typename ei_traits<Derived>::Scalar maxCoeff(int* row, int* col) const;
+    typename ei_traits<Derived>::Scalar minCoeff(Index* row, Index* col) const;
+    typename ei_traits<Derived>::Scalar maxCoeff(Index* row, Index* col) const;
 
-    typename ei_traits<Derived>::Scalar minCoeff(int* index) const;
-    typename ei_traits<Derived>::Scalar maxCoeff(int* index) const;
+    typename ei_traits<Derived>::Scalar minCoeff(Index* index) const;
+    typename ei_traits<Derived>::Scalar maxCoeff(Index* index) const;
 
     template<typename BinaryOp>
     typename ei_result_of<BinaryOp(typename ei_traits<Derived>::Scalar)>::type
@@ -490,15 +484,15 @@
 
     bool all(void) const;
     bool any(void) const;
-    int count() const;
+    Index count() const;
 
     const VectorwiseOp<Derived,Horizontal> rowwise() const;
     VectorwiseOp<Derived,Horizontal> rowwise();
     const VectorwiseOp<Derived,Vertical> colwise() const;
     VectorwiseOp<Derived,Vertical> colwise();
 
-    static const CwiseNullaryOp<ei_scalar_random_op<Scalar>,Derived> Random(int rows, int cols);
-    static const CwiseNullaryOp<ei_scalar_random_op<Scalar>,Derived> Random(int size);
+    static const CwiseNullaryOp<ei_scalar_random_op<Scalar>,Derived> Random(Index rows, Index cols);
+    static const CwiseNullaryOp<ei_scalar_random_op<Scalar>,Derived> Random(Index size);
     static const CwiseNullaryOp<ei_scalar_random_op<Scalar>,Derived> Random();
 
     template<typename ThenDerived,typename ElseDerived>
@@ -518,7 +512,7 @@
 
     template<int RowFactor, int ColFactor>
     const Replicate<Derived,RowFactor,ColFactor> replicate() const;
-    const Replicate<Derived,Dynamic,Dynamic> replicate(int rowFacor,int colFactor) const;
+    const Replicate<Derived,Dynamic,Dynamic> replicate(Index rowFacor,Index colFactor) const;
 
     Eigen::Reverse<Derived, BothDirections> reverse();
     const Eigen::Reverse<Derived, BothDirections> reverse() const;
@@ -526,8 +520,8 @@
 
 #ifdef EIGEN2_SUPPORT
 
-    Block<Derived> corner(CornerType type, int cRows, int cCols);
-    const Block<Derived> corner(CornerType type, int cRows, int cCols) const;
+    Block<Derived> corner(CornerType type, Index cRows, Index cCols);
+    const Block<Derived> corner(CornerType type, Index cRows, Index cCols) const;
     template<int CRows, int CCols>
     Block<Derived, CRows, CCols> corner(CornerType type);
     template<int CRows, int CCols>
diff --git a/Eigen/src/Core/DenseCoeffsBase.h b/Eigen/src/Core/DenseCoeffsBase.h
index ccf959b..7026bbe 100644
--- a/Eigen/src/Core/DenseCoeffsBase.h
+++ b/Eigen/src/Core/DenseCoeffsBase.h
@@ -29,7 +29,10 @@
 class DenseCoeffsBase : public EigenBase<Derived>
 {
   public:
+    typedef typename ei_traits<Derived>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
     typedef typename ei_traits<Derived>::Scalar Scalar;
+    typedef typename ei_packet_traits<Scalar>::type PacketScalar;
     typedef typename ei_meta_if<ei_has_direct_access<Derived>::ret, const Scalar&, Scalar>::ret CoeffReturnType;
 
     typedef EigenBase<Derived> Base;
@@ -38,7 +41,7 @@
     using Base::size;
     using Base::derived;
     
-    EIGEN_STRONG_INLINE int rowIndexByOuterInner(int outer, int inner) const
+    EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner) const
     {
       return int(Derived::RowsAtCompileTime) == 1 ? 0
           : int(Derived::ColsAtCompileTime) == 1 ? inner
@@ -46,7 +49,7 @@
           : inner;
     }
 
-    EIGEN_STRONG_INLINE int colIndexByOuterInner(int outer, int inner) const
+    EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner) const
     {
       return int(Derived::ColsAtCompileTime) == 1 ? 0
           : int(Derived::RowsAtCompileTime) == 1 ? inner
@@ -55,27 +58,27 @@
     }
 
     /** Short version: don't use this function, use
-      * \link operator()(int,int) const \endlink instead.
+      * \link operator()(Index,Index) const \endlink instead.
       *
       * Long version: this function is similar to
-      * \link operator()(int,int) const \endlink, but without the assertion.
+      * \link operator()(Index,Index) const \endlink, but without the assertion.
       * Use this for limiting the performance cost of debugging code when doing
       * repeated coefficient access. Only use this when it is guaranteed that the
       * parameters \a row and \a col are in range.
       *
       * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-      * function equivalent to \link operator()(int,int) const \endlink.
+      * function equivalent to \link operator()(Index,Index) const \endlink.
       *
-      * \sa operator()(int,int) const, coeffRef(int,int), coeff(int) const
+      * \sa operator()(Index,Index) const, coeffRef(Index,Index), coeff(Index) const
       */
-    EIGEN_STRONG_INLINE const CoeffReturnType coeff(int row, int col) const
+    EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index row, Index col) const
     {
       ei_internal_assert(row >= 0 && row < rows()
                         && col >= 0 && col < cols());
       return derived().coeff(row, col);
     }
 
-    EIGEN_STRONG_INLINE const CoeffReturnType coeffByOuterInner(int outer, int inner) const
+    EIGEN_STRONG_INLINE const CoeffReturnType coeffByOuterInner(Index outer, Index inner) const
     {
       return coeff(rowIndexByOuterInner(outer, inner),
                    colIndexByOuterInner(outer, inner));
@@ -83,9 +86,9 @@
 
     /** \returns the coefficient at given the given row and column.
       *
-      * \sa operator()(int,int), operator[](int)
+      * \sa operator()(Index,Index), operator[](Index)
       */
-    EIGEN_STRONG_INLINE const CoeffReturnType operator()(int row, int col) const
+    EIGEN_STRONG_INLINE const CoeffReturnType operator()(Index row, Index col) const
     {
       ei_assert(row >= 0 && row < rows()
           && col >= 0 && col < cols());
@@ -93,22 +96,22 @@
     }
 
     /** Short version: don't use this function, use
-      * \link operator[](int) const \endlink instead.
+      * \link operator[](Index) const \endlink instead.
       *
       * Long version: this function is similar to
-      * \link operator[](int) const \endlink, but without the assertion.
+      * \link operator[](Index) const \endlink, but without the assertion.
       * Use this for limiting the performance cost of debugging code when doing
       * repeated coefficient access. Only use this when it is guaranteed that the
       * parameter \a index is in range.
       *
       * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-      * function equivalent to \link operator[](int) const \endlink.
+      * function equivalent to \link operator[](Index) const \endlink.
       *
-      * \sa operator[](int) const, coeffRef(int), coeff(int,int) const
+      * \sa operator[](Index) const, coeffRef(Index), coeff(Index,Index) const
       */
 
     EIGEN_STRONG_INLINE const CoeffReturnType
-    coeff(int index) const
+    coeff(Index index) const
     {
       ei_internal_assert(index >= 0 && index < size());
       return derived().coeff(index);
@@ -119,12 +122,12 @@
       *
       * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
       *
-      * \sa operator[](int), operator()(int,int) const, x() const, y() const,
+      * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const,
       * z() const, w() const
       */
 
     EIGEN_STRONG_INLINE const CoeffReturnType
-    operator[](int index) const
+    operator[](Index index) const
     {
       EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
                           THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
@@ -134,16 +137,16 @@
 
     /** \returns the coefficient at given index.
       *
-      * This is synonymous to operator[](int) const.
+      * This is synonymous to operator[](Index) const.
       *
       * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
       *
-      * \sa operator[](int), operator()(int,int) const, x() const, y() const,
+      * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const,
       * z() const, w() const
       */
 
     EIGEN_STRONG_INLINE const CoeffReturnType
-    operator()(int index) const
+    operator()(Index index) const
     {
       ei_assert(index >= 0 && index < size());
       return derived().coeff(index);
@@ -180,17 +183,17 @@
 
     template<int LoadMode>
     EIGEN_STRONG_INLINE typename ei_packet_traits<Scalar>::type
-    packet(int row, int col) const
+    packet(Index row, Index col) const
     {
       ei_internal_assert(row >= 0 && row < rows()
-                        && col >= 0 && col < cols());
+                      && col >= 0 && col < cols());
       return derived().template packet<LoadMode>(row,col);
     }
 
 
     template<int LoadMode>
     EIGEN_STRONG_INLINE typename ei_packet_traits<Scalar>::type
-    packetByOuterInner(int outer, int inner) const
+    packetByOuterInner(Index outer, Index inner) const
     {
       return packet<LoadMode>(rowIndexByOuterInner(outer, inner),
                               colIndexByOuterInner(outer, inner));
@@ -207,7 +210,7 @@
 
     template<int LoadMode>
     EIGEN_STRONG_INLINE typename ei_packet_traits<Scalar>::type
-    packet(int index) const
+    packet(Index index) const
     {
       ei_internal_assert(index >= 0 && index < size());
       return derived().template packet<LoadMode>(index);
@@ -240,8 +243,14 @@
   public:
 
     typedef DenseCoeffsBase<Derived, false> Base;
+
+    typedef typename ei_traits<Derived>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
     typedef typename ei_traits<Derived>::Scalar Scalar;
-    using typename Base::CoeffReturnType;
+    typedef typename ei_packet_traits<Scalar>::type PacketScalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename Base::CoeffReturnType CoeffReturnType;
+
     using Base::coeff;
     using Base::rows;
     using Base::cols;
@@ -257,20 +266,20 @@
     using Base::w;
 
     /** Short version: don't use this function, use
-      * \link operator()(int,int) \endlink instead.
+      * \link operator()(Index,Index) \endlink instead.
       *
       * Long version: this function is similar to
-      * \link operator()(int,int) \endlink, but without the assertion.
+      * \link operator()(Index,Index) \endlink, but without the assertion.
       * Use this for limiting the performance cost of debugging code when doing
       * repeated coefficient access. Only use this when it is guaranteed that the
       * parameters \a row and \a col are in range.
       *
       * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-      * function equivalent to \link operator()(int,int) \endlink.
+      * function equivalent to \link operator()(Index,Index) \endlink.
       *
-      * \sa operator()(int,int), coeff(int, int) const, coeffRef(int)
+      * \sa operator()(Index,Index), coeff(Index, Index) const, coeffRef(Index)
       */
-    EIGEN_STRONG_INLINE Scalar& coeffRef(int row, int col)
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
     {
       ei_internal_assert(row >= 0 && row < rows()
                         && col >= 0 && col < cols());
@@ -278,7 +287,7 @@
     }
 
     EIGEN_STRONG_INLINE Scalar&
-    coeffRefByOuterInner(int outer, int inner)
+    coeffRefByOuterInner(Index outer, Index inner)
     {
       return coeffRef(rowIndexByOuterInner(outer, inner),
                       colIndexByOuterInner(outer, inner));
@@ -286,11 +295,11 @@
 
     /** \returns a reference to the coefficient at given the given row and column.
       *
-      * \sa operator[](int)
+      * \sa operator[](Index)
       */
 
     EIGEN_STRONG_INLINE Scalar&
-    operator()(int row, int col)
+    operator()(Index row, Index col)
     {
       ei_assert(row >= 0 && row < rows()
           && col >= 0 && col < cols());
@@ -299,22 +308,22 @@
 
 
     /** Short version: don't use this function, use
-      * \link operator[](int) \endlink instead.
+      * \link operator[](Index) \endlink instead.
       *
       * Long version: this function is similar to
-      * \link operator[](int) \endlink, but without the assertion.
+      * \link operator[](Index) \endlink, but without the assertion.
       * Use this for limiting the performance cost of debugging code when doing
       * repeated coefficient access. Only use this when it is guaranteed that the
       * parameters \a row and \a col are in range.
       *
       * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-      * function equivalent to \link operator[](int) \endlink.
+      * function equivalent to \link operator[](Index) \endlink.
       *
-      * \sa operator[](int), coeff(int) const, coeffRef(int,int)
+      * \sa operator[](Index), coeff(Index) const, coeffRef(Index,Index)
       */
 
     EIGEN_STRONG_INLINE Scalar&
-    coeffRef(int index)
+    coeffRef(Index index)
     {
       ei_internal_assert(index >= 0 && index < size());
       return derived().coeffRef(index);
@@ -324,11 +333,11 @@
       *
       * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
       *
-      * \sa operator[](int) const, operator()(int,int), x(), y(), z(), w()
+      * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
       */
 
     EIGEN_STRONG_INLINE Scalar&
-    operator[](int index)
+    operator[](Index index)
     {
       EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
                           THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
@@ -338,15 +347,15 @@
 
     /** \returns a reference to the coefficient at given index.
       *
-      * This is synonymous to operator[](int).
+      * This is synonymous to operator[](Index).
       *
       * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
       *
-      * \sa operator[](int) const, operator()(int,int), x(), y(), z(), w()
+      * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
       */
 
     EIGEN_STRONG_INLINE Scalar&
-    operator()(int index)
+    operator()(Index index)
     {
       ei_assert(index >= 0 && index < size());
       return derived().coeffRef(index);
@@ -383,7 +392,7 @@
 
     template<int StoreMode>
     EIGEN_STRONG_INLINE void writePacket
-    (int row, int col, const typename ei_packet_traits<Scalar>::type& x)
+    (Index row, Index col, const typename ei_packet_traits<Scalar>::type& x)
     {
       ei_internal_assert(row >= 0 && row < rows()
                         && col >= 0 && col < cols());
@@ -393,7 +402,7 @@
 
     template<int StoreMode>
     EIGEN_STRONG_INLINE void writePacketByOuterInner
-    (int outer, int inner, const typename ei_packet_traits<Scalar>::type& x)
+    (Index outer, Index inner, const typename ei_packet_traits<Scalar>::type& x)
     {
       writePacket<StoreMode>(rowIndexByOuterInner(outer, inner),
                             colIndexByOuterInner(outer, inner),
@@ -411,7 +420,7 @@
 
     template<int StoreMode>
     EIGEN_STRONG_INLINE void writePacket
-    (int index, const typename ei_packet_traits<Scalar>::type& x)
+    (Index index, const typename ei_packet_traits<Scalar>::type& x)
     {
       ei_internal_assert(index >= 0 && index < size());
       derived().template writePacket<StoreMode>(index,x);
@@ -428,7 +437,7 @@
       */
 
     template<typename OtherDerived>
-    EIGEN_STRONG_INLINE void copyCoeff(int row, int col, const DenseBase<OtherDerived>& other)
+    EIGEN_STRONG_INLINE void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
     {
       ei_internal_assert(row >= 0 && row < rows()
                         && col >= 0 && col < cols());
@@ -444,7 +453,7 @@
       */
 
     template<typename OtherDerived>
-    EIGEN_STRONG_INLINE void copyCoeff(int index, const DenseBase<OtherDerived>& other)
+    EIGEN_STRONG_INLINE void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
     {
       ei_internal_assert(index >= 0 && index < size());
       derived().coeffRef(index) = other.derived().coeff(index);
@@ -452,10 +461,10 @@
 
 
     template<typename OtherDerived>
-    EIGEN_STRONG_INLINE void copyCoeffByOuterInner(int outer, int inner, const DenseBase<OtherDerived>& other)
+    EIGEN_STRONG_INLINE void copyCoeffByOuterInner(Index outer, Index inner, const DenseBase<OtherDerived>& other)
     {
-      const int row = rowIndexByOuterInner(outer,inner);
-      const int col = colIndexByOuterInner(outer,inner);
+      const Index row = rowIndexByOuterInner(outer,inner);
+      const Index col = colIndexByOuterInner(outer,inner);
       // derived() is important here: copyCoeff() may be reimplemented in Derived!
       derived().copyCoeff(row, col, other);
     }
@@ -469,7 +478,7 @@
       */
 
     template<typename OtherDerived, int StoreMode, int LoadMode>
-    EIGEN_STRONG_INLINE void copyPacket(int row, int col, const DenseBase<OtherDerived>& other)
+    EIGEN_STRONG_INLINE void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
     {
       ei_internal_assert(row >= 0 && row < rows()
                         && col >= 0 && col < cols());
@@ -486,7 +495,7 @@
       */
 
     template<typename OtherDerived, int StoreMode, int LoadMode>
-    EIGEN_STRONG_INLINE void copyPacket(int index, const DenseBase<OtherDerived>& other)
+    EIGEN_STRONG_INLINE void copyPacket(Index index, const DenseBase<OtherDerived>& other)
     {
       ei_internal_assert(index >= 0 && index < size());
       derived().template writePacket<StoreMode>(index,
@@ -494,10 +503,10 @@
     }
 
     template<typename OtherDerived, int StoreMode, int LoadMode>
-    EIGEN_STRONG_INLINE void copyPacketByOuterInner(int outer, int inner, const DenseBase<OtherDerived>& other)
+    EIGEN_STRONG_INLINE void copyPacketByOuterInner(Index outer, Index inner, const DenseBase<OtherDerived>& other)
     {
-      const int row = rowIndexByOuterInner(outer,inner);
-      const int col = colIndexByOuterInner(outer,inner);
+      const Index row = rowIndexByOuterInner(outer,inner);
+      const Index col = colIndexByOuterInner(outer,inner);
       // derived() is important here: copyCoeff() may be reimplemented in Derived!
       derived().template copyPacket< OtherDerived, StoreMode, LoadMode>(row, col, other);
     }
@@ -507,7 +516,7 @@
       *
       * \sa outerStride(), rowStride(), colStride()
       */
-    inline int innerStride() const
+    inline Index innerStride() const
     {
       return derived().innerStride();
     }
@@ -517,12 +526,12 @@
       *
       * \sa innerStride(), rowStride(), colStride()
       */
-    inline int outerStride() const
+    inline Index outerStride() const
     {
       return derived().outerStride();
     }
 
-    inline int stride() const
+    inline Index stride() const
     {
       return Derived::IsVectorAtCompileTime ? innerStride() : outerStride();
     }
@@ -531,7 +540,7 @@
       *
       * \sa innerStride(), outerStride(), colStride()
       */
-    inline int rowStride() const
+    inline Index rowStride() const
     {
       return Derived::IsRowMajor ? outerStride() : innerStride();
     }
@@ -540,7 +549,7 @@
       *
       * \sa innerStride(), outerStride(), rowStride()
       */
-    inline int colStride() const
+    inline Index colStride() const
     {
       return Derived::IsRowMajor ? innerStride() : outerStride();
     }
@@ -549,14 +558,14 @@
 template<typename Derived, bool JustReturnZero>
 struct ei_first_aligned_impl
 {
-  inline static int run(const Derived&)
+  inline static typename Derived::Index run(const Derived&)
   { return 0; }
 };
 
 template<typename Derived>
 struct ei_first_aligned_impl<Derived, false>
 {
-  inline static int run(const Derived& m)
+  inline static typename Derived::Index run(const Derived& m)
   {
     return ei_first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size());
   }
@@ -568,7 +577,7 @@
   * documentation.
   */
 template<typename Derived>
-inline static int ei_first_aligned(const Derived& m)
+inline static typename Derived::Index ei_first_aligned(const Derived& m)
 {
   return ei_first_aligned_impl
           <Derived, (Derived::Flags & AlignedBit) || !(Derived::Flags & DirectAccessBit)>
diff --git a/Eigen/src/Core/DenseStorageBase.h b/Eigen/src/Core/DenseStorageBase.h
index d2bbb07..15f3988 100644
--- a/Eigen/src/Core/DenseStorageBase.h
+++ b/Eigen/src/Core/DenseStorageBase.h
@@ -44,9 +44,13 @@
   public:
     enum { Options = ei_traits<Derived>::Options };
     typedef typename ei_dense_xpr_base<Derived>::type Base;
-    typedef typename Base::PlainObject PlainObject;
-    typedef typename Base::Scalar Scalar;
-    typedef typename Base::PacketScalar PacketScalar;
+
+    typedef typename ei_traits<Derived>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
+    typedef typename ei_traits<Derived>::Scalar Scalar;
+    typedef typename ei_packet_traits<Scalar>::type PacketScalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
     using Base::RowsAtCompileTime;
     using Base::ColsAtCompileTime;
     using Base::SizeAtCompileTime;
@@ -72,10 +76,10 @@
     Base& base() { return *static_cast<Base*>(this); }
     const Base& base() const { return *static_cast<const Base*>(this); }
 
-    EIGEN_STRONG_INLINE int rows() const { return m_storage.rows(); }
-    EIGEN_STRONG_INLINE int cols() const { return m_storage.cols(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_storage.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_storage.cols(); }
 
-    EIGEN_STRONG_INLINE const Scalar& coeff(int row, int col) const
+    EIGEN_STRONG_INLINE const Scalar& coeff(Index row, Index col) const
     {
       if(Flags & RowMajorBit)
         return m_storage.data()[col + row * m_storage.cols()];
@@ -83,12 +87,12 @@
         return m_storage.data()[row + col * m_storage.rows()];
     }
 
-    EIGEN_STRONG_INLINE const Scalar& coeff(int index) const
+    EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const
     {
       return m_storage.data()[index];
     }
 
-    EIGEN_STRONG_INLINE Scalar& coeffRef(int row, int col)
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
     {
       if(Flags & RowMajorBit)
         return m_storage.data()[col + row * m_storage.cols()];
@@ -96,13 +100,13 @@
         return m_storage.data()[row + col * m_storage.rows()];
     }
 
-    EIGEN_STRONG_INLINE Scalar& coeffRef(int index)
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
     {
       return m_storage.data()[index];
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int row, int col) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
     {
       return ei_ploadt<Scalar, LoadMode>
                (m_storage.data() + (Flags & RowMajorBit
@@ -111,13 +115,13 @@
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int index) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
     {
       return ei_ploadt<Scalar, LoadMode>(m_storage.data() + index);
     }
 
     template<int StoreMode>
-    EIGEN_STRONG_INLINE void writePacket(int row, int col, const PacketScalar& x)
+    EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketScalar& x)
     {
       ei_pstoret<Scalar, PacketScalar, StoreMode>
               (m_storage.data() + (Flags & RowMajorBit
@@ -126,7 +130,7 @@
     }
 
     template<int StoreMode>
-    EIGEN_STRONG_INLINE void writePacket(int index, const PacketScalar& x)
+    EIGEN_STRONG_INLINE void writePacket(Index index, const PacketScalar& x)
     {
       ei_pstoret<Scalar, PacketScalar, StoreMode>(m_storage.data() + index, x);
     }
@@ -143,7 +147,7 @@
       *
       * This method is intended for dynamic-size matrices, although it is legal to call it on any
       * matrix as long as fixed dimensions are left unchanged. If you only want to change the number
-      * of rows and/or of columns, you can use resize(NoChange_t, int), resize(int, NoChange_t).
+      * of rows and/or of columns, you can use resize(NoChange_t, Index), resize(Index, NoChange_t).
       *
       * If the current number of coefficients of \c *this exactly matches the
       * product \a rows * \a cols, then no memory allocation is performed and
@@ -153,12 +157,12 @@
       * Example: \include Matrix_resize_int_int.cpp
       * Output: \verbinclude Matrix_resize_int_int.out
       *
-      * \sa resize(int) for vectors, resize(NoChange_t, int), resize(int, NoChange_t)
+      * \sa resize(Index) for vectors, resize(NoChange_t, Index), resize(Index, NoChange_t)
       */
-    inline void resize(int rows, int cols)
+    inline void resize(Index rows, Index cols)
     {
       #ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
-        int size = rows*cols;
+        Index size = rows*cols;
         bool size_changed = size != this->size();
         m_storage.resize(size, rows, cols);
         if(size_changed) EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
@@ -176,9 +180,9 @@
       * Example: \include Matrix_resize_int.cpp
       * Output: \verbinclude Matrix_resize_int.out
       *
-      * \sa resize(int,int), resize(NoChange_t, int), resize(int, NoChange_t)
+      * \sa resize(Index,Index), resize(NoChange_t, Index), resize(Index, NoChange_t)
       */
-    inline void resize(int size)
+    inline void resize(Index size)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(DenseStorageBase)
       ei_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == size);
@@ -200,9 +204,9 @@
       * Example: \include Matrix_resize_NoChange_int.cpp
       * Output: \verbinclude Matrix_resize_NoChange_int.out
       *
-      * \sa resize(int,int)
+      * \sa resize(Index,Index)
       */
-    inline void resize(NoChange_t, int cols)
+    inline void resize(NoChange_t, Index cols)
     {
       resize(rows(), cols);
     }
@@ -213,9 +217,9 @@
       * Example: \include Matrix_resize_int_NoChange.cpp
       * Output: \verbinclude Matrix_resize_int_NoChange.out
       *
-      * \sa resize(int,int)
+      * \sa resize(Index,Index)
       */
-    inline void resize(int rows, NoChange_t)
+    inline void resize(Index rows, NoChange_t)
     {
       resize(rows, cols());
     }
@@ -231,7 +235,7 @@
     EIGEN_STRONG_INLINE void resizeLike(const EigenBase<OtherDerived>& _other)
     {
       const OtherDerived& other = _other.derived();
-      const int othersize = other.rows()*other.cols();
+      const Index othersize = other.rows()*other.cols();
       if(RowsAtCompileTime == 1)
       {
         ei_assert(other.rows() == 1 || other.cols() == 1);
@@ -248,26 +252,26 @@
     /** Resizes \c *this to a \a rows x \a cols matrix while leaving old values of \c *this untouched.
       *
       * This method is intended for dynamic-size matrices. If you only want to change the number
-      * of rows and/or of columns, you can use conservativeResize(NoChange_t, int),
-      * conservativeResize(int, NoChange_t).
+      * of rows and/or of columns, you can use conservativeResize(NoChange_t, Index),
+      * conservativeResize(Index, NoChange_t).
       *
       * The top-left part of the resized matrix will be the same as the overlapping top-left corner
       * of \c *this. In case values need to be appended to the matrix they will be uninitialized.
       */
-    EIGEN_STRONG_INLINE void conservativeResize(int rows, int cols)
+    EIGEN_STRONG_INLINE void conservativeResize(Index rows, Index cols)
     {
       ei_conservative_resize_like_impl<Derived>::run(*this, rows, cols);
     }
 
-    EIGEN_STRONG_INLINE void conservativeResize(int rows, NoChange_t)
+    EIGEN_STRONG_INLINE void conservativeResize(Index rows, NoChange_t)
     {
-      // Note: see the comment in conservativeResize(int,int)
+      // Note: see the comment in conservativeResize(Index,Index)
       conservativeResize(rows, cols());
     }
 
-    EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, int cols)
+    EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index cols)
     {
-      // Note: see the comment in conservativeResize(int,int)
+      // Note: see the comment in conservativeResize(Index,Index)
       conservativeResize(rows(), cols);
     }
 
@@ -279,7 +283,7 @@
       *
       * When values are appended, they will be uninitialized.
       */
-    EIGEN_STRONG_INLINE void conservativeResize(int size)
+    EIGEN_STRONG_INLINE void conservativeResize(Index size)
     {
       ei_conservative_resize_like_impl<Derived>::run(*this, size);
     }
@@ -329,7 +333,7 @@
     }
 #endif
 
-    EIGEN_STRONG_INLINE DenseStorageBase(int size, int rows, int cols)
+    EIGEN_STRONG_INLINE DenseStorageBase(Index size, Index rows, Index cols)
       : m_storage(size, rows, cols)
     {
 //       _check_template_params();
@@ -370,44 +374,44 @@
     { return UnalignedMapType(data); }
     inline static UnalignedMapType Map(Scalar* data)
     { return UnalignedMapType(data); }
-    inline static const UnalignedMapType Map(const Scalar* data, int size)
+    inline static const UnalignedMapType Map(const Scalar* data, Index size)
     { return UnalignedMapType(data, size); }
-    inline static UnalignedMapType Map(Scalar* data, int size)
+    inline static UnalignedMapType Map(Scalar* data, Index size)
     { return UnalignedMapType(data, size); }
-    inline static const UnalignedMapType Map(const Scalar* data, int rows, int cols)
+    inline static const UnalignedMapType Map(const Scalar* data, Index rows, Index cols)
     { return UnalignedMapType(data, rows, cols); }
-    inline static UnalignedMapType Map(Scalar* data, int rows, int cols)
+    inline static UnalignedMapType Map(Scalar* data, Index rows, Index cols)
     { return UnalignedMapType(data, rows, cols); }
 
     inline static const AlignedMapType MapAligned(const Scalar* data)
     { return AlignedMapType(data); }
     inline static AlignedMapType MapAligned(Scalar* data)
     { return AlignedMapType(data); }
-    inline static const AlignedMapType MapAligned(const Scalar* data, int size)
+    inline static const AlignedMapType MapAligned(const Scalar* data, Index size)
     { return AlignedMapType(data, size); }
-    inline static AlignedMapType MapAligned(Scalar* data, int size)
+    inline static AlignedMapType MapAligned(Scalar* data, Index size)
     { return AlignedMapType(data, size); }
-    inline static const AlignedMapType MapAligned(const Scalar* data, int rows, int cols)
+    inline static const AlignedMapType MapAligned(const Scalar* data, Index rows, Index cols)
     { return AlignedMapType(data, rows, cols); }
-    inline static AlignedMapType MapAligned(Scalar* data, int rows, int cols)
+    inline static AlignedMapType MapAligned(Scalar* data, Index rows, Index cols)
     { return AlignedMapType(data, rows, cols); }
     //@}
 
     using Base::setConstant;
-    Derived& setConstant(int size, const Scalar& value);
-    Derived& setConstant(int rows, int cols, const Scalar& value);
+    Derived& setConstant(Index size, const Scalar& value);
+    Derived& setConstant(Index rows, Index cols, const Scalar& value);
 
     using Base::setZero;
-    Derived& setZero(int size);
-    Derived& setZero(int rows, int cols);
+    Derived& setZero(Index size);
+    Derived& setZero(Index rows, Index cols);
 
     using Base::setOnes;
-    Derived& setOnes(int size);
-    Derived& setOnes(int rows, int cols);
+    Derived& setOnes(Index size);
+    Derived& setOnes(Index rows, Index cols);
 
     using Base::setRandom;
-    Derived& setRandom(int size);
-    Derived& setRandom(int rows, int cols);
+    Derived& setRandom(Index size);
+    Derived& setRandom(Index rows, Index cols);
 
     #ifdef EIGEN_DENSESTORAGEBASE_PLUGIN
     #include EIGEN_DENSESTORAGEBASE_PLUGIN
@@ -474,7 +478,7 @@
     }
 
     template<typename T0, typename T1>
-    EIGEN_STRONG_INLINE void _init2(int rows, int cols, typename ei_enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
+    EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, typename ei_enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
     {
       ei_assert(rows > 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
              && cols > 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
@@ -526,7 +530,8 @@
 template <typename Derived, typename OtherDerived, bool IsVector>
 struct ei_conservative_resize_like_impl
 {
-  static void run(DenseBase<Derived>& _this, int rows, int cols)
+  typedef typename Derived::Index Index;
+  static void run(DenseBase<Derived>& _this, Index rows, Index cols)
   {
     if (_this.rows() == rows && _this.cols() == cols) return;
     EIGEN_STATIC_ASSERT_DYNAMIC_SIZE(Derived)
@@ -540,8 +545,8 @@
     {
       // The storage order does not allow us to use reallocation.
       typename Derived::PlainObject tmp(rows,cols);
-      const int common_rows = std::min(rows, _this.rows());
-      const int common_cols = std::min(cols, _this.cols());
+      const Index common_rows = std::min(rows, _this.rows());
+      const Index common_cols = std::min(cols, _this.cols());
       tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols);
       _this.derived().swap(tmp);
     }
@@ -551,10 +556,10 @@
   {
     if (_this.rows() == other.rows() && _this.cols() == other.cols()) return;
 
-    // Note: Here is space for improvement. Basically, for conservativeResize(int,int),
+    // Note: Here is space for improvement. Basically, for conservativeResize(Index,Index),
     // neither RowsAtCompileTime or ColsAtCompileTime must be Dynamic. If only one of the
-    // dimensions is dynamic, one could use either conservativeResize(int rows, NoChange_t) or
-    // conservativeResize(NoChange_t, int cols). For these methods new static asserts like
+    // dimensions is dynamic, one could use either conservativeResize(Index rows, NoChange_t) or
+    // conservativeResize(NoChange_t, Index cols). For these methods new static asserts like
     // EIGEN_STATIC_ASSERT_DYNAMIC_ROWS and EIGEN_STATIC_ASSERT_DYNAMIC_COLS would be good.
     EIGEN_STATIC_ASSERT_DYNAMIC_SIZE(Derived)
     EIGEN_STATIC_ASSERT_DYNAMIC_SIZE(OtherDerived)
@@ -562,8 +567,8 @@
     if ( ( Derived::IsRowMajor && _this.cols() == other.cols()) || // row-major and we change only the number of rows
          (!Derived::IsRowMajor && _this.rows() == other.rows()) )  // column-major and we change only the number of columns
     {
-      const int new_rows = other.rows() - _this.rows();
-      const int new_cols = other.cols() - _this.cols();
+      const Index new_rows = other.rows() - _this.rows();
+      const Index new_cols = other.cols() - _this.cols();
       _this.derived().m_storage.conservativeResize(other.size(),other.rows(),other.cols());
       if (new_rows>0)
         _this.bottomRightCorner(new_rows, other.cols()) = other.bottomRows(new_rows);
@@ -574,8 +579,8 @@
     {
       // The storage order does not allow us to use reallocation.
       typename Derived::PlainObject tmp(other);
-      const int common_rows = std::min(tmp.rows(), _this.rows());
-      const int common_cols = std::min(tmp.cols(), _this.cols());
+      const Index common_rows = std::min(tmp.rows(), _this.rows());
+      const Index common_cols = std::min(tmp.cols(), _this.cols());
       tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols);
       _this.derived().swap(tmp);
     }
@@ -585,10 +590,11 @@
 template <typename Derived, typename OtherDerived>
 struct ei_conservative_resize_like_impl<Derived,OtherDerived,true>
 {
-  static void run(DenseBase<Derived>& _this, int size)
+  typedef typename Derived::Index Index;
+  static void run(DenseBase<Derived>& _this, Index size)
   {
-    const int new_rows = Derived::RowsAtCompileTime==1 ? 1 : size;
-    const int new_cols = Derived::RowsAtCompileTime==1 ? size : 1;
+    const Index new_rows = Derived::RowsAtCompileTime==1 ? 1 : size;
+    const Index new_cols = Derived::RowsAtCompileTime==1 ? size : 1;
     _this.derived().m_storage.conservativeResize(size,new_rows,new_cols);
   }
 
@@ -596,10 +602,10 @@
   {
     if (_this.rows() == other.rows() && _this.cols() == other.cols()) return;
 
-    const int num_new_elements = other.size() - _this.size();
+    const Index num_new_elements = other.size() - _this.size();
 
-    const int new_rows = Derived::RowsAtCompileTime==1 ? 1 : other.rows();
-    const int new_cols = Derived::RowsAtCompileTime==1 ? other.cols() : 1;
+    const Index new_rows = Derived::RowsAtCompileTime==1 ? 1 : other.rows();
+    const Index new_cols = Derived::RowsAtCompileTime==1 ? other.cols() : 1;
     _this.derived().m_storage.conservativeResize(other.size(),new_rows,new_cols);
 
     if (num_new_elements > 0)
diff --git a/Eigen/src/Core/Diagonal.h b/Eigen/src/Core/Diagonal.h
index 9ae7d79..a4326a2 100644
--- a/Eigen/src/Core/Diagonal.h
+++ b/Eigen/src/Core/Diagonal.h
@@ -30,33 +30,34 @@
   * \brief Expression of a diagonal/subdiagonal/superdiagonal in a matrix
   *
   * \param MatrixType the type of the object in which we are taking a sub/main/super diagonal
-  * \param Index the index of the sub/super diagonal. The default is 0 and it means the main diagonal.
+  * \param DiagIndex the index of the sub/super diagonal. The default is 0 and it means the main diagonal.
   *              A positive value means a superdiagonal, a negative value means a subdiagonal.
   *              You can also use Dynamic so the index can be set at runtime.
   *
   * The matrix is not required to be square.
   *
   * This class represents an expression of the main diagonal, or any sub/super diagonal
-  * of a square matrix. It is the return type of MatrixBase::diagonal() and MatrixBase::diagonal(int) and most of the
+  * of a square matrix. It is the return type of MatrixBase::diagonal() and MatrixBase::diagonal(Index) and most of the
   * time this is the only way it is used.
   *
-  * \sa MatrixBase::diagonal(), MatrixBase::diagonal(int)
+  * \sa MatrixBase::diagonal(), MatrixBase::diagonal(Index)
   */
-template<typename MatrixType, int Index>
-struct ei_traits<Diagonal<MatrixType,Index> >
+template<typename MatrixType, int DiagIndex>
+struct ei_traits<Diagonal<MatrixType,DiagIndex> >
  : ei_traits<MatrixType>
 {
   typedef typename ei_nested<MatrixType>::type MatrixTypeNested;
   typedef typename ei_unref<MatrixTypeNested>::type _MatrixTypeNested;
+  typedef typename MatrixType::StorageKind StorageKind;
   enum {
-    AbsIndex = Index<0 ? -Index : Index, // only used if Index != Dynamic
-    RowsAtCompileTime = (int(Index) == Dynamic || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
+    AbsDiagIndex = DiagIndex<0 ? -DiagIndex : DiagIndex, // only used if DiagIndex != Dynamic
+    RowsAtCompileTime = (int(DiagIndex) == Dynamic || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
                       : (EIGEN_ENUM_MIN(MatrixType::RowsAtCompileTime,
-                                        MatrixType::ColsAtCompileTime) - AbsIndex),
+                                        MatrixType::ColsAtCompileTime) - AbsDiagIndex),
     ColsAtCompileTime = 1,
     MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
-                         : Index == Dynamic ? EIGEN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime, MatrixType::MaxColsAtCompileTime)
-                         : (EIGEN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime, MatrixType::MaxColsAtCompileTime) - AbsIndex),
+                         : DiagIndex == Dynamic ? EIGEN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime, MatrixType::MaxColsAtCompileTime)
+                         : (EIGEN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime, MatrixType::MaxColsAtCompileTime) - AbsDiagIndex),
     MaxColsAtCompileTime = 1,
     Flags = (unsigned int)_MatrixTypeNested::Flags & (HereditaryBits | LinearAccessBit | DirectAccessBit) & ~RowMajorBit,
     CoeffReadCost = _MatrixTypeNested::CoeffReadCost,
@@ -66,61 +67,62 @@
   };
 };
 
-template<typename MatrixType, int Index> class Diagonal
-   : public ei_dense_xpr_base< Diagonal<MatrixType,Index> >::type
+template<typename MatrixType, int DiagIndex> class Diagonal
+   : public ei_dense_xpr_base< Diagonal<MatrixType,DiagIndex> >::type
 {
-    // some compilers may fail to optimize std::max etc in case of compile-time constants...
-    EIGEN_STRONG_INLINE int absIndex() const { return m_index.value()>0 ? m_index.value() : -m_index.value(); }
-    EIGEN_STRONG_INLINE int rowOffset() const { return m_index.value()>0 ? 0 : -m_index.value(); }
-    EIGEN_STRONG_INLINE int colOffset() const { return m_index.value()>0 ? m_index.value() : 0; }
-
   public:
 
     typedef typename ei_dense_xpr_base<Diagonal>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
 
-    inline Diagonal(const MatrixType& matrix, int index = Index) : m_matrix(matrix), m_index(index) {}
+    inline Diagonal(const MatrixType& matrix, Index index = DiagIndex) : m_matrix(matrix), m_index(index) {}
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
 
-    inline int rows() const
+    inline Index rows() const
     { return m_index.value()<0 ? std::min(m_matrix.cols(),m_matrix.rows()+m_index.value()) : std::min(m_matrix.rows(),m_matrix.cols()-m_index.value()); }
 
-    inline int cols() const { return 1; }
+    inline Index cols() const { return 1; }
 
-    inline int innerStride() const
+    inline Index innerStride() const
     {
       return m_matrix.outerStride() + 1;
     }
 
-    inline int outerStride() const
+    inline Index outerStride() const
     {
       return 0;
     }
 
-    inline Scalar& coeffRef(int row, int)
+    inline Scalar& coeffRef(Index row, Index)
     {
       return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset());
     }
 
-    inline CoeffReturnType coeff(int row, int) const
+    inline CoeffReturnType coeff(Index row, Index) const
     {
       return m_matrix.coeff(row+rowOffset(), row+colOffset());
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       return m_matrix.const_cast_derived().coeffRef(index+rowOffset(), index+colOffset());
     }
 
-    inline CoeffReturnType coeff(int index) const
+    inline CoeffReturnType coeff(Index index) const
     {
       return m_matrix.coeff(index+rowOffset(), index+colOffset());
     }
 
   protected:
     const typename MatrixType::Nested m_matrix;
-    const ei_int_if_dynamic<Index> m_index;
+    const ei_variable_if_dynamic<Index, DiagIndex> m_index;
+
+  private:
+    // some compilers may fail to optimize std::max etc in case of compile-time constants...
+    EIGEN_STRONG_INLINE Index absDiagIndex() const { return m_index.value()>0 ? m_index.value() : -m_index.value(); }
+    EIGEN_STRONG_INLINE Index rowOffset() const { return m_index.value()>0 ? 0 : -m_index.value(); }
+    EIGEN_STRONG_INLINE Index colOffset() const { return m_index.value()>0 ? m_index.value() : 0; }
 };
 
 /** \returns an expression of the main diagonal of the matrix \c *this
@@ -146,12 +148,12 @@
   return Diagonal<Derived, 0>(derived());
 }
 
-/** \returns an expression of the \a Index-th sub or super diagonal of the matrix \c *this
+/** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
   *
   * \c *this is not required to be square.
   *
-  * The template parameter \a Index represent a super diagonal if \a Index > 0
-  * and a sub diagonal otherwise. \a Index == 0 is equivalent to the main diagonal.
+  * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
+  * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
   *
   * Example: \include MatrixBase_diagonal_int.cpp
   * Output: \verbinclude MatrixBase_diagonal_int.out
@@ -159,45 +161,45 @@
   * \sa MatrixBase::diagonal(), class Diagonal */
 template<typename Derived>
 inline Diagonal<Derived, Dynamic>
-MatrixBase<Derived>::diagonal(int index)
+MatrixBase<Derived>::diagonal(Index index)
 {
   return Diagonal<Derived, Dynamic>(derived(), index);
 }
 
-/** This is the const version of diagonal(int). */
+/** This is the const version of diagonal(Index). */
 template<typename Derived>
 inline const Diagonal<Derived, Dynamic>
-MatrixBase<Derived>::diagonal(int index) const
+MatrixBase<Derived>::diagonal(Index index) const
 {
   return Diagonal<Derived, Dynamic>(derived(), index);
 }
 
-/** \returns an expression of the \a Index-th sub or super diagonal of the matrix \c *this
+/** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
   *
   * \c *this is not required to be square.
   *
-  * The template parameter \a Index represent a super diagonal if \a Index > 0
-  * and a sub diagonal otherwise. \a Index == 0 is equivalent to the main diagonal.
+  * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
+  * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
   *
   * Example: \include MatrixBase_diagonal_template_int.cpp
   * Output: \verbinclude MatrixBase_diagonal_template_int.out
   *
   * \sa MatrixBase::diagonal(), class Diagonal */
 template<typename Derived>
-template<int Index>
-inline Diagonal<Derived,Index>
+template<int DiagIndex>
+inline Diagonal<Derived,DiagIndex>
 MatrixBase<Derived>::diagonal()
 {
-  return Diagonal<Derived,Index>(derived());
+  return Diagonal<Derived,DiagIndex>(derived());
 }
 
 /** This is the const version of diagonal<int>(). */
 template<typename Derived>
-template<int Index>
-inline const Diagonal<Derived,Index>
+template<int DiagIndex>
+inline const Diagonal<Derived,DiagIndex>
 MatrixBase<Derived>::diagonal() const
 {
-  return Diagonal<Derived,Index>(derived());
+  return Diagonal<Derived,DiagIndex>(derived());
 }
 
 #endif // EIGEN_DIAGONAL_H
diff --git a/Eigen/src/Core/DiagonalMatrix.h b/Eigen/src/Core/DiagonalMatrix.h
index 774b0d7..8d3b458 100644
--- a/Eigen/src/Core/DiagonalMatrix.h
+++ b/Eigen/src/Core/DiagonalMatrix.h
@@ -33,6 +33,8 @@
   public:
     typedef typename ei_traits<Derived>::DiagonalVectorType DiagonalVectorType;
     typedef typename DiagonalVectorType::Scalar Scalar;
+    typedef typename ei_traits<Derived>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
 
     enum {
       RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
@@ -61,8 +63,8 @@
     inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
     inline DiagonalVectorType& diagonal() { return derived().diagonal(); }
 
-    inline int rows() const { return diagonal().size(); }
-    inline int cols() const { return diagonal().size(); }
+    inline Index rows() const { return diagonal().size(); }
+    inline Index cols() const { return diagonal().size(); }
 
     template<typename MatrixDerived>
     const DiagonalProduct<MatrixDerived, Derived, OnTheLeft>
@@ -100,6 +102,7 @@
  : ei_traits<Matrix<_Scalar,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
 {
   typedef Matrix<_Scalar,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType;
+  typedef Dense StorageKind;
 };
 
 template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime>
@@ -111,6 +114,8 @@
     typedef typename ei_traits<DiagonalMatrix>::DiagonalVectorType DiagonalVectorType;
     typedef const DiagonalMatrix& Nested;
     typedef _Scalar Scalar;
+    typedef typename ei_traits<DiagonalMatrix>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
     #endif
 
   protected:
@@ -128,7 +133,7 @@
     inline DiagonalMatrix() {}
 
     /** Constructs a diagonal matrix with given dimension  */
-    inline DiagonalMatrix(int dim) : m_diagonal(dim) {}
+    inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
 
     /** 2D constructor. */
     inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x,y) {}
@@ -170,15 +175,15 @@
     #endif
 
     /** Resizes to given size. */
-    inline void resize(int size) { m_diagonal.resize(size); }
+    inline void resize(Index size) { m_diagonal.resize(size); }
     /** Sets all coefficients to zero. */
     inline void setZero() { m_diagonal.setZero(); }
     /** Resizes and sets all coefficients to zero. */
-    inline void setZero(int size) { m_diagonal.setZero(size); }
+    inline void setZero(Index size) { m_diagonal.setZero(size); }
     /** Sets this matrix to be the identity matrix of the current size. */
     inline void setIdentity() { m_diagonal.setOnes(); }
     /** Sets this matrix to be the identity matrix of the given size. */
-    inline void setIdentity(int size) { m_diagonal.setOnes(size); }
+    inline void setIdentity(Index size) { m_diagonal.setOnes(size); }
 };
 
 /** \class DiagonalWrapper
@@ -198,6 +203,7 @@
 {
   typedef _DiagonalVectorType DiagonalVectorType;
   typedef typename DiagonalVectorType::Scalar Scalar;
+  typedef typename DiagonalVectorType::StorageKind StorageKind;
   enum {
     RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
     ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
@@ -257,13 +263,13 @@
 {
   if(cols() != rows()) return false;
   RealScalar maxAbsOnDiagonal = static_cast<RealScalar>(-1);
-  for(int j = 0; j < cols(); ++j)
+  for(Index j = 0; j < cols(); ++j)
   {
     RealScalar absOnDiagonal = ei_abs(coeff(j,j));
     if(absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal;
   }
-  for(int j = 0; j < cols(); ++j)
-    for(int i = 0; i < j; ++i)
+  for(Index j = 0; j < cols(); ++j)
+    for(Index i = 0; i < j; ++i)
     {
       if(!ei_isMuchSmallerThan(coeff(i, j), maxAbsOnDiagonal, prec)) return false;
       if(!ei_isMuchSmallerThan(coeff(j, i), maxAbsOnDiagonal, prec)) return false;
diff --git a/Eigen/src/Core/DiagonalProduct.h b/Eigen/src/Core/DiagonalProduct.h
index 868b441..f3af814 100644
--- a/Eigen/src/Core/DiagonalProduct.h
+++ b/Eigen/src/Core/DiagonalProduct.h
@@ -57,23 +57,23 @@
       ei_assert(diagonal.diagonal().size() == (ProductOrder == OnTheLeft ? matrix.rows() : matrix.cols()));
     }
 
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
 
-    const Scalar coeff(int row, int col) const
+    const Scalar coeff(Index row, Index col) const
     {
       return m_diagonal.diagonal().coeff(ProductOrder == OnTheLeft ? row : col) * m_matrix.coeff(row, col);
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int row, int col) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
     {
       enum {
         StorageOrder = Flags & RowMajorBit ? RowMajor : ColMajor,
         InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime,
         DiagonalVectorPacketLoadMode = (LoadMode == Aligned && ((InnerSize%16) == 0)) ? Aligned : Unaligned
       };
-      const int indexInDiagonalVector = ProductOrder == OnTheLeft ? row : col;
+      const Index indexInDiagonalVector = ProductOrder == OnTheLeft ? row : col;
 
       if((int(StorageOrder) == RowMajor && int(ProductOrder) == OnTheLeft)
        ||(int(StorageOrder) == ColMajor && int(ProductOrder) == OnTheRight))
diff --git a/Eigen/src/Core/Dot.h b/Eigen/src/Core/Dot.h
index 4bd8187..6e54dac 100644
--- a/Eigen/src/Core/Dot.h
+++ b/Eigen/src/Core/Dot.h
@@ -159,11 +159,11 @@
 bool MatrixBase<Derived>::isUnitary(RealScalar prec) const
 {
   typename Derived::Nested nested(derived());
-  for(int i = 0; i < cols(); ++i)
+  for(Index i = 0; i < cols(); ++i)
   {
     if(!ei_isApprox(nested.col(i).squaredNorm(), static_cast<RealScalar>(1), prec))
       return false;
-    for(int j = 0; j < i; ++j)
+    for(Index j = 0; j < i; ++j)
       if(!ei_isMuchSmallerThan(nested.col(i).dot(nested.col(j)), static_cast<Scalar>(1), prec))
         return false;
   }
diff --git a/Eigen/src/Core/EigenBase.h b/Eigen/src/Core/EigenBase.h
index e583fdd..c9d3bd8 100644
--- a/Eigen/src/Core/EigenBase.h
+++ b/Eigen/src/Core/EigenBase.h
@@ -39,6 +39,9 @@
 {
 //   typedef typename ei_plain_matrix_type<Derived>::type PlainObject;
 
+  typedef typename ei_traits<Derived>::StorageKind StorageKind;
+  typedef typename ei_index<StorageKind>::type Index;
+
   /** \returns a reference to the derived object */
   Derived& derived() { return *static_cast<Derived*>(this); }
   /** \returns a const reference to the derived object */
@@ -48,12 +51,12 @@
   { return *static_cast<Derived*>(const_cast<EigenBase*>(this)); }
 
   /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
-  inline int rows() const { return derived().rows(); }
+  inline Index rows() const { return derived().rows(); }
   /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
-  inline int cols() const { return derived().cols(); }
+  inline Index cols() const { return derived().cols(); }
   /** \returns the number of coefficients, which is rows()*cols().
     * \sa rows(), cols(), SizeAtCompileTime. */
-  inline int size() const { return rows() * cols(); }
+  inline Index size() const { return rows() * cols(); }
 
   /** \internal Don't use it, but do the equivalent: \code dst = *this; \endcode */
   template<typename Dest> inline void evalTo(Dest& dst) const
diff --git a/Eigen/src/Core/Flagged.h b/Eigen/src/Core/Flagged.h
index 9413b74..7936f9d 100644
--- a/Eigen/src/Core/Flagged.h
+++ b/Eigen/src/Core/Flagged.h
@@ -58,51 +58,51 @@
 
     inline Flagged(const ExpressionType& matrix) : m_matrix(matrix) {}
 
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
-    inline int outerStride() const { return m_matrix.outerStride(); }
-    inline int innerStride() const { return m_matrix.innerStride(); }
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
+    inline Index outerStride() const { return m_matrix.outerStride(); }
+    inline Index innerStride() const { return m_matrix.innerStride(); }
 
-    inline const Scalar coeff(int row, int col) const
+    inline const Scalar coeff(Index row, Index col) const
     {
       return m_matrix.coeff(row, col);
     }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return m_matrix.const_cast_derived().coeffRef(row, col);
     }
 
-    inline const Scalar coeff(int index) const
+    inline const Scalar coeff(Index index) const
     {
       return m_matrix.coeff(index);
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       return m_matrix.const_cast_derived().coeffRef(index);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int row, int col) const
+    inline const PacketScalar packet(Index row, Index col) const
     {
       return m_matrix.template packet<LoadMode>(row, col);
     }
 
     template<int LoadMode>
-    inline void writePacket(int row, int col, const PacketScalar& x)
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
     {
       m_matrix.const_cast_derived().template writePacket<LoadMode>(row, col, x);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int index) const
+    inline const PacketScalar packet(Index index) const
     {
       return m_matrix.template packet<LoadMode>(index);
     }
 
     template<int LoadMode>
-    inline void writePacket(int index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& x)
     {
       m_matrix.const_cast_derived().template writePacket<LoadMode>(index, x);
     }
diff --git a/Eigen/src/Core/ForceAlignedAccess.h b/Eigen/src/Core/ForceAlignedAccess.h
index eedd577..7db138b 100644
--- a/Eigen/src/Core/ForceAlignedAccess.h
+++ b/Eigen/src/Core/ForceAlignedAccess.h
@@ -50,51 +50,51 @@
 
     inline ForceAlignedAccess(const ExpressionType& matrix) : m_expression(matrix) {}
 
-    inline int rows() const { return m_expression.rows(); }
-    inline int cols() const { return m_expression.cols(); }
-    inline int outerStride() const { return m_expression.outerStride(); }
-    inline int innerStride() const { return m_expression.innerStride(); }
+    inline Index rows() const { return m_expression.rows(); }
+    inline Index cols() const { return m_expression.cols(); }
+    inline Index outerStride() const { return m_expression.outerStride(); }
+    inline Index innerStride() const { return m_expression.innerStride(); }
 
-    inline const CoeffReturnType coeff(int row, int col) const
+    inline const CoeffReturnType coeff(Index row, Index col) const
     {
       return m_expression.coeff(row, col);
     }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return m_expression.const_cast_derived().coeffRef(row, col);
     }
 
-    inline const CoeffReturnType coeff(int index) const
+    inline const CoeffReturnType coeff(Index index) const
     {
       return m_expression.coeff(index);
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       return m_expression.const_cast_derived().coeffRef(index);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int row, int col) const
+    inline const PacketScalar packet(Index row, Index col) const
     {
       return m_expression.template packet<Aligned>(row, col);
     }
 
     template<int LoadMode>
-    inline void writePacket(int row, int col, const PacketScalar& x)
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
     {
       m_expression.const_cast_derived().template writePacket<Aligned>(row, col, x);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int index) const
+    inline const PacketScalar packet(Index index) const
     {
       return m_expression.template packet<Aligned>(index);
     }
 
     template<int LoadMode>
-    inline void writePacket(int index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& x)
     {
       m_expression.const_cast_derived().template writePacket<Aligned>(index, x);
     }
diff --git a/Eigen/src/Core/Functors.h b/Eigen/src/Core/Functors.h
index a42f36b..d559dee 100644
--- a/Eigen/src/Core/Functors.h
+++ b/Eigen/src/Core/Functors.h
@@ -464,8 +464,10 @@
   typedef typename ei_packet_traits<Scalar>::type PacketScalar;
   EIGEN_STRONG_INLINE ei_scalar_constant_op(const ei_scalar_constant_op& other) : m_other(other.m_other) { }
   EIGEN_STRONG_INLINE ei_scalar_constant_op(const Scalar& other) : m_other(other) { }
-  EIGEN_STRONG_INLINE const Scalar operator() (int, int = 0) const { return m_other; }
-  EIGEN_STRONG_INLINE const PacketScalar packetOp(int, int = 0) const { return ei_pset1(m_other); }
+  template<typename Index>
+  EIGEN_STRONG_INLINE const Scalar operator() (Index, Index = 0) const { return m_other; }
+  template<typename Index>
+  EIGEN_STRONG_INLINE const PacketScalar packetOp(Index, Index = 0) const { return ei_pset1(m_other); }
   const Scalar m_other;
 };
 template<typename Scalar>
@@ -474,7 +476,8 @@
 
 template<typename Scalar> struct ei_scalar_identity_op {
   EIGEN_EMPTY_STRUCT_CTOR(ei_scalar_identity_op)
-  EIGEN_STRONG_INLINE const Scalar operator() (int row, int col) const { return row==col ? Scalar(1) : Scalar(0); }
+  template<typename Index>
+  EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const { return row==col ? Scalar(1) : Scalar(0); }
 };
 template<typename Scalar>
 struct ei_functor_traits<ei_scalar_identity_op<Scalar> >
@@ -497,8 +500,10 @@
   m_packetStep(ei_pset1(ei_packet_traits<Scalar>::size*step)), 
   m_base(ei_padd(ei_pset1(low),ei_pmul(ei_pset1(step),ei_plset<Scalar>(-ei_packet_traits<Scalar>::size)))) {}
 
-  EIGEN_STRONG_INLINE const Scalar operator() (int i) const { return m_low+i*m_step; }
-  EIGEN_STRONG_INLINE const PacketScalar packetOp(int) const { return m_base = ei_padd(m_base,m_packetStep); }  
+  template<typename Index>
+  EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return m_low+i*m_step; }
+  template<typename Index>
+  EIGEN_STRONG_INLINE const PacketScalar packetOp(Index) const { return m_base = ei_padd(m_base,m_packetStep); }
 
   const Scalar m_low;
   const Scalar m_step;
@@ -518,8 +523,10 @@
   m_low(low), m_step(step), 
   m_lowPacket(ei_pset1(m_low)), m_stepPacket(ei_pset1(m_step)), m_interPacket(ei_plset<Scalar>(0)) {}
 
-  EIGEN_STRONG_INLINE const Scalar operator() (int i) const { return m_low+i*m_step; }
-  EIGEN_STRONG_INLINE const PacketScalar packetOp(int i) const 
+  template<typename Index>
+  EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return m_low+i*m_step; }
+  template<typename Index>
+  EIGEN_STRONG_INLINE const PacketScalar packetOp(Index i) const
   { return ei_padd(m_lowPacket, ei_pmul(m_stepPacket, ei_padd(ei_pset1<Scalar>(i),m_interPacket))); }
 
   const Scalar m_low;
@@ -541,8 +548,10 @@
 {
   typedef typename ei_packet_traits<Scalar>::type PacketScalar;
   ei_linspaced_op(Scalar low, Scalar high, int num_steps) : impl(low, (high-low)/(num_steps-1)) {}
-  EIGEN_STRONG_INLINE const Scalar operator() (int i, int = 0) const { return impl(i); }
-  EIGEN_STRONG_INLINE const PacketScalar packetOp(int i, int = 0) const { return impl.packetOp(i); }
+  template<typename Index>
+  EIGEN_STRONG_INLINE const Scalar operator() (Index i, Index = 0) const { return impl(i); }
+  template<typename Index>
+  EIGEN_STRONG_INLINE const PacketScalar packetOp(Index i, Index = 0) const { return impl.packetOp(i); }
   // This proxy object handles the actual required temporaries, the different 
   // implementations (random vs. sequential access) as well as the piping
   // correct piping to size 2/4 packet operations.
diff --git a/Eigen/src/Core/Fuzzy.h b/Eigen/src/Core/Fuzzy.h
index 432da42..2996409 100644
--- a/Eigen/src/Core/Fuzzy.h
+++ b/Eigen/src/Core/Fuzzy.h
@@ -201,13 +201,14 @@
 struct ei_fuzzy_selector<Derived,OtherDerived,false>
 {
   typedef typename Derived::RealScalar RealScalar;
+  typedef typename Derived::Index Index;
   static bool isApprox(const Derived& self, const OtherDerived& other, RealScalar prec)
   {
     EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived)
     ei_assert(self.rows() == other.rows() && self.cols() == other.cols());
     typename Derived::Nested nested(self);
     typename OtherDerived::Nested otherNested(other);
-    for(int i = 0; i < self.cols(); ++i)
+    for(Index i = 0; i < self.cols(); ++i)
       if((nested.col(i) - otherNested.col(i)).squaredNorm()
           > std::min(nested.col(i).squaredNorm(), otherNested.col(i).squaredNorm()) * prec * prec)
         return false;
@@ -216,7 +217,7 @@
   static bool isMuchSmallerThan(const Derived& self, const RealScalar& other, RealScalar prec)
   {
     typename Derived::Nested nested(self);
-    for(int i = 0; i < self.cols(); ++i)
+    for(Index i = 0; i < self.cols(); ++i)
       if(nested.col(i).squaredNorm() > ei_abs2(other * prec))
         return false;
     return true;
@@ -227,7 +228,7 @@
     ei_assert(self.rows() == other.rows() && self.cols() == other.cols());
     typename Derived::Nested nested(self);
     typename OtherDerived::Nested otherNested(other);
-    for(int i = 0; i < self.cols(); ++i)
+    for(Index i = 0; i < self.cols(); ++i)
       if(nested.col(i).squaredNorm() > otherNested.col(i).squaredNorm() * prec * prec)
         return false;
     return true;
diff --git a/Eigen/src/Core/IO.h b/Eigen/src/Core/IO.h
index 3da92d2..f9b2f08 100644
--- a/Eigen/src/Core/IO.h
+++ b/Eigen/src/Core/IO.h
@@ -157,8 +157,9 @@
 {
   const typename Derived::Nested m = _m;
   typedef typename Derived::Scalar Scalar;
+  typedef typename Derived::Index Index;
 
-  int width = 0;
+  Index width = 0;
 
   std::streamsize explicit_precision;
   if(fmt.precision == StreamPrecision)
@@ -185,26 +186,26 @@
   if(align_cols)
   {
     // compute the largest width
-    for(int j = 1; j < m.cols(); ++j)
-      for(int i = 0; i < m.rows(); ++i)
+    for(Index j = 1; j < m.cols(); ++j)
+      for(Index i = 0; i < m.rows(); ++i)
       {
         std::stringstream sstr;
         if(explicit_precision) sstr.precision(explicit_precision);
         sstr << m.coeff(i,j);
-        width = std::max<int>(width, int(sstr.str().length()));
+        width = std::max<Index>(width, Index(sstr.str().length()));
       }
   }
   std::streamsize old_precision = 0;
   if(explicit_precision) old_precision = s.precision(explicit_precision);
   s << fmt.matPrefix;
-  for(int i = 0; i < m.rows(); ++i)
+  for(Index i = 0; i < m.rows(); ++i)
   {
     if (i)
       s << fmt.rowSpacer;
     s << fmt.rowPrefix;
     if(width) s.width(width);
     s << m.coeff(i, 0);
-    for(int j = 1; j < m.cols(); ++j)
+    for(Index j = 1; j < m.cols(); ++j)
     {
       s << fmt.coeffSeparator;
       if (width) s.width(width);
diff --git a/Eigen/src/Core/Map.h b/Eigen/src/Core/Map.h
index a22779b..6ca24b7 100644
--- a/Eigen/src/Core/Map.h
+++ b/Eigen/src/Core/Map.h
@@ -109,12 +109,12 @@
 
     EIGEN_DENSE_PUBLIC_INTERFACE(Map)
 
-    inline int innerStride() const
+    inline Index innerStride() const
     {
       return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1;
     }
 
-    inline int outerStride() const
+    inline Index outerStride() const
     {
       return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer()
            : IsVectorAtCompileTime ? this->size()
@@ -139,7 +139,7 @@
       * \param size the size of the vector expression
       * \param stride optional Stride object, passing the strides.
       */
-    inline Map(const Scalar* data, int size, const StrideType& stride = StrideType())
+    inline Map(const Scalar* data, Index size, const StrideType& stride = StrideType())
       : Base(data, size), m_stride(stride)
     {
       PlainObjectType::Base::_check_template_params();
@@ -152,7 +152,7 @@
       * \param cols the number of columns of the matrix expression
       * \param stride optional Stride object, passing the strides.
       */
-    inline Map(const Scalar* data, int rows, int cols, const StrideType& stride = StrideType())
+    inline Map(const Scalar* data, Index rows, Index cols, const StrideType& stride = StrideType())
       : Base(data, rows, cols), m_stride(stride)
     {
       PlainObjectType::Base::_check_template_params();
diff --git a/Eigen/src/Core/MapBase.h b/Eigen/src/Core/MapBase.h
index 08b81c1..8cdd452 100644
--- a/Eigen/src/Core/MapBase.h
+++ b/Eigen/src/Core/MapBase.h
@@ -44,8 +44,13 @@
       SizeAtCompileTime = Base::SizeAtCompileTime
     };
 
+
+    typedef typename ei_traits<Derived>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
     typedef typename ei_traits<Derived>::Scalar Scalar;
-    typedef typename Base::PacketScalar PacketScalar;
+    typedef typename ei_packet_traits<Scalar>::type PacketScalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
     using Base::derived;
 //    using Base::RowsAtCompileTime;
 //    using Base::ColsAtCompileTime;
@@ -82,8 +87,8 @@
 
     typedef typename Base::CoeffReturnType CoeffReturnType;
 
-    inline int rows() const { return m_rows.value(); }
-    inline int cols() const { return m_cols.value(); }
+    inline Index rows() const { return m_rows.value(); }
+    inline Index cols() const { return m_cols.value(); }
 
     /** Returns a pointer to the first coefficient of the matrix or vector.
       *
@@ -93,50 +98,50 @@
       */
     inline const Scalar* data() const { return m_data; }
 
-    inline const Scalar& coeff(int row, int col) const
+    inline const Scalar& coeff(Index row, Index col) const
     {
       return m_data[col * colStride() + row * rowStride()];
     }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return const_cast<Scalar*>(m_data)[col * colStride() + row * rowStride()];
     }
 
-    inline const Scalar& coeff(int index) const
+    inline const Scalar& coeff(Index index) const
     {
       ei_assert(Derived::IsVectorAtCompileTime || (ei_traits<Derived>::Flags & LinearAccessBit));
       return m_data[index * innerStride()];
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       ei_assert(Derived::IsVectorAtCompileTime || (ei_traits<Derived>::Flags & LinearAccessBit));
       return const_cast<Scalar*>(m_data)[index * innerStride()];
     }
 
     template<int LoadMode>
-    inline PacketScalar packet(int row, int col) const
+    inline PacketScalar packet(Index row, Index col) const
     {
       return ei_ploadt<Scalar, LoadMode>
                (m_data + (col * colStride() + row * rowStride()));
     }
 
     template<int LoadMode>
-    inline PacketScalar packet(int index) const
+    inline PacketScalar packet(Index index) const
     {
       return ei_ploadt<Scalar, LoadMode>(m_data + index * innerStride());
     }
 
     template<int StoreMode>
-    inline void writePacket(int row, int col, const PacketScalar& x)
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
     {
       ei_pstoret<Scalar, PacketScalar, StoreMode>
                (const_cast<Scalar*>(m_data) + (col * colStride() + row * rowStride()), x);
     }
 
     template<int StoreMode>
-    inline void writePacket(int index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& x)
     {
       ei_pstoret<Scalar, PacketScalar, StoreMode>
         (const_cast<Scalar*>(m_data) + index * innerStride(), x);
@@ -148,10 +153,10 @@
       checkSanity();
     }
 
-    inline MapBase(const Scalar* data, int size)
+    inline MapBase(const Scalar* data, Index size)
             : m_data(data),
-              m_rows(RowsAtCompileTime == Dynamic ? size : RowsAtCompileTime),
-              m_cols(ColsAtCompileTime == Dynamic ? size : ColsAtCompileTime)
+              m_rows(RowsAtCompileTime == Dynamic ? size : Index(RowsAtCompileTime)),
+              m_cols(ColsAtCompileTime == Dynamic ? size : Index(ColsAtCompileTime))
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
       ei_assert(size >= 0);
@@ -159,7 +164,7 @@
       checkSanity();
     }
 
-    inline MapBase(const Scalar* data, int rows, int cols)
+    inline MapBase(const Scalar* data, Index rows, Index cols)
             : m_data(data), m_rows(rows), m_cols(cols)
     {
       ei_assert( (data == 0)
@@ -187,8 +192,8 @@
     }
 
     const Scalar* EIGEN_RESTRICT m_data;
-    const ei_int_if_dynamic<RowsAtCompileTime> m_rows;
-    const ei_int_if_dynamic<ColsAtCompileTime> m_cols;
+    const ei_variable_if_dynamic<Index, RowsAtCompileTime> m_rows;
+    const ei_variable_if_dynamic<Index, ColsAtCompileTime> m_cols;
 };
 
 #endif // EIGEN_MAPBASE_H
diff --git a/Eigen/src/Core/MathFunctions.h b/Eigen/src/Core/MathFunctions.h
index cc77799..53e5762 100644
--- a/Eigen/src/Core/MathFunctions.h
+++ b/Eigen/src/Core/MathFunctions.h
@@ -657,7 +657,7 @@
 {
   static inline Scalar run(Scalar x, Scalar y)
   {
-    int res = 1;
+    Scalar res = 1;
     ei_assert(!NumTraits<Scalar>::IsSigned || y >= 0);
     if(y & 1) res *= x;
     y >>= 1;
diff --git a/Eigen/src/Core/Matrix.h b/Eigen/src/Core/Matrix.h
index c61a3f3..4407b0d 100644
--- a/Eigen/src/Core/Matrix.h
+++ b/Eigen/src/Core/Matrix.h
@@ -206,7 +206,7 @@
       * is called a null matrix. This constructor is the unique way to create null matrices: resizing
       * a matrix to 0 is not supported.
       *
-      * \sa resize(int,int)
+      * \sa resize(Index,Index)
       */
     EIGEN_STRONG_INLINE explicit Matrix() : Base()
     {
@@ -225,7 +225,7 @@
       * it is redundant to pass the dimension here, so it makes more sense to use the default
       * constructor Matrix() instead.
       */
-    EIGEN_STRONG_INLINE explicit Matrix(int dim)
+    EIGEN_STRONG_INLINE explicit Matrix(Index dim)
       : Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
     {
       Base::_check_template_params();
@@ -248,7 +248,7 @@
       * This is useful for dynamic-size matrices. For fixed-size matrices,
       * it is redundant to pass these parameters, so one should use the default constructor
       * Matrix() instead. */
-    Matrix(int rows, int cols);
+    Matrix(Index rows, Index cols);
     /** \brief Constructs an initialized 2D vector with given coefficients */
     Matrix(const Scalar& x, const Scalar& y);
     #endif
@@ -321,8 +321,8 @@
     void swap(MatrixBase<OtherDerived> EIGEN_REF_TO_TEMPORARY other)
     { this->_swap(other.derived()); }
 
-    inline int innerStride() const { return 1; }
-    inline int outerStride() const { return this->innerSize(); }
+    inline Index innerStride() const { return 1; }
+    inline Index outerStride() const { return this->innerSize(); }
 
     /////////// Geometry module ///////////
 
diff --git a/Eigen/src/Core/MatrixBase.h b/Eigen/src/Core/MatrixBase.h
index 9e2afe7..633b010 100644
--- a/Eigen/src/Core/MatrixBase.h
+++ b/Eigen/src/Core/MatrixBase.h
@@ -56,14 +56,14 @@
 {
   public:
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** The base class for a given storage type. */
     typedef MatrixBase StorageBaseType;
-
+    typedef typename ei_traits<Derived>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
     typedef typename ei_traits<Derived>::Scalar Scalar;
     typedef typename ei_packet_traits<Scalar>::type PacketScalar;
-
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+  
     typedef DenseBase<Derived> Base;
-
     using Base::RowsAtCompileTime;
     using Base::ColsAtCompileTime;
     using Base::SizeAtCompileTime;
@@ -97,14 +97,6 @@
 
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-    /** This is the "real scalar" type; if the \a Scalar type is already real numbers
-      * (e.g. int, float or double) then \a RealScalar is just the same as \a Scalar. If
-      * \a Scalar is \a std::complex<T> then RealScalar is \a T.
-      *
-      * \sa class NumTraits
-      */
-    typedef typename NumTraits<Scalar>::Real RealScalar;
-
     /** type of the equivalent square matrix */
     typedef Matrix<Scalar,EIGEN_ENUM_MAX(RowsAtCompileTime,ColsAtCompileTime),
                           EIGEN_ENUM_MAX(RowsAtCompileTime,ColsAtCompileTime)> SquareMatrixType;
@@ -112,7 +104,7 @@
 
     /** \returns the size of the main diagonal, which is min(rows(),cols()).
       * \sa rows(), cols(), SizeAtCompileTime. */
-    inline int diagonalSize() const { return std::min(rows(),cols()); }
+    inline Index diagonalSize() const { return std::min(rows(),cols()); }
 
     /** \brief The plain matrix type corresponding to this expression.
       *
@@ -211,8 +203,8 @@
     template<int Index> Diagonal<Derived,Index> diagonal();
     template<int Index> const Diagonal<Derived,Index> diagonal() const;
 
-    Diagonal<Derived, Dynamic> diagonal(int index);
-    const Diagonal<Derived, Dynamic> diagonal(int index) const;
+    Diagonal<Derived, Dynamic> diagonal(Index index);
+    const Diagonal<Derived, Dynamic> diagonal(Index index) const;
 
     template<unsigned int Mode> TriangularView<Derived, Mode> part();
     template<unsigned int Mode> const TriangularView<Derived, Mode> part() const;
@@ -224,9 +216,9 @@
     template<unsigned int UpLo> const SelfAdjointView<Derived, UpLo> selfadjointView() const;
 
     static const IdentityReturnType Identity();
-    static const IdentityReturnType Identity(int rows, int cols);
-    static const BasisReturnType Unit(int size, int i);
-    static const BasisReturnType Unit(int i);
+    static const IdentityReturnType Identity(Index rows, Index cols);
+    static const BasisReturnType Unit(Index size, Index i);
+    static const BasisReturnType Unit(Index i);
     static const BasisReturnType UnitX();
     static const BasisReturnType UnitY();
     static const BasisReturnType UnitZ();
@@ -235,7 +227,7 @@
     const DiagonalWrapper<Derived> asDiagonal() const;
 
     Derived& setIdentity();
-    Derived& setIdentity(int rows, int cols);
+    Derived& setIdentity(Index rows, Index cols);
 
     bool isIdentity(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
     bool isDiagonal(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
@@ -329,7 +321,7 @@
     template<typename OtherDerived>
     PlainObject cross3(const MatrixBase<OtherDerived>& other) const;
     PlainObject unitOrthogonal(void) const;
-    Matrix<Scalar,3,1> eulerAngles(int a0, int a1, int a2) const;
+    Matrix<Scalar,3,1> eulerAngles(Index a0, Index a1, Index a2) const;
     const ScalarMultipleReturnType operator*(const UniformScaling<Scalar>& s) const;
     enum {
       SizeMinusOne = SizeAtCompileTime==Dynamic ? Dynamic : SizeAtCompileTime-1
@@ -362,9 +354,9 @@
 ///////// Jacobi module /////////
 
     template<typename OtherScalar>
-    void applyOnTheLeft(int p, int q, const PlanarRotation<OtherScalar>& j);
+    void applyOnTheLeft(Index p, Index q, const PlanarRotation<OtherScalar>& j);
     template<typename OtherScalar>
-    void applyOnTheRight(int p, int q, const PlanarRotation<OtherScalar>& j);
+    void applyOnTheRight(Index p, Index q, const PlanarRotation<OtherScalar>& j);
 
 ///////// MatrixFunctions module /////////
 
@@ -398,17 +390,17 @@
     inline const Cwise<Derived> cwise() const;
     inline Cwise<Derived> cwise();
 
-    VectorBlock<Derived> start(int size);
-    const VectorBlock<Derived> start(int size) const;
-    VectorBlock<Derived> end(int size);
-    const VectorBlock<Derived> end(int size) const;
+    VectorBlock<Derived> start(Index size);
+    const VectorBlock<Derived> start(Index size) const;
+    VectorBlock<Derived> end(Index size);
+    const VectorBlock<Derived> end(Index size) const;
     template<int Size> VectorBlock<Derived,Size> start();
     template<int Size> const VectorBlock<Derived,Size> start() const;
     template<int Size> VectorBlock<Derived,Size> end();
     template<int Size> const VectorBlock<Derived,Size> end() const;
 
-    Minor<Derived> minor(int row, int col);
-    const Minor<Derived> minor(int row, int col) const;
+    Minor<Derived> minor(Index row, Index col);
+    const Minor<Derived> minor(Index row, Index col) const;
 #endif
 
   protected:
diff --git a/Eigen/src/Core/MatrixStorage.h b/Eigen/src/Core/MatrixStorage.h
index f1b92ae..aff83a6 100644
--- a/Eigen/src/Core/MatrixStorage.h
+++ b/Eigen/src/Core/MatrixStorage.h
@@ -97,12 +97,12 @@
     inline explicit ei_matrix_storage() {}
     inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert)
       : m_data(ei_constructor_without_unaligned_array_assert()) {}
-    inline ei_matrix_storage(int,int,int) {}
+    inline ei_matrix_storage(DenseIndex,DenseIndex,DenseIndex) {}
     inline void swap(ei_matrix_storage& other) { std::swap(m_data,other.m_data); }
-    inline static int rows(void) {return _Rows;}
-    inline static int cols(void) {return _Cols;}
-    inline void conservativeResize(int,int,int) {}
-    inline void resize(int,int,int) {}
+    inline static DenseIndex rows(void) {return _Rows;}
+    inline static DenseIndex cols(void) {return _Cols;}
+    inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
+    inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
     inline const T *data() const { return m_data.array; }
     inline T *data() { return m_data.array; }
 };
@@ -113,12 +113,12 @@
   public:
     inline explicit ei_matrix_storage() {}
     inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert) {}
-    inline ei_matrix_storage(int,int,int) {}
+    inline ei_matrix_storage(DenseIndex,DenseIndex,DenseIndex) {}
     inline void swap(ei_matrix_storage& ) {}
-    inline static int rows(void) {return _Rows;}
-    inline static int cols(void) {return _Cols;}
-    inline void conservativeResize(int,int,int) {}
-    inline void resize(int,int,int) {}
+    inline static DenseIndex rows(void) {return _Rows;}
+    inline static DenseIndex cols(void) {return _Cols;}
+    inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
+    inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
     inline const T *data() const { return 0; }
     inline T *data() { return 0; }
 };
@@ -127,19 +127,19 @@
 template<typename T, int Size, int _Options> class ei_matrix_storage<T, Size, Dynamic, Dynamic, _Options>
 {
     ei_matrix_array<T,Size,_Options> m_data;
-    int m_rows;
-    int m_cols;
+    DenseIndex m_rows;
+    DenseIndex m_cols;
   public:
     inline explicit ei_matrix_storage() : m_rows(0), m_cols(0) {}
     inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert)
       : m_data(ei_constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
-    inline ei_matrix_storage(int, int rows, int cols) : m_rows(rows), m_cols(cols) {}
+    inline ei_matrix_storage(DenseIndex, DenseIndex rows, DenseIndex cols) : m_rows(rows), m_cols(cols) {}
     inline void swap(ei_matrix_storage& other)
     { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
-    inline int rows(void) const {return m_rows;}
-    inline int cols(void) const {return m_cols;}
-    inline void conservativeResize(int, int rows, int cols) { m_rows = rows; m_cols = cols; }
-    inline void resize(int, int rows, int cols) { m_rows = rows; m_cols = cols; }
+    inline DenseIndex rows(void) const {return m_rows;}
+    inline DenseIndex cols(void) const {return m_cols;}
+    inline void conservativeResize(DenseIndex, DenseIndex rows, DenseIndex cols) { m_rows = rows; m_cols = cols; }
+    inline void resize(DenseIndex, DenseIndex rows, DenseIndex cols) { m_rows = rows; m_cols = cols; }
     inline const T *data() const { return m_data.array; }
     inline T *data() { return m_data.array; }
 };
@@ -148,17 +148,17 @@
 template<typename T, int Size, int _Cols, int _Options> class ei_matrix_storage<T, Size, Dynamic, _Cols, _Options>
 {
     ei_matrix_array<T,Size,_Options> m_data;
-    int m_rows;
+    DenseIndex m_rows;
   public:
     inline explicit ei_matrix_storage() : m_rows(0) {}
     inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert)
       : m_data(ei_constructor_without_unaligned_array_assert()), m_rows(0) {}
-    inline ei_matrix_storage(int, int rows, int) : m_rows(rows) {}
+    inline ei_matrix_storage(DenseIndex, DenseIndex rows, DenseIndex) : m_rows(rows) {}
     inline void swap(ei_matrix_storage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
-    inline int rows(void) const {return m_rows;}
-    inline int cols(void) const {return _Cols;}
-    inline void conservativeResize(int, int rows, int) { m_rows = rows; }
-    inline void resize(int, int rows, int) { m_rows = rows; }
+    inline DenseIndex rows(void) const {return m_rows;}
+    inline DenseIndex cols(void) const {return _Cols;}
+    inline void conservativeResize(DenseIndex, DenseIndex rows, DenseIndex) { m_rows = rows; }
+    inline void resize(DenseIndex, DenseIndex rows, DenseIndex) { m_rows = rows; }
     inline const T *data() const { return m_data.array; }
     inline T *data() { return m_data.array; }
 };
@@ -167,17 +167,17 @@
 template<typename T, int Size, int _Rows, int _Options> class ei_matrix_storage<T, Size, _Rows, Dynamic, _Options>
 {
     ei_matrix_array<T,Size,_Options> m_data;
-    int m_cols;
+    DenseIndex m_cols;
   public:
     inline explicit ei_matrix_storage() : m_cols(0) {}
     inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert)
       : m_data(ei_constructor_without_unaligned_array_assert()), m_cols(0) {}
-    inline ei_matrix_storage(int, int, int cols) : m_cols(cols) {}
+    inline ei_matrix_storage(DenseIndex, DenseIndex, DenseIndex cols) : m_cols(cols) {}
     inline void swap(ei_matrix_storage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
-    inline int rows(void) const {return _Rows;}
-    inline int cols(void) const {return m_cols;}
-    inline void conservativeResize(int, int, int cols) { m_cols = cols; }
-    inline void resize(int, int, int cols) { m_cols = cols; }
+    inline DenseIndex rows(void) const {return _Rows;}
+    inline DenseIndex cols(void) const {return m_cols;}
+    inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex cols) { m_cols = cols; }
+    inline void resize(DenseIndex, DenseIndex, DenseIndex cols) { m_cols = cols; }
     inline const T *data() const { return m_data.array; }
     inline T *data() { return m_data.array; }
 };
@@ -186,27 +186,27 @@
 template<typename T, int _Options> class ei_matrix_storage<T, Dynamic, Dynamic, Dynamic, _Options>
 {
     T *m_data;
-    int m_rows;
-    int m_cols;
+    DenseIndex m_rows;
+    DenseIndex m_cols;
   public:
     inline explicit ei_matrix_storage() : m_data(0), m_rows(0), m_cols(0) {}
     inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert)
        : m_data(0), m_rows(0), m_cols(0) {}
-    inline ei_matrix_storage(int size, int rows, int cols)
+    inline ei_matrix_storage(DenseIndex size, DenseIndex rows, DenseIndex cols)
       : m_data(ei_conditional_aligned_new<T,(_Options&DontAlign)==0>(size)), m_rows(rows), m_cols(cols) 
     { EIGEN_INT_DEBUG_MATRIX_CTOR }
     inline ~ei_matrix_storage() { ei_conditional_aligned_delete<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
     inline void swap(ei_matrix_storage& other)
     { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
-    inline int rows(void) const {return m_rows;}
-    inline int cols(void) const {return m_cols;}
-    inline void conservativeResize(int size, int rows, int cols)
+    inline DenseIndex rows(void) const {return m_rows;}
+    inline DenseIndex cols(void) const {return m_cols;}
+    inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex cols)
     {
       m_data = ei_conditional_aligned_realloc_new<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
       m_rows = rows;
       m_cols = cols;
     }
-    void resize(int size, int rows, int cols)
+    void resize(DenseIndex size, DenseIndex rows, DenseIndex cols)
     {
       if(size != m_rows*m_cols)
       {
@@ -228,22 +228,22 @@
 template<typename T, int _Rows, int _Options> class ei_matrix_storage<T, Dynamic, _Rows, Dynamic, _Options>
 {
     T *m_data;
-    int m_cols;
+    DenseIndex m_cols;
   public:
     inline explicit ei_matrix_storage() : m_data(0), m_cols(0) {}
     inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
-    inline ei_matrix_storage(int size, int, int cols) : m_data(ei_conditional_aligned_new<T,(_Options&DontAlign)==0>(size)), m_cols(cols) 
+    inline ei_matrix_storage(DenseIndex size, DenseIndex, DenseIndex cols) : m_data(ei_conditional_aligned_new<T,(_Options&DontAlign)==0>(size)), m_cols(cols)
     { EIGEN_INT_DEBUG_MATRIX_CTOR }
     inline ~ei_matrix_storage() { ei_conditional_aligned_delete<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
     inline void swap(ei_matrix_storage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
-    inline static int rows(void) {return _Rows;}
-    inline int cols(void) const {return m_cols;}
-    inline void conservativeResize(int size, int, int cols)
+    inline static DenseIndex rows(void) {return _Rows;}
+    inline DenseIndex cols(void) const {return m_cols;}
+    inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex cols)
     {
       m_data = ei_conditional_aligned_realloc_new<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
       m_cols = cols;
     }
-    void resize(int size, int, int cols)
+    void resize(DenseIndex size, DenseIndex, DenseIndex cols)
     {
       if(size != _Rows*m_cols)
       {
@@ -264,22 +264,22 @@
 template<typename T, int _Cols, int _Options> class ei_matrix_storage<T, Dynamic, Dynamic, _Cols, _Options>
 {
     T *m_data;
-    int m_rows;
+    DenseIndex m_rows;
   public:
     inline explicit ei_matrix_storage() : m_data(0), m_rows(0) {}
     inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
-    inline ei_matrix_storage(int size, int rows, int) : m_data(ei_conditional_aligned_new<T,(_Options&DontAlign)==0>(size)), m_rows(rows) 
+    inline ei_matrix_storage(DenseIndex size, DenseIndex rows, DenseIndex) : m_data(ei_conditional_aligned_new<T,(_Options&DontAlign)==0>(size)), m_rows(rows)
     { EIGEN_INT_DEBUG_MATRIX_CTOR }
     inline ~ei_matrix_storage() { ei_conditional_aligned_delete<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
     inline void swap(ei_matrix_storage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
-    inline int rows(void) const {return m_rows;}
-    inline static int cols(void) {return _Cols;}
-    inline void conservativeResize(int size, int rows, int)
+    inline DenseIndex rows(void) const {return m_rows;}
+    inline static DenseIndex cols(void) {return _Cols;}
+    inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex)
     {
       m_data = ei_conditional_aligned_realloc_new<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
       m_rows = rows;
     }
-    void resize(int size, int rows, int)
+    void resize(DenseIndex size, DenseIndex rows, DenseIndex)
     {
       if(size != m_rows*_Cols)
       {
diff --git a/Eigen/src/Core/NestByValue.h b/Eigen/src/Core/NestByValue.h
index a8ca28e..ececf27 100644
--- a/Eigen/src/Core/NestByValue.h
+++ b/Eigen/src/Core/NestByValue.h
@@ -51,51 +51,51 @@
 
     inline NestByValue(const ExpressionType& matrix) : m_expression(matrix) {}
 
-    inline int rows() const { return m_expression.rows(); }
-    inline int cols() const { return m_expression.cols(); }
-    inline int outerStride() const { return m_expression.outerStride(); }
-    inline int innerStride() const { return m_expression.innerStride(); }
+    inline Index rows() const { return m_expression.rows(); }
+    inline Index cols() const { return m_expression.cols(); }
+    inline Index outerStride() const { return m_expression.outerStride(); }
+    inline Index innerStride() const { return m_expression.innerStride(); }
 
-    inline const CoeffReturnType coeff(int row, int col) const
+    inline const CoeffReturnType coeff(Index row, Index col) const
     {
       return m_expression.coeff(row, col);
     }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return m_expression.const_cast_derived().coeffRef(row, col);
     }
 
-    inline const CoeffReturnType coeff(int index) const
+    inline const CoeffReturnType coeff(Index index) const
     {
       return m_expression.coeff(index);
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       return m_expression.const_cast_derived().coeffRef(index);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int row, int col) const
+    inline const PacketScalar packet(Index row, Index col) const
     {
       return m_expression.template packet<LoadMode>(row, col);
     }
 
     template<int LoadMode>
-    inline void writePacket(int row, int col, const PacketScalar& x)
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
     {
       m_expression.const_cast_derived().template writePacket<LoadMode>(row, col, x);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int index) const
+    inline const PacketScalar packet(Index index) const
     {
       return m_expression.template packet<LoadMode>(index);
     }
 
     template<int LoadMode>
-    inline void writePacket(int index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& x)
     {
       m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
     }
diff --git a/Eigen/src/Core/Product.h b/Eigen/src/Core/Product.h
index 156f043..93e9787 100644
--- a/Eigen/src/Core/Product.h
+++ b/Eigen/src/Core/Product.h
@@ -216,10 +216,11 @@
 template<> struct ei_outer_product_selector<ColMajor> {
   template<typename ProductType, typename Dest>
   EIGEN_DONT_INLINE static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
+    typedef typename Dest::Index Index;
     // FIXME make sure lhs is sequentially stored
     // FIXME not very good if rhs is real and lhs complex while alpha is real too
-    const int cols = dest.cols();
-    for (int j=0; j<cols; ++j)
+    const Index cols = dest.cols();
+    for (Index j=0; j<cols; ++j)
       dest.col(j) += (alpha * prod.rhs().coeff(j)) * prod.lhs();
   }
 };
@@ -227,10 +228,11 @@
 template<> struct ei_outer_product_selector<RowMajor> {
   template<typename ProductType, typename Dest>
   EIGEN_DONT_INLINE static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
+    typedef typename Dest::Index Index;
     // FIXME make sure rhs is sequentially stored
     // FIXME not very good if lhs is real and rhs complex while alpha is real too
-    const int rows = dest.rows();
-    for (int i=0; i<rows; ++i)
+    const Index rows = dest.rows();
+    for (Index i=0; i<rows; ++i)
       dest.row(i) += (alpha * prod.lhs().coeff(i)) * prod.rhs();
   }
 };
@@ -383,9 +385,10 @@
   template<typename ProductType, typename Dest>
   static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
   {
+    typedef typename Dest::Index Index;
     // TODO makes sure dest is sequentially stored in memory, otherwise use a temp
-    const int size = prod.rhs().rows();
-    for(int k=0; k<size; ++k)
+    const Index size = prod.rhs().rows();
+    for(Index k=0; k<size; ++k)
       dest += (alpha*prod.rhs().coeff(k)) * prod.lhs().col(k);
   }
 };
@@ -395,9 +398,10 @@
   template<typename ProductType, typename Dest>
   static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
   {
+    typedef typename Dest::Index Index;
     // TODO makes sure rhs is sequentially stored in memory, otherwise use a temp
-    const int rows = prod.rows();
-    for(int i=0; i<rows; ++i)
+    const Index rows = prod.rows();
+    for(Index i=0; i<rows; ++i)
       dest.coeffRef(i) += alpha * (prod.lhs().row(i).cwiseProduct(prod.rhs().transpose())).sum();
   }
 };
diff --git a/Eigen/src/Core/ProductBase.h b/Eigen/src/Core/ProductBase.h
index 611ca27..36626f8 100644
--- a/Eigen/src/Core/ProductBase.h
+++ b/Eigen/src/Core/ProductBase.h
@@ -100,8 +100,8 @@
         && "if you wanted a coeff-wise or a dot product use the respective explicit functions");
     }
 
-    inline int rows() const { return m_lhs.rows(); }
-    inline int cols() const { return m_rhs.cols(); }
+    inline Index rows() const { return m_lhs.rows(); }
+    inline Index cols() const { return m_rhs.cols(); }
 
     template<typename Dest>
     inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst,Scalar(1)); }
@@ -133,7 +133,7 @@
     const Diagonal<FullyLazyCoeffBaseProductType,Index> diagonal() const
     { return FullyLazyCoeffBaseProductType(m_lhs, m_rhs); }
 
-    const Diagonal<FullyLazyCoeffBaseProductType,Dynamic> diagonal(int index) const
+    const Diagonal<FullyLazyCoeffBaseProductType,Dynamic> diagonal(Index index) const
     { return FullyLazyCoeffBaseProductType(m_lhs, m_rhs).diagonal(index); }
 
   protected:
@@ -146,10 +146,10 @@
   private:
 
     // discard coeff methods
-    void coeff(int,int) const;
-    void coeffRef(int,int);
-    void coeff(int) const;
-    void coeffRef(int);
+    void coeff(Index,Index) const;
+    void coeffRef(Index,Index);
+    void coeff(Index) const;
+    void coeffRef(Index);
 };
 
 // here we need to overload the nested rule for products
diff --git a/Eigen/src/Core/Redux.h b/Eigen/src/Core/Redux.h
index ef0f760..3fd5de7 100644
--- a/Eigen/src/Core/Redux.h
+++ b/Eigen/src/Core/Redux.h
@@ -176,15 +176,16 @@
 struct ei_redux_impl<Func, Derived, DefaultTraversal, NoUnrolling>
 {
   typedef typename Derived::Scalar Scalar;
+  typedef typename Derived::Index Index;
   static Scalar run(const Derived& mat, const Func& func)
   {
     ei_assert(mat.rows()>0 && mat.cols()>0 && "you are using a non initialized matrix");
     Scalar res;
     res = mat.coeffByOuterInner(0, 0);
-    for(int i = 1; i < mat.innerSize(); ++i)
+    for(Index i = 1; i < mat.innerSize(); ++i)
       res = func(res, mat.coeffByOuterInner(0, i));
-    for(int i = 1; i < mat.outerSize(); ++i)
-      for(int j = 0; j < mat.innerSize(); ++j)
+    for(Index i = 1; i < mat.outerSize(); ++i)
+      for(Index j = 0; j < mat.innerSize(); ++j)
         res = func(res, mat.coeffByOuterInner(i, j));
     return res;
   }
@@ -200,37 +201,38 @@
 {
   typedef typename Derived::Scalar Scalar;
   typedef typename ei_packet_traits<Scalar>::type PacketScalar;
+  typedef typename Derived::Index Index;
 
   static Scalar run(const Derived& mat, const Func& func)
   {
-    const int size = mat.size();
-    const int packetSize = ei_packet_traits<Scalar>::size;
-    const int alignedStart = ei_first_aligned(mat);
+    const Index size = mat.size();
+    const Index packetSize = ei_packet_traits<Scalar>::size;
+    const Index alignedStart = ei_first_aligned(mat);
     enum {
       alignment = (Derived::Flags & DirectAccessBit) || (Derived::Flags & AlignedBit)
                 ? Aligned : Unaligned
     };
-    const int alignedSize = ((size-alignedStart)/packetSize)*packetSize;
-    const int alignedEnd = alignedStart + alignedSize;
+    const Index alignedSize = ((size-alignedStart)/packetSize)*packetSize;
+    const Index alignedEnd = alignedStart + alignedSize;
     Scalar res;
     if(alignedSize)
     {
       PacketScalar packet_res = mat.template packet<alignment>(alignedStart);
-      for(int index = alignedStart + packetSize; index < alignedEnd; index += packetSize)
+      for(Index index = alignedStart + packetSize; index < alignedEnd; index += packetSize)
         packet_res = func.packetOp(packet_res, mat.template packet<alignment>(index));
       res = func.predux(packet_res);
 
-      for(int index = 0; index < alignedStart; ++index)
+      for(Index index = 0; index < alignedStart; ++index)
         res = func(res,mat.coeff(index));
 
-      for(int index = alignedEnd; index < size; ++index)
+      for(Index index = alignedEnd; index < size; ++index)
         res = func(res,mat.coeff(index));
     }
     else // too small to vectorize anything.
          // since this is dynamic-size hence inefficient anyway for such small sizes, don't try to optimize.
     {
       res = mat.coeff(0);
-      for(int index = 1; index < size; ++index)
+      for(Index index = 1; index < size; ++index)
         res = func(res,mat.coeff(index));
     }
 
@@ -243,26 +245,27 @@
 {
   typedef typename Derived::Scalar Scalar;
   typedef typename ei_packet_traits<Scalar>::type PacketScalar;
+  typedef typename Derived::Index Index;
 
   static Scalar run(const Derived& mat, const Func& func)
   {
-    const int innerSize = mat.innerSize();
-    const int outerSize = mat.outerSize();
+    const Index innerSize = mat.innerSize();
+    const Index outerSize = mat.outerSize();
     enum {
       packetSize = ei_packet_traits<Scalar>::size
     };
-    const int packetedInnerSize = ((innerSize)/packetSize)*packetSize;
+    const Index packetedInnerSize = ((innerSize)/packetSize)*packetSize;
     Scalar res;
     if(packetedInnerSize)
     {
       PacketScalar packet_res = mat.template packet<Unaligned>(0,0);
-      for(int j=0; j<outerSize; ++j)
-        for(int i=(j==0?packetSize:0); i<packetedInnerSize; i+=int(packetSize))
+      for(Index j=0; j<outerSize; ++j)
+        for(Index i=(j==0?packetSize:0); i<packetedInnerSize; i+=Index(packetSize))
           packet_res = func.packetOp(packet_res, mat.template packetByOuterInner<Unaligned>(j,i));
 
       res = func.predux(packet_res);
-      for(int j=0; j<outerSize; ++j)
-        for(int i=packetedInnerSize; i<innerSize; ++i)
+      for(Index j=0; j<outerSize; ++j)
+        for(Index i=packetedInnerSize; i<innerSize; ++i)
           res = func(res, mat.coeffByOuterInner(j,i));
     }
     else // too small to vectorize anything.
diff --git a/Eigen/src/Core/ReturnByValue.h b/Eigen/src/Core/ReturnByValue.h
index b2e581c..665d480 100644
--- a/Eigen/src/Core/ReturnByValue.h
+++ b/Eigen/src/Core/ReturnByValue.h
@@ -57,14 +57,15 @@
 {
   public:
     typedef typename ei_traits<Derived>::ReturnType ReturnType;
+
     typedef typename ei_dense_xpr_base<ReturnByValue>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(ReturnByValue)
 
     template<typename Dest>
     inline void evalTo(Dest& dst) const
     { static_cast<const Derived* const>(this)->evalTo(dst); }
-    inline int rows() const { return static_cast<const Derived* const>(this)->rows(); }
-    inline int cols() const { return static_cast<const Derived* const>(this)->cols(); }
+    inline Index rows() const { return static_cast<const Derived* const>(this)->rows(); }
+    inline Index cols() const { return static_cast<const Derived* const>(this)->cols(); }
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
 #define Unusable YOU_ARE_TRYING_TO_ACCESS_A_SINGLE_COEFFICIENT_IN_A_SPECIAL_EXPRESSION_WHERE_THAT_IS_NOT_ALLOWED_BECAUSE_THAT_WOULD_BE_INEFFICIENT
@@ -72,10 +73,10 @@
       Unusable(const Unusable&) {}
       Unusable& operator=(const Unusable&) {return *this;}
     };
-    const Unusable& coeff(int) const { return *reinterpret_cast<const Unusable*>(this); }
-    const Unusable& coeff(int,int) const { return *reinterpret_cast<const Unusable*>(this); }
-    Unusable& coeffRef(int) { return *reinterpret_cast<Unusable*>(this); }
-    Unusable& coeffRef(int,int) { return *reinterpret_cast<Unusable*>(this); }
+    const Unusable& coeff(Index) const { return *reinterpret_cast<const Unusable*>(this); }
+    const Unusable& coeff(Index,Index) const { return *reinterpret_cast<const Unusable*>(this); }
+    Unusable& coeffRef(Index) { return *reinterpret_cast<Unusable*>(this); }
+    Unusable& coeffRef(Index,Index) { return *reinterpret_cast<Unusable*>(this); }
 #endif
 };
 
diff --git a/Eigen/src/Core/SelfAdjointView.h b/Eigen/src/Core/SelfAdjointView.h
index 277108d..eed3f93 100644
--- a/Eigen/src/Core/SelfAdjointView.h
+++ b/Eigen/src/Core/SelfAdjointView.h
@@ -65,6 +65,8 @@
 
     typedef TriangularBase<SelfAdjointView> Base;
     typedef typename ei_traits<SelfAdjointView>::Scalar Scalar;
+    typedef typename MatrixType::Index Index;
+
     enum {
       Mode = ei_traits<SelfAdjointView>::Mode
     };
@@ -73,15 +75,15 @@
     inline SelfAdjointView(const MatrixType& matrix) : m_matrix(matrix)
     { ei_assert(ei_are_flags_consistent<Mode>::ret); }
 
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
-    inline int outerStride() const { return m_matrix.outerStride(); }
-    inline int innerStride() const { return m_matrix.innerStride(); }
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
+    inline Index outerStride() const { return m_matrix.outerStride(); }
+    inline Index innerStride() const { return m_matrix.innerStride(); }
 
     /** \sa MatrixBase::coeff()
       * \warning the coordinates must fit into the referenced triangular part
       */
-    inline Scalar coeff(int row, int col) const
+    inline Scalar coeff(Index row, Index col) const
     {
       Base::check_coordinates_internal(row, col);
       return m_matrix.coeff(row, col);
@@ -90,7 +92,7 @@
     /** \sa MatrixBase::coeffRef()
       * \warning the coordinates must fit into the referenced triangular part
       */
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       Base::check_coordinates_internal(row, col);
       return m_matrix.const_cast_derived().coeffRef(row, col);
@@ -230,11 +232,12 @@
 template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct ei_triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Upper, Dynamic, ClearOpposite>
 {
+  typedef typename Derived1::Index Index;
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    for(int j = 0; j < dst.cols(); ++j)
+    for(Index j = 0; j < dst.cols(); ++j)
     {
-      for(int i = 0; i < j; ++i)
+      for(Index i = 0; i < j; ++i)
       {
         dst.copyCoeff(i, j, src);
         dst.coeffRef(j,i) = ei_conj(dst.coeff(i,j));
@@ -249,9 +252,10 @@
 {
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    for(int i = 0; i < dst.rows(); ++i)
+  typedef typename Derived1::Index Index;
+    for(Index i = 0; i < dst.rows(); ++i)
     {
-      for(int j = 0; j < i; ++j)
+      for(Index j = 0; j < i; ++j)
       {
         dst.copyCoeff(i, j, src);
         dst.coeffRef(j,i) = ei_conj(dst.coeff(i,j));
diff --git a/Eigen/src/Core/SelfCwiseBinaryOp.h b/Eigen/src/Core/SelfCwiseBinaryOp.h
index f8f8a9f..4a85e11 100644
--- a/Eigen/src/Core/SelfCwiseBinaryOp.h
+++ b/Eigen/src/Core/SelfCwiseBinaryOp.h
@@ -55,28 +55,28 @@
 
     inline SelfCwiseBinaryOp(MatrixType& xpr, const BinaryOp& func = BinaryOp()) : m_matrix(xpr), m_functor(func) {}
 
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
-    inline int outerStride() const { return m_matrix.outerStride(); }
-    inline int innerStride() const { return m_matrix.innerStride(); }
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
+    inline Index outerStride() const { return m_matrix.outerStride(); }
+    inline Index innerStride() const { return m_matrix.innerStride(); }
     inline const Scalar* data() const { return m_matrix.data(); }
 
     // note that this function is needed by assign to correctly align loads/stores
     // TODO make Assign use .data()
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return m_matrix.const_cast_derived().coeffRef(row, col);
     }
 
     // note that this function is needed by assign to correctly align loads/stores
     // TODO make Assign use .data()
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       return m_matrix.const_cast_derived().coeffRef(index);
     }
 
     template<typename OtherDerived>
-    void copyCoeff(int row, int col, const DenseBase<OtherDerived>& other)
+    void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
     {
       OtherDerived& _other = other.const_cast_derived();
       ei_internal_assert(row >= 0 && row < rows()
@@ -86,7 +86,7 @@
     }
 
     template<typename OtherDerived>
-    void copyCoeff(int index, const DenseBase<OtherDerived>& other)
+    void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
     {
       OtherDerived& _other = other.const_cast_derived();
       ei_internal_assert(index >= 0 && index < m_matrix.size());
@@ -95,7 +95,7 @@
     }
 
     template<typename OtherDerived, int StoreMode, int LoadMode>
-    void copyPacket(int row, int col, const DenseBase<OtherDerived>& other)
+    void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
     {
       OtherDerived& _other = other.const_cast_derived();
       ei_internal_assert(row >= 0 && row < rows()
@@ -105,7 +105,7 @@
     }
 
     template<typename OtherDerived, int StoreMode, int LoadMode>
-    void copyPacket(int index, const DenseBase<OtherDerived>& other)
+    void copyPacket(Index index, const DenseBase<OtherDerived>& other)
     {
       OtherDerived& _other = other.const_cast_derived();
       ei_internal_assert(index >= 0 && index < m_matrix.size());
diff --git a/Eigen/src/Core/SolveTriangular.h b/Eigen/src/Core/SolveTriangular.h
index f74c6ee..083c9ce 100644
--- a/Eigen/src/Core/SolveTriangular.h
+++ b/Eigen/src/Core/SolveTriangular.h
@@ -56,29 +56,30 @@
   typedef typename Rhs::Scalar Scalar;
   typedef ei_blas_traits<Lhs> LhsProductTraits;
   typedef typename LhsProductTraits::ExtractType ActualLhsType;
+  typedef typename Lhs::Index Index;
   enum {
     IsLower = ((Mode&Lower)==Lower)
   };
   static void run(const Lhs& lhs, Rhs& other)
   {
-    static const int PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
+    static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
     ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
 
-    const int size = lhs.cols();
-    for(int pi=IsLower ? 0 : size;
+    const Index size = lhs.cols();
+    for(Index pi=IsLower ? 0 : size;
         IsLower ? pi<size : pi>0;
         IsLower ? pi+=PanelWidth : pi-=PanelWidth)
     {
-      int actualPanelWidth = std::min(IsLower ? size - pi : pi, PanelWidth);
+      Index actualPanelWidth = std::min(IsLower ? size - pi : pi, PanelWidth);
 
-      int r = IsLower ? pi : size - pi; // remaining size
+      Index r = IsLower ? pi : size - pi; // remaining size
       if (r > 0)
       {
         // let's directly call the low level product function because:
         // 1 - it is faster to compile
         // 2 - it is slighlty faster at runtime
-        int startRow = IsLower ? pi : pi-actualPanelWidth;
-        int startCol = IsLower ? 0 : pi;
+        Index startRow = IsLower ? pi : pi-actualPanelWidth;
+        Index startCol = IsLower ? 0 : pi;
         VectorBlock<Rhs,Dynamic> target(other,startRow,actualPanelWidth);
 
         ei_cache_friendly_product_rowmajor_times_vector<LhsProductTraits::NeedToConjugate,false>(
@@ -87,10 +88,10 @@
           target, Scalar(-1));
       }
 
-      for(int k=0; k<actualPanelWidth; ++k)
+      for(Index k=0; k<actualPanelWidth; ++k)
       {
-        int i = IsLower ? pi+k : pi-k-1;
-        int s = IsLower ? pi : i+1;
+        Index i = IsLower ? pi+k : pi-k-1;
+        Index s = IsLower ? pi : i+1;
         if (k>0)
           other.coeffRef(i) -= (lhs.row(i).segment(s,k).transpose().cwiseProduct(other.segment(s,k))).sum();
 
@@ -109,6 +110,7 @@
   typedef typename ei_packet_traits<Scalar>::type Packet;
   typedef ei_blas_traits<Lhs> LhsProductTraits;
   typedef typename LhsProductTraits::ExtractType ActualLhsType;
+  typedef typename Lhs::Index Index;
   enum {
     PacketSize =  ei_packet_traits<Scalar>::size,
     IsLower = ((Mode&Lower)==Lower)
@@ -116,30 +118,30 @@
 
   static void run(const Lhs& lhs, Rhs& other)
   {
-    static const int PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
+    static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
     ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
 
-    const int size = lhs.cols();
-    for(int pi=IsLower ? 0 : size;
+    const Index size = lhs.cols();
+    for(Index pi=IsLower ? 0 : size;
         IsLower ? pi<size : pi>0;
         IsLower ? pi+=PanelWidth : pi-=PanelWidth)
     {
-      int actualPanelWidth = std::min(IsLower ? size - pi : pi, PanelWidth);
-      int startBlock = IsLower ? pi : pi-actualPanelWidth;
-      int endBlock = IsLower ? pi + actualPanelWidth : 0;
+      Index actualPanelWidth = std::min(IsLower ? size - pi : pi, PanelWidth);
+      Index startBlock = IsLower ? pi : pi-actualPanelWidth;
+      Index endBlock = IsLower ? pi + actualPanelWidth : 0;
 
-      for(int k=0; k<actualPanelWidth; ++k)
+      for(Index k=0; k<actualPanelWidth; ++k)
       {
-        int i = IsLower ? pi+k : pi-k-1;
+        Index i = IsLower ? pi+k : pi-k-1;
         if(!(Mode & UnitDiag))
           other.coeffRef(i) /= lhs.coeff(i,i);
 
-        int r = actualPanelWidth - k - 1; // remaining size
-        int s = IsLower ? i+1 : i-r;
+        Index r = actualPanelWidth - k - 1; // remaining size
+        Index s = IsLower ? i+1 : i-r;
         if (r>0)
           other.segment(s,r) -= other.coeffRef(i) * Block<Lhs,Dynamic,1>(lhs, s, i, r, 1);
       }
-      int r = IsLower ? size - endBlock : startBlock; // remaining size
+      Index r = IsLower ? size - endBlock : startBlock; // remaining size
       if (r > 0)
       {
         // let's directly call the low level product function because:
@@ -168,7 +170,7 @@
   }
 };
 
-template <typename Scalar, int Side, int Mode, bool Conjugate, int TriStorageOrder, int OtherStorageOrder>
+template <typename Scalar, typename Index, int Side, int Mode, bool Conjugate, int TriStorageOrder, int OtherStorageOrder>
 struct ei_triangular_solve_matrix;
 
 // the rhs is a matrix
@@ -176,12 +178,13 @@
 struct ei_triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,StorageOrder,Dynamic>
 {
   typedef typename Rhs::Scalar Scalar;
+  typedef typename Rhs::Index Index;
   typedef ei_blas_traits<Lhs> LhsProductTraits;
   typedef typename LhsProductTraits::DirectLinearAccessType ActualLhsType;
   static void run(const Lhs& lhs, Rhs& rhs)
   {
     const ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
-    ei_triangular_solve_matrix<Scalar,Side,Mode,LhsProductTraits::NeedToConjugate,StorageOrder,
+    ei_triangular_solve_matrix<Scalar,Index,Side,Mode,LhsProductTraits::NeedToConjugate,StorageOrder,
                                (Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor>
       ::run(lhs.rows(), Side==OnTheLeft? rhs.cols() : rhs.rows(), &actualLhs.coeff(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.outerStride());
   }
diff --git a/Eigen/src/Core/StableNorm.h b/Eigen/src/Core/StableNorm.h
index c2ce937..d2bed92 100644
--- a/Eigen/src/Core/StableNorm.h
+++ b/Eigen/src/Core/StableNorm.h
@@ -54,15 +54,15 @@
 inline typename NumTraits<typename ei_traits<Derived>::Scalar>::Real
 MatrixBase<Derived>::stableNorm() const
 {
-  const int blockSize = 4096;
+  const Index blockSize = 4096;
   RealScalar scale = 0;
   RealScalar invScale = 1;
   RealScalar ssq = 0; // sum of square
   enum {
     Alignment = (int(Flags)&DirectAccessBit) || (int(Flags)&AlignedBit) ? 1 : 0
   };
-  int n = size();
-  int bi = ei_first_aligned(derived());
+  Index n = size();
+  Index bi = ei_first_aligned(derived());
   if (bi>0)
     ei_stable_norm_kernel(this->head(bi), ssq, scale, invScale);
   for (; bi<n; bi+=blockSize)
@@ -83,11 +83,11 @@
 inline typename NumTraits<typename ei_traits<Derived>::Scalar>::Real
 MatrixBase<Derived>::blueNorm() const
 {
-  static int nmax = -1;
+  static Index nmax = -1;
   static RealScalar b1, b2, s1m, s2m, overfl, rbig, relerr;
   if(nmax <= 0)
   {
-    int nbig, ibeta, it, iemin, iemax, iexp;
+    Index nbig, ibeta, it, iemin, iemax, iexp;
     RealScalar abig, eps;
     // This program calculates the machine-dependent constants
     // bl, b2, slm, s2m, relerr overfl, nmax
@@ -97,7 +97,7 @@
     // For portability, the PORT subprograms "ilmaeh" and "rlmach"
     // are used. For any specific computer, each of the assignment
     // statements can be replaced
-    nbig  = std::numeric_limits<int>::max();            // largest integer
+    nbig  = std::numeric_limits<Index>::max();            // largest integer
     ibeta = std::numeric_limits<RealScalar>::radix;         // base for floating-point numbers
     it    = std::numeric_limits<RealScalar>::digits;        // number of base-beta digits in mantissa
     iemin = std::numeric_limits<RealScalar>::min_exponent;  // minimum exponent
@@ -121,12 +121,12 @@
     if (RealScalar(nbig)>abig)  nmax = int(abig);  // largest safe n
     else                        nmax = nbig;
   }
-  int n = size();
+  Index n = size();
   RealScalar ab2 = b2 / RealScalar(n);
   RealScalar asml = RealScalar(0);
   RealScalar amed = RealScalar(0);
   RealScalar abig = RealScalar(0);
-  for(int j=0; j<n; ++j)
+  for(Index j=0; j<n; ++j)
   {
     RealScalar ax = ei_abs(coeff(j));
     if(ax > ab2)     abig += ei_abs2(ax*s2m);
diff --git a/Eigen/src/Core/Stride.h b/Eigen/src/Core/Stride.h
index d960dd2..afae034 100644
--- a/Eigen/src/Core/Stride.h
+++ b/Eigen/src/Core/Stride.h
@@ -86,8 +86,8 @@
     inline int inner() const { return m_inner.value(); }
 
   protected:
-    ei_int_if_dynamic<OuterStrideAtCompileTime> m_outer;
-    ei_int_if_dynamic<InnerStrideAtCompileTime> m_inner;
+    ei_variable_if_dynamic<int, OuterStrideAtCompileTime> m_outer;
+    ei_variable_if_dynamic<int, InnerStrideAtCompileTime> m_inner;
 };
 
 /** \brief Convenience specialization of Stride to specify only an inner stride */
diff --git a/Eigen/src/Core/Swap.h b/Eigen/src/Core/Swap.h
index 02ff8ad..8e5994a 100644
--- a/Eigen/src/Core/Swap.h
+++ b/Eigen/src/Core/Swap.h
@@ -45,23 +45,23 @@
 
     inline SwapWrapper(ExpressionType& xpr) : m_expression(xpr) {}
 
-    inline int rows() const { return m_expression.rows(); }
-    inline int cols() const { return m_expression.cols(); }
-    inline int outerStride() const { return m_expression.outerStride(); }
-    inline int innerStride() const { return m_expression.innerStride(); }
+    inline Index rows() const { return m_expression.rows(); }
+    inline Index cols() const { return m_expression.cols(); }
+    inline Index outerStride() const { return m_expression.outerStride(); }
+    inline Index innerStride() const { return m_expression.innerStride(); }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return m_expression.const_cast_derived().coeffRef(row, col);
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       return m_expression.const_cast_derived().coeffRef(index);
     }
 
     template<typename OtherDerived>
-    void copyCoeff(int row, int col, const DenseBase<OtherDerived>& other)
+    void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
     {
       OtherDerived& _other = other.const_cast_derived();
       ei_internal_assert(row >= 0 && row < rows()
@@ -72,7 +72,7 @@
     }
 
     template<typename OtherDerived>
-    void copyCoeff(int index, const DenseBase<OtherDerived>& other)
+    void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
     {
       OtherDerived& _other = other.const_cast_derived();
       ei_internal_assert(index >= 0 && index < m_expression.size());
@@ -82,7 +82,7 @@
     }
 
     template<typename OtherDerived, int StoreMode, int LoadMode>
-    void copyPacket(int row, int col, const DenseBase<OtherDerived>& other)
+    void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
     {
       OtherDerived& _other = other.const_cast_derived();
       ei_internal_assert(row >= 0 && row < rows()
@@ -95,7 +95,7 @@
     }
 
     template<typename OtherDerived, int StoreMode, int LoadMode>
-    void copyPacket(int index, const DenseBase<OtherDerived>& other)
+    void copyPacket(Index index, const DenseBase<OtherDerived>& other)
     {
       OtherDerived& _other = other.const_cast_derived();
       ei_internal_assert(index >= 0 && index < m_expression.size());
diff --git a/Eigen/src/Core/Transpose.h b/Eigen/src/Core/Transpose.h
index 6cb8642..38d942e 100644
--- a/Eigen/src/Core/Transpose.h
+++ b/Eigen/src/Core/Transpose.h
@@ -72,8 +72,8 @@
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose)
 
-    inline int rows() const { return m_matrix.cols(); }
-    inline int cols() const { return m_matrix.rows(); }
+    inline Index rows() const { return m_matrix.cols(); }
+    inline Index cols() const { return m_matrix.rows(); }
 
     /** \returns the nested expression */
     const typename ei_cleantype<typename MatrixType::Nested>::type&
@@ -107,51 +107,51 @@
     typedef typename ei_TransposeImpl_base<MatrixType>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Transpose<MatrixType>)
 
-    inline int innerStride() const { return derived().nestedExpression().innerStride(); }
-    inline int outerStride() const { return derived().nestedExpression().outerStride(); }
+    inline Index innerStride() const { return derived().nestedExpression().innerStride(); }
+    inline Index outerStride() const { return derived().nestedExpression().outerStride(); }
     inline Scalar* data() { return derived().nestedExpression().data(); }
     inline const Scalar* data() const { return derived().nestedExpression().data(); }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return const_cast_derived().nestedExpression().coeffRef(col, row);
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     {
       return const_cast_derived().nestedExpression().coeffRef(index);
     }
 
-    inline const CoeffReturnType coeff(int row, int col) const
+    inline const CoeffReturnType coeff(Index row, Index col) const
     {
       return derived().nestedExpression().coeff(col, row);
     }
 
-    inline const CoeffReturnType coeff(int index) const
+    inline const CoeffReturnType coeff(Index index) const
     {
       return derived().nestedExpression().coeff(index);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int row, int col) const
+    inline const PacketScalar packet(Index row, Index col) const
     {
       return derived().nestedExpression().template packet<LoadMode>(col, row);
     }
 
     template<int LoadMode>
-    inline void writePacket(int row, int col, const PacketScalar& x)
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
     {
       const_cast_derived().nestedExpression().template writePacket<LoadMode>(col, row, x);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int index) const
+    inline const PacketScalar packet(Index index) const
     {
       return derived().nestedExpression().template packet<LoadMode>(index);
     }
 
     template<int LoadMode>
-    inline void writePacket(int index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& x)
     {
       const_cast_derived().nestedExpression().template writePacket<LoadMode>(index, x);
     }
diff --git a/Eigen/src/Core/TriangularMatrix.h b/Eigen/src/Core/TriangularMatrix.h
index 3eb52a5..47c11ce 100644
--- a/Eigen/src/Core/TriangularMatrix.h
+++ b/Eigen/src/Core/TriangularMatrix.h
@@ -45,31 +45,33 @@
       MaxColsAtCompileTime = ei_traits<Derived>::MaxColsAtCompileTime
     };
     typedef typename ei_traits<Derived>::Scalar Scalar;
+    typedef typename ei_traits<Derived>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
 
     inline TriangularBase() { ei_assert(!((Mode&UnitDiag) && (Mode&ZeroDiag))); }
 
-    inline int rows() const { return derived().rows(); }
-    inline int cols() const { return derived().cols(); }
-    inline int outerStride() const { return derived().outerStride(); }
-    inline int innerStride() const { return derived().innerStride(); }
+    inline Index rows() const { return derived().rows(); }
+    inline Index cols() const { return derived().cols(); }
+    inline Index outerStride() const { return derived().outerStride(); }
+    inline Index innerStride() const { return derived().innerStride(); }
 
-    inline Scalar coeff(int row, int col) const  { return derived().coeff(row,col); }
-    inline Scalar& coeffRef(int row, int col) { return derived().coeffRef(row,col); }
+    inline Scalar coeff(Index row, Index col) const  { return derived().coeff(row,col); }
+    inline Scalar& coeffRef(Index row, Index col) { return derived().coeffRef(row,col); }
 
     /** \see MatrixBase::copyCoeff(row,col)
       */
     template<typename Other>
-    EIGEN_STRONG_INLINE void copyCoeff(int row, int col, Other& other)
+    EIGEN_STRONG_INLINE void copyCoeff(Index row, Index col, Other& other)
     {
       derived().coeffRef(row, col) = other.coeff(row, col);
     }
 
-    inline Scalar operator()(int row, int col) const
+    inline Scalar operator()(Index row, Index col) const
     {
       check_coordinates(row, col);
       return coeff(row,col);
     }
-    inline Scalar& operator()(int row, int col)
+    inline Scalar& operator()(Index row, Index col)
     {
       check_coordinates(row, col);
       return coeffRef(row,col);
@@ -87,7 +89,7 @@
 
   protected:
 
-    void check_coordinates(int row, int col)
+    void check_coordinates(Index row, Index col)
     {
       EIGEN_ONLY_USED_FOR_DEBUG(row);
       EIGEN_ONLY_USED_FOR_DEBUG(col);
@@ -99,12 +101,12 @@
     }
 
     #ifdef EIGEN_INTERNAL_DEBUGGING
-    void check_coordinates_internal(int row, int col)
+    void check_coordinates_internal(Index row, Index col)
     {
       check_coordinates(row, col);
     }
     #else
-    void check_coordinates_internal(int , int ) {}
+    void check_coordinates_internal(Index , Index ) {}
     #endif
 
 };
@@ -156,6 +158,9 @@
     typedef typename ei_cleantype<MatrixTypeNested>::type _MatrixTypeNested;
     using TriangularBase<TriangularView<_MatrixType, _Mode> >::evalToLazy;
 
+    typedef typename ei_traits<TriangularView>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
+
     enum {
       Mode = _Mode,
       TransposeMode = (Mode & Upper ? Lower : 0)
@@ -167,10 +172,10 @@
     inline TriangularView(const MatrixType& matrix) : m_matrix(matrix)
     { ei_assert(ei_are_flags_consistent<Mode>::ret); }
 
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
-    inline int outerStride() const { return m_matrix.outerStride(); }
-    inline int innerStride() const { return m_matrix.innerStride(); }
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
+    inline Index outerStride() const { return m_matrix.outerStride(); }
+    inline Index innerStride() const { return m_matrix.innerStride(); }
 
     /** \sa MatrixBase::operator+=() */
     template<typename Other> TriangularView&  operator+=(const Other& other) { return *this = m_matrix + other; }
@@ -194,7 +199,7 @@
     /** \sa MatrixBase::coeff()
       * \warning the coordinates must fit into the referenced triangular part
       */
-    inline Scalar coeff(int row, int col) const
+    inline Scalar coeff(Index row, Index col) const
     {
       Base::check_coordinates_internal(row, col);
       return m_matrix.coeff(row, col);
@@ -203,7 +208,7 @@
     /** \sa MatrixBase::coeffRef()
       * \warning the coordinates must fit into the referenced triangular part
       */
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       Base::check_coordinates_internal(row, col);
       return m_matrix.const_cast_derived().coeffRef(row, col);
@@ -371,15 +376,16 @@
 template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct ei_triangular_assignment_selector<Derived1, Derived2, Upper, Dynamic, ClearOpposite>
 {
+  typedef typename Derived1::Index Index;
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    for(int j = 0; j < dst.cols(); ++j)
+    for(Index j = 0; j < dst.cols(); ++j)
     {
-      int maxi = std::min(j, dst.rows()-1);
-      for(int i = 0; i <= maxi; ++i)
+      Index maxi = std::min(j, dst.rows()-1);
+      for(Index i = 0; i <= maxi; ++i)
         dst.copyCoeff(i, j, src);
       if (ClearOpposite)
-        for(int i = maxi+1; i < dst.rows(); ++i)
+        for(Index i = maxi+1; i < dst.rows(); ++i)
           dst.coeffRef(i, j) = 0;
     }
   }
@@ -388,15 +394,16 @@
 template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct ei_triangular_assignment_selector<Derived1, Derived2, Lower, Dynamic, ClearOpposite>
 {
+  typedef typename Derived1::Index Index;
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    for(int j = 0; j < dst.cols(); ++j)
+    for(Index j = 0; j < dst.cols(); ++j)
     {
-      for(int i = j; i < dst.rows(); ++i)
+      for(Index i = j; i < dst.rows(); ++i)
         dst.copyCoeff(i, j, src);
-      int maxi = std::min(j, dst.rows());
+      Index maxi = std::min(j, dst.rows());
       if (ClearOpposite)
-        for(int i = 0; i < maxi; ++i)
+        for(Index i = 0; i < maxi; ++i)
           dst.coeffRef(i, j) = 0;
     }
   }
@@ -405,15 +412,16 @@
 template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct ei_triangular_assignment_selector<Derived1, Derived2, StrictlyUpper, Dynamic, ClearOpposite>
 {
+  typedef typename Derived1::Index Index;
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    for(int j = 0; j < dst.cols(); ++j)
+    for(Index j = 0; j < dst.cols(); ++j)
     {
-      int maxi = std::min(j, dst.rows());
-      for(int i = 0; i < maxi; ++i)
+      Index maxi = std::min(j, dst.rows());
+      for(Index i = 0; i < maxi; ++i)
         dst.copyCoeff(i, j, src);
       if (ClearOpposite)
-        for(int i = maxi; i < dst.rows(); ++i)
+        for(Index i = maxi; i < dst.rows(); ++i)
           dst.coeffRef(i, j) = 0;
     }
   }
@@ -422,15 +430,16 @@
 template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct ei_triangular_assignment_selector<Derived1, Derived2, StrictlyLower, Dynamic, ClearOpposite>
 {
+  typedef typename Derived1::Index Index;
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    for(int j = 0; j < dst.cols(); ++j)
+    for(Index j = 0; j < dst.cols(); ++j)
     {
-      for(int i = j+1; i < dst.rows(); ++i)
+      for(Index i = j+1; i < dst.rows(); ++i)
         dst.copyCoeff(i, j, src);
-      int maxi = std::min(j, dst.rows()-1);
+      Index maxi = std::min(j, dst.rows()-1);
       if (ClearOpposite)
-        for(int i = 0; i <= maxi; ++i)
+        for(Index i = 0; i <= maxi; ++i)
           dst.coeffRef(i, j) = 0;
     }
   }
@@ -439,16 +448,17 @@
 template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct ei_triangular_assignment_selector<Derived1, Derived2, UnitUpper, Dynamic, ClearOpposite>
 {
+  typedef typename Derived1::Index Index;
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    for(int j = 0; j < dst.cols(); ++j)
+    for(Index j = 0; j < dst.cols(); ++j)
     {
-      int maxi = std::min(j, dst.rows());
-      for(int i = 0; i < maxi; ++i)
+      Index maxi = std::min(j, dst.rows());
+      for(Index i = 0; i < maxi; ++i)
         dst.copyCoeff(i, j, src);
       if (ClearOpposite)
       {
-        for(int i = maxi+1; i < dst.rows(); ++i)
+        for(Index i = maxi+1; i < dst.rows(); ++i)
           dst.coeffRef(i, j) = 0;
       }
     }
@@ -458,16 +468,17 @@
 template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct ei_triangular_assignment_selector<Derived1, Derived2, UnitLower, Dynamic, ClearOpposite>
 {
+  typedef typename Derived1::Index Index;
   inline static void run(Derived1 &dst, const Derived2 &src)
   {
-    for(int j = 0; j < dst.cols(); ++j)
+    for(Index j = 0; j < dst.cols(); ++j)
     {
-      int maxi = std::min(j, dst.rows());
-      for(int i = maxi+1; i < dst.rows(); ++i)
+      Index maxi = std::min(j, dst.rows());
+      for(Index i = maxi+1; i < dst.rows(); ++i)
         dst.copyCoeff(i, j, src);
       if (ClearOpposite)
       {
-        for(int i = 0; i < maxi; ++i)
+        for(Index i = 0; i < maxi; ++i)
           dst.coeffRef(i, j) = 0;
       }
     }
@@ -638,18 +649,18 @@
 bool MatrixBase<Derived>::isUpperTriangular(RealScalar prec) const
 {
   RealScalar maxAbsOnUpperPart = static_cast<RealScalar>(-1);
-  for(int j = 0; j < cols(); ++j)
+  for(Index j = 0; j < cols(); ++j)
   {
-    int maxi = std::min(j, rows()-1);
-    for(int i = 0; i <= maxi; ++i)
+    Index maxi = std::min(j, rows()-1);
+    for(Index i = 0; i <= maxi; ++i)
     {
       RealScalar absValue = ei_abs(coeff(i,j));
       if(absValue > maxAbsOnUpperPart) maxAbsOnUpperPart = absValue;
     }
   }
   RealScalar threshold = maxAbsOnUpperPart * prec;
-  for(int j = 0; j < cols(); ++j)
-    for(int i = j+1; i < rows(); ++i)
+  for(Index j = 0; j < cols(); ++j)
+    for(Index i = j+1; i < rows(); ++i)
       if(ei_abs(coeff(i, j)) > threshold) return false;
   return true;
 }
@@ -663,17 +674,17 @@
 bool MatrixBase<Derived>::isLowerTriangular(RealScalar prec) const
 {
   RealScalar maxAbsOnLowerPart = static_cast<RealScalar>(-1);
-  for(int j = 0; j < cols(); ++j)
-    for(int i = j; i < rows(); ++i)
+  for(Index j = 0; j < cols(); ++j)
+    for(Index i = j; i < rows(); ++i)
     {
       RealScalar absValue = ei_abs(coeff(i,j));
       if(absValue > maxAbsOnLowerPart) maxAbsOnLowerPart = absValue;
     }
   RealScalar threshold = maxAbsOnLowerPart * prec;
-  for(int j = 1; j < cols(); ++j)
+  for(Index j = 1; j < cols(); ++j)
   {
-    int maxi = std::min(j, rows()-1);
-    for(int i = 0; i < maxi; ++i)
+    Index maxi = std::min(j, rows()-1);
+    for(Index i = 0; i < maxi; ++i)
       if(ei_abs(coeff(i, j)) > threshold) return false;
   }
   return true;
diff --git a/Eigen/src/Core/VectorBlock.h b/Eigen/src/Core/VectorBlock.h
index adb69b6..c3212b8 100644
--- a/Eigen/src/Core/VectorBlock.h
+++ b/Eigen/src/Core/VectorBlock.h
@@ -34,7 +34,7 @@
   * \param Size size of the sub-vector we are taking at compile time (optional)
   *
   * This class represents an expression of either a fixed-size or dynamic-size sub-vector.
-  * It is the return type of DenseBase::segment(int,int) and DenseBase::segment<int>(int) and
+  * It is the return type of DenseBase::segment(Index,Index) and DenseBase::segment<int>(Index) and
   * most of the time this is the only way it is used.
   *
   * However, if you want to directly maniputate sub-vector expressions,
@@ -53,7 +53,7 @@
   * \include class_FixedVectorBlock.cpp
   * Output: \verbinclude class_FixedVectorBlock.out
   *
-  * \sa class Block, DenseBase::segment(int,int,int,int), DenseBase::segment(int,int)
+  * \sa class Block, DenseBase::segment(Index,Index,Index,Index), DenseBase::segment(Index,Index)
   */
 template<typename VectorType, int Size>
 struct ei_traits<VectorBlock<VectorType, Size> >
@@ -81,7 +81,7 @@
 
     /** Dynamic-size constructor
       */
-    inline VectorBlock(const VectorType& vector, int start, int size)
+    inline VectorBlock(const VectorType& vector, Index start, Index size)
       : Base(vector,
              IsColVector ? start : 0, IsColVector ? 0 : start,
              IsColVector ? size  : 1, IsColVector ? 1 : size)
@@ -91,7 +91,7 @@
 
     /** Fixed-size constructor
       */
-    inline VectorBlock(const VectorType& vector, int start)
+    inline VectorBlock(const VectorType& vector, Index start)
       : Base(vector, IsColVector ? start : 0, IsColVector ? 0 : start)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorBlock);
@@ -113,20 +113,20 @@
   * when it is applied to a fixed-size vector, it inherits a fixed maximal size,
   * which means that evaluating it does not cause a dynamic memory allocation.
   *
-  * \sa class Block, segment(int)
+  * \sa class Block, segment(Index)
   */
 template<typename Derived>
 inline VectorBlock<Derived> DenseBase<Derived>
-  ::segment(int start, int size)
+  ::segment(Index start, Index size)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived>(derived(), start, size);
 }
 
-/** This is the const version of segment(int,int).*/
+/** This is the const version of segment(Index,Index).*/
 template<typename Derived>
 inline const VectorBlock<Derived>
-DenseBase<Derived>::segment(int start, int size) const
+DenseBase<Derived>::segment(Index start, Index size) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived>(derived(), start, size);
@@ -145,20 +145,20 @@
   * when it is applied to a fixed-size vector, it inherits a fixed maximal size,
   * which means that evaluating it does not cause a dynamic memory allocation.
   *
-  * \sa class Block, block(int,int)
+  * \sa class Block, block(Index,Index)
   */
 template<typename Derived>
 inline VectorBlock<Derived>
-DenseBase<Derived>::head(int size)
+DenseBase<Derived>::head(Index size)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived>(derived(), 0, size);
 }
 
-/** This is the const version of head(int).*/
+/** This is the const version of head(Index).*/
 template<typename Derived>
 inline const VectorBlock<Derived>
-DenseBase<Derived>::head(int size) const
+DenseBase<Derived>::head(Index size) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived>(derived(), 0, size);
@@ -177,20 +177,20 @@
   * when it is applied to a fixed-size vector, it inherits a fixed maximal size,
   * which means that evaluating it does not cause a dynamic memory allocation.
   *
-  * \sa class Block, block(int,int)
+  * \sa class Block, block(Index,Index)
   */
 template<typename Derived>
 inline VectorBlock<Derived>
-DenseBase<Derived>::tail(int size)
+DenseBase<Derived>::tail(Index size)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived>(derived(), this->size() - size, size);
 }
 
-/** This is the const version of tail(int).*/
+/** This is the const version of tail(Index).*/
 template<typename Derived>
 inline const VectorBlock<Derived>
-DenseBase<Derived>::tail(int size) const
+DenseBase<Derived>::tail(Index size) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived>(derived(), this->size() - size, size);
@@ -212,17 +212,17 @@
 template<typename Derived>
 template<int Size>
 inline VectorBlock<Derived,Size>
-DenseBase<Derived>::segment(int start)
+DenseBase<Derived>::segment(Index start)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived,Size>(derived(), start);
 }
 
-/** This is the const version of segment<int>(int).*/
+/** This is the const version of segment<int>(Index).*/
 template<typename Derived>
 template<int Size>
 inline const VectorBlock<Derived,Size>
-DenseBase<Derived>::segment(int start) const
+DenseBase<Derived>::segment(Index start) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived,Size>(derived(), start);
diff --git a/Eigen/src/Core/Visitor.h b/Eigen/src/Core/Visitor.h
index e6f02b7..2e96cfe 100644
--- a/Eigen/src/Core/Visitor.h
+++ b/Eigen/src/Core/Visitor.h
@@ -52,13 +52,14 @@
 template<typename Visitor, typename Derived>
 struct ei_visitor_impl<Visitor, Derived, Dynamic>
 {
+  typedef typename Derived::Index Index;
   inline static void run(const Derived& mat, Visitor& visitor)
   {
     visitor.init(mat.coeff(0,0), 0, 0);
-    for(int i = 1; i < mat.rows(); ++i)
+    for(Index i = 1; i < mat.rows(); ++i)
       visitor(mat.coeff(i, 0), i, 0);
-    for(int j = 1; j < mat.cols(); ++j)
-      for(int i = 0; i < mat.rows(); ++i)
+    for(Index j = 1; j < mat.cols(); ++j)
+      for(Index i = 0; i < mat.rows(); ++i)
         visitor(mat.coeff(i, j), i, j);
   }
 };
@@ -70,16 +71,16 @@
   * \code
   * struct MyVisitor {
   *   // called for the first coefficient
-  *   void init(const Scalar& value, int i, int j);
+  *   void init(const Scalar& value, Index i, Index j);
   *   // called for all other coefficients
-  *   void operator() (const Scalar& value, int i, int j);
+  *   void operator() (const Scalar& value, Index i, Index j);
   * };
   * \endcode
   *
   * \note compared to one or two \em for \em loops, visitors offer automatic
   * unrolling for small fixed size matrix.
   *
-  * \sa minCoeff(int*,int*), maxCoeff(int*,int*), DenseBase::redux()
+  * \sa minCoeff(Index*,Index*), maxCoeff(Index*,Index*), DenseBase::redux()
   */
 template<typename Derived>
 template<typename Visitor>
@@ -96,12 +97,14 @@
 /** \internal
   * \brief Base class to implement min and max visitors
   */
-template <typename Scalar>
+template <typename Derived>
 struct ei_coeff_visitor
 {
-  int row, col;
+  typedef typename Derived::Index Index;
+  typedef typename Derived::Scalar Scalar;
+  Index row, col;
   Scalar res;
-  inline void init(const Scalar& value, int i, int j)
+  inline void init(const Scalar& value, Index i, Index j)
   {
     res = value;
     row = i;
@@ -112,12 +115,14 @@
 /** \internal
   * \brief Visitor computing the min coefficient with its value and coordinates
   *
-  * \sa DenseBase::minCoeff(int*, int*)
+  * \sa DenseBase::minCoeff(Index*, Index*)
   */
-template <typename Scalar>
-struct ei_min_coeff_visitor : ei_coeff_visitor<Scalar>
+template <typename Derived>
+struct ei_min_coeff_visitor : ei_coeff_visitor<Derived>
 {
-  void operator() (const Scalar& value, int i, int j)
+  typedef typename Derived::Index Index;
+  typedef typename Derived::Scalar Scalar;
+  void operator() (const Scalar& value, Index i, Index j)
   {
     if(value < this->res)
     {
@@ -138,12 +143,14 @@
 /** \internal
   * \brief Visitor computing the max coefficient with its value and coordinates
   *
-  * \sa DenseBase::maxCoeff(int*, int*)
+  * \sa DenseBase::maxCoeff(Index*, Index*)
   */
-template <typename Scalar>
-struct ei_max_coeff_visitor : ei_coeff_visitor<Scalar>
+template <typename Derived>
+struct ei_max_coeff_visitor : ei_coeff_visitor<Derived>
 {
-  void operator() (const Scalar& value, int i, int j)
+  typedef typename Derived::Index Index;
+  typedef typename Derived::Scalar Scalar;
+  void operator() (const Scalar& value, Index i, Index j)
   {
     if(value > this->res)
     {
@@ -164,13 +171,13 @@
 /** \returns the minimum of all coefficients of *this
   * and puts in *row and *col its location.
   *
-  * \sa DenseBase::minCoeff(int*), DenseBase::maxCoeff(int*,int*), DenseBase::visitor(), DenseBase::minCoeff()
+  * \sa DenseBase::minCoeff(Index*), DenseBase::maxCoeff(Index*,Index*), DenseBase::visitor(), DenseBase::minCoeff()
   */
 template<typename Derived>
 typename ei_traits<Derived>::Scalar
-DenseBase<Derived>::minCoeff(int* row, int* col) const
+DenseBase<Derived>::minCoeff(Index* row, Index* col) const
 {
-  ei_min_coeff_visitor<Scalar> minVisitor;
+  ei_min_coeff_visitor<Derived> minVisitor;
   this->visit(minVisitor);
   *row = minVisitor.row;
   if (col) *col = minVisitor.col;
@@ -180,14 +187,14 @@
 /** \returns the minimum of all coefficients of *this
   * and puts in *index its location.
   *
-  * \sa DenseBase::minCoeff(int*,int*), DenseBase::maxCoeff(int*,int*), DenseBase::visitor(), DenseBase::minCoeff()
+  * \sa DenseBase::minCoeff(Index*,Index*), DenseBase::maxCoeff(Index*,Index*), DenseBase::visitor(), DenseBase::minCoeff()
   */
 template<typename Derived>
 typename ei_traits<Derived>::Scalar
-DenseBase<Derived>::minCoeff(int* index) const
+DenseBase<Derived>::minCoeff(Index* index) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  ei_min_coeff_visitor<Scalar> minVisitor;
+  ei_min_coeff_visitor<Derived> minVisitor;
   this->visit(minVisitor);
   *index = (RowsAtCompileTime==1) ? minVisitor.col : minVisitor.row;
   return minVisitor.res;
@@ -196,13 +203,13 @@
 /** \returns the maximum of all coefficients of *this
   * and puts in *row and *col its location.
   *
-  * \sa DenseBase::minCoeff(int*,int*), DenseBase::visitor(), DenseBase::maxCoeff()
+  * \sa DenseBase::minCoeff(Index*,Index*), DenseBase::visitor(), DenseBase::maxCoeff()
   */
 template<typename Derived>
 typename ei_traits<Derived>::Scalar
-DenseBase<Derived>::maxCoeff(int* row, int* col) const
+DenseBase<Derived>::maxCoeff(Index* row, Index* col) const
 {
-  ei_max_coeff_visitor<Scalar> maxVisitor;
+  ei_max_coeff_visitor<Derived> maxVisitor;
   this->visit(maxVisitor);
   *row = maxVisitor.row;
   if (col) *col = maxVisitor.col;
@@ -212,14 +219,14 @@
 /** \returns the maximum of all coefficients of *this
   * and puts in *index its location.
   *
-  * \sa DenseBase::maxCoeff(int*,int*), DenseBase::minCoeff(int*,int*), DenseBase::visitor(), DenseBase::maxCoeff()
+  * \sa DenseBase::maxCoeff(Index*,Index*), DenseBase::minCoeff(Index*,Index*), DenseBase::visitor(), DenseBase::maxCoeff()
   */
 template<typename Derived>
 typename ei_traits<Derived>::Scalar
-DenseBase<Derived>::maxCoeff(int* index) const
+DenseBase<Derived>::maxCoeff(Index* index) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  ei_max_coeff_visitor<Scalar> maxVisitor;
+  ei_max_coeff_visitor<Derived> maxVisitor;
   this->visit(maxVisitor);
   *index = (RowsAtCompileTime==1) ? maxVisitor.col : maxVisitor.row;
   return maxVisitor.res;
diff --git a/Eigen/src/Core/products/CoeffBasedProduct.h b/Eigen/src/Core/products/CoeffBasedProduct.h
index 2f7b32c..0c39cbd 100644
--- a/Eigen/src/Core/products/CoeffBasedProduct.h
+++ b/Eigen/src/Core/products/CoeffBasedProduct.h
@@ -39,10 +39,10 @@
  * Note that here the inner-loops should always be unrolled.
  */
 
-template<int Traversal, int Index, typename Lhs, typename Rhs, typename RetScalar>
+template<int Traversal, int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
 struct ei_product_coeff_impl;
 
-template<int StorageOrder, int Index, typename Lhs, typename Rhs, typename PacketScalar, int LoadMode>
+template<int StorageOrder, int UnrollingIndex, typename Lhs, typename Rhs, typename PacketScalar, int LoadMode>
 struct ei_product_packet_impl;
 
 template<typename LhsNested, typename RhsNested, int NestingFlags>
@@ -159,10 +159,10 @@
         && "if you wanted a coeff-wise or a dot product use the respective explicit functions");
     }
 
-    EIGEN_STRONG_INLINE int rows() const { return m_lhs.rows(); }
-    EIGEN_STRONG_INLINE int cols() const { return m_rhs.cols(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); }
 
-    EIGEN_STRONG_INLINE const Scalar coeff(int row, int col) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
     {
       Scalar res;
       ScalarCoeffImpl::run(row, col, m_lhs, m_rhs, res);
@@ -172,17 +172,17 @@
     /* Allow index-based non-packet access. It is impossible though to allow index-based packed access,
      * which is why we don't set the LinearAccessBit.
      */
-    EIGEN_STRONG_INLINE const Scalar coeff(int index) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
     {
       Scalar res;
-      const int row = RowsAtCompileTime == 1 ? 0 : index;
-      const int col = RowsAtCompileTime == 1 ? index : 0;
+      const Index row = RowsAtCompileTime == 1 ? 0 : index;
+      const Index col = RowsAtCompileTime == 1 ? index : 0;
       ScalarCoeffImpl::run(row, col, m_lhs, m_rhs, res);
       return res;
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE const PacketScalar packet(int row, int col) const
+    EIGEN_STRONG_INLINE const PacketScalar packet(Index row, Index col) const
     {
       PacketScalar res;
       ei_product_packet_impl<Flags&RowMajorBit ? RowMajor : ColMajor,
@@ -205,11 +205,11 @@
     const Diagonal<LazyCoeffBasedProductType,0> diagonal() const
     { return reinterpret_cast<const LazyCoeffBasedProductType&>(*this); }
 
-    template<int Index>
-    const Diagonal<LazyCoeffBasedProductType,Index> diagonal() const
+    template<int DiagonalIndex>
+    const Diagonal<LazyCoeffBasedProductType,DiagonalIndex> diagonal() const
     { return reinterpret_cast<const LazyCoeffBasedProductType&>(*this); }
 
-    const Diagonal<LazyCoeffBasedProductType,Dynamic> diagonal(int index) const
+    const Diagonal<LazyCoeffBasedProductType,Dynamic> diagonal(Index index) const
     { return reinterpret_cast<const LazyCoeffBasedProductType&>(*this).diagonal(index); }
 
   protected:
@@ -235,20 +235,22 @@
 *** Scalar path  - no vectorization ***
 **************************************/
 
-template<int Index, typename Lhs, typename Rhs, typename RetScalar>
-struct ei_product_coeff_impl<DefaultTraversal, Index, Lhs, Rhs, RetScalar>
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
+struct ei_product_coeff_impl<DefaultTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
   {
-    ei_product_coeff_impl<DefaultTraversal, Index-1, Lhs, Rhs, RetScalar>::run(row, col, lhs, rhs, res);
-    res += lhs.coeff(row, Index) * rhs.coeff(Index, col);
+    ei_product_coeff_impl<DefaultTraversal, UnrollingIndex-1, Lhs, Rhs, RetScalar>::run(row, col, lhs, rhs, res);
+    res += lhs.coeff(row, UnrollingIndex) * rhs.coeff(UnrollingIndex, col);
   }
 };
 
 template<typename Lhs, typename Rhs, typename RetScalar>
 struct ei_product_coeff_impl<DefaultTraversal, 0, Lhs, Rhs, RetScalar>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
   {
     res = lhs.coeff(row, 0) * rhs.coeff(0, col);
   }
@@ -257,11 +259,12 @@
 template<typename Lhs, typename Rhs, typename RetScalar>
 struct ei_product_coeff_impl<DefaultTraversal, Dynamic, Lhs, Rhs, RetScalar>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, RetScalar& res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar& res)
   {
     ei_assert(lhs.cols()>0 && "you are using a non initialized matrix");
     res = lhs.coeff(row, 0) * rhs.coeff(0, col);
-      for(int i = 1; i < lhs.cols(); ++i)
+      for(Index i = 1; i < lhs.cols(); ++i)
         res += lhs.coeff(row, i) * rhs.coeff(i, col);
   }
 };
@@ -270,43 +273,47 @@
 template<typename Lhs, typename Rhs, typename RetScalar>
 struct ei_product_coeff_impl<DefaultTraversal, -1, Lhs, Rhs, RetScalar>
 {
-  EIGEN_STRONG_INLINE static void run(int, int, const Lhs&, const Rhs&, RetScalar&) {}
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index, Index, const Lhs&, const Rhs&, RetScalar&) {}
 };
 
 /*******************************************
 *** Scalar path with inner vectorization ***
 *******************************************/
 
-template<int Index, typename Lhs, typename Rhs, typename PacketScalar>
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename PacketScalar>
 struct ei_product_coeff_vectorized_unroller
 {
+  typedef typename Lhs::Index Index;
   enum { PacketSize = ei_packet_traits<typename Lhs::Scalar>::size };
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
   {
-    ei_product_coeff_vectorized_unroller<Index-PacketSize, Lhs, Rhs, PacketScalar>::run(row, col, lhs, rhs, pres);
-    pres = ei_padd(pres, ei_pmul( lhs.template packet<Aligned>(row, Index) , rhs.template packet<Aligned>(Index, col) ));
+    ei_product_coeff_vectorized_unroller<UnrollingIndex-PacketSize, Lhs, Rhs, PacketScalar>::run(row, col, lhs, rhs, pres);
+    pres = ei_padd(pres, ei_pmul( lhs.template packet<Aligned>(row, UnrollingIndex) , rhs.template packet<Aligned>(UnrollingIndex, col) ));
   }
 };
 
 template<typename Lhs, typename Rhs, typename PacketScalar>
 struct ei_product_coeff_vectorized_unroller<0, Lhs, Rhs, PacketScalar>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
   {
     pres = ei_pmul(lhs.template packet<Aligned>(row, 0) , rhs.template packet<Aligned>(0, col));
   }
 };
 
-template<int Index, typename Lhs, typename Rhs, typename RetScalar>
-struct ei_product_coeff_impl<InnerVectorizedTraversal, Index, Lhs, Rhs, RetScalar>
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
+struct ei_product_coeff_impl<InnerVectorizedTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
 {
   typedef typename Lhs::PacketScalar PacketScalar;
+  typedef typename Lhs::Index Index;
   enum { PacketSize = ei_packet_traits<typename Lhs::Scalar>::size };
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
   {
     PacketScalar pres;
-    ei_product_coeff_vectorized_unroller<Index+1-PacketSize, Lhs, Rhs, PacketScalar>::run(row, col, lhs, rhs, pres);
-    ei_product_coeff_impl<DefaultTraversal,Index,Lhs,Rhs,RetScalar>::run(row, col, lhs, rhs, res);
+    ei_product_coeff_vectorized_unroller<UnrollingIndex+1-PacketSize, Lhs, Rhs, PacketScalar>::run(row, col, lhs, rhs, pres);
+    ei_product_coeff_impl<DefaultTraversal,UnrollingIndex,Lhs,Rhs,RetScalar>::run(row, col, lhs, rhs, res);
     res = ei_predux(pres);
   }
 };
@@ -314,7 +321,8 @@
 template<typename Lhs, typename Rhs, int LhsRows = Lhs::RowsAtCompileTime, int RhsCols = Rhs::ColsAtCompileTime>
 struct ei_product_coeff_vectorized_dyn_selector
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     res = lhs.row(row).cwiseProduct(rhs.col(col)).sum();
   }
@@ -325,7 +333,8 @@
 template<typename Lhs, typename Rhs, int RhsCols>
 struct ei_product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,RhsCols>
 {
-  EIGEN_STRONG_INLINE static void run(int /*row*/, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index /*row*/, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     res = lhs.cwiseProduct(rhs.col(col)).sum();
   }
@@ -334,7 +343,8 @@
 template<typename Lhs, typename Rhs, int LhsRows>
 struct ei_product_coeff_vectorized_dyn_selector<Lhs,Rhs,LhsRows,1>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     res = lhs.row(row).cwiseProduct(rhs).sum();
   }
@@ -343,7 +353,8 @@
 template<typename Lhs, typename Rhs>
 struct ei_product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,1>
 {
-  EIGEN_STRONG_INLINE static void run(int /*row*/, int /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index /*row*/, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     res = lhs.cwiseProduct(rhs).sum();
   }
@@ -352,7 +363,8 @@
 template<typename Lhs, typename Rhs, typename RetScalar>
 struct ei_product_coeff_impl<InnerVectorizedTraversal, Dynamic, Lhs, Rhs, RetScalar>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     ei_product_coeff_vectorized_dyn_selector<Lhs,Rhs>::run(row, col, lhs, rhs, res);
   }
@@ -362,30 +374,33 @@
 *** Packet path  ***
 *******************/
 
-template<int Index, typename Lhs, typename Rhs, typename PacketScalar, int LoadMode>
-struct ei_product_packet_impl<RowMajor, Index, Lhs, Rhs, PacketScalar, LoadMode>
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename PacketScalar, int LoadMode>
+struct ei_product_packet_impl<RowMajor, UnrollingIndex, Lhs, Rhs, PacketScalar, LoadMode>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res)
   {
-    ei_product_packet_impl<RowMajor, Index-1, Lhs, Rhs, PacketScalar, LoadMode>::run(row, col, lhs, rhs, res);
-    res =  ei_pmadd(ei_pset1(lhs.coeff(row, Index)), rhs.template packet<LoadMode>(Index, col), res);
+    ei_product_packet_impl<RowMajor, UnrollingIndex-1, Lhs, Rhs, PacketScalar, LoadMode>::run(row, col, lhs, rhs, res);
+    res =  ei_pmadd(ei_pset1(lhs.coeff(row, UnrollingIndex)), rhs.template packet<LoadMode>(UnrollingIndex, col), res);
   }
 };
 
-template<int Index, typename Lhs, typename Rhs, typename PacketScalar, int LoadMode>
-struct ei_product_packet_impl<ColMajor, Index, Lhs, Rhs, PacketScalar, LoadMode>
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename PacketScalar, int LoadMode>
+struct ei_product_packet_impl<ColMajor, UnrollingIndex, Lhs, Rhs, PacketScalar, LoadMode>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res)
   {
-    ei_product_packet_impl<ColMajor, Index-1, Lhs, Rhs, PacketScalar, LoadMode>::run(row, col, lhs, rhs, res);
-    res =  ei_pmadd(lhs.template packet<LoadMode>(row, Index), ei_pset1(rhs.coeff(Index, col)), res);
+    ei_product_packet_impl<ColMajor, UnrollingIndex-1, Lhs, Rhs, PacketScalar, LoadMode>::run(row, col, lhs, rhs, res);
+    res =  ei_pmadd(lhs.template packet<LoadMode>(row, UnrollingIndex), ei_pset1(rhs.coeff(UnrollingIndex, col)), res);
   }
 };
 
 template<typename Lhs, typename Rhs, typename PacketScalar, int LoadMode>
 struct ei_product_packet_impl<RowMajor, 0, Lhs, Rhs, PacketScalar, LoadMode>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res)
   {
     res = ei_pmul(ei_pset1(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
   }
@@ -394,7 +409,8 @@
 template<typename Lhs, typename Rhs, typename PacketScalar, int LoadMode>
 struct ei_product_packet_impl<ColMajor, 0, Lhs, Rhs, PacketScalar, LoadMode>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, PacketScalar &res)
   {
     res = ei_pmul(lhs.template packet<LoadMode>(row, 0), ei_pset1(rhs.coeff(0, col)));
   }
@@ -403,11 +419,12 @@
 template<typename Lhs, typename Rhs, typename PacketScalar, int LoadMode>
 struct ei_product_packet_impl<RowMajor, Dynamic, Lhs, Rhs, PacketScalar, LoadMode>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar& res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, PacketScalar& res)
   {
     ei_assert(lhs.cols()>0 && "you are using a non initialized matrix");
     res = ei_pmul(ei_pset1(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
-      for(int i = 1; i < lhs.cols(); ++i)
+      for(Index i = 1; i < lhs.cols(); ++i)
         res =  ei_pmadd(ei_pset1(lhs.coeff(row, i)), rhs.template packet<LoadMode>(i, col), res);
   }
 };
@@ -415,11 +432,12 @@
 template<typename Lhs, typename Rhs, typename PacketScalar, int LoadMode>
 struct ei_product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, PacketScalar, LoadMode>
 {
-  EIGEN_STRONG_INLINE static void run(int row, int col, const Lhs& lhs, const Rhs& rhs, PacketScalar& res)
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, PacketScalar& res)
   {
     ei_assert(lhs.cols()>0 && "you are using a non initialized matrix");
     res = ei_pmul(lhs.template packet<LoadMode>(row, 0), ei_pset1(rhs.coeff(0, col)));
-      for(int i = 1; i < lhs.cols(); ++i)
+      for(Index i = 1; i < lhs.cols(); ++i)
         res =  ei_pmadd(lhs.template packet<LoadMode>(row, i), ei_pset1(rhs.coeff(i, col)), res);
   }
 };
diff --git a/Eigen/src/Core/products/GeneralBlockPanelKernel.h b/Eigen/src/Core/products/GeneralBlockPanelKernel.h
index bc697ce..d817155 100644
--- a/Eigen/src/Core/products/GeneralBlockPanelKernel.h
+++ b/Eigen/src/Core/products/GeneralBlockPanelKernel.h
@@ -35,40 +35,40 @@
 #endif
 
 // optimized GEneral packed Block * packed Panel product kernel
-template<typename Scalar, int mr, int nr, typename Conj>
+template<typename Scalar, typename Index, int mr, int nr, typename Conj>
 struct ei_gebp_kernel
 {
-  void operator()(Scalar* res, int resStride, const Scalar* blockA, const Scalar* blockB, int rows, int depth, int cols,
-                  int strideA=-1, int strideB=-1, int offsetA=0, int offsetB=0, Scalar* unpackedB = 0)
+  void operator()(Scalar* res, Index resStride, const Scalar* blockA, const Scalar* blockB, Index rows, Index depth, Index cols,
+                  Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0, Scalar* unpackedB = 0)
   {
     typedef typename ei_packet_traits<Scalar>::type PacketType;
     enum { PacketSize = ei_packet_traits<Scalar>::size };
     if(strideA==-1) strideA = depth;
     if(strideB==-1) strideB = depth;
     Conj cj;
-    int packet_cols = (cols/nr) * nr;
-    const int peeled_mc = (rows/mr)*mr;
-    const int peeled_mc2 = peeled_mc + (rows-peeled_mc >= PacketSize ? PacketSize : 0);
-    const int peeled_kc = (depth/4)*4;
+    Index packet_cols = (cols/nr) * nr;
+    const Index peeled_mc = (rows/mr)*mr;
+    const Index peeled_mc2 = peeled_mc + (rows-peeled_mc >= PacketSize ? PacketSize : 0);
+    const Index peeled_kc = (depth/4)*4;
 
     if(unpackedB==0)
       unpackedB = const_cast<Scalar*>(blockB - strideB * nr * PacketSize);
 
     // loops on each micro vertical panel of rhs (depth x nr)
-    for(int j2=0; j2<packet_cols; j2+=nr)
+    for(Index j2=0; j2<packet_cols; j2+=nr)
     {
       // unpack B
       {
         const Scalar* blB = &blockB[j2*strideB+offsetB*nr];
-        int n = depth*nr;
-        for(int k=0; k<n; k++)
+        Index n = depth*nr;
+        for(Index k=0; k<n; k++)
           ei_pstore(&unpackedB[k*PacketSize], ei_pset1(blB[k]));
         /*Scalar* dest = unpackedB;
-        for(int k=0; k<n; k+=4*PacketSize)
+        for(Index k=0; k<n; k+=4*PacketSize)
         {
           #ifdef EIGEN_VECTORIZE_SSE
-          const int S = 128;
-          const int G = 16;
+          const Index S = 128;
+          const Index G = 16;
           _mm_prefetch((const char*)(&blB[S/2+0]), _MM_HINT_T0);
           _mm_prefetch((const char*)(&dest[S+0*G]), _MM_HINT_T0);
           _mm_prefetch((const char*)(&dest[S+1*G]), _MM_HINT_T0);
@@ -114,7 +114,7 @@
       // loops on each micro horizontal panel of lhs (mr x depth)
       // => we select a mr x nr micro block of res which is entirely
       //    stored into mr/packet_size x nr registers.
-      for(int i=0; i<peeled_mc; i+=mr)
+      for(Index i=0; i<peeled_mc; i+=mr)
       {
         const Scalar* blA = &blockA[i*strideA+offsetA*mr];
         ei_prefetch(&blA[0]);
@@ -146,7 +146,7 @@
         // TODO let's check wether the folowing peeled loop could not be
         //      optimized via optimal prefetching from one loop to the other
         const Scalar* blB = unpackedB;
-        for(int k=0; k<peeled_kc; k+=4)
+        for(Index k=0; k<peeled_kc; k+=4)
         {
           if(nr==2)
           {
@@ -257,7 +257,7 @@
           blA += 4*mr;
         }
         // process remaining peeled loop
-        for(int k=peeled_kc; k<depth; k++)
+        for(Index k=peeled_kc; k<depth; k++)
         {
           if(nr==2)
           {
@@ -328,7 +328,7 @@
       }
       if(rows-peeled_mc>=PacketSize)
       {
-        int i = peeled_mc;
+        Index i = peeled_mc;
         const Scalar* blA = &blockA[i*strideA+offsetA*PacketSize];
         ei_prefetch(&blA[0]);
 
@@ -341,7 +341,7 @@
 
         // performs "inner" product
         const Scalar* blB = unpackedB;
-        for(int k=0; k<peeled_kc; k+=4)
+        for(Index k=0; k<peeled_kc; k+=4)
         {
           if(nr==2)
           {
@@ -417,7 +417,7 @@
           blA += 4*PacketSize;
         }
         // process remaining peeled loop
-        for(int k=peeled_kc; k<depth; k++)
+        for(Index k=peeled_kc; k<depth; k++)
         {
           if(nr==2)
           {
@@ -455,7 +455,7 @@
         if(nr==4) ei_pstoreu(&res[(j2+2)*resStride + i], C2);
         if(nr==4) ei_pstoreu(&res[(j2+3)*resStride + i], C3);
       }
-      for(int i=peeled_mc2; i<rows; i++)
+      for(Index i=peeled_mc2; i<rows; i++)
       {
         const Scalar* blA = &blockA[i*strideA+offsetA];
         ei_prefetch(&blA[0]);
@@ -464,7 +464,7 @@
         Scalar C0(0), C1(0), C2(0), C3(0);
         // TODO directly use blockB ???
         const Scalar* blB = unpackedB;//&blockB[j2*strideB+offsetB*nr];
-        for(int k=0; k<depth; k++)
+        for(Index k=0; k<depth; k++)
         {
           if(nr==2)
           {
@@ -504,16 +504,16 @@
 
     // process remaining rhs/res columns one at a time
     // => do the same but with nr==1
-    for(int j2=packet_cols; j2<cols; j2++)
+    for(Index j2=packet_cols; j2<cols; j2++)
     {
       // unpack B
       {
         const Scalar* blB = &blockB[j2*strideB+offsetB];
-        for(int k=0; k<depth; k++)
+        for(Index k=0; k<depth; k++)
           ei_pstore(&unpackedB[k*PacketSize], ei_pset1(blB[k]));
       }
 
-      for(int i=0; i<peeled_mc; i+=mr)
+      for(Index i=0; i<peeled_mc; i+=mr)
       {
         const Scalar* blA = &blockA[i*strideA+offsetA*mr];
         ei_prefetch(&blA[0]);
@@ -526,7 +526,7 @@
         C4 = ei_ploadu(&res[(j2+0)*resStride + i + PacketSize]);
 
         const Scalar* blB = unpackedB;
-        for(int k=0; k<depth; k++)
+        for(Index k=0; k<depth; k++)
         {
           PacketType B0, A0, A1, T0, T1;
 
@@ -545,14 +545,14 @@
       }
       if(rows-peeled_mc>=PacketSize)
       {
-        int i = peeled_mc;
+        Index i = peeled_mc;
         const Scalar* blA = &blockA[i*strideA+offsetA*PacketSize];
         ei_prefetch(&blA[0]);
 
         PacketType C0 = ei_ploadu(&res[(j2+0)*resStride + i]);
 
         const Scalar* blB = unpackedB;
-        for(int k=0; k<depth; k++)
+        for(Index k=0; k<depth; k++)
         {
           C0 = cj.pmadd(ei_pload(blA), ei_pload(blB), C0);
           blB += PacketSize;
@@ -561,7 +561,7 @@
 
         ei_pstoreu(&res[(j2+0)*resStride + i], C0);
       }
-      for(int i=peeled_mc2; i<rows; i++)
+      for(Index i=peeled_mc2; i<rows; i++)
       {
         const Scalar* blA = &blockA[i*strideA+offsetA];
         ei_prefetch(&blA[0]);
@@ -570,7 +570,7 @@
         Scalar C0(0);
         // FIXME directly use blockB ??
         const Scalar* blB = unpackedB;
-        for(int k=0; k<depth; k++)
+        for(Index k=0; k<depth; k++)
           C0 = cj.pmadd(blA[k], blB[k*PacketSize], C0);
         res[(j2+0)*resStride + i] += C0;
       }
@@ -594,39 +594,39 @@
 //
 //  32 33 34 35 ...
 //  36 36 38 39 ...
-template<typename Scalar, int mr, int StorageOrder, bool Conjugate, bool PanelMode>
+template<typename Scalar, typename Index, int mr, int StorageOrder, bool Conjugate, bool PanelMode>
 struct ei_gemm_pack_lhs
 {
-  void operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, int lhsStride, int depth, int rows,
-                  int stride=0, int offset=0)
+  void operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows,
+                  Index stride=0, Index offset=0)
   {
     enum { PacketSize = ei_packet_traits<Scalar>::size };
     ei_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
     ei_conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj;
-    ei_const_blas_data_mapper<Scalar, StorageOrder> lhs(_lhs,lhsStride);
-    int count = 0;
-    int peeled_mc = (rows/mr)*mr;
-    for(int i=0; i<peeled_mc; i+=mr)
+    ei_const_blas_data_mapper<Scalar, Index, StorageOrder> lhs(_lhs,lhsStride);
+    Index count = 0;
+    Index peeled_mc = (rows/mr)*mr;
+    for(Index i=0; i<peeled_mc; i+=mr)
     {
       if(PanelMode) count += mr * offset;
-      for(int k=0; k<depth; k++)
-        for(int w=0; w<mr; w++)
+      for(Index k=0; k<depth; k++)
+        for(Index w=0; w<mr; w++)
           blockA[count++] = cj(lhs(i+w, k));
       if(PanelMode) count += mr * (stride-offset-depth);
     }
     if(rows-peeled_mc>=PacketSize)
     {
       if(PanelMode) count += PacketSize*offset;
-      for(int k=0; k<depth; k++)
-        for(int w=0; w<PacketSize; w++)
+      for(Index k=0; k<depth; k++)
+        for(Index w=0; w<PacketSize; w++)
           blockA[count++] = cj(lhs(peeled_mc+w, k));
       if(PanelMode) count += PacketSize * (stride-offset-depth);
       peeled_mc += PacketSize;
     }
-    for(int i=peeled_mc; i<rows; i++)
+    for(Index i=peeled_mc; i<rows; i++)
     {
       if(PanelMode) count += offset;
-      for(int k=0; k<depth; k++)
+      for(Index k=0; k<depth; k++)
         blockA[count++] = cj(lhs(i, k));
       if(PanelMode) count += (stride-offset-depth);
     }
@@ -640,19 +640,19 @@
 //  4  5  6  7   16 17 18 19   25 28
 //  8  9 10 11   20 21 22 23   26 29
 //  .  .  .  .    .  .  .  .    .  .
-template<typename Scalar, int nr, bool PanelMode>
-struct ei_gemm_pack_rhs<Scalar, nr, ColMajor, PanelMode>
+template<typename Scalar, typename Index, int nr, bool PanelMode>
+struct ei_gemm_pack_rhs<Scalar, Index, nr, ColMajor, PanelMode>
 {
   typedef typename ei_packet_traits<Scalar>::type Packet;
   enum { PacketSize = ei_packet_traits<Scalar>::size };
-  void operator()(Scalar* blockB, const Scalar* rhs, int rhsStride, Scalar alpha, int depth, int cols,
-                  int stride=0, int offset=0)
+  void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Scalar alpha, Index depth, Index cols,
+                  Index stride=0, Index offset=0)
   {
     ei_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
     bool hasAlpha = alpha != Scalar(1);
-    int packet_cols = (cols/nr) * nr;
-    int count = 0;
-    for(int j2=0; j2<packet_cols; j2+=nr)
+    Index packet_cols = (cols/nr) * nr;
+    Index count = 0;
+    for(Index j2=0; j2<packet_cols; j2+=nr)
     {
       // skip what we have before
       if(PanelMode) count += nr * offset;
@@ -661,7 +661,7 @@
       const Scalar* b2 = &rhs[(j2+2)*rhsStride];
       const Scalar* b3 = &rhs[(j2+3)*rhsStride];
       if (hasAlpha)
-        for(int k=0; k<depth; k++)
+        for(Index k=0; k<depth; k++)
         {
                     blockB[count+0] = alpha*b0[k];
                     blockB[count+1] = alpha*b1[k];
@@ -670,7 +670,7 @@
           count += nr;
         }
       else
-        for(int k=0; k<depth; k++)
+        for(Index k=0; k<depth; k++)
         {
                     blockB[count+0] = b0[k];
                     blockB[count+1] = b1[k];
@@ -683,18 +683,18 @@
     }
 
     // copy the remaining columns one at a time (nr==1)
-    for(int j2=packet_cols; j2<cols; ++j2)
+    for(Index j2=packet_cols; j2<cols; ++j2)
     {
       if(PanelMode) count += offset;
       const Scalar* b0 = &rhs[(j2+0)*rhsStride];
       if (hasAlpha)
-        for(int k=0; k<depth; k++)
+        for(Index k=0; k<depth; k++)
         {
           blockB[count] = alpha*b0[k];
           count += 1;
         }
       else
-        for(int k=0; k<depth; k++)
+        for(Index k=0; k<depth; k++)
         {
           blockB[count] = b0[k];
           count += 1;
@@ -705,24 +705,24 @@
 };
 
 // this version is optimized for row major matrices
-template<typename Scalar, int nr, bool PanelMode>
-struct ei_gemm_pack_rhs<Scalar, nr, RowMajor, PanelMode>
+template<typename Scalar, typename Index, int nr, bool PanelMode>
+struct ei_gemm_pack_rhs<Scalar, Index, nr, RowMajor, PanelMode>
 {
   enum { PacketSize = ei_packet_traits<Scalar>::size };
-  void operator()(Scalar* blockB, const Scalar* rhs, int rhsStride, Scalar alpha, int depth, int cols,
-                  int stride=0, int offset=0)
+  void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Scalar alpha, Index depth, Index cols,
+                  Index stride=0, Index offset=0)
   {
     ei_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
     bool hasAlpha = alpha != Scalar(1);
-    int packet_cols = (cols/nr) * nr;
-    int count = 0;
-    for(int j2=0; j2<packet_cols; j2+=nr)
+    Index packet_cols = (cols/nr) * nr;
+    Index count = 0;
+    for(Index j2=0; j2<packet_cols; j2+=nr)
     {
       // skip what we have before
       if(PanelMode) count += nr * offset;
       if (hasAlpha)
       {
-        for(int k=0; k<depth; k++)
+        for(Index k=0; k<depth; k++)
         {
           const Scalar* b0 = &rhs[k*rhsStride + j2];
                     blockB[count+0] = alpha*b0[0];
@@ -734,7 +734,7 @@
       }
       else
       {
-        for(int k=0; k<depth; k++)
+        for(Index k=0; k<depth; k++)
         {
           const Scalar* b0 = &rhs[k*rhsStride + j2];
                     blockB[count+0] = b0[0];
@@ -748,11 +748,11 @@
       if(PanelMode) count += nr * (stride-offset-depth);
     }
     // copy the remaining columns one at a time (nr==1)
-    for(int j2=packet_cols; j2<cols; ++j2)
+    for(Index j2=packet_cols; j2<cols; ++j2)
     {
       if(PanelMode) count += offset;
       const Scalar* b0 = &rhs[j2];
-      for(int k=0; k<depth; k++)
+      for(Index k=0; k<depth; k++)
       {
         blockB[count] = alpha*b0[k*rhsStride];
         count += 1;
diff --git a/Eigen/src/Core/products/GeneralMatrixMatrix.h b/Eigen/src/Core/products/GeneralMatrixMatrix.h
index 7bb26c1..991977c 100644
--- a/Eigen/src/Core/products/GeneralMatrixMatrix.h
+++ b/Eigen/src/Core/products/GeneralMatrixMatrix.h
@@ -29,21 +29,21 @@
 
 /* Specialization for a row-major destination matrix => simple transposition of the product */
 template<
-  typename Scalar,
+  typename Scalar, typename Index,
   int LhsStorageOrder, bool ConjugateLhs,
   int RhsStorageOrder, bool ConjugateRhs>
-struct ei_general_matrix_matrix_product<Scalar,LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,RowMajor>
+struct ei_general_matrix_matrix_product<Scalar,Index,LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,RowMajor>
 {
   static EIGEN_STRONG_INLINE void run(
-    int rows, int cols, int depth,
-    const Scalar* lhs, int lhsStride,
-    const Scalar* rhs, int rhsStride,
-    Scalar* res, int resStride,
+    Index rows, Index cols, Index depth,
+    const Scalar* lhs, Index lhsStride,
+    const Scalar* rhs, Index rhsStride,
+    Scalar* res, Index resStride,
     Scalar alpha,
-    GemmParallelInfo<Scalar>* info = 0)
+    GemmParallelInfo<Scalar, Index>* info = 0)
   {
     // transpose the product such that the result is column major
-    ei_general_matrix_matrix_product<Scalar,
+    ei_general_matrix_matrix_product<Scalar, Index,
       RhsStorageOrder==RowMajor ? ColMajor : RowMajor,
       ConjugateRhs,
       LhsStorageOrder==RowMajor ? ColMajor : RowMajor,
@@ -56,20 +56,20 @@
 /*  Specialization for a col-major destination matrix
  *    => Blocking algorithm following Goto's paper */
 template<
-  typename Scalar,
+  typename Scalar, typename Index,
   int LhsStorageOrder, bool ConjugateLhs,
   int RhsStorageOrder, bool ConjugateRhs>
-struct ei_general_matrix_matrix_product<Scalar,LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,ColMajor>
+struct ei_general_matrix_matrix_product<Scalar,Index,LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,ColMajor>
 {
-static void run(int rows, int cols, int depth,
-  const Scalar* _lhs, int lhsStride,
-  const Scalar* _rhs, int rhsStride,
-  Scalar* res, int resStride,
+static void run(Index rows, Index cols, Index depth,
+  const Scalar* _lhs, Index lhsStride,
+  const Scalar* _rhs, Index rhsStride,
+  Scalar* res, Index resStride,
   Scalar alpha,
-  GemmParallelInfo<Scalar>* info = 0)
+  GemmParallelInfo<Scalar,Index>* info = 0)
 {
-  ei_const_blas_data_mapper<Scalar, LhsStorageOrder> lhs(_lhs,lhsStride);
-  ei_const_blas_data_mapper<Scalar, RhsStorageOrder> rhs(_rhs,rhsStride);
+  ei_const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
+  ei_const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
 
   if (ConjugateRhs)
     alpha = ei_conj(alpha);
@@ -77,19 +77,19 @@
   typedef typename ei_packet_traits<Scalar>::type PacketType;
   typedef ei_product_blocking_traits<Scalar> Blocking;
 
-  int kc = std::min<int>(Blocking::Max_kc,depth);  // cache block size along the K direction
-  int mc = std::min<int>(Blocking::Max_mc,rows);   // cache block size along the M direction
+  Index kc = std::min<Index>(Blocking::Max_kc,depth);  // cache block size along the K direction
+  Index mc = std::min<Index>(Blocking::Max_mc,rows);   // cache block size along the M direction
 
-  ei_gemm_pack_rhs<Scalar, Blocking::nr, RhsStorageOrder> pack_rhs;
-  ei_gemm_pack_lhs<Scalar, Blocking::mr, LhsStorageOrder> pack_lhs;
-  ei_gebp_kernel<Scalar, Blocking::mr, Blocking::nr, ei_conj_helper<ConjugateLhs,ConjugateRhs> > gebp;
+  ei_gemm_pack_rhs<Scalar, Index, Blocking::nr, RhsStorageOrder> pack_rhs;
+  ei_gemm_pack_lhs<Scalar, Index, Blocking::mr, LhsStorageOrder> pack_lhs;
+  ei_gebp_kernel<Scalar, Index, Blocking::mr, Blocking::nr, ei_conj_helper<ConjugateLhs,ConjugateRhs> > gebp;
 
 #ifdef EIGEN_HAS_OPENMP
   if(info)
   {
     // this is the parallel version!
-    int tid = omp_get_thread_num();
-    int threads = omp_get_num_threads();
+    Index tid = omp_get_thread_num();
+    Index threads = omp_get_num_threads();
 
     Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
     std::size_t sizeW = kc*Blocking::PacketSize*Blocking::nr*8;
@@ -98,9 +98,9 @@
 
     // For each horizontal panel of the rhs, and corresponding panel of the lhs...
     // (==GEMM_VAR1)
-    for(int k=0; k<depth; k+=kc)
+    for(Index k=0; k<depth; k+=kc)
     {
-      const int actual_kc = std::min(k+kc,depth)-k; // => rows of B', and cols of the A'
+      const Index actual_kc = std::min(k+kc,depth)-k; // => rows of B', and cols of the A'
 
       // In order to reduce the chance that a thread has to wait for the other,
       // let's start by packing A'.
@@ -121,9 +121,9 @@
       info[tid].sync = k;
 
       // Computes C_i += A' * B' per B'_j
-      for(int shift=0; shift<threads; ++shift)
+      for(Index shift=0; shift<threads; ++shift)
       {
-        int j = (tid+shift)%threads;
+        Index j = (tid+shift)%threads;
 
         // At this point we have to make sure that B'_j has been updated by the thread j,
         // we use testAndSetOrdered to mimic a volatile access.
@@ -135,9 +135,9 @@
       }
 
       // Then keep going as usual with the remaining A'
-      for(int i=mc; i<rows; i+=mc)
+      for(Index i=mc; i<rows; i+=mc)
       {
-        const int actual_mc = std::min(i+mc,rows)-i;
+        const Index actual_mc = std::min(i+mc,rows)-i;
 
         // pack A_i,k to A'
         pack_lhs(blockA, &lhs(i,k), lhsStride, actual_kc, actual_mc);
@@ -148,7 +148,7 @@
 
       // Release all the sub blocks B'_j of B' for the current thread,
       // i.e., we simply decrement the number of users by 1
-      for(int j=0; j<threads; ++j)
+      for(Index j=0; j<threads; ++j)
         #pragma omp atomic
         --(info[j].users);
     }
@@ -168,9 +168,9 @@
 
     // For each horizontal panel of the rhs, and corresponding panel of the lhs...
     // (==GEMM_VAR1)
-    for(int k2=0; k2<depth; k2+=kc)
+    for(Index k2=0; k2<depth; k2+=kc)
     {
-      const int actual_kc = std::min(k2+kc,depth)-k2;
+      const Index actual_kc = std::min(k2+kc,depth)-k2;
 
       // OK, here we have selected one horizontal panel of rhs and one vertical panel of lhs.
       // => Pack rhs's panel into a sequential chunk of memory (L2 caching)
@@ -181,9 +181,9 @@
 
       // For each mc x kc block of the lhs's vertical panel...
       // (==GEPP_VAR1)
-      for(int i2=0; i2<rows; i2+=mc)
+      for(Index i2=0; i2<rows; i2+=mc)
       {
-        const int actual_mc = std::min(i2+mc,rows)-i2;
+        const Index actual_mc = std::min(i2+mc,rows)-i2;
 
         // We pack the lhs's block into a sequential chunk of memory (L1 caching)
         // Note that this block will be read a very high number of times, which is equal to the number of
@@ -215,7 +215,7 @@
  : ei_traits<ProductBase<GeneralProduct<Lhs,Rhs,GemmProduct>, Lhs, Rhs> >
 {};
 
-template<typename Scalar, typename Gemm, typename Lhs, typename Rhs, typename Dest>
+template<typename Scalar, typename Index, typename Gemm, typename Lhs, typename Rhs, typename Dest>
 struct ei_gemm_functor
 {
   typedef typename Rhs::Scalar BlockBScalar;
@@ -224,7 +224,7 @@
     : m_lhs(lhs), m_rhs(rhs), m_dest(dest), m_actualAlpha(actualAlpha)
   {}
 
-  void operator() (int row, int rows, int col=0, int cols=-1, GemmParallelInfo<BlockBScalar>* info=0) const
+  void operator() (Index row, Index rows, Index col=0, Index cols=-1, GemmParallelInfo<BlockBScalar,Index>* info=0) const
   {
     if(cols==-1)
       cols = m_rhs.cols();
@@ -237,9 +237,9 @@
   }
 
 
-  int sharedBlockBSize() const
+  Index sharedBlockBSize() const
   {
-    return std::min<int>(ei_product_blocking_traits<Scalar>::Max_kc,m_rhs.rows()) * m_rhs.cols();
+    return std::min<Index>(ei_product_blocking_traits<Scalar>::Max_kc,m_rhs.rows()) * m_rhs.cols();
   }
 
   protected:
@@ -273,9 +273,9 @@
                                  * RhsBlasTraits::extractScalarFactor(m_rhs);
 
       typedef ei_gemm_functor<
-        Scalar,
+        Scalar, Index,
         ei_general_matrix_matrix_product<
-          Scalar,
+          Scalar, Index,
           (_ActualLhsType::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(LhsBlasTraits::NeedToConjugate),
           (_ActualRhsType::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(RhsBlasTraits::NeedToConjugate),
           (Dest::Flags&RowMajorBit) ? RowMajor : ColMajor>,
diff --git a/Eigen/src/Core/products/GeneralMatrixVector.h b/Eigen/src/Core/products/GeneralMatrixVector.h
index 3296f32..e2c5c76 100644
--- a/Eigen/src/Core/products/GeneralMatrixVector.h
+++ b/Eigen/src/Core/products/GeneralMatrixVector.h
@@ -32,11 +32,11 @@
  * same alignment pattern.
  * TODO: since rhs gets evaluated only once, no need to evaluate it
  */
-template<bool ConjugateLhs, bool ConjugateRhs, typename Scalar, typename RhsType>
+template<bool ConjugateLhs, bool ConjugateRhs, typename Scalar, typename Index, typename RhsType>
 static EIGEN_DONT_INLINE
 void ei_cache_friendly_product_colmajor_times_vector(
-  int size,
-  const Scalar* lhs, int lhsStride,
+  Index size,
+  const Scalar* lhs, Index lhsStride,
   const RhsType& rhs,
   Scalar* res,
   Scalar alpha)
@@ -59,30 +59,30 @@
 
   typedef typename NumTraits<Scalar>::Real RealScalar;
   typedef typename ei_packet_traits<Scalar>::type Packet;
-  const int PacketSize = sizeof(Packet)/sizeof(Scalar);
+  const Index PacketSize = sizeof(Packet)/sizeof(Scalar);
 
   enum { AllAligned = 0, EvenAligned, FirstAligned, NoneAligned };
-  const int columnsAtOnce = 4;
-  const int peels = 2;
-  const int PacketAlignedMask = PacketSize-1;
-  const int PeelAlignedMask = PacketSize*peels-1;
+  const Index columnsAtOnce = 4;
+  const Index peels = 2;
+  const Index PacketAlignedMask = PacketSize-1;
+  const Index PeelAlignedMask = PacketSize*peels-1;
 
   // How many coeffs of the result do we have to skip to be aligned.
   // Here we assume data are at least aligned on the base scalar type.
-  int alignedStart = ei_first_aligned(res,size);
-  int alignedSize = PacketSize>1 ? alignedStart + ((size-alignedStart) & ~PacketAlignedMask) : 0;
-  const int peeledSize  = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
+  Index alignedStart = ei_first_aligned(res,size);
+  Index alignedSize = PacketSize>1 ? alignedStart + ((size-alignedStart) & ~PacketAlignedMask) : 0;
+  const Index peeledSize  = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
 
-  const int alignmentStep = PacketSize>1 ? (PacketSize - lhsStride % PacketSize) & PacketAlignedMask : 0;
-  int alignmentPattern = alignmentStep==0 ? AllAligned
+  const Index alignmentStep = PacketSize>1 ? (PacketSize - lhsStride % PacketSize) & PacketAlignedMask : 0;
+  Index alignmentPattern = alignmentStep==0 ? AllAligned
                        : alignmentStep==(PacketSize/2) ? EvenAligned
                        : FirstAligned;
 
   // we cannot assume the first element is aligned because of sub-matrices
-  const int lhsAlignmentOffset = ei_first_aligned(lhs,size);
+  const Index lhsAlignmentOffset = ei_first_aligned(lhs,size);
 
   // find how many columns do we have to skip to be aligned with the result (if possible)
-  int skipColumns = 0;
+  Index skipColumns = 0;
   // if the data cannot be aligned (TODO add some compile time tests when possible, e.g. for floats)
   if( (size_t(lhs)%sizeof(RealScalar)) || (size_t(res)%sizeof(RealScalar)) )
   {
@@ -114,11 +114,11 @@
                       || (size_t(lhs+alignedStart+lhsStride*skipColumns)%sizeof(Packet))==0);
   }
 
-  int offset1 = (FirstAligned && alignmentStep==1?3:1);
-  int offset3 = (FirstAligned && alignmentStep==1?1:3);
+  Index offset1 = (FirstAligned && alignmentStep==1?3:1);
+  Index offset3 = (FirstAligned && alignmentStep==1?1:3);
 
-  int columnBound = ((rhs.size()-skipColumns)/columnsAtOnce)*columnsAtOnce + skipColumns;
-  for (int i=skipColumns; i<columnBound; i+=columnsAtOnce)
+  Index columnBound = ((rhs.size()-skipColumns)/columnsAtOnce)*columnsAtOnce + skipColumns;
+  for (Index i=skipColumns; i<columnBound; i+=columnsAtOnce)
   {
     Packet ptmp0 = ei_pset1(alpha*rhs[i]),   ptmp1 = ei_pset1(alpha*rhs[i+offset1]),
            ptmp2 = ei_pset1(alpha*rhs[i+2]), ptmp3 = ei_pset1(alpha*rhs[i+offset3]);
@@ -131,7 +131,7 @@
     {
       /* explicit vectorization */
       // process initial unaligned coeffs
-      for (int j=0; j<alignedStart; ++j)
+      for (Index j=0; j<alignedStart; ++j)
       {
         res[j] = cj.pmadd(lhs0[j], ei_pfirst(ptmp0), res[j]);
         res[j] = cj.pmadd(lhs1[j], ei_pfirst(ptmp1), res[j]);
@@ -144,11 +144,11 @@
         switch(alignmentPattern)
         {
           case AllAligned:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
+            for (Index j = alignedStart; j<alignedSize; j+=PacketSize)
               _EIGEN_ACCUMULATE_PACKETS(d,d,d);
             break;
           case EvenAligned:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
+            for (Index j = alignedStart; j<alignedSize; j+=PacketSize)
               _EIGEN_ACCUMULATE_PACKETS(d,du,d);
             break;
           case FirstAligned:
@@ -160,7 +160,7 @@
               A02 = ei_pload(&lhs2[alignedStart-2]);
               A03 = ei_pload(&lhs3[alignedStart-3]);
 
-              for (int j = alignedStart; j<peeledSize; j+=peels*PacketSize)
+              for (Index j = alignedStart; j<peeledSize; j+=peels*PacketSize)
               {
                 A11 = ei_pload(&lhs1[j-1+PacketSize]);  ei_palign<1>(A01,A11);
                 A12 = ei_pload(&lhs2[j-2+PacketSize]);  ei_palign<2>(A02,A12);
@@ -184,11 +184,11 @@
                 ei_pstore(&res[j+PacketSize],A10);
               }
             }
-            for (int j = peeledSize; j<alignedSize; j+=PacketSize)
+            for (Index j = peeledSize; j<alignedSize; j+=PacketSize)
               _EIGEN_ACCUMULATE_PACKETS(d,du,du);
             break;
           default:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
+            for (Index j = alignedStart; j<alignedSize; j+=PacketSize)
               _EIGEN_ACCUMULATE_PACKETS(du,du,du);
             break;
         }
@@ -196,7 +196,7 @@
     } // end explicit vectorization
 
     /* process remaining coeffs (or all if there is no explicit vectorization) */
-    for (int j=alignedSize; j<size; ++j)
+    for (Index j=alignedSize; j<size; ++j)
     {
       res[j] = cj.pmadd(lhs0[j], ei_pfirst(ptmp0), res[j]);
       res[j] = cj.pmadd(lhs1[j], ei_pfirst(ptmp1), res[j]);
@@ -206,11 +206,11 @@
   }
 
   // process remaining first and last columns (at most columnsAtOnce-1)
-  int end = rhs.size();
-  int start = columnBound;
+  Index end = rhs.size();
+  Index start = columnBound;
   do
   {
-    for (int i=start; i<end; ++i)
+    for (Index i=start; i<end; ++i)
     {
       Packet ptmp0 = ei_pset1(alpha*rhs[i]);
       const Scalar* lhs0 = lhs + i*lhsStride;
@@ -219,20 +219,20 @@
       {
         /* explicit vectorization */
         // process first unaligned result's coeffs
-        for (int j=0; j<alignedStart; ++j)
+        for (Index j=0; j<alignedStart; ++j)
           res[j] += cj.pmul(lhs0[j], ei_pfirst(ptmp0));
 
         // process aligned result's coeffs
         if ((size_t(lhs0+alignedStart)%sizeof(Packet))==0)
-          for (int j = alignedStart;j<alignedSize;j+=PacketSize)
+          for (Index j = alignedStart;j<alignedSize;j+=PacketSize)
             ei_pstore(&res[j], cj.pmadd(ei_pload(&lhs0[j]), ptmp0, ei_pload(&res[j])));
         else
-          for (int j = alignedStart;j<alignedSize;j+=PacketSize)
+          for (Index j = alignedStart;j<alignedSize;j+=PacketSize)
             ei_pstore(&res[j], cj.pmadd(ei_ploadu(&lhs0[j]), ptmp0, ei_pload(&res[j])));
       }
 
       // process remaining scalars (or all if no explicit vectorization)
-      for (int j=alignedSize; j<size; ++j)
+      for (Index j=alignedSize; j<size; ++j)
         res[j] += cj.pmul(lhs0[j], ei_pfirst(ptmp0));
     }
     if (skipColumns)
@@ -248,10 +248,10 @@
 }
 
 // TODO add peeling to mask unaligned load/stores
-template<bool ConjugateLhs, bool ConjugateRhs, typename Scalar, typename ResType>
+template<bool ConjugateLhs, bool ConjugateRhs, typename Scalar, typename Index, typename ResType>
 static EIGEN_DONT_INLINE void ei_cache_friendly_product_rowmajor_times_vector(
-  const Scalar* lhs, int lhsStride,
-  const Scalar* rhs, int rhsSize,
+  const Scalar* lhs, Index lhsStride,
+  const Scalar* rhs, Index rhsSize,
   ResType& res,
   Scalar alpha)
 {
@@ -270,32 +270,32 @@
 
   typedef typename NumTraits<Scalar>::Real RealScalar;
   typedef typename ei_packet_traits<Scalar>::type Packet;
-  const int PacketSize = sizeof(Packet)/sizeof(Scalar);
+  const Index PacketSize = sizeof(Packet)/sizeof(Scalar);
 
   enum { AllAligned=0, EvenAligned=1, FirstAligned=2, NoneAligned=3 };
-  const int rowsAtOnce = 4;
-  const int peels = 2;
-  const int PacketAlignedMask = PacketSize-1;
-  const int PeelAlignedMask = PacketSize*peels-1;
-  const int size = rhsSize;
+  const Index rowsAtOnce = 4;
+  const Index peels = 2;
+  const Index PacketAlignedMask = PacketSize-1;
+  const Index PeelAlignedMask = PacketSize*peels-1;
+  const Index size = rhsSize;
 
   // How many coeffs of the result do we have to skip to be aligned.
   // Here we assume data are at least aligned on the base scalar type
   // if that's not the case then vectorization is discarded, see below.
-  int alignedStart = ei_first_aligned(rhs, size);
-  int alignedSize = PacketSize>1 ? alignedStart + ((size-alignedStart) & ~PacketAlignedMask) : 0;
-  const int peeledSize  = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
+  Index alignedStart = ei_first_aligned(rhs, size);
+  Index alignedSize = PacketSize>1 ? alignedStart + ((size-alignedStart) & ~PacketAlignedMask) : 0;
+  const Index peeledSize  = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
 
-  const int alignmentStep = PacketSize>1 ? (PacketSize - lhsStride % PacketSize) & PacketAlignedMask : 0;
-  int alignmentPattern = alignmentStep==0 ? AllAligned
+  const Index alignmentStep = PacketSize>1 ? (PacketSize - lhsStride % PacketSize) & PacketAlignedMask : 0;
+  Index alignmentPattern = alignmentStep==0 ? AllAligned
                        : alignmentStep==(PacketSize/2) ? EvenAligned
                        : FirstAligned;
 
   // we cannot assume the first element is aligned because of sub-matrices
-  const int lhsAlignmentOffset = ei_first_aligned(lhs,size);
+  const Index lhsAlignmentOffset = ei_first_aligned(lhs,size);
 
   // find how many rows do we have to skip to be aligned with rhs (if possible)
-  int skipRows = 0;
+  Index skipRows = 0;
   // if the data cannot be aligned (TODO add some compile time tests when possible, e.g. for floats)
   if( (size_t(lhs)%sizeof(RealScalar)) || (size_t(rhs)%sizeof(RealScalar)) )
   {
@@ -317,7 +317,7 @@
     }
     else
     {
-      skipRows = std::min(skipRows,res.size());
+      skipRows = std::min(skipRows,Index(res.size()));
       // note that the skiped columns are processed later.
     }
     ei_internal_assert(  alignmentPattern==NoneAligned
@@ -327,11 +327,11 @@
                       || (size_t(lhs+alignedStart+lhsStride*skipRows)%sizeof(Packet))==0);
   }
 
-  int offset1 = (FirstAligned && alignmentStep==1?3:1);
-  int offset3 = (FirstAligned && alignmentStep==1?1:3);
+  Index offset1 = (FirstAligned && alignmentStep==1?3:1);
+  Index offset3 = (FirstAligned && alignmentStep==1?1:3);
 
-  int rowBound = ((res.size()-skipRows)/rowsAtOnce)*rowsAtOnce + skipRows;
-  for (int i=skipRows; i<rowBound; i+=rowsAtOnce)
+  Index rowBound = ((res.size()-skipRows)/rowsAtOnce)*rowsAtOnce + skipRows;
+  for (Index i=skipRows; i<rowBound; i+=rowsAtOnce)
   {
     Scalar tmp0 = Scalar(0), tmp1 = Scalar(0), tmp2 = Scalar(0), tmp3 = Scalar(0);
 
@@ -346,7 +346,7 @@
 
       // process initial unaligned coeffs
       // FIXME this loop get vectorized by the compiler !
-      for (int j=0; j<alignedStart; ++j)
+      for (Index j=0; j<alignedStart; ++j)
       {
         Scalar b = rhs[j];
         tmp0 += cj.pmul(lhs0[j],b); tmp1 += cj.pmul(lhs1[j],b);
@@ -358,11 +358,11 @@
         switch(alignmentPattern)
         {
           case AllAligned:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
+            for (Index j = alignedStart; j<alignedSize; j+=PacketSize)
               _EIGEN_ACCUMULATE_PACKETS(d,d,d);
             break;
           case EvenAligned:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
+            for (Index j = alignedStart; j<alignedSize; j+=PacketSize)
               _EIGEN_ACCUMULATE_PACKETS(d,du,d);
             break;
           case FirstAligned:
@@ -379,7 +379,7 @@
               A02 = ei_pload(&lhs2[alignedStart-2]);
               A03 = ei_pload(&lhs3[alignedStart-3]);
 
-              for (int j = alignedStart; j<peeledSize; j+=peels*PacketSize)
+              for (Index j = alignedStart; j<peeledSize; j+=peels*PacketSize)
               {
                 b = ei_pload(&rhs[j]);
                 A11 = ei_pload(&lhs1[j-1+PacketSize]);  ei_palign<1>(A01,A11);
@@ -401,11 +401,11 @@
                 ptmp3 = cj.pmadd(A13, b, ptmp3);
               }
             }
-            for (int j = peeledSize; j<alignedSize; j+=PacketSize)
+            for (Index j = peeledSize; j<alignedSize; j+=PacketSize)
               _EIGEN_ACCUMULATE_PACKETS(d,du,du);
             break;
           default:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
+            for (Index j = alignedStart; j<alignedSize; j+=PacketSize)
               _EIGEN_ACCUMULATE_PACKETS(du,du,du);
             break;
         }
@@ -418,7 +418,7 @@
 
     // process remaining coeffs (or all if no explicit vectorization)
     // FIXME this loop get vectorized by the compiler !
-    for (int j=alignedSize; j<size; ++j)
+    for (Index j=alignedSize; j<size; ++j)
     {
       Scalar b = rhs[j];
       tmp0 += cj.pmul(lhs0[j],b); tmp1 += cj.pmul(lhs1[j],b);
@@ -428,35 +428,35 @@
   }
 
   // process remaining first and last rows (at most columnsAtOnce-1)
-  int end = res.size();
-  int start = rowBound;
+  Index end = res.size();
+  Index start = rowBound;
   do
   {
-    for (int i=start; i<end; ++i)
+    for (Index i=start; i<end; ++i)
     {
       Scalar tmp0 = Scalar(0);
       Packet ptmp0 = ei_pset1(tmp0);
       const Scalar* lhs0 = lhs + i*lhsStride;
       // process first unaligned result's coeffs
       // FIXME this loop get vectorized by the compiler !
-      for (int j=0; j<alignedStart; ++j)
+      for (Index j=0; j<alignedStart; ++j)
         tmp0 += cj.pmul(lhs0[j], rhs[j]);
 
       if (alignedSize>alignedStart)
       {
         // process aligned rhs coeffs
         if ((size_t(lhs0+alignedStart)%sizeof(Packet))==0)
-          for (int j = alignedStart;j<alignedSize;j+=PacketSize)
+          for (Index j = alignedStart;j<alignedSize;j+=PacketSize)
             ptmp0 = cj.pmadd(ei_pload(&lhs0[j]), ei_pload(&rhs[j]), ptmp0);
         else
-          for (int j = alignedStart;j<alignedSize;j+=PacketSize)
+          for (Index j = alignedStart;j<alignedSize;j+=PacketSize)
             ptmp0 = cj.pmadd(ei_ploadu(&lhs0[j]), ei_pload(&rhs[j]), ptmp0);
         tmp0 += ei_predux(ptmp0);
       }
 
       // process remaining scalars
       // FIXME this loop get vectorized by the compiler !
-      for (int j=alignedSize; j<size; ++j)
+      for (Index j=alignedSize; j<size; ++j)
         tmp0 += cj.pmul(lhs0[j], rhs[j]);
       res[i] += alpha*tmp0;
     }
diff --git a/Eigen/src/Core/products/Parallelizer.h b/Eigen/src/Core/products/Parallelizer.h
index 6e15e0f..5e4eb6f 100644
--- a/Eigen/src/Core/products/Parallelizer.h
+++ b/Eigen/src/Core/products/Parallelizer.h
@@ -25,20 +25,20 @@
 #ifndef EIGEN_PARALLELIZER_H
 #define EIGEN_PARALLELIZER_H
 
-template<typename BlockBScalar> struct GemmParallelInfo
+template<typename BlockBScalar, typename Index> struct GemmParallelInfo
 {
   GemmParallelInfo() : sync(-1), users(0), rhs_start(0), rhs_length(0), blockB(0) {}
 
   int volatile sync;
   int volatile users;
 
-  int rhs_start;
-  int rhs_length;
+  Index rhs_start;
+  Index rhs_length;
   BlockBScalar* blockB;
 };
 
-template<bool Condition,typename Functor>
-void ei_parallelize_gemm(const Functor& func, int rows, int cols)
+template<bool Condition, typename Functor, typename Index>
+void ei_parallelize_gemm(const Functor& func, Index rows, Index cols)
 {
 #ifndef EIGEN_HAS_OPENMP
   func(0,rows, 0,cols);
@@ -57,16 +57,16 @@
 
   // 2- compute the maximal number of threads from the size of the product:
   // FIXME this has to be fine tuned
-  int max_threads = std::max(1,rows / 32);
+  Index max_threads = std::max(1,rows / 32);
 
   // 3 - compute the number of threads we are going to use
-  int threads = std::min(omp_get_max_threads(), max_threads);
+  Index threads = std::min<Index>(omp_get_max_threads(), max_threads);
 
   if(threads==1)
     return func(0,rows, 0,cols);
 
-  int blockCols = (cols / threads) & ~0x3;
-  int blockRows = (rows / threads) & ~0x7;
+  Index blockCols = (cols / threads) & ~Index(0x3);
+  Index blockRows = (rows / threads) & ~Index(0x7);
 
   typedef typename Functor::BlockBScalar BlockBScalar;
   BlockBScalar* sharedBlockB = new BlockBScalar[func.sharedBlockBSize()];
@@ -74,13 +74,13 @@
   GemmParallelInfo<BlockBScalar>* info = new GemmParallelInfo<BlockBScalar>[threads];
 
   #pragma omp parallel for schedule(static,1) num_threads(threads)
-  for(int i=0; i<threads; ++i)
+  for(Index i=0; i<threads; ++i)
   {
-    int r0 = i*blockRows;
-    int actualBlockRows = (i+1==threads) ? rows-r0 : blockRows;
+    Index r0 = i*blockRows;
+    Index actualBlockRows = (i+1==threads) ? rows-r0 : blockRows;
 
-    int c0 = i*blockCols;
-    int actualBlockCols = (i+1==threads) ? cols-c0 : blockCols;
+    Index c0 = i*blockCols;
+    Index actualBlockCols = (i+1==threads) ? cols-c0 : blockCols;
 
     info[i].rhs_start = c0;
     info[i].rhs_length = actualBlockCols;
diff --git a/Eigen/src/Core/products/SelfadjointMatrixMatrix.h b/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
index b23876d..31726e6 100644
--- a/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
+++ b/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
@@ -26,41 +26,41 @@
 #define EIGEN_SELFADJOINT_MATRIX_MATRIX_H
 
 // pack a selfadjoint block diagonal for use with the gebp_kernel
-template<typename Scalar, int mr, int StorageOrder>
+template<typename Scalar, typename Index, int mr, int StorageOrder>
 struct ei_symm_pack_lhs
 {
   enum { PacketSize = ei_packet_traits<Scalar>::size };
   template<int BlockRows> inline
-  void pack(Scalar* blockA, const ei_const_blas_data_mapper<Scalar,StorageOrder>& lhs, int cols, int i, int& count)
+  void pack(Scalar* blockA, const ei_const_blas_data_mapper<Scalar,Index,StorageOrder>& lhs, Index cols, Index i, Index& count)
   {
     // normal copy
-    for(int k=0; k<i; k++)
-      for(int w=0; w<BlockRows; w++)
+    for(Index k=0; k<i; k++)
+      for(Index w=0; w<BlockRows; w++)
         blockA[count++] = lhs(i+w,k);           // normal
     // symmetric copy
-    int h = 0;
-    for(int k=i; k<i+BlockRows; k++)
+    Index h = 0;
+    for(Index k=i; k<i+BlockRows; k++)
     {
-      for(int w=0; w<h; w++)
+      for(Index w=0; w<h; w++)
         blockA[count++] = ei_conj(lhs(k, i+w)); // transposed
 
       blockA[count++] = ei_real(lhs(k,k));   // real (diagonal)
 
-      for(int w=h+1; w<BlockRows; w++)
+      for(Index w=h+1; w<BlockRows; w++)
         blockA[count++] = lhs(i+w, k);          // normal
       ++h;
     }
     // transposed copy
-    for(int k=i+BlockRows; k<cols; k++)
-      for(int w=0; w<BlockRows; w++)
+    for(Index k=i+BlockRows; k<cols; k++)
+      for(Index w=0; w<BlockRows; w++)
         blockA[count++] = ei_conj(lhs(k, i+w)); // transposed
   }
-  void operator()(Scalar* blockA, const Scalar* _lhs, int lhsStride, int cols, int rows)
+  void operator()(Scalar* blockA, const Scalar* _lhs, Index lhsStride, Index cols, Index rows)
   {
-    ei_const_blas_data_mapper<Scalar,StorageOrder> lhs(_lhs,lhsStride);
-    int count = 0;
-    int peeled_mc = (rows/mr)*mr;
-    for(int i=0; i<peeled_mc; i+=mr)
+    ei_const_blas_data_mapper<Scalar,Index,StorageOrder> lhs(_lhs,lhsStride);
+    Index count = 0;
+    Index peeled_mc = (rows/mr)*mr;
+    for(Index i=0; i<peeled_mc; i+=mr)
     {
       pack<mr>(blockA, lhs, cols, i, count);
     }
@@ -72,34 +72,34 @@
     }
 
     // do the same with mr==1
-    for(int i=peeled_mc; i<rows; i++)
+    for(Index i=peeled_mc; i<rows; i++)
     {
-      for(int k=0; k<i; k++)
+      for(Index k=0; k<i; k++)
         blockA[count++] = lhs(i, k);              // normal
 
       blockA[count++] = ei_real(lhs(i, i));       // real (diagonal)
 
-      for(int k=i+1; k<cols; k++)
+      for(Index k=i+1; k<cols; k++)
         blockA[count++] = ei_conj(lhs(k, i));     // transposed
     }
   }
 };
 
-template<typename Scalar, int nr, int StorageOrder>
+template<typename Scalar, typename Index, int nr, int StorageOrder>
 struct ei_symm_pack_rhs
 {
   enum { PacketSize = ei_packet_traits<Scalar>::size };
-  void operator()(Scalar* blockB, const Scalar* _rhs, int rhsStride, Scalar alpha, int rows, int cols, int k2)
+  void operator()(Scalar* blockB, const Scalar* _rhs, Index rhsStride, Scalar alpha, Index rows, Index cols, Index k2)
   {
-    int end_k = k2 + rows;
-    int count = 0;
-    ei_const_blas_data_mapper<Scalar,StorageOrder> rhs(_rhs,rhsStride);
-    int packet_cols = (cols/nr)*nr;
+    Index end_k = k2 + rows;
+    Index count = 0;
+    ei_const_blas_data_mapper<Scalar,Index,StorageOrder> rhs(_rhs,rhsStride);
+    Index packet_cols = (cols/nr)*nr;
 
     // first part: normal case
-    for(int j2=0; j2<k2; j2+=nr)
+    for(Index j2=0; j2<k2; j2+=nr)
     {
-      for(int k=k2; k<end_k; k++)
+      for(Index k=k2; k<end_k; k++)
       {
         blockB[count+0] = alpha*rhs(k,j2+0);
         blockB[count+1] = alpha*rhs(k,j2+1);
@@ -113,11 +113,11 @@
     }
 
     // second part: diagonal block
-    for(int j2=k2; j2<std::min(k2+rows,packet_cols); j2+=nr)
+    for(Index j2=k2; j2<std::min(k2+rows,packet_cols); j2+=nr)
     {
       // again we can split vertically in three different parts (transpose, symmetric, normal)
       // transpose
-      for(int k=k2; k<j2; k++)
+      for(Index k=k2; k<j2; k++)
       {
         blockB[count+0] = alpha*ei_conj(rhs(j2+0,k));
         blockB[count+1] = alpha*ei_conj(rhs(j2+1,k));
@@ -129,23 +129,23 @@
         count += nr;
       }
       // symmetric
-      int h = 0;
-      for(int k=j2; k<j2+nr; k++)
+      Index h = 0;
+      for(Index k=j2; k<j2+nr; k++)
       {
         // normal
-        for (int w=0 ; w<h; ++w)
+        for (Index w=0 ; w<h; ++w)
           blockB[count+w] = alpha*rhs(k,j2+w);
 
         blockB[count+h] = alpha*rhs(k,k);
 
         // transpose
-        for (int w=h+1 ; w<nr; ++w)
+        for (Index w=h+1 ; w<nr; ++w)
           blockB[count+w] = alpha*ei_conj(rhs(j2+w,k));
         count += nr;
         ++h;
       }
       // normal
-      for(int k=j2+nr; k<end_k; k++)
+      for(Index k=j2+nr; k<end_k; k++)
       {
         blockB[count+0] = alpha*rhs(k,j2+0);
         blockB[count+1] = alpha*rhs(k,j2+1);
@@ -159,9 +159,9 @@
     }
 
     // third part: transposed
-    for(int j2=k2+rows; j2<packet_cols; j2+=nr)
+    for(Index j2=k2+rows; j2<packet_cols; j2+=nr)
     {
-      for(int k=k2; k<end_k; k++)
+      for(Index k=k2; k<end_k; k++)
       {
         blockB[count+0] = alpha*ei_conj(rhs(j2+0,k));
         blockB[count+1] = alpha*ei_conj(rhs(j2+1,k));
@@ -175,11 +175,11 @@
     }
 
     // copy the remaining columns one at a time (=> the same with nr==1)
-    for(int j2=packet_cols; j2<cols; ++j2)
+    for(Index j2=packet_cols; j2<cols; ++j2)
     {
       // transpose
-      int half = std::min(end_k,j2);
-      for(int k=k2; k<half; k++)
+      Index half = std::min(end_k,j2);
+      for(Index k=k2; k<half; k++)
       {
         blockB[count] = alpha*ei_conj(rhs(j2,k));
         count += 1;
@@ -194,7 +194,7 @@
         half--;
 
       // normal
-      for(int k=half+1; k<k2+rows; k++)
+      for(Index k=half+1; k<k2+rows; k++)
       {
         blockB[count] = alpha*rhs(k,j2);
         count += 1;
@@ -206,26 +206,26 @@
 /* Optimized selfadjoint matrix * matrix (_SYMM) product built on top of
  * the general matrix matrix product.
  */
-template <typename Scalar,
+template <typename Scalar, typename Index,
           int LhsStorageOrder, bool LhsSelfAdjoint, bool ConjugateLhs,
           int RhsStorageOrder, bool RhsSelfAdjoint, bool ConjugateRhs,
           int ResStorageOrder>
 struct ei_product_selfadjoint_matrix;
 
-template <typename Scalar,
+template <typename Scalar, typename Index,
           int LhsStorageOrder, bool LhsSelfAdjoint, bool ConjugateLhs,
           int RhsStorageOrder, bool RhsSelfAdjoint, bool ConjugateRhs>
-struct ei_product_selfadjoint_matrix<Scalar,LhsStorageOrder,LhsSelfAdjoint,ConjugateLhs, RhsStorageOrder,RhsSelfAdjoint,ConjugateRhs,RowMajor>
+struct ei_product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,LhsSelfAdjoint,ConjugateLhs, RhsStorageOrder,RhsSelfAdjoint,ConjugateRhs,RowMajor>
 {
 
   static EIGEN_STRONG_INLINE void run(
-    int rows, int cols,
-    const Scalar* lhs, int lhsStride,
-    const Scalar* rhs, int rhsStride,
-    Scalar* res,       int resStride,
+    Index rows, Index cols,
+    const Scalar* lhs, Index lhsStride,
+    const Scalar* rhs, Index rhsStride,
+    Scalar* res,       Index resStride,
     Scalar alpha)
   {
-    ei_product_selfadjoint_matrix<Scalar,
+    ei_product_selfadjoint_matrix<Scalar, Index,
       EIGEN_LOGICAL_XOR(RhsSelfAdjoint,RhsStorageOrder==RowMajor) ? ColMajor : RowMajor,
       RhsSelfAdjoint, NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(RhsSelfAdjoint,ConjugateRhs),
       EIGEN_LOGICAL_XOR(LhsSelfAdjoint,LhsStorageOrder==RowMajor) ? ColMajor : RowMajor,
@@ -235,45 +235,45 @@
   }
 };
 
-template <typename Scalar,
+template <typename Scalar, typename Index,
           int LhsStorageOrder, bool ConjugateLhs,
           int RhsStorageOrder, bool ConjugateRhs>
-struct ei_product_selfadjoint_matrix<Scalar,LhsStorageOrder,true,ConjugateLhs, RhsStorageOrder,false,ConjugateRhs,ColMajor>
+struct ei_product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,true,ConjugateLhs, RhsStorageOrder,false,ConjugateRhs,ColMajor>
 {
 
   static EIGEN_DONT_INLINE void run(
-    int rows, int cols,
-    const Scalar* _lhs, int lhsStride,
-    const Scalar* _rhs, int rhsStride,
-    Scalar* res,        int resStride,
+    Index rows, Index cols,
+    const Scalar* _lhs, Index lhsStride,
+    const Scalar* _rhs, Index rhsStride,
+    Scalar* res,        Index resStride,
     Scalar alpha)
   {
-    int size = rows;
+    Index size = rows;
 
-    ei_const_blas_data_mapper<Scalar, LhsStorageOrder> lhs(_lhs,lhsStride);
-    ei_const_blas_data_mapper<Scalar, RhsStorageOrder> rhs(_rhs,rhsStride);
+    ei_const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
+    ei_const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
 
     if (ConjugateRhs)
       alpha = ei_conj(alpha);
 
     typedef ei_product_blocking_traits<Scalar> Blocking;
 
-    int kc = std::min<int>(Blocking::Max_kc,size);  // cache block size along the K direction
-    int mc = std::min<int>(Blocking::Max_mc,rows);  // cache block size along the M direction
+    Index kc = std::min<Index>(Blocking::Max_kc,size);  // cache block size along the K direction
+    Index mc = std::min<Index>(Blocking::Max_mc,rows);  // cache block size along the M direction
 
     Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
     std::size_t sizeB = kc*Blocking::PacketSize*Blocking::nr + kc*cols;
     Scalar* allocatedBlockB = ei_aligned_stack_new(Scalar, sizeB);
     Scalar* blockB = allocatedBlockB + kc*Blocking::PacketSize*Blocking::nr;
 
-    ei_gebp_kernel<Scalar, Blocking::mr, Blocking::nr, ei_conj_helper<ConjugateLhs,ConjugateRhs> > gebp_kernel;
-    ei_symm_pack_lhs<Scalar,Blocking::mr,LhsStorageOrder> pack_lhs;
-    ei_gemm_pack_rhs<Scalar,Blocking::nr,RhsStorageOrder> pack_rhs;
-    ei_gemm_pack_lhs<Scalar,Blocking::mr,LhsStorageOrder==RowMajor?ColMajor:RowMajor, true> pack_lhs_transposed;
+    ei_gebp_kernel<Scalar, Index, Blocking::mr, Blocking::nr, ei_conj_helper<ConjugateLhs,ConjugateRhs> > gebp_kernel;
+    ei_symm_pack_lhs<Scalar, Index, Blocking::mr,LhsStorageOrder> pack_lhs;
+    ei_gemm_pack_rhs<Scalar, Index, Blocking::nr,RhsStorageOrder> pack_rhs;
+    ei_gemm_pack_lhs<Scalar, Index, Blocking::mr,LhsStorageOrder==RowMajor?ColMajor:RowMajor, true> pack_lhs_transposed;
 
-    for(int k2=0; k2<size; k2+=kc)
+    for(Index k2=0; k2<size; k2+=kc)
     {
-      const int actual_kc = std::min(k2+kc,size)-k2;
+      const Index actual_kc = std::min(k2+kc,size)-k2;
 
       // we have selected one row panel of rhs and one column panel of lhs
       // pack rhs's panel into a sequential chunk of memory
@@ -284,9 +284,9 @@
       //  1 - the transposed panel above the diagonal block => transposed packed copy
       //  2 - the diagonal block => special packed copy
       //  3 - the panel below the diagonal block => generic packed copy
-      for(int i2=0; i2<k2; i2+=mc)
+      for(Index i2=0; i2<k2; i2+=mc)
       {
-        const int actual_mc = std::min(i2+mc,k2)-i2;
+        const Index actual_mc = std::min(i2+mc,k2)-i2;
         // transposed packed copy
         pack_lhs_transposed(blockA, &lhs(k2, i2), lhsStride, actual_kc, actual_mc);
 
@@ -294,17 +294,17 @@
       }
       // the block diagonal
       {
-        const int actual_mc = std::min(k2+kc,size)-k2;
+        const Index actual_mc = std::min(k2+kc,size)-k2;
         // symmetric packed copy
         pack_lhs(blockA, &lhs(k2,k2), lhsStride, actual_kc, actual_mc);
 
         gebp_kernel(res+k2, resStride, blockA, blockB, actual_mc, actual_kc, cols);
       }
 
-      for(int i2=k2+kc; i2<size; i2+=mc)
+      for(Index i2=k2+kc; i2<size; i2+=mc)
       {
-        const int actual_mc = std::min(i2+mc,size)-i2;
-        ei_gemm_pack_lhs<Scalar,Blocking::mr,LhsStorageOrder,false>()
+        const Index actual_mc = std::min(i2+mc,size)-i2;
+        ei_gemm_pack_lhs<Scalar, Index, Blocking::mr,LhsStorageOrder,false>()
           (blockA, &lhs(i2, k2), lhsStride, actual_kc, actual_mc);
 
         gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols);
@@ -317,50 +317,50 @@
 };
 
 // matrix * selfadjoint product
-template <typename Scalar,
+template <typename Scalar, typename Index,
           int LhsStorageOrder, bool ConjugateLhs,
           int RhsStorageOrder, bool ConjugateRhs>
-struct ei_product_selfadjoint_matrix<Scalar,LhsStorageOrder,false,ConjugateLhs, RhsStorageOrder,true,ConjugateRhs,ColMajor>
+struct ei_product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,false,ConjugateLhs, RhsStorageOrder,true,ConjugateRhs,ColMajor>
 {
 
   static EIGEN_DONT_INLINE void run(
-    int rows, int cols,
-    const Scalar* _lhs, int lhsStride,
-    const Scalar* _rhs, int rhsStride,
-    Scalar* res,        int resStride,
+    Index rows, Index cols,
+    const Scalar* _lhs, Index lhsStride,
+    const Scalar* _rhs, Index rhsStride,
+    Scalar* res,        Index resStride,
     Scalar alpha)
   {
-    int size = cols;
+    Index size = cols;
 
-    ei_const_blas_data_mapper<Scalar, LhsStorageOrder> lhs(_lhs,lhsStride);
+    ei_const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
 
     if (ConjugateRhs)
       alpha = ei_conj(alpha);
 
     typedef ei_product_blocking_traits<Scalar> Blocking;
 
-    int kc = std::min<int>(Blocking::Max_kc,size);  // cache block size along the K direction
-    int mc = std::min<int>(Blocking::Max_mc,rows);  // cache block size along the M direction
+    Index kc = std::min<Index>(Blocking::Max_kc,size);  // cache block size along the K direction
+    Index mc = std::min<Index>(Blocking::Max_mc,rows);  // cache block size along the M direction
 
     Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
     std::size_t sizeB = kc*Blocking::PacketSize*Blocking::nr + kc*cols;
     Scalar* allocatedBlockB = ei_aligned_stack_new(Scalar, sizeB);
     Scalar* blockB = allocatedBlockB + kc*Blocking::PacketSize*Blocking::nr;
 
-    ei_gebp_kernel<Scalar, Blocking::mr, Blocking::nr, ei_conj_helper<ConjugateLhs,ConjugateRhs> > gebp_kernel;
-    ei_gemm_pack_lhs<Scalar,Blocking::mr,LhsStorageOrder> pack_lhs;
-    ei_symm_pack_rhs<Scalar,Blocking::nr,RhsStorageOrder> pack_rhs;
+    ei_gebp_kernel<Scalar, Index, Blocking::mr, Blocking::nr, ei_conj_helper<ConjugateLhs,ConjugateRhs> > gebp_kernel;
+    ei_gemm_pack_lhs<Scalar, Index, Blocking::mr,LhsStorageOrder> pack_lhs;
+    ei_symm_pack_rhs<Scalar, Index, Blocking::nr,RhsStorageOrder> pack_rhs;
 
-    for(int k2=0; k2<size; k2+=kc)
+    for(Index k2=0; k2<size; k2+=kc)
     {
-      const int actual_kc = std::min(k2+kc,size)-k2;
+      const Index actual_kc = std::min(k2+kc,size)-k2;
 
       pack_rhs(blockB, _rhs, rhsStride, alpha, actual_kc, cols, k2);
 
       // => GEPP
-      for(int i2=0; i2<rows; i2+=mc)
+      for(Index i2=0; i2<rows; i2+=mc)
       {
-        const int actual_mc = std::min(i2+mc,rows)-i2;
+        const Index actual_mc = std::min(i2+mc,rows)-i2;
         pack_lhs(blockA, &lhs(i2, k2), lhsStride, actual_kc, actual_mc);
 
         gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols);
@@ -406,7 +406,7 @@
     Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
                                * RhsBlasTraits::extractScalarFactor(m_rhs);
 
-    ei_product_selfadjoint_matrix<Scalar,
+    ei_product_selfadjoint_matrix<Scalar, Index,
       EIGEN_LOGICAL_XOR(LhsIsUpper,
                         ei_traits<Lhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, LhsIsSelfAdjoint,
       NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(LhsIsUpper,bool(LhsBlasTraits::NeedToConjugate)),
diff --git a/Eigen/src/Core/products/SelfadjointMatrixVector.h b/Eigen/src/Core/products/SelfadjointMatrixVector.h
index 0f829fd..9af310d 100644
--- a/Eigen/src/Core/products/SelfadjointMatrixVector.h
+++ b/Eigen/src/Core/products/SelfadjointMatrixVector.h
@@ -30,15 +30,15 @@
  * the number of load/stores of the result by a factor 2 and to reduce
  * the instruction dependency.
  */
-template<typename Scalar, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs>
+template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs>
 static EIGEN_DONT_INLINE void ei_product_selfadjoint_vector(
-  int size,
-  const Scalar*  lhs, int lhsStride,
-  const Scalar* _rhs, int rhsIncr,
+  Index size,
+  const Scalar*  lhs, Index lhsStride,
+  const Scalar* _rhs, Index rhsIncr,
   Scalar* res, Scalar alpha)
 {
   typedef typename ei_packet_traits<Scalar>::type Packet;
-  const int PacketSize = sizeof(Packet)/sizeof(Scalar);
+  const Index PacketSize = sizeof(Packet)/sizeof(Scalar);
 
   enum {
     IsRowMajor = StorageOrder==RowMajor ? 1 : 0,
@@ -58,16 +58,16 @@
   {
     Scalar* r = ei_aligned_stack_new(Scalar, size);
     const Scalar* it = _rhs;
-    for (int i=0; i<size; ++i, it+=rhsIncr)
+    for (Index i=0; i<size; ++i, it+=rhsIncr)
       r[i] = *it;
     rhs = r;
   }
 
-  int bound = std::max(0,size-8) & 0xfffffffE;
+  Index bound = std::max(Index(0),size-8) & 0xfffffffe;
   if (FirstTriangular)
     bound = size - bound;
 
-  for (int j=FirstTriangular ? bound : 0;
+  for (Index j=FirstTriangular ? bound : 0;
        j<(FirstTriangular ? size : bound);j+=2)
   {
     register const Scalar* EIGEN_RESTRICT A0 = lhs + j*lhsStride;
@@ -136,14 +136,14 @@
     res[j]   += alpha * (t2 + ei_predux(ptmp2));
     res[j+1] += alpha * (t3 + ei_predux(ptmp3));
   }
-  for (int j=FirstTriangular ? 0 : bound;j<(FirstTriangular ? bound : size);j++)
+  for (Index j=FirstTriangular ? 0 : bound;j<(FirstTriangular ? bound : size);j++)
   {
     register const Scalar* EIGEN_RESTRICT A0 = lhs + j*lhsStride;
 
     Scalar t1 = cjAlpha * rhs[j];
     Scalar t2 = 0;
     res[j] += cj0.pmul(A0[j],t1);
-    for (int i=FirstTriangular ? 0 : j+1; i<(FirstTriangular ? j : size); i++) {
+    for (Index i=FirstTriangular ? 0 : j+1; i<(FirstTriangular ? j : size); i++) {
       res[i] += cj0.pmul(A0[i], t1);
       t2 += cj1.pmul(A0[i], rhs[i]);
     }
@@ -187,7 +187,7 @@
 
     ei_assert(dst.innerStride()==1 && "not implemented yet");
 
-    ei_product_selfadjoint_vector<Scalar, (ei_traits<_ActualLhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>
+    ei_product_selfadjoint_vector<Scalar, Index, (ei_traits<_ActualLhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>
       (
         lhs.rows(),                           // size
         &lhs.coeff(0,0),  lhs.outerStride(),  // lhs info
diff --git a/Eigen/src/Core/products/SelfadjointProduct.h b/Eigen/src/Core/products/SelfadjointProduct.h
index 01cd33d..bf835b5 100644
--- a/Eigen/src/Core/products/SelfadjointProduct.h
+++ b/Eigen/src/Core/products/SelfadjointProduct.h
@@ -26,52 +26,52 @@
 #define EIGEN_SELFADJOINT_PRODUCT_H
 
 /**********************************************************************
-* This file implement a self adjoint product: C += A A^T updating only
-* an half of the selfadjoint matrix C.
+* This file implements a self adjoint product: C += A A^T updating only
+* half of the selfadjoint matrix C.
 * It corresponds to the level 3 SYRK Blas routine.
 **********************************************************************/
 
 // forward declarations (defined at the end of this file)
-template<typename Scalar, int mr, int nr, typename Conj, int UpLo>
+template<typename Scalar, typename Index, int mr, int nr, typename Conj, int UpLo>
 struct ei_sybb_kernel;
 
 /* Optimized selfadjoint product (_SYRK) */
-template <typename Scalar,
+template <typename Scalar, typename Index,
           int RhsStorageOrder,
           int ResStorageOrder, bool AAT, int UpLo>
 struct ei_selfadjoint_product;
 
 // as usual if the result is row major => we transpose the product
-template <typename Scalar, int MatStorageOrder, bool AAT, int UpLo>
-struct ei_selfadjoint_product<Scalar,MatStorageOrder, RowMajor, AAT, UpLo>
+template <typename Scalar, typename Index, int MatStorageOrder, bool AAT, int UpLo>
+struct ei_selfadjoint_product<Scalar, Index, MatStorageOrder, RowMajor, AAT, UpLo>
 {
-  static EIGEN_STRONG_INLINE void run(int size, int depth, const Scalar* mat, int matStride, Scalar* res, int resStride, Scalar alpha)
+  static EIGEN_STRONG_INLINE void run(Index size, Index depth, const Scalar* mat, Index matStride, Scalar* res, Index resStride, Scalar alpha)
   {
-    ei_selfadjoint_product<Scalar, MatStorageOrder, ColMajor, !AAT, UpLo==Lower?Upper:Lower>
+    ei_selfadjoint_product<Scalar, Index, MatStorageOrder, ColMajor, !AAT, UpLo==Lower?Upper:Lower>
       ::run(size, depth, mat, matStride, res, resStride, alpha);
   }
 };
 
-template <typename Scalar,
+template <typename Scalar, typename Index,
           int MatStorageOrder, bool AAT, int UpLo>
-struct ei_selfadjoint_product<Scalar,MatStorageOrder, ColMajor, AAT, UpLo>
+struct ei_selfadjoint_product<Scalar, Index, MatStorageOrder, ColMajor, AAT, UpLo>
 {
 
   static EIGEN_DONT_INLINE void run(
-    int size, int depth,
-    const Scalar* _mat, int matStride,
-    Scalar* res,        int resStride,
+    Index size, Index depth,
+    const Scalar* _mat, Index matStride,
+    Scalar* res,        Index resStride,
     Scalar alpha)
   {
-    ei_const_blas_data_mapper<Scalar, MatStorageOrder> mat(_mat,matStride);
+    ei_const_blas_data_mapper<Scalar, Index, MatStorageOrder> mat(_mat,matStride);
 
     if(AAT)
       alpha = ei_conj(alpha);
 
     typedef ei_product_blocking_traits<Scalar> Blocking;
 
-    int kc = std::min<int>(Blocking::Max_kc,depth); // cache block size along the K direction
-    int mc = std::min<int>(Blocking::Max_mc,size);  // cache block size along the M direction
+    Index kc = std::min<Index>(Blocking::Max_kc,depth); // cache block size along the K direction
+    Index mc = std::min<Index>(Blocking::Max_mc,size);  // cache block size along the M direction
 
     Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
     std::size_t sizeB = kc*Blocking::PacketSize*Blocking::nr + kc*size;
@@ -81,21 +81,21 @@
     // note that the actual rhs is the transpose/adjoint of mat
     typedef ei_conj_helper<NumTraits<Scalar>::IsComplex && !AAT, NumTraits<Scalar>::IsComplex && AAT> Conj;
 
-    ei_gebp_kernel<Scalar, Blocking::mr, Blocking::nr, Conj> gebp_kernel;
-    ei_gemm_pack_rhs<Scalar,Blocking::nr,MatStorageOrder==RowMajor ? ColMajor : RowMajor> pack_rhs;
-    ei_gemm_pack_lhs<Scalar,Blocking::mr,MatStorageOrder, false> pack_lhs;
-    ei_sybb_kernel<Scalar, Blocking::mr, Blocking::nr, Conj, UpLo> sybb;
+    ei_gebp_kernel<Scalar, Index, Blocking::mr, Blocking::nr, Conj> gebp_kernel;
+    ei_gemm_pack_rhs<Scalar, Index, Blocking::nr,MatStorageOrder==RowMajor ? ColMajor : RowMajor> pack_rhs;
+    ei_gemm_pack_lhs<Scalar, Index, Blocking::mr,MatStorageOrder, false> pack_lhs;
+    ei_sybb_kernel<Scalar, Index, Blocking::mr, Blocking::nr, Conj, UpLo> sybb;
 
-    for(int k2=0; k2<depth; k2+=kc)
+    for(Index k2=0; k2<depth; k2+=kc)
     {
-      const int actual_kc = std::min(k2+kc,depth)-k2;
+      const Index actual_kc = std::min(k2+kc,depth)-k2;
 
       // note that the actual rhs is the transpose/adjoint of mat
       pack_rhs(blockB, &mat(0,k2), matStride, alpha, actual_kc, size);
 
-      for(int i2=0; i2<size; i2+=mc)
+      for(Index i2=0; i2<size; i2+=mc)
       {
-        const int actual_mc = std::min(i2+mc,size)-i2;
+        const Index actual_mc = std::min(i2+mc,size)-i2;
 
         pack_lhs(blockA, &mat(i2, k2), matStride, actual_kc, actual_mc);
 
@@ -111,8 +111,8 @@
 
         if (UpLo==Upper)
         {
-          int j2 = i2+actual_mc;
-          gebp_kernel(res+resStride*j2+i2, resStride, blockA, blockB+actual_kc*j2, actual_mc, actual_kc, std::max(0,size-j2),
+          Index j2 = i2+actual_mc;
+          gebp_kernel(res+resStride*j2+i2, resStride, blockA, blockB+actual_kc*j2, actual_mc, actual_kc, std::max(Index(0),size-j2),
                       -1, -1, 0, 0, allocatedBlockB);
         }
       }
@@ -138,7 +138,7 @@
 
   enum { IsRowMajor = (ei_traits<MatrixType>::Flags&RowMajorBit) ? 1 : 0 };
 
-  ei_selfadjoint_product<Scalar,
+  ei_selfadjoint_product<Scalar, Index,
     _ActualUType::Flags&RowMajorBit ? RowMajor : ColMajor,
     ei_traits<MatrixType>::Flags&RowMajorBit ? RowMajor : ColMajor,
     !UBlasTraits::NeedToConjugate, UpLo>
@@ -158,23 +158,23 @@
 //   while the selfadjoint block overlapping the diagonal is evaluated into a
 //   small temporary buffer which is then accumulated into the result using a
 //   triangular traversal.
-template<typename Scalar, int mr, int nr, typename Conj, int UpLo>
+template<typename Scalar, typename Index, int mr, int nr, typename Conj, int UpLo>
 struct ei_sybb_kernel
 {
   enum {
     PacketSize = ei_packet_traits<Scalar>::size,
     BlockSize  = EIGEN_ENUM_MAX(mr,nr)
   };
-  void operator()(Scalar* res, int resStride, const Scalar* blockA, const Scalar* blockB, int size, int depth, Scalar* workspace)
+  void operator()(Scalar* res, Index resStride, const Scalar* blockA, const Scalar* blockB, Index size, Index depth, Scalar* workspace)
   {
-    ei_gebp_kernel<Scalar, mr, nr, Conj> gebp_kernel;
+    ei_gebp_kernel<Scalar, Index, mr, nr, Conj> gebp_kernel;
     Matrix<Scalar,BlockSize,BlockSize,ColMajor> buffer;
 
     // let's process the block per panel of actual_mc x BlockSize,
     // again, each is split into three parts, etc.
-    for (int j=0; j<size; j+=BlockSize)
+    for (Index j=0; j<size; j+=BlockSize)
     {
-      int actualBlockSize = std::min<int>(BlockSize,size - j);
+      Index actualBlockSize = std::min<Index>(BlockSize,size - j);
       const Scalar* actual_b = blockB+j*depth;
 
       if(UpLo==Upper)
@@ -182,16 +182,16 @@
 
       // selfadjoint micro block
       {
-        int i = j;
+        Index i = j;
         buffer.setZero();
         // 1 - apply the kernel on the temporary buffer
         gebp_kernel(buffer.data(), BlockSize, blockA+depth*i, actual_b, actualBlockSize, depth, actualBlockSize,
                     -1, -1, 0, 0, workspace);
         // 2 - triangular accumulation
-        for(int j1=0; j1<actualBlockSize; ++j1)
+        for(Index j1=0; j1<actualBlockSize; ++j1)
         {
           Scalar* r = res + (j+j1)*resStride + i;
-          for(int i1=UpLo==Lower ? j1 : 0;
+          for(Index i1=UpLo==Lower ? j1 : 0;
               UpLo==Lower ? i1<actualBlockSize : i1<=j1; ++i1)
             r[i1] += buffer(i1,j1);
         }
@@ -199,7 +199,7 @@
 
       if(UpLo==Lower)
       {
-        int i = j+actualBlockSize;
+        Index i = j+actualBlockSize;
         gebp_kernel(res+j*resStride+i, resStride, blockA+depth*i, actual_b, size-i, depth, actualBlockSize,
                     -1, -1, 0, 0, workspace);
       }
diff --git a/Eigen/src/Core/products/SelfadjointRank2Update.h b/Eigen/src/Core/products/SelfadjointRank2Update.h
index 9b52d5f..e20eb5c 100644
--- a/Eigen/src/Core/products/SelfadjointRank2Update.h
+++ b/Eigen/src/Core/products/SelfadjointRank2Update.h
@@ -29,16 +29,16 @@
  * It corresponds to the Level2 syr2 BLAS routine
  */
 
-template<typename Scalar, typename UType, typename VType, int UpLo>
+template<typename Scalar, typename Index, typename UType, typename VType, int UpLo>
 struct ei_selfadjoint_rank2_update_selector;
 
-template<typename Scalar, typename UType, typename VType>
-struct ei_selfadjoint_rank2_update_selector<Scalar,UType,VType,Lower>
+template<typename Scalar, typename Index, typename UType, typename VType>
+struct ei_selfadjoint_rank2_update_selector<Scalar,Index,UType,VType,Lower>
 {
-  static void run(Scalar* mat, int stride, const UType& u, const VType& v, Scalar alpha)
+  static void run(Scalar* mat, Index stride, const UType& u, const VType& v, Scalar alpha)
   {
-    const int size = u.size();
-    for (int i=0; i<size; ++i)
+    const Index size = u.size();
+    for (Index i=0; i<size; ++i)
     {
       Map<Matrix<Scalar,Dynamic,1> >(mat+stride*i+i, size-i) +=
                         (alpha * ei_conj(u.coeff(i))) * v.tail(size-i)
@@ -47,13 +47,13 @@
   }
 };
 
-template<typename Scalar, typename UType, typename VType>
-struct ei_selfadjoint_rank2_update_selector<Scalar,UType,VType,Upper>
+template<typename Scalar, typename Index, typename UType, typename VType>
+struct ei_selfadjoint_rank2_update_selector<Scalar,Index,UType,VType,Upper>
 {
-  static void run(Scalar* mat, int stride, const UType& u, const VType& v, Scalar alpha)
+  static void run(Scalar* mat, Index stride, const UType& u, const VType& v, Scalar alpha)
   {
-    const int size = u.size();
-    for (int i=0; i<size; ++i)
+    const Index size = u.size();
+    for (Index i=0; i<size; ++i)
       Map<Matrix<Scalar,Dynamic,1> >(mat+stride*i, i+1) +=
                         (alpha * ei_conj(u.coeff(i))) * v.head(i+1)
                       + (alpha * ei_conj(v.coeff(i))) * u.head(i+1);
@@ -84,7 +84,7 @@
                              * VBlasTraits::extractScalarFactor(v.derived());
 
   enum { IsRowMajor = (ei_traits<MatrixType>::Flags&RowMajorBit) ? 1 : 0 };
-  ei_selfadjoint_rank2_update_selector<Scalar,
+  ei_selfadjoint_rank2_update_selector<Scalar, Index,
     typename ei_cleantype<typename ei_conj_expr_if<IsRowMajor ^ UBlasTraits::NeedToConjugate,_ActualUType>::ret>::type,
     typename ei_cleantype<typename ei_conj_expr_if<IsRowMajor ^ VBlasTraits::NeedToConjugate,_ActualVType>::ret>::type,
     (IsRowMajor ? int(UpLo==Upper ? Lower : Upper) : UpLo)>
diff --git a/Eigen/src/Core/products/TriangularMatrixMatrix.h b/Eigen/src/Core/products/TriangularMatrixMatrix.h
index 53e7876..25d9ffe 100644
--- a/Eigen/src/Core/products/TriangularMatrixMatrix.h
+++ b/Eigen/src/Core/products/TriangularMatrixMatrix.h
@@ -52,29 +52,29 @@
 /* Optimized selfadjoint matrix * matrix (_SYMM) product built on top of
  * the general matrix matrix product.
  */
-template <typename Scalar,
+template <typename Scalar, typename Index,
           int Mode, bool LhsIsTriangular,
           int LhsStorageOrder, bool ConjugateLhs,
           int RhsStorageOrder, bool ConjugateRhs,
           int ResStorageOrder>
 struct ei_product_triangular_matrix_matrix;
 
-template <typename Scalar,
+template <typename Scalar, typename Index,
           int Mode, bool LhsIsTriangular,
           int LhsStorageOrder, bool ConjugateLhs,
           int RhsStorageOrder, bool ConjugateRhs>
-struct ei_product_triangular_matrix_matrix<Scalar,Mode,LhsIsTriangular,
+struct ei_product_triangular_matrix_matrix<Scalar,Index,Mode,LhsIsTriangular,
                                            LhsStorageOrder,ConjugateLhs,
                                            RhsStorageOrder,ConjugateRhs,RowMajor>
 {
   static EIGEN_STRONG_INLINE void run(
-    int size, int otherSize,
-    const Scalar* lhs, int lhsStride,
-    const Scalar* rhs, int rhsStride,
-    Scalar* res,       int resStride,
+    Index size, Index otherSize,
+    const Scalar* lhs, Index lhsStride,
+    const Scalar* rhs, Index rhsStride,
+    Scalar* res,       Index resStride,
     Scalar alpha)
   {
-    ei_product_triangular_matrix_matrix<Scalar,
+    ei_product_triangular_matrix_matrix<Scalar, Index,
       (Mode&UnitDiag) | (Mode&Upper) ? Lower : Upper,
       (!LhsIsTriangular),
       RhsStorageOrder==RowMajor ? ColMajor : RowMajor,
@@ -87,25 +87,25 @@
 };
 
 // implements col-major += alpha * op(triangular) * op(general)
-template <typename Scalar, int Mode,
+template <typename Scalar, typename Index, int Mode,
           int LhsStorageOrder, bool ConjugateLhs,
           int RhsStorageOrder, bool ConjugateRhs>
-struct ei_product_triangular_matrix_matrix<Scalar,Mode,true,
+struct ei_product_triangular_matrix_matrix<Scalar,Index,Mode,true,
                                            LhsStorageOrder,ConjugateLhs,
                                            RhsStorageOrder,ConjugateRhs,ColMajor>
 {
 
   static EIGEN_DONT_INLINE void run(
-    int size, int cols,
-    const Scalar* _lhs, int lhsStride,
-    const Scalar* _rhs, int rhsStride,
-    Scalar* res,        int resStride,
+    Index size, Index cols,
+    const Scalar* _lhs, Index lhsStride,
+    const Scalar* _rhs, Index rhsStride,
+    Scalar* res,        Index resStride,
     Scalar alpha)
   {
-    int rows = size;
+    Index rows = size;
 
-    ei_const_blas_data_mapper<Scalar, LhsStorageOrder> lhs(_lhs,lhsStride);
-    ei_const_blas_data_mapper<Scalar, RhsStorageOrder> rhs(_rhs,rhsStride);
+    ei_const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
+    ei_const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
 
     if (ConjugateRhs)
       alpha = ei_conj(alpha);
@@ -116,8 +116,8 @@
       IsLower = (Mode&Lower) == Lower
     };
 
-    int kc = std::min<int>(Blocking::Max_kc/4,size); // cache block size along the K direction
-    int mc = std::min<int>(Blocking::Max_mc,rows);   // cache block size along the M direction
+    Index kc = std::min<Index>(Blocking::Max_kc/4,size); // cache block size along the K direction
+    Index mc = std::min<Index>(Blocking::Max_mc,rows);   // cache block size along the M direction
 
     Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
     std::size_t sizeB = kc*Blocking::PacketSize*Blocking::nr + kc*cols;
@@ -129,16 +129,16 @@
     triangularBuffer.setZero();
     triangularBuffer.diagonal().setOnes();
 
-    ei_gebp_kernel<Scalar, Blocking::mr, Blocking::nr, ei_conj_helper<ConjugateLhs,ConjugateRhs> > gebp_kernel;
-    ei_gemm_pack_lhs<Scalar,Blocking::mr,LhsStorageOrder> pack_lhs;
-    ei_gemm_pack_rhs<Scalar,Blocking::nr,RhsStorageOrder> pack_rhs;
+    ei_gebp_kernel<Scalar, Index, Blocking::mr, Blocking::nr, ei_conj_helper<ConjugateLhs,ConjugateRhs> > gebp_kernel;
+    ei_gemm_pack_lhs<Scalar, Index, Blocking::mr,LhsStorageOrder> pack_lhs;
+    ei_gemm_pack_rhs<Scalar, Index, Blocking::nr,RhsStorageOrder> pack_rhs;
 
-    for(int k2=IsLower ? size : 0;
+    for(Index k2=IsLower ? size : 0;
         IsLower ? k2>0 : k2<size;
         IsLower ? k2-=kc : k2+=kc)
     {
-      const int actual_kc = std::min(IsLower ? k2 : size-k2, kc);
-      int actual_k2 = IsLower ? k2-actual_kc : k2;
+      const Index actual_kc = std::min(IsLower ? k2 : size-k2, kc);
+      Index actual_k2 = IsLower ? k2-actual_kc : k2;
 
       pack_rhs(blockB, &rhs(actual_k2,0), rhsStride, alpha, actual_kc, cols);
 
@@ -149,21 +149,21 @@
       // the block diagonal
       {
         // for each small vertical panels of lhs
-        for (int k1=0; k1<actual_kc; k1+=SmallPanelWidth)
+        for (Index k1=0; k1<actual_kc; k1+=SmallPanelWidth)
         {
-          int actualPanelWidth = std::min<int>(actual_kc-k1, SmallPanelWidth);
-          int lengthTarget = IsLower ? actual_kc-k1-actualPanelWidth : k1;
-          int startBlock   = actual_k2+k1;
-          int blockBOffset = k1;
+          Index actualPanelWidth = std::min<Index>(actual_kc-k1, SmallPanelWidth);
+          Index lengthTarget = IsLower ? actual_kc-k1-actualPanelWidth : k1;
+          Index startBlock   = actual_k2+k1;
+          Index blockBOffset = k1;
 
           // => GEBP with the micro triangular block
           // The trick is to pack this micro block while filling the opposite triangular part with zeros.
           // To this end we do an extra triangular copy to a small temporary buffer
-          for (int k=0;k<actualPanelWidth;++k)
+          for (Index k=0;k<actualPanelWidth;++k)
           {
             if (!(Mode&UnitDiag))
               triangularBuffer.coeffRef(k,k) = lhs(startBlock+k,startBlock+k);
-            for (int i=IsLower ? k+1 : 0; IsLower ? i<actualPanelWidth : i<k; ++i)
+            for (Index i=IsLower ? k+1 : 0; IsLower ? i<actualPanelWidth : i<k; ++i)
               triangularBuffer.coeffRef(i,k) = lhs(startBlock+i,startBlock+k);
           }
           pack_lhs(blockA, triangularBuffer.data(), triangularBuffer.outerStride(), actualPanelWidth, actualPanelWidth);
@@ -174,7 +174,7 @@
           // GEBP with remaining micro panel
           if (lengthTarget>0)
           {
-            int startTarget  = IsLower ? actual_k2+k1+actualPanelWidth : actual_k2;
+            Index startTarget  = IsLower ? actual_k2+k1+actualPanelWidth : actual_k2;
 
             pack_lhs(blockA, &lhs(startTarget,startBlock), lhsStride, actualPanelWidth, lengthTarget);
 
@@ -185,12 +185,12 @@
       }
       // the part below the diagonal => GEPP
       {
-        int start = IsLower ? k2 : 0;
-        int end   = IsLower ? size : actual_k2;
-        for(int i2=start; i2<end; i2+=mc)
+        Index start = IsLower ? k2 : 0;
+        Index end   = IsLower ? size : actual_k2;
+        for(Index i2=start; i2<end; i2+=mc)
         {
-          const int actual_mc = std::min(i2+mc,end)-i2;
-          ei_gemm_pack_lhs<Scalar,Blocking::mr,LhsStorageOrder,false>()
+          const Index actual_mc = std::min(i2+mc,end)-i2;
+          ei_gemm_pack_lhs<Scalar, Index, Blocking::mr,LhsStorageOrder,false>()
             (blockA, &lhs(i2, actual_k2), lhsStride, actual_kc, actual_mc);
 
           gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols);
@@ -205,25 +205,25 @@
 };
 
 // implements col-major += alpha * op(general) * op(triangular)
-template <typename Scalar, int Mode,
+template <typename Scalar, typename Index, int Mode,
           int LhsStorageOrder, bool ConjugateLhs,
           int RhsStorageOrder, bool ConjugateRhs>
-struct ei_product_triangular_matrix_matrix<Scalar,Mode,false,
+struct ei_product_triangular_matrix_matrix<Scalar,Index,Mode,false,
                                            LhsStorageOrder,ConjugateLhs,
                                            RhsStorageOrder,ConjugateRhs,ColMajor>
 {
 
   static EIGEN_DONT_INLINE void run(
-    int size, int rows,
-    const Scalar* _lhs, int lhsStride,
-    const Scalar* _rhs, int rhsStride,
-    Scalar* res,        int resStride,
+    Index size, Index rows,
+    const Scalar* _lhs, Index lhsStride,
+    const Scalar* _rhs, Index rhsStride,
+    Scalar* res,        Index resStride,
     Scalar alpha)
   {
-    int cols = size;
+    Index cols = size;
 
-    ei_const_blas_data_mapper<Scalar, LhsStorageOrder> lhs(_lhs,lhsStride);
-    ei_const_blas_data_mapper<Scalar, RhsStorageOrder> rhs(_rhs,rhsStride);
+    ei_const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
+    ei_const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
 
     if (ConjugateRhs)
       alpha = ei_conj(alpha);
@@ -234,8 +234,8 @@
       IsLower = (Mode&Lower) == Lower
     };
 
-    int kc = std::min<int>(Blocking::Max_kc/4,size); // cache block size along the K direction
-    int mc = std::min<int>(Blocking::Max_mc,rows);   // cache block size along the M direction
+    Index kc = std::min<Index>(Blocking::Max_kc/4,size); // cache block size along the K direction
+    Index mc = std::min<Index>(Blocking::Max_mc,rows);   // cache block size along the M direction
 
     Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
     std::size_t sizeB = kc*Blocking::PacketSize*Blocking::nr + kc*cols;
@@ -246,30 +246,30 @@
     triangularBuffer.setZero();
     triangularBuffer.diagonal().setOnes();
 
-    ei_gebp_kernel<Scalar, Blocking::mr, Blocking::nr, ei_conj_helper<ConjugateLhs,ConjugateRhs> > gebp_kernel;
-    ei_gemm_pack_lhs<Scalar,Blocking::mr,LhsStorageOrder> pack_lhs;
-    ei_gemm_pack_rhs<Scalar,Blocking::nr,RhsStorageOrder> pack_rhs;
-    ei_gemm_pack_rhs<Scalar,Blocking::nr,RhsStorageOrder,true> pack_rhs_panel;
+    ei_gebp_kernel<Scalar, Index, Blocking::mr, Blocking::nr, ei_conj_helper<ConjugateLhs,ConjugateRhs> > gebp_kernel;
+    ei_gemm_pack_lhs<Scalar, Index, Blocking::mr,LhsStorageOrder> pack_lhs;
+    ei_gemm_pack_rhs<Scalar, Index, Blocking::nr,RhsStorageOrder> pack_rhs;
+    ei_gemm_pack_rhs<Scalar, Index, Blocking::nr,RhsStorageOrder,true> pack_rhs_panel;
 
-    for(int k2=IsLower ? 0 : size;
+    for(Index k2=IsLower ? 0 : size;
         IsLower ? k2<size  : k2>0;
         IsLower ? k2+=kc   : k2-=kc)
     {
-      const int actual_kc = std::min(IsLower ? size-k2 : k2, kc);
-      int actual_k2 = IsLower ? k2 : k2-actual_kc;
-      int rs = IsLower ? actual_k2 : size - k2;
+      const Index actual_kc = std::min(IsLower ? size-k2 : k2, kc);
+      Index actual_k2 = IsLower ? k2 : k2-actual_kc;
+      Index rs = IsLower ? actual_k2 : size - k2;
       Scalar* geb = blockB+actual_kc*actual_kc;
 
       pack_rhs(geb, &rhs(actual_k2,IsLower ? 0 : k2), rhsStride, alpha, actual_kc, rs);
 
       // pack the triangular part of the rhs padding the unrolled blocks with zeros
       {
-        for (int j2=0; j2<actual_kc; j2+=SmallPanelWidth)
+        for (Index j2=0; j2<actual_kc; j2+=SmallPanelWidth)
         {
-          int actualPanelWidth = std::min<int>(actual_kc-j2, SmallPanelWidth);
-          int actual_j2 = actual_k2 + j2;
-          int panelOffset = IsLower ? j2+actualPanelWidth : 0;
-          int panelLength = IsLower ? actual_kc-j2-actualPanelWidth : j2;
+          Index actualPanelWidth = std::min<Index>(actual_kc-j2, SmallPanelWidth);
+          Index actual_j2 = actual_k2 + j2;
+          Index panelOffset = IsLower ? j2+actualPanelWidth : 0;
+          Index panelLength = IsLower ? actual_kc-j2-actualPanelWidth : j2;
           // general part
           pack_rhs_panel(blockB+j2*actual_kc,
                          &rhs(actual_k2+panelOffset, actual_j2), rhsStride, alpha,
@@ -277,11 +277,11 @@
                          actual_kc, panelOffset);
 
           // append the triangular part via a temporary buffer
-          for (int j=0;j<actualPanelWidth;++j)
+          for (Index j=0;j<actualPanelWidth;++j)
           {
             if (!(Mode&UnitDiag))
               triangularBuffer.coeffRef(j,j) = rhs(actual_j2+j,actual_j2+j);
-            for (int k=IsLower ? j+1 : 0; IsLower ? k<actualPanelWidth : k<j; ++k)
+            for (Index k=IsLower ? j+1 : 0; IsLower ? k<actualPanelWidth : k<j; ++k)
               triangularBuffer.coeffRef(k,j) = rhs(actual_j2+k,actual_j2+j);
           }
 
@@ -292,18 +292,18 @@
         }
       }
 
-      for (int i2=0; i2<rows; i2+=mc)
+      for (Index i2=0; i2<rows; i2+=mc)
       {
-        const int actual_mc = std::min(mc,rows-i2);
+        const Index actual_mc = std::min(mc,rows-i2);
         pack_lhs(blockA, &lhs(i2, actual_k2), lhsStride, actual_kc, actual_mc);
 
         // triangular kernel
         {
-          for (int j2=0; j2<actual_kc; j2+=SmallPanelWidth)
+          for (Index j2=0; j2<actual_kc; j2+=SmallPanelWidth)
           {
-            int actualPanelWidth = std::min<int>(actual_kc-j2, SmallPanelWidth);
-            int panelLength = IsLower ? actual_kc-j2 : j2+actualPanelWidth;
-            int blockOffset = IsLower ? j2 : 0;
+            Index actualPanelWidth = std::min<Index>(actual_kc-j2, SmallPanelWidth);
+            Index panelLength = IsLower ? actual_kc-j2 : j2+actualPanelWidth;
+            Index blockOffset = IsLower ? j2 : 0;
 
             gebp_kernel(res+i2+(actual_k2+j2)*resStride, resStride,
                         blockA, blockB+j2*actual_kc,
@@ -349,7 +349,7 @@
     Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
                                * RhsBlasTraits::extractScalarFactor(m_rhs);
 
-    ei_product_triangular_matrix_matrix<Scalar,
+    ei_product_triangular_matrix_matrix<Scalar, Index,
       Mode, LhsIsTriangular,
       (ei_traits<_ActualLhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
       (ei_traits<_ActualRhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
diff --git a/Eigen/src/Core/products/TriangularMatrixVector.h b/Eigen/src/Core/products/TriangularMatrixVector.h
index ee4c45c..1a2b183 100644
--- a/Eigen/src/Core/products/TriangularMatrixVector.h
+++ b/Eigen/src/Core/products/TriangularMatrixVector.h
@@ -33,34 +33,35 @@
 struct ei_product_triangular_vector_selector<Lhs,Rhs,Result,Mode,ConjLhs,ConjRhs,ColMajor>
 {
   typedef typename Rhs::Scalar Scalar;
+  typedef typename Rhs::Index Index;
   enum {
     IsLower = ((Mode&Lower)==Lower),
     HasUnitDiag = (Mode & UnitDiag)==UnitDiag
   };
   static EIGEN_DONT_INLINE  void run(const Lhs& lhs, const Rhs& rhs, Result& res, typename ei_traits<Lhs>::Scalar alpha)
   {
-    static const int PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
+    static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
     typename ei_conj_expr_if<ConjLhs,Lhs>::ret cjLhs(lhs);
     typename ei_conj_expr_if<ConjRhs,Rhs>::ret cjRhs(rhs);
 
-    int size = lhs.cols();
-    for (int pi=0; pi<size; pi+=PanelWidth)
+    Index size = lhs.cols();
+    for (Index pi=0; pi<size; pi+=PanelWidth)
     {
-      int actualPanelWidth = std::min(PanelWidth, size-pi);
-      for (int k=0; k<actualPanelWidth; ++k)
+      Index actualPanelWidth = std::min(PanelWidth, size-pi);
+      for (Index k=0; k<actualPanelWidth; ++k)
       {
-        int i = pi + k;
-        int s = IsLower ? (HasUnitDiag ? i+1 : i ) : pi;
-        int r = IsLower ? actualPanelWidth-k : k+1;
+        Index i = pi + k;
+        Index s = IsLower ? (HasUnitDiag ? i+1 : i ) : pi;
+        Index r = IsLower ? actualPanelWidth-k : k+1;
         if ((!HasUnitDiag) || (--r)>0)
           res.segment(s,r) += (alpha * cjRhs.coeff(i)) * cjLhs.col(i).segment(s,r);
         if (HasUnitDiag)
           res.coeffRef(i) += alpha * cjRhs.coeff(i);
       }
-      int r = IsLower ? size - pi - actualPanelWidth : pi;
+      Index r = IsLower ? size - pi - actualPanelWidth : pi;
       if (r>0)
       {
-        int s = IsLower ? pi+actualPanelWidth : 0;
+        Index s = IsLower ? pi+actualPanelWidth : 0;
         ei_cache_friendly_product_colmajor_times_vector<ConjLhs,ConjRhs>(
             r,
             &(lhs.const_cast_derived().coeffRef(s,pi)), lhs.outerStride(),
@@ -76,33 +77,34 @@
 struct ei_product_triangular_vector_selector<Lhs,Rhs,Result,Mode,ConjLhs,ConjRhs,RowMajor>
 {
   typedef typename Rhs::Scalar Scalar;
+  typedef typename Rhs::Index Index;
   enum {
     IsLower = ((Mode&Lower)==Lower),
     HasUnitDiag = (Mode & UnitDiag)==UnitDiag
   };
   static void run(const Lhs& lhs, const Rhs& rhs, Result& res, typename ei_traits<Lhs>::Scalar alpha)
   {
-    static const int PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
+    static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
     typename ei_conj_expr_if<ConjLhs,Lhs>::ret cjLhs(lhs);
     typename ei_conj_expr_if<ConjRhs,Rhs>::ret cjRhs(rhs);
-    int size = lhs.cols();
-    for (int pi=0; pi<size; pi+=PanelWidth)
+    Index size = lhs.cols();
+    for (Index pi=0; pi<size; pi+=PanelWidth)
     {
-      int actualPanelWidth = std::min(PanelWidth, size-pi);
-      for (int k=0; k<actualPanelWidth; ++k)
+      Index actualPanelWidth = std::min(PanelWidth, size-pi);
+      for (Index k=0; k<actualPanelWidth; ++k)
       {
-        int i = pi + k;
-        int s = IsLower ? pi  : (HasUnitDiag ? i+1 : i);
-        int r = IsLower ? k+1 : actualPanelWidth-k;
+        Index i = pi + k;
+        Index s = IsLower ? pi  : (HasUnitDiag ? i+1 : i);
+        Index r = IsLower ? k+1 : actualPanelWidth-k;
         if ((!HasUnitDiag) || (--r)>0)
           res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum();
         if (HasUnitDiag)
           res.coeffRef(i) += alpha * cjRhs.coeff(i);
       }
-      int r = IsLower ? pi : size - pi - actualPanelWidth;
+      Index r = IsLower ? pi : size - pi - actualPanelWidth;
       if (r>0)
       {
-        int s = IsLower ? 0 : pi + actualPanelWidth;
+        Index s = IsLower ? 0 : pi + actualPanelWidth;
         Block<Result,Dynamic,1> target(res,pi,0,actualPanelWidth,1);
         ei_cache_friendly_product_rowmajor_times_vector<ConjLhs,ConjRhs>(
             &(lhs.const_cast_derived().coeffRef(pi,s)), lhs.outerStride(),
diff --git a/Eigen/src/Core/products/TriangularSolverMatrix.h b/Eigen/src/Core/products/TriangularSolverMatrix.h
index 1774081..1d80225 100644
--- a/Eigen/src/Core/products/TriangularSolverMatrix.h
+++ b/Eigen/src/Core/products/TriangularSolverMatrix.h
@@ -26,16 +26,16 @@
 #define EIGEN_TRIANGULAR_SOLVER_MATRIX_H
 
 // if the rhs is row major, let's transpose the product
-template <typename Scalar, int Side, int Mode, bool Conjugate, int TriStorageOrder>
-struct ei_triangular_solve_matrix<Scalar,Side,Mode,Conjugate,TriStorageOrder,RowMajor>
+template <typename Scalar, typename Index, int Side, int Mode, bool Conjugate, int TriStorageOrder>
+struct ei_triangular_solve_matrix<Scalar,Index,Side,Mode,Conjugate,TriStorageOrder,RowMajor>
 {
   static EIGEN_DONT_INLINE void run(
-    int size, int cols,
-    const Scalar*  tri, int triStride,
-    Scalar* _other, int otherStride)
+    Index size, Index cols,
+    const Scalar*  tri, Index triStride,
+    Scalar* _other, Index otherStride)
   {
     ei_triangular_solve_matrix<
-      Scalar, Side==OnTheLeft?OnTheRight:OnTheLeft,
+      Scalar, Index, Side==OnTheLeft?OnTheRight:OnTheLeft,
       (Mode&UnitDiag) | ((Mode&Upper) ? Lower : Upper),
       NumTraits<Scalar>::IsComplex && Conjugate,
       TriStorageOrder==RowMajor ? ColMajor : RowMajor, ColMajor>
@@ -45,17 +45,17 @@
 
 /* Optimized triangular solver with multiple right hand side and the triangular matrix on the left
  */
-template <typename Scalar, int Mode, bool Conjugate, int TriStorageOrder>
-struct ei_triangular_solve_matrix<Scalar,OnTheLeft,Mode,Conjugate,TriStorageOrder,ColMajor>
+template <typename Scalar, typename Index, int Mode, bool Conjugate, int TriStorageOrder>
+struct ei_triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageOrder,ColMajor>
 {
   static EIGEN_DONT_INLINE void run(
-    int size, int otherSize,
-    const Scalar* _tri, int triStride,
-    Scalar* _other, int otherStride)
+    Index size, Index otherSize,
+    const Scalar* _tri, Index triStride,
+    Scalar* _other, Index otherStride)
   {
-    int cols = otherSize;
-    ei_const_blas_data_mapper<Scalar, TriStorageOrder> tri(_tri,triStride);
-    ei_blas_data_mapper<Scalar, ColMajor> other(_other,otherStride);
+    Index cols = otherSize;
+    ei_const_blas_data_mapper<Scalar, Index, TriStorageOrder> tri(_tri,triStride);
+    ei_blas_data_mapper<Scalar, Index, ColMajor> other(_other,otherStride);
 
     typedef ei_product_blocking_traits<Scalar> Blocking;
     enum {
@@ -63,8 +63,8 @@
       IsLower = (Mode&Lower) == Lower
     };
 
-    int kc = std::min<int>(Blocking::Max_kc/4,size); // cache block size along the K direction
-    int mc = std::min<int>(Blocking::Max_mc,size);   // cache block size along the M direction
+    Index kc = std::min<Index>(Blocking::Max_kc/4,size); // cache block size along the K direction
+    Index mc = std::min<Index>(Blocking::Max_mc,size);   // cache block size along the M direction
 
     Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
     std::size_t sizeB = kc*Blocking::PacketSize*Blocking::nr + kc*cols;
@@ -72,15 +72,15 @@
     Scalar* blockB = allocatedBlockB + kc*Blocking::PacketSize*Blocking::nr;
 
     ei_conj_if<Conjugate> conj;
-    ei_gebp_kernel<Scalar, Blocking::mr, Blocking::nr, ei_conj_helper<Conjugate,false> > gebp_kernel;
-    ei_gemm_pack_lhs<Scalar,Blocking::mr,TriStorageOrder> pack_lhs;
-    ei_gemm_pack_rhs<Scalar, Blocking::nr, ColMajor, true> pack_rhs;
+    ei_gebp_kernel<Scalar, Index, Blocking::mr, Blocking::nr, ei_conj_helper<Conjugate,false> > gebp_kernel;
+    ei_gemm_pack_lhs<Scalar, Index, Blocking::mr,TriStorageOrder> pack_lhs;
+    ei_gemm_pack_rhs<Scalar, Index, Blocking::nr, ColMajor, true> pack_rhs;
 
-    for(int k2=IsLower ? 0 : size;
+    for(Index k2=IsLower ? 0 : size;
         IsLower ? k2<size : k2>0;
         IsLower ? k2+=kc : k2-=kc)
     {
-      const int actual_kc = std::min(IsLower ? size-k2 : k2, kc);
+      const Index actual_kc = std::min(IsLower ? size-k2 : k2, kc);
 
       // We have selected and packed a big horizontal panel R1 of rhs. Let B be the packed copy of this panel,
       // and R2 the remaining part of rhs. The corresponding vertical panel of lhs is split into
@@ -97,45 +97,45 @@
       // and the remaining small part A2 which is processed using gebp with appropriate block strides
       {
         // for each small vertical panels of lhs
-        for (int k1=0; k1<actual_kc; k1+=SmallPanelWidth)
+        for (Index k1=0; k1<actual_kc; k1+=SmallPanelWidth)
         {
-          int actualPanelWidth = std::min<int>(actual_kc-k1, SmallPanelWidth);
+          Index actualPanelWidth = std::min<Index>(actual_kc-k1, SmallPanelWidth);
           // tr solve
-          for (int k=0; k<actualPanelWidth; ++k)
+          for (Index k=0; k<actualPanelWidth; ++k)
           {
             // TODO write a small kernel handling this (can be shared with trsv)
-            int i  = IsLower ? k2+k1+k : k2-k1-k-1;
-            int s  = IsLower ? k2+k1 : i+1;
-            int rs = actualPanelWidth - k - 1; // remaining size
+            Index i  = IsLower ? k2+k1+k : k2-k1-k-1;
+            Index s  = IsLower ? k2+k1 : i+1;
+            Index rs = actualPanelWidth - k - 1; // remaining size
 
             Scalar a = (Mode & UnitDiag) ? Scalar(1) : Scalar(1)/conj(tri(i,i));
-            for (int j=0; j<cols; ++j)
+            for (Index j=0; j<cols; ++j)
             {
               if (TriStorageOrder==RowMajor)
               {
                 Scalar b = 0;
                 const Scalar* l = &tri(i,s);
                 Scalar* r = &other(s,j);
-                for (int i3=0; i3<k; ++i3)
+                for (Index i3=0; i3<k; ++i3)
                   b += conj(l[i3]) * r[i3];
 
                 other(i,j) = (other(i,j) - b)*a;
               }
               else
               {
-                int s = IsLower ? i+1 : i-rs;
+                Index s = IsLower ? i+1 : i-rs;
                 Scalar b = (other(i,j) *= a);
                 Scalar* r = &other(s,j);
                 const Scalar* l = &tri(s,i);
-                for (int i3=0;i3<rs;++i3)
+                for (Index i3=0;i3<rs;++i3)
                   r[i3] -= b * conj(l[i3]);
               }
             }
           }
 
-          int lengthTarget = actual_kc-k1-actualPanelWidth;
-          int startBlock   = IsLower ? k2+k1 : k2-k1-actualPanelWidth;
-          int blockBOffset = IsLower ? k1 : lengthTarget;
+          Index lengthTarget = actual_kc-k1-actualPanelWidth;
+          Index startBlock   = IsLower ? k2+k1 : k2-k1-actualPanelWidth;
+          Index blockBOffset = IsLower ? k1 : lengthTarget;
 
           // update the respective rows of B from other
           pack_rhs(blockB, _other+startBlock, otherStride, -1, actualPanelWidth, cols, actual_kc, blockBOffset);
@@ -143,7 +143,7 @@
           // GEBP
           if (lengthTarget>0)
           {
-            int startTarget  = IsLower ? k2+k1+actualPanelWidth : k2-actual_kc;
+            Index startTarget  = IsLower ? k2+k1+actualPanelWidth : k2-actual_kc;
 
             pack_lhs(blockA, &tri(startTarget,startBlock), triStride, actualPanelWidth, lengthTarget);
 
@@ -155,11 +155,11 @@
 
       // R2 = A2 * B => GEPP
       {
-        int start = IsLower ? k2+kc : 0;
-        int end   = IsLower ? size : k2-kc;
-        for(int i2=start; i2<end; i2+=mc)
+        Index start = IsLower ? k2+kc : 0;
+        Index end   = IsLower ? size : k2-kc;
+        for(Index i2=start; i2<end; i2+=mc)
         {
-          const int actual_mc = std::min(mc,end-i2);
+          const Index actual_mc = std::min(mc,end-i2);
           if (actual_mc>0)
           {
             pack_lhs(blockA, &tri(i2, IsLower ? k2 : k2-kc), triStride, actual_kc, actual_mc);
@@ -177,17 +177,17 @@
 
 /* Optimized triangular solver with multiple left hand sides and the trinagular matrix on the right
  */
-template <typename Scalar, int Mode, bool Conjugate, int TriStorageOrder>
-struct ei_triangular_solve_matrix<Scalar,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor>
+template <typename Scalar, typename Index, int Mode, bool Conjugate, int TriStorageOrder>
+struct ei_triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor>
 {
   static EIGEN_DONT_INLINE void run(
-    int size, int otherSize,
-    const Scalar* _tri, int triStride,
-    Scalar* _other, int otherStride)
+    Index size, Index otherSize,
+    const Scalar* _tri, Index triStride,
+    Scalar* _other, Index otherStride)
   {
-    int rows = otherSize;
-    ei_const_blas_data_mapper<Scalar, TriStorageOrder> rhs(_tri,triStride);
-    ei_blas_data_mapper<Scalar, ColMajor> lhs(_other,otherStride);
+    Index rows = otherSize;
+    ei_const_blas_data_mapper<Scalar, Index, TriStorageOrder> rhs(_tri,triStride);
+    ei_blas_data_mapper<Scalar, Index, ColMajor> lhs(_other,otherStride);
 
     typedef ei_product_blocking_traits<Scalar> Blocking;
     enum {
@@ -196,8 +196,8 @@
       IsLower = (Mode&Lower) == Lower
     };
 
-    int kc = std::min<int>(Blocking::Max_kc/4,size); // cache block size along the K direction
-    int mc = std::min<int>(Blocking::Max_mc,size);   // cache block size along the M direction
+    Index kc = std::min<Index>(Blocking::Max_kc/4,size); // cache block size along the K direction
+    Index mc = std::min<Index>(Blocking::Max_mc,size);   // cache block size along the M direction
 
     Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
     std::size_t sizeB = kc*Blocking::PacketSize*Blocking::nr + kc*size;
@@ -205,20 +205,20 @@
     Scalar* blockB = allocatedBlockB + kc*Blocking::PacketSize*Blocking::nr;
 
     ei_conj_if<Conjugate> conj;
-    ei_gebp_kernel<Scalar, Blocking::mr, Blocking::nr, ei_conj_helper<false,Conjugate> > gebp_kernel;
-    ei_gemm_pack_rhs<Scalar,Blocking::nr,RhsStorageOrder> pack_rhs;
-    ei_gemm_pack_rhs<Scalar,Blocking::nr,RhsStorageOrder,true> pack_rhs_panel;
-    ei_gemm_pack_lhs<Scalar, Blocking::mr, ColMajor, false, true> pack_lhs_panel;
+    ei_gebp_kernel<Scalar, Index, Blocking::mr, Blocking::nr, ei_conj_helper<false,Conjugate> > gebp_kernel;
+    ei_gemm_pack_rhs<Scalar, Index, Blocking::nr,RhsStorageOrder> pack_rhs;
+    ei_gemm_pack_rhs<Scalar, Index, Blocking::nr,RhsStorageOrder,true> pack_rhs_panel;
+    ei_gemm_pack_lhs<Scalar, Index, Blocking::mr, ColMajor, false, true> pack_lhs_panel;
 
-    for(int k2=IsLower ? size : 0;
+    for(Index k2=IsLower ? size : 0;
         IsLower ? k2>0 : k2<size;
         IsLower ? k2-=kc : k2+=kc)
     {
-      const int actual_kc = std::min(IsLower ? k2 : size-k2, kc);
-      int actual_k2 = IsLower ? k2-actual_kc : k2 ;
+      const Index actual_kc = std::min(IsLower ? k2 : size-k2, kc);
+      Index actual_k2 = IsLower ? k2-actual_kc : k2 ;
 
-      int startPanel = IsLower ? 0 : k2+actual_kc;
-      int rs = IsLower ? actual_k2 : size - actual_k2 - actual_kc;
+      Index startPanel = IsLower ? 0 : k2+actual_kc;
+      Index rs = IsLower ? actual_k2 : size - actual_k2 - actual_kc;
       Scalar* geb = blockB+actual_kc*actual_kc;
 
       if (rs>0) pack_rhs(geb, &rhs(actual_k2,startPanel), triStride, -1, actual_kc, rs);
@@ -226,12 +226,12 @@
       // triangular packing (we only pack the panels off the diagonal,
       // neglecting the blocks overlapping the diagonal
       {
-        for (int j2=0; j2<actual_kc; j2+=SmallPanelWidth)
+        for (Index j2=0; j2<actual_kc; j2+=SmallPanelWidth)
         {
-          int actualPanelWidth = std::min<int>(actual_kc-j2, SmallPanelWidth);
-          int actual_j2 = actual_k2 + j2;
-          int panelOffset = IsLower ? j2+actualPanelWidth : 0;
-          int panelLength = IsLower ? actual_kc-j2-actualPanelWidth : j2;
+          Index actualPanelWidth = std::min<Index>(actual_kc-j2, SmallPanelWidth);
+          Index actual_j2 = actual_k2 + j2;
+          Index panelOffset = IsLower ? j2+actualPanelWidth : 0;
+          Index panelLength = IsLower ? actual_kc-j2-actualPanelWidth : j2;
 
           if (panelLength>0)
           pack_rhs_panel(blockB+j2*actual_kc,
@@ -241,24 +241,24 @@
         }
       }
 
-      for(int i2=0; i2<rows; i2+=mc)
+      for(Index i2=0; i2<rows; i2+=mc)
       {
-        const int actual_mc = std::min(mc,rows-i2);
+        const Index actual_mc = std::min(mc,rows-i2);
 
         // triangular solver kernel
         {
           // for each small block of the diagonal (=> vertical panels of rhs)
-          for (int j2 = IsLower
-                      ? (actual_kc - ((actual_kc%SmallPanelWidth) ? (actual_kc%SmallPanelWidth)
-                                                                  : SmallPanelWidth))
+          for (Index j2 = IsLower
+                      ? (actual_kc - ((actual_kc%SmallPanelWidth) ? Index(actual_kc%SmallPanelWidth)
+                                                                  : Index(SmallPanelWidth)))
                       : 0;
                IsLower ? j2>=0 : j2<actual_kc;
                IsLower ? j2-=SmallPanelWidth : j2+=SmallPanelWidth)
           {
-            int actualPanelWidth = std::min<int>(actual_kc-j2, SmallPanelWidth);
-            int absolute_j2 = actual_k2 + j2;
-            int panelOffset = IsLower ? j2+actualPanelWidth : 0;
-            int panelLength = IsLower ? actual_kc - j2 - actualPanelWidth : j2;
+            Index actualPanelWidth = std::min<Index>(actual_kc-j2, SmallPanelWidth);
+            Index absolute_j2 = actual_k2 + j2;
+            Index panelOffset = IsLower ? j2+actualPanelWidth : 0;
+            Index panelLength = IsLower ? actual_kc - j2 - actualPanelWidth : j2;
 
             // GEBP
             if(panelLength>0)
@@ -272,20 +272,20 @@
             }
 
             // unblocked triangular solve
-            for (int k=0; k<actualPanelWidth; ++k)
+            for (Index k=0; k<actualPanelWidth; ++k)
             {
-              int j = IsLower ? absolute_j2+actualPanelWidth-k-1 : absolute_j2+k;
+              Index j = IsLower ? absolute_j2+actualPanelWidth-k-1 : absolute_j2+k;
 
               Scalar* r = &lhs(i2,j);
-              for (int k3=0; k3<k; ++k3)
+              for (Index k3=0; k3<k; ++k3)
               {
                 Scalar b = conj(rhs(IsLower ? j+1+k3 : absolute_j2+k3,j));
                 Scalar* a = &lhs(i2,IsLower ? j+1+k3 : absolute_j2+k3);
-                for (int i=0; i<actual_mc; ++i)
+                for (Index i=0; i<actual_mc; ++i)
                   r[i] -= a[i] * b;
               }
               Scalar b = (Mode & UnitDiag) ? Scalar(1) : Scalar(1)/conj(rhs(j,j));
-              for (int i=0; i<actual_mc; ++i)
+              for (Index i=0; i<actual_mc; ++i)
                 r[i] *= b;
             }
 
diff --git a/Eigen/src/Core/util/BlasUtil.h b/Eigen/src/Core/util/BlasUtil.h
index 0fe6d29..6cbd266 100644
--- a/Eigen/src/Core/util/BlasUtil.h
+++ b/Eigen/src/Core/util/BlasUtil.h
@@ -29,29 +29,29 @@
 // implement and control fast level 2 and level 3 BLAS-like routines.
 
 // forward declarations
-template<typename Scalar, int mr, int nr, typename Conj>
+template<typename Scalar, typename Index, int mr, int nr, typename Conj>
 struct ei_gebp_kernel;
 
-template<typename Scalar, int nr, int StorageOrder, bool PanelMode=false>
+template<typename Scalar, typename Index, int nr, int StorageOrder, bool PanelMode=false>
 struct ei_gemm_pack_rhs;
 
-template<typename Scalar, int mr, int StorageOrder, bool Conjugate = false, bool PanelMode = false>
+template<typename Scalar, typename Index, int mr, int StorageOrder, bool Conjugate = false, bool PanelMode = false>
 struct ei_gemm_pack_lhs;
 
 template<
-  typename Scalar,
+  typename Scalar, typename Index,
   int LhsStorageOrder, bool ConjugateLhs,
   int RhsStorageOrder, bool ConjugateRhs,
   int ResStorageOrder>
 struct ei_general_matrix_matrix_product;
 
-template<bool ConjugateLhs, bool ConjugateRhs, typename Scalar, typename RhsType>
+template<bool ConjugateLhs, bool ConjugateRhs, typename Scalar, typename Index, typename RhsType>
 static void ei_cache_friendly_product_colmajor_times_vector(
-  int size, const Scalar* lhs, int lhsStride, const RhsType& rhs, Scalar* res, Scalar alpha);
+  Index size, const Scalar* lhs, Index lhsStride, const RhsType& rhs, Scalar* res, Scalar alpha);
 
-template<bool ConjugateLhs, bool ConjugateRhs, typename Scalar, typename ResType>
+template<bool ConjugateLhs, bool ConjugateRhs, typename Scalar, typename Index, typename ResType>
 static void ei_cache_friendly_product_rowmajor_times_vector(
-  const Scalar* lhs, int lhsStride, const Scalar* rhs, int rhsSize, ResType& res, Scalar alpha);
+  const Scalar* lhs, Index lhsStride, const Scalar* rhs, Index rhsSize, ResType& res, Scalar alpha);
 
 // Provides scalar/packet-wise product and product with accumulation
 // with optional conjugation of the arguments.
@@ -98,29 +98,29 @@
 // Lightweight helper class to access matrix coefficients.
 // Yes, this is somehow redundant with Map<>, but this version is much much lighter,
 // and so I hope better compilation performance (time and code quality).
-template<typename Scalar, int StorageOrder>
+template<typename Scalar, typename Index, int StorageOrder>
 class ei_blas_data_mapper
 {
   public:
-    ei_blas_data_mapper(Scalar* data, int stride) : m_data(data), m_stride(stride) {}
-    EIGEN_STRONG_INLINE Scalar& operator()(int i, int j)
+    ei_blas_data_mapper(Scalar* data, Index stride) : m_data(data), m_stride(stride) {}
+    EIGEN_STRONG_INLINE Scalar& operator()(Index i, Index j)
     { return m_data[StorageOrder==RowMajor ? j + i*m_stride : i + j*m_stride]; }
   protected:
     Scalar* EIGEN_RESTRICT m_data;
-    int m_stride;
+    Index m_stride;
 };
 
 // lightweight helper class to access matrix coefficients (const version)
-template<typename Scalar, int StorageOrder>
+template<typename Scalar, typename Index, int StorageOrder>
 class ei_const_blas_data_mapper
 {
   public:
-    ei_const_blas_data_mapper(const Scalar* data, int stride) : m_data(data), m_stride(stride) {}
-    EIGEN_STRONG_INLINE const Scalar& operator()(int i, int j) const
+    ei_const_blas_data_mapper(const Scalar* data, Index stride) : m_data(data), m_stride(stride) {}
+    EIGEN_STRONG_INLINE const Scalar& operator()(Index i, Index j) const
     { return m_data[StorageOrder==RowMajor ? j + i*m_stride : i + j*m_stride]; }
   protected:
     const Scalar* EIGEN_RESTRICT m_data;
-    int m_stride;
+    Index m_stride;
 };
 
 // Defines various constant controlling level 3 blocking
diff --git a/Eigen/src/Core/util/Macros.h b/Eigen/src/Core/util/Macros.h
index 7871824..312a144 100644
--- a/Eigen/src/Core/util/Macros.h
+++ b/Eigen/src/Core/util/Macros.h
@@ -94,6 +94,14 @@
 #define EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION ColMajor
 #endif
 
+#ifndef EIGEN_DEFAULT_DENSE_INDEX_TYPE
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE std::ptrdiff_t
+#endif
+
+#ifndef EIGEN_DEFAULT_SPARSE_INDEX_TYPE
+#define EIGEN_DEFAULT_SPARSE_INDEX_TYPE int
+#endif
+
 /** Allows to disable some optimizations which might affect the accuracy of the result.
   * Such optimization are enabled by default, and set EIGEN_FAST_MATH to 0 to disable them.
   * They currently include:
@@ -266,6 +274,8 @@
   typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; /*!< \brief The underlying numeric type for composed scalar types. \details In cases where Scalar is e.g. std::complex<T>, T were corresponding to RealScalar. */ \
   typedef typename Base::CoeffReturnType CoeffReturnType; /*!< \brief The return type for coefficient access. \details Depending on whether the object allows direct coefficient access (e.g. for a MatrixXd), this type is either 'const Scalar&' or simply 'Scalar' for objects that do not allow direct coefficient access. */ \
   typedef typename Eigen::ei_nested<Derived>::type Nested; \
+  typedef typename Eigen::ei_traits<Derived>::StorageKind StorageKind; \
+  typedef typename Eigen::ei_index<StorageKind>::type Index; \
   enum { RowsAtCompileTime = Eigen::ei_traits<Derived>::RowsAtCompileTime, \
         ColsAtCompileTime = Eigen::ei_traits<Derived>::ColsAtCompileTime, \
         Flags = Eigen::ei_traits<Derived>::Flags, \
@@ -281,6 +291,8 @@
   typedef typename Base::PacketScalar PacketScalar; \
   typedef typename Base::CoeffReturnType CoeffReturnType; /*!< \brief The return type for coefficient access. \details Depending on whether the object allows direct coefficient access (e.g. for a MatrixXd), this type is either 'const Scalar&' or simply 'Scalar' for objects that do not allow direct coefficient access. */ \
   typedef typename Eigen::ei_nested<Derived>::type Nested; \
+  typedef typename Eigen::ei_traits<Derived>::StorageKind StorageKind; \
+  typedef typename Eigen::ei_index<StorageKind>::type Index; \
   enum { RowsAtCompileTime = Eigen::ei_traits<Derived>::RowsAtCompileTime, \
         ColsAtCompileTime = Eigen::ei_traits<Derived>::ColsAtCompileTime, \
         MaxRowsAtCompileTime = Eigen::ei_traits<Derived>::MaxRowsAtCompileTime, \
diff --git a/Eigen/src/Core/util/Memory.h b/Eigen/src/Core/util/Memory.h
index f5cdd91..6b202db 100644
--- a/Eigen/src/Core/util/Memory.h
+++ b/Eigen/src/Core/util/Memory.h
@@ -379,10 +379,10 @@
   * other hand, we do not assume that the array address is a multiple of sizeof(Scalar), as that fails for
   * example with Scalar=double on certain 32-bit platforms, see bug #79.
   *
-  * There is also the variant ei_first_aligned(const MatrixBase&, Integer) defined in Coeffs.h.
+  * There is also the variant ei_first_aligned(const MatrixBase&) defined in DenseCoeffsBase.h.
   */
-template<typename Scalar, typename Integer>
-inline static Integer ei_first_aligned(const Scalar* array, Integer size)
+template<typename Scalar, typename Index>
+inline static Index ei_first_aligned(const Scalar* array, Index size)
 {
   typedef typename ei_packet_traits<Scalar>::type Packet;
   enum { PacketSize = ei_packet_traits<Scalar>::size,
@@ -403,7 +403,7 @@
   }
   else
   {
-    return std::min<Integer>( (PacketSize - (Integer((size_t(array)/sizeof(Scalar))) & PacketAlignedMask))
+    return std::min<Index>( (PacketSize - (Index((size_t(array)/sizeof(Scalar))) & PacketAlignedMask))
                            & PacketAlignedMask, size);
   }
 }
diff --git a/Eigen/src/Core/util/XprHelper.h b/Eigen/src/Core/util/XprHelper.h
index 667418b..4dee814 100644
--- a/Eigen/src/Core/util/XprHelper.h
+++ b/Eigen/src/Core/util/XprHelper.h
@@ -42,27 +42,35 @@
     ei_no_assignment_operator& operator=(const ei_no_assignment_operator&);
 };
 
-/** \internal If the template parameter Value is Dynamic, this class is just a wrapper around an int variable that
+template<typename StorageKind> struct ei_index {};
+
+template<>
+struct ei_index<Dense>
+{ typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE type; };
+
+typedef typename ei_index<Dense>::type DenseIndex;
+
+/** \internal If the template parameter Value is Dynamic, this class is just a wrapper around a T variable that
   * can be accessed using value() and setValue().
   * Otherwise, this class is an empty structure and value() just returns the template parameter Value.
   */
-template<int Value> class ei_int_if_dynamic
+template<typename T, int Value> class ei_variable_if_dynamic
 {
   public:
-    EIGEN_EMPTY_STRUCT_CTOR(ei_int_if_dynamic)
-    explicit ei_int_if_dynamic(int v) { EIGEN_ONLY_USED_FOR_DEBUG(v); ei_assert(v == Value); }
-    static int value() { return Value; }
-    void setValue(int) {}
+    EIGEN_EMPTY_STRUCT_CTOR(ei_variable_if_dynamic)
+    explicit ei_variable_if_dynamic(T v) { EIGEN_ONLY_USED_FOR_DEBUG(v); ei_assert(v == T(Value)); }
+    static T value() { return T(Value); }
+    void setValue(T) {}
 };
 
-template<> class ei_int_if_dynamic<Dynamic>
+template<typename T> class ei_variable_if_dynamic<T, Dynamic>
 {
-    int m_value;
-    ei_int_if_dynamic() { ei_assert(false); }
+    T m_value;
+    ei_variable_if_dynamic() { ei_assert(false); }
   public:
-    explicit ei_int_if_dynamic(int value) : m_value(value) {}
-    int value() const { return m_value; }
-    void setValue(int value) { m_value = value; }
+    explicit ei_variable_if_dynamic(T value) : m_value(value) {}
+    T value() const { return m_value; }
+    void setValue(T value) { m_value = value; }
 };
 
 template<typename T> struct ei_functor_traits
diff --git a/Eigen/src/Eigen2Support/Block.h b/Eigen/src/Eigen2Support/Block.h
index eb17a27..c5e1a9c 100644
--- a/Eigen/src/Eigen2Support/Block.h
+++ b/Eigen/src/Eigen2Support/Block.h
@@ -40,11 +40,11 @@
   * when it is applied to a fixed-size matrix, it inherits a fixed maximal size,
   * which means that evaluating it does not cause a dynamic memory allocation.
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 inline Block<Derived> DenseBase<Derived>
-  ::corner(CornerType type, int cRows, int cCols)
+  ::corner(CornerType type, Index cRows, Index cCols)
 {
   switch(type)
   {
@@ -61,10 +61,10 @@
   }
 }
 
-/** This is the const version of corner(CornerType, int, int).*/
+/** This is the const version of corner(CornerType, Index, Index).*/
 template<typename Derived>
 inline const Block<Derived>
-DenseBase<Derived>::corner(CornerType type, int cRows, int cCols) const
+DenseBase<Derived>::corner(CornerType type, Index cRows, Index cCols) const
 {
   switch(type)
   {
@@ -91,7 +91,7 @@
   * Example: \include MatrixBase_template_int_int_corner_enum.cpp
   * Output: \verbinclude MatrixBase_template_int_int_corner_enum.out
   *
-  * \sa class Block, block(int,int,int,int)
+  * \sa class Block, block(Index,Index,Index,Index)
   */
 template<typename Derived>
 template<int CRows, int CCols>
diff --git a/Eigen/src/Eigen2Support/Minor.h b/Eigen/src/Eigen2Support/Minor.h
index e7e164a..3bf913b 100644
--- a/Eigen/src/Eigen2Support/Minor.h
+++ b/Eigen/src/Eigen2Support/Minor.h
@@ -44,6 +44,7 @@
 {
   typedef typename ei_nested<MatrixType>::type MatrixTypeNested;
   typedef typename ei_unref<MatrixTypeNested>::type _MatrixTypeNested;
+  typedef typename MatrixType::StorageKind StorageKind;
   enum {
     RowsAtCompileTime = (MatrixType::RowsAtCompileTime != Dynamic) ?
                           int(MatrixType::RowsAtCompileTime) - 1 : Dynamic,
@@ -68,7 +69,7 @@
     EIGEN_DENSE_PUBLIC_INTERFACE(Minor)
 
     inline Minor(const MatrixType& matrix,
-                       int row, int col)
+                       Index row, Index col)
       : m_matrix(matrix), m_row(row), m_col(col)
     {
       ei_assert(row >= 0 && row < matrix.rows()
@@ -77,22 +78,22 @@
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Minor)
 
-    inline int rows() const { return m_matrix.rows() - 1; }
-    inline int cols() const { return m_matrix.cols() - 1; }
+    inline Index rows() const { return m_matrix.rows() - 1; }
+    inline Index cols() const { return m_matrix.cols() - 1; }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       return m_matrix.const_cast_derived().coeffRef(row + (row >= m_row), col + (col >= m_col));
     }
 
-    inline const Scalar coeff(int row, int col) const
+    inline const Scalar coeff(Index row, Index col) const
     {
       return m_matrix.coeff(row + (row >= m_row), col + (col >= m_col));
     }
 
   protected:
     const typename MatrixType::Nested m_matrix;
-    const int m_row, m_col;
+    const Index m_row, m_col;
 };
 
 /** \nonstableyet
@@ -107,7 +108,7 @@
   */
 template<typename Derived>
 inline Minor<Derived>
-MatrixBase<Derived>::minor(int row, int col)
+MatrixBase<Derived>::minor(Index row, Index col)
 {
   return Minor<Derived>(derived(), row, col);
 }
@@ -116,7 +117,7 @@
   * This is the const version of minor(). */
 template<typename Derived>
 inline const Minor<Derived>
-MatrixBase<Derived>::minor(int row, int col) const
+MatrixBase<Derived>::minor(Index row, Index col) const
 {
   return Minor<Derived>(derived(), row, col);
 }
diff --git a/Eigen/src/Eigen2Support/VectorBlock.h b/Eigen/src/Eigen2Support/VectorBlock.h
index 4ddc425..c6ac434 100644
--- a/Eigen/src/Eigen2Support/VectorBlock.h
+++ b/Eigen/src/Eigen2Support/VectorBlock.h
@@ -26,37 +26,37 @@
 #ifndef EIGEN_VECTORBLOCK2_H
 #define EIGEN_VECTORBLOCK2_H
 
-/** \deprecated use DenseMase::head(int) */
+/** \deprecated use DenseMase::head(Index) */
 template<typename Derived>
 inline VectorBlock<Derived>
-MatrixBase<Derived>::start(int size)
+MatrixBase<Derived>::start(Index size)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived>(derived(), 0, size);
 }
 
-/** \deprecated use DenseMase::head(int) */
+/** \deprecated use DenseMase::head(Index) */
 template<typename Derived>
 inline const VectorBlock<Derived>
-MatrixBase<Derived>::start(int size) const
+MatrixBase<Derived>::start(Index size) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived>(derived(), 0, size);
 }
 
-/** \deprecated use DenseMase::tail(int) */
+/** \deprecated use DenseMase::tail(Index) */
 template<typename Derived>
 inline VectorBlock<Derived>
-MatrixBase<Derived>::end(int size)
+MatrixBase<Derived>::end(Index size)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived>(derived(), this->size() - size, size);
 }
 
-/** \deprecated use DenseMase::tail(int) */
+/** \deprecated use DenseMase::tail(Index) */
 template<typename Derived>
 inline const VectorBlock<Derived>
-MatrixBase<Derived>::end(int size) const
+MatrixBase<Derived>::end(Index size) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return VectorBlock<Derived>(derived(), this->size() - size, size);
diff --git a/Eigen/src/Eigenvalues/ComplexEigenSolver.h b/Eigen/src/Eigenvalues/ComplexEigenSolver.h
index 5f956e4..f56815c 100644
--- a/Eigen/src/Eigenvalues/ComplexEigenSolver.h
+++ b/Eigen/src/Eigenvalues/ComplexEigenSolver.h
@@ -68,6 +68,7 @@
     /** \brief Scalar type for matrices of type \p _MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename MatrixType::Index Index;
 
     /** \brief Complex scalar type for \p _MatrixType. 
       *
@@ -110,7 +111,7 @@
       * according to the specified problem \a size.
       * \sa ComplexEigenSolver()
       */
-    ComplexEigenSolver(int size)
+    ComplexEigenSolver(Index size)
             : m_eivec(size, size),
               m_eivalues(size),
               m_schur(size),
@@ -216,7 +217,7 @@
 {
   // this code is inspired from Jampack
   assert(matrix.cols() == matrix.rows());
-  const int n = matrix.cols();
+  const Index n = matrix.cols();
   const RealScalar matrixnorm = matrix.norm();
 
   // Step 1: Do a complex Schur decomposition, A = U T U^*
@@ -227,11 +228,11 @@
   // Step 2: Compute X such that T = X D X^(-1), where D is the diagonal of T.
   // The matrix X is unit triangular.
   m_matX = EigenvectorType::Zero(n, n);
-  for(int k=n-1 ; k>=0 ; k--)
+  for(Index k=n-1 ; k>=0 ; k--)
   {
     m_matX.coeffRef(k,k) = ComplexScalar(1.0,0.0);
     // Compute X(i,k) using the (i,k) entry of the equation X T = D X
-    for(int i=k-1 ; i>=0 ; i--)
+    for(Index i=k-1 ; i>=0 ; i--)
     {
       m_matX.coeffRef(i,k) = -m_schur.matrixT().coeff(i,k);
       if(k-i-1>0)
@@ -250,16 +251,16 @@
   // Step 3: Compute V as V = U X; now A = U T U^* = U X D X^(-1) U^* = V D V^(-1)
   m_eivec.noalias() = m_schur.matrixU() * m_matX;
   // .. and normalize the eigenvectors
-  for(int k=0 ; k<n ; k++)
+  for(Index k=0 ; k<n ; k++)
   {
     m_eivec.col(k).normalize();
   }
   m_isInitialized = true;
 
   // Step 4: Sort the eigenvalues
-  for (int i=0; i<n; i++)
+  for (Index i=0; i<n; i++)
   {
-    int k;
+    Index k;
     m_eivalues.cwiseAbs().tail(n-i).minCoeff(&k);
     if (k != 0)
     {
diff --git a/Eigen/src/Eigenvalues/ComplexSchur.h b/Eigen/src/Eigenvalues/ComplexSchur.h
index c69e3ea..673cb46 100644
--- a/Eigen/src/Eigenvalues/ComplexSchur.h
+++ b/Eigen/src/Eigenvalues/ComplexSchur.h
@@ -71,8 +71,8 @@
 
     /** \brief Scalar type for matrices of type \p _MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
-
     typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename MatrixType::Index Index;
 
     /** \brief Complex scalar type for \p _MatrixType. 
       *
@@ -100,7 +100,7 @@
       *
       * \sa compute() for an example.
       */
-    ComplexSchur(int size = RowsAtCompileTime==Dynamic ? 1 : RowsAtCompileTime)
+    ComplexSchur(Index size = RowsAtCompileTime==Dynamic ? 1 : RowsAtCompileTime)
       : m_matT(size,size),
         m_matU(size,size),
         m_hess(size),
@@ -197,8 +197,8 @@
     bool m_matUisUptodate;
 
   private:  
-    bool subdiagonalEntryIsNeglegible(int i);
-    ComplexScalar computeShift(int iu, int iter);
+    bool subdiagonalEntryIsNeglegible(Index i);
+    ComplexScalar computeShift(Index iu, Index iter);
     void reduceToTriangularForm(bool skipU);
     friend struct ei_complex_schur_reduce_to_hessenberg<MatrixType, NumTraits<Scalar>::IsComplex>;
 };
@@ -244,7 +244,7 @@
   * compared to m_matT(i,i) and m_matT(j,j), then set it to zero and
   * return true, else return false. */
 template<typename MatrixType>
-inline bool ComplexSchur<MatrixType>::subdiagonalEntryIsNeglegible(int i)
+inline bool ComplexSchur<MatrixType>::subdiagonalEntryIsNeglegible(Index i)
 {
   RealScalar d = ei_norm1(m_matT.coeff(i,i)) + ei_norm1(m_matT.coeff(i+1,i+1));
   RealScalar sd = ei_norm1(m_matT.coeff(i+1,i));
@@ -259,7 +259,7 @@
 
 /** Compute the shift in the current QR iteration. */
 template<typename MatrixType>
-typename ComplexSchur<MatrixType>::ComplexScalar ComplexSchur<MatrixType>::computeShift(int iu, int iter)
+typename ComplexSchur<MatrixType>::ComplexScalar ComplexSchur<MatrixType>::computeShift(Index iu, Index iter)
 {
   if (iter == 10 || iter == 20) 
   {
@@ -356,9 +356,9 @@
   // Rows 0,...,il-1 are decoupled from the rest because m_matT(il,il-1) is zero. 
   // Rows il,...,iu is the part we are working on (the active submatrix).
   // Rows iu+1,...,end are already brought in triangular form.
-  int iu = m_matT.cols() - 1;
-  int il;
-  int iter = 0; // number of iterations we are working on the (iu,iu) element
+  Index iu = m_matT.cols() - 1;
+  Index il;
+  Index iter = 0; // number of iterations we are working on the (iu,iu) element
 
   while(true)
   {
@@ -395,7 +395,7 @@
     m_matT.topRows(std::min(il+2,iu)+1).applyOnTheRight(il, il+1, rot);
     if(!skipU) m_matU.applyOnTheRight(il, il+1, rot);
 
-    for(int i=il+1 ; i<iu ; i++)
+    for(Index i=il+1 ; i<iu ; i++)
     {
       rot.makeGivens(m_matT.coeffRef(i,i-1), m_matT.coeffRef(i+1,i-1), &m_matT.coeffRef(i,i-1));
       m_matT.coeffRef(i+1,i-1) = ComplexScalar(0);
diff --git a/Eigen/src/Eigenvalues/EigenSolver.h b/Eigen/src/Eigenvalues/EigenSolver.h
index b619dc2..5400fda 100644
--- a/Eigen/src/Eigenvalues/EigenSolver.h
+++ b/Eigen/src/Eigenvalues/EigenSolver.h
@@ -90,6 +90,7 @@
     /** \brief Scalar type for matrices of type \p _MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename MatrixType::Index Index;
 
     /** \brief Complex scalar type for \p _MatrixType. 
       *
@@ -128,7 +129,7 @@
       * according to the specified problem \a size.
       * \sa EigenSolver()
       */
-    EigenSolver(int size)
+    EigenSolver(Index size)
       : m_eivec(size, size),
         m_eivalues(size),
         m_isInitialized(false),
@@ -285,9 +286,9 @@
 MatrixType EigenSolver<MatrixType>::pseudoEigenvalueMatrix() const
 {
   ei_assert(m_isInitialized && "EigenSolver is not initialized.");
-  int n = m_eivec.cols();
+  Index n = m_eivec.cols();
   MatrixType matD = MatrixType::Zero(n,n);
-  for (int i=0; i<n; ++i)
+  for (Index i=0; i<n; ++i)
   {
     if (ei_isMuchSmallerThan(ei_imag(m_eivalues.coeff(i)), ei_real(m_eivalues.coeff(i))))
       matD.coeffRef(i,i) = ei_real(m_eivalues.coeff(i));
@@ -305,9 +306,9 @@
 typename EigenSolver<MatrixType>::EigenvectorsType EigenSolver<MatrixType>::eigenvectors() const
 {
   ei_assert(m_isInitialized && "EigenSolver is not initialized.");
-  int n = m_eivec.cols();
+  Index n = m_eivec.cols();
   EigenvectorsType matV(n,n);
-  for (int j=0; j<n; ++j)
+  for (Index j=0; j<n; ++j)
   {
     if (ei_isMuchSmallerThan(ei_imag(m_eivalues.coeff(j)), ei_real(m_eivalues.coeff(j))))
     {
@@ -317,7 +318,7 @@
     else
     {
       // we have a pair of complex eigen values
-      for (int i=0; i<n; ++i)
+      for (Index i=0; i<n; ++i)
       {
         matV.coeffRef(i,j)   = ComplexScalar(m_eivec.coeff(i,j),  m_eivec.coeff(i,j+1));
         matV.coeffRef(i,j+1) = ComplexScalar(m_eivec.coeff(i,j), -m_eivec.coeff(i,j+1));
@@ -342,7 +343,7 @@
 
   // Compute eigenvalues from matT
   m_eivalues.resize(matrix.cols());
-  int i = 0;
+  Index i = 0;
   while (i < matrix.cols()) 
   {
     if (i == matrix.cols() - 1 || m_matT.coeff(i+1, i) == Scalar(0)) 
@@ -390,14 +391,14 @@
 template<typename MatrixType>
 void EigenSolver<MatrixType>::computeEigenvectors()
 {
-  const int size = m_eivec.cols();
+  const Index size = m_eivec.cols();
   const Scalar eps = NumTraits<Scalar>::epsilon();
 
   // inefficient! this is already computed in RealSchur
   Scalar norm = 0.0;
-  for (int j = 0; j < size; ++j)
+  for (Index j = 0; j < size; ++j)
   {
-    norm += m_matT.row(j).segment(std::max(j-1,0), size-std::max(j-1,0)).cwiseAbs().sum();
+    norm += m_matT.row(j).segment(std::max(j-1,Index(0)), size-std::max(j-1,Index(0))).cwiseAbs().sum();
   }
   
   // Backsubstitute to find vectors of upper triangular form
@@ -406,7 +407,7 @@
       return;
   }
 
-  for (int n = size-1; n >= 0; n--)
+  for (Index n = size-1; n >= 0; n--)
   {
     Scalar p = m_eivalues.coeff(n).real();
     Scalar q = m_eivalues.coeff(n).imag();
@@ -415,10 +416,10 @@
     if (q == 0)
     {
       Scalar lastr=0, lastw=0;
-      int l = n;
+      Index l = n;
 
       m_matT.coeffRef(n,n) = 1.0;
-      for (int i = n-1; i >= 0; i--)
+      for (Index i = n-1; i >= 0; i--)
       {
         Scalar w = m_matT.coeff(i,i) - p;
         Scalar r = m_matT.row(i).segment(l,n-l+1).dot(m_matT.col(n).segment(l, n-l+1));
@@ -461,7 +462,7 @@
     else if (q < 0) // Complex vector
     {
       Scalar lastra=0, lastsa=0, lastw=0;
-      int l = n-1;
+      Index l = n-1;
 
       // Last vector component imaginary so matrix is triangular
       if (ei_abs(m_matT.coeff(n,n-1)) > ei_abs(m_matT.coeff(n-1,n)))
@@ -477,7 +478,7 @@
       }
       m_matT.coeffRef(n,n-1) = 0.0;
       m_matT.coeffRef(n,n) = 1.0;
-      for (int i = n-2; i >= 0; i--)
+      for (Index i = n-2; i >= 0; i--)
       {
         Scalar ra = m_matT.row(i).segment(l, n-l+1).dot(m_matT.col(n-1).segment(l, n-l+1));
         Scalar sa = m_matT.row(i).segment(l, n-l+1).dot(m_matT.col(n).segment(l, n-l+1));
@@ -535,7 +536,7 @@
   }
 
   // Back transformation to get eigenvectors of original matrix
-  for (int j = size-1; j >= 0; j--)
+  for (Index j = size-1; j >= 0; j--)
   {
     m_tmp.noalias() = m_eivec.leftCols(j+1) * m_matT.col(j).segment(0, j+1);
     m_eivec.col(j) = m_tmp;
diff --git a/Eigen/src/Eigenvalues/HessenbergDecomposition.h b/Eigen/src/Eigenvalues/HessenbergDecomposition.h
index 7a80aed..1111ffb 100644
--- a/Eigen/src/Eigenvalues/HessenbergDecomposition.h
+++ b/Eigen/src/Eigenvalues/HessenbergDecomposition.h
@@ -81,6 +81,7 @@
 
     /** \brief Scalar type for matrices of type #MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::Index Index;
 
     /** \brief Type for vector of Householder coefficients.
       *
@@ -104,7 +105,7 @@
       *
       * \sa compute() for an example.
       */
-    HessenbergDecomposition(int size = Size==Dynamic ? 2 : Size)
+    HessenbergDecomposition(Index size = Size==Dynamic ? 2 : Size)
       : m_matrix(size,size),
         m_temp(size)
     {
@@ -276,12 +277,12 @@
 void HessenbergDecomposition<MatrixType>::_compute(MatrixType& matA, CoeffVectorType& hCoeffs, VectorType& temp)
 {
   assert(matA.rows()==matA.cols());
-  int n = matA.rows();
+  Index n = matA.rows();
   temp.resize(n);
-  for (int i = 0; i<n-1; ++i)
+  for (Index i = 0; i<n-1; ++i)
   {
     // let's consider the vector v = i-th column starting at position i+1
-    int remainingSize = n-i-1;
+    Index remainingSize = n-i-1;
     RealScalar beta;
     Scalar h;
     matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
@@ -321,6 +322,7 @@
 template<typename MatrixType> struct HessenbergDecompositionMatrixHReturnType
 : public ReturnByValue<HessenbergDecompositionMatrixHReturnType<MatrixType> >
 {
+    typedef typename MatrixType::Index Index;
   public:
     /** \brief Constructor.
       *
@@ -337,13 +339,13 @@
     inline void evalTo(ResultType& result) const
     {
       result = m_hess.packedMatrix();
-      int n = result.rows();
+      Index n = result.rows();
       if (n>2)
 	result.bottomLeftCorner(n-2, n-2).template triangularView<Lower>().setZero();
     }
 
-    int rows() const { return m_hess.packedMatrix().rows(); }
-    int cols() const { return m_hess.packedMatrix().cols(); }
+    Index rows() const { return m_hess.packedMatrix().rows(); }
+    Index cols() const { return m_hess.packedMatrix().cols(); }
 
   protected:
     const HessenbergDecomposition<MatrixType>& m_hess;
diff --git a/Eigen/src/Eigenvalues/RealSchur.h b/Eigen/src/Eigenvalues/RealSchur.h
index f9d49c6..92ff448 100644
--- a/Eigen/src/Eigenvalues/RealSchur.h
+++ b/Eigen/src/Eigenvalues/RealSchur.h
@@ -77,6 +77,8 @@
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef std::complex<typename NumTraits<Scalar>::Real> ComplexScalar;
+    typedef typename MatrixType::Index Index;
+
     typedef Matrix<ComplexScalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> EigenvalueType;
     typedef Matrix<Scalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> ColumnVectorType;
 
@@ -91,7 +93,7 @@
       *
       * \sa compute() for an example.
       */
-    RealSchur(int size = RowsAtCompileTime==Dynamic ? 1 : RowsAtCompileTime)
+    RealSchur(Index size = RowsAtCompileTime==Dynamic ? 1 : RowsAtCompileTime)
             : m_matT(size, size),
               m_matU(size, size),
               m_workspaceVector(size),
@@ -177,11 +179,11 @@
     typedef Matrix<Scalar,3,1> Vector3s;
 
     Scalar computeNormOfT();
-    int findSmallSubdiagEntry(int iu, Scalar norm);
-    void splitOffTwoRows(int iu, Scalar exshift);
-    void computeShift(int iu, int iter, Scalar& exshift, Vector3s& shiftInfo);
-    void initFrancisQRStep(int il, int iu, const Vector3s& shiftInfo, int& im, Vector3s& firstHouseholderVector);
-    void performFrancisQRStep(int il, int im, int iu, const Vector3s& firstHouseholderVector, Scalar* workspace);
+    Index findSmallSubdiagEntry(Index iu, Scalar norm);
+    void splitOffTwoRows(Index iu, Scalar exshift);
+    void computeShift(Index iu, Index iter, Scalar& exshift, Vector3s& shiftInfo);
+    void initFrancisQRStep(Index il, Index iu, const Vector3s& shiftInfo, Index& im, Vector3s& firstHouseholderVector);
+    void performFrancisQRStep(Index il, Index im, Index iu, const Vector3s& firstHouseholderVector, Scalar* workspace);
 };
 
 
@@ -204,14 +206,14 @@
   // Rows 0,...,il-1 are decoupled from the rest because m_matT(il,il-1) is zero. 
   // Rows il,...,iu is the part we are working on (the active window).
   // Rows iu+1,...,end are already brought in triangular form.
-  int iu = m_matU.cols() - 1;
-  int iter = 0; // iteration count
+  Index iu = m_matU.cols() - 1;
+  Index iter = 0; // iteration count
   Scalar exshift = 0.0; // sum of exceptional shifts
   Scalar norm = computeNormOfT();
 
   while (iu >= 0)
   {
-    int il = findSmallSubdiagEntry(iu, norm);
+    Index il = findSmallSubdiagEntry(iu, norm);
 
     // Check for convergence
     if (il == iu) // One root found
@@ -233,7 +235,7 @@
       Vector3s firstHouseholderVector, shiftInfo;
       computeShift(iu, iter, exshift, shiftInfo);
       iter = iter + 1;   // (Could check iteration count here.)
-      int im;
+      Index im;
       initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector);
       performFrancisQRStep(il, im, iu, firstHouseholderVector, workspace);
     }
@@ -246,21 +248,21 @@
 template<typename MatrixType>
 inline typename MatrixType::Scalar RealSchur<MatrixType>::computeNormOfT()
 {
-  const int size = m_matU.cols();
+  const Index size = m_matU.cols();
   // FIXME to be efficient the following would requires a triangular reduxion code
   // Scalar norm = m_matT.upper().cwiseAbs().sum() 
   //               + m_matT.bottomLeftCorner(size-1,size-1).diagonal().cwiseAbs().sum();
   Scalar norm = 0.0;
-  for (int j = 0; j < size; ++j)
-    norm += m_matT.row(j).segment(std::max(j-1,0), size-std::max(j-1,0)).cwiseAbs().sum();
+  for (Index j = 0; j < size; ++j)
+    norm += m_matT.row(j).segment(std::max(j-1,Index(0)), size-std::max(j-1,Index(0))).cwiseAbs().sum();
   return norm;
 }
 
 /** \internal Look for single small sub-diagonal element and returns its index */
 template<typename MatrixType>
-inline int RealSchur<MatrixType>::findSmallSubdiagEntry(int iu, Scalar norm)
+inline typename MatrixType::Index RealSchur<MatrixType>::findSmallSubdiagEntry(Index iu, Scalar norm)
 {
-  int res = iu;
+  Index res = iu;
   while (res > 0)
   {
     Scalar s = ei_abs(m_matT.coeff(res-1,res-1)) + ei_abs(m_matT.coeff(res,res));
@@ -275,9 +277,9 @@
 
 /** \internal Update T given that rows iu-1 and iu decouple from the rest. */
 template<typename MatrixType>
-inline void RealSchur<MatrixType>::splitOffTwoRows(int iu, Scalar exshift)
+inline void RealSchur<MatrixType>::splitOffTwoRows(Index iu, Scalar exshift)
 {
-  const int size = m_matU.cols();
+  const Index size = m_matU.cols();
 
   // The eigenvalues of the 2x2 matrix [a b; c d] are 
   // trace +/- sqrt(discr/4) where discr = tr^2 - 4*det, tr = a + d, det = ad - bc
@@ -307,7 +309,7 @@
 
 /** \internal Form shift in shiftInfo, and update exshift if an exceptional shift is performed. */
 template<typename MatrixType>
-inline void RealSchur<MatrixType>::computeShift(int iu, int iter, Scalar& exshift, Vector3s& shiftInfo)
+inline void RealSchur<MatrixType>::computeShift(Index iu, Index iter, Scalar& exshift, Vector3s& shiftInfo)
 {
   shiftInfo.coeffRef(0) = m_matT.coeff(iu,iu);
   shiftInfo.coeffRef(1) = m_matT.coeff(iu-1,iu-1);
@@ -317,7 +319,7 @@
   if (iter == 10)
   {
     exshift += shiftInfo.coeff(0);
-    for (int i = 0; i <= iu; ++i)
+    for (Index i = 0; i <= iu; ++i)
       m_matT.coeffRef(i,i) -= shiftInfo.coeff(0);
     Scalar s = ei_abs(m_matT.coeff(iu,iu-1)) + ei_abs(m_matT.coeff(iu-1,iu-2));
     shiftInfo.coeffRef(0) = Scalar(0.75) * s;
@@ -338,7 +340,7 @@
       s = s + (shiftInfo.coeff(1) - shiftInfo.coeff(0)) / Scalar(2.0);
       s = shiftInfo.coeff(0) - shiftInfo.coeff(2) / s;
       exshift += s;
-      for (int i = 0; i <= iu; ++i)
+      for (Index i = 0; i <= iu; ++i)
         m_matT.coeffRef(i,i) -= s;
       shiftInfo.setConstant(Scalar(0.964));
     }
@@ -347,7 +349,7 @@
 
 /** \internal Compute index im at which Francis QR step starts and the first Householder vector. */
 template<typename MatrixType>
-inline void RealSchur<MatrixType>::initFrancisQRStep(int il, int iu, const Vector3s& shiftInfo, int& im, Vector3s& firstHouseholderVector)
+inline void RealSchur<MatrixType>::initFrancisQRStep(Index il, Index iu, const Vector3s& shiftInfo, Index& im, Vector3s& firstHouseholderVector)
 {
   Vector3s& v = firstHouseholderVector; // alias to save typing
 
@@ -373,14 +375,14 @@
 
 /** \internal Perform a Francis QR step involving rows il:iu and columns im:iu. */
 template<typename MatrixType>
-inline void RealSchur<MatrixType>::performFrancisQRStep(int il, int im, int iu, const Vector3s& firstHouseholderVector, Scalar* workspace)
+inline void RealSchur<MatrixType>::performFrancisQRStep(Index il, Index im, Index iu, const Vector3s& firstHouseholderVector, Scalar* workspace)
 {
   assert(im >= il);
   assert(im <= iu-2);
 
-  const int size = m_matU.cols();
+  const Index size = m_matU.cols();
 
-  for (int k = im; k <= iu-2; ++k)
+  for (Index k = im; k <= iu-2; ++k)
   {
     bool firstIteration = (k == im);
 
@@ -422,7 +424,7 @@
   }
 
   // clean up pollution due to round-off errors
-  for (int i = im+2; i <= iu; ++i)
+  for (Index i = im+2; i <= iu; ++i)
   {
     m_matT.coeffRef(i,i-2) = Scalar(0);
     if (i > im+2)
diff --git a/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h b/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
index 7634364..2c53655 100644
--- a/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
+++ b/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
@@ -82,6 +82,7 @@
 
     /** \brief Scalar type for matrices of type \p _MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::Index Index;
 
     /** \brief Real scalar type for \p _MatrixType. 
       *
@@ -105,7 +106,7 @@
       * perform decompositions via compute(const MatrixType&, bool) or
       * compute(const MatrixType&, const MatrixType&, bool). This constructor
       * can only be used if \p _MatrixType is a fixed-size matrix; use
-      * SelfAdjointEigenSolver(int) for dynamic-size matrices.
+      * SelfAdjointEigenSolver(Index) for dynamic-size matrices.
       *
       * Example: \include SelfAdjointEigenSolver_SelfAdjointEigenSolver.cpp
       * Output: \verbinclude SelfAdjointEigenSolver_SelfAdjointEigenSolver.out
@@ -132,7 +133,7 @@
       *
       * \sa compute(const MatrixType&, bool) for an example
       */
-    SelfAdjointEigenSolver(int size)
+    SelfAdjointEigenSolver(Index size)
         : m_eivec(size, size),
           m_eivalues(size),
           m_tridiag(size),
@@ -379,8 +380,8 @@
   * Implemented from Golub's "Matrix Computations", algorithm 8.3.2:
   * "implicit symmetric QR step with Wilkinson shift"
   */
-template<typename RealScalar, typename Scalar>
-static void ei_tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, int start, int end, Scalar* matrixQ, int n);
+template<typename RealScalar, typename Scalar, typename Index>
+static void ei_tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n);
 
 template<typename MatrixType>
 SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
@@ -389,7 +390,7 @@
   m_eigenvectorsOk = computeEigenvectors;
   #endif
   assert(matrix.cols() == matrix.rows());
-  int n = matrix.cols();
+  Index n = matrix.cols();
   m_eivalues.resize(n,1);
   m_eivec.resize(n,n);
 
@@ -407,11 +408,11 @@
   if (computeEigenvectors)
     m_eivec = m_tridiag.matrixQ();
 
-  int end = n-1;
-  int start = 0;
+  Index end = n-1;
+  Index start = 0;
   while (end>0)
   {
-    for (int i = start; i<end; ++i)
+    for (Index i = start; i<end; ++i)
       if (ei_isMuchSmallerThan(ei_abs(m_subdiag[i]),(ei_abs(diag[i])+ei_abs(diag[i+1]))))
         m_subdiag[i] = 0;
 
@@ -430,9 +431,9 @@
   // Sort eigenvalues and corresponding vectors.
   // TODO make the sort optional ?
   // TODO use a better sort algorithm !!
-  for (int i = 0; i < n-1; ++i)
+  for (Index i = 0; i < n-1; ++i)
   {
-    int k;
+    Index k;
     m_eivalues.segment(i,n-i).minCoeff(&k);
     if (k > 0)
     {
@@ -473,7 +474,7 @@
   {
     // transform back the eigen vectors: evecs = inv(U) * evecs
     cholB.matrixU().solveInPlace(m_eivec);
-    for (int i=0; i<m_eivec.cols(); ++i)
+    for (Index i=0; i<m_eivec.cols(); ++i)
       m_eivec.col(i) = m_eivec.col(i).normalized();
   }
   return *this;
@@ -482,8 +483,8 @@
 #endif // EIGEN_HIDE_HEAVY_CODE
 
 #ifndef EIGEN_EXTERN_INSTANTIATIONS
-template<typename RealScalar, typename Scalar>
-static void ei_tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, int start, int end, Scalar* matrixQ, int n)
+template<typename RealScalar, typename Scalar, typename Index>
+static void ei_tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n)
 {
   RealScalar td = (diag[end-1] - diag[end])*RealScalar(0.5);
   RealScalar e2 = ei_abs2(subdiag[end-1]);
@@ -491,7 +492,7 @@
   RealScalar x = diag[start] - mu;
   RealScalar z = subdiag[start];
 
-  for (int k = start; k < end; ++k)
+  for (Index k = start; k < end; ++k)
   {
     PlanarRotation<RealScalar> rot;
     rot.makeGivens(x, z);
diff --git a/Eigen/src/Eigenvalues/Tridiagonalization.h b/Eigen/src/Eigenvalues/Tridiagonalization.h
index 6ea852a..02917f2 100644
--- a/Eigen/src/Eigenvalues/Tridiagonalization.h
+++ b/Eigen/src/Eigenvalues/Tridiagonalization.h
@@ -67,6 +67,7 @@
 
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename MatrixType::Index Index;
 
     enum {
       Size = MatrixType::RowsAtCompileTime,
@@ -107,7 +108,7 @@
       *
       * \sa compute() for an example.
       */
-    Tridiagonalization(int size = Size==Dynamic ? 2 : Size)
+    Tridiagonalization(Index size = Size==Dynamic ? 2 : Size)
       : m_matrix(size,size), m_hCoeffs(size > 1 ? size-1 : 1)
     {}
 
@@ -324,7 +325,7 @@
 const typename Tridiagonalization<MatrixType>::SubDiagonalReturnType
 Tridiagonalization<MatrixType>::subDiagonal() const
 {
-  int n = m_matrix.rows();
+  Index n = m_matrix.rows();
   return Block<MatrixType,SizeMinusOne,SizeMinusOne>(m_matrix, 1, 0, n-1,n-1).diagonal();
 }
 
@@ -334,7 +335,7 @@
 {
   // FIXME should this function (and other similar ones) rather take a matrix as argument
   // and fill it ? (to avoid temporaries)
-  int n = m_matrix.rows();
+  Index n = m_matrix.rows();
   MatrixType matT = m_matrix;
   matT.topRightCorner(n-1, n-1).diagonal() = subDiagonal().template cast<Scalar>().conjugate();
   if (n>2)
@@ -363,10 +364,10 @@
 void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType& hCoeffs)
 {
   assert(matA.rows()==matA.cols());
-  int n = matA.rows();
-  for (int i = 0; i<n-1; ++i)
+  Index n = matA.rows();
+  for (Index i = 0; i<n-1; ++i)
   {
-    int remainingSize = n-i-1;
+    Index remainingSize = n-i-1;
     RealScalar beta;
     Scalar h;
     matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
@@ -391,7 +392,7 @@
 template<typename MatrixType>
 void Tridiagonalization<MatrixType>::decomposeInPlace(MatrixType& mat, DiagonalType& diag, SubDiagonalType& subdiag, bool extractQ)
 {
-  int n = mat.rows();
+  Index n = mat.rows();
   ei_assert(mat.cols()==n && diag.size()==n && subdiag.size()==n-1);
   if (n==3 && (!NumTraits<Scalar>::IsComplex) )
   {
diff --git a/Eigen/src/Geometry/AlignedBox.h b/Eigen/src/Geometry/AlignedBox.h
index f3bee6f..9d9d96f 100644
--- a/Eigen/src/Geometry/AlignedBox.h
+++ b/Eigen/src/Geometry/AlignedBox.h
@@ -45,6 +45,7 @@
   enum { AmbientDimAtCompileTime = _AmbientDim };
   typedef _Scalar                                   Scalar;
   typedef NumTraits<Scalar>                         ScalarTraits;
+  typedef DenseIndex                                Index;
   typedef typename ScalarTraits::Real               RealScalar;
   typedef typename ScalarTraits::NonInteger      NonInteger;
   typedef Matrix<Scalar,AmbientDimAtCompileTime,1>  VectorType;
@@ -72,7 +73,7 @@
   { if (AmbientDimAtCompileTime!=Dynamic) setEmpty(); }
 
   /** Constructs a null box with \a _dim the dimension of the ambient space. */
-  inline explicit AlignedBox(int _dim) : m_min(_dim), m_max(_dim)
+  inline explicit AlignedBox(Index _dim) : m_min(_dim), m_max(_dim)
   { setEmpty(); }
 
   /** Constructs a box with extremities \a _min and \a _max. */
@@ -91,7 +92,7 @@
   ~AlignedBox() {}
 
   /** \returns the dimension in which the box holds */
-  inline int dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size()-1 : AmbientDimAtCompileTime; }
+  inline Index dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size()-1 : Index(AmbientDimAtCompileTime); }
 
   /** \deprecated use isEmpty */
   inline bool isNull() const { return isEmpty(); }
@@ -157,8 +158,8 @@
 
     VectorType res;
 
-    int mult = 1;
-    for(int d=0; d<dim(); ++d)
+    Index mult = 1;
+    for(Index d=0; d<dim(); ++d)
     {
       if( mult & corner ) res[d] = m_max[d];
       else                res[d] = m_min[d];
@@ -172,7 +173,7 @@
   inline VectorType sample() const
   {
     VectorType r;
-    for(int d=0; d<dim(); ++d)
+    for(Index d=0; d<dim(); ++d)
     {
       if(!ScalarTraits::IsInteger)
       {
@@ -311,7 +312,7 @@
   const typename ei_nested<Derived,2*AmbientDim>::type p(a_p.derived());
   Scalar dist2 = 0.;
   Scalar aux;
-  for (int k=0; k<dim(); ++k)
+  for (Index k=0; k<dim(); ++k)
   {
     if( m_min[k] > p[k] )
     {
@@ -332,7 +333,7 @@
 {
   Scalar dist2 = 0.;
   Scalar aux;
-  for (int k=0; k<dim(); ++k)
+  for (Index k=0; k<dim(); ++k)
   {
     if( m_min[k] > b.m_max[k] )
     {
diff --git a/Eigen/src/Geometry/EulerAngles.h b/Eigen/src/Geometry/EulerAngles.h
index 13d2376..d910cbc 100644
--- a/Eigen/src/Geometry/EulerAngles.h
+++ b/Eigen/src/Geometry/EulerAngles.h
@@ -43,7 +43,7 @@
   */
 template<typename Derived>
 inline Matrix<typename MatrixBase<Derived>::Scalar,3,1>
-MatrixBase<Derived>::eulerAngles(int a0, int a1, int a2) const
+MatrixBase<Derived>::eulerAngles(Index a0, Index a1, Index a2) const
 {
   /* Implemented from Graphics Gems IV */
   EIGEN_STATIC_ASSERT_MATRIX_SPECIFIC_SIZE(Derived,3,3)
@@ -52,10 +52,10 @@
   typedef Matrix<typename Derived::Scalar,2,1> Vector2;
   const Scalar epsilon = NumTraits<Scalar>::dummy_precision();
 
-  const int odd = ((a0+1)%3 == a1) ? 0 : 1;
-  const int i = a0;
-  const int j = (a0 + 1 + odd)%3;
-  const int k = (a0 + 2 - odd)%3;
+  const Index odd = ((a0+1)%3 == a1) ? 0 : 1;
+  const Index i = a0;
+  const Index j = (a0 + 1 + odd)%3;
+  const Index k = (a0 + 2 - odd)%3;
 
   if (a0==a2)
   {
diff --git a/Eigen/src/Geometry/Homogeneous.h b/Eigen/src/Geometry/Homogeneous.h
index caea1db..3077f09 100644
--- a/Eigen/src/Geometry/Homogeneous.h
+++ b/Eigen/src/Geometry/Homogeneous.h
@@ -77,10 +77,10 @@
       : m_matrix(matrix)
     {}
 
-    inline int rows() const { return m_matrix.rows() + (int(Direction)==Vertical   ? 1 : 0); }
-    inline int cols() const { return m_matrix.cols() + (int(Direction)==Horizontal ? 1 : 0); }
+    inline Index rows() const { return m_matrix.rows() + (int(Direction)==Vertical   ? 1 : 0); }
+    inline Index cols() const { return m_matrix.cols() + (int(Direction)==Horizontal ? 1 : 0); }
 
-    inline Scalar coeff(int row, int col) const
+    inline Scalar coeff(Index row, Index col) const
     {
       if(  (int(Direction)==Vertical   && row==m_matrix.rows())
         || (int(Direction)==Horizontal && col==m_matrix.cols()))
@@ -223,12 +223,13 @@
   : public ReturnByValue<ei_homogeneous_left_product_impl<Homogeneous<MatrixType,Vertical>,Lhs> >
 {
   typedef typename ei_cleantype<typename Lhs::Nested>::type LhsNested;
+  typedef typename MatrixType::Index Index;
   ei_homogeneous_left_product_impl(const Lhs& lhs, const MatrixType& rhs)
     : m_lhs(lhs), m_rhs(rhs)
   {}
 
-  inline int rows() const { return m_lhs.rows(); }
-  inline int cols() const { return m_rhs.cols(); }
+  inline Index rows() const { return m_lhs.rows(); }
+  inline Index cols() const { return m_rhs.cols(); }
 
   template<typename Dest> void evalTo(Dest& dst) const
   {
@@ -261,12 +262,13 @@
   : public ReturnByValue<ei_homogeneous_right_product_impl<Homogeneous<MatrixType,Horizontal>,Rhs> >
 {
   typedef typename ei_cleantype<typename Rhs::Nested>::type RhsNested;
+  typedef typename MatrixType::Index Index;
   ei_homogeneous_right_product_impl(const MatrixType& lhs, const Rhs& rhs)
     : m_lhs(lhs), m_rhs(rhs)
   {}
 
-  inline int rows() const { return m_lhs.rows(); }
-  inline int cols() const { return m_rhs.cols(); }
+  inline Index rows() const { return m_lhs.rows(); }
+  inline Index cols() const { return m_rhs.cols(); }
 
   template<typename Dest> void evalTo(Dest& dst) const
   {
diff --git a/Eigen/src/Geometry/Hyperplane.h b/Eigen/src/Geometry/Hyperplane.h
index 1d0b299..8450c9d 100644
--- a/Eigen/src/Geometry/Hyperplane.h
+++ b/Eigen/src/Geometry/Hyperplane.h
@@ -51,10 +51,11 @@
   enum { AmbientDimAtCompileTime = _AmbientDim };
   typedef _Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  typedef DenseIndex Index;
   typedef Matrix<Scalar,AmbientDimAtCompileTime,1> VectorType;
-  typedef Matrix<Scalar,int(AmbientDimAtCompileTime)==Dynamic
+  typedef Matrix<Scalar,Index(AmbientDimAtCompileTime)==Dynamic
                         ? Dynamic
-                        : int(AmbientDimAtCompileTime)+1,1> Coefficients;
+                        : Index(AmbientDimAtCompileTime)+1,1> Coefficients;
   typedef Block<Coefficients,AmbientDimAtCompileTime,1> NormalReturnType;
 
   /** Default constructor without initialization */
@@ -62,7 +63,7 @@
 
   /** Constructs a dynamic-size hyperplane with \a _dim the dimension
     * of the ambient space */
-  inline explicit Hyperplane(int _dim) : m_coeffs(_dim+1) {}
+  inline explicit Hyperplane(Index _dim) : m_coeffs(_dim+1) {}
 
   /** Construct a plane from its normal \a n and a point \a e onto the plane.
     * \warning the vector normal is assumed to be normalized.
@@ -122,7 +123,7 @@
   ~Hyperplane() {}
 
   /** \returns the dimension in which the plane holds */
-  inline int dim() const { return AmbientDimAtCompileTime==Dynamic ? m_coeffs.size()-1 : AmbientDimAtCompileTime; }
+  inline Index dim() const { return AmbientDimAtCompileTime==Dynamic ? m_coeffs.size()-1 : Index(AmbientDimAtCompileTime); }
 
   /** normalizes \c *this */
   void normalize(void)
diff --git a/Eigen/src/Geometry/OrthoMethods.h b/Eigen/src/Geometry/OrthoMethods.h
index 265507e..ed790cc 100644
--- a/Eigen/src/Geometry/OrthoMethods.h
+++ b/Eigen/src/Geometry/OrthoMethods.h
@@ -137,12 +137,13 @@
   typedef typename ei_plain_matrix_type<Derived>::type VectorType;
   typedef typename ei_traits<Derived>::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  typedef typename Derived::Index Index;
   typedef Matrix<Scalar,2,1> Vector2;
   inline static VectorType run(const Derived& src)
   {
     VectorType perp = VectorType::Zero(src.size());
-    int maxi = 0;
-    int sndi = 0;
+    Index maxi = 0;
+    Index sndi = 0;
     src.cwiseAbs().maxCoeff(&maxi);
     if (maxi==0)
       sndi = 1;
diff --git a/Eigen/src/Geometry/ParametrizedLine.h b/Eigen/src/Geometry/ParametrizedLine.h
index 1846a44..45c2338 100644
--- a/Eigen/src/Geometry/ParametrizedLine.h
+++ b/Eigen/src/Geometry/ParametrizedLine.h
@@ -47,6 +47,7 @@
   enum { AmbientDimAtCompileTime = _AmbientDim };
   typedef _Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  typedef DenseIndex Index;
   typedef Matrix<Scalar,AmbientDimAtCompileTime,1> VectorType;
 
   /** Default constructor without initialization */
@@ -54,7 +55,7 @@
 
   /** Constructs a dynamic-size line with \a _dim the dimension
     * of the ambient space */
-  inline explicit ParametrizedLine(int _dim) : m_origin(_dim), m_direction(_dim) {}
+  inline explicit ParametrizedLine(Index _dim) : m_origin(_dim), m_direction(_dim) {}
 
   /** Initializes a parametrized line of direction \a direction and origin \a origin.
     * \warning the vector direction is assumed to be normalized.
@@ -71,7 +72,7 @@
   ~ParametrizedLine() {}
 
   /** \returns the dimension in which the line holds */
-  inline int dim() const { return m_direction.size(); }
+  inline Index dim() const { return m_direction.size(); }
 
   const VectorType& origin() const { return m_origin; }
   VectorType& origin() { return m_origin; }
diff --git a/Eigen/src/Geometry/Quaternion.h b/Eigen/src/Geometry/Quaternion.h
index 4e054d9..7d52ebf 100644
--- a/Eigen/src/Geometry/Quaternion.h
+++ b/Eigen/src/Geometry/Quaternion.h
@@ -617,6 +617,7 @@
 struct ei_quaternionbase_assign_impl<Other,3,3>
 {
   typedef typename Other::Scalar Scalar;
+  typedef DenseIndex Index;
   template<class Derived> inline static void run(QuaternionBase<Derived>& q, const Other& mat)
   {
     // This algorithm comes from  "Quaternion Calculus and Fast Animation",
@@ -633,13 +634,13 @@
     }
     else
     {
-      int i = 0;
+      DenseIndex i = 0;
       if (mat.coeff(1,1) > mat.coeff(0,0))
         i = 1;
       if (mat.coeff(2,2) > mat.coeff(i,i))
         i = 2;
-      int j = (i+1)%3;
-      int k = (j+1)%3;
+      DenseIndex j = (i+1)%3;
+      DenseIndex k = (j+1)%3;
 
       t = ei_sqrt(mat.coeff(i,i)-mat.coeff(j,j)-mat.coeff(k,k) + Scalar(1.0));
       q.coeffs().coeffRef(i) = Scalar(0.5) * t;
diff --git a/Eigen/src/Geometry/Transform.h b/Eigen/src/Geometry/Transform.h
index 6a7bb9a..207497f 100644
--- a/Eigen/src/Geometry/Transform.h
+++ b/Eigen/src/Geometry/Transform.h
@@ -174,6 +174,7 @@
   };
   /** the scalar type of the coefficients */
   typedef _Scalar Scalar;
+  typedef DenseIndex Index;
   /** type of the matrix used to represent the transformation */
   typedef Matrix<Scalar,Rows,HDim> MatrixType;
   /** type of the matrix used to represent the linear part of the transformation */
@@ -270,11 +271,11 @@
   #endif
 
   /** shortcut for m_matrix(row,col);
-    * \sa MatrixBase::operaror(int,int) const */
-  inline Scalar operator() (int row, int col) const { return m_matrix(row,col); }
+    * \sa MatrixBase::operaror(Index,Index) const */
+  inline Scalar operator() (Index row, Index col) const { return m_matrix(row,col); }
   /** shortcut for m_matrix(row,col);
-    * \sa MatrixBase::operaror(int,int) */
-  inline Scalar& operator() (int row, int col) { return m_matrix(row,col); }
+    * \sa MatrixBase::operaror(Index,Index) */
+  inline Scalar& operator() (Index row, Index col) { return m_matrix(row,col); }
 
   /** \returns a read-only expression of the transformation matrix */
   inline const MatrixType& matrix() const { return m_matrix; }
@@ -1141,7 +1142,7 @@
   static ResultType run(const TransformType& tr, const Other& other)
   {
     TransformType res;
-    const int Rows = Mode==Projective ? HDim : Dim;
+    enum { Rows = Mode==Projective ? HDim : Dim };
     res.matrix().template block<Rows,HDim>(0,0).noalias() = (tr.linearExt() * other);
     res.translationExt() += tr.translationExt();
     if(Mode!=Affine)
diff --git a/Eigen/src/Geometry/Umeyama.h b/Eigen/src/Geometry/Umeyama.h
index 262d27a..5b9fd77 100644
--- a/Eigen/src/Geometry/Umeyama.h
+++ b/Eigen/src/Geometry/Umeyama.h
@@ -109,6 +109,7 @@
   typedef typename ei_umeyama_transform_matrix_type<Derived, OtherDerived>::type TransformationMatrixType;
   typedef typename ei_traits<TransformationMatrixType>::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
+  typedef typename Derived::Index Index;
 
   EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_REAL)
   EIGEN_STATIC_ASSERT((ei_is_same_type<Scalar, typename ei_traits<OtherDerived>::Scalar>::ret),
@@ -120,8 +121,8 @@
   typedef Matrix<Scalar, Dimension, Dimension> MatrixType;
   typedef typename ei_plain_matrix_type_row_major<Derived>::type RowMajorMatrixType;
 
-  const int m = src.rows(); // dimension
-  const int n = src.cols(); // number of measurements
+  const Index m = src.rows(); // dimension
+  const Index n = src.cols(); // number of measurements
 
   // required for demeaning ...
   const RealScalar one_over_n = 1 / static_cast<RealScalar>(n);
@@ -151,7 +152,7 @@
 
   // Eq. (40) and (43)
   const VectorType& d = svd.singularValues();
-  int rank = 0; for (int i=0; i<m; ++i) if (!ei_isMuchSmallerThan(d.coeff(i),d.coeff(0))) ++rank;
+  Index rank = 0; for (Index i=0; i<m; ++i) if (!ei_isMuchSmallerThan(d.coeff(i),d.coeff(0))) ++rank;
   if (rank == m-1) {
     if ( svd.matrixU().determinant() * svd.matrixV().determinant() > 0 ) {
       Rt.block(0,0,m,m).noalias() = svd.matrixU()*svd.matrixV().transpose();
diff --git a/Eigen/src/Householder/HouseholderSequence.h b/Eigen/src/Householder/HouseholderSequence.h
index ab7702b..90c5bf8 100644
--- a/Eigen/src/Householder/HouseholderSequence.h
+++ b/Eigen/src/Householder/HouseholderSequence.h
@@ -53,6 +53,7 @@
 struct ei_traits<HouseholderSequence<VectorsType,CoeffsType,Side> >
 {
   typedef typename VectorsType::Scalar Scalar;
+  typedef typename VectorsType::StorageKind StorageKind;
   enum {
     RowsAtCompileTime = Side==OnTheLeft ? ei_traits<VectorsType>::RowsAtCompileTime
                                         : ei_traits<VectorsType>::ColsAtCompileTime,
@@ -69,9 +70,10 @@
 {
   typedef Block<VectorsType, Dynamic, 1> EssentialVectorType;
   typedef HouseholderSequence<VectorsType, CoeffsType, OnTheLeft> HouseholderSequenceType;
-  static inline const EssentialVectorType essentialVector(const HouseholderSequenceType& h, int k)
+  typedef typename VectorsType::Index Index;
+  static inline const EssentialVectorType essentialVector(const HouseholderSequenceType& h, Index k)
   {
-    const int start = k+1+h.m_shift;
+    Index start = k+1+h.m_shift;
     return Block<VectorsType,Dynamic,1>(h.m_vectors, start, k, h.rows()-start, 1);
   }
 };
@@ -81,9 +83,10 @@
 {
   typedef Transpose<Block<VectorsType, 1, Dynamic> > EssentialVectorType;
   typedef HouseholderSequence<VectorsType, CoeffsType, OnTheRight> HouseholderSequenceType;
-  static inline const EssentialVectorType essentialVector(const HouseholderSequenceType& h, int k)
+  typedef typename VectorsType::Index Index;
+  static inline const EssentialVectorType essentialVector(const HouseholderSequenceType& h, Index k)
   {
-    const int start = k+1+h.m_shift;
+    Index start = k+1+h.m_shift;
     return Block<VectorsType,1,Dynamic>(h.m_vectors, k, start, 1, h.rows()-start).transpose();
   }
 };
@@ -106,6 +109,7 @@
       MaxColsAtCompileTime = ei_traits<HouseholderSequence>::MaxColsAtCompileTime
     };
     typedef typename ei_traits<HouseholderSequence>::Scalar Scalar;
+    typedef typename VectorsType::Index Index;
 
     typedef typename ei_hseq_side_dependent_impl<VectorsType,CoeffsType,Side>::EssentialVectorType
             EssentialVectorType;
@@ -126,15 +130,15 @@
     {
     }
 
-    HouseholderSequence(const VectorsType& v, const CoeffsType& h, bool trans, int actualVectors, int shift)
+    HouseholderSequence(const VectorsType& v, const CoeffsType& h, bool trans, Index actualVectors, Index shift)
       : m_vectors(v), m_coeffs(h), m_trans(trans), m_actualVectors(actualVectors), m_shift(shift)
     {
     }
 
-    int rows() const { return Side==OnTheLeft ? m_vectors.rows() : m_vectors.cols(); }
-    int cols() const { return rows(); }
+    Index rows() const { return Side==OnTheLeft ? m_vectors.rows() : m_vectors.cols(); }
+    Index cols() const { return rows(); }
 
-    const EssentialVectorType essentialVector(int k) const
+    const EssentialVectorType essentialVector(Index k) const
     {
       ei_assert(k >= 0 && k < m_actualVectors);
       return ei_hseq_side_dependent_impl<VectorsType,CoeffsType,Side>::essentialVector(*this, k);
@@ -154,13 +158,13 @@
     /** \internal */
     template<typename DestType> void evalTo(DestType& dst) const
     {
-      int vecs = m_actualVectors;
+      Index vecs = m_actualVectors;
       dst.setIdentity(rows(), rows());
       Matrix<Scalar, DestType::RowsAtCompileTime, 1,
 	     AutoAlign|ColMajor, DestType::MaxRowsAtCompileTime, 1> temp(rows());
-      for(int k = vecs-1; k >= 0; --k)
+      for(Index k = vecs-1; k >= 0; --k)
       {
-        int cornerSize = rows() - k - m_shift;
+        Index cornerSize = rows() - k - m_shift;
         if(m_trans)
           dst.bottomRightCorner(cornerSize, cornerSize)
           .applyHouseholderOnTheRight(essentialVector(k), m_coeffs.coeff(k), &temp.coeffRef(0));
@@ -174,9 +178,9 @@
     template<typename Dest> inline void applyThisOnTheRight(Dest& dst) const
     {
       Matrix<Scalar,1,Dest::RowsAtCompileTime> temp(dst.rows());
-      for(int k = 0; k < m_actualVectors; ++k)
+      for(Index k = 0; k < m_actualVectors; ++k)
       {
-        int actual_k = m_trans ? m_actualVectors-k-1 : k;
+        Index actual_k = m_trans ? m_actualVectors-k-1 : k;
         dst.rightCols(rows()-m_shift-actual_k)
            .applyHouseholderOnTheRight(essentialVector(actual_k), m_coeffs.coeff(actual_k), &temp.coeffRef(0));
       }
@@ -186,9 +190,9 @@
     template<typename Dest> inline void applyThisOnTheLeft(Dest& dst) const
     {
       Matrix<Scalar,1,Dest::ColsAtCompileTime> temp(dst.cols());
-      for(int k = 0; k < m_actualVectors; ++k)
+      for(Index k = 0; k < m_actualVectors; ++k)
       {
-        int actual_k = m_trans ? k : m_actualVectors-k-1;
+        Index actual_k = m_trans ? k : m_actualVectors-k-1;
         dst.bottomRows(rows()-m_shift-actual_k)
            .applyHouseholderOnTheLeft(essentialVector(actual_k), m_coeffs.coeff(actual_k), &temp.coeffRef(0));
       }
@@ -218,8 +222,8 @@
     typename VectorsType::Nested m_vectors;
     typename CoeffsType::Nested m_coeffs;
     bool m_trans;
-    int m_actualVectors;
-    int m_shift;
+    Index m_actualVectors;
+    Index m_shift;
 };
 
 template<typename VectorsType, typename CoeffsType>
@@ -229,7 +233,9 @@
 }
 
 template<typename VectorsType, typename CoeffsType>
-HouseholderSequence<VectorsType,CoeffsType> householderSequence(const VectorsType& v, const CoeffsType& h, bool trans, int actualVectors, int shift)
+HouseholderSequence<VectorsType,CoeffsType> householderSequence
+   (const VectorsType& v, const CoeffsType& h,
+    bool trans, typename VectorsType::Index actualVectors, typename VectorsType::Index shift)
 {
   return HouseholderSequence<VectorsType,CoeffsType,OnTheLeft>(v, h, trans, actualVectors, shift);
 }
@@ -241,7 +247,9 @@
 }
 
 template<typename VectorsType, typename CoeffsType>
-HouseholderSequence<VectorsType,CoeffsType> rightHouseholderSequence(const VectorsType& v, const CoeffsType& h, bool trans, int actualVectors, int shift)
+HouseholderSequence<VectorsType,CoeffsType> rightHouseholderSequence
+  (const VectorsType& v, const CoeffsType& h, bool trans,
+   typename VectorsType::Index actualVectors, typename VectorsType::Index shift)
 {
   return HouseholderSequence<VectorsType,CoeffsType,OnTheRight>(v, h, trans, actualVectors, shift);
 }
diff --git a/Eigen/src/Jacobi/Jacobi.h b/Eigen/src/Jacobi/Jacobi.h
index 024a130..f34e183 100644
--- a/Eigen/src/Jacobi/Jacobi.h
+++ b/Eigen/src/Jacobi/Jacobi.h
@@ -74,7 +74,7 @@
     PlanarRotation adjoint() const { return PlanarRotation(ei_conj(m_c), -m_s); }
 
     template<typename Derived>
-    bool makeJacobi(const MatrixBase<Derived>&, int p, int q);
+    bool makeJacobi(const MatrixBase<Derived>&, typename Derived::Index p, typename Derived::Index q);
     bool makeJacobi(RealScalar x, Scalar y, RealScalar z);
 
     void makeGivens(const Scalar& p, const Scalar& q, Scalar* z=0);
@@ -89,7 +89,7 @@
 /** Makes \c *this as a Jacobi rotation \a J such that applying \a J on both the right and left sides of the selfadjoint 2x2 matrix
   * \f$ B = \left ( \begin{array}{cc} x & y \\ \overline y & z \end{array} \right )\f$ yields a diagonal matrix \f$ A = J^* B J \f$
   *
-  * \sa MatrixBase::makeJacobi(const MatrixBase<Derived>&, int, int), MatrixBase::applyOnTheLeft(), MatrixBase::applyOnTheRight()
+  * \sa MatrixBase::makeJacobi(const MatrixBase<Derived>&, Index, Index), MatrixBase::applyOnTheLeft(), MatrixBase::applyOnTheRight()
   */
 template<typename Scalar>
 bool PlanarRotation<Scalar>::makeJacobi(RealScalar x, Scalar y, RealScalar z)
@@ -133,7 +133,7 @@
   */
 template<typename Scalar>
 template<typename Derived>
-inline bool PlanarRotation<Scalar>::makeJacobi(const MatrixBase<Derived>& m, int p, int q)
+inline bool PlanarRotation<Scalar>::makeJacobi(const MatrixBase<Derived>& m, typename Derived::Index p, typename Derived::Index q)
 {
   return makeJacobi(ei_real(m.coeff(p,p)), m.coeff(p,q), ei_real(m.coeff(q,q)));
 }
@@ -277,7 +277,7 @@
   */
 template<typename Derived>
 template<typename OtherScalar>
-inline void MatrixBase<Derived>::applyOnTheLeft(int p, int q, const PlanarRotation<OtherScalar>& j)
+inline void MatrixBase<Derived>::applyOnTheLeft(Index p, Index q, const PlanarRotation<OtherScalar>& j)
 {
   RowXpr x(this->row(p));
   RowXpr y(this->row(q));
@@ -292,7 +292,7 @@
   */
 template<typename Derived>
 template<typename OtherScalar>
-inline void MatrixBase<Derived>::applyOnTheRight(int p, int q, const PlanarRotation<OtherScalar>& j)
+inline void MatrixBase<Derived>::applyOnTheRight(Index p, Index q, const PlanarRotation<OtherScalar>& j)
 {
   ColXpr x(this->col(p));
   ColXpr y(this->col(q));
@@ -303,11 +303,12 @@
 template<typename VectorX, typename VectorY, typename OtherScalar>
 void /*EIGEN_DONT_INLINE*/ ei_apply_rotation_in_the_plane(VectorX& _x, VectorY& _y, const PlanarRotation<OtherScalar>& j)
 {
+  typedef typename VectorX::Index Index;
   typedef typename VectorX::Scalar Scalar;
   ei_assert(_x.size() == _y.size());
-  int size = _x.size();
-  int incrx = size ==1 ? 1 : &_x.coeffRef(1) - &_x.coeffRef(0);
-  int incry = size ==1 ? 1 : &_y.coeffRef(1) - &_y.coeffRef(0);
+  Index size = _x.size();
+  Index incrx = size ==1 ? 1 : &_x.coeffRef(1) - &_x.coeffRef(0);
+  Index incry = size ==1 ? 1 : &_y.coeffRef(1) - &_y.coeffRef(0);
 
   Scalar* EIGEN_RESTRICT x = &_x.coeffRef(0);
   Scalar* EIGEN_RESTRICT y = &_y.coeffRef(0);
@@ -318,14 +319,14 @@
     typedef typename ei_packet_traits<Scalar>::type Packet;
     enum { PacketSize = ei_packet_traits<Scalar>::size, Peeling = 2 };
 
-    int alignedStart = ei_first_aligned(y, size);
-    int alignedEnd = alignedStart + ((size-alignedStart)/PacketSize)*PacketSize;
+    Index alignedStart = ei_first_aligned(y, size);
+    Index alignedEnd = alignedStart + ((size-alignedStart)/PacketSize)*PacketSize;
 
     const Packet pc = ei_pset1(Scalar(j.c()));
     const Packet ps = ei_pset1(Scalar(j.s()));
     ei_conj_helper<NumTraits<Scalar>::IsComplex,false> cj;
 
-    for(int i=0; i<alignedStart; ++i)
+    for(Index i=0; i<alignedStart; ++i)
     {
       Scalar xi = x[i];
       Scalar yi = y[i];
@@ -338,7 +339,7 @@
 
     if(ei_first_aligned(x, size)==alignedStart)
     {
-      for(int i=alignedStart; i<alignedEnd; i+=PacketSize)
+      for(Index i=alignedStart; i<alignedEnd; i+=PacketSize)
       {
         Packet xi = ei_pload(px);
         Packet yi = ei_pload(py);
@@ -350,8 +351,8 @@
     }
     else
     {
-      int peelingEnd = alignedStart + ((size-alignedStart)/(Peeling*PacketSize))*(Peeling*PacketSize);
-      for(int i=alignedStart; i<peelingEnd; i+=Peeling*PacketSize)
+      Index peelingEnd = alignedStart + ((size-alignedStart)/(Peeling*PacketSize))*(Peeling*PacketSize);
+      for(Index i=alignedStart; i<peelingEnd; i+=Peeling*PacketSize)
       {
         Packet xi   = ei_ploadu(px);
         Packet xi1  = ei_ploadu(px+PacketSize);
@@ -373,7 +374,7 @@
       }
     }
 
-    for(int i=alignedEnd; i<size; ++i)
+    for(Index i=alignedEnd; i<size; ++i)
     {
       Scalar xi = x[i];
       Scalar yi = y[i];
@@ -383,7 +384,7 @@
   }
   else
   {
-    for(int i=0; i<size; ++i)
+    for(Index i=0; i<size; ++i)
     {
       Scalar xi = *x;
       Scalar yi = *y;
diff --git a/Eigen/src/LU/FullPivLU.h b/Eigen/src/LU/FullPivLU.h
index 1b0e67b..da4dce6 100644
--- a/Eigen/src/LU/FullPivLU.h
+++ b/Eigen/src/LU/FullPivLU.h
@@ -68,8 +68,10 @@
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef typename ei_plain_row_type<MatrixType, int>::type IntRowVectorType;
-    typedef typename ei_plain_col_type<MatrixType, int>::type IntColVectorType;
+    typedef typename ei_traits<MatrixType>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
+    typedef typename ei_plain_row_type<MatrixType, Index>::type IntRowVectorType;
+    typedef typename ei_plain_col_type<MatrixType, Index>::type IntColVectorType;
     typedef PermutationMatrix<ColsAtCompileTime, MaxColsAtCompileTime> PermutationQType;
     typedef PermutationMatrix<RowsAtCompileTime, MaxRowsAtCompileTime> PermutationPType;
 
@@ -87,7 +89,7 @@
       * according to the specified problem \a size.
       * \sa FullPivLU()
       */
-    FullPivLU(int rows, int cols);
+    FullPivLU(Index rows, Index cols);
 
     /** Constructor.
       *
@@ -124,7 +126,7 @@
       *
       * \sa rank()
       */
-    inline int nonzeroPivots() const
+    inline Index nonzeroPivots() const
     {
       ei_assert(m_isInitialized && "LU is not initialized.");
       return m_nonzero_pivots;
@@ -301,12 +303,12 @@
       *       For that, it uses the threshold value that you can control by calling
       *       setThreshold(const RealScalar&).
       */
-    inline int rank() const
+    inline Index rank() const
     {
       ei_assert(m_isInitialized && "LU is not initialized.");
       RealScalar premultiplied_threshold = ei_abs(m_maxpivot) * threshold();
-      int result = 0;
-      for(int i = 0; i < m_nonzero_pivots; ++i)
+      Index result = 0;
+      for(Index i = 0; i < m_nonzero_pivots; ++i)
         result += (ei_abs(m_lu.coeff(i,i)) > premultiplied_threshold);
       return result;
     }
@@ -317,7 +319,7 @@
       *       For that, it uses the threshold value that you can control by calling
       *       setThreshold(const RealScalar&).
       */
-    inline int dimensionOfKernel() const
+    inline Index dimensionOfKernel() const
     {
       ei_assert(m_isInitialized && "LU is not initialized.");
       return cols() - rank();
@@ -378,8 +380,8 @@
 
     MatrixType reconstructedMatrix() const;
 
-    inline int rows() const { return m_lu.rows(); }
-    inline int cols() const { return m_lu.cols(); }
+    inline Index rows() const { return m_lu.rows(); }
+    inline Index cols() const { return m_lu.cols(); }
 
   protected:
     MatrixType m_lu;
@@ -387,7 +389,7 @@
     PermutationQType m_q;
     IntColVectorType m_rowsTranspositions;
     IntRowVectorType m_colsTranspositions;
-    int m_det_pq, m_nonzero_pivots;
+    Index m_det_pq, m_nonzero_pivots;
     RealScalar m_maxpivot, m_prescribedThreshold;
     bool m_isInitialized, m_usePrescribedThreshold;
 };
@@ -399,7 +401,7 @@
 }
 
 template<typename MatrixType>
-FullPivLU<MatrixType>::FullPivLU(int rows, int cols)
+FullPivLU<MatrixType>::FullPivLU(Index rows, Index cols)
   : m_lu(rows, cols),
     m_p(rows),
     m_q(cols),
@@ -429,26 +431,26 @@
   m_isInitialized = true;
   m_lu = matrix;
 
-  const int size = matrix.diagonalSize();
-  const int rows = matrix.rows();
-  const int cols = matrix.cols();
+  const Index size = matrix.diagonalSize();
+  const Index rows = matrix.rows();
+  const Index cols = matrix.cols();
 
   // will store the transpositions, before we accumulate them at the end.
   // can't accumulate on-the-fly because that will be done in reverse order for the rows.
   m_rowsTranspositions.resize(matrix.rows());
   m_colsTranspositions.resize(matrix.cols());
-  int number_of_transpositions = 0; // number of NONTRIVIAL transpositions, i.e. m_rowsTranspositions[i]!=i
+  Index number_of_transpositions = 0; // number of NONTRIVIAL transpositions, i.e. m_rowsTranspositions[i]!=i
 
   m_nonzero_pivots = size; // the generic case is that in which all pivots are nonzero (invertible case)
   m_maxpivot = RealScalar(0);
   RealScalar cutoff(0);
 
-  for(int k = 0; k < size; ++k)
+  for(Index k = 0; k < size; ++k)
   {
     // First, we need to find the pivot.
 
     // biggest coefficient in the remaining bottom-right corner (starting at row k, col k)
-    int row_of_biggest_in_corner, col_of_biggest_in_corner;
+    Index row_of_biggest_in_corner, col_of_biggest_in_corner;
     RealScalar biggest_in_corner;
     biggest_in_corner = m_lu.bottomRightCorner(rows-k, cols-k)
                         .cwiseAbs()
@@ -468,7 +470,7 @@
       // before exiting, make sure to initialize the still uninitialized transpositions
       // in a sane state without destroying what we already have.
       m_nonzero_pivots = k;
-      for(int i = k; i < size; ++i)
+      for(Index i = k; i < size; ++i)
       {
         m_rowsTranspositions.coeffRef(i) = i;
         m_colsTranspositions.coeffRef(i) = i;
@@ -505,11 +507,11 @@
   // permutations P and Q
 
   m_p.setIdentity(rows);
-  for(int k = size-1; k >= 0; --k)
+  for(Index k = size-1; k >= 0; --k)
     m_p.applyTranspositionOnTheRight(k, m_rowsTranspositions.coeff(k));
 
   m_q.setIdentity(cols);
-  for(int k = 0; k < size; ++k)
+  for(Index k = 0; k < size; ++k)
     m_q.applyTranspositionOnTheRight(k, m_colsTranspositions.coeff(k));
 
   m_det_pq = (number_of_transpositions%2) ? -1 : 1;
@@ -531,7 +533,7 @@
 MatrixType FullPivLU<MatrixType>::reconstructedMatrix() const
 {
   ei_assert(m_isInitialized && "LU is not initialized.");
-  const int smalldim = std::min(m_lu.rows(), m_lu.cols());
+  const Index smalldim = std::min(m_lu.rows(), m_lu.cols());
   // LU
   MatrixType res(m_lu.rows(),m_lu.cols());
   // FIXME the .toDenseMatrix() should not be needed...
@@ -564,7 +566,7 @@
 
   template<typename Dest> void evalTo(Dest& dst) const
   {
-    const int cols = dec().matrixLU().cols(), dimker = cols - rank();
+    const Index cols = dec().matrixLU().cols(), dimker = cols - rank();
     if(dimker == 0)
     {
       // The Kernel is just {0}, so it doesn't have a basis properly speaking, but let's
@@ -590,10 +592,10 @@
       * independent vectors in Ker U.
       */
 
-    Matrix<int, Dynamic, 1, 0, MaxSmallDimAtCompileTime, 1> pivots(rank());
+    Matrix<Index, Dynamic, 1, 0, MaxSmallDimAtCompileTime, 1> pivots(rank());
     RealScalar premultiplied_threshold = dec().maxPivot() * dec().threshold();
-    int p = 0;
-    for(int i = 0; i < dec().nonzeroPivots(); ++i)
+    Index p = 0;
+    for(Index i = 0; i < dec().nonzeroPivots(); ++i)
       if(ei_abs(dec().matrixLU().coeff(i,i)) > premultiplied_threshold)
         pivots.coeffRef(p++) = i;
     ei_internal_assert(p == rank());
@@ -605,14 +607,14 @@
     Matrix<typename MatrixType::Scalar, Dynamic, Dynamic, MatrixType::Options,
            MaxSmallDimAtCompileTime, MatrixType::MaxColsAtCompileTime>
       m(dec().matrixLU().block(0, 0, rank(), cols));
-    for(int i = 0; i < rank(); ++i)
+    for(Index i = 0; i < rank(); ++i)
     {
       if(i) m.row(i).head(i).setZero();
       m.row(i).tail(cols-i) = dec().matrixLU().row(pivots.coeff(i)).tail(cols-i);
     }
     m.block(0, 0, rank(), rank());
     m.block(0, 0, rank(), rank()).template triangularView<StrictlyLower>().setZero();
-    for(int i = 0; i < rank(); ++i)
+    for(Index i = 0; i < rank(); ++i)
       m.col(i).swap(m.col(pivots.coeff(i)));
 
     // ok, we have our trapezoid matrix, we can apply the triangular solver.
@@ -624,13 +626,13 @@
       );
 
     // now we must undo the column permutation that we had applied!
-    for(int i = rank()-1; i >= 0; --i)
+    for(Index i = rank()-1; i >= 0; --i)
       m.col(i).swap(m.col(pivots.coeff(i)));
 
     // see the negative sign in the next line, that's what we were talking about above.
-    for(int i = 0; i < rank(); ++i) dst.row(dec().permutationQ().indices().coeff(i)) = -m.row(i).tail(dimker);
-    for(int i = rank(); i < cols; ++i) dst.row(dec().permutationQ().indices().coeff(i)).setZero();
-    for(int k = 0; k < dimker; ++k) dst.coeffRef(dec().permutationQ().indices().coeff(rank()+k), k) = Scalar(1);
+    for(Index i = 0; i < rank(); ++i) dst.row(dec().permutationQ().indices().coeff(i)) = -m.row(i).tail(dimker);
+    for(Index i = rank(); i < cols; ++i) dst.row(dec().permutationQ().indices().coeff(i)).setZero();
+    for(Index k = 0; k < dimker; ++k) dst.coeffRef(dec().permutationQ().indices().coeff(rank()+k), k) = Scalar(1);
   }
 };
 
@@ -658,15 +660,15 @@
       return;
     }
 
-    Matrix<int, Dynamic, 1, 0, MaxSmallDimAtCompileTime, 1> pivots(rank());
+    Matrix<Index, Dynamic, 1, 0, MaxSmallDimAtCompileTime, 1> pivots(rank());
     RealScalar premultiplied_threshold = dec().maxPivot() * dec().threshold();
-    int p = 0;
-    for(int i = 0; i < dec().nonzeroPivots(); ++i)
+    Index p = 0;
+    for(Index i = 0; i < dec().nonzeroPivots(); ++i)
       if(ei_abs(dec().matrixLU().coeff(i,i)) > premultiplied_threshold)
         pivots.coeffRef(p++) = i;
     ei_internal_assert(p == rank());
 
-    for(int i = 0; i < rank(); ++i)
+    for(Index i = 0; i < rank(); ++i)
       dst.col(i) = originalMatrix().col(dec().permutationQ().indices().coeff(pivots.coeff(i)));
   }
 };
@@ -689,10 +691,10 @@
      * Step 4: result = Q * c;
      */
 
-    const int rows = dec().rows(), cols = dec().cols(),
+    const Index rows = dec().rows(), cols = dec().cols(),
               nonzero_pivots = dec().nonzeroPivots();
     ei_assert(rhs().rows() == rows);
-    const int smalldim = std::min(rows, cols);
+    const Index smalldim = std::min(rows, cols);
 
     if(nonzero_pivots == 0)
     {
@@ -724,9 +726,9 @@
         .solveInPlace(c.topRows(nonzero_pivots));
 
     // Step 4
-    for(int i = 0; i < nonzero_pivots; ++i)
+    for(Index i = 0; i < nonzero_pivots; ++i)
       dst.row(dec().permutationQ().indices().coeff(i)) = c.row(i);
-    for(int i = nonzero_pivots; i < dec().matrixLU().cols(); ++i)
+    for(Index i = nonzero_pivots; i < dec().matrixLU().cols(); ++i)
       dst.row(dec().permutationQ().indices().coeff(i)).setZero();
   }
 };
diff --git a/Eigen/src/LU/Inverse.h b/Eigen/src/LU/Inverse.h
index 1e9d69a..ed1724d 100644
--- a/Eigen/src/LU/Inverse.h
+++ b/Eigen/src/LU/Inverse.h
@@ -281,7 +281,8 @@
 template<typename MatrixType>
 struct ei_inverse_impl : public ReturnByValue<ei_inverse_impl<MatrixType> >
 {
-  typedef typename MatrixType::Nested MatrixTypeNested;
+  typedef typename MatrixType::Index Index;
+  typedef typename ei_eval<MatrixType>::type MatrixTypeNested;
   typedef typename ei_cleantype<MatrixTypeNested>::type MatrixTypeNestedCleaned;
 
   const MatrixTypeNested m_matrix;
@@ -290,8 +291,8 @@
     : m_matrix(matrix)
   {}
 
-  inline int rows() const { return m_matrix.rows(); }
-  inline int cols() const { return m_matrix.cols(); }
+  inline Index rows() const { return m_matrix.rows(); }
+  inline Index cols() const { return m_matrix.cols(); }
 
   template<typename Dest> inline void evalTo(Dest& dst) const
   {
diff --git a/Eigen/src/LU/PartialPivLU.h b/Eigen/src/LU/PartialPivLU.h
index 695b7d7..39c348e 100644
--- a/Eigen/src/LU/PartialPivLU.h
+++ b/Eigen/src/LU/PartialPivLU.h
@@ -71,7 +71,9 @@
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef typename ei_plain_col_type<MatrixType, int>::type PermutationVectorType;
+    typedef typename ei_traits<MatrixType>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
+    typedef typename ei_plain_col_type<MatrixType, Index>::type PermutationVectorType;
     typedef PermutationMatrix<RowsAtCompileTime, MaxRowsAtCompileTime> PermutationType;
 
 
@@ -89,7 +91,7 @@
       * according to the specified problem \a size.
       * \sa PartialPivLU()
       */
-    PartialPivLU(int size);
+    PartialPivLU(Index size);
 
     /** Constructor.
       *
@@ -178,14 +180,14 @@
 
     MatrixType reconstructedMatrix() const;
 
-    inline int rows() const { return m_lu.rows(); }
-    inline int cols() const { return m_lu.cols(); }
+    inline Index rows() const { return m_lu.rows(); }
+    inline Index cols() const { return m_lu.cols(); }
 
   protected:
     MatrixType m_lu;
     PermutationType m_p;
     PermutationVectorType m_rowsTranspositions;
-    int m_det_p;
+    Index m_det_p;
     bool m_isInitialized;
 };
 
@@ -200,7 +202,7 @@
 }
 
 template<typename MatrixType>
-PartialPivLU<MatrixType>::PartialPivLU(int size)
+PartialPivLU<MatrixType>::PartialPivLU(Index size)
   : m_lu(size, size),
     m_p(size),
     m_rowsTranspositions(size),
@@ -233,6 +235,7 @@
   typedef Block<MapLU, Dynamic, Dynamic> MatrixType;
   typedef Block<MatrixType,Dynamic,Dynamic> BlockType;
   typedef typename MatrixType::RealScalar RealScalar;
+  typedef typename MatrixType::Index Index;
 
   /** \internal performs the LU decomposition in-place of the matrix \a lu
     * using an unblocked algorithm.
@@ -246,14 +249,14 @@
     *          undefined coefficients (to avoid generating inf/nan values). Returns true
     *          otherwise.
     */
-  static bool unblocked_lu(MatrixType& lu, int* row_transpositions, int& nb_transpositions)
+  static bool unblocked_lu(MatrixType& lu, Index* row_transpositions, Index& nb_transpositions)
   {
-    const int rows = lu.rows();
-    const int size = std::min(lu.rows(),lu.cols());
+    const Index rows = lu.rows();
+    const Index size = std::min(lu.rows(),lu.cols());
     nb_transpositions = 0;
-    for(int k = 0; k < size; ++k)
+    for(Index k = 0; k < size; ++k)
     {
-      int row_of_biggest_in_col;
+      Index row_of_biggest_in_col;
       RealScalar biggest_in_corner
         = lu.col(k).tail(rows-k).cwiseAbs().maxCoeff(&row_of_biggest_in_col);
       row_of_biggest_in_col += k;
@@ -265,7 +268,7 @@
         // the blocked_lu code can't guarantee the same.
         // before exiting, make sure to initialize the still uninitialized row_transpositions
         // in a sane state without destroying what we already have.
-        for(int i = k; i < size; i++)
+        for(Index i = k; i < size; i++)
           row_transpositions[i] = i;
         return false;
       }
@@ -280,8 +283,8 @@
 
       if(k<rows-1)
       {
-        int rrows = rows-k-1;
-        int rsize = size-k-1;
+        Index rrows = rows-k-1;
+        Index rsize = size-k-1;
         lu.col(k).tail(rrows) /= lu.coeff(k,k);
         lu.bottomRightCorner(rrows,rsize).noalias() -= lu.col(k).tail(rrows) * lu.row(k).tail(rsize);
       }
@@ -306,12 +309,12 @@
     *   1 - reduce the number of instanciations to the strict minimum
     *   2 - avoid infinite recursion of the instanciations with Block<Block<Block<...> > >
     */
-  static bool blocked_lu(int rows, int cols, Scalar* lu_data, int luStride, int* row_transpositions, int& nb_transpositions, int maxBlockSize=256)
+  static bool blocked_lu(Index rows, Index cols, Scalar* lu_data, Index luStride, Index* row_transpositions, Index& nb_transpositions, Index maxBlockSize=256)
   {
     MapLU lu1(lu_data,StorageOrder==RowMajor?rows:luStride,StorageOrder==RowMajor?luStride:cols);
     MatrixType lu(lu1,0,0,rows,cols);
 
-    const int size = std::min(rows,cols);
+    const Index size = std::min(rows,cols);
 
     // if the matrix is too small, no blocking:
     if(size<=16)
@@ -321,19 +324,19 @@
 
     // automatically adjust the number of subdivisions to the size
     // of the matrix so that there is enough sub blocks:
-    int blockSize;
+    Index blockSize;
     {
       blockSize = size/8;
       blockSize = (blockSize/16)*16;
-      blockSize = std::min(std::max(blockSize,8), maxBlockSize);
+      blockSize = std::min(std::max(blockSize,Index(8)), maxBlockSize);
     }
 
     nb_transpositions = 0;
-    for(int k = 0; k < size; k+=blockSize)
+    for(Index k = 0; k < size; k+=blockSize)
     {
-      int bs = std::min(size-k,blockSize); // actual size of the block
-      int trows = rows - k - bs; // trailing rows
-      int tsize = size - k - bs; // trailing size
+      Index bs = std::min(size-k,blockSize); // actual size of the block
+      Index trows = rows - k - bs; // trailing rows
+      Index tsize = size - k - bs; // trailing size
 
       // partition the matrix:
       //        A00 | A01 | A02
@@ -346,7 +349,7 @@
       BlockType A21(lu,k+bs,k,trows,bs);
       BlockType A22(lu,k+bs,k+bs,trows,tsize);
 
-      int nb_transpositions_in_panel;
+      Index nb_transpositions_in_panel;
       // recursively calls the blocked LU algorithm with a very small
       // blocking size:
       if(!blocked_lu(trows+bs, bs, &lu.coeffRef(k,k), luStride,
@@ -355,23 +358,23 @@
         // end quickly with undefined coefficients, just avoid generating inf/nan values.
         // before exiting, make sure to initialize the still uninitialized row_transpositions
         // in a sane state without destroying what we already have.
-        for(int i=k; i<size; ++i)
+        for(Index i=k; i<size; ++i)
           row_transpositions[i] = i;
         return false;
       }
       nb_transpositions += nb_transpositions_in_panel;
 
       // update permutations and apply them to A10
-      for(int i=k; i<k+bs; ++i)
+      for(Index i=k; i<k+bs; ++i)
       {
-        int piv = (row_transpositions[i] += k);
+        Index piv = (row_transpositions[i] += k);
         A_0.row(i).swap(A_0.row(piv));
       }
 
       if(trows)
       {
         // apply permutations to A_2
-        for(int i=k;i<k+bs; ++i)
+        for(Index i=k;i<k+bs; ++i)
           A_2.row(i).swap(A_2.row(row_transpositions[i]));
 
         // A12 = A11^-1 A12
@@ -387,7 +390,7 @@
 /** \internal performs the LU decomposition with partial pivoting in-place.
   */
 template<typename MatrixType, typename IntVector>
-void ei_partial_lu_inplace(MatrixType& lu, IntVector& row_transpositions, int& nb_transpositions)
+void ei_partial_lu_inplace(MatrixType& lu, IntVector& row_transpositions, typename MatrixType::Index& nb_transpositions)
 {
   ei_assert(lu.cols() == row_transpositions.size());
   ei_assert((&row_transpositions.coeffRef(1)-&row_transpositions.coeffRef(0)) == 1);
@@ -403,16 +406,16 @@
   m_lu = matrix;
 
   ei_assert(matrix.rows() == matrix.cols() && "PartialPivLU is only for square (and moreover invertible) matrices");
-  const int size = matrix.rows();
+  const Index size = matrix.rows();
 
   m_rowsTranspositions.resize(size);
 
-  int nb_transpositions;
+  Index nb_transpositions;
   ei_partial_lu_inplace(m_lu, m_rowsTranspositions, nb_transpositions);
   m_det_p = (nb_transpositions%2) ? -1 : 1;
 
   m_p.setIdentity(size);
-  for(int k = size-1; k >= 0; --k)
+  for(Index k = size-1; k >= 0; --k)
     m_p.applyTranspositionOnTheRight(k, m_rowsTranspositions.coeff(k));
 
   m_isInitialized = true;
diff --git a/Eigen/src/QR/ColPivHouseholderQR.h b/Eigen/src/QR/ColPivHouseholderQR.h
index fbc80ad..b4bcfd5 100644
--- a/Eigen/src/QR/ColPivHouseholderQR.h
+++ b/Eigen/src/QR/ColPivHouseholderQR.h
@@ -56,10 +56,11 @@
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
     typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime, Options, MaxRowsAtCompileTime, MaxRowsAtCompileTime> MatrixQType;
     typedef typename ei_plain_diag_type<MatrixType>::type HCoeffsType;
     typedef PermutationMatrix<ColsAtCompileTime, MaxColsAtCompileTime> PermutationType;
-    typedef typename ei_plain_row_type<MatrixType, int>::type IntRowVectorType;
+    typedef typename ei_plain_row_type<MatrixType, Index>::type IntRowVectorType;
     typedef typename ei_plain_row_type<MatrixType>::type RowVectorType;
     typedef typename ei_plain_row_type<MatrixType, RealScalar>::type RealRowVectorType;
     typedef typename HouseholderSequence<MatrixType,HCoeffsType>::ConjugateReturnType HouseholderSequenceType;
@@ -85,7 +86,7 @@
       * according to the specified problem \a size.
       * \sa ColPivHouseholderQR()
       */
-    ColPivHouseholderQR(int rows, int cols)
+    ColPivHouseholderQR(Index rows, Index cols)
       : m_qr(rows, cols),
         m_hCoeffs(std::min(rows,cols)),
         m_colsPermutation(cols),
@@ -186,12 +187,12 @@
       *       For that, it uses the threshold value that you can control by calling
       *       setThreshold(const RealScalar&).
       */
-    inline int rank() const
+    inline Index rank() const
     {
       ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
       RealScalar premultiplied_threshold = ei_abs(m_maxpivot) * threshold();
-      int result = 0;
-      for(int i = 0; i < m_nonzero_pivots; ++i)
+      Index result = 0;
+      for(Index i = 0; i < m_nonzero_pivots; ++i)
         result += (ei_abs(m_qr.coeff(i,i)) > premultiplied_threshold);
       return result;
     }
@@ -202,7 +203,7 @@
       *       For that, it uses the threshold value that you can control by calling
       *       setThreshold(const RealScalar&).
       */
-    inline int dimensionOfKernel() const
+    inline Index dimensionOfKernel() const
     {
       ei_assert(m_isInitialized && "ColPivHouseholderQR is not initialized.");
       return cols() - rank();
@@ -260,8 +261,8 @@
                (*this, MatrixType::Identity(m_qr.rows(), m_qr.cols()));
     }
 
-    inline int rows() const { return m_qr.rows(); }
-    inline int cols() const { return m_qr.cols(); }
+    inline Index rows() const { return m_qr.rows(); }
+    inline Index cols() const { return m_qr.cols(); }
     const HCoeffsType& hCoeffs() const { return m_hCoeffs; }
 
     /** Allows to prescribe a threshold to be used by certain methods, such as rank(),
@@ -320,7 +321,7 @@
       *
       * \sa rank()
       */
-    inline int nonzeroPivots() const
+    inline Index nonzeroPivots() const
     {
       ei_assert(m_isInitialized && "LU is not initialized.");
       return m_nonzero_pivots;
@@ -340,8 +341,8 @@
     RealRowVectorType m_colSqNorms;
     bool m_isInitialized, m_usePrescribedThreshold;
     RealScalar m_prescribedThreshold, m_maxpivot;
-    int m_nonzero_pivots;
-    int m_det_pq;
+    Index m_nonzero_pivots;
+    Index m_det_pq;
 };
 
 #ifndef EIGEN_HIDE_HEAVY_CODE
@@ -365,9 +366,9 @@
 template<typename MatrixType>
 ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const MatrixType& matrix)
 {
-  int rows = matrix.rows();
-  int cols = matrix.cols();
-  int size = matrix.diagonalSize();
+  Index rows = matrix.rows();
+  Index cols = matrix.cols();
+  Index size = matrix.diagonalSize();
 
   m_qr = matrix;
   m_hCoeffs.resize(size);
@@ -375,10 +376,10 @@
   m_temp.resize(cols);
 
   m_colsTranspositions.resize(matrix.cols());
-  int number_of_transpositions = 0;
+  Index number_of_transpositions = 0;
 
   m_colSqNorms.resize(cols);
-  for(int k = 0; k < cols; ++k)
+  for(Index k = 0; k < cols; ++k)
     m_colSqNorms.coeffRef(k) = m_qr.col(k).squaredNorm();
 
   RealScalar threshold_helper = m_colSqNorms.maxCoeff() * ei_abs2(NumTraits<Scalar>::epsilon()) / rows;
@@ -386,10 +387,10 @@
   m_nonzero_pivots = size; // the generic case is that in which all pivots are nonzero (invertible case)
   m_maxpivot = RealScalar(0);
 
-  for(int k = 0; k < size; ++k)
+  for(Index k = 0; k < size; ++k)
   {
     // first, we look up in our table m_colSqNorms which column has the biggest squared norm
-    int biggest_col_index;
+    Index biggest_col_index;
     RealScalar biggest_col_sq_norm = m_colSqNorms.tail(cols-k).maxCoeff(&biggest_col_index);
     biggest_col_index += k;
 
@@ -444,7 +445,7 @@
   }
 
   m_colsPermutation.setIdentity(cols);
-  for(int k = 0; k < m_nonzero_pivots; ++k)
+  for(Index k = 0; k < m_nonzero_pivots; ++k)
     m_colsPermutation.applyTranspositionOnTheRight(k, m_colsTranspositions.coeff(k));
 
   m_det_pq = (number_of_transpositions%2) ? -1 : 1;
@@ -461,12 +462,10 @@
 
   template<typename Dest> void evalTo(Dest& dst) const
   {
-#ifndef EIGEN_NO_DEBUG
-    const int rows = dec().rows();
-    ei_assert(rhs().rows() == rows);
-#endif
+    ei_assert(rhs().rows() == dec().rows());
+
     const int cols = dec().cols(),
-              nonzero_pivots = dec().nonzeroPivots();
+    nonzero_pivots = dec().nonzeroPivots();
 
     if(nonzero_pivots == 0)
     {
@@ -498,8 +497,8 @@
        .template triangularView<Upper>()
        * c.topRows(nonzero_pivots);
 
-    for(int i = 0; i < nonzero_pivots; ++i) dst.row(dec().colsPermutation().indices().coeff(i)) = c.row(i);
-    for(int i = nonzero_pivots; i < cols; ++i) dst.row(dec().colsPermutation().indices().coeff(i)).setZero();
+    for(Index i = 0; i < nonzero_pivots; ++i) dst.row(dec().colsPermutation().indices().coeff(i)) = c.row(i);
+    for(Index i = nonzero_pivots; i < cols; ++i) dst.row(dec().colsPermutation().indices().coeff(i)).setZero();
   }
 };
 
diff --git a/Eigen/src/QR/FullPivHouseholderQR.h b/Eigen/src/QR/FullPivHouseholderQR.h
index 0195e13..3b4d02d 100644
--- a/Eigen/src/QR/FullPivHouseholderQR.h
+++ b/Eigen/src/QR/FullPivHouseholderQR.h
@@ -56,11 +56,12 @@
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
     typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime, Options, MaxRowsAtCompileTime, MaxRowsAtCompileTime> MatrixQType;
     typedef typename ei_plain_diag_type<MatrixType>::type HCoeffsType;
-    typedef Matrix<int, 1, ColsAtCompileTime, RowMajor, 1, MaxColsAtCompileTime> IntRowVectorType;
+    typedef Matrix<Index, 1, ColsAtCompileTime, RowMajor, 1, MaxColsAtCompileTime> IntRowVectorType;
     typedef PermutationMatrix<ColsAtCompileTime, MaxColsAtCompileTime> PermutationType;
-    typedef typename ei_plain_col_type<MatrixType, int>::type IntColVectorType;
+    typedef typename ei_plain_col_type<MatrixType, Index>::type IntColVectorType;
     typedef typename ei_plain_row_type<MatrixType>::type RowVectorType;
     typedef typename ei_plain_col_type<MatrixType>::type ColVectorType;
 
@@ -84,7 +85,7 @@
       * according to the specified problem \a size.
       * \sa FullPivHouseholderQR()
       */
-    FullPivHouseholderQR(int rows, int cols)
+    FullPivHouseholderQR(Index rows, Index cols)
       : m_qr(rows, cols),
         m_hCoeffs(std::min(rows,cols)),
         m_rows_transpositions(rows),
@@ -188,7 +189,7 @@
       * \note This is computed at the time of the construction of the QR decomposition. This
       *       method does not perform any further computation.
       */
-    inline int rank() const
+    inline Index rank() const
     {
       ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
       return m_rank;
@@ -199,7 +200,7 @@
       * \note Since the rank is computed at the time of the construction of the QR decomposition, this
       *       method almost does not perform any further computation.
       */
-    inline int dimensionOfKernel() const
+    inline Index dimensionOfKernel() const
     {
       ei_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
       return m_qr.cols() - m_rank;
@@ -253,8 +254,8 @@
                (*this, MatrixType::Identity(m_qr.rows(), m_qr.cols()));
     }
 
-    inline int rows() const { return m_qr.rows(); }
-    inline int cols() const { return m_qr.cols(); }
+    inline Index rows() const { return m_qr.rows(); }
+    inline Index cols() const { return m_qr.cols(); }
     const HCoeffsType& hCoeffs() const { return m_hCoeffs; }
 
   protected:
@@ -266,8 +267,8 @@
     RowVectorType m_temp;
     bool m_isInitialized;
     RealScalar m_precision;
-    int m_rank;
-    int m_det_pq;
+    Index m_rank;
+    Index m_det_pq;
 };
 
 #ifndef EIGEN_HIDE_HEAVY_CODE
@@ -291,9 +292,9 @@
 template<typename MatrixType>
 FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(const MatrixType& matrix)
 {
-  int rows = matrix.rows();
-  int cols = matrix.cols();
-  int size = std::min(rows,cols);
+  Index rows = matrix.rows();
+  Index cols = matrix.cols();
+  Index size = std::min(rows,cols);
   m_rank = size;
 
   m_qr = matrix;
@@ -305,13 +306,13 @@
 
   m_rows_transpositions.resize(matrix.rows());
   m_cols_transpositions.resize(matrix.cols());
-  int number_of_transpositions = 0;
+  Index number_of_transpositions = 0;
 
   RealScalar biggest(0);
 
-  for (int k = 0; k < size; ++k)
+  for (Index k = 0; k < size; ++k)
   {
-    int row_of_biggest_in_corner, col_of_biggest_in_corner;
+    Index row_of_biggest_in_corner, col_of_biggest_in_corner;
     RealScalar biggest_in_corner;
 
     biggest_in_corner = m_qr.bottomRightCorner(rows-k, cols-k)
@@ -325,7 +326,7 @@
     if(ei_isMuchSmallerThan(biggest_in_corner, biggest, m_precision))
     {
       m_rank = k;
-      for(int i = k; i < size; i++)
+      for(Index i = k; i < size; i++)
       {
         m_rows_transpositions.coeffRef(i) = i;
         m_cols_transpositions.coeffRef(i) = i;
@@ -354,7 +355,7 @@
   }
 
   m_cols_permutation.setIdentity(cols);
-  for(int k = 0; k < size; ++k)
+  for(Index k = 0; k < size; ++k)
     m_cols_permutation.applyTranspositionOnTheRight(k, m_cols_transpositions.coeff(k));
 
   m_det_pq = (number_of_transpositions%2) ? -1 : 1;
@@ -371,7 +372,7 @@
 
   template<typename Dest> void evalTo(Dest& dst) const
   {
-    const int rows = dec().rows(), cols = dec().cols();
+    const Index rows = dec().rows(), cols = dec().cols();
     ei_assert(rhs().rows() == rows);
 
     // FIXME introduce nonzeroPivots() and use it here. and more generally,
@@ -385,9 +386,9 @@
     typename Rhs::PlainObject c(rhs());
 
     Matrix<Scalar,1,Rhs::ColsAtCompileTime> temp(rhs().cols());
-    for (int k = 0; k < dec().rank(); ++k)
+    for (Index k = 0; k < dec().rank(); ++k)
     {
-      int remainingSize = rows-k;
+      Index remainingSize = rows-k;
       c.row(k).swap(c.row(dec().rowsTranspositions().coeff(k)));
       c.bottomRightCorner(remainingSize, rhs().cols())
        .applyHouseholderOnTheLeft(dec().matrixQR().col(k).tail(remainingSize-1),
@@ -409,8 +410,8 @@
        .template triangularView<Upper>()
        .solveInPlace(c.topRows(dec().rank()));
 
-    for(int i = 0; i < dec().rank(); ++i) dst.row(dec().colsPermutation().indices().coeff(i)) = c.row(i);
-    for(int i = dec().rank(); i < cols; ++i) dst.row(dec().colsPermutation().indices().coeff(i)).setZero();
+    for(Index i = 0; i < dec().rank(); ++i) dst.row(dec().colsPermutation().indices().coeff(i)) = c.row(i);
+    for(Index i = dec().rank(); i < cols; ++i) dst.row(dec().colsPermutation().indices().coeff(i)).setZero();
   }
 };
 
@@ -422,12 +423,12 @@
   // compute the product H'_0 H'_1 ... H'_n-1,
   // where H_k is the k-th Householder transformation I - h_k v_k v_k'
   // and v_k is the k-th Householder vector [1,m_qr(k+1,k), m_qr(k+2,k), ...]
-  int rows = m_qr.rows();
-  int cols = m_qr.cols();
-  int size = std::min(rows,cols);
+  Index rows = m_qr.rows();
+  Index cols = m_qr.cols();
+  Index size = std::min(rows,cols);
   MatrixQType res = MatrixQType::Identity(rows, rows);
   Matrix<Scalar,1,MatrixType::RowsAtCompileTime> temp(rows);
-  for (int k = size-1; k >= 0; k--)
+  for (Index k = size-1; k >= 0; k--)
   {
     res.block(k, k, rows-k, rows-k)
        .applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), ei_conj(m_hCoeffs.coeff(k)), &temp.coeffRef(k));
diff --git a/Eigen/src/QR/HouseholderQR.h b/Eigen/src/QR/HouseholderQR.h
index 6a28839..a8caacc 100644
--- a/Eigen/src/QR/HouseholderQR.h
+++ b/Eigen/src/QR/HouseholderQR.h
@@ -60,6 +60,7 @@
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
     typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime, ei_traits<MatrixType>::Flags&RowMajorBit ? RowMajor : ColMajor, MaxRowsAtCompileTime, MaxRowsAtCompileTime> MatrixQType;
     typedef typename ei_plain_diag_type<MatrixType>::type HCoeffsType;
     typedef typename ei_plain_row_type<MatrixType>::type RowVectorType;
@@ -79,7 +80,7 @@
       * according to the specified problem \a size.
       * \sa HouseholderQR()
       */
-    HouseholderQR(int rows, int cols)
+    HouseholderQR(Index rows, Index cols)
       : m_qr(rows, cols),
         m_hCoeffs(std::min(rows,cols)),
         m_temp(cols),
@@ -165,8 +166,8 @@
       */
     typename MatrixType::RealScalar logAbsDeterminant() const;
 
-    inline int rows() const { return m_qr.rows(); }
-    inline int cols() const { return m_qr.cols(); }
+    inline Index rows() const { return m_qr.rows(); }
+    inline Index cols() const { return m_qr.cols(); }
     const HCoeffsType& hCoeffs() const { return m_hCoeffs; }
 
   protected:
@@ -197,19 +198,19 @@
 template<typename MatrixType>
 HouseholderQR<MatrixType>& HouseholderQR<MatrixType>::compute(const MatrixType& matrix)
 {
-  int rows = matrix.rows();
-  int cols = matrix.cols();
-  int size = std::min(rows,cols);
+  Index rows = matrix.rows();
+  Index cols = matrix.cols();
+  Index size = std::min(rows,cols);
 
   m_qr = matrix;
   m_hCoeffs.resize(size);
 
   m_temp.resize(cols);
 
-  for(int k = 0; k < size; ++k)
+  for(Index k = 0; k < size; ++k)
   {
-    int remainingRows = rows - k;
-    int remainingCols = cols - k - 1;
+    Index remainingRows = rows - k;
+    Index remainingCols = cols - k - 1;
 
     RealScalar beta;
     m_qr.col(k).tail(remainingRows).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta);
@@ -231,8 +232,8 @@
 
   template<typename Dest> void evalTo(Dest& dst) const
   {
-    const int rows = dec().rows(), cols = dec().cols();
-    const int rank = std::min(rows, cols);
+    const Index rows = dec().rows(), cols = dec().cols();
+    const Index rank = std::min(rows, cols);
     ei_assert(rhs().rows() == rows);
 
     typename Rhs::PlainObject c(rhs());
diff --git a/Eigen/src/SVD/JacobiSVD.h b/Eigen/src/SVD/JacobiSVD.h
index 9323c01..2925306 100644
--- a/Eigen/src/SVD/JacobiSVD.h
+++ b/Eigen/src/SVD/JacobiSVD.h
@@ -1,7 +1,7 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2009-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // Eigen is free software; you can redistribute it and/or
 // modify it under the terms of the GNU Lesser General Public
@@ -63,6 +63,7 @@
   private:
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
+    typedef typename MatrixType::Index Index;
     enum {
       ComputeU = (Options & SkipU) == 0,
       ComputeV = (Options & SkipV) == 0,
@@ -107,7 +108,7 @@
       * according to the specified problem \a size.
       * \sa JacobiSVD()
       */
-    JacobiSVD(int rows, int cols) : m_matrixU(rows, rows),
+    JacobiSVD(Index rows, Index cols) : m_matrixU(rows, rows),
                                     m_matrixV(cols, cols),
                                     m_singularValues(std::min(rows, cols)),
                                     m_workMatrix(rows, cols),
@@ -119,7 +120,7 @@
                                           m_workMatrix(),
                                           m_isInitialized(false)
     {
-      const int minSize = std::min(matrix.rows(), matrix.cols());
+      const Index minSize = std::min(matrix.rows(), matrix.cols());
       m_singularValues.resize(minSize);
       m_workMatrix.resize(minSize, minSize);
       compute(matrix);
@@ -164,7 +165,8 @@
 struct ei_svd_precondition_2x2_block_to_be_real<MatrixType, Options, false>
 {
   typedef JacobiSVD<MatrixType, Options> SVD;
-  static void run(typename SVD::WorkMatrixType&, JacobiSVD<MatrixType, Options>&, int, int) {}
+  typedef typename SVD::Index Index;
+  static void run(typename SVD::WorkMatrixType&, JacobiSVD<MatrixType, Options>&, Index, Index) {}
 };
 
 template<typename MatrixType, unsigned int Options>
@@ -173,8 +175,9 @@
   typedef JacobiSVD<MatrixType, Options> SVD;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename MatrixType::RealScalar RealScalar;
+  typedef typename SVD::Index Index;
   enum { ComputeU = SVD::ComputeU, ComputeV = SVD::ComputeV };
-  static void run(typename SVD::WorkMatrixType& work_matrix, JacobiSVD<MatrixType, Options>& svd, int p, int q)
+  static void run(typename SVD::WorkMatrixType& work_matrix, JacobiSVD<MatrixType, Options>& svd, Index p, Index q)
   {
     Scalar z;
     PlanarRotation<Scalar> rot;
@@ -210,8 +213,8 @@
   }
 };
 
-template<typename MatrixType, typename RealScalar>
-void ei_real_2x2_jacobi_svd(const MatrixType& matrix, int p, int q,
+template<typename MatrixType, typename RealScalar, typename Index>
+void ei_real_2x2_jacobi_svd(const MatrixType& matrix, Index p, Index q,
                             PlanarRotation<RealScalar> *j_left,
                             PlanarRotation<RealScalar> *j_right)
 {
@@ -250,12 +253,13 @@
   typedef JacobiSVD<MatrixType, Options> SVD;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename MatrixType::RealScalar RealScalar;
+  typedef typename MatrixType::Index Index;
   enum { ComputeU = SVD::ComputeU, ComputeV = SVD::ComputeV };
   static bool run(const MatrixType& matrix, typename SVD::WorkMatrixType& work_matrix, SVD& svd)
   {
-    int rows = matrix.rows();
-    int cols = matrix.cols();
-    int diagSize = cols;
+    Index rows = matrix.rows();
+    Index cols = matrix.cols();
+    Index diagSize = cols;
     if(rows > cols)
     {
       FullPivHouseholderQR<MatrixType> qr(matrix);
@@ -282,6 +286,7 @@
   typedef JacobiSVD<MatrixType, Options> SVD;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename MatrixType::RealScalar RealScalar;
+  typedef typename MatrixType::Index Index;
   enum {
     ComputeU = SVD::ComputeU,
     ComputeV = SVD::ComputeV,
@@ -294,9 +299,9 @@
 
   static bool run(const MatrixType& matrix, typename SVD::WorkMatrixType& work_matrix, SVD& svd)
   {
-    int rows = matrix.rows();
-    int cols = matrix.cols();
-    int diagSize = rows;
+    Index rows = matrix.rows();
+    Index cols = matrix.cols();
+    Index diagSize = rows;
     if(cols > rows)
     {
       typedef Matrix<Scalar,ColsAtCompileTime,RowsAtCompileTime,
@@ -315,9 +320,9 @@
 template<typename MatrixType, unsigned int Options>
 JacobiSVD<MatrixType, Options>& JacobiSVD<MatrixType, Options>::compute(const MatrixType& matrix)
 {
-  int rows = matrix.rows();
-  int cols = matrix.cols();
-  int diagSize = std::min(rows, cols);
+  Index rows = matrix.rows();
+  Index cols = matrix.cols();
+  Index diagSize = std::min(rows, cols);
   m_singularValues.resize(diagSize);
   const RealScalar precision = 2 * NumTraits<Scalar>::epsilon();
 
@@ -333,9 +338,9 @@
   while(!finished)
   {
     finished = true;
-    for(int p = 1; p < diagSize; ++p)
+    for(Index p = 1; p < diagSize; ++p)
     {
-      for(int q = 0; q < p; ++q)
+      for(Index q = 0; q < p; ++q)
       {
         if(std::max(ei_abs(m_workMatrix.coeff(p,q)),ei_abs(m_workMatrix.coeff(q,p)))
             > std::max(ei_abs(m_workMatrix.coeff(p,p)),ei_abs(m_workMatrix.coeff(q,q)))*precision)
@@ -356,16 +361,16 @@
     }
   }
 
-  for(int i = 0; i < diagSize; ++i)
+  for(Index i = 0; i < diagSize; ++i)
   {
     RealScalar a = ei_abs(m_workMatrix.coeff(i,i));
     m_singularValues.coeffRef(i) = a;
     if(ComputeU && (a!=RealScalar(0))) m_matrixU.col(i) *= m_workMatrix.coeff(i,i)/a;
   }
 
-  for(int i = 0; i < diagSize; i++)
+  for(Index i = 0; i < diagSize; i++)
   {
-    int pos;
+    Index pos;
     m_singularValues.tail(diagSize-i).maxCoeff(&pos);
     if(pos)
     {
diff --git a/Eigen/src/SVD/SVD.h b/Eigen/src/SVD/SVD.h
index a9e22df..7360562 100644
--- a/Eigen/src/SVD/SVD.h
+++ b/Eigen/src/SVD/SVD.h
@@ -46,6 +46,7 @@
     typedef _MatrixType MatrixType;
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
+    typedef typename MatrixType::Index Index;
 
     enum {
       RowsAtCompileTime = MatrixType::RowsAtCompileTime,
@@ -79,7 +80,7 @@
       * according to the specified problem \a size.
       * \sa JacobiSVD()
       */
-    SVD(int rows, int cols) : m_matU(rows, rows),
+    SVD(Index rows, Index cols) : m_matU(rows, rows),
                               m_matV(cols,cols),
                               m_sigma(std::min(rows, cols)),
                               m_workMatrix(rows, cols),
@@ -143,13 +144,13 @@
     template<typename ScalingType, typename RotationType>
     void computeScalingRotation(ScalingType *positive, RotationType *unitary) const;
 
-    inline int rows() const
+    inline Index rows() const
     {
       ei_assert(m_isInitialized && "SVD is not initialized.");
       return m_rows;
     }
 
-    inline int cols() const
+    inline Index cols() const
     {
       ei_assert(m_isInitialized && "SVD is not initialized.");
       return m_cols;
@@ -182,7 +183,7 @@
     MatrixType m_workMatrix;
     RowVector m_rv1;
     bool m_isInitialized;
-    int m_rows, m_cols;
+    Index m_rows, m_cols;
 };
 
 /** Computes / recomputes the SVD decomposition A = U S V^* of \a matrix
@@ -194,8 +195,8 @@
 template<typename MatrixType>
 SVD<MatrixType>& SVD<MatrixType>::compute(const MatrixType& matrix)
 {
-  const int m = m_rows = matrix.rows();
-  const int n = m_cols = matrix.cols();
+  const Index m = m_rows = matrix.rows();
+  const Index n = m_cols = matrix.cols();
 
   m_matU.resize(m, m);
   m_matU.setZero();
@@ -203,14 +204,14 @@
   m_matV.resize(n,n);
   m_workMatrix = matrix;
 
-  int max_iters = 30;
+  Index max_iters = 30;
 
   MatrixVType& V = m_matV;
   MatrixType& A = m_workMatrix;
   SingularValuesType& W = m_sigma;
 
   bool flag;
-  int i=0,its=0,j=0,k=0,l=0,nm=0;
+  Index i=0,its=0,j=0,k=0,l=0,nm=0;
   Scalar anorm, c, f, g, h, s, scale, x, y, z;
   bool convergence = true;
   Scalar eps = NumTraits<Scalar>::dummy_precision();
@@ -426,9 +427,9 @@
 
   // sort the singular values:
   {
-    for (int i=0; i<n; i++)
+    for (Index i=0; i<n; i++)
     {
-      int k;
+      Index k;
       W.tail(n-i).maxCoeff(&k);
       if (k != 0)
       {
@@ -459,11 +460,11 @@
   {
     ei_assert(rhs().rows() == dec().rows());
 
-    for (int j=0; j<cols(); ++j)
+    for (Index j=0; j<cols(); ++j)
     {
       Matrix<Scalar,MatrixType::RowsAtCompileTime,1> aux = dec().matrixU().adjoint() * rhs().col(j);
 
-      for (int i = 0; i < dec().rows(); ++i)
+      for (Index i = 0; i < dec().rows(); ++i)
       {
         Scalar si = dec().singularValues().coeff(i);
         if(si == RealScalar(0))
@@ -471,7 +472,7 @@
         else
           aux.coeffRef(i) /= si;
       }
-      const int minsize = std::min(dec().rows(),dec().cols());
+      const Index minsize = std::min(dec().rows(),dec().cols());
       dst.col(j).head(minsize) = aux.head(minsize);
       if(dec().cols()>dec().rows()) dst.col(j).tail(cols()-minsize).setZero();
       dst.col(j) = dec().matrixV() * dst.col(j);
diff --git a/Eigen/src/SVD/UpperBidiagonalization.h b/Eigen/src/SVD/UpperBidiagonalization.h
index 53e0407..1e1355b 100644
--- a/Eigen/src/SVD/UpperBidiagonalization.h
+++ b/Eigen/src/SVD/UpperBidiagonalization.h
@@ -37,6 +37,7 @@
     };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
     typedef Matrix<Scalar, 1, ColsAtCompileTime> RowVectorType;
     typedef Matrix<Scalar, RowsAtCompileTime, 1> ColVectorType;
     typedef BandMatrix<RealScalar, ColsAtCompileTime, ColsAtCompileTime, 1, 0> BidiagonalType;
@@ -95,8 +96,8 @@
 template<typename _MatrixType>
 UpperBidiagonalization<_MatrixType>& UpperBidiagonalization<_MatrixType>::compute(const _MatrixType& matrix)
 {
-  int rows = matrix.rows();
-  int cols = matrix.cols();
+  Index rows = matrix.rows();
+  Index cols = matrix.cols();
   
   ei_assert(rows >= cols && "UpperBidiagonalization is only for matrices satisfying rows>=cols.");
   
@@ -104,10 +105,10 @@
 
   ColVectorType temp(rows);
 
-  for (int k = 0; /* breaks at k==cols-1 below */ ; ++k)
+  for (Index k = 0; /* breaks at k==cols-1 below */ ; ++k)
   {
-    int remainingRows = rows - k;
-    int remainingCols = cols - k - 1;
+    Index remainingRows = rows - k;
+    Index remainingCols = cols - k - 1;
 
     // construct left householder transform in-place in m_householder
     m_householder.col(k).tail(remainingRows)
diff --git a/Eigen/src/Sparse/AmbiVector.h b/Eigen/src/Sparse/AmbiVector.h
index 1ac2827..7b18f8c 100644
--- a/Eigen/src/Sparse/AmbiVector.h
+++ b/Eigen/src/Sparse/AmbiVector.h
@@ -35,7 +35,8 @@
   public:
     typedef _Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
-    AmbiVector(int size)
+    typedef SparseIndex Index;
+    AmbiVector(Index size)
       : m_buffer(0), m_zero(0), m_size(0), m_allocatedSize(0), m_allocatedElements(0), m_mode(-1)
     {
       resize(size);
@@ -44,40 +45,40 @@
     void init(double estimatedDensity);
     void init(int mode);
 
-    int nonZeros() const;
+    Index nonZeros() const;
 
     /** Specifies a sub-vector to work on */
-    void setBounds(int start, int end) { m_start = start; m_end = end; }
+    void setBounds(Index start, Index end) { m_start = start; m_end = end; }
 
     void setZero();
 
     void restart();
-    Scalar& coeffRef(int i);
-    Scalar& coeff(int i);
+    Scalar& coeffRef(Index i);
+    Scalar& coeff(Index i);
 
     class Iterator;
 
     ~AmbiVector() { delete[] m_buffer; }
 
-    void resize(int size)
+    void resize(Index size)
     {
       if (m_allocatedSize < size)
         reallocate(size);
       m_size = size;
     }
 
-    int size() const { return m_size; }
+    Index size() const { return m_size; }
 
   protected:
 
-    void reallocate(int size)
+    void reallocate(Index size)
     {
       // if the size of the matrix is not too large, let's allocate a bit more than needed such
       // that we can handle dense vector even in sparse mode.
       delete[] m_buffer;
       if (size<1000)
       {
-        int allocSize = (size * sizeof(ListEl))/sizeof(Scalar);
+        Index allocSize = (size * sizeof(ListEl))/sizeof(Scalar);
         m_allocatedElements = (allocSize*sizeof(Scalar))/sizeof(ListEl);
         m_buffer = new Scalar[allocSize];
       }
@@ -93,9 +94,9 @@
 
     void reallocateSparse()
     {
-      int copyElements = m_allocatedElements;
-      m_allocatedElements = std::min(int(m_allocatedElements*1.5),m_size);
-      int allocSize = m_allocatedElements * sizeof(ListEl);
+      Index copyElements = m_allocatedElements;
+      m_allocatedElements = std::min(Index(m_allocatedElements*1.5),m_size);
+      Index allocSize = m_allocatedElements * sizeof(ListEl);
       allocSize = allocSize/sizeof(Scalar) + (allocSize%sizeof(Scalar)>0?1:0);
       Scalar* newBuffer = new Scalar[allocSize];
       memcpy(newBuffer,  m_buffer,  copyElements * sizeof(ListEl));
@@ -107,30 +108,30 @@
     // element type of the linked list
     struct ListEl
     {
-      int next;
-      int index;
+      Index next;
+      Index index;
       Scalar value;
     };
 
     // used to store data in both mode
     Scalar* m_buffer;
     Scalar m_zero;
-    int m_size;
-    int m_start;
-    int m_end;
-    int m_allocatedSize;
-    int m_allocatedElements;
-    int m_mode;
+    Index m_size;
+    Index m_start;
+    Index m_end;
+    Index m_allocatedSize;
+    Index m_allocatedElements;
+    Index m_mode;
 
     // linked list mode
-    int m_llStart;
-    int m_llCurrent;
-    int m_llSize;
+    Index m_llStart;
+    Index m_llCurrent;
+    Index m_llSize;
 };
 
 /** \returns the number of non zeros in the current sub vector */
 template<typename Scalar>
-int AmbiVector<Scalar>::nonZeros() const
+SparseIndex AmbiVector<Scalar>::nonZeros() const
 {
   if (m_mode==IsSparse)
     return m_llSize;
@@ -175,7 +176,7 @@
 {
   if (m_mode==IsDense)
   {
-    for (int i=m_start; i<m_end; ++i)
+    for (Index i=m_start; i<m_end; ++i)
       m_buffer[i] = Scalar(0);
   }
   else
@@ -187,7 +188,7 @@
 }
 
 template<typename Scalar>
-Scalar& AmbiVector<Scalar>::coeffRef(int i)
+Scalar& AmbiVector<Scalar>::coeffRef(Index i)
 {
   if (m_mode==IsDense)
     return m_buffer[i];
@@ -221,7 +222,7 @@
     }
     else
     {
-      int nextel = llElements[m_llCurrent].next;
+      Index nextel = llElements[m_llCurrent].next;
       ei_assert(i>=llElements[m_llCurrent].index && "you must call restart() before inserting an element with lower or equal index");
       while (nextel >= 0 && llElements[nextel].index<=i)
       {
@@ -256,7 +257,7 @@
 }
 
 template<typename Scalar>
-Scalar& AmbiVector<Scalar>::coeff(int i)
+Scalar& AmbiVector<Scalar>::coeff(Index i)
 {
   if (m_mode==IsDense)
     return m_buffer[i];
@@ -270,7 +271,7 @@
     }
     else
     {
-      int elid = m_llStart;
+      Index elid = m_llStart;
       while (elid >= 0 && llElements[elid].index<i)
         elid = llElements[elid].next;
 
@@ -327,7 +328,7 @@
       }
     }
 
-    int index() const { return m_cachedIndex; }
+    Index index() const { return m_cachedIndex; }
     Scalar value() const { return m_cachedValue; }
 
     operator bool() const { return m_cachedIndex>=0; }
@@ -365,9 +366,9 @@
 
   protected:
     const AmbiVector& m_vector; // the target vector
-    int m_currentEl;            // the current element in sparse/linked-list mode
+    Index m_currentEl;            // the current element in sparse/linked-list mode
     RealScalar m_epsilon;       // epsilon used to prune zero coefficients
-    int m_cachedIndex;          // current coordinate
+    Index m_cachedIndex;          // current coordinate
     Scalar m_cachedValue;       // current value
     bool m_isDense;             // mode of the vector
 };
diff --git a/Eigen/src/Sparse/CholmodSupport.h b/Eigen/src/Sparse/CholmodSupport.h
index cf40724..82a09f3 100644
--- a/Eigen/src/Sparse/CholmodSupport.h
+++ b/Eigen/src/Sparse/CholmodSupport.h
@@ -114,8 +114,8 @@
 {
   m_innerSize = cm.nrow;
   m_outerSize = cm.ncol;
-  m_outerIndex = reinterpret_cast<int*>(cm.p);
-  m_innerIndices = reinterpret_cast<int*>(cm.i);
+  m_outerIndex = reinterpret_cast<Index*>(cm.p);
+  m_innerIndices = reinterpret_cast<Index*>(cm.i);
   m_values = reinterpret_cast<Scalar*>(cm.x);
   m_nnz = m_outerIndex[cm.ncol];
 }
@@ -220,7 +220,7 @@
 template<typename Derived>
 bool SparseLLT<MatrixType,Cholmod>::solveInPlace(MatrixBase<Derived> &b) const
 {
-  const int size = m_cholmodFactor->n;
+  const Index size = m_cholmodFactor->n;
   ei_assert(size==b.rows());
 
   // this uses Eigen's triangular sparse solver
diff --git a/Eigen/src/Sparse/CompressedStorage.h b/Eigen/src/Sparse/CompressedStorage.h
index 4fc1797..37d3376 100644
--- a/Eigen/src/Sparse/CompressedStorage.h
+++ b/Eigen/src/Sparse/CompressedStorage.h
@@ -32,6 +32,7 @@
 class CompressedStorage
 {
     typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef SparseIndex Index;
   public:
     CompressedStorage()
       : m_values(0), m_indices(0), m_size(0), m_allocatedSize(0)
@@ -53,7 +54,7 @@
     {
       resize(other.size());
       memcpy(m_values, other.m_values, m_size * sizeof(Scalar));
-      memcpy(m_indices, other.m_indices, m_size * sizeof(int));
+      memcpy(m_indices, other.m_indices, m_size * sizeof(Index));
       return *this;
     }
 
@@ -91,9 +92,9 @@
       m_size = size;
     }
 
-    void append(const Scalar& v, int i)
+    void append(const Scalar& v, Index i)
     {
-      int id = static_cast<int>(m_size);
+      Index id = static_cast<Index>(m_size);
       resize(m_size+1, 1);
       m_values[id] = v;
       m_indices[id] = i;
@@ -106,10 +107,10 @@
     inline Scalar& value(size_t i) { return m_values[i]; }
     inline const Scalar& value(size_t i) const { return m_values[i]; }
 
-    inline int& index(size_t i) { return m_indices[i]; }
-    inline const int& index(size_t i) const { return m_indices[i]; }
+    inline Index& index(size_t i) { return m_indices[i]; }
+    inline const Index& index(size_t i) const { return m_indices[i]; }
 
-    static CompressedStorage Map(int* indices, Scalar* values, size_t size)
+    static CompressedStorage Map(Index* indices, Scalar* values, size_t size)
     {
       CompressedStorage res;
       res.m_indices = indices;
@@ -119,13 +120,13 @@
     }
     
     /** \returns the largest \c k such that for all \c j in [0,k) index[\c j]\<\a key */
-    inline int searchLowerIndex(int key) const
+    inline Index searchLowerIndex(Index key) const
     {
       return searchLowerIndex(0, m_size, key);
     }
     
     /** \returns the largest \c k in [start,end) such that for all \c j in [start,k) index[\c j]\<\a key */
-    inline int searchLowerIndex(size_t start, size_t end, int key) const
+    inline Index searchLowerIndex(size_t start, size_t end, Index key) const
     {
       while(end>start)
       {
@@ -135,12 +136,12 @@
         else
           end = mid;
       }
-      return static_cast<int>(start);
+      return static_cast<Index>(start);
     }
     
     /** \returns the stored value at index \a key
       * If the value does not exist, then the value \a defaultValue is returned without any insertion. */
-    inline Scalar at(int key, Scalar defaultValue = Scalar(0)) const
+    inline Scalar at(Index key, Scalar defaultValue = Scalar(0)) const
     {
       if (m_size==0)
         return defaultValue;
@@ -153,7 +154,7 @@
     }
     
     /** Like at(), but the search is performed in the range [start,end) */
-    inline Scalar atInRange(size_t start, size_t end, int key, Scalar defaultValue = Scalar(0)) const
+    inline Scalar atInRange(size_t start, size_t end, Index key, Scalar defaultValue = Scalar(0)) const
     {
       if (start>=end)
         return Scalar(0);
@@ -168,7 +169,7 @@
     /** \returns a reference to the value at index \a key
       * If the value does not exist, then the value \a defaultValue is inserted
       * such that the keys are sorted. */
-    inline Scalar& atWithInsertion(int key, Scalar defaultValue = Scalar(0))
+    inline Scalar& atWithInsertion(Index key, Scalar defaultValue = Scalar(0))
     {
       size_t id = searchLowerIndex(0,m_size,key);
       if (id>=m_size || m_indices[id]!=key)
@@ -206,11 +207,11 @@
     inline void reallocate(size_t size)
     {
       Scalar* newValues  = new Scalar[size];
-      int* newIndices = new int[size];
+      Index* newIndices = new Index[size];
       size_t copySize = std::min(size, m_size);
       // copy
       memcpy(newValues,  m_values,  copySize * sizeof(Scalar));
-      memcpy(newIndices, m_indices, copySize * sizeof(int));
+      memcpy(newIndices, m_indices, copySize * sizeof(Index));
       // delete old stuff
       delete[] m_values;
       delete[] m_indices;
@@ -221,7 +222,7 @@
 
   protected:
     Scalar* m_values;
-    int* m_indices;
+    Index* m_indices;
     size_t m_size;
     size_t m_allocatedSize;
 
diff --git a/Eigen/src/Sparse/CoreIterators.h b/Eigen/src/Sparse/CoreIterators.h
index 6978045..7ae847d 100644
--- a/Eigen/src/Sparse/CoreIterators.h
+++ b/Eigen/src/Sparse/CoreIterators.h
@@ -38,9 +38,11 @@
 template<typename Derived> class DenseBase<Derived>::InnerIterator
 {
     typedef typename Derived::Scalar Scalar;
+    typedef typename Derived::Index Index;
+
     enum { IsRowMajor = (Derived::Flags&RowMajorBit)==RowMajorBit };
   public:
-    EIGEN_STRONG_INLINE InnerIterator(const Derived& expr, int outer)
+    EIGEN_STRONG_INLINE InnerIterator(const Derived& expr, Index outer)
       : m_expression(expr), m_inner(0), m_outer(outer), m_end(expr.rows())
     {}
 
@@ -52,17 +54,17 @@
 
     EIGEN_STRONG_INLINE InnerIterator& operator++() { m_inner++; return *this; }
 
-    EIGEN_STRONG_INLINE int index() const { return m_inner; }
-    inline int row() const { return IsRowMajor ? m_outer : index(); }
-    inline int col() const { return IsRowMajor ? index() : m_outer; }
+    EIGEN_STRONG_INLINE Index index() const { return m_inner; }
+    inline Index row() const { return IsRowMajor ? m_outer : index(); }
+    inline Index col() const { return IsRowMajor ? index() : m_outer; }
 
     EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
 
   protected:
     const Derived& m_expression;
-    int m_inner;
-    const int m_outer;
-    const int m_end;
+    Index m_inner;
+    const Index m_outer;
+    const Index m_end;
 };
 
 #endif // EIGEN_COREITERATORS_H
diff --git a/Eigen/src/Sparse/DynamicSparseMatrix.h b/Eigen/src/Sparse/DynamicSparseMatrix.h
index fd7c7fb..fea707f 100644
--- a/Eigen/src/Sparse/DynamicSparseMatrix.h
+++ b/Eigen/src/Sparse/DynamicSparseMatrix.h
@@ -75,16 +75,16 @@
 
     typedef DynamicSparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
 
-    int m_innerSize;
+    Index m_innerSize;
     std::vector<CompressedStorage<Scalar> > m_data;
 
   public:
 
-    inline int rows() const { return IsRowMajor ? outerSize() : m_innerSize; }
-    inline int cols() const { return IsRowMajor ? m_innerSize : outerSize(); }
-    inline int innerSize() const { return m_innerSize; }
-    inline int outerSize() const { return static_cast<int>(m_data.size()); }
-    inline int innerNonZeros(int j) const { return m_data[j].size(); }
+    inline Index rows() const { return IsRowMajor ? outerSize() : m_innerSize; }
+    inline Index cols() const { return IsRowMajor ? m_innerSize : outerSize(); }
+    inline Index innerSize() const { return m_innerSize; }
+    inline Index outerSize() const { return static_cast<Index>(m_data.size()); }
+    inline Index innerNonZeros(Index j) const { return m_data[j].size(); }
 
     std::vector<CompressedStorage<Scalar> >& _data() { return m_data; }
     const std::vector<CompressedStorage<Scalar> >& _data() const { return m_data; }
@@ -92,21 +92,21 @@
     /** \returns the coefficient value at given position \a row, \a col
       * This operation involes a log(rho*outer_size) binary search.
       */
-    inline Scalar coeff(int row, int col) const
+    inline Scalar coeff(Index row, Index col) const
     {
-      const int outer = IsRowMajor ? row : col;
-      const int inner = IsRowMajor ? col : row;
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
       return m_data[outer].at(inner);
     }
 
     /** \returns a reference to the coefficient value at given position \a row, \a col
       * This operation involes a log(rho*outer_size) binary search. If the coefficient does not
-      * exist yet, then a sorted insertion into a sequential buffer is performed.
+      * exist yet, then a sorted insertion Indexo a sequential buffer is performed.
       */
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
-      const int outer = IsRowMajor ? row : col;
-      const int inner = IsRowMajor ? col : row;
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
       return m_data[outer].atWithInsertion(inner);
     }
 
@@ -114,44 +114,44 @@
 
     void setZero()
     {
-      for (int j=0; j<outerSize(); ++j)
+      for (Index j=0; j<outerSize(); ++j)
         m_data[j].clear();
     }
 
     /** \returns the number of non zero coefficients */
-    int nonZeros() const
+    Index nonZeros() const
     {
-      int res = 0;
-      for (int j=0; j<outerSize(); ++j)
-        res += static_cast<int>(m_data[j].size());
+      Index res = 0;
+      for (Index j=0; j<outerSize(); ++j)
+        res += static_cast<Index>(m_data[j].size());
       return res;
     }
 
     /** \deprecated
       * Set the matrix to zero and reserve the memory for \a reserveSize nonzero coefficients. */
-    EIGEN_DEPRECATED void startFill(int reserveSize = 1000)
+    EIGEN_DEPRECATED void startFill(Index reserveSize = 1000)
     {
       setZero();
       reserve(reserveSize);
     }
 
-    void reserve(int reserveSize = 1000)
+    void reserve(Index reserveSize = 1000)
     {
       if (outerSize()>0)
       {
-        int reserveSizePerVector = std::max(reserveSize/outerSize(),4);
-        for (int j=0; j<outerSize(); ++j)
+        Index reserveSizePerVector = std::max(reserveSize/outerSize(),Index(4));
+        for (Index j=0; j<outerSize(); ++j)
         {
           m_data[j].reserve(reserveSizePerVector);
         }
       }
     }
 
-    inline void startVec(int /*outer*/) {}
+    inline void startVec(Index /*outer*/) {}
 
-    inline Scalar& insertBack(int outer, int inner)
+    inline Scalar& insertBack(Index outer, Index inner)
     {
-      ei_assert(outer<int(m_data.size()) && inner<m_innerSize && "out of range");
+      ei_assert(outer<Index(m_data.size()) && inner<m_innerSize && "out of range");
       ei_assert(((m_data[outer].size()==0) || (m_data[outer].index(m_data[outer].size()-1)<inner))
                 && "wrong sorted insertion");
       m_data[outer].append(0, inner);
@@ -167,10 +167,10 @@
       *
       * \see fillrand(), coeffRef()
       */
-    EIGEN_DEPRECATED Scalar& fill(int row, int col)
+    EIGEN_DEPRECATED Scalar& fill(Index row, Index col)
     {
-      const int outer = IsRowMajor ? row : col;
-      const int inner = IsRowMajor ? col : row;
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
       return insertBack(outer,inner);
     }
 
@@ -179,18 +179,18 @@
       * Compared to the generic coeffRef(), the unique limitation is that we assume
       * the coefficient does not exist yet.
       */
-    EIGEN_DEPRECATED Scalar& fillrand(int row, int col)
+    EIGEN_DEPRECATED Scalar& fillrand(Index row, Index col)
     {
       return insert(row,col);
     }
 
-    inline Scalar& insert(int row, int col)
+    inline Scalar& insert(Index row, Index col)
     {
-      const int outer = IsRowMajor ? row : col;
-      const int inner = IsRowMajor ? col : row;
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
 
-      int startId = 0;
-      int id = static_cast<int>(m_data[outer].size()) - 1;
+      Index startId = 0;
+      Index id = static_cast<Index>(m_data[outer].size()) - 1;
       m_data[outer].resize(id+2,1);
 
       while ( (id >= startId) && (m_data[outer].index(id) > inner) )
@@ -212,27 +212,27 @@
 
     void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
     {
-      for (int j=0; j<outerSize(); ++j)
+      for (Index j=0; j<outerSize(); ++j)
         m_data[j].prune(reference,epsilon);
     }
 
     /** Resize the matrix without preserving the data (the matrix is set to zero)
       */
-    void resize(int rows, int cols)
+    void resize(Index rows, Index cols)
     {
-      const int outerSize = IsRowMajor ? rows : cols;
+      const Index outerSize = IsRowMajor ? rows : cols;
       m_innerSize = IsRowMajor ? cols : rows;
       setZero();
-      if (int(m_data.size()) != outerSize)
+      if (Index(m_data.size()) != outerSize)
       {
         m_data.resize(outerSize);
       }
     }
 
-    void resizeAndKeepData(int rows, int cols)
+    void resizeAndKeepData(Index rows, Index cols)
     {
-      const int outerSize = IsRowMajor ? rows : cols;
-      const int innerSize = IsRowMajor ? cols : rows;
+      const Index outerSize = IsRowMajor ? rows : cols;
+      const Index innerSize = IsRowMajor ? cols : rows;
       if (m_innerSize>innerSize)
       {
         // remove all coefficients with innerCoord>=innerSize
@@ -252,7 +252,7 @@
       ei_assert(innerSize()==0 && outerSize()==0);
     }
 
-    inline DynamicSparseMatrix(int rows, int cols)
+    inline DynamicSparseMatrix(Index rows, Index cols)
       : m_innerSize(0)
     {
       resize(rows, cols);
@@ -308,15 +308,15 @@
 {
     typedef typename SparseVector<Scalar,_Flags>::InnerIterator Base;
   public:
-    InnerIterator(const DynamicSparseMatrix& mat, int outer)
+    InnerIterator(const DynamicSparseMatrix& mat, Index outer)
       : Base(mat.m_data[outer]), m_outer(outer)
     {}
 
-    inline int row() const { return IsRowMajor ? m_outer : Base::index(); }
-    inline int col() const { return IsRowMajor ? Base::index() : m_outer; }
+    inline Index row() const { return IsRowMajor ? m_outer : Base::index(); }
+    inline Index col() const { return IsRowMajor ? Base::index() : m_outer; }
 
   protected:
-    const int m_outer;
+    const Index m_outer;
 };
 
 #endif // EIGEN_DYNAMIC_SPARSEMATRIX_H
diff --git a/Eigen/src/Sparse/MappedSparseMatrix.h b/Eigen/src/Sparse/MappedSparseMatrix.h
index 43ac6b3..07233ac 100644
--- a/Eigen/src/Sparse/MappedSparseMatrix.h
+++ b/Eigen/src/Sparse/MappedSparseMatrix.h
@@ -48,40 +48,40 @@
   protected:
     enum { IsRowMajor = Base::IsRowMajor };
 
-    int m_outerSize;
-    int m_innerSize;
-    int m_nnz;
-    int* m_outerIndex;
-    int* m_innerIndices;
+    Index m_outerSize;
+    Index m_innerSize;
+    Index m_nnz;
+    Index* m_outerIndex;
+    Index* m_innerIndices;
     Scalar* m_values;
 
   public:
 
-    inline int rows() const { return IsRowMajor ? m_outerSize : m_innerSize; }
-    inline int cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
-    inline int innerSize() const { return m_innerSize; }
-    inline int outerSize() const { return m_outerSize; }
-    inline int innerNonZeros(int j) const { return m_outerIndex[j+1]-m_outerIndex[j]; }
+    inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; }
+    inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
+    inline Index innerSize() const { return m_innerSize; }
+    inline Index outerSize() const { return m_outerSize; }
+    inline Index innerNonZeros(Index j) const { return m_outerIndex[j+1]-m_outerIndex[j]; }
 
     //----------------------------------------
     // direct access interface
     inline const Scalar* _valuePtr() const { return m_values; }
     inline Scalar* _valuePtr() { return m_values; }
 
-    inline const int* _innerIndexPtr() const { return m_innerIndices; }
-    inline int* _innerIndexPtr() { return m_innerIndices; }
+    inline const Index* _innerIndexPtr() const { return m_innerIndices; }
+    inline Index* _innerIndexPtr() { return m_innerIndices; }
 
-    inline const int* _outerIndexPtr() const { return m_outerIndex; }
-    inline int* _outerIndexPtr() { return m_outerIndex; }
+    inline const Index* _outerIndexPtr() const { return m_outerIndex; }
+    inline Index* _outerIndexPtr() { return m_outerIndex; }
     //----------------------------------------
 
-    inline Scalar coeff(int row, int col) const
+    inline Scalar coeff(Index row, Index col) const
     {
-      const int outer = IsRowMajor ? row : col;
-      const int inner = IsRowMajor ? col : row;
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
 
-      int start = m_outerIndex[outer];
-      int end = m_outerIndex[outer+1];
+      Index start = m_outerIndex[outer];
+      Index end = m_outerIndex[outer+1];
       if (start==end)
         return Scalar(0);
       else if (end>0 && inner==m_innerIndices[end-1])
@@ -89,22 +89,22 @@
       // ^^  optimization: let's first check if it is the last coefficient
       // (very common in high level algorithms)
 
-      const int* r = std::lower_bound(&m_innerIndices[start],&m_innerIndices[end-1],inner);
-      const int id = r-&m_innerIndices[0];
+      const Index* r = std::lower_bound(&m_innerIndices[start],&m_innerIndices[end-1],inner);
+      const Index id = r-&m_innerIndices[0];
       return ((*r==inner) && (id<end)) ? m_values[id] : Scalar(0);
     }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
-      const int outer = IsRowMajor ? row : col;
-      const int inner = IsRowMajor ? col : row;
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
 
-      int start = m_outerIndex[outer];
-      int end = m_outerIndex[outer+1];
+      Index start = m_outerIndex[outer];
+      Index end = m_outerIndex[outer+1];
       ei_assert(end>=start && "you probably called coeffRef on a non finalized matrix");
       ei_assert(end>start && "coeffRef cannot be called on a zero coefficient");
-      int* r = std::lower_bound(&m_innerIndices[start],&m_innerIndices[end],inner);
-      const int id = r-&m_innerIndices[0];
+      Index* r = std::lower_bound(&m_innerIndices[start],&m_innerIndices[end],inner);
+      const Index id = r-&m_innerIndices[0];
       ei_assert((*r==inner) && (id<end) && "coeffRef cannot be called on a zero coefficient");
       return m_values[id];
     }
@@ -112,9 +112,9 @@
     class InnerIterator;
 
     /** \returns the number of non zero coefficients */
-    inline int nonZeros() const  { return m_nnz; }
+    inline Index nonZeros() const  { return m_nnz; }
 
-    inline MappedSparseMatrix(int rows, int cols, int nnz, int* outerIndexPtr, int* innerIndexPtr, Scalar* valuePtr)
+    inline MappedSparseMatrix(Index rows, Index cols, Index nnz, Index* outerIndexPtr, Index* innerIndexPtr, Scalar* valuePtr)
       : m_outerSize(IsRowMajor?rows:cols), m_innerSize(IsRowMajor?cols:rows), m_nnz(nnz), m_outerIndex(outerIndexPtr),
         m_innerIndices(innerIndexPtr), m_values(valuePtr)
     {}
@@ -139,7 +139,7 @@
 class MappedSparseMatrix<Scalar,_Flags>::InnerIterator
 {
   public:
-    InnerIterator(const MappedSparseMatrix& mat, int outer)
+    InnerIterator(const MappedSparseMatrix& mat, Index outer)
       : m_matrix(mat),
         m_outer(outer),
         m_id(mat._outerIndexPtr()[outer]),
@@ -148,7 +148,7 @@
     {}
 
     template<unsigned int Added, unsigned int Removed>
-    InnerIterator(const Flagged<MappedSparseMatrix,Added,Removed>& mat, int outer)
+    InnerIterator(const Flagged<MappedSparseMatrix,Added,Removed>& mat, Index outer)
       : m_matrix(mat._expression()), m_id(m_matrix._outerIndexPtr()[outer]),
         m_start(m_id), m_end(m_matrix._outerIndexPtr()[outer+1])
     {}
@@ -158,18 +158,18 @@
     inline Scalar value() const { return m_matrix._valuePtr()[m_id]; }
     inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix._valuePtr()[m_id]); }
 
-    inline int index() const { return m_matrix._innerIndexPtr()[m_id]; }
-    inline int row() const { return IsRowMajor ? m_outer : index(); }
-    inline int col() const { return IsRowMajor ? index() : m_outer; }
+    inline Index index() const { return m_matrix._innerIndexPtr()[m_id]; }
+    inline Index row() const { return IsRowMajor ? m_outer : index(); }
+    inline Index col() const { return IsRowMajor ? index() : m_outer; }
 
     inline operator bool() const { return (m_id < m_end) && (m_id>=m_start); }
 
   protected:
     const MappedSparseMatrix& m_matrix;
-    const int m_outer;
-    int m_id;
-    const int m_start;
-    const int m_end;
+    const Index m_outer;
+    Index m_id;
+    const Index m_start;
+    const Index m_end;
 };
 
 #endif // EIGEN_MAPPED_SPARSEMATRIX_H
diff --git a/Eigen/src/Sparse/RandomSetter.h b/Eigen/src/Sparse/RandomSetter.h
index 76f24cf..abe9881 100644
--- a/Eigen/src/Sparse/RandomSetter.h
+++ b/Eigen/src/Sparse/RandomSetter.h
@@ -166,7 +166,9 @@
          ,int OuterPacketBits = 6>
 class RandomSetter
 {
-    typedef typename ei_traits<SparseMatrixType>::Scalar Scalar;
+    typedef typename SparseMatrixType::Scalar Scalar;
+    typedef typename SparseMatrixType::Index Index;
+
     struct ScalarWrapper
     {
       ScalarWrapper() : value(0) {}
@@ -194,14 +196,14 @@
     inline RandomSetter(SparseMatrixType& target)
       : mp_target(&target)
     {
-      const int outerSize = SwapStorage ? target.innerSize() : target.outerSize();
-      const int innerSize = SwapStorage ? target.outerSize() : target.innerSize();
+      const Index outerSize = SwapStorage ? target.innerSize() : target.outerSize();
+      const Index innerSize = SwapStorage ? target.outerSize() : target.innerSize();
       m_outerPackets = outerSize >> OuterPacketBits;
       if (outerSize&OuterPacketMask)
         m_outerPackets += 1;
       m_hashmaps = new HashMapType[m_outerPackets];
       // compute number of bits needed to store inner indices
-      int aux = innerSize - 1;
+      Index aux = innerSize - 1;
       m_keyBitsOffset = 0;
       while (aux)
       {
@@ -209,11 +211,11 @@
         aux = aux >> 1;
       }
       KeyType ik = (1<<(OuterPacketBits+m_keyBitsOffset));
-      for (int k=0; k<m_outerPackets; ++k)
+      for (Index k=0; k<m_outerPackets; ++k)
         MapTraits<ScalarWrapper>::setInvalidKey(m_hashmaps[k],ik);
 
       // insert current coeffs
-      for (int j=0; j<mp_target->outerSize(); ++j)
+      for (Index j=0; j<mp_target->outerSize(); ++j)
         for (typename SparseMatrixType::InnerIterator it(*mp_target,j); it; ++it)
           (*this)(TargetRowMajor?j:it.index(), TargetRowMajor?it.index():j) = it.value();
     }
@@ -226,18 +228,18 @@
       {
         mp_target->setZero();
         mp_target->reserve(nonZeros());
-        int prevOuter = -1;
-        for (int k=0; k<m_outerPackets; ++k)
+        Index prevOuter = -1;
+        for (Index k=0; k<m_outerPackets; ++k)
         {
-          const int outerOffset = (1<<OuterPacketBits) * k;
+          const Index outerOffset = (1<<OuterPacketBits) * k;
           typename HashMapType::iterator end = m_hashmaps[k].end();
           for (typename HashMapType::iterator it = m_hashmaps[k].begin(); it!=end; ++it)
           {
-            const int outer = (it->first >> m_keyBitsOffset) + outerOffset;
-            const int inner = it->first & keyBitsMask;
+            const Index outer = (it->first >> m_keyBitsOffset) + outerOffset;
+            const Index inner = it->first & keyBitsMask;
             if (prevOuter!=outer)
             {
-              for (int j=prevOuter+1;j<=outer;++j)
+              for (Index j=prevOuter+1;j<=outer;++j)
                 mp_target->startVec(j);
               prevOuter = outer;
             }
@@ -251,20 +253,20 @@
         VectorXi positions(mp_target->outerSize());
         positions.setZero();
         // pass 1
-        for (int k=0; k<m_outerPackets; ++k)
+        for (Index k=0; k<m_outerPackets; ++k)
         {
           typename HashMapType::iterator end = m_hashmaps[k].end();
           for (typename HashMapType::iterator it = m_hashmaps[k].begin(); it!=end; ++it)
           {
-            const int outer = it->first & keyBitsMask;
+            const Index outer = it->first & keyBitsMask;
             ++positions[outer];
           }
         }
         // prefix sum
-        int count = 0;
-        for (int j=0; j<mp_target->outerSize(); ++j)
+        Index count = 0;
+        for (Index j=0; j<mp_target->outerSize(); ++j)
         {
-          int tmp = positions[j];
+          Index tmp = positions[j];
           mp_target->_outerIndexPtr()[j] = count;
           positions[j] = count;
           count += tmp;
@@ -272,20 +274,20 @@
         mp_target->_outerIndexPtr()[mp_target->outerSize()] = count;
         mp_target->resizeNonZeros(count);
         // pass 2
-        for (int k=0; k<m_outerPackets; ++k)
+        for (Index k=0; k<m_outerPackets; ++k)
         {
-          const int outerOffset = (1<<OuterPacketBits) * k;
+          const Index outerOffset = (1<<OuterPacketBits) * k;
           typename HashMapType::iterator end = m_hashmaps[k].end();
           for (typename HashMapType::iterator it = m_hashmaps[k].begin(); it!=end; ++it)
           {
-            const int inner = (it->first >> m_keyBitsOffset) + outerOffset;
-            const int outer = it->first & keyBitsMask;
+            const Index inner = (it->first >> m_keyBitsOffset) + outerOffset;
+            const Index outer = it->first & keyBitsMask;
             // sorted insertion
             // Note that we have to deal with at most 2^OuterPacketBits unsorted coefficients,
             // moreover those 2^OuterPacketBits coeffs are likely to be sparse, an so only a
             // small fraction of them have to be sorted, whence the following simple procedure:
-            int posStart = mp_target->_outerIndexPtr()[outer];
-            int i = (positions[outer]++) - 1;
+            Index posStart = mp_target->_outerIndexPtr()[outer];
+            Index i = (positions[outer]++) - 1;
             while ( (i >= posStart) && (mp_target->_innerIndexPtr()[i] > inner) )
             {
               mp_target->_valuePtr()[i+1] = mp_target->_valuePtr()[i];
@@ -301,14 +303,14 @@
     }
 
     /** \returns a reference to the coefficient at given coordinates \a row, \a col */
-    Scalar& operator() (int row, int col)
+    Scalar& operator() (Index row, Index col)
     {
       ei_assert(((!IsUpper) || (row<=col)) && "Invalid access to an upper triangular matrix");
       ei_assert(((!IsLower) || (col<=row)) && "Invalid access to an upper triangular matrix");
-      const int outer = SetterRowMajor ? row : col;
-      const int inner = SetterRowMajor ? col : row;
-      const int outerMajor = outer >> OuterPacketBits; // index of the packet/map
-      const int outerMinor = outer & OuterPacketMask;  // index of the inner vector in the packet
+      const Index outer = SetterRowMajor ? row : col;
+      const Index inner = SetterRowMajor ? col : row;
+      const Index outerMajor = outer >> OuterPacketBits; // index of the packet/map
+      const Index outerMinor = outer & OuterPacketMask;  // index of the inner vector in the packet
       const KeyType key = (KeyType(outerMinor)<<m_keyBitsOffset) | inner;
       return m_hashmaps[outerMajor][key].value;
     }
@@ -318,11 +320,11 @@
       * \note According to the underlying map/hash_map implementation,
       * this function might be quite expensive.
       */
-    int nonZeros() const
+    Index nonZeros() const
     {
-      int nz = 0;
-      for (int k=0; k<m_outerPackets; ++k)
-        nz += static_cast<int>(m_hashmaps[k].size());
+      Index nz = 0;
+      for (Index k=0; k<m_outerPackets; ++k)
+        nz += static_cast<Index>(m_hashmaps[k].size());
       return nz;
     }
 
@@ -331,7 +333,7 @@
 
     HashMapType* m_hashmaps;
     SparseMatrixType* mp_target;
-    int m_outerPackets;
+    Index m_outerPackets;
     unsigned char m_keyBitsOffset;
 };
 
diff --git a/Eigen/src/Sparse/SparseBlock.h b/Eigen/src/Sparse/SparseBlock.h
index bdbc460..bf8b5ad 100644
--- a/Eigen/src/Sparse/SparseBlock.h
+++ b/Eigen/src/Sparse/SparseBlock.h
@@ -54,22 +54,22 @@
     class InnerIterator: public MatrixType::InnerIterator
     {
       public:
-        inline InnerIterator(const SparseInnerVectorSet& xpr, int outer)
+        inline InnerIterator(const SparseInnerVectorSet& xpr, Index outer)
           : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
         {}
-        inline int row() const { return IsRowMajor ? m_outer : this->index(); }
-        inline int col() const { return IsRowMajor ? this->index() : m_outer; }
+        inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
+        inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
       protected:
-        int m_outer;
+        Index m_outer;
     };
 
-    inline SparseInnerVectorSet(const MatrixType& matrix, int outerStart, int outerSize)
+    inline SparseInnerVectorSet(const MatrixType& matrix, Index outerStart, Index outerSize)
       : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize)
     {
       ei_assert( (outerStart>=0) && ((outerStart+outerSize)<=matrix.outerSize()) );
     }
 
-    inline SparseInnerVectorSet(const MatrixType& matrix, int outer)
+    inline SparseInnerVectorSet(const MatrixType& matrix, Index outer)
       : m_matrix(matrix), m_outerStart(outer), m_outerSize(Size)
     {
       ei_assert(Size!=Dynamic);
@@ -88,15 +88,14 @@
 //       return *this;
 //     }
 
-    EIGEN_STRONG_INLINE int rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
-    EIGEN_STRONG_INLINE int cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
+    EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
 
   protected:
 
     const typename MatrixType::Nested m_matrix;
-    int m_outerStart;
-    const ei_int_if_dynamic<Size> m_outerSize;
-
+    Index m_outerStart;
+    const ei_variable_if_dynamic<Index, Size> m_outerSize;
 };
 
 /***************************************************************************
@@ -116,22 +115,22 @@
     class InnerIterator: public MatrixType::InnerIterator
     {
       public:
-        inline InnerIterator(const SparseInnerVectorSet& xpr, int outer)
+        inline InnerIterator(const SparseInnerVectorSet& xpr, Index outer)
           : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
         {}
-        inline int row() const { return IsRowMajor ? m_outer : this->index(); }
-        inline int col() const { return IsRowMajor ? this->index() : m_outer; }
+        inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
+        inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
       protected:
-        int m_outer;
+        Index m_outer;
     };
 
-    inline SparseInnerVectorSet(const MatrixType& matrix, int outerStart, int outerSize)
+    inline SparseInnerVectorSet(const MatrixType& matrix, Index outerStart, Index outerSize)
       : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize)
     {
       ei_assert( (outerStart>=0) && ((outerStart+outerSize)<=matrix.outerSize()) );
     }
 
-    inline SparseInnerVectorSet(const MatrixType& matrix, int outer)
+    inline SparseInnerVectorSet(const MatrixType& matrix, Index outer)
       : m_matrix(matrix), m_outerStart(outer), m_outerSize(Size)
     {
       ei_assert(Size!=Dynamic);
@@ -150,7 +149,7 @@
       else
       {
         // evaluate/copy vector per vector
-        for (int j=0; j<m_outerSize.value(); ++j)
+        for (Index j=0; j<m_outerSize.value(); ++j)
         {
           SparseVector<Scalar,IsRowMajor ? RowMajorBit : 0> aux(other.innerVector(j));
           m_matrix.const_cast_derived()._data()[m_outerStart+j].swap(aux._data());
@@ -164,10 +163,10 @@
       return operator=<SparseInnerVectorSet>(other);
     }
 
-    int nonZeros() const
+    Index nonZeros() const
     {
-      int count = 0;
-      for (int j=0; j<m_outerSize; ++j)
+      Index count = 0;
+      for (Index j=0; j<m_outerSize; ++j)
         count += m_matrix._data()[m_outerStart+j].size();
       return count;
     }
@@ -185,14 +184,14 @@
 //       return *this;
 //     }
 
-    EIGEN_STRONG_INLINE int rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
-    EIGEN_STRONG_INLINE int cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
+    EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
 
   protected:
 
     const typename MatrixType::Nested m_matrix;
-    int m_outerStart;
-    const ei_int_if_dynamic<Size> m_outerSize;
+    Index m_outerStart;
+    const ei_variable_if_dynamic<Index, Size> m_outerSize;
 
 };
 
@@ -214,22 +213,22 @@
     class InnerIterator: public MatrixType::InnerIterator
     {
       public:
-        inline InnerIterator(const SparseInnerVectorSet& xpr, int outer)
+        inline InnerIterator(const SparseInnerVectorSet& xpr, Index outer)
           : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
         {}
-        inline int row() const { return IsRowMajor ? m_outer : this->index(); }
-        inline int col() const { return IsRowMajor ? this->index() : m_outer; }
+        inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
+        inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
       protected:
-        int m_outer;
+        Index m_outer;
     };
 
-    inline SparseInnerVectorSet(const MatrixType& matrix, int outerStart, int outerSize)
+    inline SparseInnerVectorSet(const MatrixType& matrix, Index outerStart, Index outerSize)
       : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize)
     {
       ei_assert( (outerStart>=0) && ((outerStart+outerSize)<=matrix.outerSize()) );
     }
 
-    inline SparseInnerVectorSet(const MatrixType& matrix, int outer)
+    inline SparseInnerVectorSet(const MatrixType& matrix, Index outer)
       : m_matrix(matrix), m_outerStart(outer), m_outerSize(Size)
     {
       ei_assert(Size==1);
@@ -248,7 +247,7 @@
       else
       {
         // evaluate/copy vector per vector
-        for (int j=0; j<m_outerSize.value(); ++j)
+        for (Index j=0; j<m_outerSize.value(); ++j)
         {
           SparseVector<Scalar,IsRowMajor ? RowMajorBit : 0> aux(other.innerVector(j));
           m_matrix.const_cast_derived()._data()[m_outerStart+j].swap(aux._data());
@@ -267,17 +266,17 @@
     inline Scalar* _valuePtr()
     { return m_matrix.const_cast_derived()._valuePtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
 
-    inline const int* _innerIndexPtr() const
+    inline const Index* _innerIndexPtr() const
     { return m_matrix._innerIndexPtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
-    inline int* _innerIndexPtr()
+    inline Index* _innerIndexPtr()
     { return m_matrix.const_cast_derived()._innerIndexPtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
 
-    inline const int* _outerIndexPtr() const
+    inline const Index* _outerIndexPtr() const
     { return m_matrix._outerIndexPtr() + m_outerStart; }
-    inline int* _outerIndexPtr()
+    inline Index* _outerIndexPtr()
     { return m_matrix.const_cast_derived()._outerIndexPtr() + m_outerStart; }
 
-    int nonZeros() const
+    Index nonZeros() const
     {
       return  size_t(m_matrix._outerIndexPtr()[m_outerStart+m_outerSize.value()])
             - size_t(m_matrix._outerIndexPtr()[m_outerStart]); }
@@ -295,14 +294,14 @@
 //       return *this;
 //     }
 
-    EIGEN_STRONG_INLINE int rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
-    EIGEN_STRONG_INLINE int cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
+    EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
 
   protected:
 
     const typename MatrixType::Nested m_matrix;
-    int m_outerStart;
-    const ei_int_if_dynamic<Size> m_outerSize;
+    Index m_outerStart;
+    const ei_variable_if_dynamic<Index, Size> m_outerSize;
 
 };
 
@@ -310,7 +309,7 @@
 
 /** \returns the i-th row of the matrix \c *this. For row-major matrix only. */
 template<typename Derived>
-SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::row(int i)
+SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::row(Index i)
 {
   EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
   return innerVector(i);
@@ -319,7 +318,7 @@
 /** \returns the i-th row of the matrix \c *this. For row-major matrix only.
   * (read-only version) */
 template<typename Derived>
-const SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::row(int i) const
+const SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::row(Index i) const
 {
   EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
   return innerVector(i);
@@ -327,7 +326,7 @@
 
 /** \returns the i-th column of the matrix \c *this. For column-major matrix only. */
 template<typename Derived>
-SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::col(int i)
+SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::col(Index i)
 {
   EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
   return innerVector(i);
@@ -336,7 +335,7 @@
 /** \returns the i-th column of the matrix \c *this. For column-major matrix only.
   * (read-only version) */
 template<typename Derived>
-const SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::col(int i) const
+const SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::col(Index i) const
 {
   EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
   return innerVector(i);
@@ -346,21 +345,21 @@
   * is col-major (resp. row-major).
   */
 template<typename Derived>
-SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::innerVector(int outer)
+SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::innerVector(Index outer)
 { return SparseInnerVectorSet<Derived,1>(derived(), outer); }
 
 /** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this
   * is col-major (resp. row-major). Read-only.
   */
 template<typename Derived>
-const SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::innerVector(int outer) const
+const SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::innerVector(Index outer) const
 { return SparseInnerVectorSet<Derived,1>(derived(), outer); }
 
 //----------
 
 /** \returns the i-th row of the matrix \c *this. For row-major matrix only. */
 template<typename Derived>
-SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subrows(int start, int size)
+SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subrows(Index start, Index size)
 {
   EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
   return innerVectors(start, size);
@@ -369,7 +368,7 @@
 /** \returns the i-th row of the matrix \c *this. For row-major matrix only.
   * (read-only version) */
 template<typename Derived>
-const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subrows(int start, int size) const
+const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subrows(Index start, Index size) const
 {
   EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
   return innerVectors(start, size);
@@ -377,7 +376,7 @@
 
 /** \returns the i-th column of the matrix \c *this. For column-major matrix only. */
 template<typename Derived>
-SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subcols(int start, int size)
+SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subcols(Index start, Index size)
 {
   EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
   return innerVectors(start, size);
@@ -386,7 +385,7 @@
 /** \returns the i-th column of the matrix \c *this. For column-major matrix only.
   * (read-only version) */
 template<typename Derived>
-const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subcols(int start, int size) const
+const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subcols(Index start, Index size) const
 {
   EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
   return innerVectors(start, size);
@@ -396,14 +395,14 @@
   * is col-major (resp. row-major).
   */
 template<typename Derived>
-SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::innerVectors(int outerStart, int outerSize)
+SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize)
 { return SparseInnerVectorSet<Derived,Dynamic>(derived(), outerStart, outerSize); }
 
 /** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this
   * is col-major (resp. row-major). Read-only.
   */
 template<typename Derived>
-const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::innerVectors(int outerStart, int outerSize) const
+const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize) const
 { return SparseInnerVectorSet<Derived,Dynamic>(derived(), outerStart, outerSize); }
 
 #endif // EIGEN_SPARSE_BLOCK_H
diff --git a/Eigen/src/Sparse/SparseCwiseBinaryOp.h b/Eigen/src/Sparse/SparseCwiseBinaryOp.h
index 91fbcb1..90878fe 100644
--- a/Eigen/src/Sparse/SparseCwiseBinaryOp.h
+++ b/Eigen/src/Sparse/SparseCwiseBinaryOp.h
@@ -68,10 +68,11 @@
   : public ei_sparse_cwise_binary_op_inner_iterator_selector<BinaryOp,Lhs,Rhs,typename CwiseBinaryOpImpl<BinaryOp,Lhs,Rhs,Sparse>::InnerIterator>
 {
   public:
+    typedef typename Lhs::Index Index;
     typedef ei_sparse_cwise_binary_op_inner_iterator_selector<
       BinaryOp,Lhs,Rhs, InnerIterator> Base;
 
-    EIGEN_STRONG_INLINE InnerIterator(const CwiseBinaryOpImpl& binOp, int outer)
+    EIGEN_STRONG_INLINE InnerIterator(const CwiseBinaryOpImpl& binOp, Index outer)
       : Base(binOp.derived(),outer)
     {}
 };
@@ -95,9 +96,11 @@
     typedef typename ei_traits<CwiseBinaryXpr>::_RhsNested _RhsNested;
     typedef typename _LhsNested::InnerIterator LhsIterator;
     typedef typename _RhsNested::InnerIterator RhsIterator;
+    typedef typename Lhs::Index Index;
+
   public:
 
-    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, int outer)
+    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer)
       : m_lhsIter(xpr.lhs(),outer), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor())
     {
       this->operator++();
@@ -134,9 +137,9 @@
 
     EIGEN_STRONG_INLINE Scalar value() const { return m_value; }
 
-    EIGEN_STRONG_INLINE int index() const { return m_id; }
-    EIGEN_STRONG_INLINE int row() const { return Lhs::IsRowMajor ? m_lhsIter.row() : index(); }
-    EIGEN_STRONG_INLINE int col() const { return Lhs::IsRowMajor ? index() : m_lhsIter.col(); }
+    EIGEN_STRONG_INLINE Index index() const { return m_id; }
+    EIGEN_STRONG_INLINE Index row() const { return Lhs::IsRowMajor ? m_lhsIter.row() : index(); }
+    EIGEN_STRONG_INLINE Index col() const { return Lhs::IsRowMajor ? index() : m_lhsIter.col(); }
 
     EIGEN_STRONG_INLINE operator bool() const { return m_id>=0; }
 
@@ -145,7 +148,7 @@
     RhsIterator m_rhsIter;
     const BinaryOp& m_functor;
     Scalar m_value;
-    int m_id;
+    Index m_id;
 };
 
 // sparse - sparse  (product)
@@ -159,9 +162,10 @@
     typedef typename _LhsNested::InnerIterator LhsIterator;
     typedef typename ei_traits<CwiseBinaryXpr>::_RhsNested _RhsNested;
     typedef typename _RhsNested::InnerIterator RhsIterator;
+    typedef typename Lhs::Index Index;
   public:
 
-    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, int outer)
+    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer)
       : m_lhsIter(xpr.lhs(),outer), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor())
     {
       while (m_lhsIter && m_rhsIter && (m_lhsIter.index() != m_rhsIter.index()))
@@ -189,9 +193,9 @@
 
     EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_lhsIter.value(), m_rhsIter.value()); }
 
-    EIGEN_STRONG_INLINE int index() const { return m_lhsIter.index(); }
-    EIGEN_STRONG_INLINE int row() const { return m_lhsIter.row(); }
-    EIGEN_STRONG_INLINE int col() const { return m_lhsIter.col(); }
+    EIGEN_STRONG_INLINE Index index() const { return m_lhsIter.index(); }
+    EIGEN_STRONG_INLINE Index row() const { return m_lhsIter.row(); }
+    EIGEN_STRONG_INLINE Index col() const { return m_lhsIter.col(); }
 
     EIGEN_STRONG_INLINE operator bool() const { return (m_lhsIter && m_rhsIter); }
 
@@ -211,10 +215,11 @@
     typedef typename ei_traits<CwiseBinaryXpr>::_LhsNested _LhsNested;
     typedef typename ei_traits<CwiseBinaryXpr>::RhsNested RhsNested;
     typedef typename _LhsNested::InnerIterator LhsIterator;
+    typedef typename Lhs::Index Index;
     enum { IsRowMajor = (int(Lhs::Flags)&RowMajorBit)==RowMajorBit };
   public:
 
-    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, int outer)
+    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer)
       : m_rhs(xpr.rhs()), m_lhsIter(xpr.lhs(),outer), m_functor(xpr.functor()), m_outer(outer)
     {}
 
@@ -228,9 +233,9 @@
     { return m_functor(m_lhsIter.value(),
                        m_rhs.coeff(IsRowMajor?m_outer:m_lhsIter.index(),IsRowMajor?m_lhsIter.index():m_outer)); }
 
-    EIGEN_STRONG_INLINE int index() const { return m_lhsIter.index(); }
-    EIGEN_STRONG_INLINE int row() const { return m_lhsIter.row(); }
-    EIGEN_STRONG_INLINE int col() const { return m_lhsIter.col(); }
+    EIGEN_STRONG_INLINE Index index() const { return m_lhsIter.index(); }
+    EIGEN_STRONG_INLINE Index row() const { return m_lhsIter.row(); }
+    EIGEN_STRONG_INLINE Index col() const { return m_lhsIter.col(); }
 
     EIGEN_STRONG_INLINE operator bool() const { return m_lhsIter; }
 
@@ -238,7 +243,7 @@
     const RhsNested m_rhs;
     LhsIterator m_lhsIter;
     const BinaryFunc m_functor;
-    const int m_outer;
+    const Index m_outer;
 };
 
 // sparse - dense  (product)
@@ -250,10 +255,12 @@
     typedef typename CwiseBinaryXpr::Scalar Scalar;
     typedef typename ei_traits<CwiseBinaryXpr>::_RhsNested _RhsNested;
     typedef typename _RhsNested::InnerIterator RhsIterator;
+    typedef typename Lhs::Index Index;
+
     enum { IsRowMajor = (int(Rhs::Flags)&RowMajorBit)==RowMajorBit };
   public:
 
-    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, int outer)
+    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, Index outer)
       : m_xpr(xpr), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor()), m_outer(outer)
     {}
 
@@ -266,9 +273,9 @@
     EIGEN_STRONG_INLINE Scalar value() const
     { return m_functor(m_xpr.lhs().coeff(IsRowMajor?m_outer:m_rhsIter.index(),IsRowMajor?m_rhsIter.index():m_outer), m_rhsIter.value()); }
 
-    EIGEN_STRONG_INLINE int index() const { return m_rhsIter.index(); }
-    EIGEN_STRONG_INLINE int row() const { return m_rhsIter.row(); }
-    EIGEN_STRONG_INLINE int col() const { return m_rhsIter.col(); }
+    EIGEN_STRONG_INLINE Index index() const { return m_rhsIter.index(); }
+    EIGEN_STRONG_INLINE Index row() const { return m_rhsIter.row(); }
+    EIGEN_STRONG_INLINE Index col() const { return m_rhsIter.col(); }
 
     EIGEN_STRONG_INLINE operator bool() const { return m_rhsIter; }
 
@@ -276,7 +283,7 @@
     const CwiseBinaryXpr& m_xpr;
     RhsIterator m_rhsIter;
     const BinaryFunc& m_functor;
-    const int m_outer;
+    const Index m_outer;
 };
 
 
diff --git a/Eigen/src/Sparse/SparseCwiseUnaryOp.h b/Eigen/src/Sparse/SparseCwiseUnaryOp.h
index f3f8c82..5e12da4 100644
--- a/Eigen/src/Sparse/SparseCwiseUnaryOp.h
+++ b/Eigen/src/Sparse/SparseCwiseUnaryOp.h
@@ -57,9 +57,10 @@
     typedef typename CwiseUnaryOpImpl::Scalar Scalar;
     typedef typename ei_traits<Derived>::_XprTypeNested _MatrixTypeNested;
     typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
+    typedef typename MatrixType::Index Index;
   public:
 
-    EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryOpImpl& unaryOp, int outer)
+    EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryOpImpl& unaryOp, Index outer)
       : m_iter(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor())
     {}
 
@@ -68,9 +69,9 @@
 
     EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_iter.value()); }
 
-    EIGEN_STRONG_INLINE int index() const { return m_iter.index(); }
-    EIGEN_STRONG_INLINE int row() const { return m_iter.row(); }
-    EIGEN_STRONG_INLINE int col() const { return m_iter.col(); }
+    EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); }
+    EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); }
+    EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); }
 
     EIGEN_STRONG_INLINE operator bool() const { return m_iter; }
 
@@ -98,9 +99,10 @@
     typedef typename CwiseUnaryViewImpl::Scalar Scalar;
     typedef typename ei_traits<Derived>::_MatrixTypeNested _MatrixTypeNested;
     typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
+    typedef typename MatrixType::Index Index;
   public:
 
-    EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryViewImpl& unaryView, int outer)
+    EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryViewImpl& unaryView, Index outer)
       : m_iter(unaryView.derived().nestedExpression(),outer), m_functor(unaryView.derived().functor())
     {}
 
@@ -110,9 +112,9 @@
     EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_iter.value()); }
     EIGEN_STRONG_INLINE Scalar& valueRef() { return m_functor(m_iter.valueRef()); }
 
-    EIGEN_STRONG_INLINE int index() const { return m_iter.index(); }
-    EIGEN_STRONG_INLINE int row() const { return m_iter.row(); }
-    EIGEN_STRONG_INLINE int col() const { return m_iter.col(); }
+    EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); }
+    EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); }
+    EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); }
 
     EIGEN_STRONG_INLINE operator bool() const { return m_iter; }
 
@@ -125,7 +127,7 @@
 EIGEN_STRONG_INLINE Derived&
 SparseMatrixBase<Derived>::operator*=(const Scalar& other)
 {
-  for (int j=0; j<outerSize(); ++j)
+  for (Index j=0; j<outerSize(); ++j)
     for (typename Derived::InnerIterator i(derived(),j); i; ++i)
       i.valueRef() *= other;
   return derived();
@@ -135,7 +137,7 @@
 EIGEN_STRONG_INLINE Derived&
 SparseMatrixBase<Derived>::operator/=(const Scalar& other)
 {
-  for (int j=0; j<outerSize(); ++j)
+  for (Index j=0; j<outerSize(); ++j)
     for (typename Derived::InnerIterator i(derived(),j); i; ++i)
       i.valueRef() /= other;
   return derived();
diff --git a/Eigen/src/Sparse/SparseDiagonalProduct.h b/Eigen/src/Sparse/SparseDiagonalProduct.h
index d0d0517..70b35bc 100644
--- a/Eigen/src/Sparse/SparseDiagonalProduct.h
+++ b/Eigen/src/Sparse/SparseDiagonalProduct.h
@@ -93,8 +93,8 @@
       ei_assert(lhs.cols() == rhs.rows() && "invalid sparse matrix * diagonal matrix product");
     }
 
-    EIGEN_STRONG_INLINE int rows() const { return m_lhs.rows(); }
-    EIGEN_STRONG_INLINE int cols() const { return m_rhs.cols(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); }
 
     EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; }
     EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; }
@@ -111,9 +111,10 @@
   : public CwiseUnaryOp<ei_scalar_multiple_op<typename Lhs::Scalar>,Rhs>::InnerIterator
 {
     typedef typename CwiseUnaryOp<ei_scalar_multiple_op<typename Lhs::Scalar>,Rhs>::InnerIterator Base;
+    typedef typename Lhs::Index Index;
   public:
     inline ei_sparse_diagonal_product_inner_iterator_selector(
-              const SparseDiagonalProductType& expr, int outer)
+              const SparseDiagonalProductType& expr, Index outer)
       : Base(expr.rhs()*(expr.lhs().diagonal().coeff(outer)), outer)
     {}
 };
@@ -130,9 +131,10 @@
       ei_scalar_product_op<typename Lhs::Scalar>,
       SparseInnerVectorSet<Rhs,1>,
       typename Lhs::DiagonalVectorType>::InnerIterator Base;
+    typedef typename Lhs::Index Index;
   public:
     inline ei_sparse_diagonal_product_inner_iterator_selector(
-              const SparseDiagonalProductType& expr, int outer)
+              const SparseDiagonalProductType& expr, Index outer)
       : Base(expr.rhs().innerVector(outer) .cwiseProduct(expr.lhs().diagonal()), 0)
     {}
 };
@@ -143,9 +145,10 @@
   : public CwiseUnaryOp<ei_scalar_multiple_op<typename Rhs::Scalar>,Lhs>::InnerIterator
 {
     typedef typename CwiseUnaryOp<ei_scalar_multiple_op<typename Rhs::Scalar>,Lhs>::InnerIterator Base;
+    typedef typename Lhs::Index Index;
   public:
     inline ei_sparse_diagonal_product_inner_iterator_selector(
-              const SparseDiagonalProductType& expr, int outer)
+              const SparseDiagonalProductType& expr, Index outer)
       : Base(expr.lhs()*expr.rhs().diagonal().coeff(outer), outer)
     {}
 };
@@ -162,9 +165,10 @@
       ei_scalar_product_op<typename Rhs::Scalar>,
       SparseInnerVectorSet<Lhs,1>,
       Transpose<typename Rhs::DiagonalVectorType> >::InnerIterator Base;
+    typedef typename Lhs::Index Index;
   public:
     inline ei_sparse_diagonal_product_inner_iterator_selector(
-              const SparseDiagonalProductType& expr, int outer)
+              const SparseDiagonalProductType& expr, Index outer)
       : Base(expr.lhs().innerVector(outer) .cwiseProduct(expr.rhs().diagonal().transpose()), 0)
     {}
 };
diff --git a/Eigen/src/Sparse/SparseLDLT.h b/Eigen/src/Sparse/SparseLDLT.h
index 28797a6..b6a51c6 100644
--- a/Eigen/src/Sparse/SparseLDLT.h
+++ b/Eigen/src/Sparse/SparseLDLT.h
@@ -78,6 +78,7 @@
 {
   protected:
     typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::Index Index;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
     typedef SparseMatrix<Scalar> CholMatrixType;
     typedef Matrix<Scalar,MatrixType::ColsAtCompileTime,1> VectorType;
@@ -188,36 +189,36 @@
 void SparseLDLT<MatrixType,Backend>::_symbolic(const MatrixType& a)
 {
   assert(a.rows()==a.cols());
-  const int size = a.rows();
+  const Index size = a.rows();
   m_matrix.resize(size, size);
   m_parent.resize(size);
   m_nonZerosPerCol.resize(size);
-  int * tags = ei_aligned_stack_new(int, size);
+  Index * tags = ei_aligned_stack_new(Index, size);
 
-  const int* Ap = a._outerIndexPtr();
-  const int* Ai = a._innerIndexPtr();
-  int* Lp = m_matrix._outerIndexPtr();
-  const int* P = 0;
-  int* Pinv = 0;
+  const Index* Ap = a._outerIndexPtr();
+  const Index* Ai = a._innerIndexPtr();
+  Index* Lp = m_matrix._outerIndexPtr();
+  const Index* P = 0;
+  Index* Pinv = 0;
 
   if (P)
   {
     /* If P is present then compute Pinv, the inverse of P */
-    for (int k = 0; k < size; ++k)
+    for (Index k = 0; k < size; ++k)
       Pinv[P[k]] = k;
   }
-  for (int k = 0; k < size; ++k)
+  for (Index k = 0; k < size; ++k)
   {
     /* L(k,:) pattern: all nodes reachable in etree from nz in A(0:k-1,k) */
     m_parent[k] = -1;             /* parent of k is not yet known */
     tags[k] = k;                  /* mark node k as visited */
     m_nonZerosPerCol[k] = 0;      /* count of nonzeros in column k of L */
-    int kk = P ? P[k] : k;  /* kth original, or permuted, column */
-    int p2 = Ap[kk+1];
-    for (int p = Ap[kk]; p < p2; ++p)
+    Index kk = P ? P[k] : k;  /* kth original, or permuted, column */
+    Index p2 = Ap[kk+1];
+    for (Index p = Ap[kk]; p < p2; ++p)
     {
       /* A (i,k) is nonzero (original or permuted A) */
-      int i = Pinv ? Pinv[Ai[p]] : Ai[p];
+      Index i = Pinv ? Pinv[Ai[p]] : Ai[p];
       if (i < k)
       {
         /* follow path from i to root of etree, stop at flagged node */
@@ -234,53 +235,53 @@
   }
   /* construct Lp index array from m_nonZerosPerCol column counts */
   Lp[0] = 0;
-  for (int k = 0; k < size; ++k)
+  for (Index k = 0; k < size; ++k)
     Lp[k+1] = Lp[k] + m_nonZerosPerCol[k];
 
   m_matrix.resizeNonZeros(Lp[size]);
-  ei_aligned_stack_delete(int, tags, size);
+  ei_aligned_stack_delete(Index, tags, size);
 }
 
 template<typename MatrixType, int Backend>
 bool SparseLDLT<MatrixType,Backend>::_numeric(const MatrixType& a)
 {
   assert(a.rows()==a.cols());
-  const int size = a.rows();
+  const Index size = a.rows();
   assert(m_parent.size()==size);
   assert(m_nonZerosPerCol.size()==size);
 
-  const int* Ap = a._outerIndexPtr();
-  const int* Ai = a._innerIndexPtr();
+  const Index* Ap = a._outerIndexPtr();
+  const Index* Ai = a._innerIndexPtr();
   const Scalar* Ax = a._valuePtr();
-  const int* Lp = m_matrix._outerIndexPtr();
-  int* Li = m_matrix._innerIndexPtr();
+  const Index* Lp = m_matrix._outerIndexPtr();
+  Index* Li = m_matrix._innerIndexPtr();
   Scalar* Lx = m_matrix._valuePtr();
   m_diag.resize(size);
 
   Scalar * y = ei_aligned_stack_new(Scalar, size);
-  int * pattern = ei_aligned_stack_new(int, size);
-  int * tags = ei_aligned_stack_new(int, size);
+  Index * pattern = ei_aligned_stack_new(Index, size);
+  Index * tags = ei_aligned_stack_new(Index, size);
 
-  const int* P = 0;
-  const int* Pinv = 0;
+  const Index* P = 0;
+  const Index* Pinv = 0;
   bool ok = true;
 
-  for (int k = 0; k < size; ++k)
+  for (Index k = 0; k < size; ++k)
   {
     /* compute nonzero pattern of kth row of L, in topological order */
     y[k] = 0.0;                   /* Y(0:k) is now all zero */
-    int top = size;               /* stack for pattern is empty */
+    Index top = size;               /* stack for pattern is empty */
     tags[k] = k;                  /* mark node k as visited */
     m_nonZerosPerCol[k] = 0;      /* count of nonzeros in column k of L */
-    int kk = (P) ? (P[k]) : (k);  /* kth original, or permuted, column */
-    int p2 = Ap[kk+1];
-    for (int p = Ap[kk]; p < p2; ++p)
+    Index kk = (P) ? (P[k]) : (k);  /* kth original, or permuted, column */
+    Index p2 = Ap[kk+1];
+    for (Index p = Ap[kk]; p < p2; ++p)
     {
-      int i = Pinv ? Pinv[Ai[p]] : Ai[p]; /* get A(i,k) */
+      Index i = Pinv ? Pinv[Ai[p]] : Ai[p]; /* get A(i,k) */
       if (i <= k)
       {
         y[i] += Ax[p];            /* scatter A(i,k) into Y (sum duplicates) */
-        int len;
+        Index len;
         for (len = 0; tags[i] != k; i = m_parent[i])
         {
           pattern[len++] = i;     /* L(k,i) is nonzero */
@@ -295,11 +296,11 @@
     y[k] = 0.0;
     for (; top < size; ++top)
     {
-      int i = pattern[top];      /* pattern[top:n-1] is pattern of L(:,k) */
+      Index i = pattern[top];      /* pattern[top:n-1] is pattern of L(:,k) */
       Scalar yi = y[i];          /* get and clear Y(i) */
       y[i] = 0.0;
-      int p2 = Lp[i] + m_nonZerosPerCol[i];
-      int p;
+      Index p2 = Lp[i] + m_nonZerosPerCol[i];
+      Index p;
       for (p = Lp[i]; p < p2; ++p)
         y[Li[p]] -= Lx[p] * yi;
       Scalar l_ki = yi / m_diag[i];       /* the nonzero entry L(k,i) */
@@ -316,8 +317,8 @@
   }
 
   ei_aligned_stack_delete(Scalar, y, size);
-  ei_aligned_stack_delete(int, pattern, size);
-  ei_aligned_stack_delete(int, tags, size);
+  ei_aligned_stack_delete(Index, pattern, size);
+  ei_aligned_stack_delete(Index, tags, size);
 
   return ok;  /* success, diagonal of D is all nonzero */
 }
@@ -327,7 +328,7 @@
 template<typename Derived>
 bool SparseLDLT<MatrixType, Backend>::solveInPlace(MatrixBase<Derived> &b) const
 {
-  const int size = m_matrix.rows();
+  const Index size = m_matrix.rows();
   ei_assert(size==b.rows());
   if (!m_succeeded)
     return false;
diff --git a/Eigen/src/Sparse/SparseLLT.h b/Eigen/src/Sparse/SparseLLT.h
index a1c10ba..37c6c3f 100644
--- a/Eigen/src/Sparse/SparseLLT.h
+++ b/Eigen/src/Sparse/SparseLLT.h
@@ -40,6 +40,7 @@
 {
   protected:
     typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::Index Index;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
     typedef SparseMatrix<Scalar> CholMatrixType;
 
@@ -127,7 +128,7 @@
 void SparseLLT<MatrixType,Backend>::compute(const MatrixType& a)
 {
   assert(a.rows()==a.cols());
-  const int size = a.rows();
+  const Index size = a.rows();
   m_matrix.resize(size, size);
 
   // allocate a temporary vector for accumulations
@@ -137,7 +138,7 @@
   // TODO estimate the number of non zeros
   m_matrix.setZero();
   m_matrix.reserve(a.nonZeros()*2);
-  for (int j = 0; j < size; ++j)
+  for (Index j = 0; j < size; ++j)
   {
     Scalar x = ei_real(a.coeff(j,j));
 
@@ -154,7 +155,7 @@
       for (; it; ++it)
         tempVector.coeffRef(it.index()) = it.value();
     }
-    for (int k=0; k<j+1; ++k)
+    for (Index k=0; k<j+1; ++k)
     {
       typename CholMatrixType::InnerIterator it(m_matrix, k);
       while (it && it.index()<j)
@@ -190,7 +191,7 @@
 template<typename Derived>
 bool SparseLLT<MatrixType, Backend>::solveInPlace(MatrixBase<Derived> &b) const
 {
-  const int size = m_matrix.rows();
+  const Index size = m_matrix.rows();
   ei_assert(size==b.rows());
 
   m_matrix.template triangularView<Lower>().solveInPlace(b);
diff --git a/Eigen/src/Sparse/SparseMatrix.h b/Eigen/src/Sparse/SparseMatrix.h
index 06cc7a9..fd41d73 100644
--- a/Eigen/src/Sparse/SparseMatrix.h
+++ b/Eigen/src/Sparse/SparseMatrix.h
@@ -77,46 +77,46 @@
 
     typedef SparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
 
-    int m_outerSize;
-    int m_innerSize;
-    int* m_outerIndex;
+    Index m_outerSize;
+    Index m_innerSize;
+    Index* m_outerIndex;
     CompressedStorage<Scalar> m_data;
 
   public:
 
-    inline int rows() const { return IsRowMajor ? m_outerSize : m_innerSize; }
-    inline int cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
+    inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; }
+    inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
 
-    inline int innerSize() const { return m_innerSize; }
-    inline int outerSize() const { return m_outerSize; }
-    inline int innerNonZeros(int j) const { return m_outerIndex[j+1]-m_outerIndex[j]; }
+    inline Index innerSize() const { return m_innerSize; }
+    inline Index outerSize() const { return m_outerSize; }
+    inline Index innerNonZeros(Index j) const { return m_outerIndex[j+1]-m_outerIndex[j]; }
 
     inline const Scalar* _valuePtr() const { return &m_data.value(0); }
     inline Scalar* _valuePtr() { return &m_data.value(0); }
 
-    inline const int* _innerIndexPtr() const { return &m_data.index(0); }
-    inline int* _innerIndexPtr() { return &m_data.index(0); }
+    inline const Index* _innerIndexPtr() const { return &m_data.index(0); }
+    inline Index* _innerIndexPtr() { return &m_data.index(0); }
 
-    inline const int* _outerIndexPtr() const { return m_outerIndex; }
-    inline int* _outerIndexPtr() { return m_outerIndex; }
+    inline const Index* _outerIndexPtr() const { return m_outerIndex; }
+    inline Index* _outerIndexPtr() { return m_outerIndex; }
 
-    inline Scalar coeff(int row, int col) const
+    inline Scalar coeff(Index row, Index col) const
     {
-      const int outer = IsRowMajor ? row : col;
-      const int inner = IsRowMajor ? col : row;
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
       return m_data.atInRange(m_outerIndex[outer], m_outerIndex[outer+1], inner);
     }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
-      const int outer = IsRowMajor ? row : col;
-      const int inner = IsRowMajor ? col : row;
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
 
-      int start = m_outerIndex[outer];
-      int end = m_outerIndex[outer+1];
+      Index start = m_outerIndex[outer];
+      Index end = m_outerIndex[outer+1];
       ei_assert(end>=start && "you probably called coeffRef on a non finalized matrix");
       ei_assert(end>start && "coeffRef cannot be called on a zero coefficient");
-      const int id = m_data.searchLowerIndex(start,end-1,inner);
+      const Index id = m_data.searchLowerIndex(start,end-1,inner);
       ei_assert((id<end) && (m_data.index(id)==inner) && "coeffRef cannot be called on a zero coefficient");
       return m_data.value(id);
     }
@@ -129,40 +129,40 @@
     inline void setZero()
     {
       m_data.clear();
-      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(int));
+      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index));
     }
 
     /** \returns the number of non zero coefficients */
-    inline int nonZeros() const  { return static_cast<int>(m_data.size()); }
+    inline Index nonZeros() const  { return static_cast<Index>(m_data.size()); }
 
     /** \deprecated use setZero() and reserve()
       * Initializes the filling process of \c *this.
       * \param reserveSize approximate number of nonzeros
       * Note that the matrix \c *this is zero-ed.
       */
-    EIGEN_DEPRECATED void startFill(int reserveSize = 1000)
+    EIGEN_DEPRECATED void startFill(Index reserveSize = 1000)
     {
       setZero();
       m_data.reserve(reserveSize);
     }
 
     /** Preallocates \a reserveSize non zeros */
-    inline void reserve(int reserveSize)
+    inline void reserve(Index reserveSize)
     {
       m_data.reserve(reserveSize);
     }
 
     /** \deprecated use insert()
       */
-    EIGEN_DEPRECATED Scalar& fill(int row, int col)
+    EIGEN_DEPRECATED Scalar& fill(Index row, Index col)
     {
-      const int outer = IsRowMajor ? row : col;
-      const int inner = IsRowMajor ? col : row;
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
 
       if (m_outerIndex[outer+1]==0)
       {
         // we start a new inner vector
-        int i = outer;
+        Index i = outer;
         while (i>=0 && m_outerIndex[i]==0)
         {
           m_outerIndex[i] = m_data.size();
@@ -176,7 +176,7 @@
       }
 //       std::cerr << size_t(m_outerIndex[outer+1]) << " == " << m_data.size() << "\n";
       assert(size_t(m_outerIndex[outer+1]) == m_data.size());
-      int id = m_outerIndex[outer+1];
+      Index id = m_outerIndex[outer+1];
       ++m_outerIndex[outer+1];
 
       m_data.append(0, inner);
@@ -185,25 +185,25 @@
 
     //--- low level purely coherent filling ---
 
-    inline Scalar& insertBack(int outer, int inner)
+    inline Scalar& insertBack(Index outer, Index inner)
     {
       ei_assert(size_t(m_outerIndex[outer+1]) == m_data.size() && "wrong sorted insertion");
       ei_assert( (m_outerIndex[outer+1]-m_outerIndex[outer]==0 || m_data.index(m_data.size()-1)<inner) && "wrong sorted insertion");
-      int id = m_outerIndex[outer+1];
+      Index id = m_outerIndex[outer+1];
       ++m_outerIndex[outer+1];
       m_data.append(0, inner);
       return m_data.value(id);
     }
 
-    inline Scalar& insertBackNoCheck(int outer, int inner)
+    inline Scalar& insertBackNoCheck(Index outer, Index inner)
     {
-      int id = m_outerIndex[outer+1];
+      Index id = m_outerIndex[outer+1];
       ++m_outerIndex[outer+1];
       m_data.append(0, inner);
       return m_data.value(id);
     }
 
-    inline void startVec(int outer)
+    inline void startVec(Index outer)
     {
       ei_assert(m_outerIndex[outer]==int(m_data.size()) && "you must call startVec on each inner vec");
       ei_assert(m_outerIndex[outer+1]==0 && "you must call startVec on each inner vec");
@@ -215,7 +215,7 @@
     /** \deprecated use insert()
       * Like fill() but with random inner coordinates.
       */
-    EIGEN_DEPRECATED Scalar& fillrand(int row, int col)
+    EIGEN_DEPRECATED Scalar& fillrand(Index row, Index col)
     {
       return insert(row,col);
     }
@@ -228,18 +228,18 @@
       *
       * After an insertion session, you should call the finalize() function.
       */
-    EIGEN_DONT_INLINE Scalar& insert(int row, int col)
+    EIGEN_DONT_INLINE Scalar& insert(Index row, Index col)
     {
-      const int outer = IsRowMajor ? row : col;
-      const int inner = IsRowMajor ? col : row;
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
 
-      int previousOuter = outer;
+      Index previousOuter = outer;
       if (m_outerIndex[outer+1]==0)
       {
         // we start a new inner vector
         while (previousOuter>=0 && m_outerIndex[previousOuter]==0)
         {
-          m_outerIndex[previousOuter] = static_cast<int>(m_data.size());
+          m_outerIndex[previousOuter] = static_cast<Index>(m_data.size());
           --previousOuter;
         }
         m_outerIndex[outer+1] = m_outerIndex[outer];
@@ -285,9 +285,9 @@
         {
           // oops wrong guess.
           // let's correct the outer offsets
-          for (int k=0; k<=(outer+1); ++k)
+          for (Index k=0; k<=(outer+1); ++k)
             m_outerIndex[k] = 0;
-          int k=outer+1;
+          Index k=outer+1;
           while(m_outerIndex[k]==0)
             m_outerIndex[k++] = 1;
           while (k<=m_outerSize && m_outerIndex[k]!=0)
@@ -306,13 +306,13 @@
         {
           // we are not inserting into the last inner vec
           // update outer indices:
-          int j = outer+2;
+          Index j = outer+2;
           while (j<=m_outerSize && m_outerIndex[j]!=0)
             m_outerIndex[j++]++;
           --j;
           // shift data of last vecs:
-          int k = m_outerIndex[j]-1;
-          while (k>=int(id))
+          Index k = m_outerIndex[j]-1;
+          while (k>=Index(id))
           {
             m_data.index(k) = m_data.index(k-1);
             m_data.value(k) = m_data.value(k-1);
@@ -338,8 +338,8 @@
       */
     inline void finalize()
     {
-      int size = static_cast<int>(m_data.size());
-      int i = m_outerSize;
+      Index size = static_cast<Index>(m_data.size());
+      Index i = m_outerSize;
       // find the last filled column
       while (i>=0 && m_outerIndex[i]==0)
         --i;
@@ -353,13 +353,13 @@
 
     void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
     {
-      int k = 0;
-      for (int j=0; j<m_outerSize; ++j)
+      Index k = 0;
+      for (Index j=0; j<m_outerSize; ++j)
       {
-        int previousStart = m_outerIndex[j];
+        Index previousStart = m_outerIndex[j];
         m_outerIndex[j] = k;
-        int end = m_outerIndex[j+1];
-        for (int i=previousStart; i<end; ++i)
+        Index end = m_outerIndex[j+1];
+        for (Index i=previousStart; i<end; ++i)
         {
           if (!ei_isMuchSmallerThan(m_data.value(i), reference, epsilon))
           {
@@ -374,22 +374,22 @@
     }
 
     /** Resizes the matrix to a \a rows x \a cols matrix and initializes it to zero
-      * \sa resizeNonZeros(int), reserve(), setZero()
+      * \sa resizeNonZeros(Index), reserve(), setZero()
       */
-    void resize(int rows, int cols)
+    void resize(Index rows, Index cols)
     {
-      const int outerSize = IsRowMajor ? rows : cols;
+      const Index outerSize = IsRowMajor ? rows : cols;
       m_innerSize = IsRowMajor ? cols : rows;
       m_data.clear();
       if (m_outerSize != outerSize || m_outerSize==0)
       {
         delete[] m_outerIndex;
-        m_outerIndex = new int [outerSize+1];
+        m_outerIndex = new Index [outerSize+1];
         m_outerSize = outerSize;
       }
-      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(int));
+      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index));
     }
-    void resizeNonZeros(int size)
+    void resizeNonZeros(Index size)
     {
       m_data.resize(size);
     }
@@ -400,7 +400,7 @@
       resize(0, 0);
     }
 
-    inline SparseMatrix(int rows, int cols)
+    inline SparseMatrix(Index rows, Index cols)
       : m_outerSize(0), m_innerSize(0), m_outerIndex(0)
     {
       resize(rows, cols);
@@ -438,7 +438,7 @@
       else
       {
         resize(other.rows(), other.cols());
-        memcpy(m_outerIndex, other.m_outerIndex, (m_outerSize+1)*sizeof(int));
+        memcpy(m_outerIndex, other.m_outerIndex, (m_outerSize+1)*sizeof(Index));
         m_data = other.m_data;
       }
       return *this;
@@ -465,19 +465,19 @@
         OtherCopy otherCopy(other.derived());
 
         resize(other.rows(), other.cols());
-        Eigen::Map<VectorXi>(m_outerIndex,outerSize()).setZero();
+        Eigen::Map<Matrix<Index, Dynamic, 1> > (m_outerIndex,outerSize()).setZero();
         // pass 1
         // FIXME the above copy could be merged with that pass
-        for (int j=0; j<otherCopy.outerSize(); ++j)
+        for (Index j=0; j<otherCopy.outerSize(); ++j)
           for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
             ++m_outerIndex[it.index()];
 
         // prefix sum
-        int count = 0;
+        Index count = 0;
         VectorXi positions(outerSize());
-        for (int j=0; j<outerSize(); ++j)
+        for (Index j=0; j<outerSize(); ++j)
         {
-          int tmp = m_outerIndex[j];
+          Index tmp = m_outerIndex[j];
           m_outerIndex[j] = count;
           positions[j] = count;
           count += tmp;
@@ -486,11 +486,11 @@
         // alloc
         m_data.resize(count);
         // pass 2
-        for (int j=0; j<otherCopy.outerSize(); ++j)
+        for (Index j=0; j<otherCopy.outerSize(); ++j)
         {
           for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
           {
-            int pos = positions[it.index()]++;
+            Index pos = positions[it.index()]++;
             m_data.index(pos) = j;
             m_data.value(pos) = it.value();
           }
@@ -508,14 +508,14 @@
     {
       EIGEN_DBG_SPARSE(
         s << "Nonzero entries:\n";
-        for (int i=0; i<m.nonZeros(); ++i)
+        for (Index i=0; i<m.nonZeros(); ++i)
         {
           s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") ";
         }
         s << std::endl;
         s << std::endl;
         s << "Column pointers:\n";
-        for (int i=0; i<m.outerSize(); ++i)
+        for (Index i=0; i<m.outerSize(); ++i)
         {
           s << m.m_outerIndex[i] << " ";
         }
@@ -540,12 +540,12 @@
 class SparseMatrix<Scalar,_Options>::InnerIterator
 {
   public:
-    InnerIterator(const SparseMatrix& mat, int outer)
+    InnerIterator(const SparseMatrix& mat, Index outer)
       : m_matrix(mat), m_outer(outer), m_id(mat.m_outerIndex[outer]), m_start(m_id), m_end(mat.m_outerIndex[outer+1])
     {}
 
     template<unsigned int Added, unsigned int Removed>
-    InnerIterator(const Flagged<SparseMatrix,Added,Removed>& mat, int outer)
+    InnerIterator(const Flagged<SparseMatrix,Added,Removed>& mat, Index outer)
       : m_matrix(mat._expression()), m_outer(outer), m_id(m_matrix.m_outerIndex[outer]),
         m_start(m_id), m_end(m_matrix.m_outerIndex[outer+1])
     {}
@@ -555,19 +555,19 @@
     inline Scalar value() const { return m_matrix.m_data.value(m_id); }
     inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix.m_data.value(m_id)); }
 
-    inline int index() const { return m_matrix.m_data.index(m_id); }
-    inline int outer() const { return m_outer; }
-    inline int row() const { return IsRowMajor ? m_outer : index(); }
-    inline int col() const { return IsRowMajor ? index() : m_outer; }
+    inline Index index() const { return m_matrix.m_data.index(m_id); }
+    inline Index outer() const { return m_outer; }
+    inline Index row() const { return IsRowMajor ? m_outer : index(); }
+    inline Index col() const { return IsRowMajor ? index() : m_outer; }
 
     inline operator bool() const { return (m_id < m_end) && (m_id>=m_start); }
 
   protected:
     const SparseMatrix& m_matrix;
-    const int m_outer;
-    int m_id;
-    const int m_start;
-    const int m_end;
+    const Index m_outer;
+    Index m_id;
+    const Index m_start;
+    const Index m_end;
 };
 
 #endif // EIGEN_SPARSEMATRIX_H
diff --git a/Eigen/src/Sparse/SparseMatrixBase.h b/Eigen/src/Sparse/SparseMatrixBase.h
index 65fa19a..a432682 100644
--- a/Eigen/src/Sparse/SparseMatrixBase.h
+++ b/Eigen/src/Sparse/SparseMatrixBase.h
@@ -42,6 +42,9 @@
 
     typedef typename ei_traits<Derived>::Scalar Scalar;
     typedef typename ei_packet_traits<Scalar>::type PacketScalar;
+    typedef typename ei_traits<Derived>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
+
     typedef SparseMatrixBase StorageBaseType;
 
     enum {
@@ -145,15 +148,15 @@
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
     /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
-    inline int rows() const { return derived().rows(); }
+    inline Index rows() const { return derived().rows(); }
     /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
-    inline int cols() const { return derived().cols(); }
+    inline Index cols() const { return derived().cols(); }
     /** \returns the number of coefficients, which is \a rows()*cols().
       * \sa rows(), cols(), SizeAtCompileTime. */
-    inline int size() const { return rows() * cols(); }
+    inline Index size() const { return rows() * cols(); }
     /** \returns the number of nonzero coefficients which is in practice the number
       * of stored coefficients. */
-    inline int nonZeros() const { return derived().nonZeros(); }
+    inline Index nonZeros() const { return derived().nonZeros(); }
     /** \returns true if either the number of rows or the number of columns is equal to 1.
       * In other words, this function returns
       * \code rows()==1 || cols()==1 \endcode
@@ -161,10 +164,10 @@
     inline bool isVector() const { return rows()==1 || cols()==1; }
     /** \returns the size of the storage major dimension,
       * i.e., the number of columns for a columns major matrix, and the number of rows otherwise */
-    int outerSize() const { return (int(Flags)&RowMajorBit) ? this->rows() : this->cols(); }
+    Index outerSize() const { return (int(Flags)&RowMajorBit) ? this->rows() : this->cols(); }
     /** \returns the size of the inner dimension according to the storage order,
       * i.e., the number of rows for a columns major matrix, and the number of cols otherwise */
-    int innerSize() const { return (int(Flags)&RowMajorBit) ? this->cols() : this->rows(); }
+    Index innerSize() const { return (int(Flags)&RowMajorBit) ? this->cols() : this->rows(); }
 
     bool isRValue() const { return m_isRValue; }
     Derived& markAsRValue() { m_isRValue = true; return derived(); }
@@ -193,13 +196,13 @@
 
       enum { Flip = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit) };
 
-      const int outerSize = other.outerSize();
+      const Index outerSize = other.outerSize();
       //typedef typename ei_meta_if<transpose, LinkedVectorMatrix<Scalar,Flags&RowMajorBit>, Derived>::ret TempType;
       // thanks to shallow copies, we always eval to a tempary
       Derived temp(other.rows(), other.cols());
 
       temp.reserve(std::max(this->rows(),this->cols())*2);
-      for (int j=0; j<outerSize; ++j)
+      for (Index j=0; j<outerSize; ++j)
       {
         temp.startVec(j);
         for (typename OtherDerived::InnerIterator it(other.derived(), j); it; ++it)
@@ -222,14 +225,14 @@
 //       std::cout << Flags << " " << OtherDerived::Flags << "\n";
       const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
 //       std::cout << "eval transpose = " << transpose << "\n";
-      const int outerSize = (int(OtherDerived::Flags) & RowMajorBit) ? other.rows() : other.cols();
+      const Index outerSize = (int(OtherDerived::Flags) & RowMajorBit) ? other.rows() : other.cols();
       if ((!transpose) && other.isRValue())
       {
         // eval without temporary
         derived().resize(other.rows(), other.cols());
         derived().setZero();
         derived().reserve(std::max(this->rows(),this->cols())*2);
-        for (int j=0; j<outerSize; ++j)
+        for (Index j=0; j<outerSize; ++j)
         {
           derived().startVec(j);
           for (typename OtherDerived::InnerIterator it(other.derived(), j); it; ++it)
@@ -258,9 +261,9 @@
     {
       if (Flags&RowMajorBit)
       {
-        for (int row=0; row<m.outerSize(); ++row)
+        for (Index row=0; row<m.outerSize(); ++row)
         {
-          int col = 0;
+          Index col = 0;
           for (typename Derived::InnerIterator it(m.derived(), row); it; ++it)
           {
             for ( ; col<it.index(); ++col)
@@ -276,7 +279,7 @@
       else
       {
         if (m.cols() == 1) {
-          int row = 0;
+          Index row = 0;
           for (typename Derived::InnerIterator it(m.derived(), 0); it; ++it)
           {
             for ( ; row<it.index(); ++row)
@@ -405,20 +408,20 @@
     const AdjointReturnType adjoint() const { return transpose(); }
 
     // sub-vector
-    SparseInnerVectorSet<Derived,1> row(int i);
-    const SparseInnerVectorSet<Derived,1> row(int i) const;
-    SparseInnerVectorSet<Derived,1> col(int j);
-    const SparseInnerVectorSet<Derived,1> col(int j) const;
-    SparseInnerVectorSet<Derived,1> innerVector(int outer);
-    const SparseInnerVectorSet<Derived,1> innerVector(int outer) const;
+    SparseInnerVectorSet<Derived,1> row(Index i);
+    const SparseInnerVectorSet<Derived,1> row(Index i) const;
+    SparseInnerVectorSet<Derived,1> col(Index j);
+    const SparseInnerVectorSet<Derived,1> col(Index j) const;
+    SparseInnerVectorSet<Derived,1> innerVector(Index outer);
+    const SparseInnerVectorSet<Derived,1> innerVector(Index outer) const;
 
     // set of sub-vectors
-    SparseInnerVectorSet<Derived,Dynamic> subrows(int start, int size);
-    const SparseInnerVectorSet<Derived,Dynamic> subrows(int start, int size) const;
-    SparseInnerVectorSet<Derived,Dynamic> subcols(int start, int size);
-    const SparseInnerVectorSet<Derived,Dynamic> subcols(int start, int size) const;
-    SparseInnerVectorSet<Derived,Dynamic> innerVectors(int outerStart, int outerSize);
-    const SparseInnerVectorSet<Derived,Dynamic> innerVectors(int outerStart, int outerSize) const;
+    SparseInnerVectorSet<Derived,Dynamic> subrows(Index start, Index size);
+    const SparseInnerVectorSet<Derived,Dynamic> subrows(Index start, Index size) const;
+    SparseInnerVectorSet<Derived,Dynamic> subcols(Index start, Index size);
+    const SparseInnerVectorSet<Derived,Dynamic> subcols(Index start, Index size) const;
+    SparseInnerVectorSet<Derived,Dynamic> innerVectors(Index outerStart, Index outerSize);
+    const SparseInnerVectorSet<Derived,Dynamic> innerVectors(Index outerStart, Index outerSize) const;
 
 //     typename BlockReturnType<Derived>::Type block(int startRow, int startCol, int blockRows, int blockCols);
 //     const typename BlockReturnType<Derived>::Type
@@ -493,7 +496,7 @@
       void evalTo(MatrixBase<DenseDerived>& dst) const
       {
         dst.setZero();
-        for (int j=0; j<outerSize(); ++j)
+        for (Index j=0; j<outerSize(); ++j)
           for (typename Derived::InnerIterator i(derived(),j); i; ++i)
             dst.coeffRef(i.row(),i.col()) = i.value();
       }
diff --git a/Eigen/src/Sparse/SparseProduct.h b/Eigen/src/Sparse/SparseProduct.h
index 078ac5f..fb53902 100644
--- a/Eigen/src/Sparse/SparseProduct.h
+++ b/Eigen/src/Sparse/SparseProduct.h
@@ -126,8 +126,8 @@
       EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
     }
 
-    EIGEN_STRONG_INLINE int rows() const { return m_lhs.rows(); }
-    EIGEN_STRONG_INLINE int cols() const { return m_rhs.cols(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); }
 
     EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; }
     EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; }
@@ -140,16 +140,17 @@
 template<typename Lhs, typename Rhs, typename ResultType>
 static void ei_sparse_product_impl2(const Lhs& lhs, const Rhs& rhs, ResultType& res)
 {
-  typedef typename ei_traits<typename ei_cleantype<Lhs>::type>::Scalar Scalar;
+  typedef typename ei_cleantype<Lhs>::type::Scalar Scalar;
+  typedef typename ei_cleantype<Lhs>::type::Index Index;
 
   // make sure to call innerSize/outerSize since we fake the storage order.
-  int rows = lhs.innerSize();
-  int cols = rhs.outerSize();
+  Index rows = lhs.innerSize();
+  Index cols = rhs.outerSize();
   ei_assert(lhs.outerSize() == rhs.innerSize());
 
   std::vector<bool> mask(rows,false);
   Matrix<Scalar,Dynamic,1> values(rows);
-  Matrix<int,Dynamic,1>    indices(rows);
+  Matrix<Index,Dynamic,1>    indices(rows);
 
   // estimate the number of non zero entries
   float ratioLhs = float(lhs.nonZeros())/(float(lhs.rows())*float(lhs.cols()));
@@ -160,20 +161,20 @@
 //  int t = (rows*100)/139;
 
   res.resize(rows, cols);
-  res.reserve(int(ratioRes*rows*cols));
+  res.reserve(Index(ratioRes*rows*cols));
   // we compute each column of the result, one after the other
-  for (int j=0; j<cols; ++j)
+  for (Index j=0; j<cols; ++j)
   {
 
     res.startVec(j);
-    int nnz = 0;
+    Index nnz = 0;
     for (typename Rhs::InnerIterator rhsIt(rhs, j); rhsIt; ++rhsIt)
     {
       Scalar y = rhsIt.value();
-      int k = rhsIt.index();
+      Index k = rhsIt.index();
       for (typename Lhs::InnerIterator lhsIt(lhs, k); lhsIt; ++lhsIt)
       {
-        int i = lhsIt.index();
+        Index i = lhsIt.index();
         Scalar x = lhsIt.value();
         if(!mask[i])
         {
@@ -225,11 +226,12 @@
 {
 //   return ei_sparse_product_impl2(lhs,rhs,res);
 
-  typedef typename ei_traits<typename ei_cleantype<Lhs>::type>::Scalar Scalar;
+  typedef typename ei_cleantype<Lhs>::type::Scalar Scalar;
+  typedef typename ei_cleantype<Lhs>::type::Index Index;
 
   // make sure to call innerSize/outerSize since we fake the storage order.
-  int rows = lhs.innerSize();
-  int cols = rhs.outerSize();
+  Index rows = lhs.innerSize();
+  Index cols = rhs.outerSize();
   //int size = lhs.outerSize();
   ei_assert(lhs.outerSize() == rhs.innerSize());
 
@@ -242,8 +244,8 @@
   float ratioRes = std::min(ratioLhs * avgNnzPerRhsColumn, 1.f);
 
   res.resize(rows, cols);
-  res.reserve(int(ratioRes*rows*cols));
-  for (int j=0; j<cols; ++j)
+  res.reserve(Index(ratioRes*rows*cols));
+  for (Index j=0; j<cols; ++j)
   {
     // let's do a more accurate determination of the nnz ratio for the current column j of res
     //float ratioColRes = std::min(ratioLhs * rhs.innerNonZeros(j), 1.f);
@@ -514,7 +516,7 @@
       typedef typename ei_cleantype<Rhs>::type _Rhs;
       typedef typename _Lhs::InnerIterator LhsInnerIterator;
       enum { LhsIsRowMajor = (_Lhs::Flags&RowMajorBit)==RowMajorBit };
-      for(int j=0; j<m_lhs.outerSize(); ++j)
+      for(Index j=0; j<m_lhs.outerSize(); ++j)
       {
         typename Rhs::Scalar rhs_j = alpha * m_rhs.coeff(j,0);
         Block<Dest,1,Dest::ColsAtCompileTime> dest_j(dest.row(LhsIsRowMajor ? j : 0));
@@ -555,7 +557,7 @@
       typedef typename ei_cleantype<Rhs>::type _Rhs;
       typedef typename _Rhs::InnerIterator RhsInnerIterator;
       enum { RhsIsRowMajor = (_Rhs::Flags&RowMajorBit)==RowMajorBit };
-      for(int j=0; j<m_rhs.outerSize(); ++j)
+      for(Index j=0; j<m_rhs.outerSize(); ++j)
         for(RhsInnerIterator i(m_rhs,j); i; ++i)
           dest.col(RhsIsRowMajor ? i.index() : j) += (alpha*i.value()) * m_lhs.col(RhsIsRowMajor ? j : i.index());
     }
diff --git a/Eigen/src/Sparse/SparseRedux.h b/Eigen/src/Sparse/SparseRedux.h
index a243be6..ea2ce18 100644
--- a/Eigen/src/Sparse/SparseRedux.h
+++ b/Eigen/src/Sparse/SparseRedux.h
@@ -31,7 +31,7 @@
 {
   ei_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix");
   Scalar res = 0;
-  for (int j=0; j<outerSize(); ++j)
+  for (Index j=0; j<outerSize(); ++j)
     for (typename Derived::InnerIterator iter(derived(),j); iter; ++iter)
       res += iter.value();
   return res;
diff --git a/Eigen/src/Sparse/SparseSelfAdjointView.h b/Eigen/src/Sparse/SparseSelfAdjointView.h
index d477053..703ca64 100644
--- a/Eigen/src/Sparse/SparseSelfAdjointView.h
+++ b/Eigen/src/Sparse/SparseSelfAdjointView.h
@@ -49,7 +49,8 @@
 {
   public:
 
-    typedef typename ei_traits<MatrixType>::Scalar Scalar;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::Index Index;
 
     inline SparseSelfAdjointView(const MatrixType& matrix) : m_matrix(matrix)
     {
@@ -57,8 +58,8 @@
       ei_assert(rows()==cols() && "SelfAdjointView is only for squared matrices");
     }
 
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
 
     /** \internal \returns a reference to the nested matrix */
     const MatrixType& matrix() const { return m_matrix; }
@@ -173,7 +174,7 @@
               || ( (UpLo&Lower) && LhsIsRowMajor),
         ProcessSecondHalf = !ProcessFirstHalf
       };
-      for (int j=0; j<m_lhs.outerSize(); ++j)
+      for (Index j=0; j<m_lhs.outerSize(); ++j)
       {
         LhsInnerIterator i(m_lhs,j);
         if (ProcessSecondHalf && i && (i.index()==j))
@@ -184,8 +185,8 @@
         Block<Dest,1,Dest::ColsAtCompileTime> dest_j(dest.row(LhsIsRowMajor ? j : 0));
         for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i)
         {
-          int a = LhsIsRowMajor ? j : i.index();
-          int b = LhsIsRowMajor ? i.index() : j;
+          Index a = LhsIsRowMajor ? j : i.index();
+          Index b = LhsIsRowMajor ? i.index() : j;
           typename Lhs::Scalar v = i.value();
           dest.row(a) += (v) * m_rhs.row(b);
           dest.row(b) += ei_conj(v) * m_rhs.row(a);
diff --git a/Eigen/src/Sparse/SparseTranspose.h b/Eigen/src/Sparse/SparseTranspose.h
index b8c3861..a94f5ae 100644
--- a/Eigen/src/Sparse/SparseTranspose.h
+++ b/Eigen/src/Sparse/SparseTranspose.h
@@ -35,19 +35,19 @@
     class InnerIterator;
     class ReverseInnerIterator;
 
-    inline int nonZeros() const { return derived().nestedExpression().nonZeros(); }
+    inline Index nonZeros() const { return derived().nestedExpression().nonZeros(); }
 
     // FIXME should be keep them ?
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     { return const_cast_derived().nestedExpression().coeffRef(col, row); }
 
-    inline const Scalar coeff(int row, int col) const
+    inline const Scalar coeff(Index row, Index col) const
     { return derived().nestedExpression().coeff(col, row); }
 
-    inline const Scalar coeff(int index) const
+    inline const Scalar coeff(Index index) const
     { return derived().nestedExpression().coeff(index); }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index index)
     { return const_cast_derived().nestedExpression().coeffRef(index); }
 };
 
@@ -56,11 +56,11 @@
     typedef typename MatrixType::InnerIterator Base;
   public:
 
-    EIGEN_STRONG_INLINE InnerIterator(const TransposeImpl& trans, int outer)
+    EIGEN_STRONG_INLINE InnerIterator(const TransposeImpl& trans, Index outer)
       : Base(trans.derived().nestedExpression(), outer)
     {}
-    inline int row() const { return Base::col(); }
-    inline int col() const { return Base::row(); }
+    inline Index row() const { return Base::col(); }
+    inline Index col() const { return Base::row(); }
 };
 
 template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>::ReverseInnerIterator : public MatrixType::ReverseInnerIterator
@@ -68,11 +68,11 @@
     typedef typename MatrixType::ReverseInnerIterator Base;
   public:
 
-    EIGEN_STRONG_INLINE ReverseInnerIterator(const TransposeImpl& xpr, int outer)
+    EIGEN_STRONG_INLINE ReverseInnerIterator(const TransposeImpl& xpr, Index outer)
       : Base(xpr.derived().nestedExpression(), outer)
     {}
-    inline int row() const { return Base::col(); }
-    inline int col() const { return Base::row(); }
+    inline Index row() const { return Base::col(); }
+    inline Index col() const { return Base::row(); }
 };
 
 #endif // EIGEN_SPARSETRANSPOSE_H
diff --git a/Eigen/src/Sparse/SparseTriangularView.h b/Eigen/src/Sparse/SparseTriangularView.h
index e713220..2588c36 100644
--- a/Eigen/src/Sparse/SparseTriangularView.h
+++ b/Eigen/src/Sparse/SparseTriangularView.h
@@ -38,11 +38,12 @@
   public:
 
     class InnerIterator;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::Index Index;
 
-    inline int rows() { return m_matrix.rows(); }
-    inline int cols() { return m_matrix.cols(); }
+    inline Index rows() { return m_matrix.rows(); }
+    inline Index cols() { return m_matrix.cols(); }
 
-    typedef typename ei_traits<MatrixType>::Scalar Scalar;
     typedef typename ei_meta_if<ei_must_nest_by_value<MatrixType>::ret,
         MatrixType, const MatrixType&>::ret MatrixTypeNested;
 
@@ -68,15 +69,15 @@
     typedef typename MatrixType::InnerIterator Base;
   public:
 
-    EIGEN_STRONG_INLINE InnerIterator(const SparseTriangularView& view, int outer)
+    EIGEN_STRONG_INLINE InnerIterator(const SparseTriangularView& view, Index outer)
       : Base(view.nestedExpression(), outer)
     {
       if(SkipFirst)
         while((*this) && this->index()<outer)
           ++(*this);
     }
-    inline int row() const { return Base::row(); }
-    inline int col() const { return Base::col(); }
+    inline Index row() const { return Base::row(); }
+    inline Index col() const { return Base::col(); }
 
     EIGEN_STRONG_INLINE operator bool() const
     {
diff --git a/Eigen/src/Sparse/SparseUtil.h b/Eigen/src/Sparse/SparseUtil.h
index 782690b..7f10040 100644
--- a/Eigen/src/Sparse/SparseUtil.h
+++ b/Eigen/src/Sparse/SparseUtil.h
@@ -57,16 +57,18 @@
 EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, /=)
 
 #define _EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(Derived, BaseClass) \
-typedef BaseClass Base; \
-typedef typename Eigen::ei_traits<Derived>::Scalar Scalar; \
-typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; \
-typedef typename Eigen::ei_nested<Derived>::type Nested; \
-enum { RowsAtCompileTime = Eigen::ei_traits<Derived>::RowsAtCompileTime, \
-       ColsAtCompileTime = Eigen::ei_traits<Derived>::ColsAtCompileTime, \
-       Flags = Eigen::ei_traits<Derived>::Flags, \
-       CoeffReadCost = Eigen::ei_traits<Derived>::CoeffReadCost, \
-       SizeAtCompileTime = Base::SizeAtCompileTime, \
-       IsVectorAtCompileTime = Base::IsVectorAtCompileTime };
+  typedef BaseClass Base; \
+  typedef typename Eigen::ei_traits<Derived>::Scalar Scalar; \
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; \
+  typedef typename Eigen::ei_nested<Derived>::type Nested; \
+  typedef typename Eigen::ei_traits<Derived>::StorageKind StorageKind; \
+  typedef typename Eigen::ei_index<StorageKind>::type Index; \
+  enum { RowsAtCompileTime = Eigen::ei_traits<Derived>::RowsAtCompileTime, \
+        ColsAtCompileTime = Eigen::ei_traits<Derived>::ColsAtCompileTime, \
+        Flags = Eigen::ei_traits<Derived>::Flags, \
+        CoeffReadCost = Eigen::ei_traits<Derived>::CoeffReadCost, \
+        SizeAtCompileTime = Base::SizeAtCompileTime, \
+        IsVectorAtCompileTime = Base::IsVectorAtCompileTime };
 
 #define EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(Derived) \
   _EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(Derived, Eigen::SparseMatrixBase<Derived>)
@@ -76,6 +78,8 @@
   typedef typename Eigen::ei_traits<Derived>::Scalar Scalar; \
   typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; \
   typedef typename Eigen::ei_nested<Derived>::type Nested; \
+  typedef typename Eigen::ei_traits<Derived>::StorageKind StorageKind; \
+  typedef typename Eigen::ei_index<StorageKind>::type Index; \
   enum { RowsAtCompileTime = Eigen::ei_traits<Derived>::RowsAtCompileTime, \
         ColsAtCompileTime = Eigen::ei_traits<Derived>::ColsAtCompileTime, \
         Flags = Eigen::ei_traits<Derived>::Flags, \
@@ -88,6 +92,12 @@
 #define EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) \
   _EIGEN_SPARSE_PUBLIC_INTERFACE(Derived, Eigen::SparseMatrixBase<Derived>)
 
+template<>
+struct ei_index<Sparse>
+{ typedef EIGEN_DEFAULT_SPARSE_INDEX_TYPE type; };
+
+typedef typename ei_index<Sparse>::type SparseIndex;
+
 enum SparseBackend {
   DefaultBackend,
   Taucs,
diff --git a/Eigen/src/Sparse/SparseVector.h b/Eigen/src/Sparse/SparseVector.h
index 6806ab2..4013b4d 100644
--- a/Eigen/src/Sparse/SparseVector.h
+++ b/Eigen/src/Sparse/SparseVector.h
@@ -70,33 +70,33 @@
     enum { IsColVector = ei_traits<SparseVector>::IsColVector };
 
     CompressedStorage<Scalar> m_data;
-    int m_size;
+    Index m_size;
 
     CompressedStorage<Scalar>& _data() { return m_data; }
     CompressedStorage<Scalar>& _data() const { return m_data; }
 
   public:
 
-    EIGEN_STRONG_INLINE int rows() const { return IsColVector ? m_size : 1; }
-    EIGEN_STRONG_INLINE int cols() const { return IsColVector ? 1 : m_size; }
-    EIGEN_STRONG_INLINE int innerSize() const { return m_size; }
-    EIGEN_STRONG_INLINE int outerSize() const { return 1; }
-    EIGEN_STRONG_INLINE int innerNonZeros(int j) const { ei_assert(j==0); return m_size; }
+    EIGEN_STRONG_INLINE Index rows() const { return IsColVector ? m_size : 1; }
+    EIGEN_STRONG_INLINE Index cols() const { return IsColVector ? 1 : m_size; }
+    EIGEN_STRONG_INLINE Index innerSize() const { return m_size; }
+    EIGEN_STRONG_INLINE Index outerSize() const { return 1; }
+    EIGEN_STRONG_INLINE Index innerNonZeros(Index j) const { ei_assert(j==0); return m_size; }
 
     EIGEN_STRONG_INLINE const Scalar* _valuePtr() const { return &m_data.value(0); }
     EIGEN_STRONG_INLINE Scalar* _valuePtr() { return &m_data.value(0); }
 
-    EIGEN_STRONG_INLINE const int* _innerIndexPtr() const { return &m_data.index(0); }
-    EIGEN_STRONG_INLINE int* _innerIndexPtr() { return &m_data.index(0); }
+    EIGEN_STRONG_INLINE const Index* _innerIndexPtr() const { return &m_data.index(0); }
+    EIGEN_STRONG_INLINE Index* _innerIndexPtr() { return &m_data.index(0); }
 
-    inline Scalar coeff(int row, int col) const
+    inline Scalar coeff(Index row, Index col) const
     {
       ei_assert((IsColVector ? col : row)==0);
       return coeff(IsColVector ? row : col);
     }
-    inline Scalar coeff(int i) const { return m_data.at(i); }
+    inline Scalar coeff(Index i) const { return m_data.at(i); }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline Scalar& coeffRef(Index row, Index col)
     {
       ei_assert((IsColVector ? col : row)==0);
       return coeff(IsColVector ? row : col);
@@ -108,7 +108,7 @@
       *
       * This insertion might be very costly if the number of nonzeros above \a i is large.
       */
-    inline Scalar& coeffRef(int i)
+    inline Scalar& coeffRef(Index i)
     {
       return m_data.atWithInsertion(i);
     }
@@ -120,33 +120,33 @@
     inline void setZero() { m_data.clear(); }
 
     /** \returns the number of non zero coefficients */
-    inline int nonZeros() const  { return static_cast<int>(m_data.size()); }
+    inline Index nonZeros() const  { return static_cast<Index>(m_data.size()); }
 
-    inline void startVec(int outer)
+    inline void startVec(Index outer)
     {
       ei_assert(outer==0);
     }
 
-    inline Scalar& insertBack(int outer, int inner)
+    inline Scalar& insertBack(Index outer, Index inner)
     {
       ei_assert(outer==0);
       return insertBack(inner);
     }
-    inline Scalar& insertBack(int i)
+    inline Scalar& insertBack(Index i)
     {
       m_data.append(0, i);
       return m_data.value(m_data.size()-1);
     }
 
-    inline Scalar& insert(int outer, int inner)
+    inline Scalar& insert(Index outer, Index inner)
     {
       ei_assert(outer==0);
       return insert(inner);
     }
-    Scalar& insert(int i)
+    Scalar& insert(Index i)
     {
-      int startId = 0;
-      int id = m_data.size() - 1;
+      Index startId = 0;
+      Index id = m_data.size() - 1;
       // TODO smart realloc
       m_data.resize(id+2,1);
 
@@ -163,38 +163,38 @@
 
     /**
       */
-    inline void reserve(int reserveSize) { m_data.reserve(reserveSize); }
+    inline void reserve(Index reserveSize) { m_data.reserve(reserveSize); }
 
     /** \deprecated use setZero() and reserve() */
-    EIGEN_DEPRECATED void startFill(int reserve)
+    EIGEN_DEPRECATED void startFill(Index reserve)
     {
       setZero();
       m_data.reserve(reserve);
     }
 
-    /** \deprecated use insertBack(int,int) */
-    EIGEN_DEPRECATED Scalar& fill(int r, int c)
+    /** \deprecated use insertBack(Index,Index) */
+    EIGEN_DEPRECATED Scalar& fill(Index r, Index c)
     {
       ei_assert(r==0 || c==0);
       return fill(IsColVector ? r : c);
     }
 
-    /** \deprecated use insertBack(int) */
-    EIGEN_DEPRECATED Scalar& fill(int i)
+    /** \deprecated use insertBack(Index) */
+    EIGEN_DEPRECATED Scalar& fill(Index i)
     {
       m_data.append(0, i);
       return m_data.value(m_data.size()-1);
     }
 
-    /** \deprecated use insert(int,int) */
-    EIGEN_DEPRECATED Scalar& fillrand(int r, int c)
+    /** \deprecated use insert(Index,Index) */
+    EIGEN_DEPRECATED Scalar& fillrand(Index r, Index c)
     {
       ei_assert(r==0 || c==0);
       return fillrand(IsColVector ? r : c);
     }
 
-    /** \deprecated use insert(int) */
-    EIGEN_DEPRECATED Scalar& fillrand(int i)
+    /** \deprecated use insert(Index) */
+    EIGEN_DEPRECATED Scalar& fillrand(Index i)
     {
       return insert(i);
     }
@@ -208,25 +208,25 @@
       m_data.prune(reference,epsilon);
     }
 
-    void resize(int rows, int cols)
+    void resize(Index rows, Index cols)
     {
       ei_assert(rows==1 || cols==1);
       resize(IsColVector ? rows : cols);
     }
 
-    void resize(int newSize)
+    void resize(Index newSize)
     {
       m_size = newSize;
       m_data.clear();
     }
 
-    void resizeNonZeros(int size) { m_data.resize(size); }
+    void resizeNonZeros(Index size) { m_data.resize(size); }
 
     inline SparseVector() : m_size(0) { resize(0); }
 
-    inline SparseVector(int size) : m_size(0) { resize(size); }
+    inline SparseVector(Index size) : m_size(0) { resize(size); }
 
-    inline SparseVector(int rows, int cols) : m_size(0) { resize(rows,cols); }
+    inline SparseVector(Index rows, Index cols) : m_size(0) { resize(rows,cols); }
 
     template<typename OtherDerived>
     inline SparseVector(const MatrixBase<OtherDerived>& other)
@@ -329,7 +329,7 @@
 
     friend std::ostream & operator << (std::ostream & s, const SparseVector& m)
     {
-      for (unsigned int i=0; i<m.nonZeros(); ++i)
+      for (Index i=0; i<m.nonZeros(); ++i)
         s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") ";
       s << std::endl;
       return s;
@@ -368,18 +368,18 @@
 class SparseVector<Scalar,_Options>::InnerIterator
 {
   public:
-    InnerIterator(const SparseVector& vec, int outer=0)
-      : m_data(vec.m_data), m_id(0), m_end(static_cast<int>(m_data.size()))
+    InnerIterator(const SparseVector& vec, Index outer=0)
+      : m_data(vec.m_data), m_id(0), m_end(static_cast<Index>(m_data.size()))
     {
       ei_assert(outer==0);
     }
 
     InnerIterator(const CompressedStorage<Scalar>& data)
-      : m_data(data), m_id(0), m_end(static_cast<int>(m_data.size()))
+      : m_data(data), m_id(0), m_end(static_cast<Index>(m_data.size()))
     {}
 
     template<unsigned int Added, unsigned int Removed>
-    InnerIterator(const Flagged<SparseVector,Added,Removed>& vec, int )
+    InnerIterator(const Flagged<SparseVector,Added,Removed>& vec, Index )
       : m_data(vec._expression().m_data), m_id(0), m_end(m_data.size())
     {}
 
@@ -388,16 +388,16 @@
     inline Scalar value() const { return m_data.value(m_id); }
     inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id)); }
 
-    inline int index() const { return m_data.index(m_id); }
-    inline int row() const { return IsColVector ? index() : 0; }
-    inline int col() const { return IsColVector ? 0 : index(); }
+    inline Index index() const { return m_data.index(m_id); }
+    inline Index row() const { return IsColVector ? index() : 0; }
+    inline Index col() const { return IsColVector ? 0 : index(); }
 
     inline operator bool() const { return (m_id < m_end); }
 
   protected:
     const CompressedStorage<Scalar>& m_data;
-    int m_id;
-    const int m_end;
+    Index m_id;
+    const Index m_end;
 };
 
 #endif // EIGEN_SPARSEVECTOR_H
diff --git a/Eigen/src/misc/Image.h b/Eigen/src/misc/Image.h
index 1d63d81..32392fd 100644
--- a/Eigen/src/misc/Image.h
+++ b/Eigen/src/misc/Image.h
@@ -48,6 +48,8 @@
 {
   typedef _DecompositionType DecompositionType;
   typedef typename DecompositionType::MatrixType MatrixType;
+  typedef ReturnByValue<ei_image_retval_base> Base;
+  typedef typename Base::Index Index;
 
   ei_image_retval_base(const DecompositionType& dec, const MatrixType& originalMatrix)
     : m_dec(dec), m_rank(dec.rank()),
@@ -55,9 +57,9 @@
       m_originalMatrix(originalMatrix)
   {}
 
-  inline int rows() const { return m_dec.rows(); }
-  inline int cols() const { return m_cols; }
-  inline int rank() const { return m_rank; }
+  inline Index rows() const { return m_dec.rows(); }
+  inline Index cols() const { return m_cols; }
+  inline Index rank() const { return m_rank; }
   inline const DecompositionType& dec() const { return m_dec; }
   inline const MatrixType& originalMatrix() const { return m_originalMatrix; }
 
@@ -68,7 +70,7 @@
 
   protected:
     const DecompositionType& m_dec;
-    int m_rank, m_cols;
+    Index m_rank, m_cols;
     const MatrixType& m_originalMatrix;
 };
 
@@ -76,6 +78,7 @@
   typedef typename DecompositionType::MatrixType MatrixType; \
   typedef typename MatrixType::Scalar Scalar; \
   typedef typename MatrixType::RealScalar RealScalar; \
+  typedef typename MatrixType::Index Index; \
   typedef ei_image_retval_base<DecompositionType> Base; \
   using Base::dec; \
   using Base::originalMatrix; \
diff --git a/Eigen/src/misc/Kernel.h b/Eigen/src/misc/Kernel.h
index 497b42e..38a2d40 100644
--- a/Eigen/src/misc/Kernel.h
+++ b/Eigen/src/misc/Kernel.h
@@ -49,6 +49,8 @@
  : public ReturnByValue<ei_kernel_retval_base<_DecompositionType> >
 {
   typedef _DecompositionType DecompositionType;
+  typedef ReturnByValue<ei_kernel_retval_base> Base;
+  typedef typename Base::Index Index;
 
   ei_kernel_retval_base(const DecompositionType& dec)
     : m_dec(dec),
@@ -56,9 +58,9 @@
       m_cols(m_rank==dec.cols() ? 1 : dec.cols() - m_rank)
   {}
 
-  inline int rows() const { return m_dec.cols(); }
-  inline int cols() const { return m_cols; }
-  inline int rank() const { return m_rank; }
+  inline Index rows() const { return m_dec.cols(); }
+  inline Index cols() const { return m_cols; }
+  inline Index rank() const { return m_rank; }
   inline const DecompositionType& dec() const { return m_dec; }
 
   template<typename Dest> inline void evalTo(Dest& dst) const
@@ -68,13 +70,14 @@
 
   protected:
     const DecompositionType& m_dec;
-    int m_rank, m_cols;
+    Index m_rank, m_cols;
 };
 
 #define EIGEN_MAKE_KERNEL_HELPERS(DecompositionType) \
   typedef typename DecompositionType::MatrixType MatrixType; \
   typedef typename MatrixType::Scalar Scalar; \
   typedef typename MatrixType::RealScalar RealScalar; \
+  typedef typename MatrixType::Index Index; \
   typedef ei_kernel_retval_base<DecompositionType> Base; \
   using Base::dec; \
   using Base::rank; \
diff --git a/Eigen/src/misc/Solve.h b/Eigen/src/misc/Solve.h
index 028716a..d6fc674 100644
--- a/Eigen/src/misc/Solve.h
+++ b/Eigen/src/misc/Solve.h
@@ -45,13 +45,15 @@
 {
   typedef typename ei_cleantype<typename Rhs::Nested>::type RhsNestedCleaned;
   typedef _DecompositionType DecompositionType;
+  typedef ReturnByValue<ei_solve_retval_base> Base;
+  typedef typename Base::Index Index;
 
   ei_solve_retval_base(const DecompositionType& dec, const Rhs& rhs)
     : m_dec(dec), m_rhs(rhs)
   {}
 
-  inline int rows() const { return m_dec.cols(); }
-  inline int cols() const { return m_rhs.cols(); }
+  inline Index rows() const { return m_dec.cols(); }
+  inline Index cols() const { return m_rhs.cols(); }
   inline const DecompositionType& dec() const { return m_dec; }
   inline const RhsNestedCleaned& rhs() const { return m_rhs; }
 
@@ -69,6 +71,7 @@
   typedef typename DecompositionType::MatrixType MatrixType; \
   typedef typename MatrixType::Scalar Scalar; \
   typedef typename MatrixType::RealScalar RealScalar; \
+  typedef typename MatrixType::Index Index; \
   typedef ei_solve_retval_base<DecompositionType,Rhs> Base; \
   using Base::dec; \
   using Base::rhs; \
diff --git a/test/array.cpp b/test/array.cpp
index 8006531..df1e1b4 100644
--- a/test/array.cpp
+++ b/test/array.cpp
@@ -127,9 +127,12 @@
 
   // count
   VERIFY(((m1.abs()+1)>RealScalar(0.1)).count() == rows*cols);
+
+  typedef Array<typename ArrayType::Index, Dynamic, 1> ArrayOfIndices;
+  
   // TODO allows colwise/rowwise for array
-  VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).colwise().count(), ArrayXi::Constant(cols,rows).transpose());
-  VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).rowwise().count(), ArrayXi::Constant(rows, cols));
+  VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).colwise().count(), ArrayOfIndices::Constant(cols,rows).transpose());
+  VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).rowwise().count(), ArrayOfIndices::Constant(rows, cols));
 }
 
 template<typename ArrayType> void array_real(const ArrayType& m)
diff --git a/test/array_for_matrix.cpp b/test/array_for_matrix.cpp
index 516c040..477d178 100644
--- a/test/array_for_matrix.cpp
+++ b/test/array_for_matrix.cpp
@@ -124,9 +124,12 @@
 
   // count
   VERIFY(((m1.array().abs()+1)>RealScalar(0.1)).count() == rows*cols);
+
+  typedef Matrix<typename MatrixType::Index, Dynamic, 1> VectorOfIndices;
+
   // TODO allows colwise/rowwise for array
-  VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().colwise().count(), RowVectorXi::Constant(cols,rows));
-  VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().rowwise().count(), VectorXi::Constant(rows, cols));
+  VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().colwise().count(), VectorOfIndices::Constant(cols,rows).transpose());
+  VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().rowwise().count(), VectorOfIndices::Constant(rows, cols));
 }
 
 template<typename VectorType> void lpNorm(const VectorType& v)
diff --git a/test/nomalloc.cpp b/test/nomalloc.cpp
index a80145f..9eb8d13 100644
--- a/test/nomalloc.cpp
+++ b/test/nomalloc.cpp
@@ -133,7 +133,7 @@
 void test_nomalloc()
 {
   // check that our operator new is indeed called:
-  VERIFY_RAISES_ASSERT(MatrixXd dummy = MatrixXd::Random(3,3));
+  VERIFY_RAISES_ASSERT(MatrixXd dummy(MatrixXd::Random(3,3)));
   CALL_SUBTEST_1(nomalloc(Matrix<float, 1, 1>()) );
   CALL_SUBTEST_2(nomalloc(Matrix4d()) );
   CALL_SUBTEST_3(nomalloc(Matrix<float,32,32>()) );
diff --git a/test/qr_colpivoting.cpp b/test/qr_colpivoting.cpp
index a34feed..7064bc2 100644
--- a/test/qr_colpivoting.cpp
+++ b/test/qr_colpivoting.cpp
@@ -38,7 +38,7 @@
   MatrixType m1;
   createRandomPIMatrixOfRank(rank,rows,cols,m1);
   ColPivHouseholderQR<MatrixType> qr(m1);
-  VERIFY_IS_APPROX(rank, qr.rank());
+  VERIFY(rank == qr.rank());
   VERIFY(cols - qr.rank() == qr.dimensionOfKernel());
   VERIFY(!qr.isInjective());
   VERIFY(!qr.isInvertible());
@@ -66,7 +66,7 @@
   Matrix<Scalar,Rows,Cols> m1;
   createRandomPIMatrixOfRank(rank,Rows,Cols,m1);
   ColPivHouseholderQR<Matrix<Scalar,Rows,Cols> > qr(m1);
-  VERIFY_IS_APPROX(rank, qr.rank());
+  VERIFY(rank == qr.rank());
   VERIFY(Cols - qr.rank() == qr.dimensionOfKernel());
   VERIFY(qr.isInjective() == (rank == Rows));
   VERIFY(qr.isSurjective() == (rank == Cols));
diff --git a/test/qr_fullpivoting.cpp b/test/qr_fullpivoting.cpp
index 82c42c7..33350ce 100644
--- a/test/qr_fullpivoting.cpp
+++ b/test/qr_fullpivoting.cpp
@@ -37,7 +37,7 @@
   MatrixType m1;
   createRandomPIMatrixOfRank(rank,rows,cols,m1);
   FullPivHouseholderQR<MatrixType> qr(m1);
-  VERIFY_IS_APPROX(rank, qr.rank());
+  VERIFY(rank == qr.rank());
   VERIFY(cols - qr.rank() == qr.dimensionOfKernel());
   VERIFY(!qr.isInjective());
   VERIFY(!qr.isInvertible());
diff --git a/test/sizeof.cpp b/test/sizeof.cpp
index a724359..779f3b5 100644
--- a/test/sizeof.cpp
+++ b/test/sizeof.cpp
@@ -30,7 +30,7 @@
   if (MatrixType::RowsAtCompileTime!=Dynamic && MatrixType::ColsAtCompileTime!=Dynamic)
     VERIFY(sizeof(MatrixType)==sizeof(Scalar)*MatrixType::SizeAtCompileTime);
   else
-    VERIFY(sizeof(MatrixType)==sizeof(Scalar*) + 2 * sizeof(int));
+    VERIFY(sizeof(MatrixType)==sizeof(Scalar*) + 2 * sizeof(typename MatrixType::Index));
 }
 
 void test_sizeof()
diff --git a/test/visitor.cpp b/test/visitor.cpp
index 65ee60b..1ddabc6 100644
--- a/test/visitor.cpp
+++ b/test/visitor.cpp
@@ -27,22 +27,23 @@
 template<typename MatrixType> void matrixVisitor(const MatrixType& p)
 {
   typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::Index Index;
 
-  int rows = p.rows();
-  int cols = p.cols();
+  Index rows = p.rows();
+  Index cols = p.cols();
 
   // construct a random matrix where all coefficients are different
   MatrixType m;
   m = MatrixType::Random(rows, cols);
-  for(int i = 0; i < m.size(); i++)
-    for(int i2 = 0; i2 < i; i2++)
+  for(Index i = 0; i < m.size(); i++)
+    for(Index i2 = 0; i2 < i; i2++)
       while(m(i) == m(i2)) // yes, ==
         m(i) = ei_random<Scalar>();
   
   Scalar minc = Scalar(1000), maxc = Scalar(-1000);
-  int minrow=0,mincol=0,maxrow=0,maxcol=0;
-  for(int j = 0; j < cols; j++)
-  for(int i = 0; i < rows; i++)
+  Index minrow=0,mincol=0,maxrow=0,maxcol=0;
+  for(Index j = 0; j < cols; j++)
+  for(Index i = 0; i < rows; i++)
   {
     if(m(i,j) < minc)
     {
@@ -57,7 +58,7 @@
       maxcol = j;
     }
   }
-  int eigen_minrow, eigen_mincol, eigen_maxrow, eigen_maxcol;
+  Index eigen_minrow, eigen_mincol, eigen_maxrow, eigen_maxcol;
   Scalar eigen_minc, eigen_maxc;
   eigen_minc = m.minCoeff(&eigen_minrow,&eigen_mincol);
   eigen_maxc = m.maxCoeff(&eigen_maxrow,&eigen_maxcol);
@@ -74,20 +75,21 @@
 template<typename VectorType> void vectorVisitor(const VectorType& w)
 {
   typedef typename VectorType::Scalar Scalar;
+  typedef typename VectorType::Index Index;
 
-  int size = w.size();
+  Index size = w.size();
 
   // construct a random vector where all coefficients are different
   VectorType v;
   v = VectorType::Random(size);
-  for(int i = 0; i < size; i++)
-    for(int i2 = 0; i2 < i; i2++)
+  for(Index i = 0; i < size; i++)
+    for(Index i2 = 0; i2 < i; i2++)
       while(v(i) == v(i2)) // yes, ==
         v(i) = ei_random<Scalar>();
   
   Scalar minc = Scalar(1000), maxc = Scalar(-1000);
-  int minidx=0,maxidx=0;
-  for(int i = 0; i < size; i++)
+  Index minidx=0,maxidx=0;
+  for(Index i = 0; i < size; i++)
   {
     if(v(i) < minc)
     {
@@ -100,7 +102,7 @@
       maxidx = i;
     }
   }
-  int eigen_minidx, eigen_maxidx;
+  Index eigen_minidx, eigen_maxidx;
   Scalar eigen_minc, eigen_maxc;
   eigen_minc = v.minCoeff(&eigen_minidx);
   eigen_maxc = v.maxCoeff(&eigen_maxidx);
diff --git a/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h b/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h
index b3983f8..6a6516c 100644
--- a/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h
+++ b/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h
@@ -51,6 +51,7 @@
   typedef typename Functor::ValueType ValueType;
   typedef typename Functor::JacobianType JacobianType;
   typedef typename JacobianType::Scalar Scalar;
+  typedef typename JacobianType::Index Index;
 
   typedef Matrix<Scalar,InputsAtCompileTime,1> DerivativeType;
   typedef AutoDiffScalar<DerivativeType> ActiveScalar;
@@ -74,15 +75,15 @@
     ActiveValue av(jac.rows());
 
     if(InputsAtCompileTime==Dynamic)
-      for (int j=0; j<jac.rows(); j++)
+      for (Index j=0; j<jac.rows(); j++)
         av[j].derivatives().resize(this->inputs());
 
-    for (int i=0; i<jac.cols(); i++)
+    for (Index i=0; i<jac.cols(); i++)
       ax[i].derivatives() = DerivativeType::Unit(this->inputs(),i);
 
     Functor::operator()(ax, &av);
 
-    for (int i=0; i<jac.rows(); i++)
+    for (Index i=0; i<jac.rows(); i++)
     {
       (*v)[i] = av[i].value();
       jac.row(i) = av[i].derivatives();
diff --git a/unsupported/Eigen/src/AutoDiff/AutoDiffVector.h b/unsupported/Eigen/src/AutoDiff/AutoDiffVector.h
index c0765d4..9b9dbcc 100644
--- a/unsupported/Eigen/src/AutoDiff/AutoDiffVector.h
+++ b/unsupported/Eigen/src/AutoDiff/AutoDiffVector.h
@@ -53,6 +53,7 @@
     typedef AutoDiffScalar<Matrix<BaseScalar,JacobianType::RowsAtCompileTime,1> > ActiveScalar;
     typedef ActiveScalar Scalar;
     typedef AutoDiffScalar<typename JacobianType::ColXpr> CoeffType;
+    typedef typename JacobianType::Index Index;
 
     inline AutoDiffVector() {}
 
@@ -63,16 +64,16 @@
     }
 
 
-    CoeffType operator[] (int i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
-    const CoeffType operator[] (int i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
+    CoeffType operator[] (Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
+    const CoeffType operator[] (Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
 
-    CoeffType operator() (int i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
-    const CoeffType operator() (int i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
+    CoeffType operator() (Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
+    const CoeffType operator() (Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
 
-    CoeffType coeffRef(int i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
-    const CoeffType coeffRef(int i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
+    CoeffType coeffRef(Index i) { return CoeffType(m_values[i], m_jacobian.col(i)); }
+    const CoeffType coeffRef(Index i) const { return CoeffType(m_values[i], m_jacobian.col(i)); }
 
-    int size() const { return m_values.size(); }
+    Index size() const { return m_values.size(); }
 
     // FIXME here we could return an expression of the sum
     Scalar sum() const { /*std::cerr << "sum \n\n";*/ /*std::cerr << m_jacobian.rowwise().sum() << "\n\n";*/ return Scalar(m_values.sum(), m_jacobian.rowwise().sum()); }
diff --git a/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h b/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h
index c2b7763..8f2a353 100644
--- a/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h
+++ b/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h
@@ -61,17 +61,18 @@
 {
   // optimisable : copie de la ligne, precalcul de C * trans(C).
   typedef typename CMatrix::Scalar Scalar;
+  typedef typename CMatrix::Index Index;
   // FIXME use sparse vectors ?
   typedef Matrix<Scalar,Dynamic,1> TmpVec;
 
-  int rows = C.rows(), cols = C.cols();
+  Index rows = C.rows(), cols = C.cols();
 
   TmpVec d(rows), e(rows), l(cols), p(rows), q(rows), r(rows);
   Scalar rho, rho_1, alpha;
   d.setZero();
 
   CINV.startFill(); // FIXME estimate the number of non-zeros
-  for (int i = 0; i < rows; ++i)
+  for (Index i = 0; i < rows; ++i)
   {
     d[i] = 1.0;
     rho = 1.0;
@@ -94,7 +95,7 @@
 
     l = C.transpose() * e; // l is the i-th row of CINV
     // FIXME add a generic "prune/filter" expression for both dense and sparse object to sparse
-    for (int j=0; j<l.size(); ++j)
+    for (Index j=0; j<l.size(); ++j)
       if (l[j]<1e-15)
         CINV.fill(i,j) = l[j];
 
@@ -116,10 +117,11 @@
                        const VectorB& b, const VectorF& f, IterationController &iter)
 {
   typedef typename TMatrix::Scalar Scalar;
+  typedef typename TMatrix::Index Index;
   typedef Matrix<Scalar,Dynamic,1>  TmpVec;
 
   Scalar rho = 1.0, rho_1, lambda, gamma;
-  int xSize = x.size();
+  Index xSize = x.size();
   TmpVec  p(xSize), q(xSize), q2(xSize),
           r(xSize), old_z(xSize), z(xSize),
           memox(xSize);
@@ -140,7 +142,7 @@
     r += A * -x;
     z = r;
     bool transition = false;
-    for (int i = 0; i < C.rows(); ++i)
+    for (Index i = 0; i < C.rows(); ++i)
     {
       Scalar al = C.row(i).dot(x) - f.coeff(i);
       if (al >= -1.0E-15)
@@ -175,7 +177,7 @@
     // one dimensionnal optimization
     q = A * p;
     lambda = rho / q.dot(p);
-    for (int i = 0; i < C.rows(); ++i)
+    for (Index i = 0; i < C.rows(); ++i)
     {
       if (!satured[i])
       {
diff --git a/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h b/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
index d7eb1b2..5d47f2c 100644
--- a/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
+++ b/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
@@ -296,6 +296,7 @@
 template<typename Derived> struct MatrixExponentialReturnValue
 : public ReturnByValue<MatrixExponentialReturnValue<Derived> >
 {
+    typedef typename Derived::Index Index;
   public:
     /** \brief Constructor.
       *
@@ -317,8 +318,8 @@
       me.compute(result);
     }
 
-    int rows() const { return m_src.rows(); }
-    int cols() const { return m_src.cols(); }
+    Index rows() const { return m_src.rows(); }
+    Index cols() const { return m_src.cols(); }
 
   protected:
     const Derived& m_src;
diff --git a/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h b/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
index 8ed8567..be27c50 100644
--- a/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
+++ b/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
@@ -131,14 +131,15 @@
   private:
 
     typedef ei_traits<MatrixType> Traits;
-    typedef typename Traits::Scalar Scalar;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::Index Index;
     static const int RowsAtCompileTime = Traits::RowsAtCompileTime;
     static const int ColsAtCompileTime = Traits::ColsAtCompileTime;
     static const int Options = MatrixType::Options;
     typedef typename NumTraits<Scalar>::Real RealScalar;
     typedef typename ei_stem_function<Scalar>::type StemFunction;
     typedef Matrix<Scalar, Traits::RowsAtCompileTime, 1> VectorType;
-    typedef Matrix<int, Traits::RowsAtCompileTime, 1> IntVectorType;
+    typedef Matrix<Index, Traits::RowsAtCompileTime, 1> IntVectorType;
     typedef std::list<Scalar> Cluster;
     typedef std::list<Cluster> ListOfClusters;
     typedef Matrix<Scalar, Dynamic, Dynamic, Options, RowsAtCompileTime, ColsAtCompileTime> DynMatrixType;
@@ -157,9 +158,9 @@
     void computeBlockStart();
     void constructPermutation();
     void permuteSchur();
-    void swapEntriesInSchur(int index);
+    void swapEntriesInSchur(Index index);
     void computeBlockAtomic();
-    Block<MatrixType> block(const MatrixType& A, int i, int j);
+    Block<MatrixType> block(const MatrixType& A, Index i, Index j);
     void computeOffDiagonal();
     DynMatrixType solveTriangularSylvester(const DynMatrixType& A, const DynMatrixType& B, const DynMatrixType& C);
 
@@ -238,10 +239,10 @@
 template <typename MatrixType>
 void MatrixFunction<MatrixType,1>::partitionEigenvalues()
 {
-  const int rows = m_T.rows();
+  const Index rows = m_T.rows();
   VectorType diag = m_T.diagonal(); // contains eigenvalues of A
 
-  for (int i=0; i<rows; ++i) {
+  for (Index i=0; i<rows; ++i) {
     // Find set containing diag(i), adding a new set if necessary
     typename ListOfClusters::iterator qi = findCluster(diag(i));
     if (qi == m_clusters.end()) {
@@ -253,7 +254,7 @@
     }
 
     // Look for other element to add to the set
-    for (int j=i+1; j<rows; ++j) {
+    for (Index j=i+1; j<rows; ++j) {
       if (ei_abs(diag(j) - diag(i)) <= separation() && std::find(qi->begin(), qi->end(), diag(j)) == qi->end()) {
 	typename ListOfClusters::iterator qj = findCluster(diag(j));
 	if (qj == m_clusters.end()) {
@@ -288,15 +289,15 @@
 template <typename MatrixType>
 void MatrixFunction<MatrixType,1>::computeClusterSize()
 {
-  const int rows = m_T.rows();
+  const Index rows = m_T.rows();
   VectorType diag = m_T.diagonal(); 
-  const int numClusters = static_cast<int>(m_clusters.size());
+  const Index numClusters = static_cast<Index>(m_clusters.size());
 
   m_clusterSize.setZero(numClusters);
   m_eivalToCluster.resize(rows);
-  int clusterIndex = 0;
+  Index clusterIndex = 0;
   for (typename ListOfClusters::const_iterator cluster = m_clusters.begin(); cluster != m_clusters.end(); ++cluster) {
-    for (int i = 0; i < diag.rows(); ++i) {
+    for (Index i = 0; i < diag.rows(); ++i) {
       if (std::find(cluster->begin(), cluster->end(), diag(i)) != cluster->end()) {
 	++m_clusterSize[clusterIndex];
 	m_eivalToCluster[i] = clusterIndex;
@@ -312,7 +313,7 @@
 {
   m_blockStart.resize(m_clusterSize.rows());
   m_blockStart(0) = 0;
-  for (int i = 1; i < m_clusterSize.rows(); i++) {
+  for (Index i = 1; i < m_clusterSize.rows(); i++) {
     m_blockStart(i) = m_blockStart(i-1) + m_clusterSize(i-1);
   }
 }
@@ -323,8 +324,8 @@
 {
   VectorXi indexNextEntry = m_blockStart;
   m_permutation.resize(m_T.rows());
-  for (int i = 0; i < m_T.rows(); i++) {
-    int cluster = m_eivalToCluster[i];
+  for (Index i = 0; i < m_T.rows(); i++) {
+    Index cluster = m_eivalToCluster[i];
     m_permutation[i] = indexNextEntry[cluster];
     ++indexNextEntry[cluster];
   }
@@ -335,13 +336,13 @@
 void MatrixFunction<MatrixType,1>::permuteSchur()
 {
   IntVectorType p = m_permutation;
-  for (int i = 0; i < p.rows() - 1; i++) {
-    int j;
+  for (Index i = 0; i < p.rows() - 1; i++) {
+    Index j;
     for (j = i; j < p.rows(); j++) {
       if (p(j) == i) break;
     }
     ei_assert(p(j) == i);
-    for (int k = j-1; k >= i; k--) {
+    for (Index k = j-1; k >= i; k--) {
       swapEntriesInSchur(k);
       std::swap(p.coeffRef(k), p.coeffRef(k+1));
     }
@@ -350,7 +351,7 @@
 
 /** \brief Swap rows \a index and \a index+1 in Schur decomposition in #m_U and #m_T */
 template <typename MatrixType>
-void MatrixFunction<MatrixType,1>::swapEntriesInSchur(int index)
+void MatrixFunction<MatrixType,1>::swapEntriesInSchur(Index index)
 {
   PlanarRotation<Scalar> rotation;
   rotation.makeGivens(m_T(index, index+1), m_T(index+1, index+1) - m_T(index, index));
@@ -372,14 +373,14 @@
   m_fT.resize(m_T.rows(), m_T.cols());
   m_fT.setZero();
   MatrixFunctionAtomic<DynMatrixType> mfa(m_f);
-  for (int i = 0; i < m_clusterSize.rows(); ++i) {
+  for (Index i = 0; i < m_clusterSize.rows(); ++i) {
     block(m_fT, i, i) = mfa.compute(block(m_T, i, i));
   }
 }
 
 /** \brief Return block of matrix according to blocking given by #m_blockStart */
 template <typename MatrixType>
-Block<MatrixType> MatrixFunction<MatrixType,1>::block(const MatrixType& A, int i, int j)
+Block<MatrixType> MatrixFunction<MatrixType,1>::block(const MatrixType& A, Index i, Index j)
 {
   return A.block(m_blockStart(i), m_blockStart(j), m_clusterSize(i), m_clusterSize(j));
 }
@@ -394,14 +395,14 @@
 template <typename MatrixType>
 void MatrixFunction<MatrixType,1>::computeOffDiagonal()
 { 
-  for (int diagIndex = 1; diagIndex < m_clusterSize.rows(); diagIndex++) {
-    for (int blockIndex = 0; blockIndex < m_clusterSize.rows() - diagIndex; blockIndex++) {
+  for (Index diagIndex = 1; diagIndex < m_clusterSize.rows(); diagIndex++) {
+    for (Index blockIndex = 0; blockIndex < m_clusterSize.rows() - diagIndex; blockIndex++) {
       // compute (blockIndex, blockIndex+diagIndex) block
       DynMatrixType A = block(m_T, blockIndex, blockIndex);
       DynMatrixType B = -block(m_T, blockIndex+diagIndex, blockIndex+diagIndex);
       DynMatrixType C = block(m_fT, blockIndex, blockIndex) * block(m_T, blockIndex, blockIndex+diagIndex);
       C -= block(m_T, blockIndex, blockIndex+diagIndex) * block(m_fT, blockIndex+diagIndex, blockIndex+diagIndex);
-      for (int k = blockIndex + 1; k < blockIndex + diagIndex; k++) {
+      for (Index k = blockIndex + 1; k < blockIndex + diagIndex; k++) {
 	C += block(m_fT, blockIndex, k) * block(m_T, k, blockIndex+diagIndex);
 	C -= block(m_T, blockIndex, k) * block(m_fT, k, blockIndex+diagIndex);
       }
@@ -446,12 +447,12 @@
   ei_assert(C.rows() == A.rows());
   ei_assert(C.cols() == B.rows());
 
-  int m = A.rows();
-  int n = B.rows();
+  Index m = A.rows();
+  Index n = B.rows();
   DynMatrixType X(m, n);
 
-  for (int i = m - 1; i >= 0; --i) {
-    for (int j = 0; j < n; ++j) {
+  for (Index i = m - 1; i >= 0; --i) {
+    for (Index j = 0; j < n; ++j) {
 
       // Compute AX = \sum_{k=i+1}^m A_{ik} X_{kj}
       Scalar AX;
@@ -494,7 +495,8 @@
 {
   public:
 
-    typedef typename ei_traits<Derived>::Scalar Scalar;
+    typedef typename Derived::Scalar Scalar;
+    typedef typename Derived::Index Index;
     typedef typename ei_stem_function<Scalar>::type StemFunction;
 
    /** \brief Constructor.
@@ -518,8 +520,8 @@
       mf.compute(result);
     }
 
-    int rows() const { return m_A.rows(); }
-    int cols() const { return m_A.cols(); }
+    Index rows() const { return m_A.rows(); }
+    Index cols() const { return m_A.cols(); }
 
   private:
     const Derived& m_A;
diff --git a/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h b/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h
index 4bcae47..b578c13 100644
--- a/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h
+++ b/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h
@@ -38,11 +38,11 @@
 {
   public:
 
-    typedef ei_traits<MatrixType> Traits;
-    typedef typename Traits::Scalar Scalar;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::Index Index;
     typedef typename NumTraits<Scalar>::Real RealScalar;
     typedef typename ei_stem_function<Scalar>::type StemFunction;
-    typedef Matrix<Scalar, Traits::RowsAtCompileTime, 1> VectorType;
+    typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
 
     /** \brief Constructor
       * \param[in]  f  matrix function to compute.
@@ -62,13 +62,13 @@
     MatrixFunctionAtomic& operator=(const MatrixFunctionAtomic&);
 
     void computeMu();
-    bool taylorConverged(int s, const MatrixType& F, const MatrixType& Fincr, const MatrixType& P);
+    bool taylorConverged(Index s, const MatrixType& F, const MatrixType& Fincr, const MatrixType& P);
 
     /** \brief Pointer to scalar function */
     StemFunction* m_f;
 
     /** \brief Size of matrix function */
-    int m_Arows;
+    Index m_Arows;
 
     /** \brief Mean of eigenvalues */
     Scalar m_avgEival;
@@ -91,7 +91,7 @@
   MatrixType F = m_f(m_avgEival, 0) * MatrixType::Identity(m_Arows, m_Arows);
   MatrixType P = m_Ashifted;
   MatrixType Fincr;
-  for (int s = 1; s < 1.1 * m_Arows + 10; s++) { // upper limit is fairly arbitrary
+  for (Index s = 1; s < 1.1 * m_Arows + 10; s++) { // upper limit is fairly arbitrary
     Fincr = m_f(m_avgEival, s) * P;
     F += Fincr;
     P = Scalar(RealScalar(1.0/(s + 1))) * P * m_Ashifted;
@@ -115,18 +115,18 @@
 
 /** \brief Determine whether Taylor series has converged */
 template <typename MatrixType>
-bool MatrixFunctionAtomic<MatrixType>::taylorConverged(int s, const MatrixType& F,
+bool MatrixFunctionAtomic<MatrixType>::taylorConverged(Index s, const MatrixType& F,
 						       const MatrixType& Fincr, const MatrixType& P)
 {
-  const int n = F.rows();
+  const Index n = F.rows();
   const RealScalar F_norm = F.cwiseAbs().rowwise().sum().maxCoeff();
   const RealScalar Fincr_norm = Fincr.cwiseAbs().rowwise().sum().maxCoeff();
   if (Fincr_norm < NumTraits<Scalar>::epsilon() * F_norm) {
     RealScalar delta = 0;
     RealScalar rfactorial = 1;
-    for (int r = 0; r < n; r++) {
+    for (Index r = 0; r < n; r++) {
       RealScalar mx = 0;
-      for (int i = 0; i < n; i++)
+      for (Index i = 0; i < n; i++)
         mx = std::max(mx, std::abs(m_f(m_Ashifted(i, i) + m_avgEival, s+r)));
       if (r != 0)
         rfactorial *= RealScalar(r);
diff --git a/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h b/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
index d75b140..aba31b2 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
@@ -56,6 +56,8 @@
 class HybridNonLinearSolver
 {
 public:
+    typedef DenseIndex Index;
+
     HybridNonLinearSolver(FunctorType &_functor)
         : functor(_functor) { nfev=njev=iter = 0;  fnorm= 0.; useExternalScaling=false;}
 
@@ -68,10 +70,10 @@
             , nb_of_superdiagonals(-1)
             , epsfcn(Scalar(0.)) {}
         Scalar factor;
-        int maxfev;   // maximum number of function evaluation
+        Index maxfev;   // maximum number of function evaluation
         Scalar xtol;
-        int nb_of_subdiagonals;
-        int nb_of_superdiagonals;
+        Index nb_of_subdiagonals;
+        Index nb_of_superdiagonals;
         Scalar epsfcn;
     };
     typedef Matrix< Scalar, Dynamic, 1 > FVectorType;
@@ -102,24 +104,24 @@
     FVectorType  fvec, qtf, diag;
     JacobianType fjac;
     UpperTriangularType R;
-    int nfev;
-    int njev;
-    int iter;
+    Index nfev;
+    Index njev;
+    Index iter;
     Scalar fnorm;
     bool useExternalScaling; 
 private:
     FunctorType &functor;
-    int n;
+    Index n;
     Scalar sum;
     bool sing;
     Scalar temp;
     Scalar delta;
     bool jeval;
-    int ncsuc;
+    Index ncsuc;
     Scalar ratio;
     Scalar pnorm, xnorm, fnorm1;
-    int nslow1, nslow2;
-    int ncfail;
+    Index nslow1, nslow2;
+    Index ncfail;
     Scalar actred, prered;
     FVectorType wa1, wa2, wa3, wa4;
 };
@@ -169,7 +171,7 @@
     if (n <= 0 || parameters.xtol < 0. || parameters.maxfev <= 0 || parameters.factor <= 0. )
         return HybridNonLinearSolverSpace::ImproperInputParameters;
     if (useExternalScaling)
-        for (int j = 0; j < n; ++j)
+        for (Index j = 0; j < n; ++j)
             if (diag[j] <= 0.)
                 return HybridNonLinearSolverSpace::ImproperInputParameters;
 
@@ -196,7 +198,7 @@
 {
     assert(x.size()==n); // check the caller is not cheating us
 
-    int j;
+    Index j;
     std::vector<PlanarRotation<Scalar> > v_givens(n), w_givens(n);
 
     jeval = true;
@@ -408,7 +410,7 @@
     if (n <= 0 || parameters.xtol < 0. || parameters.maxfev <= 0 || parameters.nb_of_subdiagonals< 0 || parameters.nb_of_superdiagonals< 0 || parameters.factor <= 0. )
         return HybridNonLinearSolverSpace::ImproperInputParameters;
     if (useExternalScaling)
-        for (int j = 0; j < n; ++j)
+        for (Index j = 0; j < n; ++j)
             if (diag[j] <= 0.)
                 return HybridNonLinearSolverSpace::ImproperInputParameters;
 
@@ -435,7 +437,7 @@
 {
     assert(x.size()==n); // check the caller is not cheating us
 
-    int j;
+    Index j;
     std::vector<PlanarRotation<Scalar> > v_givens(n), w_givens(n);
 
     jeval = true;
diff --git a/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h b/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
index 3d5b6ea..63eb667 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
@@ -63,6 +63,8 @@
     LevenbergMarquardt(FunctorType &_functor)
         : functor(_functor) { nfev = njev = iter = 0;  fnorm = gnorm = 0.; useExternalScaling=false; }
 
+    typedef DenseIndex Index;
+
     struct Parameters {
         Parameters()
             : factor(Scalar(100.))
@@ -72,7 +74,7 @@
             , gtol(Scalar(0.))
             , epsfcn(Scalar(0.)) {}
         Scalar factor;
-        int maxfev;   // maximum number of function evaluation
+        Index maxfev;   // maximum number of function evaluation
         Scalar ftol;
         Scalar xtol;
         Scalar gtol;
@@ -94,7 +96,7 @@
     static LevenbergMarquardtSpace::Status lmdif1(
             FunctorType &functor,
             FVectorType &x,
-            int *nfev,
+            Index *nfev,
             const Scalar tol = ei_sqrt(NumTraits<Scalar>::epsilon())
             );
 
@@ -113,17 +115,17 @@
     FVectorType  fvec, qtf, diag;
     JacobianType fjac;
     PermutationMatrix<Dynamic,Dynamic> permutation;
-    int nfev;
-    int njev;
-    int iter;
+    Index nfev;
+    Index njev;
+    Index iter;
     Scalar fnorm, gnorm;
     bool useExternalScaling; 
 
     Scalar lm_param(void) { return par; }
 private:
     FunctorType &functor;
-    int n;
-    int m;
+    Index n;
+    Index m;
     FVectorType wa1, wa2, wa3, wa4;
 
     Scalar par, sum;
@@ -194,7 +196,7 @@
         return LevenbergMarquardtSpace::ImproperInputParameters;
 
     if (useExternalScaling)
-        for (int j = 0; j < n; ++j)
+        for (Index j = 0; j < n; ++j)
             if (diag[j] <= 0.)
                 return LevenbergMarquardtSpace::ImproperInputParameters;
 
@@ -219,7 +221,7 @@
     assert(x.size()==n); // check the caller is not cheating us
 
     /* calculate the jacobian matrix. */
-    int df_ret = functor.df(x, fjac);
+    Index df_ret = functor.df(x, fjac);
     if (df_ret<0)
         return LevenbergMarquardtSpace::UserAsked;
     if (df_ret>0)
@@ -237,7 +239,7 @@
     /* to the norms of the columns of the initial jacobian. */
     if (iter == 1) {
         if (!useExternalScaling)
-            for (int j = 0; j < n; ++j)
+            for (Index j = 0; j < n; ++j)
                 diag[j] = (wa2[j]==0.)? 1. : wa2[j];
 
         /* on the first iteration, calculate the norm of the scaled x */
@@ -257,7 +259,7 @@
     /* compute the norm of the scaled gradient. */
     gnorm = 0.;
     if (fnorm != 0.)
-        for (int j = 0; j < n; ++j)
+        for (Index j = 0; j < n; ++j)
             if (wa2[permutation.indices()[j]] != 0.)
                 gnorm = std::max(gnorm, ei_abs( fjac.col(j).head(j+1).dot(qtf.head(j+1)/fnorm) / wa2[permutation.indices()[j]]));
 
@@ -410,7 +412,7 @@
         return LevenbergMarquardtSpace::ImproperInputParameters;
 
     if (useExternalScaling)
-        for (int j = 0; j < n; ++j)
+        for (Index j = 0; j < n; ++j)
             if (diag[j] <= 0.)
                 return LevenbergMarquardtSpace::ImproperInputParameters;
 
@@ -435,7 +437,7 @@
 {
     assert(x.size()==n); // check the caller is not cheating us
 
-    int i, j;
+    Index i, j;
     bool sing;
 
     /* compute the qr factorization of the jacobian matrix */
@@ -444,7 +446,7 @@
     /* n components in qtf. */
     qtf.fill(0.);
     fjac.fill(0.);
-    int rownb = 2;
+    Index rownb = 2;
     for (i = 0; i < m; ++i) {
         if (functor.df(x, wa3, rownb) < 0) return LevenbergMarquardtSpace::UserAsked;
         ei_rwupdt<Scalar>(fjac, wa3, qtf, fvec[i]);
@@ -471,7 +473,7 @@
         fjac.diagonal() = qrfac.hCoeffs();
         permutation = qrfac.colsPermutation();
         // TODO : avoid this:
-        for(int ii=0; ii< fjac.cols(); ii++) fjac.col(ii).segment(ii+1, fjac.rows()-ii-1) *= fjac(ii,ii); // rescale vectors
+        for(Index ii=0; ii< fjac.cols(); ii++) fjac.col(ii).segment(ii+1, fjac.rows()-ii-1) *= fjac(ii,ii); // rescale vectors
 
         for (j = 0; j < n; ++j) {
             if (fjac(j,j) != 0.) {
@@ -623,12 +625,12 @@
 LevenbergMarquardt<FunctorType,Scalar>::lmdif1(
         FunctorType &functor,
         FVectorType  &x,
-        int *nfev,
+        Index *nfev,
         const Scalar tol
         )
 {
-    int n = x.size();
-    int m = functor.values();
+    Index n = x.size();
+    Index m = functor.values();
 
     /* check the input parameters for errors. */
     if (n <= 0 || m < n || tol < 0.)
diff --git a/unsupported/Eigen/src/NonLinearOptimization/chkder.h b/unsupported/Eigen/src/NonLinearOptimization/chkder.h
index 591e8be..4cb4fbd 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/chkder.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/chkder.h
@@ -13,17 +13,19 @@
         Matrix< Scalar, Dynamic, 1 >  &err
         )
 {
+    typedef DenseIndex Index;
+
     const Scalar eps = ei_sqrt(NumTraits<Scalar>::epsilon());
     const Scalar epsf = chkder_factor * NumTraits<Scalar>::epsilon();
     const Scalar epslog = chkder_log10e * ei_log(eps);
     Scalar temp;
 
-    const int m = fvec.size(), n = x.size();
+    const Index m = fvec.size(), n = x.size();
 
     if (mode != 2) {
         /* mode = 1. */
         xp.resize(n);
-        for (int j = 0; j < n; ++j) {
+        for (Index j = 0; j < n; ++j) {
             temp = eps * ei_abs(x[j]);
             if (temp == 0.)
                 temp = eps;
@@ -33,13 +35,13 @@
     else {
         /* mode = 2. */
         err.setZero(m); 
-        for (int j = 0; j < n; ++j) {
+        for (Index j = 0; j < n; ++j) {
             temp = ei_abs(x[j]);
             if (temp == 0.)
                 temp = 1.;
             err += temp * fjac.col(j);
         }
-        for (int i = 0; i < m; ++i) {
+        for (Index i = 0; i < m; ++i) {
             temp = 1.;
             if (fvec[i] != 0. && fvecp[i] != 0. && ei_abs(fvecp[i] - fvec[i]) >= epsf * ei_abs(fvec[i]))
                 temp = eps * ei_abs((fvecp[i] - fvec[i]) / eps - err[i]) / (ei_abs(fvec[i]) + ei_abs(fvecp[i]));
diff --git a/unsupported/Eigen/src/NonLinearOptimization/covar.h b/unsupported/Eigen/src/NonLinearOptimization/covar.h
index 7cfaa22..104898a 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/covar.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/covar.h
@@ -5,13 +5,15 @@
         const VectorXi &ipvt,
         Scalar tol = ei_sqrt(NumTraits<Scalar>::epsilon()) )
 {
+    typedef DenseIndex Index;
+
     /* Local variables */
-    int i, j, k, l, ii, jj;
-    int sing;
+    Index i, j, k, l, ii, jj;
+    bool sing;
     Scalar temp;
 
     /* Function Body */
-    const int n = r.cols();
+    const Index n = r.cols();
     const Scalar tolr = tol * ei_abs(r(0,0));
     Matrix< Scalar, Dynamic, 1 > wa(n);
     assert(ipvt.size()==n);
diff --git a/unsupported/Eigen/src/NonLinearOptimization/dogleg.h b/unsupported/Eigen/src/NonLinearOptimization/dogleg.h
index 9c1d38d..ab01d5c 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/dogleg.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/dogleg.h
@@ -7,15 +7,17 @@
         Scalar delta,
         Matrix< Scalar, Dynamic, 1 >  &x)
 {
+    typedef DenseIndex Index;
+
     /* Local variables */
-    int i, j;
+    Index i, j;
     Scalar sum, temp, alpha, bnorm;
     Scalar gnorm, qnorm;
     Scalar sgnorm;
 
     /* Function Body */
     const Scalar epsmch = NumTraits<Scalar>::epsilon();
-    const int n = qrfac.cols();
+    const Index n = qrfac.cols();
     assert(n==qtb.size());
     assert(n==x.size());
     assert(n==diag.size());
diff --git a/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h b/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h
index 3dc1e80..74cf53b 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h
@@ -1,24 +1,26 @@
 
 template<typename FunctorType, typename Scalar>
-int ei_fdjac1(
+DenseIndex ei_fdjac1(
         const FunctorType &Functor,
         Matrix< Scalar, Dynamic, 1 >  &x,
         Matrix< Scalar, Dynamic, 1 >  &fvec,
         Matrix< Scalar, Dynamic, Dynamic > &fjac,
-        int ml, int mu,
+        DenseIndex ml, DenseIndex mu,
         Scalar epsfcn)
 {
+    typedef DenseIndex Index;
+
     /* Local variables */
     Scalar h;
-    int j, k;
+    Index j, k;
     Scalar eps, temp;
-    int msum;
+    Index msum;
     int iflag;
-    int start, length;
+    Index start, length;
 
     /* Function Body */
     const Scalar epsmch = NumTraits<Scalar>::epsilon();
-    const int n = x.size();
+    const Index n = x.size();
     assert(fvec.size()==n);
     Matrix< Scalar, Dynamic, 1 >  wa1(n);
     Matrix< Scalar, Dynamic, 1 >  wa2(n);
@@ -57,7 +59,7 @@
                 h = eps * ei_abs(wa2[j]);
                 if (h == 0.) h = eps;
                 fjac.col(j).setZero();
-                start = std::max(0,j-mu);
+                start = std::max<Index>(0,j-mu);
                 length = std::min(n-1, j+ml) - start + 1;
                 fjac.col(j).segment(start, length) = ( wa1.segment(start, length)-fvec.segment(start, length))/h;
             }
diff --git a/unsupported/Eigen/src/NonLinearOptimization/lmpar.h b/unsupported/Eigen/src/NonLinearOptimization/lmpar.h
index 8500119..27138de 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/lmpar.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/lmpar.h
@@ -9,11 +9,13 @@
         Scalar &par,
         Matrix< Scalar, Dynamic, 1 >  &x)
 {
+    typedef DenseIndex Index;
+
     /* Local variables */
-    int i, j, l;
+    Index i, j, l;
     Scalar fp;
     Scalar parc, parl;
-    int iter;
+    Index iter;
     Scalar temp, paru;
     Scalar gnorm;
     Scalar dxnorm;
@@ -21,7 +23,7 @@
 
     /* Function Body */
     const Scalar dwarf = std::numeric_limits<Scalar>::min();
-    const int n = r.cols();
+    const Index n = r.cols();
     assert(n==diag.size());
     assert(n==qtb.size());
     assert(n==x.size());
@@ -30,7 +32,7 @@
 
     /* compute and store in x the gauss-newton direction. if the */
     /* jacobian is rank-deficient, obtain a least squares solution. */
-    int nsing = n-1;
+    Index nsing = n-1;
     wa1 = qtb;
     for (j = 0; j < n; ++j) {
         if (r(j,j) == 0. && nsing == n-1)
@@ -163,11 +165,13 @@
         Matrix< Scalar, Dynamic, 1 >  &x)
 
 {
+    typedef DenseIndex Index;
+
     /* Local variables */
-    int j;
+    Index j;
     Scalar fp;
     Scalar parc, parl;
-    int iter;
+    Index iter;
     Scalar temp, paru;
     Scalar gnorm;
     Scalar dxnorm;
@@ -175,7 +179,7 @@
 
     /* Function Body */
     const Scalar dwarf = std::numeric_limits<Scalar>::min();
-    const int n = qr.matrixQR().cols();
+    const Index n = qr.matrixQR().cols();
     assert(n==diag.size());
     assert(n==qtb.size());
 
@@ -184,8 +188,8 @@
     /* compute and store in x the gauss-newton direction. if the */
     /* jacobian is rank-deficient, obtain a least squares solution. */
 
-//    const int rank = qr.nonzeroPivots(); // exactly double(0.)
-    const int rank = qr.rank(); // use a threshold
+//    const Index rank = qr.nonzeroPivots(); // exactly double(0.)
+    const Index rank = qr.rank(); // use a threshold
     wa1 = qtb;
     wa1.tail(n-rank).setZero();
     qr.matrixQR().topLeftCorner(rank, rank).template triangularView<Upper>().solveInPlace(wa1.head(rank));
@@ -262,7 +266,7 @@
         for (j = 0; j < n; ++j) {
             wa1[j] /= sdiag[j];
             temp = wa1[j];
-            for (int i = j+1; i < n; ++i)
+            for (Index i = j+1; i < n; ++i)
                 wa1[i] -= s(i,j) * temp;
         }
         temp = wa1.blueNorm();
diff --git a/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h b/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h
index 205d934..bce8a44 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h
@@ -11,10 +11,12 @@
         Matrix< Scalar, Dynamic, 1 >  &sdiag)
 
 {
+    typedef DenseIndex Index;
+
     /* Local variables */
-    int i, j, k, l;
+    Index i, j, k, l;
     Scalar temp;
-    int n = s.cols();
+    Index n = s.cols();
     Matrix< Scalar, Dynamic, 1 >  wa(n);
     PlanarRotation<Scalar> givens;
 
@@ -67,7 +69,7 @@
 
     /*     solve the triangular system for z. if the system is */
     /*     singular, then obtain a least squares solution. */
-    int nsing;
+    Index nsing;
     for (nsing=0; nsing<n && sdiag[nsing]!=0; nsing++);
 
     wa.tail(n-nsing).setZero();
diff --git a/unsupported/Eigen/src/NonLinearOptimization/r1mpyq.h b/unsupported/Eigen/src/NonLinearOptimization/r1mpyq.h
index 855cb7a..ad319d9 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/r1mpyq.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/r1mpyq.h
@@ -2,18 +2,20 @@
 // TODO : move this to GivensQR once there's such a thing in Eigen
 
 template <typename Scalar>
-void ei_r1mpyq(int m, int n, Scalar *a, const std::vector<PlanarRotation<Scalar> > &v_givens, const std::vector<PlanarRotation<Scalar> > &w_givens)
+void ei_r1mpyq(DenseIndex m, DenseIndex n, Scalar *a, const std::vector<PlanarRotation<Scalar> > &v_givens, const std::vector<PlanarRotation<Scalar> > &w_givens)
 {
+    typedef DenseIndex Index;
+
     /*     apply the first set of givens rotations to a. */
-    for (int j = n-2; j>=0; --j)
-        for (int i = 0; i<m; ++i) {
+    for (Index j = n-2; j>=0; --j)
+        for (Index i = 0; i<m; ++i) {
             Scalar temp = v_givens[j].c() * a[i+m*j] - v_givens[j].s() * a[i+m*(n-1)];
             a[i+m*(n-1)] = v_givens[j].s() * a[i+m*j] + v_givens[j].c() * a[i+m*(n-1)];
             a[i+m*j] = temp;
         }
     /*     apply the second set of givens rotations to a. */
-    for (int j = 0; j<n-1; ++j)
-        for (int i = 0; i<m; ++i) {
+    for (Index j = 0; j<n-1; ++j)
+        for (Index i = 0; i<m; ++i) {
             Scalar temp = w_givens[j].c() * a[i+m*j] + w_givens[j].s() * a[i+m*(n-1)];
             a[i+m*(n-1)] = -w_givens[j].s() * a[i+m*j] + w_givens[j].c() * a[i+m*(n-1)];
             a[i+m*j] = temp;
diff --git a/unsupported/Eigen/src/NonLinearOptimization/r1updt.h b/unsupported/Eigen/src/NonLinearOptimization/r1updt.h
index 3d89788..e01d029 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/r1updt.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/r1updt.h
@@ -9,10 +9,12 @@
         Matrix< Scalar, Dynamic, 1> &w,
         bool *sing)
 {
+    typedef DenseIndex Index;
+
     /* Local variables */
-    const int m = s.rows();
-    const int n = s.cols();
-    int i, j=1;
+    const Index m = s.rows();
+    const Index n = s.cols();
+    Index i, j=1;
     Scalar temp;
     PlanarRotation<Scalar> givens;
 
diff --git a/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h b/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h
index b0bf729..aa0bf7d 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/rwupdt.h
@@ -6,7 +6,9 @@
         Matrix< Scalar, Dynamic, 1>  &b,
         Scalar alpha)
 {
-    const int n = r.cols();
+    typedef DenseIndex Index;
+
+    const Index n = r.cols();
     assert(r.rows()>=n);
     std::vector<PlanarRotation<Scalar> > givens(n);
 
@@ -14,12 +16,12 @@
     Scalar temp, rowj;
 
     /* Function Body */
-    for (int j = 0; j < n; ++j) {
+    for (Index j = 0; j < n; ++j) {
         rowj = w[j];
 
         /* apply the previous transformations to */
         /* r(i,j), i=0,1,...,j-1, and to w(j). */
-        for (int i = 0; i < j; ++i) {
+        for (Index i = 0; i < j; ++i) {
             temp = givens[i].c() * r(i,j) + givens[i].s() * rowj;
             rowj = -givens[i].s() * r(i,j) + givens[i].c() * rowj;
             r(i,j) = temp;
diff --git a/unsupported/Eigen/src/Polynomials/Companion.h b/unsupported/Eigen/src/Polynomials/Companion.h
index 7c9e9c5..5a3bacc 100644
--- a/unsupported/Eigen/src/Polynomials/Companion.h
+++ b/unsupported/Eigen/src/Polynomials/Companion.h
@@ -68,8 +68,10 @@
     typedef Matrix< Scalar, Deg_1, Deg_1 >         BottomLeftBlock;
     typedef Matrix< Scalar, 1, Deg_1 >             LeftBlockFirstRow;
 
+    typedef DenseIndex Index;
+
   public:
-    EIGEN_STRONG_INLINE const _Scalar operator()( int row, int col ) const
+    EIGEN_STRONG_INLINE const _Scalar operator()(Index row, Index col ) const
     {
       if( m_bl_diag.rows() > col )
       {
@@ -83,7 +85,7 @@
     template<typename VectorType>
     void setPolynomial( const VectorType& poly )
     {
-      const int deg = poly.size()-1;
+      const Index deg = poly.size()-1;
       m_monic = -1/poly[deg] * poly.head(deg);
       //m_bl_diag.setIdentity( deg-1 );
       m_bl_diag.setOnes(deg-1);
@@ -96,8 +98,8 @@
   public:
     DenseCompanionMatrixType denseMatrix() const
     {
-      const int deg   = m_monic.size();
-      const int deg_1 = deg-1;
+      const Index deg   = m_monic.size();
+      const Index deg_1 = deg-1;
       DenseCompanionMatrixType companion(deg,deg);
       companion <<
         ( LeftBlock(deg,deg_1)
@@ -220,8 +222,8 @@
 void ei_companion<_Scalar,_Deg>::balance()
 {
   EIGEN_STATIC_ASSERT( 1 < Deg, YOU_MADE_A_PROGRAMMING_MISTAKE );
-  const int deg   = m_monic.size();
-  const int deg_1 = deg-1;
+  const Index deg   = m_monic.size();
+  const Index deg_1 = deg-1;
 
   bool hasConverged=false;
   while( !hasConverged )
@@ -244,7 +246,7 @@
 
     //Middle rows and columns excluding the diagonal
     //==============================================
-    for( int i=1; i<deg_1; ++i )
+    for( Index i=1; i<deg_1; ++i )
     {
       // column norm, excluding the diagonal
       colNorm = ei_abs(m_bl_diag[i]);
@@ -263,7 +265,7 @@
 
     //Last row, last column excluding the diagonal
     //============================================
-    const int ebl = m_bl_diag.size()-1;
+    const Index ebl = m_bl_diag.size()-1;
     VectorBlock<RightColumn,Deg_1> headMonic( m_monic, 0, deg_1 );
     colNorm = headMonic.array().abs().sum();
     rowNorm = ei_abs( m_bl_diag[ebl] );
diff --git a/unsupported/Eigen/src/Polynomials/PolynomialSolver.h b/unsupported/Eigen/src/Polynomials/PolynomialSolver.h
index 2078365..ba14b59 100644
--- a/unsupported/Eigen/src/Polynomials/PolynomialSolver.h
+++ b/unsupported/Eigen/src/Polynomials/PolynomialSolver.h
@@ -49,6 +49,8 @@
     typedef std::complex<RealScalar>            RootType;
     typedef Matrix<RootType,_Deg,1>             RootsType;
 
+    typedef DenseIndex Index;
+
   protected:
     template< typename OtherPolynomial >
     inline void setPolynomial( const OtherPolynomial& poly ){
@@ -81,7 +83,7 @@
         const RealScalar& absImaginaryThreshold = NumTraits<Scalar>::dummy_precision() ) const
     {
       bi_seq.clear();
-      for( int i=0; i<m_roots.size(); ++i )
+      for(Index i=0; i<m_roots.size(); ++i )
       {
         if( ei_abs( m_roots[i].imag() ) < absImaginaryThreshold ){
           bi_seq.push_back( m_roots[i].real() ); }
@@ -92,9 +94,9 @@
     template<typename squaredNormBinaryPredicate>
     inline const RootType& selectComplexRoot_withRespectToNorm( squaredNormBinaryPredicate& pred ) const
     {
-      int res=0;
+      Index res=0;
       RealScalar norm2 = ei_abs2( m_roots[0] );
-      for( int i=1; i<m_roots.size(); ++i )
+      for( Index i=1; i<m_roots.size(); ++i )
       {
         const RealScalar currNorm2 = ei_abs2( m_roots[i] );
         if( pred( currNorm2, norm2 ) ){
@@ -130,10 +132,10 @@
         const RealScalar& absImaginaryThreshold = NumTraits<Scalar>::dummy_precision() ) const
     {
       hasArealRoot = false;
-      int res=0;
+      Index res=0;
       RealScalar abs2(0);
 
-      for( int i=0; i<m_roots.size(); ++i )
+      for( Index i=0; i<m_roots.size(); ++i )
       {
         if( ei_abs( m_roots[i].imag() ) < absImaginaryThreshold )
         {
@@ -170,10 +172,10 @@
         const RealScalar& absImaginaryThreshold = NumTraits<Scalar>::dummy_precision() ) const
     {
       hasArealRoot = false;
-      int res=0;
+      Index res=0;
       RealScalar val(0);
 
-      for( int i=0; i<m_roots.size(); ++i )
+      for( Index i=0; i<m_roots.size(); ++i )
       {
         if( ei_abs( m_roots[i].imag() ) < absImaginaryThreshold )
         {
diff --git a/unsupported/Eigen/src/Polynomials/PolynomialUtils.h b/unsupported/Eigen/src/Polynomials/PolynomialUtils.h
index d78821f..d10b8f4 100644
--- a/unsupported/Eigen/src/Polynomials/PolynomialUtils.h
+++ b/unsupported/Eigen/src/Polynomials/PolynomialUtils.h
@@ -41,7 +41,7 @@
 T poly_eval_horner( const Polynomials& poly, const T& x )
 {
   T val=poly[poly.size()-1];
-  for( int i=poly.size()-2; i>=0; --i ){
+  for(DenseIndex i=poly.size()-2; i>=0; --i ){
     val = val*x + poly[i]; }
   return val;
 }
@@ -66,7 +66,7 @@
   {
     T val=poly[0];
     T inv_x = T(1)/x;
-    for( int i=1; i<poly.size(); ++i ){
+    for( DenseIndex i=1; i<poly.size(); ++i ){
       val = val*inv_x + poly[i]; }
 
     return std::pow(x,(T)(poly.size()-1)) * val;
@@ -94,7 +94,7 @@
   const Scalar inv_leading_coeff = Scalar(1)/poly[poly.size()-1];
   Real cb(0);
 
-  for( int i=0; i<poly.size()-1; ++i ){
+  for( DenseIndex i=0; i<poly.size()-1; ++i ){
     cb += ei_abs(poly[i]*inv_leading_coeff); }
   return cb + Real(1);
 }
@@ -112,14 +112,14 @@
   typedef typename Polynomial::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real Real;
 
-  int i=0;
+  DenseIndex i=0;
   while( i<poly.size()-1 && Scalar(0) == poly(i) ){ ++i; }
   if( poly.size()-1 == i ){
     return Real(1); }
 
   const Scalar inv_min_coeff = Scalar(1)/poly[i];
   Real cb(1);
-  for( int j=i+1; j<poly.size(); ++j ){
+  for( DenseIndex j=i+1; j<poly.size(); ++j ){
     cb += ei_abs(poly[j]*inv_min_coeff); }
   return Real(1)/cb;
 }
@@ -142,9 +142,9 @@
 
   poly.setZero( rv.size()+1 );
   poly[0] = -rv[0]; poly[1] = Scalar(1);
-  for( int i=1; i<(int)rv.size(); ++i )
+  for( DenseIndex i=1; i< rv.size(); ++i )
   {
-    for( int j=i+1; j>0; --j ){ poly[j] = poly[j-1] - rv[i]*poly[j]; }
+    for( DenseIndex j=i+1; j>0; --j ){ poly[j] = poly[j-1] - rv[i]*poly[j]; }
     poly[0] = -rv[i]*poly[0];
   }
 }
diff --git a/unsupported/Eigen/src/Skyline/SkylineInplaceLU.h b/unsupported/Eigen/src/Skyline/SkylineInplaceLU.h
index c8c5f75..fa8f819 100644
--- a/unsupported/Eigen/src/Skyline/SkylineInplaceLU.h
+++ b/unsupported/Eigen/src/Skyline/SkylineInplaceLU.h
@@ -38,6 +38,8 @@
 class SkylineInplaceLU {
 protected:
     typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::Index Index;
+    
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
 
 public:
@@ -135,18 +137,18 @@
     ei_assert(rows == cols && "We do not (yet) support rectangular LU.");
     ei_assert(!m_lu.IsRowMajor && "LU decomposition does not work with rowMajor Storage");
 
-    for (unsigned int row = 0; row < rows; row++) {
+    for (Index row = 0; row < rows; row++) {
         const double pivot = m_lu.coeffDiag(row);
 
         //Lower matrix Columns update
-        const unsigned int& col = row;
+        const Index& col = row;
         for (typename MatrixType::InnerLowerIterator lIt(m_lu, col); lIt; ++lIt) {
             lIt.valueRef() /= pivot;
         }
 
         //Upper matrix update -> contiguous memory access
         typename MatrixType::InnerLowerIterator lIt(m_lu, col);
-        for (unsigned int rrow = row + 1; rrow < m_lu.rows(); rrow++) {
+        for (Index rrow = row + 1; rrow < m_lu.rows(); rrow++) {
             typename MatrixType::InnerUpperIterator uItPivot(m_lu, row);
             typename MatrixType::InnerUpperIterator uIt(m_lu, rrow);
             const double coef = lIt.value();
@@ -165,12 +167,12 @@
 
         //Upper matrix update -> non contiguous memory access
         typename MatrixType::InnerLowerIterator lIt3(m_lu, col);
-        for (unsigned int rrow = row + 1; rrow < m_lu.rows(); rrow++) {
+        for (Index rrow = row + 1; rrow < m_lu.rows(); rrow++) {
             typename MatrixType::InnerUpperIterator uItPivot(m_lu, row);
             const double coef = lIt3.value();
 
             //update lower part ->  non contiguous memory access
-            for (unsigned int i = 0; i < rrow - row - 1; i++) {
+            for (Index i = 0; i < rrow - row - 1; i++) {
                 m_lu.coeffRefLower(rrow, row + i + 1) -= uItPivot.value() * coef;
                 ++uItPivot;
             }
@@ -178,7 +180,7 @@
         }
         //update diag -> contiguous
         typename MatrixType::InnerLowerIterator lIt2(m_lu, col);
-        for (unsigned int rrow = row + 1; rrow < m_lu.rows(); rrow++) {
+        for (Index rrow = row + 1; rrow < m_lu.rows(); rrow++) {
 
             typename MatrixType::InnerUpperIterator uItPivot(m_lu, row);
             typename MatrixType::InnerUpperIterator uIt(m_lu, rrow);
@@ -199,11 +201,11 @@
     ei_assert(rows == cols && "We do not (yet) support rectangular LU.");
     ei_assert(m_lu.IsRowMajor && "You're trying to apply rowMajor decomposition on a ColMajor matrix !");
 
-    for (unsigned int row = 0; row < rows; row++) {
+    for (Index row = 0; row < rows; row++) {
         typename MatrixType::InnerLowerIterator llIt(m_lu, row);
 
 
-        for (unsigned int col = llIt.col(); col < row; col++) {
+        for (Index col = llIt.col(); col < row; col++) {
             if (m_lu.coeffExistLower(row, col)) {
                 const double diag = m_lu.coeffDiag(col);
 
@@ -211,10 +213,10 @@
                 typename MatrixType::InnerUpperIterator uIt(m_lu, col);
 
 
-                const int offset = lIt.col() - uIt.row();
+                const Index offset = lIt.col() - uIt.row();
 
 
-                int stop = offset > 0 ? col - lIt.col() : col - uIt.row();
+                Index stop = offset > 0 ? col - lIt.col() : col - uIt.row();
 
                 //#define VECTORIZE
 #ifdef VECTORIZE
@@ -230,7 +232,7 @@
                     lIt += -offset;
                 Scalar newCoeff = m_lu.coeffLower(row, col);
 
-                for (int k = 0; k < stop; ++k) {
+                for (Index k = 0; k < stop; ++k) {
                     const Scalar tmp = newCoeff;
                     newCoeff = tmp - lIt.value() * uIt.value();
                     ++lIt;
@@ -243,15 +245,15 @@
         }
 
         //Upper matrix update
-        const int col = row;
+        const Index col = row;
         typename MatrixType::InnerUpperIterator uuIt(m_lu, col);
-        for (unsigned int rrow = uuIt.row(); rrow < col; rrow++) {
+        for (Index rrow = uuIt.row(); rrow < col; rrow++) {
 
             typename MatrixType::InnerLowerIterator lIt(m_lu, rrow);
             typename MatrixType::InnerUpperIterator uIt(m_lu, col);
-            const int offset = lIt.col() - uIt.row();
+            const Index offset = lIt.col() - uIt.row();
 
-            int stop = offset > 0 ? rrow - lIt.col() : rrow - uIt.row();
+            Index stop = offset > 0 ? rrow - lIt.col() : rrow - uIt.row();
 
 #ifdef VECTORIZE
             Map<VectorXd > rowVal(lIt.valuePtr() + (offset > 0 ? 0 : -offset), stop);
@@ -264,7 +266,7 @@
             else //Skip zero values of uIt
                 lIt += -offset;
             Scalar newCoeff = m_lu.coeffUpper(rrow, col);
-            for (int k = 0; k < stop; ++k) {
+            for (Index k = 0; k < stop; ++k) {
                 const Scalar tmp = newCoeff;
                 newCoeff = tmp - lIt.value() * uIt.value();
 
@@ -280,10 +282,10 @@
         typename MatrixType::InnerLowerIterator lIt(m_lu, row);
         typename MatrixType::InnerUpperIterator uIt(m_lu, row);
 
-        const int offset = lIt.col() - uIt.row();
+        const Index offset = lIt.col() - uIt.row();
 
 
-        int stop = offset > 0 ? lIt.size() : uIt.size();
+        Index stop = offset > 0 ? lIt.size() : uIt.size();
 #ifdef VECTORIZE
         Map<VectorXd > rowVal(lIt.valuePtr() + (offset > 0 ? 0 : -offset), stop);
         Map<VectorXd > colVal(uIt.valuePtr() + (offset > 0 ? offset : 0), stop);
@@ -294,7 +296,7 @@
         else //Skip zero values of uIt
             lIt += -offset;
         Scalar newCoeff = m_lu.coeffDiag(row);
-        for (unsigned int k = 0; k < stop; ++k) {
+        for (Index k = 0; k < stop; ++k) {
             const Scalar tmp = newCoeff;
             newCoeff = tmp - lIt.value() * uIt.value();
             ++lIt;
@@ -320,12 +322,12 @@
     const size_t cols = m_lu.cols();
 
 
-    for (int row = 0; row < rows; row++) {
+    for (Index row = 0; row < rows; row++) {
         x->coeffRef(row) = b.coeff(row);
         Scalar newVal = x->coeff(row);
         typename MatrixType::InnerLowerIterator lIt(m_lu, row);
 
-        unsigned int col = lIt.col();
+        Index col = lIt.col();
         while (lIt.col() < row) {
 
             newVal -= x->coeff(col++) * lIt.value();
@@ -336,7 +338,7 @@
     }
 
 
-    for (int col = rows - 1; col > 0; col--) {
+    for (Index col = rows - 1; col > 0; col--) {
         x->coeffRef(col) = x->coeff(col) / m_lu.coeffDiag(col);
 
         const Scalar x_col = x->coeff(col);
diff --git a/unsupported/Eigen/src/Skyline/SkylineMatrix.h b/unsupported/Eigen/src/Skyline/SkylineMatrix.h
index 6dd4f17..20fafaf 100644
--- a/unsupported/Eigen/src/Skyline/SkylineMatrix.h
+++ b/unsupported/Eigen/src/Skyline/SkylineMatrix.h
@@ -46,6 +46,7 @@
 template<typename _Scalar, int _Options>
 struct ei_traits<SkylineMatrix<_Scalar, _Options> > {
     typedef _Scalar Scalar;
+    typedef Sparse StorageKind;
 
     enum {
         RowsAtCompileTime = Dynamic,
@@ -71,45 +72,45 @@
 
     typedef SkylineMatrix<Scalar, (Flags&~RowMajorBit) | (IsRowMajor ? RowMajorBit : 0) > TransposedSkylineMatrix;
 
-    int m_outerSize;
-    int m_innerSize;
+    Index m_outerSize;
+    Index m_innerSize;
 
 public:
-    int* m_colStartIndex;
-    int* m_rowStartIndex;
+    Index* m_colStartIndex;
+    Index* m_rowStartIndex;
     SkylineStorage<Scalar> m_data;
 
 public:
 
-    inline int rows() const {
+    inline Index rows() const {
         return IsRowMajor ? m_outerSize : m_innerSize;
     }
 
-    inline int cols() const {
+    inline Index cols() const {
         return IsRowMajor ? m_innerSize : m_outerSize;
     }
 
-    inline int innerSize() const {
+    inline Index innerSize() const {
         return m_innerSize;
     }
 
-    inline int outerSize() const {
+    inline Index outerSize() const {
         return m_outerSize;
     }
 
-    inline int upperNonZeros() const {
+    inline Index upperNonZeros() const {
         return m_data.upperSize();
     }
 
-    inline int lowerNonZeros() const {
+    inline Index lowerNonZeros() const {
         return m_data.lowerSize();
     }
 
-    inline int upperNonZeros(int j) const {
+    inline Index upperNonZeros(Index j) const {
         return m_colStartIndex[j + 1] - m_colStartIndex[j];
     }
 
-    inline int lowerNonZeros(int j) const {
+    inline Index lowerNonZeros(Index j) const {
         return m_rowStartIndex[j + 1] - m_rowStartIndex[j];
     }
 
@@ -137,25 +138,25 @@
         return &m_data.lower(0);
     }
 
-    inline const int* _upperProfilePtr() const {
+    inline const Index* _upperProfilePtr() const {
         return &m_data.upperProfile(0);
     }
 
-    inline int* _upperProfilePtr() {
+    inline Index* _upperProfilePtr() {
         return &m_data.upperProfile(0);
     }
 
-    inline const int* _lowerProfilePtr() const {
+    inline const Index* _lowerProfilePtr() const {
         return &m_data.lowerProfile(0);
     }
 
-    inline int* _lowerProfilePtr() {
+    inline Index* _lowerProfilePtr() {
         return &m_data.lowerProfile(0);
     }
 
-    inline Scalar coeff(int row, int col) const {
-        const int outer = IsRowMajor ? row : col;
-        const int inner = IsRowMajor ? col : row;
+    inline Scalar coeff(Index row, Index col) const {
+        const Index outer = IsRowMajor ? row : col;
+        const Index inner = IsRowMajor ? col : row;
 
         ei_assert(outer < outerSize());
         ei_assert(inner < innerSize());
@@ -166,7 +167,7 @@
         if (IsRowMajor) {
             if (inner > outer) //upper matrix
             {
-                const int minOuterIndex = inner - m_data.upperProfile(inner);
+                const Index minOuterIndex = inner - m_data.upperProfile(inner);
                 if (outer >= minOuterIndex)
                     return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
                 else
@@ -174,7 +175,7 @@
             }
             if (inner < outer) //lower matrix
             {
-                const int minInnerIndex = outer - m_data.lowerProfile(outer);
+                const Index minInnerIndex = outer - m_data.lowerProfile(outer);
                 if (inner >= minInnerIndex)
                     return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
                 else
@@ -184,7 +185,7 @@
         } else {
             if (outer > inner) //upper matrix
             {
-                const int maxOuterIndex = inner + m_data.upperProfile(inner);
+                const Index maxOuterIndex = inner + m_data.upperProfile(inner);
                 if (outer <= maxOuterIndex)
                     return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
                 else
@@ -192,7 +193,7 @@
             }
             if (outer < inner) //lower matrix
             {
-                const int maxInnerIndex = outer + m_data.lowerProfile(outer);
+                const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
 
                 if (inner <= maxInnerIndex)
                     return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
@@ -202,9 +203,9 @@
         }
     }
 
-    inline Scalar& coeffRef(int row, int col) {
-        const int outer = IsRowMajor ? row : col;
-        const int inner = IsRowMajor ? col : row;
+    inline Scalar& coeffRef(Index row, Index col) {
+        const Index outer = IsRowMajor ? row : col;
+        const Index inner = IsRowMajor ? col : row;
 
         ei_assert(outer < outerSize());
         ei_assert(inner < innerSize());
@@ -215,55 +216,55 @@
         if (IsRowMajor) {
             if (col > row) //upper matrix
             {
-                const int minOuterIndex = inner - m_data.upperProfile(inner);
+                const Index minOuterIndex = inner - m_data.upperProfile(inner);
                 ei_assert(outer >= minOuterIndex && "you try to acces a coeff that do not exist in the storage");
                 return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
             }
             if (col < row) //lower matrix
             {
-                const int minInnerIndex = outer - m_data.lowerProfile(outer);
+                const Index minInnerIndex = outer - m_data.lowerProfile(outer);
                 ei_assert(inner >= minInnerIndex && "you try to acces a coeff that do not exist in the storage");
                 return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
             }
         } else {
             if (outer > inner) //upper matrix
             {
-                const int maxOuterIndex = inner + m_data.upperProfile(inner);
+                const Index maxOuterIndex = inner + m_data.upperProfile(inner);
                 ei_assert(outer <= maxOuterIndex && "you try to acces a coeff that do not exist in the storage");
                 return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
             }
             if (outer < inner) //lower matrix
             {
-                const int maxInnerIndex = outer + m_data.lowerProfile(outer);
+                const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
                 ei_assert(inner <= maxInnerIndex && "you try to acces a coeff that do not exist in the storage");
                 return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
             }
         }
     }
 
-    inline Scalar coeffDiag(int idx) const {
+    inline Scalar coeffDiag(Index idx) const {
         ei_assert(idx < outerSize());
         ei_assert(idx < innerSize());
         return this->m_data.diag(idx);
     }
 
-    inline Scalar coeffLower(int row, int col) const {
-        const int outer = IsRowMajor ? row : col;
-        const int inner = IsRowMajor ? col : row;
+    inline Scalar coeffLower(Index row, Index col) const {
+        const Index outer = IsRowMajor ? row : col;
+        const Index inner = IsRowMajor ? col : row;
 
         ei_assert(outer < outerSize());
         ei_assert(inner < innerSize());
         ei_assert(inner != outer);
 
         if (IsRowMajor) {
-            const int minInnerIndex = outer - m_data.lowerProfile(outer);
+            const Index minInnerIndex = outer - m_data.lowerProfile(outer);
             if (inner >= minInnerIndex)
                 return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
             else
                 return Scalar(0);
 
         } else {
-            const int maxInnerIndex = outer + m_data.lowerProfile(outer);
+            const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
             if (inner <= maxInnerIndex)
                 return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
             else
@@ -271,22 +272,22 @@
         }
     }
 
-    inline Scalar coeffUpper(int row, int col) const {
-        const int outer = IsRowMajor ? row : col;
-        const int inner = IsRowMajor ? col : row;
+    inline Scalar coeffUpper(Index row, Index col) const {
+        const Index outer = IsRowMajor ? row : col;
+        const Index inner = IsRowMajor ? col : row;
 
         ei_assert(outer < outerSize());
         ei_assert(inner < innerSize());
         ei_assert(inner != outer);
 
         if (IsRowMajor) {
-            const int minOuterIndex = inner - m_data.upperProfile(inner);
+            const Index minOuterIndex = inner - m_data.upperProfile(inner);
             if (outer >= minOuterIndex)
                 return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
             else
                 return Scalar(0);
         } else {
-            const int maxOuterIndex = inner + m_data.upperProfile(inner);
+            const Index maxOuterIndex = inner + m_data.upperProfile(inner);
             if (outer <= maxOuterIndex)
                 return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
             else
@@ -294,80 +295,80 @@
         }
     }
 
-    inline Scalar& coeffRefDiag(int idx) {
+    inline Scalar& coeffRefDiag(Index idx) {
         ei_assert(idx < outerSize());
         ei_assert(idx < innerSize());
         return this->m_data.diag(idx);
     }
 
-    inline Scalar& coeffRefLower(int row, int col) {
-        const int outer = IsRowMajor ? row : col;
-        const int inner = IsRowMajor ? col : row;
+    inline Scalar& coeffRefLower(Index row, Index col) {
+        const Index outer = IsRowMajor ? row : col;
+        const Index inner = IsRowMajor ? col : row;
 
         ei_assert(outer < outerSize());
         ei_assert(inner < innerSize());
         ei_assert(inner != outer);
 
         if (IsRowMajor) {
-            const int minInnerIndex = outer - m_data.lowerProfile(outer);
+            const Index minInnerIndex = outer - m_data.lowerProfile(outer);
             ei_assert(inner >= minInnerIndex && "you try to acces a coeff that do not exist in the storage");
             return this->m_data.lower(m_rowStartIndex[outer] + inner - (outer - m_data.lowerProfile(outer)));
         } else {
-            const int maxInnerIndex = outer + m_data.lowerProfile(outer);
+            const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
             ei_assert(inner <= maxInnerIndex && "you try to acces a coeff that do not exist in the storage");
             return this->m_data.lower(m_rowStartIndex[outer] + (inner - outer));
         }
     }
 
-    inline bool coeffExistLower(int row, int col) {
-        const int outer = IsRowMajor ? row : col;
-        const int inner = IsRowMajor ? col : row;
+    inline bool coeffExistLower(Index row, Index col) {
+        const Index outer = IsRowMajor ? row : col;
+        const Index inner = IsRowMajor ? col : row;
 
         ei_assert(outer < outerSize());
         ei_assert(inner < innerSize());
         ei_assert(inner != outer);
 
         if (IsRowMajor) {
-            const int minInnerIndex = outer - m_data.lowerProfile(outer);
+            const Index minInnerIndex = outer - m_data.lowerProfile(outer);
             return inner >= minInnerIndex;
         } else {
-            const int maxInnerIndex = outer + m_data.lowerProfile(outer);
+            const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
             return inner <= maxInnerIndex;
         }
     }
 
-    inline Scalar& coeffRefUpper(int row, int col) {
-        const int outer = IsRowMajor ? row : col;
-        const int inner = IsRowMajor ? col : row;
+    inline Scalar& coeffRefUpper(Index row, Index col) {
+        const Index outer = IsRowMajor ? row : col;
+        const Index inner = IsRowMajor ? col : row;
 
         ei_assert(outer < outerSize());
         ei_assert(inner < innerSize());
         ei_assert(inner != outer);
 
         if (IsRowMajor) {
-            const int minOuterIndex = inner - m_data.upperProfile(inner);
+            const Index minOuterIndex = inner - m_data.upperProfile(inner);
             ei_assert(outer >= minOuterIndex && "you try to acces a coeff that do not exist in the storage");
             return this->m_data.upper(m_colStartIndex[inner] + outer - (inner - m_data.upperProfile(inner)));
         } else {
-            const int maxOuterIndex = inner + m_data.upperProfile(inner);
+            const Index maxOuterIndex = inner + m_data.upperProfile(inner);
             ei_assert(outer <= maxOuterIndex && "you try to acces a coeff that do not exist in the storage");
             return this->m_data.upper(m_colStartIndex[inner] + (outer - inner));
         }
     }
 
-    inline bool coeffExistUpper(int row, int col) {
-        const int outer = IsRowMajor ? row : col;
-        const int inner = IsRowMajor ? col : row;
+    inline bool coeffExistUpper(Index row, Index col) {
+        const Index outer = IsRowMajor ? row : col;
+        const Index inner = IsRowMajor ? col : row;
 
         ei_assert(outer < outerSize());
         ei_assert(inner < innerSize());
         ei_assert(inner != outer);
 
         if (IsRowMajor) {
-            const int minOuterIndex = inner - m_data.upperProfile(inner);
+            const Index minOuterIndex = inner - m_data.upperProfile(inner);
             return outer >= minOuterIndex;
         } else {
-            const int maxOuterIndex = inner + m_data.upperProfile(inner);
+            const Index maxOuterIndex = inner + m_data.upperProfile(inner);
             return outer <= maxOuterIndex;
         }
     }
@@ -385,17 +386,17 @@
     /** Removes all non zeros */
     inline void setZero() {
         m_data.clear();
-        memset(m_colStartIndex, 0, (m_outerSize + 1) * sizeof (int));
-        memset(m_rowStartIndex, 0, (m_outerSize + 1) * sizeof (int));
+        memset(m_colStartIndex, 0, (m_outerSize + 1) * sizeof (Index));
+        memset(m_rowStartIndex, 0, (m_outerSize + 1) * sizeof (Index));
     }
 
     /** \returns the number of non zero coefficients */
-    inline int nonZeros() const {
+    inline Index nonZeros() const {
         return m_data.diagSize() + m_data.upperSize() + m_data.lowerSize();
     }
 
     /** Preallocates \a reserveSize non zeros */
-    inline void reserve(int reserveSize, int reserveUpperSize, int reserveLowerSize) {
+    inline void reserve(Index reserveSize, Index reserveUpperSize, Index reserveLowerSize) {
         m_data.reserve(reserveSize, reserveUpperSize, reserveLowerSize);
     }
 
@@ -407,9 +408,9 @@
      *
      * After an insertion session, you should call the finalize() function.
      */
-    EIGEN_DONT_INLINE Scalar & insert(int row, int col) {
-        const int outer = IsRowMajor ? row : col;
-        const int inner = IsRowMajor ? col : row;
+    EIGEN_DONT_INLINE Scalar & insert(Index row, Index col) {
+        const Index outer = IsRowMajor ? row : col;
+        const Index inner = IsRowMajor ? col : row;
 
         ei_assert(outer < outerSize());
         ei_assert(inner < innerSize());
@@ -420,27 +421,27 @@
         if (IsRowMajor) {
             if (outer < inner) //upper matrix
             {
-                int minOuterIndex = 0;
+                Index minOuterIndex = 0;
                 minOuterIndex = inner - m_data.upperProfile(inner);
 
                 if (outer < minOuterIndex) //The value does not yet exist
                 {
-                    const int previousProfile = m_data.upperProfile(inner);
+                    const Index previousProfile = m_data.upperProfile(inner);
 
                     m_data.upperProfile(inner) = inner - outer;
 
 
-                    const int bandIncrement = m_data.upperProfile(inner) - previousProfile;
+                    const Index bandIncrement = m_data.upperProfile(inner) - previousProfile;
                     //shift data stored after this new one
-                    const int stop = m_colStartIndex[cols()];
-                    const int start = m_colStartIndex[inner];
+                    const Index stop = m_colStartIndex[cols()];
+                    const Index start = m_colStartIndex[inner];
 
 
-                    for (int innerIdx = stop; innerIdx >= start; innerIdx--) {
+                    for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
                         m_data.upper(innerIdx + bandIncrement) = m_data.upper(innerIdx);
                     }
 
-                    for (int innerIdx = cols(); innerIdx > inner; innerIdx--) {
+                    for (Index innerIdx = cols(); innerIdx > inner; innerIdx--) {
                         m_colStartIndex[innerIdx] += bandIncrement;
                     }
 
@@ -455,23 +456,23 @@
 
             if (outer > inner) //lower matrix
             {
-                const int minInnerIndex = outer - m_data.lowerProfile(outer);
+                const Index minInnerIndex = outer - m_data.lowerProfile(outer);
                 if (inner < minInnerIndex) //The value does not yet exist
                 {
-                    const int previousProfile = m_data.lowerProfile(outer);
+                    const Index previousProfile = m_data.lowerProfile(outer);
                     m_data.lowerProfile(outer) = outer - inner;
 
-                    const int bandIncrement = m_data.lowerProfile(outer) - previousProfile;
+                    const Index bandIncrement = m_data.lowerProfile(outer) - previousProfile;
                     //shift data stored after this new one
-                    const int stop = m_rowStartIndex[rows()];
-                    const int start = m_rowStartIndex[outer];
+                    const Index stop = m_rowStartIndex[rows()];
+                    const Index start = m_rowStartIndex[outer];
 
 
-                    for (int innerIdx = stop; innerIdx >= start; innerIdx--) {
+                    for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
                         m_data.lower(innerIdx + bandIncrement) = m_data.lower(innerIdx);
                     }
 
-                    for (int innerIdx = rows(); innerIdx > outer; innerIdx--) {
+                    for (Index innerIdx = rows(); innerIdx > outer; innerIdx--) {
                         m_rowStartIndex[innerIdx] += bandIncrement;
                     }
 
@@ -485,22 +486,22 @@
         } else {
             if (outer > inner) //upper matrix
             {
-                const int maxOuterIndex = inner + m_data.upperProfile(inner);
+                const Index maxOuterIndex = inner + m_data.upperProfile(inner);
                 if (outer > maxOuterIndex) //The value does not yet exist
                 {
-                    const int previousProfile = m_data.upperProfile(inner);
+                    const Index previousProfile = m_data.upperProfile(inner);
                     m_data.upperProfile(inner) = outer - inner;
 
-                    const int bandIncrement = m_data.upperProfile(inner) - previousProfile;
+                    const Index bandIncrement = m_data.upperProfile(inner) - previousProfile;
                     //shift data stored after this new one
-                    const int stop = m_rowStartIndex[rows()];
-                    const int start = m_rowStartIndex[inner + 1];
+                    const Index stop = m_rowStartIndex[rows()];
+                    const Index start = m_rowStartIndex[inner + 1];
 
-                    for (int innerIdx = stop; innerIdx >= start; innerIdx--) {
+                    for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
                         m_data.upper(innerIdx + bandIncrement) = m_data.upper(innerIdx);
                     }
 
-                    for (int innerIdx = inner + 1; innerIdx < outerSize() + 1; innerIdx++) {
+                    for (Index innerIdx = inner + 1; innerIdx < outerSize() + 1; innerIdx++) {
                         m_rowStartIndex[innerIdx] += bandIncrement;
                     }
                     memset(this->_upperPtr() + m_rowStartIndex[inner] + previousProfile + 1, 0, (bandIncrement - 1) * sizeof (Scalar));
@@ -512,22 +513,22 @@
 
             if (outer < inner) //lower matrix
             {
-                const int maxInnerIndex = outer + m_data.lowerProfile(outer);
+                const Index maxInnerIndex = outer + m_data.lowerProfile(outer);
                 if (inner > maxInnerIndex) //The value does not yet exist
                 {
-                    const int previousProfile = m_data.lowerProfile(outer);
+                    const Index previousProfile = m_data.lowerProfile(outer);
                     m_data.lowerProfile(outer) = inner - outer;
 
-                    const int bandIncrement = m_data.lowerProfile(outer) - previousProfile;
+                    const Index bandIncrement = m_data.lowerProfile(outer) - previousProfile;
                     //shift data stored after this new one
-                    const int stop = m_colStartIndex[cols()];
-                    const int start = m_colStartIndex[outer + 1];
+                    const Index stop = m_colStartIndex[cols()];
+                    const Index start = m_colStartIndex[outer + 1];
 
-                    for (int innerIdx = stop; innerIdx >= start; innerIdx--) {
+                    for (Index innerIdx = stop; innerIdx >= start; innerIdx--) {
                         m_data.lower(innerIdx + bandIncrement) = m_data.lower(innerIdx);
                     }
 
-                    for (int innerIdx = outer + 1; innerIdx < outerSize() + 1; innerIdx++) {
+                    for (Index innerIdx = outer + 1; innerIdx < outerSize() + 1; innerIdx++) {
                         m_colStartIndex[innerIdx] += bandIncrement;
                     }
                     memset(this->_lowerPtr() + m_colStartIndex[outer] + previousProfile + 1, 0, (bandIncrement - 1) * sizeof (Scalar));
@@ -551,16 +552,16 @@
             //            ei_assert(rows() == cols() && "memory reorganisatrion only works with suare matrix");
             //
             //            Scalar* newArray = new Scalar[m_colStartIndex[cols()] + 1 + m_rowStartIndex[rows()] + 1];
-            //            unsigned int dataIdx = 0;
-            //            for (unsigned int row = 0; row < rows(); row++) {
+            //            Index dataIdx = 0;
+            //            for (Index row = 0; row < rows(); row++) {
             //
-            //                const unsigned int nbLowerElts = m_rowStartIndex[row + 1] - m_rowStartIndex[row];
+            //                const Index nbLowerElts = m_rowStartIndex[row + 1] - m_rowStartIndex[row];
             //                //                std::cout << "nbLowerElts" << nbLowerElts << std::endl;
             //                memcpy(newArray + dataIdx, m_data.m_lower + m_rowStartIndex[row], nbLowerElts * sizeof (Scalar));
             //                m_rowStartIndex[row] = dataIdx;
             //                dataIdx += nbLowerElts;
             //
-            //                const unsigned int nbUpperElts = m_colStartIndex[row + 1] - m_colStartIndex[row];
+            //                const Index nbUpperElts = m_colStartIndex[row + 1] - m_colStartIndex[row];
             //                memcpy(newArray + dataIdx, m_data.m_upper + m_colStartIndex[row], nbUpperElts * sizeof (Scalar));
             //                m_colStartIndex[row] = dataIdx;
             //                dataIdx += nbUpperElts;
@@ -594,16 +595,16 @@
     }
 
     /** Resizes the matrix to a \a rows x \a cols matrix and initializes it to zero
-     * \sa resizeNonZeros(int), reserve(), setZero()
+     * \sa resizeNonZeros(Index), reserve(), setZero()
      */
     void resize(size_t rows, size_t cols) {
-        const int diagSize = rows > cols ? cols : rows;
+        const Index diagSize = rows > cols ? cols : rows;
         m_innerSize = IsRowMajor ? cols : rows;
 
         ei_assert(rows == cols && "Skyline matrix must be square matrix");
 
         if (diagSize % 2) { // diagSize is odd
-            const int k = (diagSize - 1) / 2;
+            const Index k = (diagSize - 1) / 2;
 
             m_data.resize(diagSize, IsRowMajor ? cols : rows, IsRowMajor ? rows : cols,
                     2 * k * k + k + 1,
@@ -611,7 +612,7 @@
 
         } else // diagSize is even
         {
-            const int k = diagSize / 2;
+            const Index k = diagSize / 2;
             m_data.resize(diagSize, IsRowMajor ? cols : rows, IsRowMajor ? rows : cols,
                     2 * k * k - k + 1,
                     2 * k * k - k + 1);
@@ -621,19 +622,19 @@
             delete[] m_colStartIndex;
             delete[] m_rowStartIndex;
         }
-        m_colStartIndex = new int [cols + 1];
-        m_rowStartIndex = new int [rows + 1];
+        m_colStartIndex = new Index [cols + 1];
+        m_rowStartIndex = new Index [rows + 1];
         m_outerSize = diagSize;
 
         m_data.reset();
         m_data.clear();
 
         m_outerSize = diagSize;
-        memset(m_colStartIndex, 0, (cols + 1) * sizeof (int));
-        memset(m_rowStartIndex, 0, (rows + 1) * sizeof (int));
+        memset(m_colStartIndex, 0, (cols + 1) * sizeof (Index));
+        memset(m_rowStartIndex, 0, (rows + 1) * sizeof (Index));
     }
 
-    void resizeNonZeros(int size) {
+    void resizeNonZeros(Index size) {
         m_data.resize(size);
     }
 
@@ -673,8 +674,8 @@
             swap(other.const_cast_derived());
         } else {
             resize(other.rows(), other.cols());
-            memcpy(m_colStartIndex, other.m_colStartIndex, (m_outerSize + 1) * sizeof (int));
-            memcpy(m_rowStartIndex, other.m_rowStartIndex, (m_outerSize + 1) * sizeof (int));
+            memcpy(m_colStartIndex, other.m_colStartIndex, (m_outerSize + 1) * sizeof (Index));
+            memcpy(m_rowStartIndex, other.m_rowStartIndex, (m_outerSize + 1) * sizeof (Index));
             m_data = other.m_data;
         }
         return *this;
@@ -696,34 +697,34 @@
 
         EIGEN_DBG_SKYLINE(
         std::cout << "upper elements : " << std::endl;
-        for (unsigned int i = 0; i < m.m_data.upperSize(); i++)
+        for (Index i = 0; i < m.m_data.upperSize(); i++)
             std::cout << m.m_data.upper(i) << "\t";
         std::cout << std::endl;
         std::cout << "upper profile : " << std::endl;
-        for (unsigned int i = 0; i < m.m_data.upperProfileSize(); i++)
+        for (Index i = 0; i < m.m_data.upperProfileSize(); i++)
             std::cout << m.m_data.upperProfile(i) << "\t";
         std::cout << std::endl;
         std::cout << "lower startIdx : " << std::endl;
-        for (unsigned int i = 0; i < m.m_data.upperProfileSize(); i++)
+        for (Index i = 0; i < m.m_data.upperProfileSize(); i++)
             std::cout << (IsRowMajor ? m.m_colStartIndex[i] : m.m_rowStartIndex[i]) << "\t";
         std::cout << std::endl;
 
 
         std::cout << "lower elements : " << std::endl;
-        for (unsigned int i = 0; i < m.m_data.lowerSize(); i++)
+        for (Index i = 0; i < m.m_data.lowerSize(); i++)
             std::cout << m.m_data.lower(i) << "\t";
         std::cout << std::endl;
         std::cout << "lower profile : " << std::endl;
-        for (unsigned int i = 0; i < m.m_data.lowerProfileSize(); i++)
+        for (Index i = 0; i < m.m_data.lowerProfileSize(); i++)
             std::cout << m.m_data.lowerProfile(i) << "\t";
         std::cout << std::endl;
         std::cout << "lower startIdx : " << std::endl;
-        for (unsigned int i = 0; i < m.m_data.lowerProfileSize(); i++)
+        for (Index i = 0; i < m.m_data.lowerProfileSize(); i++)
             std::cout << (IsRowMajor ? m.m_rowStartIndex[i] : m.m_colStartIndex[i]) << "\t";
         std::cout << std::endl;
         );
-        for (unsigned int rowIdx = 0; rowIdx < m.rows(); rowIdx++) {
-            for (unsigned int colIdx = 0; colIdx < m.cols(); colIdx++) {
+        for (Index rowIdx = 0; rowIdx < m.rows(); rowIdx++) {
+            for (Index colIdx = 0; colIdx < m.cols(); colIdx++) {
                 s << m.coeff(rowIdx, colIdx) << "\t";
             }
             s << std::endl;
@@ -745,7 +746,7 @@
 class SkylineMatrix<Scalar, _Options>::InnerUpperIterator {
 public:
 
-    InnerUpperIterator(const SkylineMatrix& mat, int outer)
+    InnerUpperIterator(const SkylineMatrix& mat, Index outer)
     : m_matrix(mat), m_outer(outer),
     m_id(_Options == RowMajor ? mat.m_colStartIndex[outer] : mat.m_rowStartIndex[outer] + 1),
     m_start(m_id),
@@ -757,7 +758,7 @@
         return *this;
     }
 
-    inline InnerUpperIterator & operator+=(unsigned int shift) {
+    inline InnerUpperIterator & operator+=(Index shift) {
         m_id += shift;
         return *this;
     }
@@ -774,16 +775,16 @@
         return const_cast<Scalar&> (m_matrix.m_data.upper(m_id));
     }
 
-    inline int index() const {
+    inline Index index() const {
         return IsRowMajor ? m_outer - m_matrix.m_data.upperProfile(m_outer) + (m_id - m_start) :
                 m_outer + (m_id - m_start) + 1;
     }
 
-    inline int row() const {
+    inline Index row() const {
         return IsRowMajor ? index() : m_outer;
     }
 
-    inline int col() const {
+    inline Index col() const {
         return IsRowMajor ? m_outer : index();
     }
 
@@ -797,17 +798,17 @@
 
 protected:
     const SkylineMatrix& m_matrix;
-    const int m_outer;
-    int m_id;
-    const int m_start;
-    const int m_end;
+    const Index m_outer;
+    Index m_id;
+    const Index m_start;
+    const Index m_end;
 };
 
 template<typename Scalar, int _Options>
 class SkylineMatrix<Scalar, _Options>::InnerLowerIterator {
 public:
 
-    InnerLowerIterator(const SkylineMatrix& mat, int outer)
+    InnerLowerIterator(const SkylineMatrix& mat, Index outer)
     : m_matrix(mat),
     m_outer(outer),
     m_id(_Options == RowMajor ? mat.m_rowStartIndex[outer] : mat.m_colStartIndex[outer] + 1),
@@ -820,7 +821,7 @@
         return *this;
     }
 
-    inline InnerLowerIterator & operator+=(unsigned int shift) {
+    inline InnerLowerIterator & operator+=(Index shift) {
         m_id += shift;
         return *this;
     }
@@ -837,17 +838,17 @@
         return const_cast<Scalar&> (m_matrix.m_data.lower(m_id));
     }
 
-    inline int index() const {
+    inline Index index() const {
         return IsRowMajor ? m_outer - m_matrix.m_data.lowerProfile(m_outer) + (m_id - m_start) :
                 m_outer + (m_id - m_start) + 1;
         ;
     }
 
-    inline int row() const {
+    inline Index row() const {
         return IsRowMajor ? m_outer : index();
     }
 
-    inline int col() const {
+    inline Index col() const {
         return IsRowMajor ? index() : m_outer;
     }
 
@@ -861,10 +862,10 @@
 
 protected:
     const SkylineMatrix& m_matrix;
-    const int m_outer;
-    int m_id;
-    const int m_start;
-    const int m_end;
+    const Index m_outer;
+    Index m_id;
+    const Index m_start;
+    const Index m_end;
 };
 
 #endif // EIGEN_SkylineMatrix_H
diff --git a/unsupported/Eigen/src/Skyline/SkylineMatrixBase.h b/unsupported/Eigen/src/Skyline/SkylineMatrixBase.h
index ff20b83..17349c1 100644
--- a/unsupported/Eigen/src/Skyline/SkylineMatrixBase.h
+++ b/unsupported/Eigen/src/Skyline/SkylineMatrixBase.h
@@ -40,6 +40,8 @@
 public:
 
     typedef typename ei_traits<Derived>::Scalar Scalar;
+    typedef typename ei_traits<Derived>::StorageKind StorageKind;
+    typedef typename ei_index<StorageKind>::type Index;
 
     enum {
         RowsAtCompileTime = ei_traits<Derived>::RowsAtCompileTime,
@@ -113,36 +115,36 @@
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
     /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
-    inline int rows() const {
+    inline Index rows() const {
         return derived().rows();
     }
 
     /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
-    inline int cols() const {
+    inline Index cols() const {
         return derived().cols();
     }
 
     /** \returns the number of coefficients, which is \a rows()*cols().
      * \sa rows(), cols(), SizeAtCompileTime. */
-    inline int size() const {
+    inline Index size() const {
         return rows() * cols();
     }
 
     /** \returns the number of nonzero coefficients which is in practice the number
      * of stored coefficients. */
-    inline int nonZeros() const {
+    inline Index nonZeros() const {
         return derived().nonZeros();
     }
 
     /** \returns the size of the storage major dimension,
      * i.e., the number of columns for a columns major matrix, and the number of rows otherwise */
-    int outerSize() const {
+    Index outerSize() const {
         return (int(Flags) & RowMajorBit) ? this->rows() : this->cols();
     }
 
     /** \returns the size of the inner dimension according to the storage order,
      * i.e., the number of rows for a columns major matrix, and the number of cols otherwise */
-    int innerSize() const {
+    Index innerSize() const {
         return (int(Flags) & RowMajorBit) ? this->cols() : this->rows();
     }
 
@@ -167,8 +169,8 @@
     template<typename OtherDerived>
     inline void assignGeneric(const OtherDerived& other) {
         derived().resize(other.rows(), other.cols());
-        for (unsigned int row = 0; row < rows(); row++)
-            for (unsigned int col = 0; col < cols(); col++) {
+        for (Index row = 0; row < rows(); row++)
+            for (Index col = 0; col < cols(); col++) {
                 if (other.coeff(row, col) != Scalar(0))
                     derived().insert(row, col) = other.coeff(row, col);
             }
@@ -196,8 +198,8 @@
     template<typename DenseDerived>
     void evalTo(MatrixBase<DenseDerived>& dst) const {
         dst.setZero();
-        for (unsigned int i = 0; i < rows(); i++)
-            for (unsigned int j = 0; j < rows(); j++)
+        for (Index i = 0; i < rows(); i++)
+            for (Index j = 0; j < rows(); j++)
                 dst(i, j) = derived().coeff(i, j);
     }
 
diff --git a/unsupported/Eigen/src/Skyline/SkylineProduct.h b/unsupported/Eigen/src/Skyline/SkylineProduct.h
index 9586576..e6484ad 100644
--- a/unsupported/Eigen/src/Skyline/SkylineProduct.h
+++ b/unsupported/Eigen/src/Skyline/SkylineProduct.h
@@ -106,11 +106,11 @@
                 EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
     }
 
-    EIGEN_STRONG_INLINE int rows() const {
+    EIGEN_STRONG_INLINE Index rows() const {
         return m_lhs.rows();
     }
 
-    EIGEN_STRONG_INLINE int cols() const {
+    EIGEN_STRONG_INLINE Index cols() const {
         return m_rhs.cols();
     }
 
@@ -147,18 +147,18 @@
     };
 
     //Use matrix diagonal part <- Improvement : use inner iterator on dense matrix.
-    for (unsigned int col = 0; col < rhs.cols(); col++) {
-        for (unsigned int row = 0; row < lhs.rows(); row++) {
+    for (Index col = 0; col < rhs.cols(); col++) {
+        for (Index row = 0; row < lhs.rows(); row++) {
             dst(row, col) = lhs.coeffDiag(row) * rhs(row, col);
         }
     }
     //Use matrix lower triangular part
-    for (unsigned int row = 0; row < lhs.rows(); row++) {
+    for (Index row = 0; row < lhs.rows(); row++) {
         typename _Lhs::InnerLowerIterator lIt(lhs, row);
-        const int stop = lIt.col() + lIt.size();
-        for (unsigned int col = 0; col < rhs.cols(); col++) {
+        const Index stop = lIt.col() + lIt.size();
+        for (Index col = 0; col < rhs.cols(); col++) {
 
-            unsigned int k = lIt.col();
+            Index k = lIt.col();
             Scalar tmp = 0;
             while (k < stop) {
                 tmp +=
@@ -173,14 +173,14 @@
     }
 
     //Use matrix upper triangular part
-    for (unsigned int lhscol = 0; lhscol < lhs.cols(); lhscol++) {
+    for (Index lhscol = 0; lhscol < lhs.cols(); lhscol++) {
         typename _Lhs::InnerUpperIterator uIt(lhs, lhscol);
-        const int stop = uIt.size() + uIt.row();
-        for (unsigned int rhscol = 0; rhscol < rhs.cols(); rhscol++) {
+        const Index stop = uIt.size() + uIt.row();
+        for (Index rhscol = 0; rhscol < rhs.cols(); rhscol++) {
 
 
             const Scalar rhsCoeff = rhs.coeff(lhscol, rhscol);
-            unsigned int k = uIt.row();
+            Index k = uIt.row();
             while (k < stop) {
                 dst(k++, rhscol) +=
                         uIt.value() *
@@ -210,19 +210,19 @@
     };
 
     //Use matrix diagonal part <- Improvement : use inner iterator on dense matrix.
-    for (unsigned int col = 0; col < rhs.cols(); col++) {
-        for (unsigned int row = 0; row < lhs.rows(); row++) {
+    for (Index col = 0; col < rhs.cols(); col++) {
+        for (Index row = 0; row < lhs.rows(); row++) {
             dst(row, col) = lhs.coeffDiag(row) * rhs(row, col);
         }
     }
 
     //Use matrix upper triangular part
-    for (unsigned int row = 0; row < lhs.rows(); row++) {
+    for (Index row = 0; row < lhs.rows(); row++) {
         typename _Lhs::InnerUpperIterator uIt(lhs, row);
-        const int stop = uIt.col() + uIt.size();
-        for (unsigned int col = 0; col < rhs.cols(); col++) {
+        const Index stop = uIt.col() + uIt.size();
+        for (Index col = 0; col < rhs.cols(); col++) {
 
-            unsigned int k = uIt.col();
+            Index k = uIt.col();
             Scalar tmp = 0;
             while (k < stop) {
                 tmp +=
@@ -238,13 +238,13 @@
     }
 
     //Use matrix lower triangular part
-    for (unsigned int lhscol = 0; lhscol < lhs.cols(); lhscol++) {
+    for (Index lhscol = 0; lhscol < lhs.cols(); lhscol++) {
         typename _Lhs::InnerLowerIterator lIt(lhs, lhscol);
-        const int stop = lIt.size() + lIt.row();
-        for (unsigned int rhscol = 0; rhscol < rhs.cols(); rhscol++) {
+        const Index stop = lIt.size() + lIt.row();
+        for (Index rhscol = 0; rhscol < rhs.cols(); rhscol++) {
 
             const Scalar rhsCoeff = rhs.coeff(lhscol, rhscol);
-            unsigned int k = lIt.row();
+            Index k = lIt.row();
             while (k < stop) {
                 dst(k++, rhscol) +=
                         lIt.value() *
diff --git a/unsupported/Eigen/src/Skyline/SkylineStorage.h b/unsupported/Eigen/src/Skyline/SkylineStorage.h
index 641508f..13f3e0c 100644
--- a/unsupported/Eigen/src/Skyline/SkylineStorage.h
+++ b/unsupported/Eigen/src/Skyline/SkylineStorage.h
@@ -34,6 +34,7 @@
 template<typename Scalar>
 class SkylineStorage {
     typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef SparseIndex Index;
 public:
 
     SkylineStorage()
@@ -70,8 +71,8 @@
         memcpy(m_diag, other.m_diag, m_diagSize * sizeof (Scalar));
         memcpy(m_upper, other.m_upper, other.upperSize() * sizeof (Scalar));
         memcpy(m_lower, other.m_lower, other.lowerSize() * sizeof (Scalar));
-        memcpy(m_upperProfile, other.m_upperProfile, m_upperProfileSize * sizeof (int));
-        memcpy(m_lowerProfile, other.m_lowerProfile, m_lowerProfileSize * sizeof (int));
+        memcpy(m_upperProfile, other.m_upperProfile, m_upperProfileSize * sizeof (Index));
+        memcpy(m_lowerProfile, other.m_lowerProfile, m_lowerProfileSize * sizeof (Index));
         return *this;
     }
 
@@ -96,8 +97,8 @@
         delete[] m_lowerProfile;
     }
 
-    void reserve(size_t size, size_t upperProfileSize, size_t lowerProfileSize, size_t upperSize, size_t lowerSize) {
-        int newAllocatedSize = size + upperSize + lowerSize;
+    void reserve(Index size, Index upperProfileSize, Index lowerProfileSize, Index upperSize, Index lowerSize) {
+        Index newAllocatedSize = size + upperSize + lowerSize;
         if (newAllocatedSize > m_allocatedSize)
             reallocate(size, upperProfileSize, lowerProfileSize, upperSize, lowerSize);
     }
@@ -107,9 +108,9 @@
             reallocate(m_diagSize, m_upperProfileSize, m_lowerProfileSize, m_upperSize, m_lowerSize);
     }
 
-    void resize(size_t diagSize, size_t upperProfileSize, size_t lowerProfileSize, size_t upperSize, size_t lowerSize, float reserveSizeFactor = 0) {
+    void resize(Index diagSize, Index upperProfileSize, Index lowerProfileSize, Index upperSize, Index lowerSize, float reserveSizeFactor = 0) {
         if (m_allocatedSize < diagSize + upperSize + lowerSize)
-            reallocate(diagSize, upperProfileSize, lowerProfileSize, upperSize + size_t(reserveSizeFactor * upperSize), lowerSize + size_t(reserveSizeFactor * lowerSize));
+            reallocate(diagSize, upperProfileSize, lowerProfileSize, upperSize + Index(reserveSizeFactor * upperSize), lowerSize + Index(reserveSizeFactor * lowerSize));
         m_diagSize = diagSize;
         m_upperSize = upperSize;
         m_lowerSize = lowerSize;
@@ -117,27 +118,27 @@
         m_lowerProfileSize = lowerProfileSize;
     }
 
-    inline size_t diagSize() const {
+    inline Index diagSize() const {
         return m_diagSize;
     }
 
-    inline size_t upperSize() const {
+    inline Index upperSize() const {
         return m_upperSize;
     }
 
-    inline size_t lowerSize() const {
+    inline Index lowerSize() const {
         return m_lowerSize;
     }
 
-    inline size_t upperProfileSize() const {
+    inline Index upperProfileSize() const {
         return m_upperProfileSize;
     }
 
-    inline size_t lowerProfileSize() const {
+    inline Index lowerProfileSize() const {
         return m_lowerProfileSize;
     }
 
-    inline size_t allocatedSize() const {
+    inline Index allocatedSize() const {
         return m_allocatedSize;
     }
 
@@ -145,47 +146,47 @@
         m_diagSize = 0;
     }
 
-    inline Scalar& diag(size_t i) {
+    inline Scalar& diag(Index i) {
         return m_diag[i];
     }
 
-    inline const Scalar& diag(size_t i) const {
+    inline const Scalar& diag(Index i) const {
         return m_diag[i];
     }
 
-    inline Scalar& upper(size_t i) {
+    inline Scalar& upper(Index i) {
         return m_upper[i];
     }
 
-    inline const Scalar& upper(size_t i) const {
+    inline const Scalar& upper(Index i) const {
         return m_upper[i];
     }
 
-    inline Scalar& lower(size_t i) {
+    inline Scalar& lower(Index i) {
         return m_lower[i];
     }
 
-    inline const Scalar& lower(size_t i) const {
+    inline const Scalar& lower(Index i) const {
         return m_lower[i];
     }
 
-    inline int& upperProfile(size_t i) {
+    inline Index& upperProfile(Index i) {
         return m_upperProfile[i];
     }
 
-    inline const int& upperProfile(size_t i) const {
+    inline const Index& upperProfile(Index i) const {
         return m_upperProfile[i];
     }
 
-    inline int& lowerProfile(size_t i) {
+    inline Index& lowerProfile(Index i) {
         return m_lowerProfile[i];
     }
 
-    inline const int& lowerProfile(size_t i) const {
+    inline const Index& lowerProfile(Index i) const {
         return m_lowerProfile[i];
     }
 
-    static SkylineStorage Map(int* upperProfile, int* lowerProfile, Scalar* diag, Scalar* upper, Scalar* lower, size_t size, size_t upperSize, size_t lowerSize) {
+    static SkylineStorage Map(Index* upperProfile, Index* lowerProfile, Scalar* diag, Scalar* upper, Scalar* lower, Index size, Index upperSize, Index lowerSize) {
         SkylineStorage res;
         res.m_upperProfile = upperProfile;
         res.m_lowerProfile = lowerProfile;
@@ -202,8 +203,8 @@
         memset(m_diag, 0, m_diagSize * sizeof (Scalar));
         memset(m_upper, 0, m_upperSize * sizeof (Scalar));
         memset(m_lower, 0, m_lowerSize * sizeof (Scalar));
-        memset(m_upperProfile, 0, m_diagSize * sizeof (int));
-        memset(m_lowerProfile, 0, m_diagSize * sizeof (int));
+        memset(m_upperProfile, 0, m_diagSize * sizeof (Index));
+        memset(m_lowerProfile, 0, m_diagSize * sizeof (Index));
     }
 
     void prune(Scalar reference, RealScalar epsilon = dummy_precision<RealScalar>()) {
@@ -212,26 +213,26 @@
 
 protected:
 
-    inline void reallocate(size_t diagSize, size_t upperProfileSize, size_t lowerProfileSize, size_t upperSize, size_t lowerSize) {
+    inline void reallocate(Index diagSize, Index upperProfileSize, Index lowerProfileSize, Index upperSize, Index lowerSize) {
 
         Scalar* diag = new Scalar[diagSize];
         Scalar* upper = new Scalar[upperSize];
         Scalar* lower = new Scalar[lowerSize];
-        int* upperProfile = new int[upperProfileSize];
-        int* lowerProfile = new int[lowerProfileSize];
+        Index* upperProfile = new Index[upperProfileSize];
+        Index* lowerProfile = new Index[lowerProfileSize];
 
-        size_t copyDiagSize = std::min(diagSize, m_diagSize);
-        size_t copyUpperSize = std::min(upperSize, m_upperSize);
-        size_t copyLowerSize = std::min(lowerSize, m_lowerSize);
-        size_t copyUpperProfileSize = std::min(upperProfileSize, m_upperProfileSize);
-        size_t copyLowerProfileSize = std::min(lowerProfileSize, m_lowerProfileSize);
+        Index copyDiagSize = std::min(diagSize, m_diagSize);
+        Index copyUpperSize = std::min(upperSize, m_upperSize);
+        Index copyLowerSize = std::min(lowerSize, m_lowerSize);
+        Index copyUpperProfileSize = std::min(upperProfileSize, m_upperProfileSize);
+        Index copyLowerProfileSize = std::min(lowerProfileSize, m_lowerProfileSize);
 
         // copy
         memcpy(diag, m_diag, copyDiagSize * sizeof (Scalar));
         memcpy(upper, m_upper, copyUpperSize * sizeof (Scalar));
         memcpy(lower, m_lower, copyLowerSize * sizeof (Scalar));
-        memcpy(upperProfile, m_upperProfile, copyUpperProfileSize * sizeof (int));
-        memcpy(lowerProfile, m_lowerProfile, copyLowerProfileSize * sizeof (int));
+        memcpy(upperProfile, m_upperProfile, copyUpperProfileSize * sizeof (Index));
+        memcpy(lowerProfile, m_lowerProfile, copyLowerProfileSize * sizeof (Index));
 
 
 
@@ -255,14 +256,14 @@
     Scalar* m_diag;
     Scalar* m_upper;
     Scalar* m_lower;
-    int* m_upperProfile;
-    int* m_lowerProfile;
-    size_t m_diagSize;
-    size_t m_upperSize;
-    size_t m_lowerSize;
-    size_t m_upperProfileSize;
-    size_t m_lowerProfileSize;
-    size_t m_allocatedSize;
+    Index* m_upperProfile;
+    Index* m_lowerProfile;
+    Index m_diagSize;
+    Index m_upperSize;
+    Index m_lowerSize;
+    Index m_upperProfileSize;
+    Index m_lowerProfileSize;
+    Index m_allocatedSize;
 
 };
 
diff --git a/unsupported/Eigen/src/Skyline/SkylineUtil.h b/unsupported/Eigen/src/Skyline/SkylineUtil.h
index 71563ad..7781c33 100644
--- a/unsupported/Eigen/src/Skyline/SkylineUtil.h
+++ b/unsupported/Eigen/src/Skyline/SkylineUtil.h
@@ -56,20 +56,22 @@
 }
 
 #define EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATORS(Derived) \
-EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(Derived, =) \
-EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(Derived, +=) \
-EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(Derived, -=) \
-EIGEN_SKYLINE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, *=) \
-EIGEN_SKYLINE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, /=)
+  EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(Derived, =) \
+  EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(Derived, +=) \
+  EIGEN_SKYLINE_INHERIT_ASSIGNMENT_OPERATOR(Derived, -=) \
+  EIGEN_SKYLINE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, *=) \
+  EIGEN_SKYLINE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, /=)
 
 #define _EIGEN_SKYLINE_GENERIC_PUBLIC_INTERFACE(Derived, BaseClass) \
-typedef BaseClass Base; \
-typedef typename Eigen::ei_traits<Derived>::Scalar Scalar; \
-typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; \
-enum {  Flags = Eigen::ei_traits<Derived>::Flags, };
+  typedef BaseClass Base; \
+  typedef typename Eigen::ei_traits<Derived>::Scalar Scalar; \
+  typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; \
+  typedef typename Eigen::ei_traits<Derived>::StorageKind StorageKind; \
+  typedef typename Eigen::ei_index<StorageKind>::type Index; \
+  enum {  Flags = Eigen::ei_traits<Derived>::Flags, };
 
 #define EIGEN_SKYLINE_GENERIC_PUBLIC_INTERFACE(Derived) \
-_EIGEN_SKYLINE_GENERIC_PUBLIC_INTERFACE(Derived, Eigen::SkylineMatrixBase<Derived>)
+  _EIGEN_SKYLINE_GENERIC_PUBLIC_INTERFACE(Derived, Eigen::SkylineMatrixBase<Derived>)
 
 template<typename Derived> class SkylineMatrixBase;
 template<typename _Scalar, int _Flags = 0> class SkylineMatrix;
diff --git a/unsupported/test/NonLinearOptimization.cpp b/unsupported/test/NonLinearOptimization.cpp
index 3867c31..0a609f7 100644
--- a/unsupported/test/NonLinearOptimization.cpp
+++ b/unsupported/test/NonLinearOptimization.cpp
@@ -558,7 +558,7 @@
 
   // do the computation
   lmdif_functor functor;
-  int nfev;
+  DenseIndex nfev;
   info = LevenbergMarquardt<lmdif_functor>::lmdif1(functor, x, &nfev);
 
   // check return value