Fix PPC rand and other failures.

diff --git a/test/array_for_matrix.cpp b/test/array_for_matrix.cpp
index afe6894..6d7d0dd 100644
--- a/test/array_for_matrix.cpp
+++ b/test/array_for_matrix.cpp

@@ -19,12 +19,18 @@
   Index cols = m.cols();
 
   MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), m3(rows, cols);
-
   ColVectorType cv1 = ColVectorType::Random(rows);
   RowVectorType rv1 = RowVectorType::Random(cols);
 
   Scalar s1 = internal::random<Scalar>(), s2 = internal::random<Scalar>();
 
+  // Prevent overflows for integer types.
+  if (Eigen::NumTraits<Scalar>::IsInteger) {
+    constexpr Scalar kMaxVal = Scalar(10000);
+    m1.array() = m1.array() - kMaxVal * (m1.array() / kMaxVal);
+    m2.array() = m2.array() - kMaxVal * (m2.array() / kMaxVal);
+  }
+
   // scalar addition
   VERIFY_IS_APPROX(m1.array() + s1, s1 + m1.array());
   VERIFY_IS_APPROX((m1.array() + s1).matrix(), MatrixType::Constant(rows, cols, s1) + m1);

diff --git a/test/main.h b/test/main.h
index 771725f..bce6736 100644
--- a/test/main.h
+++ b/test/main.h

@@ -176,11 +176,6 @@
 #define DEBUG
 #endif
 
-// bounds integer values for AltiVec
-#if defined(__ALTIVEC__) || defined(__VSX__)
-#define EIGEN_MAKING_DOCS
-#endif
-
 #define DEFAULT_REPEAT 10
 
 namespace Eigen {

diff --git a/test/product.h b/test/product.h
index 8d46846..31f577f 100644
--- a/test/product.h
+++ b/test/product.h

@@ -53,7 +53,7 @@
                  MatrixType::Flags & RowMajorBit ? ColMajor : RowMajor>
       OtherMajorMatrixType;
 
-  // Wwe want a tighter epsilon for not-approx tests.  Otherwise, for certain
+  // We want a tighter epsilon for not-approx tests.  Otherwise, for certain
   // low-precision types (e.g. bfloat16), the bound ends up being relatively large
   // (e.g. 0.12), causing flaky tests.
   RealScalar not_approx_epsilon = RealScalar(0.1) * NumTraits<RealScalar>::dummy_precision();
@@ -69,6 +69,15 @@
   ColSquareMatrixType square2 = ColSquareMatrixType::Random(cols, cols), res2 = ColSquareMatrixType::Random(cols, cols);
   RowVectorType v1 = RowVectorType::Random(rows);
   ColVectorType vc2 = ColVectorType::Random(cols), vcres(cols);
+
+  // Prevent overflows for integer types.
+  if (Eigen::NumTraits<Scalar>::IsInteger) {
+    constexpr Scalar kMaxVal = Scalar(10000);
+    m1.array() = m1.array() - kMaxVal * (m1.array() / kMaxVal);
+    m2.array() = m2.array() - kMaxVal * (m2.array() / kMaxVal);
+    v1.array() = v1.array() - kMaxVal * (v1.array() / kMaxVal);
+  }
+
   OtherMajorMatrixType tm1 = m1;
 
   Scalar s1 = internal::random<Scalar>();

diff --git a/test/redux.cpp b/test/redux.cpp
index 8a8138d..872e44f 100644
--- a/test/redux.cpp
+++ b/test/redux.cpp

@@ -30,6 +30,12 @@
 
   Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> m2(rows, rows);
   m2.setRandom();
+  // Prevent overflows for integer types.
+  if (Eigen::NumTraits<Scalar>::IsInteger) {
+    constexpr Scalar kMaxVal = Scalar(10000);
+    m1.array() = m1.array() - kMaxVal * (m1.array() / kMaxVal);
+    m2.array() = m2.array() - kMaxVal * (m2.array() / kMaxVal);
+  }
 
   VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1));
   VERIFY_IS_APPROX(

diff --git a/test/stl_iterators.cpp b/test/stl_iterators.cpp
index 7a62673..4b60e68 100644
--- a/test/stl_iterators.cpp
+++ b/test/stl_iterators.cpp

@@ -463,6 +463,13 @@
   // check rows/cols iterators with STL algorithms
   {
     RowVectorType row = RowVectorType::Random(cols);
+    VectorType col = VectorType::Random(rows);
+    // Prevent overflows for integer types.
+    if (Eigen::NumTraits<Scalar>::IsInteger) {
+      constexpr Scalar kMaxVal = Scalar(1000);
+      row.array() = row.array() - kMaxVal * (row.array() / kMaxVal);
+      col.array() = col.array() - kMaxVal * (col.array() / kMaxVal);
+    }
     A.rowwise() = row;
     VERIFY(std::all_of(A.rowwise().begin(), A.rowwise().end(), [&row](typename ColMatrixType::RowXpr x) {
       return internal::isApprox(x.squaredNorm(), row.squaredNorm());
@@ -471,7 +478,6 @@
       return internal::isApprox(x.squaredNorm(), row.squaredNorm());
     }));
 
-    VectorType col = VectorType::Random(rows);
     A.colwise() = col;
     VERIFY(std::all_of(A.colwise().begin(), A.colwise().end(), [&col](typename ColMatrixType::ColXpr x) {
       return internal::isApprox(x.squaredNorm(), col.squaredNorm());