| /* | |
| Copyright (c) 2011, Intel Corporation. All rights reserved. | |
| Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr> | |
| Redistribution and use in source and binary forms, with or without modification, | |
| are permitted provided that the following conditions are met: | |
| * Redistributions of source code must retain the above copyright notice, this | |
| list of conditions and the following disclaimer. | |
| * Redistributions in binary form must reproduce the above copyright notice, | |
| this list of conditions and the following disclaimer in the documentation | |
| and/or other materials provided with the distribution. | |
| * Neither the name of Intel Corporation nor the names of its contributors may | |
| be used to endorse or promote products derived from this software without | |
| specific prior written permission. | |
| THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND | |
| ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | |
| WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | |
| DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR | |
| ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES | |
| (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | |
| LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON | |
| ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT | |
| (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS | |
| SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | |
| ******************************************************************************** | |
| * Content : Eigen bindings to Intel(R) MKL | |
| * MKL VML support for coefficient-wise unary Eigen expressions like a=b.sin() | |
| ******************************************************************************** | |
| */ | |
| #ifndef EIGEN_ASSIGN_VML_H | |
| #define EIGEN_ASSIGN_VML_H | |
| namespace Eigen { | |
| namespace internal { | |
| template<typename Dst, typename Src> | |
| class vml_assign_traits | |
| { | |
| private: | |
| enum { | |
| DstHasDirectAccess = Dst::Flags & DirectAccessBit, | |
| SrcHasDirectAccess = Src::Flags & DirectAccessBit, | |
| StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)), | |
| InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime) | |
| : int(Dst::Flags)&RowMajorBit ? int(Dst::ColsAtCompileTime) | |
| : int(Dst::RowsAtCompileTime), | |
| InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime) | |
| : int(Dst::Flags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime) | |
| : int(Dst::MaxRowsAtCompileTime), | |
| MaxSizeAtCompileTime = Dst::SizeAtCompileTime, | |
| MightEnableVml = StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1, | |
| MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit), | |
| VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize, | |
| LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD | |
| }; | |
| public: | |
| enum { | |
| EnableVml = MightEnableVml && LargeEnough, | |
| Traversal = MightLinearize ? LinearTraversal : DefaultTraversal | |
| }; | |
| }; | |
| #define EIGEN_PP_EXPAND(ARG) ARG | |
| #if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1) | |
| #define EIGEN_VMLMODE_EXPAND_xLA , VML_HA | |
| #else | |
| #define EIGEN_VMLMODE_EXPAND_xLA , VML_LA | |
| #endif | |
| #define EIGEN_VMLMODE_EXPAND_x_ | |
| #define EIGEN_VMLMODE_PREFIX_xLA vm | |
| #define EIGEN_VMLMODE_PREFIX_x_ v | |
| #define EIGEN_VMLMODE_PREFIX(VMLMODE) EIGEN_CAT(EIGEN_VMLMODE_PREFIX_x,VMLMODE) | |
| #define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \ | |
| template< typename DstXprType, typename SrcXprNested> \ | |
| struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, assign_op<EIGENTYPE,EIGENTYPE>, \ | |
| Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> { \ | |
| typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType; \ | |
| static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &func) { \ | |
| resize_if_allowed(dst, src, func); \ | |
| eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \ | |
| if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) { \ | |
| VMLOP(dst.size(), (const VMLTYPE*)src.nestedExpression().data(), \ | |
| (VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE) ); \ | |
| } else { \ | |
| const Index outerSize = dst.outerSize(); \ | |
| for(Index outer = 0; outer < outerSize; ++outer) { \ | |
| const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer,0)) : \ | |
| &(src.nestedExpression().coeffRef(0, outer)); \ | |
| EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer)); \ | |
| VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr, \ | |
| (VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \ | |
| } \ | |
| } \ | |
| } \ | |
| }; \ | |
| #define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \ | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),s##VMLOP), float, float, VMLMODE) \ | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),d##VMLOP), double, double, VMLMODE) | |
| #define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE) \ | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),c##VMLOP), scomplex, MKL_Complex8, VMLMODE) \ | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),z##VMLOP), dcomplex, MKL_Complex16, VMLMODE) | |
| #define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP, VMLMODE) \ | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \ | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sin, Sin, LA) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(asin, Asin, LA) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sinh, Sinh, LA) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cos, Cos, LA) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(acos, Acos, LA) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cosh, Cosh, LA) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tan, Tan, LA) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(atan, Atan, LA) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tanh, Tanh, LA) | |
| // EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs, Abs, _) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(exp, Exp, LA) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log, Ln, LA) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log10, Log10, LA) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sqrt, Sqrt, _) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr, _) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(arg, Arg, _) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(round, Round, _) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(floor, Floor, _) | |
| EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil, Ceil, _) | |
| #define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \ | |
| template< typename DstXprType, typename SrcXprNested, typename Plain> \ | |
| struct Assignment<DstXprType, CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE,EIGENTYPE>, SrcXprNested, \ | |
| const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>,Plain> >, assign_op<EIGENTYPE,EIGENTYPE>, \ | |
| Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> { \ | |
| typedef CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE,EIGENTYPE>, SrcXprNested, \ | |
| const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>,Plain> > SrcXprType; \ | |
| static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &func) { \ | |
| resize_if_allowed(dst, src, func); \ | |
| eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \ | |
| VMLTYPE exponent = reinterpret_cast<const VMLTYPE&>(src.rhs().functor().m_other); \ | |
| if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) \ | |
| { \ | |
| VMLOP( dst.size(), (const VMLTYPE*)src.lhs().data(), exponent, \ | |
| (VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE) ); \ | |
| } else { \ | |
| const Index outerSize = dst.outerSize(); \ | |
| for(Index outer = 0; outer < outerSize; ++outer) { \ | |
| const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.lhs().coeffRef(outer,0)) : \ | |
| &(src.lhs().coeffRef(0, outer)); \ | |
| EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer)); \ | |
| VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr, exponent, \ | |
| (VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \ | |
| } \ | |
| } \ | |
| } \ | |
| }; | |
| EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmsPowx, float, float, LA) | |
| EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdPowx, double, double, LA) | |
| EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcPowx, scomplex, MKL_Complex8, LA) | |
| EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzPowx, dcomplex, MKL_Complex16, LA) | |
| } // end namespace internal | |
| } // end namespace Eigen | |
| #endif // EIGEN_ASSIGN_VML_H |