Assign_MKL.h (12488B)
1 /* 2 Copyright (c) 2011, Intel Corporation. All rights reserved. 3 Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr> 4 5 Redistribution and use in source and binary forms, with or without modification, 6 are permitted provided that the following conditions are met: 7 8 * Redistributions of source code must retain the above copyright notice, this 9 list of conditions and the following disclaimer. 10 * Redistributions in binary form must reproduce the above copyright notice, 11 this list of conditions and the following disclaimer in the documentation 12 and/or other materials provided with the distribution. 13 * Neither the name of Intel Corporation nor the names of its contributors may 14 be used to endorse or promote products derived from this software without 15 specific prior written permission. 16 17 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND 18 ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 19 WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 20 DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR 21 ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES 22 (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 23 LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON 24 ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 25 (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 26 SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 27 28 ******************************************************************************** 29 * Content : Eigen bindings to Intel(R) MKL 30 * MKL VML support for coefficient-wise unary Eigen expressions like a=b.sin() 31 ******************************************************************************** 32 */ 33 34 #ifndef EIGEN_ASSIGN_VML_H 35 #define EIGEN_ASSIGN_VML_H 36 37 namespace Eigen { 38 39 namespace internal { 40 41 template<typename Dst, typename Src> 42 class vml_assign_traits 43 { 44 private: 45 enum { 46 DstHasDirectAccess = Dst::Flags & DirectAccessBit, 47 SrcHasDirectAccess = Src::Flags & DirectAccessBit, 48 StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)), 49 InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime) 50 : int(Dst::Flags)&RowMajorBit ? int(Dst::ColsAtCompileTime) 51 : int(Dst::RowsAtCompileTime), 52 InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime) 53 : int(Dst::Flags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime) 54 : int(Dst::MaxRowsAtCompileTime), 55 MaxSizeAtCompileTime = Dst::SizeAtCompileTime, 56 57 MightEnableVml = StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1, 58 MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit), 59 VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize, 60 LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD 61 }; 62 public: 63 enum { 64 EnableVml = MightEnableVml && LargeEnough, 65 Traversal = MightLinearize ? LinearTraversal : DefaultTraversal 66 }; 67 }; 68 69 #define EIGEN_PP_EXPAND(ARG) ARG 70 #if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1) 71 #define EIGEN_VMLMODE_EXPAND_xLA , VML_HA 72 #else 73 #define EIGEN_VMLMODE_EXPAND_xLA , VML_LA 74 #endif 75 76 #define EIGEN_VMLMODE_EXPAND_x_ 77 78 #define EIGEN_VMLMODE_PREFIX_xLA vm 79 #define EIGEN_VMLMODE_PREFIX_x_ v 80 #define EIGEN_VMLMODE_PREFIX(VMLMODE) EIGEN_CAT(EIGEN_VMLMODE_PREFIX_x,VMLMODE) 81 82 #define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \ 83 template< typename DstXprType, typename SrcXprNested> \ 84 struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, assign_op<EIGENTYPE,EIGENTYPE>, \ 85 Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> { \ 86 typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType; \ 87 static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &func) { \ 88 resize_if_allowed(dst, src, func); \ 89 eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \ 90 if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) { \ 91 VMLOP(dst.size(), (const VMLTYPE*)src.nestedExpression().data(), \ 92 (VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE) ); \ 93 } else { \ 94 const Index outerSize = dst.outerSize(); \ 95 for(Index outer = 0; outer < outerSize; ++outer) { \ 96 const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer,0)) : \ 97 &(src.nestedExpression().coeffRef(0, outer)); \ 98 EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer)); \ 99 VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr, \ 100 (VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \ 101 } \ 102 } \ 103 } \ 104 }; \ 105 106 107 #define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \ 108 EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),s##VMLOP), float, float, VMLMODE) \ 109 EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),d##VMLOP), double, double, VMLMODE) 110 111 #define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE) \ 112 EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),c##VMLOP), scomplex, MKL_Complex8, VMLMODE) \ 113 EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE),z##VMLOP), dcomplex, MKL_Complex16, VMLMODE) 114 115 #define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP, VMLMODE) \ 116 EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \ 117 EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE) 118 119 120 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sin, Sin, LA) 121 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(asin, Asin, LA) 122 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sinh, Sinh, LA) 123 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cos, Cos, LA) 124 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(acos, Acos, LA) 125 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cosh, Cosh, LA) 126 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tan, Tan, LA) 127 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(atan, Atan, LA) 128 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tanh, Tanh, LA) 129 // EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs, Abs, _) 130 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(exp, Exp, LA) 131 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log, Ln, LA) 132 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log10, Log10, LA) 133 EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sqrt, Sqrt, _) 134 135 EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr, _) 136 EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(arg, Arg, _) 137 EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(round, Round, _) 138 EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(floor, Floor, _) 139 EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil, Ceil, _) 140 141 #define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \ 142 template< typename DstXprType, typename SrcXprNested, typename Plain> \ 143 struct Assignment<DstXprType, CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE,EIGENTYPE>, SrcXprNested, \ 144 const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>,Plain> >, assign_op<EIGENTYPE,EIGENTYPE>, \ 145 Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> { \ 146 typedef CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE,EIGENTYPE>, SrcXprNested, \ 147 const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>,Plain> > SrcXprType; \ 148 static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &func) { \ 149 resize_if_allowed(dst, src, func); \ 150 eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \ 151 VMLTYPE exponent = reinterpret_cast<const VMLTYPE&>(src.rhs().functor().m_other); \ 152 if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) \ 153 { \ 154 VMLOP( dst.size(), (const VMLTYPE*)src.lhs().data(), exponent, \ 155 (VMLTYPE*)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE) ); \ 156 } else { \ 157 const Index outerSize = dst.outerSize(); \ 158 for(Index outer = 0; outer < outerSize; ++outer) { \ 159 const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.lhs().coeffRef(outer,0)) : \ 160 &(src.lhs().coeffRef(0, outer)); \ 161 EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer)); \ 162 VMLOP( dst.innerSize(), (const VMLTYPE*)src_ptr, exponent, \ 163 (VMLTYPE*)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \ 164 } \ 165 } \ 166 } \ 167 }; 168 169 EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmsPowx, float, float, LA) 170 EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdPowx, double, double, LA) 171 EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcPowx, scomplex, MKL_Complex8, LA) 172 EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzPowx, dcomplex, MKL_Complex16, LA) 173 174 } // end namespace internal 175 176 } // end namespace Eigen 177 178 #endif // EIGEN_ASSIGN_VML_H