1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library 2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra. 3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> 5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla 7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed 8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_TRIANGULAR_MATRIX_MATRIX_H 11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_TRIANGULAR_MATRIX_MATRIX_H 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen { 14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal { 16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// template<typename Scalar, int mr, int StorageOrder, bool Conjugate, int Mode> 18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// struct gemm_pack_lhs_triangular 19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// { 20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Matrix<Scalar,mr,mr, 21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// void operator()(Scalar* blockA, const EIGEN_RESTRICT Scalar* _lhs, int lhsStride, int depth, int rows) 22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// { 23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj; 24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// const_blas_data_mapper<Scalar, StorageOrder> lhs(_lhs,lhsStride); 25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// int count = 0; 26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// const int peeled_mc = (rows/mr)*mr; 27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for(int i=0; i<peeled_mc; i+=mr) 28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// { 29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for(int k=0; k<depth; k++) 30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for(int w=0; w<mr; w++) 31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// blockA[count++] = cj(lhs(i+w, k)); 32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// } 33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for(int i=peeled_mc; i<rows; i++) 34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// { 35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for(int k=0; k<depth; k++) 36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// blockA[count++] = cj(lhs(i, k)); 37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// } 38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// } 39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// }; 40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/* Optimized triangular matrix * matrix (_TRMM++) product built on top of 42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * the general matrix matrix product. 43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath */ 44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename Scalar, typename Index, 45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int Mode, bool LhsIsTriangular, 46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int LhsStorageOrder, bool ConjugateLhs, 47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int RhsStorageOrder, bool ConjugateRhs, 48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int ResStorageOrder, int Version = Specialized> 49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct product_triangular_matrix_matrix; 50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename Scalar, typename Index, 52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int Mode, bool LhsIsTriangular, 53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int LhsStorageOrder, bool ConjugateLhs, 54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int RhsStorageOrder, bool ConjugateRhs, int Version> 55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct product_triangular_matrix_matrix<Scalar,Index,Mode,LhsIsTriangular, 56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath LhsStorageOrder,ConjugateLhs, 57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath RhsStorageOrder,ConjugateRhs,RowMajor,Version> 58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static EIGEN_STRONG_INLINE void run( 60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index rows, Index cols, Index depth, 61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const Scalar* lhs, Index lhsStride, 62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const Scalar* rhs, Index rhsStride, 63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Scalar* res, Index resStride, 647faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking) 65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath product_triangular_matrix_matrix<Scalar, Index, 67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath (Mode&(UnitDiag|ZeroDiag)) | ((Mode&Upper) ? Lower : Upper), 68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath (!LhsIsTriangular), 69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath RhsStorageOrder==RowMajor ? ColMajor : RowMajor, 70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ConjugateRhs, 71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath LhsStorageOrder==RowMajor ? ColMajor : RowMajor, 72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ConjugateLhs, 73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ColMajor> 74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ::run(cols, rows, depth, rhs, rhsStride, lhs, lhsStride, res, resStride, alpha, blocking); 75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// implements col-major += alpha * op(triangular) * op(general) 79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename Scalar, typename Index, int Mode, 80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int LhsStorageOrder, bool ConjugateLhs, 81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int RhsStorageOrder, bool ConjugateRhs, int Version> 82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct product_triangular_matrix_matrix<Scalar,Index,Mode,true, 83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath LhsStorageOrder,ConjugateLhs, 84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath RhsStorageOrder,ConjugateRhs,ColMajor,Version> 85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef gebp_traits<Scalar,Scalar> Traits; 88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath enum { 89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath SmallPanelWidth = 2 * EIGEN_PLAIN_ENUM_MAX(Traits::mr,Traits::nr), 90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath IsLower = (Mode&Lower) == Lower, 91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1 92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath }; 93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static EIGEN_DONT_INLINE void run( 95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index _rows, Index _cols, Index _depth, 96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const Scalar* _lhs, Index lhsStride, 97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const Scalar* _rhs, Index rhsStride, 98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Scalar* res, Index resStride, 997faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking); 1007faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez}; 1017faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez 1027faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandeztemplate <typename Scalar, typename Index, int Mode, 1037faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez int LhsStorageOrder, bool ConjugateLhs, 1047faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez int RhsStorageOrder, bool ConjugateRhs, int Version> 1057faaa9f3f0df9d23790277834d426c3d992ac3baCarlos HernandezEIGEN_DONT_INLINE void product_triangular_matrix_matrix<Scalar,Index,Mode,true, 1067faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez LhsStorageOrder,ConjugateLhs, 1077faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez RhsStorageOrder,ConjugateRhs,ColMajor,Version>::run( 1087faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez Index _rows, Index _cols, Index _depth, 1097faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez const Scalar* _lhs, Index lhsStride, 1107faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez const Scalar* _rhs, Index rhsStride, 1117faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez Scalar* res, Index resStride, 1127faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking) 113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // strip zeros 115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index diagSize = (std::min)(_rows,_depth); 116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index rows = IsLower ? _rows : diagSize; 117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index depth = IsLower ? diagSize : _depth; 118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index cols = _cols; 119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride); 121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride); 122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index kc = blocking.kc(); // cache block size along the K direction 124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index mc = (std::min)(rows,blocking.mc()); // cache block size along the M direction 125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::size_t sizeA = kc*mc; 127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::size_t sizeB = kc*cols; 128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::size_t sizeW = kc*Traits::WorkSpaceFactor; 129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA()); 131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB()); 132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW()); 133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,LhsStorageOrder> triangularBuffer; 135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath triangularBuffer.setZero(); 136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if((Mode&ZeroDiag)==ZeroDiag) 137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath triangularBuffer.diagonal().setZero(); 138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath else 139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath triangularBuffer.diagonal().setOnes(); 140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel; 142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs; 143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs; 144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(Index k2=IsLower ? depth : 0; 146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath IsLower ? k2>0 : k2<depth; 147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath IsLower ? k2-=kc : k2+=kc) 148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index actual_kc = (std::min)(IsLower ? k2 : depth-k2, kc); 150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index actual_k2 = IsLower ? k2-actual_kc : k2; 151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // align blocks with the end of the triangular part for trapezoidal lhs 153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if((!IsLower)&&(k2<rows)&&(k2+actual_kc>rows)) 154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath actual_kc = rows-k2; 156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath k2 = k2+actual_kc-kc; 157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath pack_rhs(blockB, &rhs(actual_k2,0), rhsStride, actual_kc, cols); 160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // the selected lhs's panel has to be split in three different parts: 162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // 1 - the part which is zero => skip it 163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // 2 - the diagonal block => special kernel 164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // 3 - the dense panel below (lower case) or above (upper case) the diagonal block => GEPP 165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // the block diagonal, if any: 167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if(IsLower || actual_k2<rows) 168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // for each small vertical panels of lhs 170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for (Index k1=0; k1<actual_kc; k1+=SmallPanelWidth) 171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index actualPanelWidth = std::min<Index>(actual_kc-k1, SmallPanelWidth); 173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index lengthTarget = IsLower ? actual_kc-k1-actualPanelWidth : k1; 174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index startBlock = actual_k2+k1; 175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index blockBOffset = k1; 176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // => GEBP with the micro triangular block 178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // The trick is to pack this micro block while filling the opposite triangular part with zeros. 179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // To this end we do an extra triangular copy to a small temporary buffer 180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for (Index k=0;k<actualPanelWidth;++k) 181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if (SetDiag) 183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath triangularBuffer.coeffRef(k,k) = lhs(startBlock+k,startBlock+k); 184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for (Index i=IsLower ? k+1 : 0; IsLower ? i<actualPanelWidth : i<k; ++i) 185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath triangularBuffer.coeffRef(i,k) = lhs(startBlock+i,startBlock+k); 186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath pack_lhs(blockA, triangularBuffer.data(), triangularBuffer.outerStride(), actualPanelWidth, actualPanelWidth); 188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gebp_kernel(res+startBlock, resStride, blockA, blockB, actualPanelWidth, actualPanelWidth, cols, alpha, 190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath actualPanelWidth, actual_kc, 0, blockBOffset, blockW); 191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // GEBP with remaining micro panel 193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if (lengthTarget>0) 194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index startTarget = IsLower ? actual_k2+k1+actualPanelWidth : actual_k2; 196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath pack_lhs(blockA, &lhs(startTarget,startBlock), lhsStride, actualPanelWidth, lengthTarget); 198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gebp_kernel(res+startTarget, resStride, blockA, blockB, lengthTarget, actualPanelWidth, cols, alpha, 200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath actualPanelWidth, actual_kc, 0, blockBOffset, blockW); 201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // the part below (lower case) or above (upper case) the diagonal => GEPP 205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index start = IsLower ? k2 : 0; 207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index end = IsLower ? rows : (std::min)(actual_k2,rows); 208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(Index i2=start; i2<end; i2+=mc) 209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 210c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const Index actual_mc = (std::min)(i2+mc,end)-i2; 211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gemm_pack_lhs<Scalar, Index, Traits::mr,Traits::LhsProgress, LhsStorageOrder,false>() 212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath (blockA, &lhs(i2, actual_k2), lhsStride, actual_kc, actual_mc); 213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha, -1, -1, 0, 0, blockW); 215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// implements col-major += alpha * op(general) * op(triangular) 221c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename Scalar, typename Index, int Mode, 222c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int LhsStorageOrder, bool ConjugateLhs, 223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int RhsStorageOrder, bool ConjugateRhs, int Version> 224c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct product_triangular_matrix_matrix<Scalar,Index,Mode,false, 2257faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez LhsStorageOrder,ConjugateLhs, 2267faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez RhsStorageOrder,ConjugateRhs,ColMajor,Version> 227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef gebp_traits<Scalar,Scalar> Traits; 229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath enum { 230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath SmallPanelWidth = EIGEN_PLAIN_ENUM_MAX(Traits::mr,Traits::nr), 231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath IsLower = (Mode&Lower) == Lower, 232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1 233c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath }; 234c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath static EIGEN_DONT_INLINE void run( 236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index _rows, Index _cols, Index _depth, 237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const Scalar* _lhs, Index lhsStride, 238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const Scalar* _rhs, Index rhsStride, 239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Scalar* res, Index resStride, 2407faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking); 2417faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez}; 2427faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez 2437faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandeztemplate <typename Scalar, typename Index, int Mode, 2447faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez int LhsStorageOrder, bool ConjugateLhs, 2457faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez int RhsStorageOrder, bool ConjugateRhs, int Version> 2467faaa9f3f0df9d23790277834d426c3d992ac3baCarlos HernandezEIGEN_DONT_INLINE void product_triangular_matrix_matrix<Scalar,Index,Mode,false, 2477faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez LhsStorageOrder,ConjugateLhs, 2487faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez RhsStorageOrder,ConjugateRhs,ColMajor,Version>::run( 2497faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez Index _rows, Index _cols, Index _depth, 2507faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez const Scalar* _lhs, Index lhsStride, 2517faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez const Scalar* _rhs, Index rhsStride, 2527faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez Scalar* res, Index resStride, 2537faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking) 254c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 255c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // strip zeros 256c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index diagSize = (std::min)(_cols,_depth); 257c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index rows = _rows; 258c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index depth = IsLower ? _depth : diagSize; 259c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index cols = IsLower ? diagSize : _cols; 260c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 261c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride); 262c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride); 263c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 264c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index kc = blocking.kc(); // cache block size along the K direction 265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index mc = (std::min)(rows,blocking.mc()); // cache block size along the M direction 266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::size_t sizeA = kc*mc; 268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::size_t sizeB = kc*cols; 269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::size_t sizeW = kc*Traits::WorkSpaceFactor; 270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA()); 272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB()); 273c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW()); 274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,RhsStorageOrder> triangularBuffer; 276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath triangularBuffer.setZero(); 277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if((Mode&ZeroDiag)==ZeroDiag) 278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath triangularBuffer.diagonal().setZero(); 279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath else 280c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath triangularBuffer.diagonal().setOnes(); 281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 282c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel; 283c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs; 284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs; 285c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder,false,true> pack_rhs_panel; 286c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 287c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(Index k2=IsLower ? 0 : depth; 288c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath IsLower ? k2<depth : k2>0; 289c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath IsLower ? k2+=kc : k2-=kc) 290c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 291c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index actual_kc = (std::min)(IsLower ? depth-k2 : k2, kc); 292c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index actual_k2 = IsLower ? k2 : k2-actual_kc; 293c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 294c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // align blocks with the end of the triangular part for trapezoidal rhs 295c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if(IsLower && (k2<cols) && (actual_k2+actual_kc>cols)) 296c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 297c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath actual_kc = cols-k2; 298c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath k2 = actual_k2 + actual_kc - kc; 299c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 301c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // remaining size 302c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index rs = IsLower ? (std::min)(cols,actual_k2) : cols - k2; 303c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // size of the triangular part 304c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index ts = (IsLower && actual_k2>=cols) ? 0 : actual_kc; 305c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 306c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Scalar* geb = blockB+ts*ts; 307c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 308c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath pack_rhs(geb, &rhs(actual_k2,IsLower ? 0 : k2), rhsStride, actual_kc, rs); 309c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 310c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // pack the triangular part of the rhs padding the unrolled blocks with zeros 311c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if(ts>0) 312c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 313c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for (Index j2=0; j2<actual_kc; j2+=SmallPanelWidth) 314c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 315c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index actualPanelWidth = std::min<Index>(actual_kc-j2, SmallPanelWidth); 316c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index actual_j2 = actual_k2 + j2; 317c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index panelOffset = IsLower ? j2+actualPanelWidth : 0; 318c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index panelLength = IsLower ? actual_kc-j2-actualPanelWidth : j2; 319c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // general part 320c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath pack_rhs_panel(blockB+j2*actual_kc, 321c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath &rhs(actual_k2+panelOffset, actual_j2), rhsStride, 322c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath panelLength, actualPanelWidth, 323c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath actual_kc, panelOffset); 324c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 325c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // append the triangular part via a temporary buffer 326c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for (Index j=0;j<actualPanelWidth;++j) 327c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 328c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if (SetDiag) 329c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath triangularBuffer.coeffRef(j,j) = rhs(actual_j2+j,actual_j2+j); 330c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for (Index k=IsLower ? j+1 : 0; IsLower ? k<actualPanelWidth : k<j; ++k) 331c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath triangularBuffer.coeffRef(k,j) = rhs(actual_j2+k,actual_j2+j); 332c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 333c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 334c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath pack_rhs_panel(blockB+j2*actual_kc, 335c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath triangularBuffer.data(), triangularBuffer.outerStride(), 336c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath actualPanelWidth, actualPanelWidth, 337c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath actual_kc, j2); 338c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 339c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 340c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 341c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for (Index i2=0; i2<rows; i2+=mc) 342c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 343c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const Index actual_mc = (std::min)(mc,rows-i2); 344c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath pack_lhs(blockA, &lhs(i2, actual_k2), lhsStride, actual_kc, actual_mc); 345c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 346c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // triangular kernel 347c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if(ts>0) 348c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 349c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for (Index j2=0; j2<actual_kc; j2+=SmallPanelWidth) 350c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 351c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index actualPanelWidth = std::min<Index>(actual_kc-j2, SmallPanelWidth); 352c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index panelLength = IsLower ? actual_kc-j2 : j2+actualPanelWidth; 353c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index blockOffset = IsLower ? j2 : 0; 354c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 355c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gebp_kernel(res+i2+(actual_k2+j2)*resStride, resStride, 356c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath blockA, blockB+j2*actual_kc, 357c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath actual_mc, panelLength, actualPanelWidth, 358c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath alpha, 359c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath actual_kc, actual_kc, // strides 360c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath blockOffset, blockOffset,// offsets 361c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath blockW); // workspace 362c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 363c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 364c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath gebp_kernel(res+i2+(IsLower ? 0 : k2)*resStride, resStride, 365c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath blockA, geb, actual_mc, actual_kc, rs, 366c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath alpha, 367c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath -1, -1, 0, 0, blockW); 368c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 369c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 370c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 371c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 372c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath/*************************************************************************** 373c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath* Wrapper to product_triangular_matrix_matrix 374c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath***************************************************************************/ 375c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 376c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<int Mode, bool LhsIsTriangular, typename Lhs, typename Rhs> 377c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct traits<TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false> > 378c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : traits<ProductBase<TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false>, Lhs, Rhs> > 379c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{}; 380c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 381c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace internal 382c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 383c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<int Mode, bool LhsIsTriangular, typename Lhs, typename Rhs> 384c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false> 385c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : public ProductBase<TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false>, Lhs, Rhs > 386c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 387c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath EIGEN_PRODUCT_PUBLIC_INTERFACE(TriangularProduct) 388c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 389c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath TriangularProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {} 390c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 3917faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const 392c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 393c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(m_lhs); 394c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(m_rhs); 395c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 396c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs) 397c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath * RhsBlasTraits::extractScalarFactor(m_rhs); 398c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 399c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar, 400c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Lhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxColsAtCompileTime,4> BlockingType; 401c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 402c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath enum { IsLower = (Mode&Lower) == Lower }; 403c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index stripedRows = ((!LhsIsTriangular) || (IsLower)) ? lhs.rows() : (std::min)(lhs.rows(),lhs.cols()); 404c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index stripedCols = ((LhsIsTriangular) || (!IsLower)) ? rhs.cols() : (std::min)(rhs.cols(),rhs.rows()); 405c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index stripedDepth = LhsIsTriangular ? ((!IsLower) ? lhs.cols() : (std::min)(lhs.cols(),lhs.rows())) 406c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath : ((IsLower) ? rhs.rows() : (std::min)(rhs.rows(),rhs.cols())); 407c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 408c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath BlockingType blocking(stripedRows, stripedCols, stripedDepth); 409c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 410c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath internal::product_triangular_matrix_matrix<Scalar, Index, 411c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Mode, LhsIsTriangular, 412c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath (internal::traits<_ActualLhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, 413c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath (internal::traits<_ActualRhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, 414c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath (internal::traits<Dest >::Flags&RowMajorBit) ? RowMajor : ColMajor> 415c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ::run( 416c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath stripedRows, stripedCols, stripedDepth, // sizes 417c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info 418c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info 419c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath &dst.coeffRef(0,0), dst.outerStride(), // result info 420c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath actualAlpha, blocking 421c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ); 422c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 423c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 424c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 425c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} // end namespace Eigen 426c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 427c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_TRIANGULAR_MATRIX_MATRIX_H 428