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
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