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SelfadjointMatrixMatrix.h
1// This file is part of Eigen, a lightweight C++ template library
2// for linear algebra.
3//
4// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
5//
6// This Source Code Form is subject to the terms of the Mozilla
7// Public License v. 2.0. If a copy of the MPL was not distributed
8// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9
10#ifndef EIGEN_SELFADJOINT_MATRIX_MATRIX_H
11#define EIGEN_SELFADJOINT_MATRIX_MATRIX_H
12
13namespace Eigen {
14
15namespace internal {
16
17// pack a selfadjoint block diagonal for use with the gebp_kernel
18template<typename Scalar, typename Index, int Pack1, int Pack2_dummy, int StorageOrder>
19struct symm_pack_lhs
20{
21 template<int BlockRows> inline
22 void pack(Scalar* blockA, const const_blas_data_mapper<Scalar,Index,StorageOrder>& lhs, Index cols, Index i, Index& count)
23 {
24 // normal copy
25 for(Index k=0; k<i; k++)
26 for(Index w=0; w<BlockRows; w++)
27 blockA[count++] = lhs(i+w,k); // normal
28 // symmetric copy
29 Index h = 0;
30 for(Index k=i; k<i+BlockRows; k++)
31 {
32 for(Index w=0; w<h; w++)
33 blockA[count++] = numext::conj(lhs(k, i+w)); // transposed
34
35 blockA[count++] = numext::real(lhs(k,k)); // real (diagonal)
36
37 for(Index w=h+1; w<BlockRows; w++)
38 blockA[count++] = lhs(i+w, k); // normal
39 ++h;
40 }
41 // transposed copy
42 for(Index k=i+BlockRows; k<cols; k++)
43 for(Index w=0; w<BlockRows; w++)
44 blockA[count++] = numext::conj(lhs(k, i+w)); // transposed
45 }
46 void operator()(Scalar* blockA, const Scalar* lhs_, Index lhsStride, Index cols, Index rows)
47 {
48 typedef typename unpacket_traits<typename packet_traits<Scalar>::type>::half HalfPacket;
49 typedef typename unpacket_traits<typename unpacket_traits<typename packet_traits<Scalar>::type>::half>::half QuarterPacket;
50 enum { PacketSize = packet_traits<Scalar>::size,
51 HalfPacketSize = unpacket_traits<HalfPacket>::size,
52 QuarterPacketSize = unpacket_traits<QuarterPacket>::size,
53 HasHalf = (int)HalfPacketSize < (int)PacketSize,
54 HasQuarter = (int)QuarterPacketSize < (int)HalfPacketSize};
55
56 const_blas_data_mapper<Scalar,Index,StorageOrder> lhs(lhs_,lhsStride);
57 Index count = 0;
58 //Index peeled_mc3 = (rows/Pack1)*Pack1;
59
60 const Index peeled_mc3 = Pack1>=3*PacketSize ? (rows/(3*PacketSize))*(3*PacketSize) : 0;
61 const Index peeled_mc2 = Pack1>=2*PacketSize ? peeled_mc3+((rows-peeled_mc3)/(2*PacketSize))*(2*PacketSize) : 0;
62 const Index peeled_mc1 = Pack1>=1*PacketSize ? peeled_mc2+((rows-peeled_mc2)/(1*PacketSize))*(1*PacketSize) : 0;
63 const Index peeled_mc_half = Pack1>=HalfPacketSize ? peeled_mc1+((rows-peeled_mc1)/(HalfPacketSize))*(HalfPacketSize) : 0;
64 const Index peeled_mc_quarter = Pack1>=QuarterPacketSize ? peeled_mc_half+((rows-peeled_mc_half)/(QuarterPacketSize))*(QuarterPacketSize) : 0;
65
66 if(Pack1>=3*PacketSize)
67 for(Index i=0; i<peeled_mc3; i+=3*PacketSize)
68 pack<3*PacketSize>(blockA, lhs, cols, i, count);
69
70 if(Pack1>=2*PacketSize)
71 for(Index i=peeled_mc3; i<peeled_mc2; i+=2*PacketSize)
72 pack<2*PacketSize>(blockA, lhs, cols, i, count);
73
74 if(Pack1>=1*PacketSize)
75 for(Index i=peeled_mc2; i<peeled_mc1; i+=1*PacketSize)
76 pack<1*PacketSize>(blockA, lhs, cols, i, count);
77
78 if(HasHalf && Pack1>=HalfPacketSize)
79 for(Index i=peeled_mc1; i<peeled_mc_half; i+=HalfPacketSize)
80 pack<HalfPacketSize>(blockA, lhs, cols, i, count);
81
82 if(HasQuarter && Pack1>=QuarterPacketSize)
83 for(Index i=peeled_mc_half; i<peeled_mc_quarter; i+=QuarterPacketSize)
84 pack<QuarterPacketSize>(blockA, lhs, cols, i, count);
85
86 // do the same with mr==1
87 for(Index i=peeled_mc_quarter; i<rows; i++)
88 {
89 for(Index k=0; k<i; k++)
90 blockA[count++] = lhs(i, k); // normal
91
92 blockA[count++] = numext::real(lhs(i, i)); // real (diagonal)
93
94 for(Index k=i+1; k<cols; k++)
95 blockA[count++] = numext::conj(lhs(k, i)); // transposed
96 }
97 }
98};
99
100template<typename Scalar, typename Index, int nr, int StorageOrder>
101struct symm_pack_rhs
102{
103 enum { PacketSize = packet_traits<Scalar>::size };
104 void operator()(Scalar* blockB, const Scalar* rhs_, Index rhsStride, Index rows, Index cols, Index k2)
105 {
106 Index end_k = k2 + rows;
107 Index count = 0;
108 const_blas_data_mapper<Scalar,Index,StorageOrder> rhs(rhs_,rhsStride);
109 Index packet_cols8 = nr>=8 ? (cols/8) * 8 : 0;
110 Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0;
111
112 // first part: normal case
113 for(Index j2=0; j2<k2; j2+=nr)
114 {
115 for(Index k=k2; k<end_k; k++)
116 {
117 blockB[count+0] = rhs(k,j2+0);
118 blockB[count+1] = rhs(k,j2+1);
119 if (nr>=4)
120 {
121 blockB[count+2] = rhs(k,j2+2);
122 blockB[count+3] = rhs(k,j2+3);
123 }
124 if (nr>=8)
125 {
126 blockB[count+4] = rhs(k,j2+4);
127 blockB[count+5] = rhs(k,j2+5);
128 blockB[count+6] = rhs(k,j2+6);
129 blockB[count+7] = rhs(k,j2+7);
130 }
131 count += nr;
132 }
133 }
134
135 // second part: diagonal block
136 Index end8 = nr>=8 ? (std::min)(k2+rows,packet_cols8) : k2;
137 if(nr>=8)
138 {
139 for(Index j2=k2; j2<end8; j2+=8)
140 {
141 // again we can split vertically in three different parts (transpose, symmetric, normal)
142 // transpose
143 for(Index k=k2; k<j2; k++)
144 {
145 blockB[count+0] = numext::conj(rhs(j2+0,k));
146 blockB[count+1] = numext::conj(rhs(j2+1,k));
147 blockB[count+2] = numext::conj(rhs(j2+2,k));
148 blockB[count+3] = numext::conj(rhs(j2+3,k));
149 blockB[count+4] = numext::conj(rhs(j2+4,k));
150 blockB[count+5] = numext::conj(rhs(j2+5,k));
151 blockB[count+6] = numext::conj(rhs(j2+6,k));
152 blockB[count+7] = numext::conj(rhs(j2+7,k));
153 count += 8;
154 }
155 // symmetric
156 Index h = 0;
157 for(Index k=j2; k<j2+8; k++)
158 {
159 // normal
160 for (Index w=0 ; w<h; ++w)
161 blockB[count+w] = rhs(k,j2+w);
162
163 blockB[count+h] = numext::real(rhs(k,k));
164
165 // transpose
166 for (Index w=h+1 ; w<8; ++w)
167 blockB[count+w] = numext::conj(rhs(j2+w,k));
168 count += 8;
169 ++h;
170 }
171 // normal
172 for(Index k=j2+8; k<end_k; k++)
173 {
174 blockB[count+0] = rhs(k,j2+0);
175 blockB[count+1] = rhs(k,j2+1);
176 blockB[count+2] = rhs(k,j2+2);
177 blockB[count+3] = rhs(k,j2+3);
178 blockB[count+4] = rhs(k,j2+4);
179 blockB[count+5] = rhs(k,j2+5);
180 blockB[count+6] = rhs(k,j2+6);
181 blockB[count+7] = rhs(k,j2+7);
182 count += 8;
183 }
184 }
185 }
186 if(nr>=4)
187 {
188 for(Index j2=end8; j2<(std::min)(k2+rows,packet_cols4); j2+=4)
189 {
190 // again we can split vertically in three different parts (transpose, symmetric, normal)
191 // transpose
192 for(Index k=k2; k<j2; k++)
193 {
194 blockB[count+0] = numext::conj(rhs(j2+0,k));
195 blockB[count+1] = numext::conj(rhs(j2+1,k));
196 blockB[count+2] = numext::conj(rhs(j2+2,k));
197 blockB[count+3] = numext::conj(rhs(j2+3,k));
198 count += 4;
199 }
200 // symmetric
201 Index h = 0;
202 for(Index k=j2; k<j2+4; k++)
203 {
204 // normal
205 for (Index w=0 ; w<h; ++w)
206 blockB[count+w] = rhs(k,j2+w);
207
208 blockB[count+h] = numext::real(rhs(k,k));
209
210 // transpose
211 for (Index w=h+1 ; w<4; ++w)
212 blockB[count+w] = numext::conj(rhs(j2+w,k));
213 count += 4;
214 ++h;
215 }
216 // normal
217 for(Index k=j2+4; k<end_k; k++)
218 {
219 blockB[count+0] = rhs(k,j2+0);
220 blockB[count+1] = rhs(k,j2+1);
221 blockB[count+2] = rhs(k,j2+2);
222 blockB[count+3] = rhs(k,j2+3);
223 count += 4;
224 }
225 }
226 }
227
228 // third part: transposed
229 if(nr>=8)
230 {
231 for(Index j2=k2+rows; j2<packet_cols8; j2+=8)
232 {
233 for(Index k=k2; k<end_k; k++)
234 {
235 blockB[count+0] = numext::conj(rhs(j2+0,k));
236 blockB[count+1] = numext::conj(rhs(j2+1,k));
237 blockB[count+2] = numext::conj(rhs(j2+2,k));
238 blockB[count+3] = numext::conj(rhs(j2+3,k));
239 blockB[count+4] = numext::conj(rhs(j2+4,k));
240 blockB[count+5] = numext::conj(rhs(j2+5,k));
241 blockB[count+6] = numext::conj(rhs(j2+6,k));
242 blockB[count+7] = numext::conj(rhs(j2+7,k));
243 count += 8;
244 }
245 }
246 }
247 if(nr>=4)
248 {
249 for(Index j2=(std::max)(packet_cols8,k2+rows); j2<packet_cols4; j2+=4)
250 {
251 for(Index k=k2; k<end_k; k++)
252 {
253 blockB[count+0] = numext::conj(rhs(j2+0,k));
254 blockB[count+1] = numext::conj(rhs(j2+1,k));
255 blockB[count+2] = numext::conj(rhs(j2+2,k));
256 blockB[count+3] = numext::conj(rhs(j2+3,k));
257 count += 4;
258 }
259 }
260 }
261
262 // copy the remaining columns one at a time (=> the same with nr==1)
263 for(Index j2=packet_cols4; j2<cols; ++j2)
264 {
265 // transpose
266 Index half = (std::min)(end_k,j2);
267 for(Index k=k2; k<half; k++)
268 {
269 blockB[count] = numext::conj(rhs(j2,k));
270 count += 1;
271 }
272
273 if(half==j2 && half<k2+rows)
274 {
275 blockB[count] = numext::real(rhs(j2,j2));
276 count += 1;
277 }
278 else
279 half--;
280
281 // normal
282 for(Index k=half+1; k<k2+rows; k++)
283 {
284 blockB[count] = rhs(k,j2);
285 count += 1;
286 }
287 }
288 }
289};
290
291/* Optimized selfadjoint matrix * matrix (_SYMM) product built on top of
292 * the general matrix matrix product.
293 */
294template <typename Scalar, typename Index,
295 int LhsStorageOrder, bool LhsSelfAdjoint, bool ConjugateLhs,
296 int RhsStorageOrder, bool RhsSelfAdjoint, bool ConjugateRhs,
297 int ResStorageOrder, int ResInnerStride>
298struct product_selfadjoint_matrix;
299
300template <typename Scalar, typename Index,
301 int LhsStorageOrder, bool LhsSelfAdjoint, bool ConjugateLhs,
302 int RhsStorageOrder, bool RhsSelfAdjoint, bool ConjugateRhs,
303 int ResInnerStride>
304struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,LhsSelfAdjoint,ConjugateLhs, RhsStorageOrder,RhsSelfAdjoint,ConjugateRhs,RowMajor,ResInnerStride>
305{
306
307 static EIGEN_STRONG_INLINE void run(
308 Index rows, Index cols,
309 const Scalar* lhs, Index lhsStride,
310 const Scalar* rhs, Index rhsStride,
311 Scalar* res, Index resIncr, Index resStride,
312 const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
313 {
314 product_selfadjoint_matrix<Scalar, Index,
315 EIGEN_LOGICAL_XOR(RhsSelfAdjoint,RhsStorageOrder==RowMajor) ? ColMajor : RowMajor,
316 RhsSelfAdjoint, NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(RhsSelfAdjoint,ConjugateRhs),
317 EIGEN_LOGICAL_XOR(LhsSelfAdjoint,LhsStorageOrder==RowMajor) ? ColMajor : RowMajor,
318 LhsSelfAdjoint, NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(LhsSelfAdjoint,ConjugateLhs),
319 ColMajor,ResInnerStride>
320 ::run(cols, rows, rhs, rhsStride, lhs, lhsStride, res, resIncr, resStride, alpha, blocking);
321 }
322};
323
324template <typename Scalar, typename Index,
325 int LhsStorageOrder, bool ConjugateLhs,
326 int RhsStorageOrder, bool ConjugateRhs,
327 int ResInnerStride>
328struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,true,ConjugateLhs, RhsStorageOrder,false,ConjugateRhs,ColMajor,ResInnerStride>
329{
330
331 static EIGEN_DONT_INLINE void run(
332 Index rows, Index cols,
333 const Scalar* lhs_, Index lhsStride,
334 const Scalar* rhs_, Index rhsStride,
335 Scalar* res, Index resIncr, Index resStride,
336 const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking);
337};
338
339template <typename Scalar, typename Index,
340 int LhsStorageOrder, bool ConjugateLhs,
341 int RhsStorageOrder, bool ConjugateRhs,
342 int ResInnerStride>
343EIGEN_DONT_INLINE void product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,true,ConjugateLhs, RhsStorageOrder,false,ConjugateRhs,ColMajor,ResInnerStride>::run(
344 Index rows, Index cols,
345 const Scalar* lhs_, Index lhsStride,
346 const Scalar* rhs_, Index rhsStride,
347 Scalar* res_, Index resIncr, Index resStride,
348 const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
349 {
350 Index size = rows;
351
352 typedef gebp_traits<Scalar,Scalar> Traits;
353
354 typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
355 typedef const_blas_data_mapper<Scalar, Index, (LhsStorageOrder == RowMajor) ? ColMajor : RowMajor> LhsTransposeMapper;
356 typedef const_blas_data_mapper<Scalar, Index, RhsStorageOrder> RhsMapper;
357 typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor, Unaligned, ResInnerStride> ResMapper;
358 LhsMapper lhs(lhs_,lhsStride);
359 LhsTransposeMapper lhs_transpose(lhs_,lhsStride);
360 RhsMapper rhs(rhs_,rhsStride);
361 ResMapper res(res_, resStride, resIncr);
362
363 Index kc = blocking.kc(); // cache block size along the K direction
364 Index mc = (std::min)(rows,blocking.mc()); // cache block size along the M direction
365 // kc must be smaller than mc
366 kc = (std::min)(kc,mc);
367 std::size_t sizeA = kc*mc;
368 std::size_t sizeB = kc*cols;
369 ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
370 ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
371
372 gebp_kernel<Scalar, Scalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
373 symm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
374 gemm_pack_rhs<Scalar, Index, RhsMapper, Traits::nr,RhsStorageOrder> pack_rhs;
375 gemm_pack_lhs<Scalar, Index, LhsTransposeMapper, Traits::mr, Traits::LhsProgress, typename Traits::LhsPacket4Packing, LhsStorageOrder==RowMajor?ColMajor:RowMajor, true> pack_lhs_transposed;
376
377 for(Index k2=0; k2<size; k2+=kc)
378 {
379 const Index actual_kc = (std::min)(k2+kc,size)-k2;
380
381 // we have selected one row panel of rhs and one column panel of lhs
382 // pack rhs's panel into a sequential chunk of memory
383 // and expand each coeff to a constant packet for further reuse
384 pack_rhs(blockB, rhs.getSubMapper(k2,0), actual_kc, cols);
385
386 // the select lhs's panel has to be split in three different parts:
387 // 1 - the transposed panel above the diagonal block => transposed packed copy
388 // 2 - the diagonal block => special packed copy
389 // 3 - the panel below the diagonal block => generic packed copy
390 for(Index i2=0; i2<k2; i2+=mc)
391 {
392 const Index actual_mc = (std::min)(i2+mc,k2)-i2;
393 // transposed packed copy
394 pack_lhs_transposed(blockA, lhs_transpose.getSubMapper(i2, k2), actual_kc, actual_mc);
395
396 gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
397 }
398 // the block diagonal
399 {
400 const Index actual_mc = (std::min)(k2+kc,size)-k2;
401 // symmetric packed copy
402 pack_lhs(blockA, &lhs(k2,k2), lhsStride, actual_kc, actual_mc);
403
404 gebp_kernel(res.getSubMapper(k2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
405 }
406
407 for(Index i2=k2+kc; i2<size; i2+=mc)
408 {
409 const Index actual_mc = (std::min)(i2+mc,size)-i2;
410 gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, typename Traits::LhsPacket4Packing, LhsStorageOrder,false>()
411 (blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
412
413 gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
414 }
415 }
416 }
417
418// matrix * selfadjoint product
419template <typename Scalar, typename Index,
420 int LhsStorageOrder, bool ConjugateLhs,
421 int RhsStorageOrder, bool ConjugateRhs,
422 int ResInnerStride>
423struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,false,ConjugateLhs, RhsStorageOrder,true,ConjugateRhs,ColMajor,ResInnerStride>
424{
425
426 static EIGEN_DONT_INLINE void run(
427 Index rows, Index cols,
428 const Scalar* lhs_, Index lhsStride,
429 const Scalar* rhs_, Index rhsStride,
430 Scalar* res, Index resIncr, Index resStride,
431 const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking);
432};
433
434template <typename Scalar, typename Index,
435 int LhsStorageOrder, bool ConjugateLhs,
436 int RhsStorageOrder, bool ConjugateRhs,
437 int ResInnerStride>
438EIGEN_DONT_INLINE void product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,false,ConjugateLhs, RhsStorageOrder,true,ConjugateRhs,ColMajor,ResInnerStride>::run(
439 Index rows, Index cols,
440 const Scalar* lhs_, Index lhsStride,
441 const Scalar* rhs_, Index rhsStride,
442 Scalar* res_, Index resIncr, Index resStride,
443 const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
444 {
445 Index size = cols;
446
447 typedef gebp_traits<Scalar,Scalar> Traits;
448
449 typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
450 typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor, Unaligned, ResInnerStride> ResMapper;
451 LhsMapper lhs(lhs_,lhsStride);
452 ResMapper res(res_,resStride, resIncr);
453
454 Index kc = blocking.kc(); // cache block size along the K direction
455 Index mc = (std::min)(rows,blocking.mc()); // cache block size along the M direction
456 std::size_t sizeA = kc*mc;
457 std::size_t sizeB = kc*cols;
458 ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
459 ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
460
461 gebp_kernel<Scalar, Scalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
462 gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, typename Traits::LhsPacket4Packing, LhsStorageOrder> pack_lhs;
463 symm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs;
464
465 for(Index k2=0; k2<size; k2+=kc)
466 {
467 const Index actual_kc = (std::min)(k2+kc,size)-k2;
468
469 pack_rhs(blockB, rhs_, rhsStride, actual_kc, cols, k2);
470
471 // => GEPP
472 for(Index i2=0; i2<rows; i2+=mc)
473 {
474 const Index actual_mc = (std::min)(i2+mc,rows)-i2;
475 pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
476
477 gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
478 }
479 }
480 }
481
482} // end namespace internal
483
484/***************************************************************************
485* Wrapper to product_selfadjoint_matrix
486***************************************************************************/
487
488namespace internal {
489
490template<typename Lhs, int LhsMode, typename Rhs, int RhsMode>
491struct selfadjoint_product_impl<Lhs,LhsMode,false,Rhs,RhsMode,false>
492{
493 typedef typename Product<Lhs,Rhs>::Scalar Scalar;
494
495 typedef internal::blas_traits<Lhs> LhsBlasTraits;
496 typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
497 typedef internal::blas_traits<Rhs> RhsBlasTraits;
498 typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
499
500 enum {
501 LhsIsUpper = (LhsMode&(Upper|Lower))==Upper,
502 LhsIsSelfAdjoint = (LhsMode&SelfAdjoint)==SelfAdjoint,
503 RhsIsUpper = (RhsMode&(Upper|Lower))==Upper,
504 RhsIsSelfAdjoint = (RhsMode&SelfAdjoint)==SelfAdjoint
505 };
506
507 template<typename Dest>
508 static void run(Dest &dst, const Lhs &a_lhs, const Rhs &a_rhs, const Scalar& alpha)
509 {
510 eigen_assert(dst.rows()==a_lhs.rows() && dst.cols()==a_rhs.cols());
511
512 typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(a_lhs);
513 typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(a_rhs);
514
515 Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(a_lhs)
516 * RhsBlasTraits::extractScalarFactor(a_rhs);
517
518 typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar,
519 Lhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxColsAtCompileTime,1> BlockingType;
520
521 BlockingType blocking(lhs.rows(), rhs.cols(), lhs.cols(), 1, false);
522
523 internal::product_selfadjoint_matrix<Scalar, Index,
524 EIGEN_LOGICAL_XOR(LhsIsUpper,internal::traits<Lhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, LhsIsSelfAdjoint,
525 NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(LhsIsUpper,bool(LhsBlasTraits::NeedToConjugate)),
526 EIGEN_LOGICAL_XOR(RhsIsUpper,internal::traits<Rhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, RhsIsSelfAdjoint,
527 NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(RhsIsUpper,bool(RhsBlasTraits::NeedToConjugate)),
528 internal::traits<Dest>::Flags&RowMajorBit ? RowMajor : ColMajor,
529 Dest::InnerStrideAtCompileTime>
530 ::run(
531 lhs.rows(), rhs.cols(), // sizes
532 &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info
533 &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info
534 &dst.coeffRef(0,0), dst.innerStride(), dst.outerStride(), // result info
535 actualAlpha, blocking // alpha
536 );
537 }
538};
539
540} // end namespace internal
541
542} // end namespace Eigen
543
544#endif // EIGEN_SELFADJOINT_MATRIX_MATRIX_H
Eigen::MatrixBase
Base class for all dense matrices, vectors, and expressions.
Definition MatrixBase.h:50
Eigen::Product
Expression of the product of two arbitrary matrices or vectors.
Definition Product.h:75
Eigen::internal::const_blas_data_mapper
Definition BlasUtil.h:389
Eigen::internal::gemm_blocking_space
Definition GeneralMatrixMatrix.h:248
Eigen::SelfAdjoint
@ SelfAdjoint
Used in BandMatrix and SelfAdjointView to indicate that the matrix is self-adjoint.
Definition Constants.h:225
Eigen::Lower
@ Lower
View matrix as a lower triangular matrix.
Definition Constants.h:209
Eigen::Upper
@ Upper
View matrix as an upper triangular matrix.
Definition Constants.h:211
Eigen::ColMajor
@ ColMajor
Storage order is column major (see TopicStorageOrders).
Definition Constants.h:319
Eigen::RowMajor
@ RowMajor
Storage order is row major (see TopicStorageOrders).
Definition Constants.h:321
Eigen::RowMajorBit
const unsigned int RowMajorBit
for a matrix, this means that the storage order is row-major.
Definition Constants.h:66
Eigen
Namespace containing all symbols from the Eigen library.
Definition LDLT.h:16
Eigen::Index
EIGEN_DEFAULT_DENSE_INDEX_TYPE Index
The Index type as used for the API.
Definition Meta.h:74
Eigen::NumTraits
Holds information about the various numeric (i.e.
Definition NumTraits.h:236
Eigen::half
Definition Half.h:140
Eigen::internal::blas_traits
Definition BlasUtil.h:403
Eigen::internal::gebp_kernel
Definition GeneralBlockPanelKernel.h:1058
Eigen::internal::packet_traits
Definition GenericPacketMath.h:107
Eigen::internal::product_selfadjoint_matrix
Definition SelfadjointMatrixMatrix.h:298
Eigen::internal::selfadjoint_product_impl
Definition ProductEvaluators.h:793
Eigen::internal::symm_pack_lhs
Definition SelfadjointMatrixMatrix.h:20
Eigen::internal::symm_pack_rhs
Definition SelfadjointMatrixMatrix.h:102
Eigen::internal::traits
Definition ForwardDeclarations.h:17
Eigen::internal::true_type
Definition Meta.h:96
Eigen::internal::unpacket_traits
Definition GenericPacketMath.h:133
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