source: pacpussensors/trunk/Vislab/lib3dv/eigen/blas/level3_impl.h@ 140

Last change on this file since 140 was 136, checked in by ldecherf, 8 years ago

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1// This file is part of Eigen, a lightweight C++ template library
2// for linear algebra.
3//
4// Copyright (C) 2009-2010 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#include "common.h"
11
12int EIGEN_BLAS_FUNC(gemm)(char *opa, char *opb, int *m, int *n, int *k, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb, RealScalar *pbeta, RealScalar *pc, int *ldc)
13{
14// std::cerr << "in gemm " << *opa << " " << *opb << " " << *m << " " << *n << " " << *k << " " << *lda << " " << *ldb << " " << *ldc << " " << *palpha << " " << *pbeta << "\n";
15 typedef void (*functype)(DenseIndex, DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, Scalar, internal::level3_blocking<Scalar,Scalar>&, Eigen::internal::GemmParallelInfo<DenseIndex>*);
16 static functype func[12];
17
18 static bool init = false;
19 if(!init)
20 {
21 for(int k=0; k<12; ++k)
22 func[k] = 0;
23 func[NOTR | (NOTR << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,ColMajor,false,ColMajor>::run);
24 func[TR | (NOTR << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,false,ColMajor>::run);
25 func[ADJ | (NOTR << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor>::run);
26 func[NOTR | (TR << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,false,ColMajor>::run);
27 func[TR | (TR << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,RowMajor,false,ColMajor>::run);
28 func[ADJ | (TR << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,RowMajor,false,ColMajor>::run);
29 func[NOTR | (ADJ << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor>::run);
30 func[TR | (ADJ << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,RowMajor,Conj, ColMajor>::run);
31 func[ADJ | (ADJ << 2)] = (internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,RowMajor,Conj, ColMajor>::run);
32 init = true;
33 }
34
35 Scalar* a = reinterpret_cast<Scalar*>(pa);
36 Scalar* b = reinterpret_cast<Scalar*>(pb);
37 Scalar* c = reinterpret_cast<Scalar*>(pc);
38 Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
39 Scalar beta = *reinterpret_cast<Scalar*>(pbeta);
40
41 int info = 0;
42 if(OP(*opa)==INVALID) info = 1;
43 else if(OP(*opb)==INVALID) info = 2;
44 else if(*m<0) info = 3;
45 else if(*n<0) info = 4;
46 else if(*k<0) info = 5;
47 else if(*lda<std::max(1,(OP(*opa)==NOTR)?*m:*k)) info = 8;
48 else if(*ldb<std::max(1,(OP(*opb)==NOTR)?*k:*n)) info = 10;
49 else if(*ldc<std::max(1,*m)) info = 13;
50 if(info)
51 return xerbla_(SCALAR_SUFFIX_UP"GEMM ",&info,6);
52
53 if(beta!=Scalar(1))
54 {
55 if(beta==Scalar(0)) matrix(c, *m, *n, *ldc).setZero();
56 else matrix(c, *m, *n, *ldc) *= beta;
57 }
58
59 internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*m,*n,*k);
60
61 int code = OP(*opa) | (OP(*opb) << 2);
62 func[code](*m, *n, *k, a, *lda, b, *ldb, c, *ldc, alpha, blocking, 0);
63 return 0;
64}
65
66int EIGEN_BLAS_FUNC(trsm)(char *side, char *uplo, char *opa, char *diag, int *m, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb)
67{
68// std::cerr << "in trsm " << *side << " " << *uplo << " " << *opa << " " << *diag << " " << *m << "," << *n << " " << *palpha << " " << *lda << " " << *ldb<< "\n";
69 typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, internal::level3_blocking<Scalar,Scalar>&);
70 static functype func[32];
71
72 static bool init = false;
73 if(!init)
74 {
75 for(int k=0; k<32; ++k)
76 func[k] = 0;
77
78 func[NOTR | (LEFT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0, false,ColMajor,ColMajor>::run);
79 func[TR | (LEFT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0, false,RowMajor,ColMajor>::run);
80 func[ADJ | (LEFT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0, Conj, RowMajor,ColMajor>::run);
81
82 func[NOTR | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0, false,ColMajor,ColMajor>::run);
83 func[TR | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0, false,RowMajor,ColMajor>::run);
84 func[ADJ | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0, Conj, RowMajor,ColMajor>::run);
85
86 func[NOTR | (LEFT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0, false,ColMajor,ColMajor>::run);
87 func[TR | (LEFT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0, false,RowMajor,ColMajor>::run);
88 func[ADJ | (LEFT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0, Conj, RowMajor,ColMajor>::run);
89
90 func[NOTR | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0, false,ColMajor,ColMajor>::run);
91 func[TR | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0, false,RowMajor,ColMajor>::run);
92 func[ADJ | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0, Conj, RowMajor,ColMajor>::run);
93
94
95 func[NOTR | (LEFT << 2) | (UP << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,false,ColMajor,ColMajor>::run);
96 func[TR | (LEFT << 2) | (UP << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,false,RowMajor,ColMajor>::run);
97 func[ADJ | (LEFT << 2) | (UP << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,Conj, RowMajor,ColMajor>::run);
98
99 func[NOTR | (RIGHT << 2) | (UP << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,false,ColMajor,ColMajor>::run);
100 func[TR | (RIGHT << 2) | (UP << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,false,RowMajor,ColMajor>::run);
101 func[ADJ | (RIGHT << 2) | (UP << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,Conj, RowMajor,ColMajor>::run);
102
103 func[NOTR | (LEFT << 2) | (LO << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,false,ColMajor,ColMajor>::run);
104 func[TR | (LEFT << 2) | (LO << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,false,RowMajor,ColMajor>::run);
105 func[ADJ | (LEFT << 2) | (LO << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,Conj, RowMajor,ColMajor>::run);
106
107 func[NOTR | (RIGHT << 2) | (LO << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,false,ColMajor,ColMajor>::run);
108 func[TR | (RIGHT << 2) | (LO << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,false,RowMajor,ColMajor>::run);
109 func[ADJ | (RIGHT << 2) | (LO << 3) | (UNIT << 4)] = (internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,Conj, RowMajor,ColMajor>::run);
110
111 init = true;
112 }
113
114 Scalar* a = reinterpret_cast<Scalar*>(pa);
115 Scalar* b = reinterpret_cast<Scalar*>(pb);
116 Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
117
118 int info = 0;
119 if(SIDE(*side)==INVALID) info = 1;
120 else if(UPLO(*uplo)==INVALID) info = 2;
121 else if(OP(*opa)==INVALID) info = 3;
122 else if(DIAG(*diag)==INVALID) info = 4;
123 else if(*m<0) info = 5;
124 else if(*n<0) info = 6;
125 else if(*lda<std::max(1,(SIDE(*side)==LEFT)?*m:*n)) info = 9;
126 else if(*ldb<std::max(1,*m)) info = 11;
127 if(info)
128 return xerbla_(SCALAR_SUFFIX_UP"TRSM ",&info,6);
129
130 int code = OP(*opa) | (SIDE(*side) << 2) | (UPLO(*uplo) << 3) | (DIAG(*diag) << 4);
131
132 if(SIDE(*side)==LEFT)
133 {
134 internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*m);
135 func[code](*m, *n, a, *lda, b, *ldb, blocking);
136 }
137 else
138 {
139 internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*n);
140 func[code](*n, *m, a, *lda, b, *ldb, blocking);
141 }
142
143 if(alpha!=Scalar(1))
144 matrix(b,*m,*n,*ldb) *= alpha;
145
146 return 0;
147}
148
149
150// b = alpha*op(a)*b for side = 'L'or'l'
151// b = alpha*b*op(a) for side = 'R'or'r'
152int EIGEN_BLAS_FUNC(trmm)(char *side, char *uplo, char *opa, char *diag, int *m, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb)
153{
154// std::cerr << "in trmm " << *side << " " << *uplo << " " << *opa << " " << *diag << " " << *m << " " << *n << " " << *lda << " " << *ldb << " " << *palpha << "\n";
155 typedef void (*functype)(DenseIndex, DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, const Scalar&, internal::level3_blocking<Scalar,Scalar>&);
156 static functype func[32];
157 static bool init = false;
158 if(!init)
159 {
160 for(int k=0; k<32; ++k)
161 func[k] = 0;
162
163 func[NOTR | (LEFT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, true, ColMajor,false,ColMajor,false,ColMajor>::run);
164 func[TR | (LEFT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, true, RowMajor,false,ColMajor,false,ColMajor>::run);
165 func[ADJ | (LEFT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, true, RowMajor,Conj, ColMajor,false,ColMajor>::run);
166
167 func[NOTR | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, false,ColMajor,false,ColMajor,false,ColMajor>::run);
168 func[TR | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, false,ColMajor,false,RowMajor,false,ColMajor>::run);
169 func[ADJ | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, false,ColMajor,false,RowMajor,Conj, ColMajor>::run);
170
171 func[NOTR | (LEFT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, true, ColMajor,false,ColMajor,false,ColMajor>::run);
172 func[TR | (LEFT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, true, RowMajor,false,ColMajor,false,ColMajor>::run);
173 func[ADJ | (LEFT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, true, RowMajor,Conj, ColMajor,false,ColMajor>::run);
174
175 func[NOTR | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, false,ColMajor,false,ColMajor,false,ColMajor>::run);
176 func[TR | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, false,ColMajor,false,RowMajor,false,ColMajor>::run);
177 func[ADJ | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, false,ColMajor,false,RowMajor,Conj, ColMajor>::run);
178
179 func[NOTR | (LEFT << 2) | (UP << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, ColMajor,false,ColMajor,false,ColMajor>::run);
180 func[TR | (LEFT << 2) | (UP << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, RowMajor,false,ColMajor,false,ColMajor>::run);
181 func[ADJ | (LEFT << 2) | (UP << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, RowMajor,Conj, ColMajor,false,ColMajor>::run);
182
183 func[NOTR | (RIGHT << 2) | (UP << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,ColMajor,false,ColMajor>::run);
184 func[TR | (RIGHT << 2) | (UP << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,RowMajor,false,ColMajor>::run);
185 func[ADJ | (RIGHT << 2) | (UP << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,RowMajor,Conj, ColMajor>::run);
186
187 func[NOTR | (LEFT << 2) | (LO << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, ColMajor,false,ColMajor,false,ColMajor>::run);
188 func[TR | (LEFT << 2) | (LO << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, RowMajor,false,ColMajor,false,ColMajor>::run);
189 func[ADJ | (LEFT << 2) | (LO << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, RowMajor,Conj, ColMajor,false,ColMajor>::run);
190
191 func[NOTR | (RIGHT << 2) | (LO << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,ColMajor,false,ColMajor>::run);
192 func[TR | (RIGHT << 2) | (LO << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,RowMajor,false,ColMajor>::run);
193 func[ADJ | (RIGHT << 2) | (LO << 3) | (UNIT << 4)] = (internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,RowMajor,Conj, ColMajor>::run);
194
195 init = true;
196 }
197
198 Scalar* a = reinterpret_cast<Scalar*>(pa);
199 Scalar* b = reinterpret_cast<Scalar*>(pb);
200 Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
201
202 int info = 0;
203 if(SIDE(*side)==INVALID) info = 1;
204 else if(UPLO(*uplo)==INVALID) info = 2;
205 else if(OP(*opa)==INVALID) info = 3;
206 else if(DIAG(*diag)==INVALID) info = 4;
207 else if(*m<0) info = 5;
208 else if(*n<0) info = 6;
209 else if(*lda<std::max(1,(SIDE(*side)==LEFT)?*m:*n)) info = 9;
210 else if(*ldb<std::max(1,*m)) info = 11;
211 if(info)
212 return xerbla_(SCALAR_SUFFIX_UP"TRMM ",&info,6);
213
214 int code = OP(*opa) | (SIDE(*side) << 2) | (UPLO(*uplo) << 3) | (DIAG(*diag) << 4);
215
216 if(*m==0 || *n==0)
217 return 1;
218
219 // FIXME find a way to avoid this copy
220 Matrix<Scalar,Dynamic,Dynamic,ColMajor> tmp = matrix(b,*m,*n,*ldb);
221 matrix(b,*m,*n,*ldb).setZero();
222
223 if(SIDE(*side)==LEFT)
224 {
225 internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*m);
226 func[code](*m, *n, *m, a, *lda, tmp.data(), tmp.outerStride(), b, *ldb, alpha, blocking);
227 }
228 else
229 {
230 internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*n);
231 func[code](*m, *n, *n, tmp.data(), tmp.outerStride(), a, *lda, b, *ldb, alpha, blocking);
232 }
233 return 1;
234}
235
236// c = alpha*a*b + beta*c for side = 'L'or'l'
237// c = alpha*b*a + beta*c for side = 'R'or'r
238int EIGEN_BLAS_FUNC(symm)(char *side, char *uplo, int *m, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb, RealScalar *pbeta, RealScalar *pc, int *ldc)
239{
240// std::cerr << "in symm " << *side << " " << *uplo << " " << *m << "x" << *n << " lda:" << *lda << " ldb:" << *ldb << " ldc:" << *ldc << " alpha:" << *palpha << " beta:" << *pbeta << "\n";
241 Scalar* a = reinterpret_cast<Scalar*>(pa);
242 Scalar* b = reinterpret_cast<Scalar*>(pb);
243 Scalar* c = reinterpret_cast<Scalar*>(pc);
244 Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
245 Scalar beta = *reinterpret_cast<Scalar*>(pbeta);
246
247 int info = 0;
248 if(SIDE(*side)==INVALID) info = 1;
249 else if(UPLO(*uplo)==INVALID) info = 2;
250 else if(*m<0) info = 3;
251 else if(*n<0) info = 4;
252 else if(*lda<std::max(1,(SIDE(*side)==LEFT)?*m:*n)) info = 7;
253 else if(*ldb<std::max(1,*m)) info = 9;
254 else if(*ldc<std::max(1,*m)) info = 12;
255 if(info)
256 return xerbla_(SCALAR_SUFFIX_UP"SYMM ",&info,6);
257
258 if(beta!=Scalar(1))
259 {
260 if(beta==Scalar(0)) matrix(c, *m, *n, *ldc).setZero();
261 else matrix(c, *m, *n, *ldc) *= beta;
262 }
263
264 if(*m==0 || *n==0)
265 {
266 return 1;
267 }
268
269 #if ISCOMPLEX
270 // FIXME add support for symmetric complex matrix
271 int size = (SIDE(*side)==LEFT) ? (*m) : (*n);
272 Matrix<Scalar,Dynamic,Dynamic,ColMajor> matA(size,size);
273 if(UPLO(*uplo)==UP)
274 {
275 matA.triangularView<Upper>() = matrix(a,size,size,*lda);
276 matA.triangularView<Lower>() = matrix(a,size,size,*lda).transpose();
277 }
278 else if(UPLO(*uplo)==LO)
279 {
280 matA.triangularView<Lower>() = matrix(a,size,size,*lda);
281 matA.triangularView<Upper>() = matrix(a,size,size,*lda).transpose();
282 }
283 if(SIDE(*side)==LEFT)
284 matrix(c, *m, *n, *ldc) += alpha * matA * matrix(b, *m, *n, *ldb);
285 else if(SIDE(*side)==RIGHT)
286 matrix(c, *m, *n, *ldc) += alpha * matrix(b, *m, *n, *ldb) * matA;
287 #else
288 if(SIDE(*side)==LEFT)
289 if(UPLO(*uplo)==UP) internal::product_selfadjoint_matrix<Scalar, DenseIndex, RowMajor,true,false, ColMajor,false,false, ColMajor>::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha);
290 else if(UPLO(*uplo)==LO) internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,true,false, ColMajor,false,false, ColMajor>::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha);
291 else return 0;
292 else if(SIDE(*side)==RIGHT)
293 if(UPLO(*uplo)==UP) internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,false,false, RowMajor,true,false, ColMajor>::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha);
294 else if(UPLO(*uplo)==LO) internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,false,false, ColMajor,true,false, ColMajor>::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha);
295 else return 0;
296 else
297 return 0;
298 #endif
299
300 return 0;
301}
302
303// c = alpha*a*a' + beta*c for op = 'N'or'n'
304// c = alpha*a'*a + beta*c for op = 'T'or't','C'or'c'
305int EIGEN_BLAS_FUNC(syrk)(char *uplo, char *op, int *n, int *k, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pbeta, RealScalar *pc, int *ldc)
306{
307// std::cerr << "in syrk " << *uplo << " " << *op << " " << *n << " " << *k << " " << *palpha << " " << *lda << " " << *pbeta << " " << *ldc << "\n";
308 #if !ISCOMPLEX
309 typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, const Scalar&);
310 static functype func[8];
311
312 static bool init = false;
313 if(!init)
314 {
315 for(int k=0; k<8; ++k)
316 func[k] = 0;
317
318 func[NOTR | (UP << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,ColMajor,Conj, Upper>::run);
319 func[TR | (UP << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,ColMajor,Conj, Upper>::run);
320 func[ADJ | (UP << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,ColMajor,false,Upper>::run);
321
322 func[NOTR | (LO << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,ColMajor,Conj, Lower>::run);
323 func[TR | (LO << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,ColMajor,Conj, Lower>::run);
324 func[ADJ | (LO << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,ColMajor,false,Lower>::run);
325
326 init = true;
327 }
328 #endif
329
330 Scalar* a = reinterpret_cast<Scalar*>(pa);
331 Scalar* c = reinterpret_cast<Scalar*>(pc);
332 Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
333 Scalar beta = *reinterpret_cast<Scalar*>(pbeta);
334
335 int info = 0;
336 if(UPLO(*uplo)==INVALID) info = 1;
337 else if(OP(*op)==INVALID) info = 2;
338 else if(*n<0) info = 3;
339 else if(*k<0) info = 4;
340 else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 7;
341 else if(*ldc<std::max(1,*n)) info = 10;
342 if(info)
343 return xerbla_(SCALAR_SUFFIX_UP"SYRK ",&info,6);
344
345 if(beta!=Scalar(1))
346 {
347 if(UPLO(*uplo)==UP)
348 if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Upper>().setZero();
349 else matrix(c, *n, *n, *ldc).triangularView<Upper>() *= beta;
350 else
351 if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Lower>().setZero();
352 else matrix(c, *n, *n, *ldc).triangularView<Lower>() *= beta;
353 }
354
355 #if ISCOMPLEX
356 // FIXME add support for symmetric complex matrix
357 if(UPLO(*uplo)==UP)
358 {
359 if(OP(*op)==NOTR)
360 matrix(c, *n, *n, *ldc).triangularView<Upper>() += alpha * matrix(a,*n,*k,*lda) * matrix(a,*n,*k,*lda).transpose();
361 else
362 matrix(c, *n, *n, *ldc).triangularView<Upper>() += alpha * matrix(a,*k,*n,*lda).transpose() * matrix(a,*k,*n,*lda);
363 }
364 else
365 {
366 if(OP(*op)==NOTR)
367 matrix(c, *n, *n, *ldc).triangularView<Lower>() += alpha * matrix(a,*n,*k,*lda) * matrix(a,*n,*k,*lda).transpose();
368 else
369 matrix(c, *n, *n, *ldc).triangularView<Lower>() += alpha * matrix(a,*k,*n,*lda).transpose() * matrix(a,*k,*n,*lda);
370 }
371 #else
372 int code = OP(*op) | (UPLO(*uplo) << 2);
373 func[code](*n, *k, a, *lda, a, *lda, c, *ldc, alpha);
374 #endif
375
376 return 0;
377}
378
379// c = alpha*a*b' + alpha*b*a' + beta*c for op = 'N'or'n'
380// c = alpha*a'*b + alpha*b'*a + beta*c for op = 'T'or't'
381int EIGEN_BLAS_FUNC(syr2k)(char *uplo, char *op, int *n, int *k, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb, RealScalar *pbeta, RealScalar *pc, int *ldc)
382{
383 Scalar* a = reinterpret_cast<Scalar*>(pa);
384 Scalar* b = reinterpret_cast<Scalar*>(pb);
385 Scalar* c = reinterpret_cast<Scalar*>(pc);
386 Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
387 Scalar beta = *reinterpret_cast<Scalar*>(pbeta);
388
389 int info = 0;
390 if(UPLO(*uplo)==INVALID) info = 1;
391 else if(OP(*op)==INVALID) info = 2;
392 else if(*n<0) info = 3;
393 else if(*k<0) info = 4;
394 else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 7;
395 else if(*ldb<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 9;
396 else if(*ldc<std::max(1,*n)) info = 12;
397 if(info)
398 return xerbla_(SCALAR_SUFFIX_UP"SYR2K",&info,6);
399
400 if(beta!=Scalar(1))
401 {
402 if(UPLO(*uplo)==UP)
403 if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Upper>().setZero();
404 else matrix(c, *n, *n, *ldc).triangularView<Upper>() *= beta;
405 else
406 if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Lower>().setZero();
407 else matrix(c, *n, *n, *ldc).triangularView<Lower>() *= beta;
408 }
409
410 if(*k==0)
411 return 1;
412
413 if(OP(*op)==NOTR)
414 {
415 if(UPLO(*uplo)==UP)
416 {
417 matrix(c, *n, *n, *ldc).triangularView<Upper>()
418 += alpha *matrix(a, *n, *k, *lda)*matrix(b, *n, *k, *ldb).transpose()
419 + alpha*matrix(b, *n, *k, *ldb)*matrix(a, *n, *k, *lda).transpose();
420 }
421 else if(UPLO(*uplo)==LO)
422 matrix(c, *n, *n, *ldc).triangularView<Lower>()
423 += alpha*matrix(a, *n, *k, *lda)*matrix(b, *n, *k, *ldb).transpose()
424 + alpha*matrix(b, *n, *k, *ldb)*matrix(a, *n, *k, *lda).transpose();
425 }
426 else if(OP(*op)==TR || OP(*op)==ADJ)
427 {
428 if(UPLO(*uplo)==UP)
429 matrix(c, *n, *n, *ldc).triangularView<Upper>()
430 += alpha*matrix(a, *k, *n, *lda).transpose()*matrix(b, *k, *n, *ldb)
431 + alpha*matrix(b, *k, *n, *ldb).transpose()*matrix(a, *k, *n, *lda);
432 else if(UPLO(*uplo)==LO)
433 matrix(c, *n, *n, *ldc).triangularView<Lower>()
434 += alpha*matrix(a, *k, *n, *lda).transpose()*matrix(b, *k, *n, *ldb)
435 + alpha*matrix(b, *k, *n, *ldb).transpose()*matrix(a, *k, *n, *lda);
436 }
437
438 return 0;
439}
440
441
442#if ISCOMPLEX
443
444// c = alpha*a*b + beta*c for side = 'L'or'l'
445// c = alpha*b*a + beta*c for side = 'R'or'r
446int EIGEN_BLAS_FUNC(hemm)(char *side, char *uplo, int *m, int *n, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb, RealScalar *pbeta, RealScalar *pc, int *ldc)
447{
448 Scalar* a = reinterpret_cast<Scalar*>(pa);
449 Scalar* b = reinterpret_cast<Scalar*>(pb);
450 Scalar* c = reinterpret_cast<Scalar*>(pc);
451 Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
452 Scalar beta = *reinterpret_cast<Scalar*>(pbeta);
453
454// std::cerr << "in hemm " << *side << " " << *uplo << " " << *m << " " << *n << " " << alpha << " " << *lda << " " << beta << " " << *ldc << "\n";
455
456 int info = 0;
457 if(SIDE(*side)==INVALID) info = 1;
458 else if(UPLO(*uplo)==INVALID) info = 2;
459 else if(*m<0) info = 3;
460 else if(*n<0) info = 4;
461 else if(*lda<std::max(1,(SIDE(*side)==LEFT)?*m:*n)) info = 7;
462 else if(*ldb<std::max(1,*m)) info = 9;
463 else if(*ldc<std::max(1,*m)) info = 12;
464 if(info)
465 return xerbla_(SCALAR_SUFFIX_UP"HEMM ",&info,6);
466
467 if(beta==Scalar(0)) matrix(c, *m, *n, *ldc).setZero();
468 else if(beta!=Scalar(1)) matrix(c, *m, *n, *ldc) *= beta;
469
470 if(*m==0 || *n==0)
471 {
472 return 1;
473 }
474
475 if(SIDE(*side)==LEFT)
476 {
477 if(UPLO(*uplo)==UP) internal::product_selfadjoint_matrix<Scalar,DenseIndex,RowMajor,true,Conj, ColMajor,false,false, ColMajor>
478 ::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha);
479 else if(UPLO(*uplo)==LO) internal::product_selfadjoint_matrix<Scalar,DenseIndex,ColMajor,true,false, ColMajor,false,false, ColMajor>
480 ::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha);
481 else return 0;
482 }
483 else if(SIDE(*side)==RIGHT)
484 {
485 if(UPLO(*uplo)==UP) matrix(c,*m,*n,*ldc) += alpha * matrix(b,*m,*n,*ldb) * matrix(a,*n,*n,*lda).selfadjointView<Upper>();/*internal::product_selfadjoint_matrix<Scalar,DenseIndex,ColMajor,false,false, RowMajor,true,Conj, ColMajor>
486 ::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha);*/
487 else if(UPLO(*uplo)==LO) internal::product_selfadjoint_matrix<Scalar,DenseIndex,ColMajor,false,false, ColMajor,true,false, ColMajor>
488 ::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha);
489 else return 0;
490 }
491 else
492 {
493 return 0;
494 }
495
496 return 0;
497}
498
499// c = alpha*a*conj(a') + beta*c for op = 'N'or'n'
500// c = alpha*conj(a')*a + beta*c for op = 'C'or'c'
501int EIGEN_BLAS_FUNC(herk)(char *uplo, char *op, int *n, int *k, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pbeta, RealScalar *pc, int *ldc)
502{
503 typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, const Scalar&);
504 static functype func[8];
505
506 static bool init = false;
507 if(!init)
508 {
509 for(int k=0; k<8; ++k)
510 func[k] = 0;
511
512 func[NOTR | (UP << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor,Upper>::run);
513 func[ADJ | (UP << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor,Upper>::run);
514
515 func[NOTR | (LO << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor,Lower>::run);
516 func[ADJ | (LO << 2)] = (internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor,Lower>::run);
517
518 init = true;
519 }
520
521 Scalar* a = reinterpret_cast<Scalar*>(pa);
522 Scalar* c = reinterpret_cast<Scalar*>(pc);
523 RealScalar alpha = *palpha;
524 RealScalar beta = *pbeta;
525
526// std::cerr << "in herk " << *uplo << " " << *op << " " << *n << " " << *k << " " << alpha << " " << *lda << " " << beta << " " << *ldc << "\n";
527
528 int info = 0;
529 if(UPLO(*uplo)==INVALID) info = 1;
530 else if((OP(*op)==INVALID) || (OP(*op)==TR)) info = 2;
531 else if(*n<0) info = 3;
532 else if(*k<0) info = 4;
533 else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 7;
534 else if(*ldc<std::max(1,*n)) info = 10;
535 if(info)
536 return xerbla_(SCALAR_SUFFIX_UP"HERK ",&info,6);
537
538 int code = OP(*op) | (UPLO(*uplo) << 2);
539
540 if(beta!=RealScalar(1))
541 {
542 if(UPLO(*uplo)==UP)
543 if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Upper>().setZero();
544 else matrix(c, *n, *n, *ldc).triangularView<StrictlyUpper>() *= beta;
545 else
546 if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Lower>().setZero();
547 else matrix(c, *n, *n, *ldc).triangularView<StrictlyLower>() *= beta;
548
549 if(beta!=Scalar(0))
550 {
551 matrix(c, *n, *n, *ldc).diagonal().real() *= beta;
552 matrix(c, *n, *n, *ldc).diagonal().imag().setZero();
553 }
554 }
555
556 if(*k>0 && alpha!=RealScalar(0))
557 {
558 func[code](*n, *k, a, *lda, a, *lda, c, *ldc, alpha);
559 matrix(c, *n, *n, *ldc).diagonal().imag().setZero();
560 }
561 return 0;
562}
563
564// c = alpha*a*conj(b') + conj(alpha)*b*conj(a') + beta*c, for op = 'N'or'n'
565// c = alpha*conj(a')*b + conj(alpha)*conj(b')*a + beta*c, for op = 'C'or'c'
566int EIGEN_BLAS_FUNC(her2k)(char *uplo, char *op, int *n, int *k, RealScalar *palpha, RealScalar *pa, int *lda, RealScalar *pb, int *ldb, RealScalar *pbeta, RealScalar *pc, int *ldc)
567{
568 Scalar* a = reinterpret_cast<Scalar*>(pa);
569 Scalar* b = reinterpret_cast<Scalar*>(pb);
570 Scalar* c = reinterpret_cast<Scalar*>(pc);
571 Scalar alpha = *reinterpret_cast<Scalar*>(palpha);
572 RealScalar beta = *pbeta;
573
574 int info = 0;
575 if(UPLO(*uplo)==INVALID) info = 1;
576 else if((OP(*op)==INVALID) || (OP(*op)==TR)) info = 2;
577 else if(*n<0) info = 3;
578 else if(*k<0) info = 4;
579 else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 7;
580 else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 9;
581 else if(*ldc<std::max(1,*n)) info = 12;
582 if(info)
583 return xerbla_(SCALAR_SUFFIX_UP"HER2K",&info,6);
584
585 if(beta!=RealScalar(1))
586 {
587 if(UPLO(*uplo)==UP)
588 if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Upper>().setZero();
589 else matrix(c, *n, *n, *ldc).triangularView<StrictlyUpper>() *= beta;
590 else
591 if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Lower>().setZero();
592 else matrix(c, *n, *n, *ldc).triangularView<StrictlyLower>() *= beta;
593
594 if(beta!=Scalar(0))
595 {
596 matrix(c, *n, *n, *ldc).diagonal().real() *= beta;
597 matrix(c, *n, *n, *ldc).diagonal().imag().setZero();
598 }
599 }
600 else if(*k>0 && alpha!=Scalar(0))
601 matrix(c, *n, *n, *ldc).diagonal().imag().setZero();
602
603 if(*k==0)
604 return 1;
605
606 if(OP(*op)==NOTR)
607 {
608 if(UPLO(*uplo)==UP)
609 {
610 matrix(c, *n, *n, *ldc).triangularView<Upper>()
611 += alpha *matrix(a, *n, *k, *lda)*matrix(b, *n, *k, *ldb).adjoint()
612 + numext::conj(alpha)*matrix(b, *n, *k, *ldb)*matrix(a, *n, *k, *lda).adjoint();
613 }
614 else if(UPLO(*uplo)==LO)
615 matrix(c, *n, *n, *ldc).triangularView<Lower>()
616 += alpha*matrix(a, *n, *k, *lda)*matrix(b, *n, *k, *ldb).adjoint()
617 + numext::conj(alpha)*matrix(b, *n, *k, *ldb)*matrix(a, *n, *k, *lda).adjoint();
618 }
619 else if(OP(*op)==ADJ)
620 {
621 if(UPLO(*uplo)==UP)
622 matrix(c, *n, *n, *ldc).triangularView<Upper>()
623 += alpha*matrix(a, *k, *n, *lda).adjoint()*matrix(b, *k, *n, *ldb)
624 + numext::conj(alpha)*matrix(b, *k, *n, *ldb).adjoint()*matrix(a, *k, *n, *lda);
625 else if(UPLO(*uplo)==LO)
626 matrix(c, *n, *n, *ldc).triangularView<Lower>()
627 += alpha*matrix(a, *k, *n, *lda).adjoint()*matrix(b, *k, *n, *ldb)
628 + numext::conj(alpha)*matrix(b, *k, *n, *ldb).adjoint()*matrix(a, *k, *n, *lda);
629 }
630
631 return 1;
632}
633
634#endif // ISCOMPLEX
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