1 2 /* 3 Defines the basic matrix operations for sequential dense. 4 */ 5 6 #include <../src/mat/impls/dense/seq/dense.h> /*I "petscmat.h" I*/ 7 #include <petscblaslapack.h> 8 9 #include <../src/mat/impls/aij/seq/aij.h> 10 11 static PetscErrorCode MatSeqDenseSymmetrize_Private(Mat A, PetscBool hermitian) 12 { 13 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 14 PetscInt j, k, n = A->rmap->n; 15 16 PetscFunctionBegin; 17 if (A->rmap->n != A->cmap->n) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Cannot symmetrize a rectangular matrix"); 18 if (!hermitian) { 19 for (k=0;k<n;k++) { 20 for (j=k;j<n;j++) { 21 mat->v[j*mat->lda + k] = mat->v[k*mat->lda + j]; 22 } 23 } 24 } else { 25 for (k=0;k<n;k++) { 26 for (j=k;j<n;j++) { 27 mat->v[j*mat->lda + k] = PetscConj(mat->v[k*mat->lda + j]); 28 } 29 } 30 } 31 PetscFunctionReturn(0); 32 } 33 34 PETSC_EXTERN PetscErrorCode MatSeqDenseInvertFactors_Private(Mat A) 35 { 36 #if defined(PETSC_MISSING_LAPACK_POTRF) 37 PetscFunctionBegin; 38 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRF - Lapack routine is unavailable."); 39 #else 40 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 41 PetscErrorCode ierr; 42 PetscBLASInt info,n; 43 44 PetscFunctionBegin; 45 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 46 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 47 if (A->factortype == MAT_FACTOR_LU) { 48 if (!mat->pivots) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Pivots not present"); 49 if (!mat->fwork) { 50 mat->lfwork = n; 51 ierr = PetscMalloc1(mat->lfwork,&mat->fwork);CHKERRQ(ierr); 52 ierr = PetscLogObjectMemory((PetscObject)A,mat->lfwork*sizeof(PetscBLASInt));CHKERRQ(ierr); 53 } 54 PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&mat->lfwork,&info)); 55 ierr = PetscLogFlops((1.0*A->cmap->n*A->cmap->n*A->cmap->n)/3.0);CHKERRQ(ierr); /* TODO CHECK FLOPS */ 56 } else if (A->factortype == MAT_FACTOR_CHOLESKY) { 57 if (A->spd) { 58 PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_("L",&n,mat->v,&mat->lda,&info)); 59 ierr = MatSeqDenseSymmetrize_Private(A,PETSC_TRUE);CHKERRQ(ierr); 60 #if defined (PETSC_USE_COMPLEX) 61 } else if (A->hermitian) { 62 if (!mat->pivots) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Pivots not present"); 63 if (!mat->fwork) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Fwork not present"); 64 PetscStackCallBLAS("LAPACKhetri",LAPACKhetri_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&info)); 65 ierr = MatSeqDenseSymmetrize_Private(A,PETSC_TRUE);CHKERRQ(ierr); 66 #endif 67 } else { /* symmetric case */ 68 if (!mat->pivots) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Pivots not present"); 69 if (!mat->fwork) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Fwork not present"); 70 PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&info)); 71 ierr = MatSeqDenseSymmetrize_Private(A,PETSC_FALSE);CHKERRQ(ierr); 72 } 73 if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_CH_ZRPVT,"Bad Inversion: zero pivot in row %D",(PetscInt)info-1); 74 ierr = PetscLogFlops((1.0*A->cmap->n*A->cmap->n*A->cmap->n)/3.0);CHKERRQ(ierr); /* TODO CHECK FLOPS */ 75 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve"); 76 #endif 77 78 A->ops->solve = NULL; 79 A->ops->matsolve = NULL; 80 A->ops->solvetranspose = NULL; 81 A->ops->matsolvetranspose = NULL; 82 A->ops->solveadd = NULL; 83 A->ops->solvetransposeadd = NULL; 84 A->factortype = MAT_FACTOR_NONE; 85 ierr = PetscFree(A->solvertype);CHKERRQ(ierr); 86 PetscFunctionReturn(0); 87 } 88 89 PetscErrorCode MatZeroRowsColumns_SeqDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 90 { 91 PetscErrorCode ierr; 92 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 93 PetscInt m = l->lda, n = A->cmap->n,r = A->rmap->n, i,j; 94 PetscScalar *slot,*bb; 95 const PetscScalar *xx; 96 97 PetscFunctionBegin; 98 #if defined(PETSC_USE_DEBUG) 99 for (i=0; i<N; i++) { 100 if (rows[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row requested to be zeroed"); 101 if (rows[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D requested to be zeroed greater than or equal number of rows %D",rows[i],A->rmap->n); 102 if (rows[i] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Col %D requested to be zeroed greater than or equal number of cols %D",rows[i],A->cmap->n); 103 } 104 #endif 105 106 /* fix right hand side if needed */ 107 if (x && b) { 108 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 109 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 110 for (i=0; i<N; i++) bb[rows[i]] = diag*xx[rows[i]]; 111 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 112 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 113 } 114 115 for (i=0; i<N; i++) { 116 slot = l->v + rows[i]*m; 117 ierr = PetscMemzero(slot,r*sizeof(PetscScalar));CHKERRQ(ierr); 118 } 119 for (i=0; i<N; i++) { 120 slot = l->v + rows[i]; 121 for (j=0; j<n; j++) { *slot = 0.0; slot += m;} 122 } 123 if (diag != 0.0) { 124 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only coded for square matrices"); 125 for (i=0; i<N; i++) { 126 slot = l->v + (m+1)*rows[i]; 127 *slot = diag; 128 } 129 } 130 PetscFunctionReturn(0); 131 } 132 133 PetscErrorCode MatPtAPNumeric_SeqDense_SeqDense(Mat A,Mat P,Mat C) 134 { 135 Mat_SeqDense *c = (Mat_SeqDense*)(C->data); 136 PetscErrorCode ierr; 137 138 PetscFunctionBegin; 139 ierr = MatMatMultNumeric_SeqDense_SeqDense(A,P,c->ptapwork);CHKERRQ(ierr); 140 ierr = MatTransposeMatMultNumeric_SeqDense_SeqDense(P,c->ptapwork,C);CHKERRQ(ierr); 141 PetscFunctionReturn(0); 142 } 143 144 PetscErrorCode MatPtAPSymbolic_SeqDense_SeqDense(Mat A,Mat P,PetscReal fill,Mat *C) 145 { 146 Mat_SeqDense *c; 147 PetscErrorCode ierr; 148 149 PetscFunctionBegin; 150 ierr = MatCreateSeqDense(PetscObjectComm((PetscObject)A),P->cmap->N,P->cmap->N,NULL,C);CHKERRQ(ierr); 151 c = (Mat_SeqDense*)((*C)->data); 152 ierr = MatCreateSeqDense(PetscObjectComm((PetscObject)A),A->rmap->N,P->cmap->N,NULL,&c->ptapwork);CHKERRQ(ierr); 153 PetscFunctionReturn(0); 154 } 155 156 PETSC_INTERN PetscErrorCode MatPtAP_SeqDense_SeqDense(Mat A,Mat P,MatReuse reuse,PetscReal fill,Mat *C) 157 { 158 PetscErrorCode ierr; 159 160 PetscFunctionBegin; 161 if (reuse == MAT_INITIAL_MATRIX) { 162 ierr = MatPtAPSymbolic_SeqDense_SeqDense(A,P,fill,C);CHKERRQ(ierr); 163 } 164 ierr = PetscLogEventBegin(MAT_PtAPNumeric,A,P,0,0);CHKERRQ(ierr); 165 ierr = (*(*C)->ops->ptapnumeric)(A,P,*C);CHKERRQ(ierr); 166 ierr = PetscLogEventEnd(MAT_PtAPNumeric,A,P,0,0);CHKERRQ(ierr); 167 PetscFunctionReturn(0); 168 } 169 170 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 171 { 172 Mat B = NULL; 173 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 174 Mat_SeqDense *b; 175 PetscErrorCode ierr; 176 PetscInt *ai=a->i,*aj=a->j,m=A->rmap->N,n=A->cmap->N,i; 177 MatScalar *av=a->a; 178 PetscBool isseqdense; 179 180 PetscFunctionBegin; 181 if (reuse == MAT_REUSE_MATRIX) { 182 ierr = PetscObjectTypeCompare((PetscObject)*newmat,MATSEQDENSE,&isseqdense);CHKERRQ(ierr); 183 if (!isseqdense) SETERRQ1(PetscObjectComm((PetscObject)*newmat),PETSC_ERR_USER,"Cannot reuse matrix of type %s",((PetscObject)(*newmat))->type); 184 } 185 if (reuse != MAT_REUSE_MATRIX) { 186 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 187 ierr = MatSetSizes(B,m,n,m,n);CHKERRQ(ierr); 188 ierr = MatSetType(B,MATSEQDENSE);CHKERRQ(ierr); 189 ierr = MatSeqDenseSetPreallocation(B,NULL);CHKERRQ(ierr); 190 b = (Mat_SeqDense*)(B->data); 191 } else { 192 b = (Mat_SeqDense*)((*newmat)->data); 193 ierr = PetscMemzero(b->v,m*n*sizeof(PetscScalar));CHKERRQ(ierr); 194 } 195 for (i=0; i<m; i++) { 196 PetscInt j; 197 for (j=0;j<ai[1]-ai[0];j++) { 198 b->v[*aj*m+i] = *av; 199 aj++; 200 av++; 201 } 202 ai++; 203 } 204 205 if (reuse == MAT_INPLACE_MATRIX) { 206 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 207 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 208 ierr = MatHeaderReplace(A,&B);CHKERRQ(ierr); 209 } else { 210 if (B) *newmat = B; 211 ierr = MatAssemblyBegin(*newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 212 ierr = MatAssemblyEnd(*newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 213 } 214 PetscFunctionReturn(0); 215 } 216 217 PETSC_INTERN PetscErrorCode MatConvert_SeqDense_SeqAIJ(Mat A, MatType newtype,MatReuse reuse,Mat *newmat) 218 { 219 Mat B; 220 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 221 PetscErrorCode ierr; 222 PetscInt i, j; 223 PetscInt *rows, *nnz; 224 MatScalar *aa = a->v, *vals; 225 226 PetscFunctionBegin; 227 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 228 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 229 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 230 ierr = PetscCalloc3(A->rmap->n,&rows,A->rmap->n,&nnz,A->rmap->n,&vals);CHKERRQ(ierr); 231 for (j=0; j<A->cmap->n; j++) { 232 for (i=0; i<A->rmap->n; i++) if (aa[i] != 0.0 || i == j) ++nnz[i]; 233 aa += a->lda; 234 } 235 ierr = MatSeqAIJSetPreallocation(B,PETSC_DETERMINE,nnz);CHKERRQ(ierr); 236 aa = a->v; 237 for (j=0; j<A->cmap->n; j++) { 238 PetscInt numRows = 0; 239 for (i=0; i<A->rmap->n; i++) if (aa[i] != 0.0 || i == j) {rows[numRows] = i; vals[numRows++] = aa[i];} 240 ierr = MatSetValues(B,numRows,rows,1,&j,vals,INSERT_VALUES);CHKERRQ(ierr); 241 aa += a->lda; 242 } 243 ierr = PetscFree3(rows,nnz,vals);CHKERRQ(ierr); 244 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 245 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 246 247 if (reuse == MAT_INPLACE_MATRIX) { 248 ierr = MatHeaderReplace(A,&B);CHKERRQ(ierr); 249 } else { 250 *newmat = B; 251 } 252 PetscFunctionReturn(0); 253 } 254 255 static PetscErrorCode MatAXPY_SeqDense(Mat Y,PetscScalar alpha,Mat X,MatStructure str) 256 { 257 Mat_SeqDense *x = (Mat_SeqDense*)X->data,*y = (Mat_SeqDense*)Y->data; 258 PetscScalar oalpha = alpha; 259 PetscInt j; 260 PetscBLASInt N,m,ldax,lday,one = 1; 261 PetscErrorCode ierr; 262 263 PetscFunctionBegin; 264 ierr = PetscBLASIntCast(X->rmap->n*X->cmap->n,&N);CHKERRQ(ierr); 265 ierr = PetscBLASIntCast(X->rmap->n,&m);CHKERRQ(ierr); 266 ierr = PetscBLASIntCast(x->lda,&ldax);CHKERRQ(ierr); 267 ierr = PetscBLASIntCast(y->lda,&lday);CHKERRQ(ierr); 268 if (ldax>m || lday>m) { 269 for (j=0; j<X->cmap->n; j++) { 270 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&m,&oalpha,x->v+j*ldax,&one,y->v+j*lday,&one)); 271 } 272 } else { 273 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&N,&oalpha,x->v,&one,y->v,&one)); 274 } 275 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 276 ierr = PetscLogFlops(PetscMax(2*N-1,0));CHKERRQ(ierr); 277 PetscFunctionReturn(0); 278 } 279 280 static PetscErrorCode MatGetInfo_SeqDense(Mat A,MatInfoType flag,MatInfo *info) 281 { 282 PetscInt N = A->rmap->n*A->cmap->n; 283 284 PetscFunctionBegin; 285 info->block_size = 1.0; 286 info->nz_allocated = (double)N; 287 info->nz_used = (double)N; 288 info->nz_unneeded = (double)0; 289 info->assemblies = (double)A->num_ass; 290 info->mallocs = 0; 291 info->memory = ((PetscObject)A)->mem; 292 info->fill_ratio_given = 0; 293 info->fill_ratio_needed = 0; 294 info->factor_mallocs = 0; 295 PetscFunctionReturn(0); 296 } 297 298 static PetscErrorCode MatScale_SeqDense(Mat A,PetscScalar alpha) 299 { 300 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 301 PetscScalar oalpha = alpha; 302 PetscErrorCode ierr; 303 PetscBLASInt one = 1,j,nz,lda; 304 305 PetscFunctionBegin; 306 ierr = PetscBLASIntCast(a->lda,&lda);CHKERRQ(ierr); 307 if (lda>A->rmap->n) { 308 ierr = PetscBLASIntCast(A->rmap->n,&nz);CHKERRQ(ierr); 309 for (j=0; j<A->cmap->n; j++) { 310 PetscStackCallBLAS("BLASscal",BLASscal_(&nz,&oalpha,a->v+j*lda,&one)); 311 } 312 } else { 313 ierr = PetscBLASIntCast(A->rmap->n*A->cmap->n,&nz);CHKERRQ(ierr); 314 PetscStackCallBLAS("BLASscal",BLASscal_(&nz,&oalpha,a->v,&one)); 315 } 316 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 317 PetscFunctionReturn(0); 318 } 319 320 static PetscErrorCode MatIsHermitian_SeqDense(Mat A,PetscReal rtol,PetscBool *fl) 321 { 322 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 323 PetscInt i,j,m = A->rmap->n,N; 324 PetscScalar *v = a->v; 325 326 PetscFunctionBegin; 327 *fl = PETSC_FALSE; 328 if (A->rmap->n != A->cmap->n) PetscFunctionReturn(0); 329 N = a->lda; 330 331 for (i=0; i<m; i++) { 332 for (j=i+1; j<m; j++) { 333 if (PetscAbsScalar(v[i+j*N] - PetscConj(v[j+i*N])) > rtol) PetscFunctionReturn(0); 334 } 335 } 336 *fl = PETSC_TRUE; 337 PetscFunctionReturn(0); 338 } 339 340 static PetscErrorCode MatDuplicateNoCreate_SeqDense(Mat newi,Mat A,MatDuplicateOption cpvalues) 341 { 342 Mat_SeqDense *mat = (Mat_SeqDense*)A->data,*l; 343 PetscErrorCode ierr; 344 PetscInt lda = (PetscInt)mat->lda,j,m; 345 346 PetscFunctionBegin; 347 ierr = PetscLayoutReference(A->rmap,&newi->rmap);CHKERRQ(ierr); 348 ierr = PetscLayoutReference(A->cmap,&newi->cmap);CHKERRQ(ierr); 349 ierr = MatSeqDenseSetPreallocation(newi,NULL);CHKERRQ(ierr); 350 if (cpvalues == MAT_COPY_VALUES) { 351 l = (Mat_SeqDense*)newi->data; 352 if (lda>A->rmap->n) { 353 m = A->rmap->n; 354 for (j=0; j<A->cmap->n; j++) { 355 ierr = PetscMemcpy(l->v+j*m,mat->v+j*lda,m*sizeof(PetscScalar));CHKERRQ(ierr); 356 } 357 } else { 358 ierr = PetscMemcpy(l->v,mat->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 359 } 360 } 361 newi->assembled = PETSC_TRUE; 362 PetscFunctionReturn(0); 363 } 364 365 static PetscErrorCode MatDuplicate_SeqDense(Mat A,MatDuplicateOption cpvalues,Mat *newmat) 366 { 367 PetscErrorCode ierr; 368 369 PetscFunctionBegin; 370 ierr = MatCreate(PetscObjectComm((PetscObject)A),newmat);CHKERRQ(ierr); 371 ierr = MatSetSizes(*newmat,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 372 ierr = MatSetType(*newmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 373 ierr = MatDuplicateNoCreate_SeqDense(*newmat,A,cpvalues);CHKERRQ(ierr); 374 PetscFunctionReturn(0); 375 } 376 377 378 static PetscErrorCode MatLUFactor_SeqDense(Mat,IS,IS,const MatFactorInfo*); 379 380 static PetscErrorCode MatLUFactorNumeric_SeqDense(Mat fact,Mat A,const MatFactorInfo *info_dummy) 381 { 382 MatFactorInfo info; 383 PetscErrorCode ierr; 384 385 PetscFunctionBegin; 386 ierr = MatDuplicateNoCreate_SeqDense(fact,A,MAT_COPY_VALUES);CHKERRQ(ierr); 387 ierr = MatLUFactor_SeqDense(fact,0,0,&info);CHKERRQ(ierr); 388 PetscFunctionReturn(0); 389 } 390 391 static PetscErrorCode MatSolve_SeqDense(Mat A,Vec xx,Vec yy) 392 { 393 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 394 PetscErrorCode ierr; 395 const PetscScalar *x; 396 PetscScalar *y; 397 PetscBLASInt one = 1,info,m; 398 399 PetscFunctionBegin; 400 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 401 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 402 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 403 ierr = PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 404 if (A->factortype == MAT_FACTOR_LU) { 405 #if defined(PETSC_MISSING_LAPACK_GETRS) 406 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable."); 407 #else 408 PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("N",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info)); 409 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"GETRS - Bad solve"); 410 #endif 411 } else if (A->factortype == MAT_FACTOR_CHOLESKY) { 412 #if defined(PETSC_MISSING_LAPACK_POTRS) 413 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable."); 414 #else 415 if (A->spd) { 416 PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info)); 417 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve"); 418 #if defined (PETSC_USE_COMPLEX) 419 } else if (A->hermitian) { 420 PetscStackCallBLAS("LAPACKhetrs",LAPACKhetrs_("L",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info)); 421 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"HETRS Bad solve"); 422 #endif 423 } else { /* symmetric case */ 424 PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info)); 425 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"SYTRS Bad solve"); 426 } 427 #endif 428 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve"); 429 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 430 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 431 ierr = PetscLogFlops(2.0*A->cmap->n*A->cmap->n - A->cmap->n);CHKERRQ(ierr); 432 PetscFunctionReturn(0); 433 } 434 435 static PetscErrorCode MatMatSolve_SeqDense(Mat A,Mat B,Mat X) 436 { 437 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 438 PetscErrorCode ierr; 439 PetscScalar *b,*x; 440 PetscInt n; 441 PetscBLASInt nrhs,info,m; 442 PetscBool flg; 443 444 PetscFunctionBegin; 445 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 446 ierr = PetscObjectTypeCompareAny((PetscObject)B,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); 447 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix"); 448 ierr = PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); 449 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix"); 450 451 ierr = MatGetSize(B,NULL,&n);CHKERRQ(ierr); 452 ierr = PetscBLASIntCast(n,&nrhs);CHKERRQ(ierr); 453 ierr = MatDenseGetArray(B,&b);CHKERRQ(ierr); 454 ierr = MatDenseGetArray(X,&x);CHKERRQ(ierr); 455 456 ierr = PetscMemcpy(x,b,m*nrhs*sizeof(PetscScalar));CHKERRQ(ierr); 457 458 if (A->factortype == MAT_FACTOR_LU) { 459 #if defined(PETSC_MISSING_LAPACK_GETRS) 460 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable."); 461 #else 462 PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("N",&m,&nrhs,mat->v,&mat->lda,mat->pivots,x,&m,&info)); 463 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"GETRS - Bad solve"); 464 #endif 465 } else if (A->factortype == MAT_FACTOR_CHOLESKY) { 466 #if defined(PETSC_MISSING_LAPACK_POTRS) 467 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable."); 468 #else 469 if (A->spd) { 470 PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&nrhs,mat->v,&mat->lda,x,&m,&info)); 471 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve"); 472 #if defined (PETSC_USE_COMPLEX) 473 } else if (A->hermitian) { 474 PetscStackCallBLAS("LAPACKhetrs",LAPACKhetrs_("L",&m,&nrhs,mat->v,&mat->lda,mat->pivots,x,&m,&info)); 475 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"HETRS Bad solve"); 476 #endif 477 } else { /* symmetric case */ 478 PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&m,&nrhs,mat->v,&mat->lda,mat->pivots,x,&m,&info)); 479 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"SYTRS Bad solve"); 480 } 481 #endif 482 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve"); 483 484 ierr = MatDenseRestoreArray(B,&b);CHKERRQ(ierr); 485 ierr = MatDenseRestoreArray(X,&x);CHKERRQ(ierr); 486 ierr = PetscLogFlops(nrhs*(2.0*m*m - m));CHKERRQ(ierr); 487 PetscFunctionReturn(0); 488 } 489 490 static PetscErrorCode MatSolveTranspose_SeqDense(Mat A,Vec xx,Vec yy) 491 { 492 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 493 PetscErrorCode ierr; 494 const PetscScalar *x; 495 PetscScalar *y; 496 PetscBLASInt one = 1,info,m; 497 498 PetscFunctionBegin; 499 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 500 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 501 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 502 ierr = PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 503 if (A->factortype == MAT_FACTOR_LU) { 504 #if defined(PETSC_MISSING_LAPACK_GETRS) 505 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable."); 506 #else 507 PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("T",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info)); 508 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS - Bad solve"); 509 #endif 510 } else if (A->factortype == MAT_FACTOR_CHOLESKY) { 511 #if defined(PETSC_MISSING_LAPACK_POTRS) 512 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable."); 513 #else 514 if (A->spd) { 515 PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info)); 516 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve"); 517 #if defined (PETSC_USE_COMPLEX) 518 } else if (A->hermitian) { 519 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSolveTranspose with Cholesky/Hermitian not available"); 520 #endif 521 } else { /* symmetric case */ 522 PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info)); 523 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"SYTRS Bad solve"); 524 } 525 #endif 526 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve"); 527 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 528 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 529 ierr = PetscLogFlops(2.0*A->cmap->n*A->cmap->n - A->cmap->n);CHKERRQ(ierr); 530 PetscFunctionReturn(0); 531 } 532 533 static PetscErrorCode MatSolveAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 534 { 535 PetscErrorCode ierr; 536 const PetscScalar *x; 537 PetscScalar *y,sone = 1.0; 538 Vec tmp = 0; 539 540 PetscFunctionBegin; 541 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 542 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 543 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 544 if (yy == zz) { 545 ierr = VecDuplicate(yy,&tmp);CHKERRQ(ierr); 546 ierr = PetscLogObjectParent((PetscObject)A,(PetscObject)tmp);CHKERRQ(ierr); 547 ierr = VecCopy(yy,tmp);CHKERRQ(ierr); 548 } 549 ierr = MatSolve_SeqDense(A,xx,yy);CHKERRQ(ierr); 550 if (tmp) { 551 ierr = VecAXPY(yy,sone,tmp);CHKERRQ(ierr); 552 ierr = VecDestroy(&tmp);CHKERRQ(ierr); 553 } else { 554 ierr = VecAXPY(yy,sone,zz);CHKERRQ(ierr); 555 } 556 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 557 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 558 ierr = PetscLogFlops(A->cmap->n);CHKERRQ(ierr); 559 PetscFunctionReturn(0); 560 } 561 562 static PetscErrorCode MatSolveTransposeAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 563 { 564 PetscErrorCode ierr; 565 const PetscScalar *x; 566 PetscScalar *y,sone = 1.0; 567 Vec tmp = NULL; 568 569 PetscFunctionBegin; 570 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 571 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 572 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 573 if (yy == zz) { 574 ierr = VecDuplicate(yy,&tmp);CHKERRQ(ierr); 575 ierr = PetscLogObjectParent((PetscObject)A,(PetscObject)tmp);CHKERRQ(ierr); 576 ierr = VecCopy(yy,tmp);CHKERRQ(ierr); 577 } 578 ierr = MatSolveTranspose_SeqDense(A,xx,yy);CHKERRQ(ierr); 579 if (tmp) { 580 ierr = VecAXPY(yy,sone,tmp);CHKERRQ(ierr); 581 ierr = VecDestroy(&tmp);CHKERRQ(ierr); 582 } else { 583 ierr = VecAXPY(yy,sone,zz);CHKERRQ(ierr); 584 } 585 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 586 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 587 ierr = PetscLogFlops(A->cmap->n);CHKERRQ(ierr); 588 PetscFunctionReturn(0); 589 } 590 591 /* ---------------------------------------------------------------*/ 592 /* COMMENT: I have chosen to hide row permutation in the pivots, 593 rather than put it in the Mat->row slot.*/ 594 static PetscErrorCode MatLUFactor_SeqDense(Mat A,IS row,IS col,const MatFactorInfo *minfo) 595 { 596 #if defined(PETSC_MISSING_LAPACK_GETRF) 597 PetscFunctionBegin; 598 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRF - Lapack routine is unavailable."); 599 #else 600 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 601 PetscErrorCode ierr; 602 PetscBLASInt n,m,info; 603 604 PetscFunctionBegin; 605 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 606 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 607 if (!mat->pivots) { 608 ierr = PetscMalloc1(A->rmap->n,&mat->pivots);CHKERRQ(ierr); 609 ierr = PetscLogObjectMemory((PetscObject)A,A->rmap->n*sizeof(PetscBLASInt));CHKERRQ(ierr); 610 } 611 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 612 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 613 PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&m,&n,mat->v,&mat->lda,mat->pivots,&info)); 614 ierr = PetscFPTrapPop();CHKERRQ(ierr); 615 616 if (info<0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad argument to LU factorization"); 617 if (info>0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Bad LU factorization"); 618 619 A->ops->solve = MatSolve_SeqDense; 620 A->ops->matsolve = MatMatSolve_SeqDense; 621 A->ops->solvetranspose = MatSolveTranspose_SeqDense; 622 A->ops->solveadd = MatSolveAdd_SeqDense; 623 A->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense; 624 A->factortype = MAT_FACTOR_LU; 625 626 ierr = PetscFree(A->solvertype);CHKERRQ(ierr); 627 ierr = PetscStrallocpy(MATSOLVERPETSC,&A->solvertype);CHKERRQ(ierr); 628 629 ierr = PetscLogFlops((2.0*A->cmap->n*A->cmap->n*A->cmap->n)/3);CHKERRQ(ierr); 630 #endif 631 PetscFunctionReturn(0); 632 } 633 634 /* Cholesky as L*L^T or L*D*L^T and the symmetric/hermitian complex variants */ 635 static PetscErrorCode MatCholeskyFactor_SeqDense(Mat A,IS perm,const MatFactorInfo *factinfo) 636 { 637 #if defined(PETSC_MISSING_LAPACK_POTRF) 638 PetscFunctionBegin; 639 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRF - Lapack routine is unavailable."); 640 #else 641 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 642 PetscErrorCode ierr; 643 PetscBLASInt info,n; 644 645 PetscFunctionBegin; 646 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 647 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 648 if (A->spd) { 649 PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_("L",&n,mat->v,&mat->lda,&info)); 650 #if defined (PETSC_USE_COMPLEX) 651 } else if (A->hermitian) { 652 if (!mat->pivots) { 653 ierr = PetscMalloc1(A->rmap->n,&mat->pivots);CHKERRQ(ierr); 654 ierr = PetscLogObjectMemory((PetscObject)A,A->rmap->n*sizeof(PetscBLASInt));CHKERRQ(ierr); 655 } 656 if (!mat->fwork) { 657 PetscScalar dummy; 658 659 mat->lfwork = -1; 660 PetscStackCallBLAS("LAPACKhetrf",LAPACKhetrf_("L",&n,mat->v,&mat->lda,mat->pivots,&dummy,&mat->lfwork,&info)); 661 mat->lfwork = (PetscInt)PetscRealPart(dummy); 662 ierr = PetscMalloc1(mat->lfwork,&mat->fwork);CHKERRQ(ierr); 663 ierr = PetscLogObjectMemory((PetscObject)A,mat->lfwork*sizeof(PetscBLASInt));CHKERRQ(ierr); 664 } 665 PetscStackCallBLAS("LAPACKhetrf",LAPACKhetrf_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&mat->lfwork,&info)); 666 #endif 667 } else { /* symmetric case */ 668 if (!mat->pivots) { 669 ierr = PetscMalloc1(A->rmap->n,&mat->pivots);CHKERRQ(ierr); 670 ierr = PetscLogObjectMemory((PetscObject)A,A->rmap->n*sizeof(PetscBLASInt));CHKERRQ(ierr); 671 } 672 if (!mat->fwork) { 673 PetscScalar dummy; 674 675 mat->lfwork = -1; 676 PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&n,mat->v,&mat->lda,mat->pivots,&dummy,&mat->lfwork,&info)); 677 mat->lfwork = (PetscInt)PetscRealPart(dummy); 678 ierr = PetscMalloc1(mat->lfwork,&mat->fwork);CHKERRQ(ierr); 679 ierr = PetscLogObjectMemory((PetscObject)A,mat->lfwork*sizeof(PetscBLASInt));CHKERRQ(ierr); 680 } 681 PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&mat->lfwork,&info)); 682 } 683 if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_CH_ZRPVT,"Bad factorization: zero pivot in row %D",(PetscInt)info-1); 684 685 A->ops->solve = MatSolve_SeqDense; 686 A->ops->matsolve = MatMatSolve_SeqDense; 687 A->ops->solvetranspose = MatSolveTranspose_SeqDense; 688 A->ops->solveadd = MatSolveAdd_SeqDense; 689 A->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense; 690 A->factortype = MAT_FACTOR_CHOLESKY; 691 692 ierr = PetscFree(A->solvertype);CHKERRQ(ierr); 693 ierr = PetscStrallocpy(MATSOLVERPETSC,&A->solvertype);CHKERRQ(ierr); 694 695 ierr = PetscLogFlops((1.0*A->cmap->n*A->cmap->n*A->cmap->n)/3.0);CHKERRQ(ierr); 696 #endif 697 PetscFunctionReturn(0); 698 } 699 700 701 PetscErrorCode MatCholeskyFactorNumeric_SeqDense(Mat fact,Mat A,const MatFactorInfo *info_dummy) 702 { 703 PetscErrorCode ierr; 704 MatFactorInfo info; 705 706 PetscFunctionBegin; 707 info.fill = 1.0; 708 709 ierr = MatDuplicateNoCreate_SeqDense(fact,A,MAT_COPY_VALUES);CHKERRQ(ierr); 710 ierr = MatCholeskyFactor_SeqDense(fact,0,&info);CHKERRQ(ierr); 711 PetscFunctionReturn(0); 712 } 713 714 static PetscErrorCode MatCholeskyFactorSymbolic_SeqDense(Mat fact,Mat A,IS row,const MatFactorInfo *info) 715 { 716 PetscFunctionBegin; 717 fact->assembled = PETSC_TRUE; 718 fact->preallocated = PETSC_TRUE; 719 fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqDense; 720 fact->ops->solve = MatSolve_SeqDense; 721 fact->ops->matsolve = MatMatSolve_SeqDense; 722 fact->ops->solvetranspose = MatSolveTranspose_SeqDense; 723 fact->ops->solveadd = MatSolveAdd_SeqDense; 724 fact->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense; 725 PetscFunctionReturn(0); 726 } 727 728 static PetscErrorCode MatLUFactorSymbolic_SeqDense(Mat fact,Mat A,IS row,IS col,const MatFactorInfo *info) 729 { 730 PetscFunctionBegin; 731 fact->preallocated = PETSC_TRUE; 732 fact->assembled = PETSC_TRUE; 733 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqDense; 734 fact->ops->solve = MatSolve_SeqDense; 735 fact->ops->matsolve = MatMatSolve_SeqDense; 736 fact->ops->solvetranspose = MatSolveTranspose_SeqDense; 737 fact->ops->solveadd = MatSolveAdd_SeqDense; 738 fact->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense; 739 PetscFunctionReturn(0); 740 } 741 742 PETSC_INTERN PetscErrorCode MatGetFactor_seqdense_petsc(Mat A,MatFactorType ftype,Mat *fact) 743 { 744 PetscErrorCode ierr; 745 746 PetscFunctionBegin; 747 ierr = MatCreate(PetscObjectComm((PetscObject)A),fact);CHKERRQ(ierr); 748 ierr = MatSetSizes(*fact,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 749 ierr = MatSetType(*fact,((PetscObject)A)->type_name);CHKERRQ(ierr); 750 if (ftype == MAT_FACTOR_LU) { 751 (*fact)->ops->lufactorsymbolic = MatLUFactorSymbolic_SeqDense; 752 } else { 753 (*fact)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqDense; 754 } 755 (*fact)->factortype = ftype; 756 757 ierr = PetscFree((*fact)->solvertype);CHKERRQ(ierr); 758 ierr = PetscStrallocpy(MATSOLVERPETSC,&(*fact)->solvertype);CHKERRQ(ierr); 759 PetscFunctionReturn(0); 760 } 761 762 /* ------------------------------------------------------------------*/ 763 static PetscErrorCode MatSOR_SeqDense(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal shift,PetscInt its,PetscInt lits,Vec xx) 764 { 765 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 766 PetscScalar *x,*v = mat->v,zero = 0.0,xt; 767 const PetscScalar *b; 768 PetscErrorCode ierr; 769 PetscInt m = A->rmap->n,i; 770 PetscBLASInt o = 1,bm; 771 772 PetscFunctionBegin; 773 if (shift == -1) shift = 0.0; /* negative shift indicates do not error on zero diagonal; this code never zeros on zero diagonal */ 774 ierr = PetscBLASIntCast(m,&bm);CHKERRQ(ierr); 775 if (flag & SOR_ZERO_INITIAL_GUESS) { 776 /* this is a hack fix, should have another version without the second BLASdotu */ 777 ierr = VecSet(xx,zero);CHKERRQ(ierr); 778 } 779 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 780 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 781 its = its*lits; 782 if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 783 while (its--) { 784 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 785 for (i=0; i<m; i++) { 786 PetscStackCallBLAS("BLASdotu",xt = b[i] - BLASdotu_(&bm,v+i,&bm,x,&o)); 787 x[i] = (1. - omega)*x[i] + omega*(xt+v[i + i*m]*x[i])/(v[i + i*m]+shift); 788 } 789 } 790 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 791 for (i=m-1; i>=0; i--) { 792 PetscStackCallBLAS("BLASdotu",xt = b[i] - BLASdotu_(&bm,v+i,&bm,x,&o)); 793 x[i] = (1. - omega)*x[i] + omega*(xt+v[i + i*m]*x[i])/(v[i + i*m]+shift); 794 } 795 } 796 } 797 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 798 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 799 PetscFunctionReturn(0); 800 } 801 802 /* -----------------------------------------------------------------*/ 803 PETSC_INTERN PetscErrorCode MatMultTranspose_SeqDense(Mat A,Vec xx,Vec yy) 804 { 805 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 806 const PetscScalar *v = mat->v,*x; 807 PetscScalar *y; 808 PetscErrorCode ierr; 809 PetscBLASInt m, n,_One=1; 810 PetscScalar _DOne=1.0,_DZero=0.0; 811 812 PetscFunctionBegin; 813 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 814 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 815 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 816 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 817 if (!A->rmap->n || !A->cmap->n) { 818 PetscBLASInt i; 819 for (i=0; i<n; i++) y[i] = 0.0; 820 } else { 821 PetscStackCallBLAS("BLASgemv",BLASgemv_("T",&m,&n,&_DOne,v,&mat->lda,x,&_One,&_DZero,y,&_One)); 822 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->cmap->n);CHKERRQ(ierr); 823 } 824 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 825 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 826 PetscFunctionReturn(0); 827 } 828 829 PETSC_INTERN PetscErrorCode MatMult_SeqDense(Mat A,Vec xx,Vec yy) 830 { 831 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 832 PetscScalar *y,_DOne=1.0,_DZero=0.0; 833 PetscErrorCode ierr; 834 PetscBLASInt m, n, _One=1; 835 const PetscScalar *v = mat->v,*x; 836 837 PetscFunctionBegin; 838 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 839 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 840 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 841 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 842 if (!A->rmap->n || !A->cmap->n) { 843 PetscBLASInt i; 844 for (i=0; i<m; i++) y[i] = 0.0; 845 } else { 846 PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DZero,y,&_One)); 847 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->rmap->n);CHKERRQ(ierr); 848 } 849 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 850 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 851 PetscFunctionReturn(0); 852 } 853 854 PETSC_INTERN PetscErrorCode MatMultAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 855 { 856 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 857 const PetscScalar *v = mat->v,*x; 858 PetscScalar *y,_DOne=1.0; 859 PetscErrorCode ierr; 860 PetscBLASInt m, n, _One=1; 861 862 PetscFunctionBegin; 863 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 864 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 865 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 866 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 867 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 868 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 869 PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One)); 870 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 871 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 872 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n);CHKERRQ(ierr); 873 PetscFunctionReturn(0); 874 } 875 876 static PetscErrorCode MatMultTransposeAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 877 { 878 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 879 const PetscScalar *v = mat->v,*x; 880 PetscScalar *y; 881 PetscErrorCode ierr; 882 PetscBLASInt m, n, _One=1; 883 PetscScalar _DOne=1.0; 884 885 PetscFunctionBegin; 886 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 887 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 888 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 889 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 890 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 891 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 892 PetscStackCallBLAS("BLASgemv",BLASgemv_("T",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One)); 893 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 894 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 895 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n);CHKERRQ(ierr); 896 PetscFunctionReturn(0); 897 } 898 899 /* -----------------------------------------------------------------*/ 900 static PetscErrorCode MatGetRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals) 901 { 902 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 903 PetscScalar *v; 904 PetscErrorCode ierr; 905 PetscInt i; 906 907 PetscFunctionBegin; 908 *ncols = A->cmap->n; 909 if (cols) { 910 ierr = PetscMalloc1(A->cmap->n+1,cols);CHKERRQ(ierr); 911 for (i=0; i<A->cmap->n; i++) (*cols)[i] = i; 912 } 913 if (vals) { 914 ierr = PetscMalloc1(A->cmap->n+1,vals);CHKERRQ(ierr); 915 v = mat->v + row; 916 for (i=0; i<A->cmap->n; i++) {(*vals)[i] = *v; v += mat->lda;} 917 } 918 PetscFunctionReturn(0); 919 } 920 921 static PetscErrorCode MatRestoreRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals) 922 { 923 PetscErrorCode ierr; 924 925 PetscFunctionBegin; 926 if (cols) {ierr = PetscFree(*cols);CHKERRQ(ierr);} 927 if (vals) {ierr = PetscFree(*vals);CHKERRQ(ierr); } 928 PetscFunctionReturn(0); 929 } 930 /* ----------------------------------------------------------------*/ 931 static PetscErrorCode MatSetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],const PetscScalar v[],InsertMode addv) 932 { 933 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 934 PetscInt i,j,idx=0; 935 936 PetscFunctionBegin; 937 if (!mat->roworiented) { 938 if (addv == INSERT_VALUES) { 939 for (j=0; j<n; j++) { 940 if (indexn[j] < 0) {idx += m; continue;} 941 #if defined(PETSC_USE_DEBUG) 942 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 943 #endif 944 for (i=0; i<m; i++) { 945 if (indexm[i] < 0) {idx++; continue;} 946 #if defined(PETSC_USE_DEBUG) 947 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 948 #endif 949 mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++]; 950 } 951 } 952 } else { 953 for (j=0; j<n; j++) { 954 if (indexn[j] < 0) {idx += m; continue;} 955 #if defined(PETSC_USE_DEBUG) 956 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 957 #endif 958 for (i=0; i<m; i++) { 959 if (indexm[i] < 0) {idx++; continue;} 960 #if defined(PETSC_USE_DEBUG) 961 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 962 #endif 963 mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++]; 964 } 965 } 966 } 967 } else { 968 if (addv == INSERT_VALUES) { 969 for (i=0; i<m; i++) { 970 if (indexm[i] < 0) { idx += n; continue;} 971 #if defined(PETSC_USE_DEBUG) 972 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 973 #endif 974 for (j=0; j<n; j++) { 975 if (indexn[j] < 0) { idx++; continue;} 976 #if defined(PETSC_USE_DEBUG) 977 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 978 #endif 979 mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++]; 980 } 981 } 982 } else { 983 for (i=0; i<m; i++) { 984 if (indexm[i] < 0) { idx += n; continue;} 985 #if defined(PETSC_USE_DEBUG) 986 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 987 #endif 988 for (j=0; j<n; j++) { 989 if (indexn[j] < 0) { idx++; continue;} 990 #if defined(PETSC_USE_DEBUG) 991 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 992 #endif 993 mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++]; 994 } 995 } 996 } 997 } 998 PetscFunctionReturn(0); 999 } 1000 1001 static PetscErrorCode MatGetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],PetscScalar v[]) 1002 { 1003 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1004 PetscInt i,j; 1005 1006 PetscFunctionBegin; 1007 /* row-oriented output */ 1008 for (i=0; i<m; i++) { 1009 if (indexm[i] < 0) {v += n;continue;} 1010 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D requested larger than number rows %D",indexm[i],A->rmap->n); 1011 for (j=0; j<n; j++) { 1012 if (indexn[j] < 0) {v++; continue;} 1013 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column %D requested larger than number columns %D",indexn[j],A->cmap->n); 1014 *v++ = mat->v[indexn[j]*mat->lda + indexm[i]]; 1015 } 1016 } 1017 PetscFunctionReturn(0); 1018 } 1019 1020 /* -----------------------------------------------------------------*/ 1021 1022 static PetscErrorCode MatLoad_SeqDense(Mat newmat,PetscViewer viewer) 1023 { 1024 Mat_SeqDense *a; 1025 PetscErrorCode ierr; 1026 PetscInt *scols,i,j,nz,header[4]; 1027 int fd; 1028 PetscMPIInt size; 1029 PetscInt *rowlengths = 0,M,N,*cols,grows,gcols; 1030 PetscScalar *vals,*svals,*v,*w; 1031 MPI_Comm comm; 1032 1033 PetscFunctionBegin; 1034 /* force binary viewer to load .info file if it has not yet done so */ 1035 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 1036 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 1037 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1038 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor"); 1039 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1040 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 1041 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Not matrix object"); 1042 M = header[1]; N = header[2]; nz = header[3]; 1043 1044 /* set global size if not set already*/ 1045 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) { 1046 ierr = MatSetSizes(newmat,M,N,M,N);CHKERRQ(ierr); 1047 } else { 1048 /* if sizes and type are already set, check if the vector global sizes are correct */ 1049 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 1050 if (M != grows || N != gcols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different length (%d, %d) than the input matrix (%d, %d)",M,N,grows,gcols); 1051 } 1052 a = (Mat_SeqDense*)newmat->data; 1053 if (!a->user_alloc) { 1054 ierr = MatSeqDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1055 } 1056 1057 if (nz == MATRIX_BINARY_FORMAT_DENSE) { /* matrix in file is dense */ 1058 a = (Mat_SeqDense*)newmat->data; 1059 v = a->v; 1060 /* Allocate some temp space to read in the values and then flip them 1061 from row major to column major */ 1062 ierr = PetscMalloc1(M*N > 0 ? M*N : 1,&w);CHKERRQ(ierr); 1063 /* read in nonzero values */ 1064 ierr = PetscBinaryRead(fd,w,M*N,PETSC_SCALAR);CHKERRQ(ierr); 1065 /* now flip the values and store them in the matrix*/ 1066 for (j=0; j<N; j++) { 1067 for (i=0; i<M; i++) { 1068 *v++ =w[i*N+j]; 1069 } 1070 } 1071 ierr = PetscFree(w);CHKERRQ(ierr); 1072 } else { 1073 /* read row lengths */ 1074 ierr = PetscMalloc1(M+1,&rowlengths);CHKERRQ(ierr); 1075 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 1076 1077 a = (Mat_SeqDense*)newmat->data; 1078 v = a->v; 1079 1080 /* read column indices and nonzeros */ 1081 ierr = PetscMalloc1(nz+1,&scols);CHKERRQ(ierr); 1082 cols = scols; 1083 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 1084 ierr = PetscMalloc1(nz+1,&svals);CHKERRQ(ierr); 1085 vals = svals; 1086 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1087 1088 /* insert into matrix */ 1089 for (i=0; i<M; i++) { 1090 for (j=0; j<rowlengths[i]; j++) v[i+M*scols[j]] = svals[j]; 1091 svals += rowlengths[i]; scols += rowlengths[i]; 1092 } 1093 ierr = PetscFree(vals);CHKERRQ(ierr); 1094 ierr = PetscFree(cols);CHKERRQ(ierr); 1095 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1096 } 1097 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1098 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1099 PetscFunctionReturn(0); 1100 } 1101 1102 static PetscErrorCode MatView_SeqDense_ASCII(Mat A,PetscViewer viewer) 1103 { 1104 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1105 PetscErrorCode ierr; 1106 PetscInt i,j; 1107 const char *name; 1108 PetscScalar *v; 1109 PetscViewerFormat format; 1110 #if defined(PETSC_USE_COMPLEX) 1111 PetscBool allreal = PETSC_TRUE; 1112 #endif 1113 1114 PetscFunctionBegin; 1115 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1116 if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1117 PetscFunctionReturn(0); /* do nothing for now */ 1118 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 1119 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1120 for (i=0; i<A->rmap->n; i++) { 1121 v = a->v + i; 1122 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 1123 for (j=0; j<A->cmap->n; j++) { 1124 #if defined(PETSC_USE_COMPLEX) 1125 if (PetscRealPart(*v) != 0.0 && PetscImaginaryPart(*v) != 0.0) { 1126 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i) ",j,(double)PetscRealPart(*v),(double)PetscImaginaryPart(*v));CHKERRQ(ierr); 1127 } else if (PetscRealPart(*v)) { 1128 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",j,(double)PetscRealPart(*v));CHKERRQ(ierr); 1129 } 1130 #else 1131 if (*v) { 1132 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",j,(double)*v);CHKERRQ(ierr); 1133 } 1134 #endif 1135 v += a->lda; 1136 } 1137 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1138 } 1139 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1140 } else { 1141 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1142 #if defined(PETSC_USE_COMPLEX) 1143 /* determine if matrix has all real values */ 1144 v = a->v; 1145 for (i=0; i<A->rmap->n*A->cmap->n; i++) { 1146 if (PetscImaginaryPart(v[i])) { allreal = PETSC_FALSE; break;} 1147 } 1148 #endif 1149 if (format == PETSC_VIEWER_ASCII_MATLAB) { 1150 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 1151 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",A->rmap->n,A->cmap->n);CHKERRQ(ierr); 1152 ierr = PetscViewerASCIIPrintf(viewer,"%s = zeros(%D,%D);\n",name,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 1153 ierr = PetscViewerASCIIPrintf(viewer,"%s = [\n",name);CHKERRQ(ierr); 1154 } 1155 1156 for (i=0; i<A->rmap->n; i++) { 1157 v = a->v + i; 1158 for (j=0; j<A->cmap->n; j++) { 1159 #if defined(PETSC_USE_COMPLEX) 1160 if (allreal) { 1161 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)PetscRealPart(*v));CHKERRQ(ierr); 1162 } else { 1163 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e + %18.16ei ",(double)PetscRealPart(*v),(double)PetscImaginaryPart(*v));CHKERRQ(ierr); 1164 } 1165 #else 1166 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)*v);CHKERRQ(ierr); 1167 #endif 1168 v += a->lda; 1169 } 1170 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1171 } 1172 if (format == PETSC_VIEWER_ASCII_MATLAB) { 1173 ierr = PetscViewerASCIIPrintf(viewer,"];\n");CHKERRQ(ierr); 1174 } 1175 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1176 } 1177 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1178 PetscFunctionReturn(0); 1179 } 1180 1181 static PetscErrorCode MatView_SeqDense_Binary(Mat A,PetscViewer viewer) 1182 { 1183 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1184 PetscErrorCode ierr; 1185 int fd; 1186 PetscInt ict,j,n = A->cmap->n,m = A->rmap->n,i,*col_lens,nz = m*n; 1187 PetscScalar *v,*anonz,*vals; 1188 PetscViewerFormat format; 1189 1190 PetscFunctionBegin; 1191 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1192 1193 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1194 if (format == PETSC_VIEWER_NATIVE) { 1195 /* store the matrix as a dense matrix */ 1196 ierr = PetscMalloc1(4,&col_lens);CHKERRQ(ierr); 1197 1198 col_lens[0] = MAT_FILE_CLASSID; 1199 col_lens[1] = m; 1200 col_lens[2] = n; 1201 col_lens[3] = MATRIX_BINARY_FORMAT_DENSE; 1202 1203 ierr = PetscBinaryWrite(fd,col_lens,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1204 ierr = PetscFree(col_lens);CHKERRQ(ierr); 1205 1206 /* write out matrix, by rows */ 1207 ierr = PetscMalloc1(m*n+1,&vals);CHKERRQ(ierr); 1208 v = a->v; 1209 for (j=0; j<n; j++) { 1210 for (i=0; i<m; i++) { 1211 vals[j + i*n] = *v++; 1212 } 1213 } 1214 ierr = PetscBinaryWrite(fd,vals,n*m,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 1215 ierr = PetscFree(vals);CHKERRQ(ierr); 1216 } else { 1217 ierr = PetscMalloc1(4+nz,&col_lens);CHKERRQ(ierr); 1218 1219 col_lens[0] = MAT_FILE_CLASSID; 1220 col_lens[1] = m; 1221 col_lens[2] = n; 1222 col_lens[3] = nz; 1223 1224 /* store lengths of each row and write (including header) to file */ 1225 for (i=0; i<m; i++) col_lens[4+i] = n; 1226 ierr = PetscBinaryWrite(fd,col_lens,4+m,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1227 1228 /* Possibly should write in smaller increments, not whole matrix at once? */ 1229 /* store column indices (zero start index) */ 1230 ict = 0; 1231 for (i=0; i<m; i++) { 1232 for (j=0; j<n; j++) col_lens[ict++] = j; 1233 } 1234 ierr = PetscBinaryWrite(fd,col_lens,nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 1235 ierr = PetscFree(col_lens);CHKERRQ(ierr); 1236 1237 /* store nonzero values */ 1238 ierr = PetscMalloc1(nz+1,&anonz);CHKERRQ(ierr); 1239 ict = 0; 1240 for (i=0; i<m; i++) { 1241 v = a->v + i; 1242 for (j=0; j<n; j++) { 1243 anonz[ict++] = *v; v += a->lda; 1244 } 1245 } 1246 ierr = PetscBinaryWrite(fd,anonz,nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 1247 ierr = PetscFree(anonz);CHKERRQ(ierr); 1248 } 1249 PetscFunctionReturn(0); 1250 } 1251 1252 #include <petscdraw.h> 1253 static PetscErrorCode MatView_SeqDense_Draw_Zoom(PetscDraw draw,void *Aa) 1254 { 1255 Mat A = (Mat) Aa; 1256 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1257 PetscErrorCode ierr; 1258 PetscInt m = A->rmap->n,n = A->cmap->n,i,j; 1259 int color = PETSC_DRAW_WHITE; 1260 PetscScalar *v = a->v; 1261 PetscViewer viewer; 1262 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 1263 PetscViewerFormat format; 1264 1265 PetscFunctionBegin; 1266 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 1267 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1268 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 1269 1270 /* Loop over matrix elements drawing boxes */ 1271 1272 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 1273 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 1274 /* Blue for negative and Red for positive */ 1275 for (j = 0; j < n; j++) { 1276 x_l = j; x_r = x_l + 1.0; 1277 for (i = 0; i < m; i++) { 1278 y_l = m - i - 1.0; 1279 y_r = y_l + 1.0; 1280 if (PetscRealPart(v[j*m+i]) > 0.) { 1281 color = PETSC_DRAW_RED; 1282 } else if (PetscRealPart(v[j*m+i]) < 0.) { 1283 color = PETSC_DRAW_BLUE; 1284 } else { 1285 continue; 1286 } 1287 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1288 } 1289 } 1290 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 1291 } else { 1292 /* use contour shading to indicate magnitude of values */ 1293 /* first determine max of all nonzero values */ 1294 PetscReal minv = 0.0, maxv = 0.0; 1295 PetscDraw popup; 1296 1297 for (i=0; i < m*n; i++) { 1298 if (PetscAbsScalar(v[i]) > maxv) maxv = PetscAbsScalar(v[i]); 1299 } 1300 if (minv >= maxv) maxv = minv + PETSC_SMALL; 1301 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 1302 ierr = PetscDrawScalePopup(popup,minv,maxv);CHKERRQ(ierr); 1303 1304 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 1305 for (j=0; j<n; j++) { 1306 x_l = j; 1307 x_r = x_l + 1.0; 1308 for (i=0; i<m; i++) { 1309 y_l = m - i - 1.0; 1310 y_r = y_l + 1.0; 1311 color = PetscDrawRealToColor(PetscAbsScalar(v[j*m+i]),minv,maxv); 1312 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1313 } 1314 } 1315 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 1316 } 1317 PetscFunctionReturn(0); 1318 } 1319 1320 static PetscErrorCode MatView_SeqDense_Draw(Mat A,PetscViewer viewer) 1321 { 1322 PetscDraw draw; 1323 PetscBool isnull; 1324 PetscReal xr,yr,xl,yl,h,w; 1325 PetscErrorCode ierr; 1326 1327 PetscFunctionBegin; 1328 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1329 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1330 if (isnull) PetscFunctionReturn(0); 1331 1332 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 1333 xr += w; yr += h; xl = -w; yl = -h; 1334 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 1335 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 1336 ierr = PetscDrawZoom(draw,MatView_SeqDense_Draw_Zoom,A);CHKERRQ(ierr); 1337 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 1338 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 1339 PetscFunctionReturn(0); 1340 } 1341 1342 PetscErrorCode MatView_SeqDense(Mat A,PetscViewer viewer) 1343 { 1344 PetscErrorCode ierr; 1345 PetscBool iascii,isbinary,isdraw; 1346 1347 PetscFunctionBegin; 1348 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1349 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1350 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1351 1352 if (iascii) { 1353 ierr = MatView_SeqDense_ASCII(A,viewer);CHKERRQ(ierr); 1354 } else if (isbinary) { 1355 ierr = MatView_SeqDense_Binary(A,viewer);CHKERRQ(ierr); 1356 } else if (isdraw) { 1357 ierr = MatView_SeqDense_Draw(A,viewer);CHKERRQ(ierr); 1358 } 1359 PetscFunctionReturn(0); 1360 } 1361 1362 static PetscErrorCode MatDensePlaceArray_SeqDense(Mat A,const PetscScalar array[]) 1363 { 1364 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1365 1366 PetscFunctionBegin; 1367 a->unplacedarray = a->v; 1368 a->unplaced_user_alloc = a->user_alloc; 1369 a->v = (PetscScalar*) array; 1370 PetscFunctionReturn(0); 1371 } 1372 1373 static PetscErrorCode MatDenseResetArray_SeqDense(Mat A) 1374 { 1375 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1376 1377 PetscFunctionBegin; 1378 a->v = a->unplacedarray; 1379 a->user_alloc = a->unplaced_user_alloc; 1380 a->unplacedarray = NULL; 1381 PetscFunctionReturn(0); 1382 } 1383 1384 static PetscErrorCode MatDestroy_SeqDense(Mat mat) 1385 { 1386 Mat_SeqDense *l = (Mat_SeqDense*)mat->data; 1387 PetscErrorCode ierr; 1388 1389 PetscFunctionBegin; 1390 #if defined(PETSC_USE_LOG) 1391 PetscLogObjectState((PetscObject)mat,"Rows %D Cols %D",mat->rmap->n,mat->cmap->n); 1392 #endif 1393 ierr = PetscFree(l->pivots);CHKERRQ(ierr); 1394 ierr = PetscFree(l->fwork);CHKERRQ(ierr); 1395 ierr = MatDestroy(&l->ptapwork);CHKERRQ(ierr); 1396 if (!l->user_alloc) {ierr = PetscFree(l->v);CHKERRQ(ierr);} 1397 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1398 1399 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1400 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",NULL);CHKERRQ(ierr); 1401 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDensePlaceArray_C",NULL);CHKERRQ(ierr); 1402 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseResetArray_C",NULL);CHKERRQ(ierr); 1403 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",NULL);CHKERRQ(ierr); 1404 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_seqdense_seqaij_C",NULL);CHKERRQ(ierr); 1405 #if defined(PETSC_HAVE_ELEMENTAL) 1406 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_seqdense_elemental_C",NULL);CHKERRQ(ierr); 1407 #endif 1408 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSeqDenseSetPreallocation_C",NULL);CHKERRQ(ierr); 1409 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1410 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1411 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1412 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatPtAP_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1413 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1414 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1415 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1416 PetscFunctionReturn(0); 1417 } 1418 1419 static PetscErrorCode MatTranspose_SeqDense(Mat A,MatReuse reuse,Mat *matout) 1420 { 1421 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1422 PetscErrorCode ierr; 1423 PetscInt k,j,m,n,M; 1424 PetscScalar *v,tmp; 1425 1426 PetscFunctionBegin; 1427 v = mat->v; m = A->rmap->n; M = mat->lda; n = A->cmap->n; 1428 if (reuse == MAT_INPLACE_MATRIX) { /* in place transpose */ 1429 if (m != n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can not transpose non-square matrix in place"); 1430 else { 1431 for (j=0; j<m; j++) { 1432 for (k=0; k<j; k++) { 1433 tmp = v[j + k*M]; 1434 v[j + k*M] = v[k + j*M]; 1435 v[k + j*M] = tmp; 1436 } 1437 } 1438 } 1439 } else { /* out-of-place transpose */ 1440 Mat tmat; 1441 Mat_SeqDense *tmatd; 1442 PetscScalar *v2; 1443 PetscInt M2; 1444 1445 if (reuse == MAT_INITIAL_MATRIX) { 1446 ierr = MatCreate(PetscObjectComm((PetscObject)A),&tmat);CHKERRQ(ierr); 1447 ierr = MatSetSizes(tmat,A->cmap->n,A->rmap->n,A->cmap->n,A->rmap->n);CHKERRQ(ierr); 1448 ierr = MatSetType(tmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1449 ierr = MatSeqDenseSetPreallocation(tmat,NULL);CHKERRQ(ierr); 1450 } else { 1451 tmat = *matout; 1452 } 1453 tmatd = (Mat_SeqDense*)tmat->data; 1454 v = mat->v; v2 = tmatd->v; M2 = tmatd->lda; 1455 for (j=0; j<n; j++) { 1456 for (k=0; k<m; k++) v2[j + k*M2] = v[k + j*M]; 1457 } 1458 ierr = MatAssemblyBegin(tmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1459 ierr = MatAssemblyEnd(tmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1460 *matout = tmat; 1461 } 1462 PetscFunctionReturn(0); 1463 } 1464 1465 static PetscErrorCode MatEqual_SeqDense(Mat A1,Mat A2,PetscBool *flg) 1466 { 1467 Mat_SeqDense *mat1 = (Mat_SeqDense*)A1->data; 1468 Mat_SeqDense *mat2 = (Mat_SeqDense*)A2->data; 1469 PetscInt i,j; 1470 PetscScalar *v1,*v2; 1471 1472 PetscFunctionBegin; 1473 if (A1->rmap->n != A2->rmap->n) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1474 if (A1->cmap->n != A2->cmap->n) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1475 for (i=0; i<A1->rmap->n; i++) { 1476 v1 = mat1->v+i; v2 = mat2->v+i; 1477 for (j=0; j<A1->cmap->n; j++) { 1478 if (*v1 != *v2) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1479 v1 += mat1->lda; v2 += mat2->lda; 1480 } 1481 } 1482 *flg = PETSC_TRUE; 1483 PetscFunctionReturn(0); 1484 } 1485 1486 static PetscErrorCode MatGetDiagonal_SeqDense(Mat A,Vec v) 1487 { 1488 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1489 PetscErrorCode ierr; 1490 PetscInt i,n,len; 1491 PetscScalar *x,zero = 0.0; 1492 1493 PetscFunctionBegin; 1494 ierr = VecSet(v,zero);CHKERRQ(ierr); 1495 ierr = VecGetSize(v,&n);CHKERRQ(ierr); 1496 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1497 len = PetscMin(A->rmap->n,A->cmap->n); 1498 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec"); 1499 for (i=0; i<len; i++) { 1500 x[i] = mat->v[i*mat->lda + i]; 1501 } 1502 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1503 PetscFunctionReturn(0); 1504 } 1505 1506 static PetscErrorCode MatDiagonalScale_SeqDense(Mat A,Vec ll,Vec rr) 1507 { 1508 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1509 const PetscScalar *l,*r; 1510 PetscScalar x,*v; 1511 PetscErrorCode ierr; 1512 PetscInt i,j,m = A->rmap->n,n = A->cmap->n; 1513 1514 PetscFunctionBegin; 1515 if (ll) { 1516 ierr = VecGetSize(ll,&m);CHKERRQ(ierr); 1517 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 1518 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vec wrong size"); 1519 for (i=0; i<m; i++) { 1520 x = l[i]; 1521 v = mat->v + i; 1522 for (j=0; j<n; j++) { (*v) *= x; v+= mat->lda;} 1523 } 1524 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 1525 ierr = PetscLogFlops(1.0*n*m);CHKERRQ(ierr); 1526 } 1527 if (rr) { 1528 ierr = VecGetSize(rr,&n);CHKERRQ(ierr); 1529 ierr = VecGetArrayRead(rr,&r);CHKERRQ(ierr); 1530 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vec wrong size"); 1531 for (i=0; i<n; i++) { 1532 x = r[i]; 1533 v = mat->v + i*mat->lda; 1534 for (j=0; j<m; j++) (*v++) *= x; 1535 } 1536 ierr = VecRestoreArrayRead(rr,&r);CHKERRQ(ierr); 1537 ierr = PetscLogFlops(1.0*n*m);CHKERRQ(ierr); 1538 } 1539 PetscFunctionReturn(0); 1540 } 1541 1542 static PetscErrorCode MatNorm_SeqDense(Mat A,NormType type,PetscReal *nrm) 1543 { 1544 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1545 PetscScalar *v = mat->v; 1546 PetscReal sum = 0.0; 1547 PetscInt lda =mat->lda,m=A->rmap->n,i,j; 1548 PetscErrorCode ierr; 1549 1550 PetscFunctionBegin; 1551 if (type == NORM_FROBENIUS) { 1552 if (lda>m) { 1553 for (j=0; j<A->cmap->n; j++) { 1554 v = mat->v+j*lda; 1555 for (i=0; i<m; i++) { 1556 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1557 } 1558 } 1559 } else { 1560 #if defined(PETSC_USE_REAL___FP16) 1561 PetscBLASInt one = 1,cnt = A->cmap->n*A->rmap->n; 1562 *nrm = BLASnrm2_(&cnt,v,&one); 1563 } 1564 #else 1565 for (i=0; i<A->cmap->n*A->rmap->n; i++) { 1566 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1567 } 1568 } 1569 *nrm = PetscSqrtReal(sum); 1570 #endif 1571 ierr = PetscLogFlops(2.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1572 } else if (type == NORM_1) { 1573 *nrm = 0.0; 1574 for (j=0; j<A->cmap->n; j++) { 1575 v = mat->v + j*mat->lda; 1576 sum = 0.0; 1577 for (i=0; i<A->rmap->n; i++) { 1578 sum += PetscAbsScalar(*v); v++; 1579 } 1580 if (sum > *nrm) *nrm = sum; 1581 } 1582 ierr = PetscLogFlops(1.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1583 } else if (type == NORM_INFINITY) { 1584 *nrm = 0.0; 1585 for (j=0; j<A->rmap->n; j++) { 1586 v = mat->v + j; 1587 sum = 0.0; 1588 for (i=0; i<A->cmap->n; i++) { 1589 sum += PetscAbsScalar(*v); v += mat->lda; 1590 } 1591 if (sum > *nrm) *nrm = sum; 1592 } 1593 ierr = PetscLogFlops(1.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1594 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No two norm"); 1595 PetscFunctionReturn(0); 1596 } 1597 1598 static PetscErrorCode MatSetOption_SeqDense(Mat A,MatOption op,PetscBool flg) 1599 { 1600 Mat_SeqDense *aij = (Mat_SeqDense*)A->data; 1601 PetscErrorCode ierr; 1602 1603 PetscFunctionBegin; 1604 switch (op) { 1605 case MAT_ROW_ORIENTED: 1606 aij->roworiented = flg; 1607 break; 1608 case MAT_NEW_NONZERO_LOCATIONS: 1609 case MAT_NEW_NONZERO_LOCATION_ERR: 1610 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1611 case MAT_NEW_DIAGONALS: 1612 case MAT_KEEP_NONZERO_PATTERN: 1613 case MAT_IGNORE_OFF_PROC_ENTRIES: 1614 case MAT_USE_HASH_TABLE: 1615 case MAT_IGNORE_ZERO_ENTRIES: 1616 case MAT_IGNORE_LOWER_TRIANGULAR: 1617 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1618 break; 1619 case MAT_SPD: 1620 case MAT_SYMMETRIC: 1621 case MAT_STRUCTURALLY_SYMMETRIC: 1622 case MAT_HERMITIAN: 1623 case MAT_SYMMETRY_ETERNAL: 1624 /* These options are handled directly by MatSetOption() */ 1625 break; 1626 default: 1627 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %s",MatOptions[op]); 1628 } 1629 PetscFunctionReturn(0); 1630 } 1631 1632 static PetscErrorCode MatZeroEntries_SeqDense(Mat A) 1633 { 1634 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 1635 PetscErrorCode ierr; 1636 PetscInt lda=l->lda,m=A->rmap->n,j; 1637 1638 PetscFunctionBegin; 1639 if (lda>m) { 1640 for (j=0; j<A->cmap->n; j++) { 1641 ierr = PetscMemzero(l->v+j*lda,m*sizeof(PetscScalar));CHKERRQ(ierr); 1642 } 1643 } else { 1644 ierr = PetscMemzero(l->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 1645 } 1646 PetscFunctionReturn(0); 1647 } 1648 1649 static PetscErrorCode MatZeroRows_SeqDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1650 { 1651 PetscErrorCode ierr; 1652 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 1653 PetscInt m = l->lda, n = A->cmap->n, i,j; 1654 PetscScalar *slot,*bb; 1655 const PetscScalar *xx; 1656 1657 PetscFunctionBegin; 1658 #if defined(PETSC_USE_DEBUG) 1659 for (i=0; i<N; i++) { 1660 if (rows[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row requested to be zeroed"); 1661 if (rows[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D requested to be zeroed greater than or equal number of rows %D",rows[i],A->rmap->n); 1662 } 1663 #endif 1664 1665 /* fix right hand side if needed */ 1666 if (x && b) { 1667 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1668 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1669 for (i=0; i<N; i++) bb[rows[i]] = diag*xx[rows[i]]; 1670 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1671 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1672 } 1673 1674 for (i=0; i<N; i++) { 1675 slot = l->v + rows[i]; 1676 for (j=0; j<n; j++) { *slot = 0.0; slot += m;} 1677 } 1678 if (diag != 0.0) { 1679 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only coded for square matrices"); 1680 for (i=0; i<N; i++) { 1681 slot = l->v + (m+1)*rows[i]; 1682 *slot = diag; 1683 } 1684 } 1685 PetscFunctionReturn(0); 1686 } 1687 1688 static PetscErrorCode MatDenseGetArray_SeqDense(Mat A,PetscScalar *array[]) 1689 { 1690 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1691 1692 PetscFunctionBegin; 1693 if (mat->lda != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Cannot get array for Dense matrices with LDA different from number of rows"); 1694 *array = mat->v; 1695 PetscFunctionReturn(0); 1696 } 1697 1698 static PetscErrorCode MatDenseRestoreArray_SeqDense(Mat A,PetscScalar *array[]) 1699 { 1700 PetscFunctionBegin; 1701 PetscFunctionReturn(0); 1702 } 1703 1704 /*@C 1705 MatDenseGetArray - gives access to the array where the data for a SeqDense matrix is stored 1706 1707 Logically Collective on Mat 1708 1709 Input Parameter: 1710 . mat - a MATSEQDENSE or MATMPIDENSE matrix 1711 1712 Output Parameter: 1713 . array - pointer to the data 1714 1715 Level: intermediate 1716 1717 .seealso: MatDenseRestoreArray(), MatDenseGetArrayRead(), MatDenseRestoreArrayRead() 1718 @*/ 1719 PetscErrorCode MatDenseGetArray(Mat A,PetscScalar **array) 1720 { 1721 PetscErrorCode ierr; 1722 1723 PetscFunctionBegin; 1724 ierr = PetscUseMethod(A,"MatDenseGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 1725 PetscFunctionReturn(0); 1726 } 1727 1728 /*@C 1729 MatDenseRestoreArray - returns access to the array where the data for a dense matrix is stored obtained by MatDenseGetArray() 1730 1731 Logically Collective on Mat 1732 1733 Input Parameters: 1734 . mat - a MATSEQDENSE or MATMPIDENSE matrix 1735 . array - pointer to the data 1736 1737 Level: intermediate 1738 1739 .seealso: MatDenseGetArray(), MatDenseGetArrayRead(), MatDenseRestoreArrayRead() 1740 @*/ 1741 PetscErrorCode MatDenseRestoreArray(Mat A,PetscScalar **array) 1742 { 1743 PetscErrorCode ierr; 1744 1745 PetscFunctionBegin; 1746 ierr = PetscUseMethod(A,"MatDenseRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 1747 if (array) *array = NULL; 1748 ierr = PetscObjectStateIncrease((PetscObject)A);CHKERRQ(ierr); 1749 PetscFunctionReturn(0); 1750 } 1751 1752 /*@C 1753 MatDenseGetArrayRead - gives access to the array where the data for a SeqDense matrix is stored 1754 1755 Not Collective 1756 1757 Input Parameter: 1758 . mat - a MATSEQDENSE or MATMPIDENSE matrix 1759 1760 Output Parameter: 1761 . array - pointer to the data 1762 1763 Level: intermediate 1764 1765 .seealso: MatDenseRestoreArray(), MatDenseGetArray(), MatDenseRestoreArrayRead() 1766 @*/ 1767 PetscErrorCode MatDenseGetArrayRead(Mat A,const PetscScalar **array) 1768 { 1769 PetscErrorCode ierr; 1770 1771 PetscFunctionBegin; 1772 ierr = PetscUseMethod(A,"MatDenseGetArrayRead_C",(Mat,const PetscScalar**),(A,array));CHKERRQ(ierr); 1773 PetscFunctionReturn(0); 1774 } 1775 1776 /*@C 1777 MatDenseRestoreArrayRead - returns access to the array where the data for a dense matrix is stored obtained by MatDenseGetArray() 1778 1779 Not Collective 1780 1781 Input Parameters: 1782 . mat - a MATSEQDENSE or MATMPIDENSE matrix 1783 . array - pointer to the data 1784 1785 Level: intermediate 1786 1787 .seealso: MatDenseGetArray(), MatDenseGetArrayRead(), MatDenseRestoreArray() 1788 @*/ 1789 PetscErrorCode MatDenseRestoreArrayRead(Mat A,const PetscScalar **array) 1790 { 1791 PetscErrorCode ierr; 1792 1793 PetscFunctionBegin; 1794 ierr = PetscUseMethod(A,"MatDenseRestoreArrayRead_C",(Mat,const PetscScalar**),(A,array));CHKERRQ(ierr); 1795 if (array) *array = NULL; 1796 PetscFunctionReturn(0); 1797 } 1798 1799 static PetscErrorCode MatCreateSubMatrix_SeqDense(Mat A,IS isrow,IS iscol,PetscInt cs,MatReuse scall,Mat *B) 1800 { 1801 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1802 PetscErrorCode ierr; 1803 PetscInt i,j,nrows,ncols; 1804 const PetscInt *irow,*icol; 1805 PetscScalar *av,*bv,*v = mat->v; 1806 Mat newmat; 1807 1808 PetscFunctionBegin; 1809 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 1810 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 1811 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 1812 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 1813 1814 /* Check submatrixcall */ 1815 if (scall == MAT_REUSE_MATRIX) { 1816 PetscInt n_cols,n_rows; 1817 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 1818 if (n_rows != nrows || n_cols != ncols) { 1819 /* resize the result matrix to match number of requested rows/columns */ 1820 ierr = MatSetSizes(*B,nrows,ncols,nrows,ncols);CHKERRQ(ierr); 1821 } 1822 newmat = *B; 1823 } else { 1824 /* Create and fill new matrix */ 1825 ierr = MatCreate(PetscObjectComm((PetscObject)A),&newmat);CHKERRQ(ierr); 1826 ierr = MatSetSizes(newmat,nrows,ncols,nrows,ncols);CHKERRQ(ierr); 1827 ierr = MatSetType(newmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1828 ierr = MatSeqDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1829 } 1830 1831 /* Now extract the data pointers and do the copy,column at a time */ 1832 bv = ((Mat_SeqDense*)newmat->data)->v; 1833 1834 for (i=0; i<ncols; i++) { 1835 av = v + mat->lda*icol[i]; 1836 for (j=0; j<nrows; j++) *bv++ = av[irow[j]]; 1837 } 1838 1839 /* Assemble the matrices so that the correct flags are set */ 1840 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1841 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1842 1843 /* Free work space */ 1844 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 1845 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 1846 *B = newmat; 1847 PetscFunctionReturn(0); 1848 } 1849 1850 static PetscErrorCode MatCreateSubMatrices_SeqDense(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1851 { 1852 PetscErrorCode ierr; 1853 PetscInt i; 1854 1855 PetscFunctionBegin; 1856 if (scall == MAT_INITIAL_MATRIX) { 1857 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 1858 } 1859 1860 for (i=0; i<n; i++) { 1861 ierr = MatCreateSubMatrix_SeqDense(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 1862 } 1863 PetscFunctionReturn(0); 1864 } 1865 1866 static PetscErrorCode MatAssemblyBegin_SeqDense(Mat mat,MatAssemblyType mode) 1867 { 1868 PetscFunctionBegin; 1869 PetscFunctionReturn(0); 1870 } 1871 1872 static PetscErrorCode MatAssemblyEnd_SeqDense(Mat mat,MatAssemblyType mode) 1873 { 1874 PetscFunctionBegin; 1875 PetscFunctionReturn(0); 1876 } 1877 1878 static PetscErrorCode MatCopy_SeqDense(Mat A,Mat B,MatStructure str) 1879 { 1880 Mat_SeqDense *a = (Mat_SeqDense*)A->data,*b = (Mat_SeqDense*)B->data; 1881 PetscErrorCode ierr; 1882 PetscInt lda1=a->lda,lda2=b->lda, m=A->rmap->n,n=A->cmap->n, j; 1883 1884 PetscFunctionBegin; 1885 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1886 if (A->ops->copy != B->ops->copy) { 1887 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1888 PetscFunctionReturn(0); 1889 } 1890 if (m != B->rmap->n || n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"size(B) != size(A)"); 1891 if (lda1>m || lda2>m) { 1892 for (j=0; j<n; j++) { 1893 ierr = PetscMemcpy(b->v+j*lda2,a->v+j*lda1,m*sizeof(PetscScalar));CHKERRQ(ierr); 1894 } 1895 } else { 1896 ierr = PetscMemcpy(b->v,a->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 1897 } 1898 ierr = PetscObjectStateIncrease((PetscObject)B);CHKERRQ(ierr); 1899 PetscFunctionReturn(0); 1900 } 1901 1902 static PetscErrorCode MatSetUp_SeqDense(Mat A) 1903 { 1904 PetscErrorCode ierr; 1905 1906 PetscFunctionBegin; 1907 ierr = MatSeqDenseSetPreallocation(A,0);CHKERRQ(ierr); 1908 PetscFunctionReturn(0); 1909 } 1910 1911 static PetscErrorCode MatConjugate_SeqDense(Mat A) 1912 { 1913 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1914 PetscInt i,nz = A->rmap->n*A->cmap->n; 1915 PetscScalar *aa = a->v; 1916 1917 PetscFunctionBegin; 1918 for (i=0; i<nz; i++) aa[i] = PetscConj(aa[i]); 1919 PetscFunctionReturn(0); 1920 } 1921 1922 static PetscErrorCode MatRealPart_SeqDense(Mat A) 1923 { 1924 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1925 PetscInt i,nz = A->rmap->n*A->cmap->n; 1926 PetscScalar *aa = a->v; 1927 1928 PetscFunctionBegin; 1929 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1930 PetscFunctionReturn(0); 1931 } 1932 1933 static PetscErrorCode MatImaginaryPart_SeqDense(Mat A) 1934 { 1935 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1936 PetscInt i,nz = A->rmap->n*A->cmap->n; 1937 PetscScalar *aa = a->v; 1938 1939 PetscFunctionBegin; 1940 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1941 PetscFunctionReturn(0); 1942 } 1943 1944 /* ----------------------------------------------------------------*/ 1945 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1946 { 1947 PetscErrorCode ierr; 1948 1949 PetscFunctionBegin; 1950 if (scall == MAT_INITIAL_MATRIX) { 1951 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1952 ierr = MatMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 1953 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1954 } 1955 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 1956 ierr = MatMatMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 1957 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 1958 PetscFunctionReturn(0); 1959 } 1960 1961 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 1962 { 1963 PetscErrorCode ierr; 1964 PetscInt m=A->rmap->n,n=B->cmap->n; 1965 Mat Cmat; 1966 1967 PetscFunctionBegin; 1968 if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n); 1969 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 1970 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 1971 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 1972 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 1973 1974 *C = Cmat; 1975 PetscFunctionReturn(0); 1976 } 1977 1978 PetscErrorCode MatMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 1979 { 1980 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1981 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 1982 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 1983 PetscBLASInt m,n,k; 1984 PetscScalar _DOne=1.0,_DZero=0.0; 1985 PetscErrorCode ierr; 1986 PetscBool flg; 1987 1988 PetscFunctionBegin; 1989 ierr = PetscObjectTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr); 1990 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Second matrix must be dense"); 1991 1992 /* Handle case where where user provided the final C matrix rather than calling MatMatMult() with MAT_INITIAL_MATRIX*/ 1993 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&flg);CHKERRQ(ierr); 1994 if (flg) { 1995 C->ops->matmultnumeric = MatMatMultNumeric_SeqAIJ_SeqDense; 1996 ierr = (*C->ops->matmultnumeric)(A,B,C);CHKERRQ(ierr); 1997 PetscFunctionReturn(0); 1998 } 1999 2000 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQDENSE,&flg);CHKERRQ(ierr); 2001 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"First matrix must be dense"); 2002 ierr = PetscBLASIntCast(C->rmap->n,&m);CHKERRQ(ierr); 2003 ierr = PetscBLASIntCast(C->cmap->n,&n);CHKERRQ(ierr); 2004 ierr = PetscBLASIntCast(A->cmap->n,&k);CHKERRQ(ierr); 2005 PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 2006 PetscFunctionReturn(0); 2007 } 2008 2009 PetscErrorCode MatMatTransposeMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 2010 { 2011 PetscErrorCode ierr; 2012 2013 PetscFunctionBegin; 2014 if (scall == MAT_INITIAL_MATRIX) { 2015 ierr = PetscLogEventBegin(MAT_MatTransposeMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2016 ierr = MatMatTransposeMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 2017 ierr = PetscLogEventEnd(MAT_MatTransposeMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2018 } 2019 ierr = PetscLogEventBegin(MAT_MatTransposeMultNumeric,A,B,0,0);CHKERRQ(ierr); 2020 ierr = MatMatTransposeMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 2021 ierr = PetscLogEventEnd(MAT_MatTransposeMultNumeric,A,B,0,0);CHKERRQ(ierr); 2022 PetscFunctionReturn(0); 2023 } 2024 2025 PetscErrorCode MatMatTransposeMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 2026 { 2027 PetscErrorCode ierr; 2028 PetscInt m=A->rmap->n,n=B->rmap->n; 2029 Mat Cmat; 2030 2031 PetscFunctionBegin; 2032 if (A->cmap->n != B->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->cmap->n %d\n",A->cmap->n,B->cmap->n); 2033 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 2034 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 2035 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 2036 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 2037 2038 Cmat->assembled = PETSC_TRUE; 2039 2040 *C = Cmat; 2041 PetscFunctionReturn(0); 2042 } 2043 2044 PetscErrorCode MatMatTransposeMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 2045 { 2046 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2047 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2048 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 2049 PetscBLASInt m,n,k; 2050 PetscScalar _DOne=1.0,_DZero=0.0; 2051 PetscErrorCode ierr; 2052 2053 PetscFunctionBegin; 2054 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 2055 ierr = PetscBLASIntCast(B->rmap->n,&n);CHKERRQ(ierr); 2056 ierr = PetscBLASIntCast(A->cmap->n,&k);CHKERRQ(ierr); 2057 PetscStackCallBLAS("BLASgemm",BLASgemm_("N","T",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 2058 PetscFunctionReturn(0); 2059 } 2060 2061 PetscErrorCode MatTransposeMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 2062 { 2063 PetscErrorCode ierr; 2064 2065 PetscFunctionBegin; 2066 if (scall == MAT_INITIAL_MATRIX) { 2067 ierr = PetscLogEventBegin(MAT_TransposeMatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2068 ierr = MatTransposeMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 2069 ierr = PetscLogEventEnd(MAT_TransposeMatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2070 } 2071 ierr = PetscLogEventBegin(MAT_TransposeMatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2072 ierr = MatTransposeMatMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 2073 ierr = PetscLogEventEnd(MAT_TransposeMatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2074 PetscFunctionReturn(0); 2075 } 2076 2077 PetscErrorCode MatTransposeMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 2078 { 2079 PetscErrorCode ierr; 2080 PetscInt m=A->cmap->n,n=B->cmap->n; 2081 Mat Cmat; 2082 2083 PetscFunctionBegin; 2084 if (A->rmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->rmap->n %d != B->rmap->n %d\n",A->rmap->n,B->rmap->n); 2085 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 2086 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 2087 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 2088 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 2089 2090 Cmat->assembled = PETSC_TRUE; 2091 2092 *C = Cmat; 2093 PetscFunctionReturn(0); 2094 } 2095 2096 PetscErrorCode MatTransposeMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 2097 { 2098 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2099 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2100 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 2101 PetscBLASInt m,n,k; 2102 PetscScalar _DOne=1.0,_DZero=0.0; 2103 PetscErrorCode ierr; 2104 2105 PetscFunctionBegin; 2106 ierr = PetscBLASIntCast(C->rmap->n,&m);CHKERRQ(ierr); 2107 ierr = PetscBLASIntCast(C->cmap->n,&n);CHKERRQ(ierr); 2108 ierr = PetscBLASIntCast(A->rmap->n,&k);CHKERRQ(ierr); 2109 PetscStackCallBLAS("BLASgemm",BLASgemm_("T","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 2110 PetscFunctionReturn(0); 2111 } 2112 2113 static PetscErrorCode MatGetRowMax_SeqDense(Mat A,Vec v,PetscInt idx[]) 2114 { 2115 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2116 PetscErrorCode ierr; 2117 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2118 PetscScalar *x; 2119 MatScalar *aa = a->v; 2120 2121 PetscFunctionBegin; 2122 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2123 2124 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2125 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2126 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2127 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2128 for (i=0; i<m; i++) { 2129 x[i] = aa[i]; if (idx) idx[i] = 0; 2130 for (j=1; j<n; j++) { 2131 if (PetscRealPart(x[i]) < PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;} 2132 } 2133 } 2134 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2135 PetscFunctionReturn(0); 2136 } 2137 2138 static PetscErrorCode MatGetRowMaxAbs_SeqDense(Mat A,Vec v,PetscInt idx[]) 2139 { 2140 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2141 PetscErrorCode ierr; 2142 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2143 PetscScalar *x; 2144 PetscReal atmp; 2145 MatScalar *aa = a->v; 2146 2147 PetscFunctionBegin; 2148 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2149 2150 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2151 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2152 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2153 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2154 for (i=0; i<m; i++) { 2155 x[i] = PetscAbsScalar(aa[i]); 2156 for (j=1; j<n; j++) { 2157 atmp = PetscAbsScalar(aa[i+m*j]); 2158 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = j;} 2159 } 2160 } 2161 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2162 PetscFunctionReturn(0); 2163 } 2164 2165 static PetscErrorCode MatGetRowMin_SeqDense(Mat A,Vec v,PetscInt idx[]) 2166 { 2167 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2168 PetscErrorCode ierr; 2169 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2170 PetscScalar *x; 2171 MatScalar *aa = a->v; 2172 2173 PetscFunctionBegin; 2174 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2175 2176 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2177 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2178 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2179 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2180 for (i=0; i<m; i++) { 2181 x[i] = aa[i]; if (idx) idx[i] = 0; 2182 for (j=1; j<n; j++) { 2183 if (PetscRealPart(x[i]) > PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;} 2184 } 2185 } 2186 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2187 PetscFunctionReturn(0); 2188 } 2189 2190 static PetscErrorCode MatGetColumnVector_SeqDense(Mat A,Vec v,PetscInt col) 2191 { 2192 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2193 PetscErrorCode ierr; 2194 PetscScalar *x; 2195 2196 PetscFunctionBegin; 2197 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2198 2199 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2200 ierr = PetscMemcpy(x,a->v+col*a->lda,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 2201 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2202 PetscFunctionReturn(0); 2203 } 2204 2205 2206 PetscErrorCode MatGetColumnNorms_SeqDense(Mat A,NormType type,PetscReal *norms) 2207 { 2208 PetscErrorCode ierr; 2209 PetscInt i,j,m,n; 2210 PetscScalar *a; 2211 2212 PetscFunctionBegin; 2213 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 2214 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 2215 ierr = MatDenseGetArray(A,&a);CHKERRQ(ierr); 2216 if (type == NORM_2) { 2217 for (i=0; i<n; i++) { 2218 for (j=0; j<m; j++) { 2219 norms[i] += PetscAbsScalar(a[j]*a[j]); 2220 } 2221 a += m; 2222 } 2223 } else if (type == NORM_1) { 2224 for (i=0; i<n; i++) { 2225 for (j=0; j<m; j++) { 2226 norms[i] += PetscAbsScalar(a[j]); 2227 } 2228 a += m; 2229 } 2230 } else if (type == NORM_INFINITY) { 2231 for (i=0; i<n; i++) { 2232 for (j=0; j<m; j++) { 2233 norms[i] = PetscMax(PetscAbsScalar(a[j]),norms[i]); 2234 } 2235 a += m; 2236 } 2237 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2238 ierr = MatDenseRestoreArray(A,&a);CHKERRQ(ierr); 2239 if (type == NORM_2) { 2240 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 2241 } 2242 PetscFunctionReturn(0); 2243 } 2244 2245 static PetscErrorCode MatSetRandom_SeqDense(Mat x,PetscRandom rctx) 2246 { 2247 PetscErrorCode ierr; 2248 PetscScalar *a; 2249 PetscInt m,n,i; 2250 2251 PetscFunctionBegin; 2252 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 2253 ierr = MatDenseGetArray(x,&a);CHKERRQ(ierr); 2254 for (i=0; i<m*n; i++) { 2255 ierr = PetscRandomGetValue(rctx,a+i);CHKERRQ(ierr); 2256 } 2257 ierr = MatDenseRestoreArray(x,&a);CHKERRQ(ierr); 2258 PetscFunctionReturn(0); 2259 } 2260 2261 static PetscErrorCode MatMissingDiagonal_SeqDense(Mat A,PetscBool *missing,PetscInt *d) 2262 { 2263 PetscFunctionBegin; 2264 *missing = PETSC_FALSE; 2265 PetscFunctionReturn(0); 2266 } 2267 2268 2269 /* -------------------------------------------------------------------*/ 2270 static struct _MatOps MatOps_Values = { MatSetValues_SeqDense, 2271 MatGetRow_SeqDense, 2272 MatRestoreRow_SeqDense, 2273 MatMult_SeqDense, 2274 /* 4*/ MatMultAdd_SeqDense, 2275 MatMultTranspose_SeqDense, 2276 MatMultTransposeAdd_SeqDense, 2277 0, 2278 0, 2279 0, 2280 /* 10*/ 0, 2281 MatLUFactor_SeqDense, 2282 MatCholeskyFactor_SeqDense, 2283 MatSOR_SeqDense, 2284 MatTranspose_SeqDense, 2285 /* 15*/ MatGetInfo_SeqDense, 2286 MatEqual_SeqDense, 2287 MatGetDiagonal_SeqDense, 2288 MatDiagonalScale_SeqDense, 2289 MatNorm_SeqDense, 2290 /* 20*/ MatAssemblyBegin_SeqDense, 2291 MatAssemblyEnd_SeqDense, 2292 MatSetOption_SeqDense, 2293 MatZeroEntries_SeqDense, 2294 /* 24*/ MatZeroRows_SeqDense, 2295 0, 2296 0, 2297 0, 2298 0, 2299 /* 29*/ MatSetUp_SeqDense, 2300 0, 2301 0, 2302 0, 2303 0, 2304 /* 34*/ MatDuplicate_SeqDense, 2305 0, 2306 0, 2307 0, 2308 0, 2309 /* 39*/ MatAXPY_SeqDense, 2310 MatCreateSubMatrices_SeqDense, 2311 0, 2312 MatGetValues_SeqDense, 2313 MatCopy_SeqDense, 2314 /* 44*/ MatGetRowMax_SeqDense, 2315 MatScale_SeqDense, 2316 MatShift_Basic, 2317 0, 2318 MatZeroRowsColumns_SeqDense, 2319 /* 49*/ MatSetRandom_SeqDense, 2320 0, 2321 0, 2322 0, 2323 0, 2324 /* 54*/ 0, 2325 0, 2326 0, 2327 0, 2328 0, 2329 /* 59*/ 0, 2330 MatDestroy_SeqDense, 2331 MatView_SeqDense, 2332 0, 2333 0, 2334 /* 64*/ 0, 2335 0, 2336 0, 2337 0, 2338 0, 2339 /* 69*/ MatGetRowMaxAbs_SeqDense, 2340 0, 2341 0, 2342 0, 2343 0, 2344 /* 74*/ 0, 2345 0, 2346 0, 2347 0, 2348 0, 2349 /* 79*/ 0, 2350 0, 2351 0, 2352 0, 2353 /* 83*/ MatLoad_SeqDense, 2354 0, 2355 MatIsHermitian_SeqDense, 2356 0, 2357 0, 2358 0, 2359 /* 89*/ MatMatMult_SeqDense_SeqDense, 2360 MatMatMultSymbolic_SeqDense_SeqDense, 2361 MatMatMultNumeric_SeqDense_SeqDense, 2362 MatPtAP_SeqDense_SeqDense, 2363 MatPtAPSymbolic_SeqDense_SeqDense, 2364 /* 94*/ MatPtAPNumeric_SeqDense_SeqDense, 2365 MatMatTransposeMult_SeqDense_SeqDense, 2366 MatMatTransposeMultSymbolic_SeqDense_SeqDense, 2367 MatMatTransposeMultNumeric_SeqDense_SeqDense, 2368 0, 2369 /* 99*/ 0, 2370 0, 2371 0, 2372 MatConjugate_SeqDense, 2373 0, 2374 /*104*/ 0, 2375 MatRealPart_SeqDense, 2376 MatImaginaryPart_SeqDense, 2377 0, 2378 0, 2379 /*109*/ 0, 2380 0, 2381 MatGetRowMin_SeqDense, 2382 MatGetColumnVector_SeqDense, 2383 MatMissingDiagonal_SeqDense, 2384 /*114*/ 0, 2385 0, 2386 0, 2387 0, 2388 0, 2389 /*119*/ 0, 2390 0, 2391 0, 2392 0, 2393 0, 2394 /*124*/ 0, 2395 MatGetColumnNorms_SeqDense, 2396 0, 2397 0, 2398 0, 2399 /*129*/ 0, 2400 MatTransposeMatMult_SeqDense_SeqDense, 2401 MatTransposeMatMultSymbolic_SeqDense_SeqDense, 2402 MatTransposeMatMultNumeric_SeqDense_SeqDense, 2403 0, 2404 /*134*/ 0, 2405 0, 2406 0, 2407 0, 2408 0, 2409 /*139*/ 0, 2410 0, 2411 0 2412 }; 2413 2414 /*@C 2415 MatCreateSeqDense - Creates a sequential dense matrix that 2416 is stored in column major order (the usual Fortran 77 manner). Many 2417 of the matrix operations use the BLAS and LAPACK routines. 2418 2419 Collective on MPI_Comm 2420 2421 Input Parameters: 2422 + comm - MPI communicator, set to PETSC_COMM_SELF 2423 . m - number of rows 2424 . n - number of columns 2425 - data - optional location of matrix data in column major order. Set data=NULL for PETSc 2426 to control all matrix memory allocation. 2427 2428 Output Parameter: 2429 . A - the matrix 2430 2431 Notes: 2432 The data input variable is intended primarily for Fortran programmers 2433 who wish to allocate their own matrix memory space. Most users should 2434 set data=NULL. 2435 2436 Level: intermediate 2437 2438 .keywords: dense, matrix, LAPACK, BLAS 2439 2440 .seealso: MatCreate(), MatCreateDense(), MatSetValues() 2441 @*/ 2442 PetscErrorCode MatCreateSeqDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscScalar *data,Mat *A) 2443 { 2444 PetscErrorCode ierr; 2445 2446 PetscFunctionBegin; 2447 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2448 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 2449 ierr = MatSetType(*A,MATSEQDENSE);CHKERRQ(ierr); 2450 ierr = MatSeqDenseSetPreallocation(*A,data);CHKERRQ(ierr); 2451 PetscFunctionReturn(0); 2452 } 2453 2454 /*@C 2455 MatSeqDenseSetPreallocation - Sets the array used for storing the matrix elements 2456 2457 Collective on MPI_Comm 2458 2459 Input Parameters: 2460 + B - the matrix 2461 - data - the array (or NULL) 2462 2463 Notes: 2464 The data input variable is intended primarily for Fortran programmers 2465 who wish to allocate their own matrix memory space. Most users should 2466 need not call this routine. 2467 2468 Level: intermediate 2469 2470 .keywords: dense, matrix, LAPACK, BLAS 2471 2472 .seealso: MatCreate(), MatCreateDense(), MatSetValues(), MatSeqDenseSetLDA() 2473 2474 @*/ 2475 PetscErrorCode MatSeqDenseSetPreallocation(Mat B,PetscScalar data[]) 2476 { 2477 PetscErrorCode ierr; 2478 2479 PetscFunctionBegin; 2480 ierr = PetscTryMethod(B,"MatSeqDenseSetPreallocation_C",(Mat,PetscScalar[]),(B,data));CHKERRQ(ierr); 2481 PetscFunctionReturn(0); 2482 } 2483 2484 PetscErrorCode MatSeqDenseSetPreallocation_SeqDense(Mat B,PetscScalar *data) 2485 { 2486 Mat_SeqDense *b; 2487 PetscErrorCode ierr; 2488 2489 PetscFunctionBegin; 2490 B->preallocated = PETSC_TRUE; 2491 2492 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2493 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2494 2495 b = (Mat_SeqDense*)B->data; 2496 b->Mmax = B->rmap->n; 2497 b->Nmax = B->cmap->n; 2498 if (b->lda <= 0 || b->changelda) b->lda = B->rmap->n; 2499 2500 ierr = PetscIntMultError(b->lda,b->Nmax,NULL);CHKERRQ(ierr); 2501 if (!data) { /* petsc-allocated storage */ 2502 if (!b->user_alloc) { ierr = PetscFree(b->v);CHKERRQ(ierr); } 2503 ierr = PetscCalloc1((size_t)b->lda*b->Nmax,&b->v);CHKERRQ(ierr); 2504 ierr = PetscLogObjectMemory((PetscObject)B,b->lda*b->Nmax*sizeof(PetscScalar));CHKERRQ(ierr); 2505 2506 b->user_alloc = PETSC_FALSE; 2507 } else { /* user-allocated storage */ 2508 if (!b->user_alloc) { ierr = PetscFree(b->v);CHKERRQ(ierr); } 2509 b->v = data; 2510 b->user_alloc = PETSC_TRUE; 2511 } 2512 B->assembled = PETSC_TRUE; 2513 PetscFunctionReturn(0); 2514 } 2515 2516 #if defined(PETSC_HAVE_ELEMENTAL) 2517 PETSC_INTERN PetscErrorCode MatConvert_SeqDense_Elemental(Mat A, MatType newtype,MatReuse reuse,Mat *newmat) 2518 { 2519 Mat mat_elemental; 2520 PetscErrorCode ierr; 2521 PetscScalar *array,*v_colwise; 2522 PetscInt M=A->rmap->N,N=A->cmap->N,i,j,k,*rows,*cols; 2523 2524 PetscFunctionBegin; 2525 ierr = PetscMalloc3(M*N,&v_colwise,M,&rows,N,&cols);CHKERRQ(ierr); 2526 ierr = MatDenseGetArray(A,&array);CHKERRQ(ierr); 2527 /* convert column-wise array into row-wise v_colwise, see MatSetValues_Elemental() */ 2528 k = 0; 2529 for (j=0; j<N; j++) { 2530 cols[j] = j; 2531 for (i=0; i<M; i++) { 2532 v_colwise[j*M+i] = array[k++]; 2533 } 2534 } 2535 for (i=0; i<M; i++) { 2536 rows[i] = i; 2537 } 2538 ierr = MatDenseRestoreArray(A,&array);CHKERRQ(ierr); 2539 2540 ierr = MatCreate(PetscObjectComm((PetscObject)A), &mat_elemental);CHKERRQ(ierr); 2541 ierr = MatSetSizes(mat_elemental,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 2542 ierr = MatSetType(mat_elemental,MATELEMENTAL);CHKERRQ(ierr); 2543 ierr = MatSetUp(mat_elemental);CHKERRQ(ierr); 2544 2545 /* PETSc-Elemental interaface uses axpy for setting off-processor entries, only ADD_VALUES is allowed */ 2546 ierr = MatSetValues(mat_elemental,M,rows,N,cols,v_colwise,ADD_VALUES);CHKERRQ(ierr); 2547 ierr = MatAssemblyBegin(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2548 ierr = MatAssemblyEnd(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2549 ierr = PetscFree3(v_colwise,rows,cols);CHKERRQ(ierr); 2550 2551 if (reuse == MAT_INPLACE_MATRIX) { 2552 ierr = MatHeaderReplace(A,&mat_elemental);CHKERRQ(ierr); 2553 } else { 2554 *newmat = mat_elemental; 2555 } 2556 PetscFunctionReturn(0); 2557 } 2558 #endif 2559 2560 /*@C 2561 MatSeqDenseSetLDA - Declare the leading dimension of the user-provided array 2562 2563 Input parameter: 2564 + A - the matrix 2565 - lda - the leading dimension 2566 2567 Notes: 2568 This routine is to be used in conjunction with MatSeqDenseSetPreallocation(); 2569 it asserts that the preallocation has a leading dimension (the LDA parameter 2570 of Blas and Lapack fame) larger than M, the first dimension of the matrix. 2571 2572 Level: intermediate 2573 2574 .keywords: dense, matrix, LAPACK, BLAS 2575 2576 .seealso: MatCreate(), MatCreateSeqDense(), MatSeqDenseSetPreallocation(), MatSetMaximumSize() 2577 2578 @*/ 2579 PetscErrorCode MatSeqDenseSetLDA(Mat B,PetscInt lda) 2580 { 2581 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2582 2583 PetscFunctionBegin; 2584 if (lda < B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"LDA %D must be at least matrix dimension %D",lda,B->rmap->n); 2585 b->lda = lda; 2586 b->changelda = PETSC_FALSE; 2587 b->Mmax = PetscMax(b->Mmax,lda); 2588 PetscFunctionReturn(0); 2589 } 2590 2591 /*MC 2592 MATSEQDENSE - MATSEQDENSE = "seqdense" - A matrix type to be used for sequential dense matrices. 2593 2594 Options Database Keys: 2595 . -mat_type seqdense - sets the matrix type to "seqdense" during a call to MatSetFromOptions() 2596 2597 Level: beginner 2598 2599 .seealso: MatCreateSeqDense() 2600 2601 M*/ 2602 2603 PETSC_EXTERN PetscErrorCode MatCreate_SeqDense(Mat B) 2604 { 2605 Mat_SeqDense *b; 2606 PetscErrorCode ierr; 2607 PetscMPIInt size; 2608 2609 PetscFunctionBegin; 2610 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 2611 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1"); 2612 2613 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 2614 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2615 B->data = (void*)b; 2616 2617 b->roworiented = PETSC_TRUE; 2618 2619 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseGetArray_C",MatDenseGetArray_SeqDense);CHKERRQ(ierr); 2620 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseRestoreArray_C",MatDenseRestoreArray_SeqDense);CHKERRQ(ierr); 2621 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDensePlaceArray_C",MatDensePlaceArray_SeqDense);CHKERRQ(ierr); 2622 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseResetArray_C",MatDenseResetArray_SeqDense);CHKERRQ(ierr); 2623 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseGetArrayRead_C",MatDenseGetArray_SeqDense);CHKERRQ(ierr); 2624 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseRestoreArray_C",MatDenseRestoreArray_SeqDense);CHKERRQ(ierr); 2625 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqdense_seqaij_C",MatConvert_SeqDense_SeqAIJ);CHKERRQ(ierr); 2626 #if defined(PETSC_HAVE_ELEMENTAL) 2627 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqdense_elemental_C",MatConvert_SeqDense_Elemental);CHKERRQ(ierr); 2628 #endif 2629 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqDenseSetPreallocation_C",MatSeqDenseSetPreallocation_SeqDense);CHKERRQ(ierr); 2630 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaij_seqdense_C",MatMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2631 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaij_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2632 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaij_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2633 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaij_seqdense_C",MatPtAP_SeqDense_SeqDense);CHKERRQ(ierr); 2634 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaijperm_seqdense_C",MatMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2635 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaijperm_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2636 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaijperm_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2637 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaijperm_seqdense_C",MatPtAP_SeqDense_SeqDense);CHKERRQ(ierr); 2638 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaijmkl_seqdense_C",MatMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2639 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaijmkl_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2640 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaijmkl_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2641 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaijmkl_seqdense_C",MatPtAP_SeqDense_SeqDense);CHKERRQ(ierr); 2642 2643 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaij_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2644 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaij_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2645 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaij_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2646 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaijperm_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2647 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaijperm_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2648 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaijperm_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2649 2650 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaijmkl_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2651 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaijmkl_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2652 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaijmkl_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2653 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQDENSE);CHKERRQ(ierr); 2654 PetscFunctionReturn(0); 2655 } 2656