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 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetColumn_C",NULL);CHKERRQ(ierr); 1417 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreColumn_C",NULL);CHKERRQ(ierr); 1418 PetscFunctionReturn(0); 1419 } 1420 1421 static PetscErrorCode MatTranspose_SeqDense(Mat A,MatReuse reuse,Mat *matout) 1422 { 1423 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1424 PetscErrorCode ierr; 1425 PetscInt k,j,m,n,M; 1426 PetscScalar *v,tmp; 1427 1428 PetscFunctionBegin; 1429 v = mat->v; m = A->rmap->n; M = mat->lda; n = A->cmap->n; 1430 if (reuse == MAT_INPLACE_MATRIX) { /* in place transpose */ 1431 if (m != n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can not transpose non-square matrix in place"); 1432 else { 1433 for (j=0; j<m; j++) { 1434 for (k=0; k<j; k++) { 1435 tmp = v[j + k*M]; 1436 v[j + k*M] = v[k + j*M]; 1437 v[k + j*M] = tmp; 1438 } 1439 } 1440 } 1441 } else { /* out-of-place transpose */ 1442 Mat tmat; 1443 Mat_SeqDense *tmatd; 1444 PetscScalar *v2; 1445 PetscInt M2; 1446 1447 if (reuse == MAT_INITIAL_MATRIX) { 1448 ierr = MatCreate(PetscObjectComm((PetscObject)A),&tmat);CHKERRQ(ierr); 1449 ierr = MatSetSizes(tmat,A->cmap->n,A->rmap->n,A->cmap->n,A->rmap->n);CHKERRQ(ierr); 1450 ierr = MatSetType(tmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1451 ierr = MatSeqDenseSetPreallocation(tmat,NULL);CHKERRQ(ierr); 1452 } else { 1453 tmat = *matout; 1454 } 1455 tmatd = (Mat_SeqDense*)tmat->data; 1456 v = mat->v; v2 = tmatd->v; M2 = tmatd->lda; 1457 for (j=0; j<n; j++) { 1458 for (k=0; k<m; k++) v2[j + k*M2] = v[k + j*M]; 1459 } 1460 ierr = MatAssemblyBegin(tmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1461 ierr = MatAssemblyEnd(tmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1462 *matout = tmat; 1463 } 1464 PetscFunctionReturn(0); 1465 } 1466 1467 static PetscErrorCode MatEqual_SeqDense(Mat A1,Mat A2,PetscBool *flg) 1468 { 1469 Mat_SeqDense *mat1 = (Mat_SeqDense*)A1->data; 1470 Mat_SeqDense *mat2 = (Mat_SeqDense*)A2->data; 1471 PetscInt i,j; 1472 PetscScalar *v1,*v2; 1473 1474 PetscFunctionBegin; 1475 if (A1->rmap->n != A2->rmap->n) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1476 if (A1->cmap->n != A2->cmap->n) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1477 for (i=0; i<A1->rmap->n; i++) { 1478 v1 = mat1->v+i; v2 = mat2->v+i; 1479 for (j=0; j<A1->cmap->n; j++) { 1480 if (*v1 != *v2) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1481 v1 += mat1->lda; v2 += mat2->lda; 1482 } 1483 } 1484 *flg = PETSC_TRUE; 1485 PetscFunctionReturn(0); 1486 } 1487 1488 static PetscErrorCode MatGetDiagonal_SeqDense(Mat A,Vec v) 1489 { 1490 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1491 PetscErrorCode ierr; 1492 PetscInt i,n,len; 1493 PetscScalar *x,zero = 0.0; 1494 1495 PetscFunctionBegin; 1496 ierr = VecSet(v,zero);CHKERRQ(ierr); 1497 ierr = VecGetSize(v,&n);CHKERRQ(ierr); 1498 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1499 len = PetscMin(A->rmap->n,A->cmap->n); 1500 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec"); 1501 for (i=0; i<len; i++) { 1502 x[i] = mat->v[i*mat->lda + i]; 1503 } 1504 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1505 PetscFunctionReturn(0); 1506 } 1507 1508 static PetscErrorCode MatDiagonalScale_SeqDense(Mat A,Vec ll,Vec rr) 1509 { 1510 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1511 const PetscScalar *l,*r; 1512 PetscScalar x,*v; 1513 PetscErrorCode ierr; 1514 PetscInt i,j,m = A->rmap->n,n = A->cmap->n; 1515 1516 PetscFunctionBegin; 1517 if (ll) { 1518 ierr = VecGetSize(ll,&m);CHKERRQ(ierr); 1519 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 1520 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vec wrong size"); 1521 for (i=0; i<m; i++) { 1522 x = l[i]; 1523 v = mat->v + i; 1524 for (j=0; j<n; j++) { (*v) *= x; v+= mat->lda;} 1525 } 1526 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 1527 ierr = PetscLogFlops(1.0*n*m);CHKERRQ(ierr); 1528 } 1529 if (rr) { 1530 ierr = VecGetSize(rr,&n);CHKERRQ(ierr); 1531 ierr = VecGetArrayRead(rr,&r);CHKERRQ(ierr); 1532 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vec wrong size"); 1533 for (i=0; i<n; i++) { 1534 x = r[i]; 1535 v = mat->v + i*mat->lda; 1536 for (j=0; j<m; j++) (*v++) *= x; 1537 } 1538 ierr = VecRestoreArrayRead(rr,&r);CHKERRQ(ierr); 1539 ierr = PetscLogFlops(1.0*n*m);CHKERRQ(ierr); 1540 } 1541 PetscFunctionReturn(0); 1542 } 1543 1544 static PetscErrorCode MatNorm_SeqDense(Mat A,NormType type,PetscReal *nrm) 1545 { 1546 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1547 PetscScalar *v = mat->v; 1548 PetscReal sum = 0.0; 1549 PetscInt lda =mat->lda,m=A->rmap->n,i,j; 1550 PetscErrorCode ierr; 1551 1552 PetscFunctionBegin; 1553 if (type == NORM_FROBENIUS) { 1554 if (lda>m) { 1555 for (j=0; j<A->cmap->n; j++) { 1556 v = mat->v+j*lda; 1557 for (i=0; i<m; i++) { 1558 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1559 } 1560 } 1561 } else { 1562 #if defined(PETSC_USE_REAL___FP16) 1563 PetscBLASInt one = 1,cnt = A->cmap->n*A->rmap->n; 1564 *nrm = BLASnrm2_(&cnt,v,&one); 1565 } 1566 #else 1567 for (i=0; i<A->cmap->n*A->rmap->n; i++) { 1568 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1569 } 1570 } 1571 *nrm = PetscSqrtReal(sum); 1572 #endif 1573 ierr = PetscLogFlops(2.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1574 } else if (type == NORM_1) { 1575 *nrm = 0.0; 1576 for (j=0; j<A->cmap->n; j++) { 1577 v = mat->v + j*mat->lda; 1578 sum = 0.0; 1579 for (i=0; i<A->rmap->n; i++) { 1580 sum += PetscAbsScalar(*v); v++; 1581 } 1582 if (sum > *nrm) *nrm = sum; 1583 } 1584 ierr = PetscLogFlops(1.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1585 } else if (type == NORM_INFINITY) { 1586 *nrm = 0.0; 1587 for (j=0; j<A->rmap->n; j++) { 1588 v = mat->v + j; 1589 sum = 0.0; 1590 for (i=0; i<A->cmap->n; i++) { 1591 sum += PetscAbsScalar(*v); v += mat->lda; 1592 } 1593 if (sum > *nrm) *nrm = sum; 1594 } 1595 ierr = PetscLogFlops(1.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1596 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No two norm"); 1597 PetscFunctionReturn(0); 1598 } 1599 1600 static PetscErrorCode MatSetOption_SeqDense(Mat A,MatOption op,PetscBool flg) 1601 { 1602 Mat_SeqDense *aij = (Mat_SeqDense*)A->data; 1603 PetscErrorCode ierr; 1604 1605 PetscFunctionBegin; 1606 switch (op) { 1607 case MAT_ROW_ORIENTED: 1608 aij->roworiented = flg; 1609 break; 1610 case MAT_NEW_NONZERO_LOCATIONS: 1611 case MAT_NEW_NONZERO_LOCATION_ERR: 1612 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1613 case MAT_NEW_DIAGONALS: 1614 case MAT_KEEP_NONZERO_PATTERN: 1615 case MAT_IGNORE_OFF_PROC_ENTRIES: 1616 case MAT_USE_HASH_TABLE: 1617 case MAT_IGNORE_ZERO_ENTRIES: 1618 case MAT_IGNORE_LOWER_TRIANGULAR: 1619 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1620 break; 1621 case MAT_SPD: 1622 case MAT_SYMMETRIC: 1623 case MAT_STRUCTURALLY_SYMMETRIC: 1624 case MAT_HERMITIAN: 1625 case MAT_SYMMETRY_ETERNAL: 1626 /* These options are handled directly by MatSetOption() */ 1627 break; 1628 default: 1629 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %s",MatOptions[op]); 1630 } 1631 PetscFunctionReturn(0); 1632 } 1633 1634 static PetscErrorCode MatZeroEntries_SeqDense(Mat A) 1635 { 1636 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 1637 PetscErrorCode ierr; 1638 PetscInt lda=l->lda,m=A->rmap->n,j; 1639 1640 PetscFunctionBegin; 1641 if (lda>m) { 1642 for (j=0; j<A->cmap->n; j++) { 1643 ierr = PetscMemzero(l->v+j*lda,m*sizeof(PetscScalar));CHKERRQ(ierr); 1644 } 1645 } else { 1646 ierr = PetscMemzero(l->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 1647 } 1648 PetscFunctionReturn(0); 1649 } 1650 1651 static PetscErrorCode MatZeroRows_SeqDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1652 { 1653 PetscErrorCode ierr; 1654 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 1655 PetscInt m = l->lda, n = A->cmap->n, i,j; 1656 PetscScalar *slot,*bb; 1657 const PetscScalar *xx; 1658 1659 PetscFunctionBegin; 1660 #if defined(PETSC_USE_DEBUG) 1661 for (i=0; i<N; i++) { 1662 if (rows[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row requested to be zeroed"); 1663 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); 1664 } 1665 #endif 1666 1667 /* fix right hand side if needed */ 1668 if (x && b) { 1669 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1670 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1671 for (i=0; i<N; i++) bb[rows[i]] = diag*xx[rows[i]]; 1672 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1673 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1674 } 1675 1676 for (i=0; i<N; i++) { 1677 slot = l->v + rows[i]; 1678 for (j=0; j<n; j++) { *slot = 0.0; slot += m;} 1679 } 1680 if (diag != 0.0) { 1681 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only coded for square matrices"); 1682 for (i=0; i<N; i++) { 1683 slot = l->v + (m+1)*rows[i]; 1684 *slot = diag; 1685 } 1686 } 1687 PetscFunctionReturn(0); 1688 } 1689 1690 static PetscErrorCode MatDenseGetArray_SeqDense(Mat A,PetscScalar *array[]) 1691 { 1692 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1693 1694 PetscFunctionBegin; 1695 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"); 1696 *array = mat->v; 1697 PetscFunctionReturn(0); 1698 } 1699 1700 static PetscErrorCode MatDenseRestoreArray_SeqDense(Mat A,PetscScalar *array[]) 1701 { 1702 PetscFunctionBegin; 1703 *array = 0; /* user cannot accidently use the array later */ 1704 PetscFunctionReturn(0); 1705 } 1706 1707 /*@C 1708 MatDenseGetArray - gives access to the array where the data for a SeqDense matrix is stored 1709 1710 Not Collective 1711 1712 Input Parameter: 1713 . mat - a MATSEQDENSE or MATMPIDENSE matrix 1714 1715 Output Parameter: 1716 . array - pointer to the data 1717 1718 Level: intermediate 1719 1720 .seealso: MatDenseRestoreArray() 1721 @*/ 1722 PetscErrorCode MatDenseGetArray(Mat A,PetscScalar **array) 1723 { 1724 PetscErrorCode ierr; 1725 1726 PetscFunctionBegin; 1727 ierr = PetscUseMethod(A,"MatDenseGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 1728 PetscFunctionReturn(0); 1729 } 1730 1731 /*@C 1732 MatDenseRestoreArray - returns access to the array where the data for a dense matrix is stored obtained by MatDenseGetArray() 1733 1734 Not Collective 1735 1736 Input Parameters: 1737 . mat - a MATSEQDENSE or MATMPIDENSE matrix 1738 . array - pointer to the data 1739 1740 Level: intermediate 1741 1742 .seealso: MatDenseGetArray() 1743 @*/ 1744 PetscErrorCode MatDenseRestoreArray(Mat A,PetscScalar **array) 1745 { 1746 PetscErrorCode ierr; 1747 1748 PetscFunctionBegin; 1749 ierr = PetscUseMethod(A,"MatDenseRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 1750 PetscFunctionReturn(0); 1751 } 1752 1753 static PetscErrorCode MatCreateSubMatrix_SeqDense(Mat A,IS isrow,IS iscol,PetscInt cs,MatReuse scall,Mat *B) 1754 { 1755 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1756 PetscErrorCode ierr; 1757 PetscInt i,j,nrows,ncols; 1758 const PetscInt *irow,*icol; 1759 PetscScalar *av,*bv,*v = mat->v; 1760 Mat newmat; 1761 1762 PetscFunctionBegin; 1763 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 1764 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 1765 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 1766 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 1767 1768 /* Check submatrixcall */ 1769 if (scall == MAT_REUSE_MATRIX) { 1770 PetscInt n_cols,n_rows; 1771 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 1772 if (n_rows != nrows || n_cols != ncols) { 1773 /* resize the result matrix to match number of requested rows/columns */ 1774 ierr = MatSetSizes(*B,nrows,ncols,nrows,ncols);CHKERRQ(ierr); 1775 } 1776 newmat = *B; 1777 } else { 1778 /* Create and fill new matrix */ 1779 ierr = MatCreate(PetscObjectComm((PetscObject)A),&newmat);CHKERRQ(ierr); 1780 ierr = MatSetSizes(newmat,nrows,ncols,nrows,ncols);CHKERRQ(ierr); 1781 ierr = MatSetType(newmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1782 ierr = MatSeqDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1783 } 1784 1785 /* Now extract the data pointers and do the copy,column at a time */ 1786 bv = ((Mat_SeqDense*)newmat->data)->v; 1787 1788 for (i=0; i<ncols; i++) { 1789 av = v + mat->lda*icol[i]; 1790 for (j=0; j<nrows; j++) *bv++ = av[irow[j]]; 1791 } 1792 1793 /* Assemble the matrices so that the correct flags are set */ 1794 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1795 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1796 1797 /* Free work space */ 1798 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 1799 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 1800 *B = newmat; 1801 PetscFunctionReturn(0); 1802 } 1803 1804 static PetscErrorCode MatCreateSubMatrices_SeqDense(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1805 { 1806 PetscErrorCode ierr; 1807 PetscInt i; 1808 1809 PetscFunctionBegin; 1810 if (scall == MAT_INITIAL_MATRIX) { 1811 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 1812 } 1813 1814 for (i=0; i<n; i++) { 1815 ierr = MatCreateSubMatrix_SeqDense(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 1816 } 1817 PetscFunctionReturn(0); 1818 } 1819 1820 static PetscErrorCode MatAssemblyBegin_SeqDense(Mat mat,MatAssemblyType mode) 1821 { 1822 PetscFunctionBegin; 1823 PetscFunctionReturn(0); 1824 } 1825 1826 static PetscErrorCode MatAssemblyEnd_SeqDense(Mat mat,MatAssemblyType mode) 1827 { 1828 PetscFunctionBegin; 1829 PetscFunctionReturn(0); 1830 } 1831 1832 static PetscErrorCode MatCopy_SeqDense(Mat A,Mat B,MatStructure str) 1833 { 1834 Mat_SeqDense *a = (Mat_SeqDense*)A->data,*b = (Mat_SeqDense*)B->data; 1835 PetscErrorCode ierr; 1836 PetscInt lda1=a->lda,lda2=b->lda, m=A->rmap->n,n=A->cmap->n, j; 1837 1838 PetscFunctionBegin; 1839 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1840 if (A->ops->copy != B->ops->copy) { 1841 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1842 PetscFunctionReturn(0); 1843 } 1844 if (m != B->rmap->n || n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"size(B) != size(A)"); 1845 if (lda1>m || lda2>m) { 1846 for (j=0; j<n; j++) { 1847 ierr = PetscMemcpy(b->v+j*lda2,a->v+j*lda1,m*sizeof(PetscScalar));CHKERRQ(ierr); 1848 } 1849 } else { 1850 ierr = PetscMemcpy(b->v,a->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 1851 } 1852 ierr = PetscObjectStateIncrease((PetscObject)B);CHKERRQ(ierr); 1853 PetscFunctionReturn(0); 1854 } 1855 1856 static PetscErrorCode MatSetUp_SeqDense(Mat A) 1857 { 1858 PetscErrorCode ierr; 1859 1860 PetscFunctionBegin; 1861 ierr = MatSeqDenseSetPreallocation(A,0);CHKERRQ(ierr); 1862 PetscFunctionReturn(0); 1863 } 1864 1865 static PetscErrorCode MatConjugate_SeqDense(Mat A) 1866 { 1867 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1868 PetscInt i,nz = A->rmap->n*A->cmap->n; 1869 PetscScalar *aa = a->v; 1870 1871 PetscFunctionBegin; 1872 for (i=0; i<nz; i++) aa[i] = PetscConj(aa[i]); 1873 PetscFunctionReturn(0); 1874 } 1875 1876 static PetscErrorCode MatRealPart_SeqDense(Mat A) 1877 { 1878 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1879 PetscInt i,nz = A->rmap->n*A->cmap->n; 1880 PetscScalar *aa = a->v; 1881 1882 PetscFunctionBegin; 1883 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1884 PetscFunctionReturn(0); 1885 } 1886 1887 static PetscErrorCode MatImaginaryPart_SeqDense(Mat A) 1888 { 1889 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1890 PetscInt i,nz = A->rmap->n*A->cmap->n; 1891 PetscScalar *aa = a->v; 1892 1893 PetscFunctionBegin; 1894 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1895 PetscFunctionReturn(0); 1896 } 1897 1898 /* ----------------------------------------------------------------*/ 1899 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1900 { 1901 PetscErrorCode ierr; 1902 1903 PetscFunctionBegin; 1904 if (scall == MAT_INITIAL_MATRIX) { 1905 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1906 ierr = MatMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 1907 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1908 } 1909 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 1910 ierr = MatMatMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 1911 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 1912 PetscFunctionReturn(0); 1913 } 1914 1915 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 1916 { 1917 PetscErrorCode ierr; 1918 PetscInt m=A->rmap->n,n=B->cmap->n; 1919 Mat Cmat; 1920 1921 PetscFunctionBegin; 1922 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); 1923 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 1924 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 1925 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 1926 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 1927 1928 *C = Cmat; 1929 PetscFunctionReturn(0); 1930 } 1931 1932 PetscErrorCode MatMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 1933 { 1934 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1935 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 1936 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 1937 PetscBLASInt m,n,k; 1938 PetscScalar _DOne=1.0,_DZero=0.0; 1939 PetscErrorCode ierr; 1940 PetscBool flg; 1941 1942 PetscFunctionBegin; 1943 ierr = PetscObjectTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr); 1944 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Second matrix must be dense"); 1945 1946 /* Handle case where where user provided the final C matrix rather than calling MatMatMult() with MAT_INITIAL_MATRIX*/ 1947 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&flg);CHKERRQ(ierr); 1948 if (flg) { 1949 C->ops->matmultnumeric = MatMatMultNumeric_SeqAIJ_SeqDense; 1950 ierr = (*C->ops->matmultnumeric)(A,B,C);CHKERRQ(ierr); 1951 PetscFunctionReturn(0); 1952 } 1953 1954 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQDENSE,&flg);CHKERRQ(ierr); 1955 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"First matrix must be dense"); 1956 ierr = PetscBLASIntCast(C->rmap->n,&m);CHKERRQ(ierr); 1957 ierr = PetscBLASIntCast(C->cmap->n,&n);CHKERRQ(ierr); 1958 ierr = PetscBLASIntCast(A->cmap->n,&k);CHKERRQ(ierr); 1959 PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 1960 PetscFunctionReturn(0); 1961 } 1962 1963 PetscErrorCode MatMatTransposeMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1964 { 1965 PetscErrorCode ierr; 1966 1967 PetscFunctionBegin; 1968 if (scall == MAT_INITIAL_MATRIX) { 1969 ierr = PetscLogEventBegin(MAT_MatTransposeMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1970 ierr = MatMatTransposeMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 1971 ierr = PetscLogEventEnd(MAT_MatTransposeMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1972 } 1973 ierr = PetscLogEventBegin(MAT_MatTransposeMultNumeric,A,B,0,0);CHKERRQ(ierr); 1974 ierr = MatMatTransposeMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 1975 ierr = PetscLogEventEnd(MAT_MatTransposeMultNumeric,A,B,0,0);CHKERRQ(ierr); 1976 PetscFunctionReturn(0); 1977 } 1978 1979 PetscErrorCode MatMatTransposeMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 1980 { 1981 PetscErrorCode ierr; 1982 PetscInt m=A->rmap->n,n=B->rmap->n; 1983 Mat Cmat; 1984 1985 PetscFunctionBegin; 1986 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); 1987 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 1988 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 1989 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 1990 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 1991 1992 Cmat->assembled = PETSC_TRUE; 1993 1994 *C = Cmat; 1995 PetscFunctionReturn(0); 1996 } 1997 1998 PetscErrorCode MatMatTransposeMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 1999 { 2000 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2001 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2002 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 2003 PetscBLASInt m,n,k; 2004 PetscScalar _DOne=1.0,_DZero=0.0; 2005 PetscErrorCode ierr; 2006 2007 PetscFunctionBegin; 2008 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 2009 ierr = PetscBLASIntCast(B->rmap->n,&n);CHKERRQ(ierr); 2010 ierr = PetscBLASIntCast(A->cmap->n,&k);CHKERRQ(ierr); 2011 PetscStackCallBLAS("BLASgemm",BLASgemm_("N","T",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 2012 PetscFunctionReturn(0); 2013 } 2014 2015 PetscErrorCode MatTransposeMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 2016 { 2017 PetscErrorCode ierr; 2018 2019 PetscFunctionBegin; 2020 if (scall == MAT_INITIAL_MATRIX) { 2021 ierr = PetscLogEventBegin(MAT_TransposeMatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2022 ierr = MatTransposeMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 2023 ierr = PetscLogEventEnd(MAT_TransposeMatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2024 } 2025 ierr = PetscLogEventBegin(MAT_TransposeMatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2026 ierr = MatTransposeMatMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 2027 ierr = PetscLogEventEnd(MAT_TransposeMatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2028 PetscFunctionReturn(0); 2029 } 2030 2031 PetscErrorCode MatTransposeMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 2032 { 2033 PetscErrorCode ierr; 2034 PetscInt m=A->cmap->n,n=B->cmap->n; 2035 Mat Cmat; 2036 2037 PetscFunctionBegin; 2038 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); 2039 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 2040 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 2041 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 2042 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 2043 2044 Cmat->assembled = PETSC_TRUE; 2045 2046 *C = Cmat; 2047 PetscFunctionReturn(0); 2048 } 2049 2050 PetscErrorCode MatTransposeMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 2051 { 2052 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2053 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2054 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 2055 PetscBLASInt m,n,k; 2056 PetscScalar _DOne=1.0,_DZero=0.0; 2057 PetscErrorCode ierr; 2058 2059 PetscFunctionBegin; 2060 ierr = PetscBLASIntCast(C->rmap->n,&m);CHKERRQ(ierr); 2061 ierr = PetscBLASIntCast(C->cmap->n,&n);CHKERRQ(ierr); 2062 ierr = PetscBLASIntCast(A->rmap->n,&k);CHKERRQ(ierr); 2063 PetscStackCallBLAS("BLASgemm",BLASgemm_("T","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 2064 PetscFunctionReturn(0); 2065 } 2066 2067 static PetscErrorCode MatGetRowMax_SeqDense(Mat A,Vec v,PetscInt idx[]) 2068 { 2069 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2070 PetscErrorCode ierr; 2071 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2072 PetscScalar *x; 2073 MatScalar *aa = a->v; 2074 2075 PetscFunctionBegin; 2076 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2077 2078 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2079 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2080 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2081 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2082 for (i=0; i<m; i++) { 2083 x[i] = aa[i]; if (idx) idx[i] = 0; 2084 for (j=1; j<n; j++) { 2085 if (PetscRealPart(x[i]) < PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;} 2086 } 2087 } 2088 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2089 PetscFunctionReturn(0); 2090 } 2091 2092 static PetscErrorCode MatGetRowMaxAbs_SeqDense(Mat A,Vec v,PetscInt idx[]) 2093 { 2094 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2095 PetscErrorCode ierr; 2096 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2097 PetscScalar *x; 2098 PetscReal atmp; 2099 MatScalar *aa = a->v; 2100 2101 PetscFunctionBegin; 2102 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2103 2104 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2105 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2106 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2107 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2108 for (i=0; i<m; i++) { 2109 x[i] = PetscAbsScalar(aa[i]); 2110 for (j=1; j<n; j++) { 2111 atmp = PetscAbsScalar(aa[i+m*j]); 2112 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = j;} 2113 } 2114 } 2115 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2116 PetscFunctionReturn(0); 2117 } 2118 2119 static PetscErrorCode MatGetRowMin_SeqDense(Mat A,Vec v,PetscInt idx[]) 2120 { 2121 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2122 PetscErrorCode ierr; 2123 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2124 PetscScalar *x; 2125 MatScalar *aa = a->v; 2126 2127 PetscFunctionBegin; 2128 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2129 2130 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2131 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2132 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2133 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2134 for (i=0; i<m; i++) { 2135 x[i] = aa[i]; if (idx) idx[i] = 0; 2136 for (j=1; j<n; j++) { 2137 if (PetscRealPart(x[i]) > PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;} 2138 } 2139 } 2140 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2141 PetscFunctionReturn(0); 2142 } 2143 2144 static PetscErrorCode MatGetColumnVector_SeqDense(Mat A,Vec v,PetscInt col) 2145 { 2146 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2147 PetscErrorCode ierr; 2148 PetscScalar *x; 2149 2150 PetscFunctionBegin; 2151 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2152 2153 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2154 ierr = PetscMemcpy(x,a->v+col*a->lda,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 2155 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2156 PetscFunctionReturn(0); 2157 } 2158 2159 PetscErrorCode MatGetColumnNorms_SeqDense(Mat A,NormType type,PetscReal *norms) 2160 { 2161 PetscErrorCode ierr; 2162 PetscInt i,j,m,n; 2163 PetscScalar *a; 2164 2165 PetscFunctionBegin; 2166 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 2167 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 2168 ierr = MatDenseGetArray(A,&a);CHKERRQ(ierr); 2169 if (type == NORM_2) { 2170 for (i=0; i<n; i++) { 2171 for (j=0; j<m; j++) { 2172 norms[i] += PetscAbsScalar(a[j]*a[j]); 2173 } 2174 a += m; 2175 } 2176 } else if (type == NORM_1) { 2177 for (i=0; i<n; i++) { 2178 for (j=0; j<m; j++) { 2179 norms[i] += PetscAbsScalar(a[j]); 2180 } 2181 a += m; 2182 } 2183 } else if (type == NORM_INFINITY) { 2184 for (i=0; i<n; i++) { 2185 for (j=0; j<m; j++) { 2186 norms[i] = PetscMax(PetscAbsScalar(a[j]),norms[i]); 2187 } 2188 a += m; 2189 } 2190 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2191 ierr = MatDenseRestoreArray(A,&a);CHKERRQ(ierr); 2192 if (type == NORM_2) { 2193 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 2194 } 2195 PetscFunctionReturn(0); 2196 } 2197 2198 static PetscErrorCode MatSetRandom_SeqDense(Mat x,PetscRandom rctx) 2199 { 2200 PetscErrorCode ierr; 2201 PetscScalar *a; 2202 PetscInt m,n,i; 2203 2204 PetscFunctionBegin; 2205 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 2206 ierr = MatDenseGetArray(x,&a);CHKERRQ(ierr); 2207 for (i=0; i<m*n; i++) { 2208 ierr = PetscRandomGetValue(rctx,a+i);CHKERRQ(ierr); 2209 } 2210 ierr = MatDenseRestoreArray(x,&a);CHKERRQ(ierr); 2211 PetscFunctionReturn(0); 2212 } 2213 2214 static PetscErrorCode MatMissingDiagonal_SeqDense(Mat A,PetscBool *missing,PetscInt *d) 2215 { 2216 PetscFunctionBegin; 2217 *missing = PETSC_FALSE; 2218 PetscFunctionReturn(0); 2219 } 2220 2221 static PetscErrorCode MatDenseGetColumn_SeqDense(Mat A,PetscInt col,PetscScalar **vals) 2222 { 2223 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2224 2225 PetscFunctionBegin; 2226 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2227 *vals = a->v+col*a->lda; 2228 PetscFunctionReturn(0); 2229 } 2230 2231 static PetscErrorCode MatDenseRestoreColumn_SeqDense(Mat A,PetscScalar **vals) 2232 { 2233 PetscFunctionBegin; 2234 *vals = 0; /* user cannot accidently use the array later */ 2235 PetscFunctionReturn(0); 2236 } 2237 2238 /* -------------------------------------------------------------------*/ 2239 static struct _MatOps MatOps_Values = { MatSetValues_SeqDense, 2240 MatGetRow_SeqDense, 2241 MatRestoreRow_SeqDense, 2242 MatMult_SeqDense, 2243 /* 4*/ MatMultAdd_SeqDense, 2244 MatMultTranspose_SeqDense, 2245 MatMultTransposeAdd_SeqDense, 2246 0, 2247 0, 2248 0, 2249 /* 10*/ 0, 2250 MatLUFactor_SeqDense, 2251 MatCholeskyFactor_SeqDense, 2252 MatSOR_SeqDense, 2253 MatTranspose_SeqDense, 2254 /* 15*/ MatGetInfo_SeqDense, 2255 MatEqual_SeqDense, 2256 MatGetDiagonal_SeqDense, 2257 MatDiagonalScale_SeqDense, 2258 MatNorm_SeqDense, 2259 /* 20*/ MatAssemblyBegin_SeqDense, 2260 MatAssemblyEnd_SeqDense, 2261 MatSetOption_SeqDense, 2262 MatZeroEntries_SeqDense, 2263 /* 24*/ MatZeroRows_SeqDense, 2264 0, 2265 0, 2266 0, 2267 0, 2268 /* 29*/ MatSetUp_SeqDense, 2269 0, 2270 0, 2271 0, 2272 0, 2273 /* 34*/ MatDuplicate_SeqDense, 2274 0, 2275 0, 2276 0, 2277 0, 2278 /* 39*/ MatAXPY_SeqDense, 2279 MatCreateSubMatrices_SeqDense, 2280 0, 2281 MatGetValues_SeqDense, 2282 MatCopy_SeqDense, 2283 /* 44*/ MatGetRowMax_SeqDense, 2284 MatScale_SeqDense, 2285 MatShift_Basic, 2286 0, 2287 MatZeroRowsColumns_SeqDense, 2288 /* 49*/ MatSetRandom_SeqDense, 2289 0, 2290 0, 2291 0, 2292 0, 2293 /* 54*/ 0, 2294 0, 2295 0, 2296 0, 2297 0, 2298 /* 59*/ 0, 2299 MatDestroy_SeqDense, 2300 MatView_SeqDense, 2301 0, 2302 0, 2303 /* 64*/ 0, 2304 0, 2305 0, 2306 0, 2307 0, 2308 /* 69*/ MatGetRowMaxAbs_SeqDense, 2309 0, 2310 0, 2311 0, 2312 0, 2313 /* 74*/ 0, 2314 0, 2315 0, 2316 0, 2317 0, 2318 /* 79*/ 0, 2319 0, 2320 0, 2321 0, 2322 /* 83*/ MatLoad_SeqDense, 2323 0, 2324 MatIsHermitian_SeqDense, 2325 0, 2326 0, 2327 0, 2328 /* 89*/ MatMatMult_SeqDense_SeqDense, 2329 MatMatMultSymbolic_SeqDense_SeqDense, 2330 MatMatMultNumeric_SeqDense_SeqDense, 2331 MatPtAP_SeqDense_SeqDense, 2332 MatPtAPSymbolic_SeqDense_SeqDense, 2333 /* 94*/ MatPtAPNumeric_SeqDense_SeqDense, 2334 MatMatTransposeMult_SeqDense_SeqDense, 2335 MatMatTransposeMultSymbolic_SeqDense_SeqDense, 2336 MatMatTransposeMultNumeric_SeqDense_SeqDense, 2337 0, 2338 /* 99*/ 0, 2339 0, 2340 0, 2341 MatConjugate_SeqDense, 2342 0, 2343 /*104*/ 0, 2344 MatRealPart_SeqDense, 2345 MatImaginaryPart_SeqDense, 2346 0, 2347 0, 2348 /*109*/ 0, 2349 0, 2350 MatGetRowMin_SeqDense, 2351 MatGetColumnVector_SeqDense, 2352 MatMissingDiagonal_SeqDense, 2353 /*114*/ 0, 2354 0, 2355 0, 2356 0, 2357 0, 2358 /*119*/ 0, 2359 0, 2360 0, 2361 0, 2362 0, 2363 /*124*/ 0, 2364 MatGetColumnNorms_SeqDense, 2365 0, 2366 0, 2367 0, 2368 /*129*/ 0, 2369 MatTransposeMatMult_SeqDense_SeqDense, 2370 MatTransposeMatMultSymbolic_SeqDense_SeqDense, 2371 MatTransposeMatMultNumeric_SeqDense_SeqDense, 2372 0, 2373 /*134*/ 0, 2374 0, 2375 0, 2376 0, 2377 0, 2378 /*139*/ 0, 2379 0, 2380 0 2381 }; 2382 2383 /*@C 2384 MatCreateSeqDense - Creates a sequential dense matrix that 2385 is stored in column major order (the usual Fortran 77 manner). Many 2386 of the matrix operations use the BLAS and LAPACK routines. 2387 2388 Collective on MPI_Comm 2389 2390 Input Parameters: 2391 + comm - MPI communicator, set to PETSC_COMM_SELF 2392 . m - number of rows 2393 . n - number of columns 2394 - data - optional location of matrix data in column major order. Set data=NULL for PETSc 2395 to control all matrix memory allocation. 2396 2397 Output Parameter: 2398 . A - the matrix 2399 2400 Notes: 2401 The data input variable is intended primarily for Fortran programmers 2402 who wish to allocate their own matrix memory space. Most users should 2403 set data=NULL. 2404 2405 Level: intermediate 2406 2407 .keywords: dense, matrix, LAPACK, BLAS 2408 2409 .seealso: MatCreate(), MatCreateDense(), MatSetValues() 2410 @*/ 2411 PetscErrorCode MatCreateSeqDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscScalar *data,Mat *A) 2412 { 2413 PetscErrorCode ierr; 2414 2415 PetscFunctionBegin; 2416 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2417 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 2418 ierr = MatSetType(*A,MATSEQDENSE);CHKERRQ(ierr); 2419 ierr = MatSeqDenseSetPreallocation(*A,data);CHKERRQ(ierr); 2420 PetscFunctionReturn(0); 2421 } 2422 2423 /*@C 2424 MatSeqDenseSetPreallocation - Sets the array used for storing the matrix elements 2425 2426 Collective on MPI_Comm 2427 2428 Input Parameters: 2429 + B - the matrix 2430 - data - the array (or NULL) 2431 2432 Notes: 2433 The data input variable is intended primarily for Fortran programmers 2434 who wish to allocate their own matrix memory space. Most users should 2435 need not call this routine. 2436 2437 Level: intermediate 2438 2439 .keywords: dense, matrix, LAPACK, BLAS 2440 2441 .seealso: MatCreate(), MatCreateDense(), MatSetValues(), MatSeqDenseSetLDA() 2442 2443 @*/ 2444 PetscErrorCode MatSeqDenseSetPreallocation(Mat B,PetscScalar data[]) 2445 { 2446 PetscErrorCode ierr; 2447 2448 PetscFunctionBegin; 2449 ierr = PetscTryMethod(B,"MatSeqDenseSetPreallocation_C",(Mat,PetscScalar[]),(B,data));CHKERRQ(ierr); 2450 PetscFunctionReturn(0); 2451 } 2452 2453 PetscErrorCode MatSeqDenseSetPreallocation_SeqDense(Mat B,PetscScalar *data) 2454 { 2455 Mat_SeqDense *b; 2456 PetscErrorCode ierr; 2457 2458 PetscFunctionBegin; 2459 B->preallocated = PETSC_TRUE; 2460 2461 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2462 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2463 2464 b = (Mat_SeqDense*)B->data; 2465 b->Mmax = B->rmap->n; 2466 b->Nmax = B->cmap->n; 2467 if (b->lda <= 0 || b->changelda) b->lda = B->rmap->n; 2468 2469 ierr = PetscIntMultError(b->lda,b->Nmax,NULL);CHKERRQ(ierr); 2470 if (!data) { /* petsc-allocated storage */ 2471 if (!b->user_alloc) { ierr = PetscFree(b->v);CHKERRQ(ierr); } 2472 ierr = PetscCalloc1((size_t)b->lda*b->Nmax,&b->v);CHKERRQ(ierr); 2473 ierr = PetscLogObjectMemory((PetscObject)B,b->lda*b->Nmax*sizeof(PetscScalar));CHKERRQ(ierr); 2474 2475 b->user_alloc = PETSC_FALSE; 2476 } else { /* user-allocated storage */ 2477 if (!b->user_alloc) { ierr = PetscFree(b->v);CHKERRQ(ierr); } 2478 b->v = data; 2479 b->user_alloc = PETSC_TRUE; 2480 } 2481 B->assembled = PETSC_TRUE; 2482 PetscFunctionReturn(0); 2483 } 2484 2485 #if defined(PETSC_HAVE_ELEMENTAL) 2486 PETSC_INTERN PetscErrorCode MatConvert_SeqDense_Elemental(Mat A, MatType newtype,MatReuse reuse,Mat *newmat) 2487 { 2488 Mat mat_elemental; 2489 PetscErrorCode ierr; 2490 PetscScalar *array,*v_colwise; 2491 PetscInt M=A->rmap->N,N=A->cmap->N,i,j,k,*rows,*cols; 2492 2493 PetscFunctionBegin; 2494 ierr = PetscMalloc3(M*N,&v_colwise,M,&rows,N,&cols);CHKERRQ(ierr); 2495 ierr = MatDenseGetArray(A,&array);CHKERRQ(ierr); 2496 /* convert column-wise array into row-wise v_colwise, see MatSetValues_Elemental() */ 2497 k = 0; 2498 for (j=0; j<N; j++) { 2499 cols[j] = j; 2500 for (i=0; i<M; i++) { 2501 v_colwise[j*M+i] = array[k++]; 2502 } 2503 } 2504 for (i=0; i<M; i++) { 2505 rows[i] = i; 2506 } 2507 ierr = MatDenseRestoreArray(A,&array);CHKERRQ(ierr); 2508 2509 ierr = MatCreate(PetscObjectComm((PetscObject)A), &mat_elemental);CHKERRQ(ierr); 2510 ierr = MatSetSizes(mat_elemental,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 2511 ierr = MatSetType(mat_elemental,MATELEMENTAL);CHKERRQ(ierr); 2512 ierr = MatSetUp(mat_elemental);CHKERRQ(ierr); 2513 2514 /* PETSc-Elemental interaface uses axpy for setting off-processor entries, only ADD_VALUES is allowed */ 2515 ierr = MatSetValues(mat_elemental,M,rows,N,cols,v_colwise,ADD_VALUES);CHKERRQ(ierr); 2516 ierr = MatAssemblyBegin(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2517 ierr = MatAssemblyEnd(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2518 ierr = PetscFree3(v_colwise,rows,cols);CHKERRQ(ierr); 2519 2520 if (reuse == MAT_INPLACE_MATRIX) { 2521 ierr = MatHeaderReplace(A,&mat_elemental);CHKERRQ(ierr); 2522 } else { 2523 *newmat = mat_elemental; 2524 } 2525 PetscFunctionReturn(0); 2526 } 2527 #endif 2528 2529 /*@C 2530 MatSeqDenseSetLDA - Declare the leading dimension of the user-provided array 2531 2532 Input parameter: 2533 + A - the matrix 2534 - lda - the leading dimension 2535 2536 Notes: 2537 This routine is to be used in conjunction with MatSeqDenseSetPreallocation(); 2538 it asserts that the preallocation has a leading dimension (the LDA parameter 2539 of Blas and Lapack fame) larger than M, the first dimension of the matrix. 2540 2541 Level: intermediate 2542 2543 .keywords: dense, matrix, LAPACK, BLAS 2544 2545 .seealso: MatCreate(), MatCreateSeqDense(), MatSeqDenseSetPreallocation(), MatSetMaximumSize() 2546 2547 @*/ 2548 PetscErrorCode MatSeqDenseSetLDA(Mat B,PetscInt lda) 2549 { 2550 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2551 2552 PetscFunctionBegin; 2553 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); 2554 b->lda = lda; 2555 b->changelda = PETSC_FALSE; 2556 b->Mmax = PetscMax(b->Mmax,lda); 2557 PetscFunctionReturn(0); 2558 } 2559 2560 /*MC 2561 MATSEQDENSE - MATSEQDENSE = "seqdense" - A matrix type to be used for sequential dense matrices. 2562 2563 Options Database Keys: 2564 . -mat_type seqdense - sets the matrix type to "seqdense" during a call to MatSetFromOptions() 2565 2566 Level: beginner 2567 2568 .seealso: MatCreateSeqDense() 2569 2570 M*/ 2571 2572 PETSC_EXTERN PetscErrorCode MatCreate_SeqDense(Mat B) 2573 { 2574 Mat_SeqDense *b; 2575 PetscErrorCode ierr; 2576 PetscMPIInt size; 2577 2578 PetscFunctionBegin; 2579 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 2580 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1"); 2581 2582 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 2583 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2584 B->data = (void*)b; 2585 2586 b->roworiented = PETSC_TRUE; 2587 2588 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseGetArray_C",MatDenseGetArray_SeqDense);CHKERRQ(ierr); 2589 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDensePlaceArray_C",MatDensePlaceArray_SeqDense);CHKERRQ(ierr); 2590 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseResetArray_C",MatDenseResetArray_SeqDense);CHKERRQ(ierr); 2591 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseRestoreArray_C",MatDenseRestoreArray_SeqDense);CHKERRQ(ierr); 2592 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqdense_seqaij_C",MatConvert_SeqDense_SeqAIJ);CHKERRQ(ierr); 2593 #if defined(PETSC_HAVE_ELEMENTAL) 2594 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqdense_elemental_C",MatConvert_SeqDense_Elemental);CHKERRQ(ierr); 2595 #endif 2596 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqDenseSetPreallocation_C",MatSeqDenseSetPreallocation_SeqDense);CHKERRQ(ierr); 2597 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaij_seqdense_C",MatMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2598 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaij_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2599 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaij_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2600 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaij_seqdense_C",MatPtAP_SeqDense_SeqDense);CHKERRQ(ierr); 2601 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaijperm_seqdense_C",MatMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2602 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaijperm_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2603 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaijperm_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2604 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaijperm_seqdense_C",MatPtAP_SeqDense_SeqDense);CHKERRQ(ierr); 2605 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaijmkl_seqdense_C",MatMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2606 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaijmkl_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2607 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaijmkl_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2608 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaijmkl_seqdense_C",MatPtAP_SeqDense_SeqDense);CHKERRQ(ierr); 2609 2610 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaij_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2611 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaij_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2612 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaij_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2613 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaijperm_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2614 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaijperm_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2615 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaijperm_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2616 2617 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaijmkl_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2618 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaijmkl_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2619 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaijmkl_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2620 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseGetColumn_C",MatDenseGetColumn_SeqDense);CHKERRQ(ierr); 2621 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseRestoreColumn_C",MatDenseRestoreColumn_SeqDense);CHKERRQ(ierr); 2622 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQDENSE);CHKERRQ(ierr); 2623 PetscFunctionReturn(0); 2624 } 2625 2626 /*@C 2627 MatDenseGetColumn - gives access to a column of a dense matrix. This is only the local part of the column. You MUST call MatDenseRestoreColumn() to avoid memory bleeding. 2628 2629 Not Collective 2630 2631 Input Parameter: 2632 + mat - a MATSEQDENSE or MATMPIDENSE matrix 2633 - col - column index 2634 2635 Output Parameter: 2636 . vals - pointer to the data 2637 2638 Level: intermediate 2639 2640 .seealso: MatDenseRestoreColumn() 2641 @*/ 2642 PetscErrorCode MatDenseGetColumn(Mat A,PetscInt col,PetscScalar **vals) 2643 { 2644 PetscErrorCode ierr; 2645 2646 PetscFunctionBegin; 2647 ierr = PetscUseMethod(A,"MatDenseGetColumn_C",(Mat,PetscInt,PetscScalar**),(A,col,vals));CHKERRQ(ierr); 2648 PetscFunctionReturn(0); 2649 } 2650 2651 /*@C 2652 MatDenseRestoreColumn - returns access to a column of a dense matrix which is returned by MatDenseGetColumn(). 2653 2654 Not Collective 2655 2656 Input Parameter: 2657 . mat - a MATSEQDENSE or MATMPIDENSE matrix 2658 2659 Output Parameter: 2660 . vals - pointer to the data 2661 2662 Level: intermediate 2663 2664 .seealso: MatDenseGetColumn() 2665 @*/ 2666 PetscErrorCode MatDenseRestoreColumn(Mat A,PetscScalar **vals) 2667 { 2668 PetscErrorCode ierr; 2669 2670 PetscFunctionBegin; 2671 ierr = PetscUseMethod(A,"MatDenseRestoreColumn_C",(Mat,PetscScalar**),(A,vals));CHKERRQ(ierr); 2672 PetscFunctionReturn(0); 2673 } 2674