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 BLASdot */ 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("BLASdot",xt = b[i] - BLASdot_(&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("BLASdot",xt = b[i] - BLASdot_(&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 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 816 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 817 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 818 PetscStackCallBLAS("BLASgemv",BLASgemv_("T",&m,&n,&_DOne,v,&mat->lda,x,&_One,&_DZero,y,&_One)); 819 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 820 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 821 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->cmap->n);CHKERRQ(ierr); 822 PetscFunctionReturn(0); 823 } 824 825 PETSC_INTERN PetscErrorCode MatMult_SeqDense(Mat A,Vec xx,Vec yy) 826 { 827 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 828 PetscScalar *y,_DOne=1.0,_DZero=0.0; 829 PetscErrorCode ierr; 830 PetscBLASInt m, n, _One=1; 831 const PetscScalar *v = mat->v,*x; 832 833 PetscFunctionBegin; 834 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 835 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 836 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 837 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 838 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 839 PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DZero,y,&_One)); 840 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 841 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 842 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->rmap->n);CHKERRQ(ierr); 843 PetscFunctionReturn(0); 844 } 845 846 PETSC_INTERN PetscErrorCode MatMultAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 847 { 848 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 849 const PetscScalar *v = mat->v,*x; 850 PetscScalar *y,_DOne=1.0; 851 PetscErrorCode ierr; 852 PetscBLASInt m, n, _One=1; 853 854 PetscFunctionBegin; 855 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 856 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 857 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 858 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 859 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 860 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 861 PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One)); 862 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 863 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 864 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n);CHKERRQ(ierr); 865 PetscFunctionReturn(0); 866 } 867 868 static PetscErrorCode MatMultTransposeAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 869 { 870 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 871 const PetscScalar *v = mat->v,*x; 872 PetscScalar *y; 873 PetscErrorCode ierr; 874 PetscBLASInt m, n, _One=1; 875 PetscScalar _DOne=1.0; 876 877 PetscFunctionBegin; 878 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 879 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 880 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 881 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 882 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 883 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 884 PetscStackCallBLAS("BLASgemv",BLASgemv_("T",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One)); 885 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 886 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 887 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n);CHKERRQ(ierr); 888 PetscFunctionReturn(0); 889 } 890 891 /* -----------------------------------------------------------------*/ 892 static PetscErrorCode MatGetRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals) 893 { 894 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 895 PetscScalar *v; 896 PetscErrorCode ierr; 897 PetscInt i; 898 899 PetscFunctionBegin; 900 *ncols = A->cmap->n; 901 if (cols) { 902 ierr = PetscMalloc1(A->cmap->n+1,cols);CHKERRQ(ierr); 903 for (i=0; i<A->cmap->n; i++) (*cols)[i] = i; 904 } 905 if (vals) { 906 ierr = PetscMalloc1(A->cmap->n+1,vals);CHKERRQ(ierr); 907 v = mat->v + row; 908 for (i=0; i<A->cmap->n; i++) {(*vals)[i] = *v; v += mat->lda;} 909 } 910 PetscFunctionReturn(0); 911 } 912 913 static PetscErrorCode MatRestoreRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals) 914 { 915 PetscErrorCode ierr; 916 917 PetscFunctionBegin; 918 if (cols) {ierr = PetscFree(*cols);CHKERRQ(ierr);} 919 if (vals) {ierr = PetscFree(*vals);CHKERRQ(ierr); } 920 PetscFunctionReturn(0); 921 } 922 /* ----------------------------------------------------------------*/ 923 static PetscErrorCode MatSetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],const PetscScalar v[],InsertMode addv) 924 { 925 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 926 PetscInt i,j,idx=0; 927 928 PetscFunctionBegin; 929 if (!mat->roworiented) { 930 if (addv == INSERT_VALUES) { 931 for (j=0; j<n; j++) { 932 if (indexn[j] < 0) {idx += m; continue;} 933 #if defined(PETSC_USE_DEBUG) 934 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); 935 #endif 936 for (i=0; i<m; i++) { 937 if (indexm[i] < 0) {idx++; continue;} 938 #if defined(PETSC_USE_DEBUG) 939 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); 940 #endif 941 mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++]; 942 } 943 } 944 } else { 945 for (j=0; j<n; j++) { 946 if (indexn[j] < 0) {idx += m; continue;} 947 #if defined(PETSC_USE_DEBUG) 948 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); 949 #endif 950 for (i=0; i<m; i++) { 951 if (indexm[i] < 0) {idx++; continue;} 952 #if defined(PETSC_USE_DEBUG) 953 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); 954 #endif 955 mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++]; 956 } 957 } 958 } 959 } else { 960 if (addv == INSERT_VALUES) { 961 for (i=0; i<m; i++) { 962 if (indexm[i] < 0) { idx += n; continue;} 963 #if defined(PETSC_USE_DEBUG) 964 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); 965 #endif 966 for (j=0; j<n; j++) { 967 if (indexn[j] < 0) { idx++; continue;} 968 #if defined(PETSC_USE_DEBUG) 969 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); 970 #endif 971 mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++]; 972 } 973 } 974 } else { 975 for (i=0; i<m; i++) { 976 if (indexm[i] < 0) { idx += n; continue;} 977 #if defined(PETSC_USE_DEBUG) 978 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); 979 #endif 980 for (j=0; j<n; j++) { 981 if (indexn[j] < 0) { idx++; continue;} 982 #if defined(PETSC_USE_DEBUG) 983 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); 984 #endif 985 mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++]; 986 } 987 } 988 } 989 } 990 PetscFunctionReturn(0); 991 } 992 993 static PetscErrorCode MatGetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],PetscScalar v[]) 994 { 995 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 996 PetscInt i,j; 997 998 PetscFunctionBegin; 999 /* row-oriented output */ 1000 for (i=0; i<m; i++) { 1001 if (indexm[i] < 0) {v += n;continue;} 1002 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); 1003 for (j=0; j<n; j++) { 1004 if (indexn[j] < 0) {v++; continue;} 1005 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); 1006 *v++ = mat->v[indexn[j]*mat->lda + indexm[i]]; 1007 } 1008 } 1009 PetscFunctionReturn(0); 1010 } 1011 1012 /* -----------------------------------------------------------------*/ 1013 1014 static PetscErrorCode MatLoad_SeqDense(Mat newmat,PetscViewer viewer) 1015 { 1016 Mat_SeqDense *a; 1017 PetscErrorCode ierr; 1018 PetscInt *scols,i,j,nz,header[4]; 1019 int fd; 1020 PetscMPIInt size; 1021 PetscInt *rowlengths = 0,M,N,*cols,grows,gcols; 1022 PetscScalar *vals,*svals,*v,*w; 1023 MPI_Comm comm; 1024 1025 PetscFunctionBegin; 1026 /* force binary viewer to load .info file if it has not yet done so */ 1027 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 1028 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 1029 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1030 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor"); 1031 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1032 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 1033 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Not matrix object"); 1034 M = header[1]; N = header[2]; nz = header[3]; 1035 1036 /* set global size if not set already*/ 1037 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) { 1038 ierr = MatSetSizes(newmat,M,N,M,N);CHKERRQ(ierr); 1039 } else { 1040 /* if sizes and type are already set, check if the vector global sizes are correct */ 1041 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 1042 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); 1043 } 1044 a = (Mat_SeqDense*)newmat->data; 1045 if (!a->user_alloc) { 1046 ierr = MatSeqDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1047 } 1048 1049 if (nz == MATRIX_BINARY_FORMAT_DENSE) { /* matrix in file is dense */ 1050 a = (Mat_SeqDense*)newmat->data; 1051 v = a->v; 1052 /* Allocate some temp space to read in the values and then flip them 1053 from row major to column major */ 1054 ierr = PetscMalloc1(M*N > 0 ? M*N : 1,&w);CHKERRQ(ierr); 1055 /* read in nonzero values */ 1056 ierr = PetscBinaryRead(fd,w,M*N,PETSC_SCALAR);CHKERRQ(ierr); 1057 /* now flip the values and store them in the matrix*/ 1058 for (j=0; j<N; j++) { 1059 for (i=0; i<M; i++) { 1060 *v++ =w[i*N+j]; 1061 } 1062 } 1063 ierr = PetscFree(w);CHKERRQ(ierr); 1064 } else { 1065 /* read row lengths */ 1066 ierr = PetscMalloc1(M+1,&rowlengths);CHKERRQ(ierr); 1067 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 1068 1069 a = (Mat_SeqDense*)newmat->data; 1070 v = a->v; 1071 1072 /* read column indices and nonzeros */ 1073 ierr = PetscMalloc1(nz+1,&scols);CHKERRQ(ierr); 1074 cols = scols; 1075 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 1076 ierr = PetscMalloc1(nz+1,&svals);CHKERRQ(ierr); 1077 vals = svals; 1078 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1079 1080 /* insert into matrix */ 1081 for (i=0; i<M; i++) { 1082 for (j=0; j<rowlengths[i]; j++) v[i+M*scols[j]] = svals[j]; 1083 svals += rowlengths[i]; scols += rowlengths[i]; 1084 } 1085 ierr = PetscFree(vals);CHKERRQ(ierr); 1086 ierr = PetscFree(cols);CHKERRQ(ierr); 1087 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1088 } 1089 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1090 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1091 PetscFunctionReturn(0); 1092 } 1093 1094 static PetscErrorCode MatView_SeqDense_ASCII(Mat A,PetscViewer viewer) 1095 { 1096 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1097 PetscErrorCode ierr; 1098 PetscInt i,j; 1099 const char *name; 1100 PetscScalar *v; 1101 PetscViewerFormat format; 1102 #if defined(PETSC_USE_COMPLEX) 1103 PetscBool allreal = PETSC_TRUE; 1104 #endif 1105 1106 PetscFunctionBegin; 1107 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1108 if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1109 PetscFunctionReturn(0); /* do nothing for now */ 1110 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 1111 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1112 for (i=0; i<A->rmap->n; i++) { 1113 v = a->v + i; 1114 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 1115 for (j=0; j<A->cmap->n; j++) { 1116 #if defined(PETSC_USE_COMPLEX) 1117 if (PetscRealPart(*v) != 0.0 && PetscImaginaryPart(*v) != 0.0) { 1118 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i) ",j,(double)PetscRealPart(*v),(double)PetscImaginaryPart(*v));CHKERRQ(ierr); 1119 } else if (PetscRealPart(*v)) { 1120 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",j,(double)PetscRealPart(*v));CHKERRQ(ierr); 1121 } 1122 #else 1123 if (*v) { 1124 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",j,(double)*v);CHKERRQ(ierr); 1125 } 1126 #endif 1127 v += a->lda; 1128 } 1129 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1130 } 1131 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1132 } else { 1133 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1134 #if defined(PETSC_USE_COMPLEX) 1135 /* determine if matrix has all real values */ 1136 v = a->v; 1137 for (i=0; i<A->rmap->n*A->cmap->n; i++) { 1138 if (PetscImaginaryPart(v[i])) { allreal = PETSC_FALSE; break;} 1139 } 1140 #endif 1141 if (format == PETSC_VIEWER_ASCII_MATLAB) { 1142 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 1143 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",A->rmap->n,A->cmap->n);CHKERRQ(ierr); 1144 ierr = PetscViewerASCIIPrintf(viewer,"%s = zeros(%D,%D);\n",name,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 1145 ierr = PetscViewerASCIIPrintf(viewer,"%s = [\n",name);CHKERRQ(ierr); 1146 } 1147 1148 for (i=0; i<A->rmap->n; i++) { 1149 v = a->v + i; 1150 for (j=0; j<A->cmap->n; j++) { 1151 #if defined(PETSC_USE_COMPLEX) 1152 if (allreal) { 1153 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)PetscRealPart(*v));CHKERRQ(ierr); 1154 } else { 1155 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e + %18.16ei ",(double)PetscRealPart(*v),(double)PetscImaginaryPart(*v));CHKERRQ(ierr); 1156 } 1157 #else 1158 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)*v);CHKERRQ(ierr); 1159 #endif 1160 v += a->lda; 1161 } 1162 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1163 } 1164 if (format == PETSC_VIEWER_ASCII_MATLAB) { 1165 ierr = PetscViewerASCIIPrintf(viewer,"];\n");CHKERRQ(ierr); 1166 } 1167 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1168 } 1169 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1170 PetscFunctionReturn(0); 1171 } 1172 1173 static PetscErrorCode MatView_SeqDense_Binary(Mat A,PetscViewer viewer) 1174 { 1175 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1176 PetscErrorCode ierr; 1177 int fd; 1178 PetscInt ict,j,n = A->cmap->n,m = A->rmap->n,i,*col_lens,nz = m*n; 1179 PetscScalar *v,*anonz,*vals; 1180 PetscViewerFormat format; 1181 1182 PetscFunctionBegin; 1183 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1184 1185 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1186 if (format == PETSC_VIEWER_NATIVE) { 1187 /* store the matrix as a dense matrix */ 1188 ierr = PetscMalloc1(4,&col_lens);CHKERRQ(ierr); 1189 1190 col_lens[0] = MAT_FILE_CLASSID; 1191 col_lens[1] = m; 1192 col_lens[2] = n; 1193 col_lens[3] = MATRIX_BINARY_FORMAT_DENSE; 1194 1195 ierr = PetscBinaryWrite(fd,col_lens,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1196 ierr = PetscFree(col_lens);CHKERRQ(ierr); 1197 1198 /* write out matrix, by rows */ 1199 ierr = PetscMalloc1(m*n+1,&vals);CHKERRQ(ierr); 1200 v = a->v; 1201 for (j=0; j<n; j++) { 1202 for (i=0; i<m; i++) { 1203 vals[j + i*n] = *v++; 1204 } 1205 } 1206 ierr = PetscBinaryWrite(fd,vals,n*m,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 1207 ierr = PetscFree(vals);CHKERRQ(ierr); 1208 } else { 1209 ierr = PetscMalloc1(4+nz,&col_lens);CHKERRQ(ierr); 1210 1211 col_lens[0] = MAT_FILE_CLASSID; 1212 col_lens[1] = m; 1213 col_lens[2] = n; 1214 col_lens[3] = nz; 1215 1216 /* store lengths of each row and write (including header) to file */ 1217 for (i=0; i<m; i++) col_lens[4+i] = n; 1218 ierr = PetscBinaryWrite(fd,col_lens,4+m,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1219 1220 /* Possibly should write in smaller increments, not whole matrix at once? */ 1221 /* store column indices (zero start index) */ 1222 ict = 0; 1223 for (i=0; i<m; i++) { 1224 for (j=0; j<n; j++) col_lens[ict++] = j; 1225 } 1226 ierr = PetscBinaryWrite(fd,col_lens,nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 1227 ierr = PetscFree(col_lens);CHKERRQ(ierr); 1228 1229 /* store nonzero values */ 1230 ierr = PetscMalloc1(nz+1,&anonz);CHKERRQ(ierr); 1231 ict = 0; 1232 for (i=0; i<m; i++) { 1233 v = a->v + i; 1234 for (j=0; j<n; j++) { 1235 anonz[ict++] = *v; v += a->lda; 1236 } 1237 } 1238 ierr = PetscBinaryWrite(fd,anonz,nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 1239 ierr = PetscFree(anonz);CHKERRQ(ierr); 1240 } 1241 PetscFunctionReturn(0); 1242 } 1243 1244 #include <petscdraw.h> 1245 static PetscErrorCode MatView_SeqDense_Draw_Zoom(PetscDraw draw,void *Aa) 1246 { 1247 Mat A = (Mat) Aa; 1248 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1249 PetscErrorCode ierr; 1250 PetscInt m = A->rmap->n,n = A->cmap->n,i,j; 1251 int color = PETSC_DRAW_WHITE; 1252 PetscScalar *v = a->v; 1253 PetscViewer viewer; 1254 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 1255 PetscViewerFormat format; 1256 1257 PetscFunctionBegin; 1258 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 1259 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1260 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 1261 1262 /* Loop over matrix elements drawing boxes */ 1263 1264 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 1265 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 1266 /* Blue for negative and Red for positive */ 1267 for (j = 0; j < n; j++) { 1268 x_l = j; x_r = x_l + 1.0; 1269 for (i = 0; i < m; i++) { 1270 y_l = m - i - 1.0; 1271 y_r = y_l + 1.0; 1272 if (PetscRealPart(v[j*m+i]) > 0.) { 1273 color = PETSC_DRAW_RED; 1274 } else if (PetscRealPart(v[j*m+i]) < 0.) { 1275 color = PETSC_DRAW_BLUE; 1276 } else { 1277 continue; 1278 } 1279 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1280 } 1281 } 1282 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 1283 } else { 1284 /* use contour shading to indicate magnitude of values */ 1285 /* first determine max of all nonzero values */ 1286 PetscReal minv = 0.0, maxv = 0.0; 1287 PetscDraw popup; 1288 1289 for (i=0; i < m*n; i++) { 1290 if (PetscAbsScalar(v[i]) > maxv) maxv = PetscAbsScalar(v[i]); 1291 } 1292 if (minv >= maxv) maxv = minv + PETSC_SMALL; 1293 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 1294 ierr = PetscDrawScalePopup(popup,minv,maxv);CHKERRQ(ierr); 1295 1296 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 1297 for (j=0; j<n; j++) { 1298 x_l = j; 1299 x_r = x_l + 1.0; 1300 for (i=0; i<m; i++) { 1301 y_l = m - i - 1.0; 1302 y_r = y_l + 1.0; 1303 color = PetscDrawRealToColor(PetscAbsScalar(v[j*m+i]),minv,maxv); 1304 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1305 } 1306 } 1307 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 1308 } 1309 PetscFunctionReturn(0); 1310 } 1311 1312 static PetscErrorCode MatView_SeqDense_Draw(Mat A,PetscViewer viewer) 1313 { 1314 PetscDraw draw; 1315 PetscBool isnull; 1316 PetscReal xr,yr,xl,yl,h,w; 1317 PetscErrorCode ierr; 1318 1319 PetscFunctionBegin; 1320 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1321 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1322 if (isnull) PetscFunctionReturn(0); 1323 1324 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 1325 xr += w; yr += h; xl = -w; yl = -h; 1326 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 1327 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 1328 ierr = PetscDrawZoom(draw,MatView_SeqDense_Draw_Zoom,A);CHKERRQ(ierr); 1329 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 1330 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 1331 PetscFunctionReturn(0); 1332 } 1333 1334 PetscErrorCode MatView_SeqDense(Mat A,PetscViewer viewer) 1335 { 1336 PetscErrorCode ierr; 1337 PetscBool iascii,isbinary,isdraw; 1338 1339 PetscFunctionBegin; 1340 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1341 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1342 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1343 1344 if (iascii) { 1345 ierr = MatView_SeqDense_ASCII(A,viewer);CHKERRQ(ierr); 1346 } else if (isbinary) { 1347 ierr = MatView_SeqDense_Binary(A,viewer);CHKERRQ(ierr); 1348 } else if (isdraw) { 1349 ierr = MatView_SeqDense_Draw(A,viewer);CHKERRQ(ierr); 1350 } 1351 PetscFunctionReturn(0); 1352 } 1353 1354 static PetscErrorCode MatDestroy_SeqDense(Mat mat) 1355 { 1356 Mat_SeqDense *l = (Mat_SeqDense*)mat->data; 1357 PetscErrorCode ierr; 1358 1359 PetscFunctionBegin; 1360 #if defined(PETSC_USE_LOG) 1361 PetscLogObjectState((PetscObject)mat,"Rows %D Cols %D",mat->rmap->n,mat->cmap->n); 1362 #endif 1363 ierr = PetscFree(l->pivots);CHKERRQ(ierr); 1364 ierr = PetscFree(l->fwork);CHKERRQ(ierr); 1365 ierr = MatDestroy(&l->ptapwork);CHKERRQ(ierr); 1366 if (!l->user_alloc) {ierr = PetscFree(l->v);CHKERRQ(ierr);} 1367 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1368 1369 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1370 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",NULL);CHKERRQ(ierr); 1371 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",NULL);CHKERRQ(ierr); 1372 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_seqdense_seqaij_C",NULL);CHKERRQ(ierr); 1373 #if defined(PETSC_HAVE_ELEMENTAL) 1374 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_seqdense_elemental_C",NULL);CHKERRQ(ierr); 1375 #endif 1376 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSeqDenseSetPreallocation_C",NULL);CHKERRQ(ierr); 1377 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1378 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1379 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1380 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatPtAP_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1381 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1382 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1383 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1384 PetscFunctionReturn(0); 1385 } 1386 1387 static PetscErrorCode MatTranspose_SeqDense(Mat A,MatReuse reuse,Mat *matout) 1388 { 1389 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1390 PetscErrorCode ierr; 1391 PetscInt k,j,m,n,M; 1392 PetscScalar *v,tmp; 1393 1394 PetscFunctionBegin; 1395 v = mat->v; m = A->rmap->n; M = mat->lda; n = A->cmap->n; 1396 if (reuse == MAT_INPLACE_MATRIX) { /* in place transpose */ 1397 if (m != n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can not transpose non-square matrix in place"); 1398 else { 1399 for (j=0; j<m; j++) { 1400 for (k=0; k<j; k++) { 1401 tmp = v[j + k*M]; 1402 v[j + k*M] = v[k + j*M]; 1403 v[k + j*M] = tmp; 1404 } 1405 } 1406 } 1407 } else { /* out-of-place transpose */ 1408 Mat tmat; 1409 Mat_SeqDense *tmatd; 1410 PetscScalar *v2; 1411 PetscInt M2; 1412 1413 if (reuse == MAT_INITIAL_MATRIX) { 1414 ierr = MatCreate(PetscObjectComm((PetscObject)A),&tmat);CHKERRQ(ierr); 1415 ierr = MatSetSizes(tmat,A->cmap->n,A->rmap->n,A->cmap->n,A->rmap->n);CHKERRQ(ierr); 1416 ierr = MatSetType(tmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1417 ierr = MatSeqDenseSetPreallocation(tmat,NULL);CHKERRQ(ierr); 1418 } else { 1419 tmat = *matout; 1420 } 1421 tmatd = (Mat_SeqDense*)tmat->data; 1422 v = mat->v; v2 = tmatd->v; M2 = tmatd->lda; 1423 for (j=0; j<n; j++) { 1424 for (k=0; k<m; k++) v2[j + k*M2] = v[k + j*M]; 1425 } 1426 ierr = MatAssemblyBegin(tmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1427 ierr = MatAssemblyEnd(tmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1428 *matout = tmat; 1429 } 1430 PetscFunctionReturn(0); 1431 } 1432 1433 static PetscErrorCode MatEqual_SeqDense(Mat A1,Mat A2,PetscBool *flg) 1434 { 1435 Mat_SeqDense *mat1 = (Mat_SeqDense*)A1->data; 1436 Mat_SeqDense *mat2 = (Mat_SeqDense*)A2->data; 1437 PetscInt i,j; 1438 PetscScalar *v1,*v2; 1439 1440 PetscFunctionBegin; 1441 if (A1->rmap->n != A2->rmap->n) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1442 if (A1->cmap->n != A2->cmap->n) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1443 for (i=0; i<A1->rmap->n; i++) { 1444 v1 = mat1->v+i; v2 = mat2->v+i; 1445 for (j=0; j<A1->cmap->n; j++) { 1446 if (*v1 != *v2) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1447 v1 += mat1->lda; v2 += mat2->lda; 1448 } 1449 } 1450 *flg = PETSC_TRUE; 1451 PetscFunctionReturn(0); 1452 } 1453 1454 static PetscErrorCode MatGetDiagonal_SeqDense(Mat A,Vec v) 1455 { 1456 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1457 PetscErrorCode ierr; 1458 PetscInt i,n,len; 1459 PetscScalar *x,zero = 0.0; 1460 1461 PetscFunctionBegin; 1462 ierr = VecSet(v,zero);CHKERRQ(ierr); 1463 ierr = VecGetSize(v,&n);CHKERRQ(ierr); 1464 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1465 len = PetscMin(A->rmap->n,A->cmap->n); 1466 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec"); 1467 for (i=0; i<len; i++) { 1468 x[i] = mat->v[i*mat->lda + i]; 1469 } 1470 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1471 PetscFunctionReturn(0); 1472 } 1473 1474 static PetscErrorCode MatDiagonalScale_SeqDense(Mat A,Vec ll,Vec rr) 1475 { 1476 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1477 const PetscScalar *l,*r; 1478 PetscScalar x,*v; 1479 PetscErrorCode ierr; 1480 PetscInt i,j,m = A->rmap->n,n = A->cmap->n; 1481 1482 PetscFunctionBegin; 1483 if (ll) { 1484 ierr = VecGetSize(ll,&m);CHKERRQ(ierr); 1485 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 1486 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vec wrong size"); 1487 for (i=0; i<m; i++) { 1488 x = l[i]; 1489 v = mat->v + i; 1490 for (j=0; j<n; j++) { (*v) *= x; v+= mat->lda;} 1491 } 1492 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 1493 ierr = PetscLogFlops(1.0*n*m);CHKERRQ(ierr); 1494 } 1495 if (rr) { 1496 ierr = VecGetSize(rr,&n);CHKERRQ(ierr); 1497 ierr = VecGetArrayRead(rr,&r);CHKERRQ(ierr); 1498 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vec wrong size"); 1499 for (i=0; i<n; i++) { 1500 x = r[i]; 1501 v = mat->v + i*mat->lda; 1502 for (j=0; j<m; j++) (*v++) *= x; 1503 } 1504 ierr = VecRestoreArrayRead(rr,&r);CHKERRQ(ierr); 1505 ierr = PetscLogFlops(1.0*n*m);CHKERRQ(ierr); 1506 } 1507 PetscFunctionReturn(0); 1508 } 1509 1510 static PetscErrorCode MatNorm_SeqDense(Mat A,NormType type,PetscReal *nrm) 1511 { 1512 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1513 PetscScalar *v = mat->v; 1514 PetscReal sum = 0.0; 1515 PetscInt lda =mat->lda,m=A->rmap->n,i,j; 1516 PetscErrorCode ierr; 1517 1518 PetscFunctionBegin; 1519 if (type == NORM_FROBENIUS) { 1520 if (lda>m) { 1521 for (j=0; j<A->cmap->n; j++) { 1522 v = mat->v+j*lda; 1523 for (i=0; i<m; i++) { 1524 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1525 } 1526 } 1527 } else { 1528 #if defined(PETSC_USE_REAL___FP16) 1529 PetscBLASInt one = 1,cnt = A->cmap->n*A->rmap->n; 1530 *nrm = BLASnrm2_(&cnt,v,&one); 1531 } 1532 #else 1533 for (i=0; i<A->cmap->n*A->rmap->n; i++) { 1534 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1535 } 1536 } 1537 *nrm = PetscSqrtReal(sum); 1538 #endif 1539 ierr = PetscLogFlops(2.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1540 } else if (type == NORM_1) { 1541 *nrm = 0.0; 1542 for (j=0; j<A->cmap->n; j++) { 1543 v = mat->v + j*mat->lda; 1544 sum = 0.0; 1545 for (i=0; i<A->rmap->n; i++) { 1546 sum += PetscAbsScalar(*v); v++; 1547 } 1548 if (sum > *nrm) *nrm = sum; 1549 } 1550 ierr = PetscLogFlops(1.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1551 } else if (type == NORM_INFINITY) { 1552 *nrm = 0.0; 1553 for (j=0; j<A->rmap->n; j++) { 1554 v = mat->v + j; 1555 sum = 0.0; 1556 for (i=0; i<A->cmap->n; i++) { 1557 sum += PetscAbsScalar(*v); v += mat->lda; 1558 } 1559 if (sum > *nrm) *nrm = sum; 1560 } 1561 ierr = PetscLogFlops(1.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1562 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No two norm"); 1563 PetscFunctionReturn(0); 1564 } 1565 1566 static PetscErrorCode MatSetOption_SeqDense(Mat A,MatOption op,PetscBool flg) 1567 { 1568 Mat_SeqDense *aij = (Mat_SeqDense*)A->data; 1569 PetscErrorCode ierr; 1570 1571 PetscFunctionBegin; 1572 switch (op) { 1573 case MAT_ROW_ORIENTED: 1574 aij->roworiented = flg; 1575 break; 1576 case MAT_NEW_NONZERO_LOCATIONS: 1577 case MAT_NEW_NONZERO_LOCATION_ERR: 1578 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1579 case MAT_NEW_DIAGONALS: 1580 case MAT_KEEP_NONZERO_PATTERN: 1581 case MAT_IGNORE_OFF_PROC_ENTRIES: 1582 case MAT_USE_HASH_TABLE: 1583 case MAT_IGNORE_LOWER_TRIANGULAR: 1584 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1585 break; 1586 case MAT_SPD: 1587 case MAT_SYMMETRIC: 1588 case MAT_STRUCTURALLY_SYMMETRIC: 1589 case MAT_HERMITIAN: 1590 case MAT_SYMMETRY_ETERNAL: 1591 /* These options are handled directly by MatSetOption() */ 1592 break; 1593 default: 1594 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %s",MatOptions[op]); 1595 } 1596 PetscFunctionReturn(0); 1597 } 1598 1599 static PetscErrorCode MatZeroEntries_SeqDense(Mat A) 1600 { 1601 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 1602 PetscErrorCode ierr; 1603 PetscInt lda=l->lda,m=A->rmap->n,j; 1604 1605 PetscFunctionBegin; 1606 if (lda>m) { 1607 for (j=0; j<A->cmap->n; j++) { 1608 ierr = PetscMemzero(l->v+j*lda,m*sizeof(PetscScalar));CHKERRQ(ierr); 1609 } 1610 } else { 1611 ierr = PetscMemzero(l->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 1612 } 1613 PetscFunctionReturn(0); 1614 } 1615 1616 static PetscErrorCode MatZeroRows_SeqDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1617 { 1618 PetscErrorCode ierr; 1619 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 1620 PetscInt m = l->lda, n = A->cmap->n, i,j; 1621 PetscScalar *slot,*bb; 1622 const PetscScalar *xx; 1623 1624 PetscFunctionBegin; 1625 #if defined(PETSC_USE_DEBUG) 1626 for (i=0; i<N; i++) { 1627 if (rows[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row requested to be zeroed"); 1628 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); 1629 } 1630 #endif 1631 1632 /* fix right hand side if needed */ 1633 if (x && b) { 1634 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1635 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1636 for (i=0; i<N; i++) bb[rows[i]] = diag*xx[rows[i]]; 1637 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1638 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1639 } 1640 1641 for (i=0; i<N; i++) { 1642 slot = l->v + rows[i]; 1643 for (j=0; j<n; j++) { *slot = 0.0; slot += m;} 1644 } 1645 if (diag != 0.0) { 1646 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only coded for square matrices"); 1647 for (i=0; i<N; i++) { 1648 slot = l->v + (m+1)*rows[i]; 1649 *slot = diag; 1650 } 1651 } 1652 PetscFunctionReturn(0); 1653 } 1654 1655 static PetscErrorCode MatDenseGetArray_SeqDense(Mat A,PetscScalar *array[]) 1656 { 1657 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1658 1659 PetscFunctionBegin; 1660 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"); 1661 *array = mat->v; 1662 PetscFunctionReturn(0); 1663 } 1664 1665 static PetscErrorCode MatDenseRestoreArray_SeqDense(Mat A,PetscScalar *array[]) 1666 { 1667 PetscFunctionBegin; 1668 *array = 0; /* user cannot accidently use the array later */ 1669 PetscFunctionReturn(0); 1670 } 1671 1672 /*@C 1673 MatDenseGetArray - gives access to the array where the data for a SeqDense matrix is stored 1674 1675 Not Collective 1676 1677 Input Parameter: 1678 . mat - a MATSEQDENSE or MATMPIDENSE matrix 1679 1680 Output Parameter: 1681 . array - pointer to the data 1682 1683 Level: intermediate 1684 1685 .seealso: MatDenseRestoreArray() 1686 @*/ 1687 PetscErrorCode MatDenseGetArray(Mat A,PetscScalar **array) 1688 { 1689 PetscErrorCode ierr; 1690 1691 PetscFunctionBegin; 1692 ierr = PetscUseMethod(A,"MatDenseGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 1693 PetscFunctionReturn(0); 1694 } 1695 1696 /*@C 1697 MatDenseRestoreArray - returns access to the array where the data for a dense matrix is stored obtained by MatDenseGetArray() 1698 1699 Not Collective 1700 1701 Input Parameters: 1702 . mat - a MATSEQDENSE or MATMPIDENSE matrix 1703 . array - pointer to the data 1704 1705 Level: intermediate 1706 1707 .seealso: MatDenseGetArray() 1708 @*/ 1709 PetscErrorCode MatDenseRestoreArray(Mat A,PetscScalar **array) 1710 { 1711 PetscErrorCode ierr; 1712 1713 PetscFunctionBegin; 1714 ierr = PetscUseMethod(A,"MatDenseRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 1715 PetscFunctionReturn(0); 1716 } 1717 1718 static PetscErrorCode MatCreateSubMatrix_SeqDense(Mat A,IS isrow,IS iscol,PetscInt cs,MatReuse scall,Mat *B) 1719 { 1720 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1721 PetscErrorCode ierr; 1722 PetscInt i,j,nrows,ncols; 1723 const PetscInt *irow,*icol; 1724 PetscScalar *av,*bv,*v = mat->v; 1725 Mat newmat; 1726 1727 PetscFunctionBegin; 1728 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 1729 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 1730 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 1731 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 1732 1733 /* Check submatrixcall */ 1734 if (scall == MAT_REUSE_MATRIX) { 1735 PetscInt n_cols,n_rows; 1736 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 1737 if (n_rows != nrows || n_cols != ncols) { 1738 /* resize the result matrix to match number of requested rows/columns */ 1739 ierr = MatSetSizes(*B,nrows,ncols,nrows,ncols);CHKERRQ(ierr); 1740 } 1741 newmat = *B; 1742 } else { 1743 /* Create and fill new matrix */ 1744 ierr = MatCreate(PetscObjectComm((PetscObject)A),&newmat);CHKERRQ(ierr); 1745 ierr = MatSetSizes(newmat,nrows,ncols,nrows,ncols);CHKERRQ(ierr); 1746 ierr = MatSetType(newmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1747 ierr = MatSeqDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1748 } 1749 1750 /* Now extract the data pointers and do the copy,column at a time */ 1751 bv = ((Mat_SeqDense*)newmat->data)->v; 1752 1753 for (i=0; i<ncols; i++) { 1754 av = v + mat->lda*icol[i]; 1755 for (j=0; j<nrows; j++) *bv++ = av[irow[j]]; 1756 } 1757 1758 /* Assemble the matrices so that the correct flags are set */ 1759 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1760 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1761 1762 /* Free work space */ 1763 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 1764 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 1765 *B = newmat; 1766 PetscFunctionReturn(0); 1767 } 1768 1769 static PetscErrorCode MatCreateSubMatrices_SeqDense(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1770 { 1771 PetscErrorCode ierr; 1772 PetscInt i; 1773 1774 PetscFunctionBegin; 1775 if (scall == MAT_INITIAL_MATRIX) { 1776 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 1777 } 1778 1779 for (i=0; i<n; i++) { 1780 ierr = MatCreateSubMatrix_SeqDense(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 1781 } 1782 PetscFunctionReturn(0); 1783 } 1784 1785 static PetscErrorCode MatAssemblyBegin_SeqDense(Mat mat,MatAssemblyType mode) 1786 { 1787 PetscFunctionBegin; 1788 PetscFunctionReturn(0); 1789 } 1790 1791 static PetscErrorCode MatAssemblyEnd_SeqDense(Mat mat,MatAssemblyType mode) 1792 { 1793 PetscFunctionBegin; 1794 PetscFunctionReturn(0); 1795 } 1796 1797 static PetscErrorCode MatCopy_SeqDense(Mat A,Mat B,MatStructure str) 1798 { 1799 Mat_SeqDense *a = (Mat_SeqDense*)A->data,*b = (Mat_SeqDense*)B->data; 1800 PetscErrorCode ierr; 1801 PetscInt lda1=a->lda,lda2=b->lda, m=A->rmap->n,n=A->cmap->n, j; 1802 1803 PetscFunctionBegin; 1804 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1805 if (A->ops->copy != B->ops->copy) { 1806 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1807 PetscFunctionReturn(0); 1808 } 1809 if (m != B->rmap->n || n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"size(B) != size(A)"); 1810 if (lda1>m || lda2>m) { 1811 for (j=0; j<n; j++) { 1812 ierr = PetscMemcpy(b->v+j*lda2,a->v+j*lda1,m*sizeof(PetscScalar));CHKERRQ(ierr); 1813 } 1814 } else { 1815 ierr = PetscMemcpy(b->v,a->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 1816 } 1817 PetscFunctionReturn(0); 1818 } 1819 1820 static PetscErrorCode MatSetUp_SeqDense(Mat A) 1821 { 1822 PetscErrorCode ierr; 1823 1824 PetscFunctionBegin; 1825 ierr = MatSeqDenseSetPreallocation(A,0);CHKERRQ(ierr); 1826 PetscFunctionReturn(0); 1827 } 1828 1829 static PetscErrorCode MatConjugate_SeqDense(Mat A) 1830 { 1831 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1832 PetscInt i,nz = A->rmap->n*A->cmap->n; 1833 PetscScalar *aa = a->v; 1834 1835 PetscFunctionBegin; 1836 for (i=0; i<nz; i++) aa[i] = PetscConj(aa[i]); 1837 PetscFunctionReturn(0); 1838 } 1839 1840 static PetscErrorCode MatRealPart_SeqDense(Mat A) 1841 { 1842 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1843 PetscInt i,nz = A->rmap->n*A->cmap->n; 1844 PetscScalar *aa = a->v; 1845 1846 PetscFunctionBegin; 1847 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1848 PetscFunctionReturn(0); 1849 } 1850 1851 static PetscErrorCode MatImaginaryPart_SeqDense(Mat A) 1852 { 1853 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1854 PetscInt i,nz = A->rmap->n*A->cmap->n; 1855 PetscScalar *aa = a->v; 1856 1857 PetscFunctionBegin; 1858 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1859 PetscFunctionReturn(0); 1860 } 1861 1862 /* ----------------------------------------------------------------*/ 1863 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1864 { 1865 PetscErrorCode ierr; 1866 1867 PetscFunctionBegin; 1868 if (scall == MAT_INITIAL_MATRIX) { 1869 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1870 ierr = MatMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 1871 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1872 } 1873 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 1874 ierr = MatMatMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 1875 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 1876 PetscFunctionReturn(0); 1877 } 1878 1879 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 1880 { 1881 PetscErrorCode ierr; 1882 PetscInt m=A->rmap->n,n=B->cmap->n; 1883 Mat Cmat; 1884 1885 PetscFunctionBegin; 1886 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); 1887 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 1888 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 1889 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 1890 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 1891 1892 *C = Cmat; 1893 PetscFunctionReturn(0); 1894 } 1895 1896 PetscErrorCode MatMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 1897 { 1898 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1899 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 1900 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 1901 PetscBLASInt m,n,k; 1902 PetscScalar _DOne=1.0,_DZero=0.0; 1903 PetscErrorCode ierr; 1904 PetscBool flg; 1905 1906 PetscFunctionBegin; 1907 ierr = PetscObjectTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr); 1908 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Second matrix must be dense"); 1909 1910 /* Handle case where where user provided the final C matrix rather than calling MatMatMult() with MAT_INITIAL_MATRIX*/ 1911 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&flg);CHKERRQ(ierr); 1912 if (flg) { 1913 C->ops->matmultnumeric = MatMatMultNumeric_SeqAIJ_SeqDense; 1914 ierr = (*C->ops->matmultnumeric)(A,B,C);CHKERRQ(ierr); 1915 PetscFunctionReturn(0); 1916 } 1917 1918 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQDENSE,&flg);CHKERRQ(ierr); 1919 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"First matrix must be dense"); 1920 ierr = PetscBLASIntCast(C->rmap->n,&m);CHKERRQ(ierr); 1921 ierr = PetscBLASIntCast(C->cmap->n,&n);CHKERRQ(ierr); 1922 ierr = PetscBLASIntCast(A->cmap->n,&k);CHKERRQ(ierr); 1923 PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 1924 PetscFunctionReturn(0); 1925 } 1926 1927 PetscErrorCode MatMatTransposeMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1928 { 1929 PetscErrorCode ierr; 1930 1931 PetscFunctionBegin; 1932 if (scall == MAT_INITIAL_MATRIX) { 1933 ierr = PetscLogEventBegin(MAT_MatTransposeMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1934 ierr = MatMatTransposeMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 1935 ierr = PetscLogEventEnd(MAT_MatTransposeMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1936 } 1937 ierr = PetscLogEventBegin(MAT_MatTransposeMultNumeric,A,B,0,0);CHKERRQ(ierr); 1938 ierr = MatMatTransposeMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 1939 ierr = PetscLogEventEnd(MAT_MatTransposeMultNumeric,A,B,0,0);CHKERRQ(ierr); 1940 PetscFunctionReturn(0); 1941 } 1942 1943 PetscErrorCode MatMatTransposeMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 1944 { 1945 PetscErrorCode ierr; 1946 PetscInt m=A->rmap->n,n=B->rmap->n; 1947 Mat Cmat; 1948 1949 PetscFunctionBegin; 1950 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); 1951 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 1952 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 1953 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 1954 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 1955 1956 Cmat->assembled = PETSC_TRUE; 1957 1958 *C = Cmat; 1959 PetscFunctionReturn(0); 1960 } 1961 1962 PetscErrorCode MatMatTransposeMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 1963 { 1964 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1965 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 1966 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 1967 PetscBLASInt m,n,k; 1968 PetscScalar _DOne=1.0,_DZero=0.0; 1969 PetscErrorCode ierr; 1970 1971 PetscFunctionBegin; 1972 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 1973 ierr = PetscBLASIntCast(B->rmap->n,&n);CHKERRQ(ierr); 1974 ierr = PetscBLASIntCast(A->cmap->n,&k);CHKERRQ(ierr); 1975 PetscStackCallBLAS("BLASgemm",BLASgemm_("N","T",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 1976 PetscFunctionReturn(0); 1977 } 1978 1979 PetscErrorCode MatTransposeMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1980 { 1981 PetscErrorCode ierr; 1982 1983 PetscFunctionBegin; 1984 if (scall == MAT_INITIAL_MATRIX) { 1985 ierr = PetscLogEventBegin(MAT_TransposeMatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1986 ierr = MatTransposeMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 1987 ierr = PetscLogEventEnd(MAT_TransposeMatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1988 } 1989 ierr = PetscLogEventBegin(MAT_TransposeMatMultNumeric,A,B,0,0);CHKERRQ(ierr); 1990 ierr = MatTransposeMatMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 1991 ierr = PetscLogEventEnd(MAT_TransposeMatMultNumeric,A,B,0,0);CHKERRQ(ierr); 1992 PetscFunctionReturn(0); 1993 } 1994 1995 PetscErrorCode MatTransposeMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 1996 { 1997 PetscErrorCode ierr; 1998 PetscInt m=A->cmap->n,n=B->cmap->n; 1999 Mat Cmat; 2000 2001 PetscFunctionBegin; 2002 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); 2003 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 2004 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 2005 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 2006 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 2007 2008 Cmat->assembled = PETSC_TRUE; 2009 2010 *C = Cmat; 2011 PetscFunctionReturn(0); 2012 } 2013 2014 PetscErrorCode MatTransposeMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 2015 { 2016 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2017 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2018 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 2019 PetscBLASInt m,n,k; 2020 PetscScalar _DOne=1.0,_DZero=0.0; 2021 PetscErrorCode ierr; 2022 2023 PetscFunctionBegin; 2024 ierr = PetscBLASIntCast(C->rmap->n,&m);CHKERRQ(ierr); 2025 ierr = PetscBLASIntCast(C->cmap->n,&n);CHKERRQ(ierr); 2026 ierr = PetscBLASIntCast(A->rmap->n,&k);CHKERRQ(ierr); 2027 PetscStackCallBLAS("BLASgemm",BLASgemm_("T","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 2028 PetscFunctionReturn(0); 2029 } 2030 2031 static PetscErrorCode MatGetRowMax_SeqDense(Mat A,Vec v,PetscInt idx[]) 2032 { 2033 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2034 PetscErrorCode ierr; 2035 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2036 PetscScalar *x; 2037 MatScalar *aa = a->v; 2038 2039 PetscFunctionBegin; 2040 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2041 2042 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2043 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2044 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2045 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2046 for (i=0; i<m; i++) { 2047 x[i] = aa[i]; if (idx) idx[i] = 0; 2048 for (j=1; j<n; j++) { 2049 if (PetscRealPart(x[i]) < PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;} 2050 } 2051 } 2052 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2053 PetscFunctionReturn(0); 2054 } 2055 2056 static PetscErrorCode MatGetRowMaxAbs_SeqDense(Mat A,Vec v,PetscInt idx[]) 2057 { 2058 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2059 PetscErrorCode ierr; 2060 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2061 PetscScalar *x; 2062 PetscReal atmp; 2063 MatScalar *aa = a->v; 2064 2065 PetscFunctionBegin; 2066 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2067 2068 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2069 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2070 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2071 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2072 for (i=0; i<m; i++) { 2073 x[i] = PetscAbsScalar(aa[i]); 2074 for (j=1; j<n; j++) { 2075 atmp = PetscAbsScalar(aa[i+m*j]); 2076 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = j;} 2077 } 2078 } 2079 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2080 PetscFunctionReturn(0); 2081 } 2082 2083 static PetscErrorCode MatGetRowMin_SeqDense(Mat A,Vec v,PetscInt idx[]) 2084 { 2085 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2086 PetscErrorCode ierr; 2087 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2088 PetscScalar *x; 2089 MatScalar *aa = a->v; 2090 2091 PetscFunctionBegin; 2092 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2093 2094 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2095 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2096 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2097 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2098 for (i=0; i<m; i++) { 2099 x[i] = aa[i]; if (idx) idx[i] = 0; 2100 for (j=1; j<n; j++) { 2101 if (PetscRealPart(x[i]) > PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;} 2102 } 2103 } 2104 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2105 PetscFunctionReturn(0); 2106 } 2107 2108 static PetscErrorCode MatGetColumnVector_SeqDense(Mat A,Vec v,PetscInt col) 2109 { 2110 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2111 PetscErrorCode ierr; 2112 PetscScalar *x; 2113 2114 PetscFunctionBegin; 2115 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2116 2117 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2118 ierr = PetscMemcpy(x,a->v+col*a->lda,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 2119 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2120 PetscFunctionReturn(0); 2121 } 2122 2123 2124 PetscErrorCode MatGetColumnNorms_SeqDense(Mat A,NormType type,PetscReal *norms) 2125 { 2126 PetscErrorCode ierr; 2127 PetscInt i,j,m,n; 2128 PetscScalar *a; 2129 2130 PetscFunctionBegin; 2131 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 2132 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 2133 ierr = MatDenseGetArray(A,&a);CHKERRQ(ierr); 2134 if (type == NORM_2) { 2135 for (i=0; i<n; i++) { 2136 for (j=0; j<m; j++) { 2137 norms[i] += PetscAbsScalar(a[j]*a[j]); 2138 } 2139 a += m; 2140 } 2141 } else if (type == NORM_1) { 2142 for (i=0; i<n; i++) { 2143 for (j=0; j<m; j++) { 2144 norms[i] += PetscAbsScalar(a[j]); 2145 } 2146 a += m; 2147 } 2148 } else if (type == NORM_INFINITY) { 2149 for (i=0; i<n; i++) { 2150 for (j=0; j<m; j++) { 2151 norms[i] = PetscMax(PetscAbsScalar(a[j]),norms[i]); 2152 } 2153 a += m; 2154 } 2155 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2156 ierr = MatDenseRestoreArray(A,&a);CHKERRQ(ierr); 2157 if (type == NORM_2) { 2158 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 2159 } 2160 PetscFunctionReturn(0); 2161 } 2162 2163 static PetscErrorCode MatSetRandom_SeqDense(Mat x,PetscRandom rctx) 2164 { 2165 PetscErrorCode ierr; 2166 PetscScalar *a; 2167 PetscInt m,n,i; 2168 2169 PetscFunctionBegin; 2170 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 2171 ierr = MatDenseGetArray(x,&a);CHKERRQ(ierr); 2172 for (i=0; i<m*n; i++) { 2173 ierr = PetscRandomGetValue(rctx,a+i);CHKERRQ(ierr); 2174 } 2175 ierr = MatDenseRestoreArray(x,&a);CHKERRQ(ierr); 2176 PetscFunctionReturn(0); 2177 } 2178 2179 static PetscErrorCode MatMissingDiagonal_SeqDense(Mat A,PetscBool *missing,PetscInt *d) 2180 { 2181 PetscFunctionBegin; 2182 *missing = PETSC_FALSE; 2183 PetscFunctionReturn(0); 2184 } 2185 2186 2187 /* -------------------------------------------------------------------*/ 2188 static struct _MatOps MatOps_Values = { MatSetValues_SeqDense, 2189 MatGetRow_SeqDense, 2190 MatRestoreRow_SeqDense, 2191 MatMult_SeqDense, 2192 /* 4*/ MatMultAdd_SeqDense, 2193 MatMultTranspose_SeqDense, 2194 MatMultTransposeAdd_SeqDense, 2195 0, 2196 0, 2197 0, 2198 /* 10*/ 0, 2199 MatLUFactor_SeqDense, 2200 MatCholeskyFactor_SeqDense, 2201 MatSOR_SeqDense, 2202 MatTranspose_SeqDense, 2203 /* 15*/ MatGetInfo_SeqDense, 2204 MatEqual_SeqDense, 2205 MatGetDiagonal_SeqDense, 2206 MatDiagonalScale_SeqDense, 2207 MatNorm_SeqDense, 2208 /* 20*/ MatAssemblyBegin_SeqDense, 2209 MatAssemblyEnd_SeqDense, 2210 MatSetOption_SeqDense, 2211 MatZeroEntries_SeqDense, 2212 /* 24*/ MatZeroRows_SeqDense, 2213 0, 2214 0, 2215 0, 2216 0, 2217 /* 29*/ MatSetUp_SeqDense, 2218 0, 2219 0, 2220 0, 2221 0, 2222 /* 34*/ MatDuplicate_SeqDense, 2223 0, 2224 0, 2225 0, 2226 0, 2227 /* 39*/ MatAXPY_SeqDense, 2228 MatCreateSubMatrices_SeqDense, 2229 0, 2230 MatGetValues_SeqDense, 2231 MatCopy_SeqDense, 2232 /* 44*/ MatGetRowMax_SeqDense, 2233 MatScale_SeqDense, 2234 MatShift_Basic, 2235 0, 2236 MatZeroRowsColumns_SeqDense, 2237 /* 49*/ MatSetRandom_SeqDense, 2238 0, 2239 0, 2240 0, 2241 0, 2242 /* 54*/ 0, 2243 0, 2244 0, 2245 0, 2246 0, 2247 /* 59*/ 0, 2248 MatDestroy_SeqDense, 2249 MatView_SeqDense, 2250 0, 2251 0, 2252 /* 64*/ 0, 2253 0, 2254 0, 2255 0, 2256 0, 2257 /* 69*/ MatGetRowMaxAbs_SeqDense, 2258 0, 2259 0, 2260 0, 2261 0, 2262 /* 74*/ 0, 2263 0, 2264 0, 2265 0, 2266 0, 2267 /* 79*/ 0, 2268 0, 2269 0, 2270 0, 2271 /* 83*/ MatLoad_SeqDense, 2272 0, 2273 MatIsHermitian_SeqDense, 2274 0, 2275 0, 2276 0, 2277 /* 89*/ MatMatMult_SeqDense_SeqDense, 2278 MatMatMultSymbolic_SeqDense_SeqDense, 2279 MatMatMultNumeric_SeqDense_SeqDense, 2280 MatPtAP_SeqDense_SeqDense, 2281 MatPtAPSymbolic_SeqDense_SeqDense, 2282 /* 94*/ MatPtAPNumeric_SeqDense_SeqDense, 2283 MatMatTransposeMult_SeqDense_SeqDense, 2284 MatMatTransposeMultSymbolic_SeqDense_SeqDense, 2285 MatMatTransposeMultNumeric_SeqDense_SeqDense, 2286 0, 2287 /* 99*/ 0, 2288 0, 2289 0, 2290 MatConjugate_SeqDense, 2291 0, 2292 /*104*/ 0, 2293 MatRealPart_SeqDense, 2294 MatImaginaryPart_SeqDense, 2295 0, 2296 0, 2297 /*109*/ 0, 2298 0, 2299 MatGetRowMin_SeqDense, 2300 MatGetColumnVector_SeqDense, 2301 MatMissingDiagonal_SeqDense, 2302 /*114*/ 0, 2303 0, 2304 0, 2305 0, 2306 0, 2307 /*119*/ 0, 2308 0, 2309 0, 2310 0, 2311 0, 2312 /*124*/ 0, 2313 MatGetColumnNorms_SeqDense, 2314 0, 2315 0, 2316 0, 2317 /*129*/ 0, 2318 MatTransposeMatMult_SeqDense_SeqDense, 2319 MatTransposeMatMultSymbolic_SeqDense_SeqDense, 2320 MatTransposeMatMultNumeric_SeqDense_SeqDense, 2321 0, 2322 /*134*/ 0, 2323 0, 2324 0, 2325 0, 2326 0, 2327 /*139*/ 0, 2328 0, 2329 0 2330 }; 2331 2332 /*@C 2333 MatCreateSeqDense - Creates a sequential dense matrix that 2334 is stored in column major order (the usual Fortran 77 manner). Many 2335 of the matrix operations use the BLAS and LAPACK routines. 2336 2337 Collective on MPI_Comm 2338 2339 Input Parameters: 2340 + comm - MPI communicator, set to PETSC_COMM_SELF 2341 . m - number of rows 2342 . n - number of columns 2343 - data - optional location of matrix data in column major order. Set data=NULL for PETSc 2344 to control all matrix memory allocation. 2345 2346 Output Parameter: 2347 . A - the matrix 2348 2349 Notes: 2350 The data input variable is intended primarily for Fortran programmers 2351 who wish to allocate their own matrix memory space. Most users should 2352 set data=NULL. 2353 2354 Level: intermediate 2355 2356 .keywords: dense, matrix, LAPACK, BLAS 2357 2358 .seealso: MatCreate(), MatCreateDense(), MatSetValues() 2359 @*/ 2360 PetscErrorCode MatCreateSeqDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscScalar *data,Mat *A) 2361 { 2362 PetscErrorCode ierr; 2363 2364 PetscFunctionBegin; 2365 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2366 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 2367 ierr = MatSetType(*A,MATSEQDENSE);CHKERRQ(ierr); 2368 ierr = MatSeqDenseSetPreallocation(*A,data);CHKERRQ(ierr); 2369 PetscFunctionReturn(0); 2370 } 2371 2372 /*@C 2373 MatSeqDenseSetPreallocation - Sets the array used for storing the matrix elements 2374 2375 Collective on MPI_Comm 2376 2377 Input Parameters: 2378 + B - the matrix 2379 - data - the array (or NULL) 2380 2381 Notes: 2382 The data input variable is intended primarily for Fortran programmers 2383 who wish to allocate their own matrix memory space. Most users should 2384 need not call this routine. 2385 2386 Level: intermediate 2387 2388 .keywords: dense, matrix, LAPACK, BLAS 2389 2390 .seealso: MatCreate(), MatCreateDense(), MatSetValues(), MatSeqDenseSetLDA() 2391 2392 @*/ 2393 PetscErrorCode MatSeqDenseSetPreallocation(Mat B,PetscScalar data[]) 2394 { 2395 PetscErrorCode ierr; 2396 2397 PetscFunctionBegin; 2398 ierr = PetscTryMethod(B,"MatSeqDenseSetPreallocation_C",(Mat,PetscScalar[]),(B,data));CHKERRQ(ierr); 2399 PetscFunctionReturn(0); 2400 } 2401 2402 PetscErrorCode MatSeqDenseSetPreallocation_SeqDense(Mat B,PetscScalar *data) 2403 { 2404 Mat_SeqDense *b; 2405 PetscErrorCode ierr; 2406 2407 PetscFunctionBegin; 2408 B->preallocated = PETSC_TRUE; 2409 2410 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2411 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2412 2413 b = (Mat_SeqDense*)B->data; 2414 b->Mmax = B->rmap->n; 2415 b->Nmax = B->cmap->n; 2416 if (b->lda <= 0 || b->changelda) b->lda = B->rmap->n; 2417 2418 ierr = PetscIntMultError(b->lda,b->Nmax,NULL);CHKERRQ(ierr); 2419 if (!data) { /* petsc-allocated storage */ 2420 if (!b->user_alloc) { ierr = PetscFree(b->v);CHKERRQ(ierr); } 2421 ierr = PetscCalloc1((size_t)b->lda*b->Nmax,&b->v);CHKERRQ(ierr); 2422 ierr = PetscLogObjectMemory((PetscObject)B,b->lda*b->Nmax*sizeof(PetscScalar));CHKERRQ(ierr); 2423 2424 b->user_alloc = PETSC_FALSE; 2425 } else { /* user-allocated storage */ 2426 if (!b->user_alloc) { ierr = PetscFree(b->v);CHKERRQ(ierr); } 2427 b->v = data; 2428 b->user_alloc = PETSC_TRUE; 2429 } 2430 B->assembled = PETSC_TRUE; 2431 PetscFunctionReturn(0); 2432 } 2433 2434 #if defined(PETSC_HAVE_ELEMENTAL) 2435 PETSC_INTERN PetscErrorCode MatConvert_SeqDense_Elemental(Mat A, MatType newtype,MatReuse reuse,Mat *newmat) 2436 { 2437 Mat mat_elemental; 2438 PetscErrorCode ierr; 2439 PetscScalar *array,*v_colwise; 2440 PetscInt M=A->rmap->N,N=A->cmap->N,i,j,k,*rows,*cols; 2441 2442 PetscFunctionBegin; 2443 ierr = PetscMalloc3(M*N,&v_colwise,M,&rows,N,&cols);CHKERRQ(ierr); 2444 ierr = MatDenseGetArray(A,&array);CHKERRQ(ierr); 2445 /* convert column-wise array into row-wise v_colwise, see MatSetValues_Elemental() */ 2446 k = 0; 2447 for (j=0; j<N; j++) { 2448 cols[j] = j; 2449 for (i=0; i<M; i++) { 2450 v_colwise[j*M+i] = array[k++]; 2451 } 2452 } 2453 for (i=0; i<M; i++) { 2454 rows[i] = i; 2455 } 2456 ierr = MatDenseRestoreArray(A,&array);CHKERRQ(ierr); 2457 2458 ierr = MatCreate(PetscObjectComm((PetscObject)A), &mat_elemental);CHKERRQ(ierr); 2459 ierr = MatSetSizes(mat_elemental,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 2460 ierr = MatSetType(mat_elemental,MATELEMENTAL);CHKERRQ(ierr); 2461 ierr = MatSetUp(mat_elemental);CHKERRQ(ierr); 2462 2463 /* PETSc-Elemental interaface uses axpy for setting off-processor entries, only ADD_VALUES is allowed */ 2464 ierr = MatSetValues(mat_elemental,M,rows,N,cols,v_colwise,ADD_VALUES);CHKERRQ(ierr); 2465 ierr = MatAssemblyBegin(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2466 ierr = MatAssemblyEnd(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2467 ierr = PetscFree3(v_colwise,rows,cols);CHKERRQ(ierr); 2468 2469 if (reuse == MAT_INPLACE_MATRIX) { 2470 ierr = MatHeaderReplace(A,&mat_elemental);CHKERRQ(ierr); 2471 } else { 2472 *newmat = mat_elemental; 2473 } 2474 PetscFunctionReturn(0); 2475 } 2476 #endif 2477 2478 /*@C 2479 MatSeqDenseSetLDA - Declare the leading dimension of the user-provided array 2480 2481 Input parameter: 2482 + A - the matrix 2483 - lda - the leading dimension 2484 2485 Notes: 2486 This routine is to be used in conjunction with MatSeqDenseSetPreallocation(); 2487 it asserts that the preallocation has a leading dimension (the LDA parameter 2488 of Blas and Lapack fame) larger than M, the first dimension of the matrix. 2489 2490 Level: intermediate 2491 2492 .keywords: dense, matrix, LAPACK, BLAS 2493 2494 .seealso: MatCreate(), MatCreateSeqDense(), MatSeqDenseSetPreallocation(), MatSetMaximumSize() 2495 2496 @*/ 2497 PetscErrorCode MatSeqDenseSetLDA(Mat B,PetscInt lda) 2498 { 2499 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2500 2501 PetscFunctionBegin; 2502 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); 2503 b->lda = lda; 2504 b->changelda = PETSC_FALSE; 2505 b->Mmax = PetscMax(b->Mmax,lda); 2506 PetscFunctionReturn(0); 2507 } 2508 2509 /*MC 2510 MATSEQDENSE - MATSEQDENSE = "seqdense" - A matrix type to be used for sequential dense matrices. 2511 2512 Options Database Keys: 2513 . -mat_type seqdense - sets the matrix type to "seqdense" during a call to MatSetFromOptions() 2514 2515 Level: beginner 2516 2517 .seealso: MatCreateSeqDense() 2518 2519 M*/ 2520 2521 PETSC_EXTERN PetscErrorCode MatCreate_SeqDense(Mat B) 2522 { 2523 Mat_SeqDense *b; 2524 PetscErrorCode ierr; 2525 PetscMPIInt size; 2526 2527 PetscFunctionBegin; 2528 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 2529 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1"); 2530 2531 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 2532 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2533 B->data = (void*)b; 2534 2535 b->roworiented = PETSC_TRUE; 2536 2537 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseGetArray_C",MatDenseGetArray_SeqDense);CHKERRQ(ierr); 2538 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseRestoreArray_C",MatDenseRestoreArray_SeqDense);CHKERRQ(ierr); 2539 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqdense_seqaij_C",MatConvert_SeqDense_SeqAIJ);CHKERRQ(ierr); 2540 #if defined(PETSC_HAVE_ELEMENTAL) 2541 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqdense_elemental_C",MatConvert_SeqDense_Elemental);CHKERRQ(ierr); 2542 #endif 2543 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqDenseSetPreallocation_C",MatSeqDenseSetPreallocation_SeqDense);CHKERRQ(ierr); 2544 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaij_seqdense_C",MatMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2545 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaij_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2546 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaij_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2547 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaij_seqdense_C",MatPtAP_SeqDense_SeqDense);CHKERRQ(ierr); 2548 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaij_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2549 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaij_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2550 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaij_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2551 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQDENSE);CHKERRQ(ierr); 2552 PetscFunctionReturn(0); 2553 } 2554