1 2 /* 3 Defines the basic matrix operations for the AIJ (compressed row) 4 matrix storage format. 5 */ 6 7 8 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 9 #include <petscblaslapack.h> 10 #include <petscbt.h> 11 #include <petsc/private/kernels/blocktranspose.h> 12 13 PetscErrorCode MatSeqAIJSetTypeFromOptions(Mat A) 14 { 15 PetscErrorCode ierr; 16 PetscBool flg; 17 char type[256]; 18 19 PetscFunctionBegin; 20 ierr = PetscObjectOptionsBegin((PetscObject)A); 21 ierr = PetscOptionsFList("-mat_seqaij_type","Matrix SeqAIJ type","MatSeqAIJSetType",MatSeqAIJList,"seqaij",type,256,&flg);CHKERRQ(ierr); 22 if (flg) { 23 ierr = MatSeqAIJSetType(A,type);CHKERRQ(ierr); 24 } 25 ierr = PetscOptionsEnd();CHKERRQ(ierr); 26 PetscFunctionReturn(0); 27 } 28 29 PetscErrorCode MatGetColumnNorms_SeqAIJ(Mat A,NormType type,PetscReal *norms) 30 { 31 PetscErrorCode ierr; 32 PetscInt i,m,n; 33 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 34 35 PetscFunctionBegin; 36 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 37 ierr = PetscArrayzero(norms,n);CHKERRQ(ierr); 38 if (type == NORM_2) { 39 for (i=0; i<aij->i[m]; i++) { 40 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]*aij->a[i]); 41 } 42 } else if (type == NORM_1) { 43 for (i=0; i<aij->i[m]; i++) { 44 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]); 45 } 46 } else if (type == NORM_INFINITY) { 47 for (i=0; i<aij->i[m]; i++) { 48 norms[aij->j[i]] = PetscMax(PetscAbsScalar(aij->a[i]),norms[aij->j[i]]); 49 } 50 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown NormType"); 51 52 if (type == NORM_2) { 53 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 54 } 55 PetscFunctionReturn(0); 56 } 57 58 PetscErrorCode MatFindOffBlockDiagonalEntries_SeqAIJ(Mat A,IS *is) 59 { 60 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 61 PetscInt i,m=A->rmap->n,cnt = 0, bs = A->rmap->bs; 62 const PetscInt *jj = a->j,*ii = a->i; 63 PetscInt *rows; 64 PetscErrorCode ierr; 65 66 PetscFunctionBegin; 67 for (i=0; i<m; i++) { 68 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 69 cnt++; 70 } 71 } 72 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 73 cnt = 0; 74 for (i=0; i<m; i++) { 75 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 76 rows[cnt] = i; 77 cnt++; 78 } 79 } 80 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 81 PetscFunctionReturn(0); 82 } 83 84 PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat A,PetscInt *nrows,PetscInt **zrows) 85 { 86 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 87 const MatScalar *aa = a->a; 88 PetscInt i,m=A->rmap->n,cnt = 0; 89 const PetscInt *ii = a->i,*jj = a->j,*diag; 90 PetscInt *rows; 91 PetscErrorCode ierr; 92 93 PetscFunctionBegin; 94 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 95 diag = a->diag; 96 for (i=0; i<m; i++) { 97 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 98 cnt++; 99 } 100 } 101 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 102 cnt = 0; 103 for (i=0; i<m; i++) { 104 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 105 rows[cnt++] = i; 106 } 107 } 108 *nrows = cnt; 109 *zrows = rows; 110 PetscFunctionReturn(0); 111 } 112 113 PetscErrorCode MatFindZeroDiagonals_SeqAIJ(Mat A,IS *zrows) 114 { 115 PetscInt nrows,*rows; 116 PetscErrorCode ierr; 117 118 PetscFunctionBegin; 119 *zrows = NULL; 120 ierr = MatFindZeroDiagonals_SeqAIJ_Private(A,&nrows,&rows);CHKERRQ(ierr); 121 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 122 PetscFunctionReturn(0); 123 } 124 125 PetscErrorCode MatFindNonzeroRows_SeqAIJ(Mat A,IS *keptrows) 126 { 127 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 128 const MatScalar *aa; 129 PetscInt m=A->rmap->n,cnt = 0; 130 const PetscInt *ii; 131 PetscInt n,i,j,*rows; 132 PetscErrorCode ierr; 133 134 PetscFunctionBegin; 135 *keptrows = 0; 136 ii = a->i; 137 for (i=0; i<m; i++) { 138 n = ii[i+1] - ii[i]; 139 if (!n) { 140 cnt++; 141 goto ok1; 142 } 143 aa = a->a + ii[i]; 144 for (j=0; j<n; j++) { 145 if (aa[j] != 0.0) goto ok1; 146 } 147 cnt++; 148 ok1:; 149 } 150 if (!cnt) PetscFunctionReturn(0); 151 ierr = PetscMalloc1(A->rmap->n-cnt,&rows);CHKERRQ(ierr); 152 cnt = 0; 153 for (i=0; i<m; i++) { 154 n = ii[i+1] - ii[i]; 155 if (!n) continue; 156 aa = a->a + ii[i]; 157 for (j=0; j<n; j++) { 158 if (aa[j] != 0.0) { 159 rows[cnt++] = i; 160 break; 161 } 162 } 163 } 164 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 165 PetscFunctionReturn(0); 166 } 167 168 PetscErrorCode MatDiagonalSet_SeqAIJ(Mat Y,Vec D,InsertMode is) 169 { 170 PetscErrorCode ierr; 171 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) Y->data; 172 PetscInt i,m = Y->rmap->n; 173 const PetscInt *diag; 174 MatScalar *aa = aij->a; 175 const PetscScalar *v; 176 PetscBool missing; 177 178 PetscFunctionBegin; 179 if (Y->assembled) { 180 ierr = MatMissingDiagonal_SeqAIJ(Y,&missing,NULL);CHKERRQ(ierr); 181 if (!missing) { 182 diag = aij->diag; 183 ierr = VecGetArrayRead(D,&v);CHKERRQ(ierr); 184 if (is == INSERT_VALUES) { 185 for (i=0; i<m; i++) { 186 aa[diag[i]] = v[i]; 187 } 188 } else { 189 for (i=0; i<m; i++) { 190 aa[diag[i]] += v[i]; 191 } 192 } 193 ierr = VecRestoreArrayRead(D,&v);CHKERRQ(ierr); 194 PetscFunctionReturn(0); 195 } 196 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 197 } 198 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 199 PetscFunctionReturn(0); 200 } 201 202 PetscErrorCode MatGetRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *m,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 203 { 204 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 205 PetscErrorCode ierr; 206 PetscInt i,ishift; 207 208 PetscFunctionBegin; 209 *m = A->rmap->n; 210 if (!ia) PetscFunctionReturn(0); 211 ishift = 0; 212 if (symmetric && !A->structurally_symmetric) { 213 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,ishift,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 214 } else if (oshift == 1) { 215 PetscInt *tia; 216 PetscInt nz = a->i[A->rmap->n]; 217 /* malloc space and add 1 to i and j indices */ 218 ierr = PetscMalloc1(A->rmap->n+1,&tia);CHKERRQ(ierr); 219 for (i=0; i<A->rmap->n+1; i++) tia[i] = a->i[i] + 1; 220 *ia = tia; 221 if (ja) { 222 PetscInt *tja; 223 ierr = PetscMalloc1(nz+1,&tja);CHKERRQ(ierr); 224 for (i=0; i<nz; i++) tja[i] = a->j[i] + 1; 225 *ja = tja; 226 } 227 } else { 228 *ia = a->i; 229 if (ja) *ja = a->j; 230 } 231 PetscFunctionReturn(0); 232 } 233 234 PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 235 { 236 PetscErrorCode ierr; 237 238 PetscFunctionBegin; 239 if (!ia) PetscFunctionReturn(0); 240 if ((symmetric && !A->structurally_symmetric) || oshift == 1) { 241 ierr = PetscFree(*ia);CHKERRQ(ierr); 242 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 243 } 244 PetscFunctionReturn(0); 245 } 246 247 PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 248 { 249 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 250 PetscErrorCode ierr; 251 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 252 PetscInt nz = a->i[m],row,*jj,mr,col; 253 254 PetscFunctionBegin; 255 *nn = n; 256 if (!ia) PetscFunctionReturn(0); 257 if (symmetric) { 258 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 259 } else { 260 ierr = PetscCalloc1(n,&collengths);CHKERRQ(ierr); 261 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 262 ierr = PetscMalloc1(nz,&cja);CHKERRQ(ierr); 263 jj = a->j; 264 for (i=0; i<nz; i++) { 265 collengths[jj[i]]++; 266 } 267 cia[0] = oshift; 268 for (i=0; i<n; i++) { 269 cia[i+1] = cia[i] + collengths[i]; 270 } 271 ierr = PetscArrayzero(collengths,n);CHKERRQ(ierr); 272 jj = a->j; 273 for (row=0; row<m; row++) { 274 mr = a->i[row+1] - a->i[row]; 275 for (i=0; i<mr; i++) { 276 col = *jj++; 277 278 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 279 } 280 } 281 ierr = PetscFree(collengths);CHKERRQ(ierr); 282 *ia = cia; *ja = cja; 283 } 284 PetscFunctionReturn(0); 285 } 286 287 PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 288 { 289 PetscErrorCode ierr; 290 291 PetscFunctionBegin; 292 if (!ia) PetscFunctionReturn(0); 293 294 ierr = PetscFree(*ia);CHKERRQ(ierr); 295 ierr = PetscFree(*ja);CHKERRQ(ierr); 296 PetscFunctionReturn(0); 297 } 298 299 /* 300 MatGetColumnIJ_SeqAIJ_Color() and MatRestoreColumnIJ_SeqAIJ_Color() are customized from 301 MatGetColumnIJ_SeqAIJ() and MatRestoreColumnIJ_SeqAIJ() by adding an output 302 spidx[], index of a->a, to be used in MatTransposeColoringCreate_SeqAIJ() and MatFDColoringCreate_SeqXAIJ() 303 */ 304 PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 305 { 306 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 307 PetscErrorCode ierr; 308 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 309 PetscInt nz = a->i[m],row,mr,col,tmp; 310 PetscInt *cspidx; 311 const PetscInt *jj; 312 313 PetscFunctionBegin; 314 *nn = n; 315 if (!ia) PetscFunctionReturn(0); 316 317 ierr = PetscCalloc1(n,&collengths);CHKERRQ(ierr); 318 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 319 ierr = PetscMalloc1(nz,&cja);CHKERRQ(ierr); 320 ierr = PetscMalloc1(nz,&cspidx);CHKERRQ(ierr); 321 jj = a->j; 322 for (i=0; i<nz; i++) { 323 collengths[jj[i]]++; 324 } 325 cia[0] = oshift; 326 for (i=0; i<n; i++) { 327 cia[i+1] = cia[i] + collengths[i]; 328 } 329 ierr = PetscArrayzero(collengths,n);CHKERRQ(ierr); 330 jj = a->j; 331 for (row=0; row<m; row++) { 332 mr = a->i[row+1] - a->i[row]; 333 for (i=0; i<mr; i++) { 334 col = *jj++; 335 tmp = cia[col] + collengths[col]++ - oshift; 336 cspidx[tmp] = a->i[row] + i; /* index of a->j */ 337 cja[tmp] = row + oshift; 338 } 339 } 340 ierr = PetscFree(collengths);CHKERRQ(ierr); 341 *ia = cia; 342 *ja = cja; 343 *spidx = cspidx; 344 PetscFunctionReturn(0); 345 } 346 347 PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 348 { 349 PetscErrorCode ierr; 350 351 PetscFunctionBegin; 352 ierr = MatRestoreColumnIJ_SeqAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);CHKERRQ(ierr); 353 ierr = PetscFree(*spidx);CHKERRQ(ierr); 354 PetscFunctionReturn(0); 355 } 356 357 PetscErrorCode MatSetValuesRow_SeqAIJ(Mat A,PetscInt row,const PetscScalar v[]) 358 { 359 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 360 PetscInt *ai = a->i; 361 PetscErrorCode ierr; 362 363 PetscFunctionBegin; 364 ierr = PetscArraycpy(a->a+ai[row],v,ai[row+1]-ai[row]);CHKERRQ(ierr); 365 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 366 if (A->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED && ai[row+1]-ai[row]) A->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 367 #endif 368 PetscFunctionReturn(0); 369 } 370 371 /* 372 MatSeqAIJSetValuesLocalFast - An optimized version of MatSetValuesLocal() for SeqAIJ matrices with several assumptions 373 374 - a single row of values is set with each call 375 - no row or column indices are negative or (in error) larger than the number of rows or columns 376 - the values are always added to the matrix, not set 377 - no new locations are introduced in the nonzero structure of the matrix 378 379 This does NOT assume the global column indices are sorted 380 381 */ 382 383 #include <petsc/private/isimpl.h> 384 PetscErrorCode MatSeqAIJSetValuesLocalFast(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 385 { 386 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 387 PetscInt low,high,t,row,nrow,i,col,l; 388 const PetscInt *rp,*ai = a->i,*ailen = a->ilen,*aj = a->j; 389 PetscInt lastcol = -1; 390 MatScalar *ap,value,*aa = a->a; 391 const PetscInt *ridx = A->rmap->mapping->indices,*cidx = A->cmap->mapping->indices; 392 393 row = ridx[im[0]]; 394 rp = aj + ai[row]; 395 ap = aa + ai[row]; 396 nrow = ailen[row]; 397 low = 0; 398 high = nrow; 399 for (l=0; l<n; l++) { /* loop over added columns */ 400 col = cidx[in[l]]; 401 value = v[l]; 402 403 if (col <= lastcol) low = 0; 404 else high = nrow; 405 lastcol = col; 406 while (high-low > 5) { 407 t = (low+high)/2; 408 if (rp[t] > col) high = t; 409 else low = t; 410 } 411 for (i=low; i<high; i++) { 412 if (rp[i] == col) { 413 ap[i] += value; 414 low = i + 1; 415 break; 416 } 417 } 418 } 419 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 420 if (A->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED && m*n) A->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 421 #endif 422 return 0; 423 } 424 425 PetscErrorCode MatSetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 426 { 427 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 428 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 429 PetscInt *imax = a->imax,*ai = a->i,*ailen = a->ilen; 430 PetscErrorCode ierr; 431 PetscInt *aj = a->j,nonew = a->nonew,lastcol = -1; 432 MatScalar *ap=NULL,value=0.0,*aa = a->a; 433 PetscBool ignorezeroentries = a->ignorezeroentries; 434 PetscBool roworiented = a->roworiented; 435 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 436 PetscBool inserted = PETSC_FALSE; 437 #endif 438 439 PetscFunctionBegin; 440 for (k=0; k<m; k++) { /* loop over added rows */ 441 row = im[k]; 442 if (row < 0) continue; 443 #if defined(PETSC_USE_DEBUG) 444 if (row >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); 445 #endif 446 rp = aj + ai[row]; 447 if (!A->structure_only) ap = aa + ai[row]; 448 rmax = imax[row]; nrow = ailen[row]; 449 low = 0; 450 high = nrow; 451 for (l=0; l<n; l++) { /* loop over added columns */ 452 if (in[l] < 0) continue; 453 #if defined(PETSC_USE_DEBUG) 454 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 455 #endif 456 col = in[l]; 457 if (v && !A->structure_only) value = roworiented ? v[l + k*n] : v[k + l*m]; 458 if (!A->structure_only && value == 0.0 && ignorezeroentries && is == ADD_VALUES && row != col) continue; 459 460 if (col <= lastcol) low = 0; 461 else high = nrow; 462 lastcol = col; 463 while (high-low > 5) { 464 t = (low+high)/2; 465 if (rp[t] > col) high = t; 466 else low = t; 467 } 468 for (i=low; i<high; i++) { 469 if (rp[i] > col) break; 470 if (rp[i] == col) { 471 if (!A->structure_only) { 472 if (is == ADD_VALUES) { 473 ap[i] += value; 474 (void)PetscLogFlops(1.0); 475 } 476 else ap[i] = value; 477 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 478 inserted = PETSC_TRUE; 479 #endif 480 } 481 low = i + 1; 482 goto noinsert; 483 } 484 } 485 if (value == 0.0 && ignorezeroentries && row != col) goto noinsert; 486 if (nonew == 1) goto noinsert; 487 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); 488 if (A->structure_only) { 489 MatSeqXAIJReallocateAIJ_structure_only(A,A->rmap->n,1,nrow,row,col,rmax,ai,aj,rp,imax,nonew,MatScalar); 490 } else { 491 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 492 } 493 N = nrow++ - 1; a->nz++; high++; 494 /* shift up all the later entries in this row */ 495 ierr = PetscArraymove(rp+i+1,rp+i,N-i+1);CHKERRQ(ierr); 496 rp[i] = col; 497 if (!A->structure_only){ 498 ierr = PetscArraymove(ap+i+1,ap+i,N-i+1);CHKERRQ(ierr); 499 ap[i] = value; 500 } 501 low = i + 1; 502 A->nonzerostate++; 503 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 504 inserted = PETSC_TRUE; 505 #endif 506 noinsert:; 507 } 508 ailen[row] = nrow; 509 } 510 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 511 if (A->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED && inserted) A->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 512 #endif 513 PetscFunctionReturn(0); 514 } 515 516 PetscErrorCode MatSetValues_SeqAIJ_SortedFull(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 517 { 518 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 519 PetscInt *rp,k,row; 520 PetscInt *ai = a->i,*ailen = a->ilen; 521 PetscErrorCode ierr; 522 PetscInt *aj = a->j; 523 MatScalar *aa = a->a,*ap; 524 525 PetscFunctionBegin; 526 for (k=0; k<m; k++) { /* loop over added rows */ 527 row = im[k]; 528 rp = aj + ai[row]; 529 ap = aa + ai[row]; 530 if (!A->was_assembled) { 531 ierr = PetscMemcpy(rp,in,n*sizeof(PetscInt));CHKERRQ(ierr); 532 } 533 if (!A->structure_only) { 534 if (v) { 535 ierr = PetscMemcpy(ap,v,n*sizeof(PetscScalar));CHKERRQ(ierr); 536 v += n; 537 } else { 538 ierr = PetscMemzero(ap,n*sizeof(PetscScalar));CHKERRQ(ierr); 539 } 540 } 541 ailen[row] = n; 542 a->nz += n; 543 } 544 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 545 if (A->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED && m*n) A->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 546 #endif 547 PetscFunctionReturn(0); 548 } 549 550 551 PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 552 { 553 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 554 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 555 PetscInt *ai = a->i,*ailen = a->ilen; 556 MatScalar *ap,*aa = a->a; 557 558 PetscFunctionBegin; 559 for (k=0; k<m; k++) { /* loop over rows */ 560 row = im[k]; 561 if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */ 562 if (row >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); 563 rp = aj + ai[row]; ap = aa + ai[row]; 564 nrow = ailen[row]; 565 for (l=0; l<n; l++) { /* loop over columns */ 566 if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */ 567 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 568 col = in[l]; 569 high = nrow; low = 0; /* assume unsorted */ 570 while (high-low > 5) { 571 t = (low+high)/2; 572 if (rp[t] > col) high = t; 573 else low = t; 574 } 575 for (i=low; i<high; i++) { 576 if (rp[i] > col) break; 577 if (rp[i] == col) { 578 *v++ = ap[i]; 579 goto finished; 580 } 581 } 582 *v++ = 0.0; 583 finished:; 584 } 585 } 586 PetscFunctionReturn(0); 587 } 588 589 590 PetscErrorCode MatView_SeqAIJ_Binary(Mat A,PetscViewer viewer) 591 { 592 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 593 PetscErrorCode ierr; 594 PetscInt i,*col_lens; 595 int fd; 596 FILE *file; 597 598 PetscFunctionBegin; 599 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 600 ierr = PetscMalloc1(4+A->rmap->n,&col_lens);CHKERRQ(ierr); 601 602 col_lens[0] = MAT_FILE_CLASSID; 603 col_lens[1] = A->rmap->n; 604 col_lens[2] = A->cmap->n; 605 col_lens[3] = a->nz; 606 607 /* store lengths of each row and write (including header) to file */ 608 for (i=0; i<A->rmap->n; i++) { 609 col_lens[4+i] = a->i[i+1] - a->i[i]; 610 } 611 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 612 ierr = PetscFree(col_lens);CHKERRQ(ierr); 613 614 /* store column indices (zero start index) */ 615 ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 616 617 /* store nonzero values */ 618 ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 619 620 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 621 if (file) { 622 fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(A->rmap->bs)); 623 } 624 PetscFunctionReturn(0); 625 } 626 627 static PetscErrorCode MatView_SeqAIJ_ASCII_structonly(Mat A,PetscViewer viewer) 628 { 629 PetscErrorCode ierr; 630 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 631 PetscInt i,k,m=A->rmap->N; 632 633 PetscFunctionBegin; 634 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 635 for (i=0; i<m; i++) { 636 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 637 for (k=a->i[i]; k<a->i[i+1]; k++) { 638 ierr = PetscViewerASCIIPrintf(viewer," (%D) ",a->j[k]);CHKERRQ(ierr); 639 } 640 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 641 } 642 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 643 PetscFunctionReturn(0); 644 } 645 646 extern PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); 647 648 PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) 649 { 650 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 651 PetscErrorCode ierr; 652 PetscInt i,j,m = A->rmap->n; 653 const char *name; 654 PetscViewerFormat format; 655 656 PetscFunctionBegin; 657 if (A->structure_only) { 658 ierr = MatView_SeqAIJ_ASCII_structonly(A,viewer);CHKERRQ(ierr); 659 PetscFunctionReturn(0); 660 } 661 662 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 663 if (format == PETSC_VIEWER_ASCII_MATLAB) { 664 PetscInt nofinalvalue = 0; 665 if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-1))) { 666 /* Need a dummy value to ensure the dimension of the matrix. */ 667 nofinalvalue = 1; 668 } 669 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 670 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); 671 ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); 672 #if defined(PETSC_USE_COMPLEX) 673 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,4);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 674 #else 675 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 676 #endif 677 ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); 678 679 for (i=0; i<m; i++) { 680 for (j=a->i[i]; j<a->i[i+1]; j++) { 681 #if defined(PETSC_USE_COMPLEX) 682 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",i+1,a->j[j]+1,(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 683 #else 684 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+1,(double)a->a[j]);CHKERRQ(ierr); 685 #endif 686 } 687 } 688 if (nofinalvalue) { 689 #if defined(PETSC_USE_COMPLEX) 690 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",m,A->cmap->n,0.,0.);CHKERRQ(ierr); 691 #else 692 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); 693 #endif 694 } 695 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 696 ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); 697 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 698 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 699 PetscFunctionReturn(0); 700 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 701 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 702 for (i=0; i<m; i++) { 703 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 704 for (j=a->i[i]; j<a->i[i+1]; j++) { 705 #if defined(PETSC_USE_COMPLEX) 706 if (PetscImaginaryPart(a->a[j]) > 0.0 && PetscRealPart(a->a[j]) != 0.0) { 707 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 708 } else if (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { 709 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 710 } else if (PetscRealPart(a->a[j]) != 0.0) { 711 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 712 } 713 #else 714 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr);} 715 #endif 716 } 717 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 718 } 719 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 720 } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { 721 PetscInt nzd=0,fshift=1,*sptr; 722 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 723 ierr = PetscMalloc1(m+1,&sptr);CHKERRQ(ierr); 724 for (i=0; i<m; i++) { 725 sptr[i] = nzd+1; 726 for (j=a->i[i]; j<a->i[i+1]; j++) { 727 if (a->j[j] >= i) { 728 #if defined(PETSC_USE_COMPLEX) 729 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; 730 #else 731 if (a->a[j] != 0.0) nzd++; 732 #endif 733 } 734 } 735 } 736 sptr[m] = nzd+1; 737 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); 738 for (i=0; i<m+1; i+=6) { 739 if (i+4<m) { 740 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4],sptr[i+5]);CHKERRQ(ierr); 741 } else if (i+3<m) { 742 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4]);CHKERRQ(ierr); 743 } else if (i+2<m) { 744 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]);CHKERRQ(ierr); 745 } else if (i+1<m) { 746 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2]);CHKERRQ(ierr); 747 } else if (i<m) { 748 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n",sptr[i],sptr[i+1]);CHKERRQ(ierr); 749 } else { 750 ierr = PetscViewerASCIIPrintf(viewer," %D\n",sptr[i]);CHKERRQ(ierr); 751 } 752 } 753 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 754 ierr = PetscFree(sptr);CHKERRQ(ierr); 755 for (i=0; i<m; i++) { 756 for (j=a->i[i]; j<a->i[i+1]; j++) { 757 if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} 758 } 759 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 760 } 761 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 762 for (i=0; i<m; i++) { 763 for (j=a->i[i]; j<a->i[i+1]; j++) { 764 if (a->j[j] >= i) { 765 #if defined(PETSC_USE_COMPLEX) 766 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { 767 ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 768 } 769 #else 770 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",(double)a->a[j]);CHKERRQ(ierr);} 771 #endif 772 } 773 } 774 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 775 } 776 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 777 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 778 PetscInt cnt = 0,jcnt; 779 PetscScalar value; 780 #if defined(PETSC_USE_COMPLEX) 781 PetscBool realonly = PETSC_TRUE; 782 783 for (i=0; i<a->i[m]; i++) { 784 if (PetscImaginaryPart(a->a[i]) != 0.0) { 785 realonly = PETSC_FALSE; 786 break; 787 } 788 } 789 #endif 790 791 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 792 for (i=0; i<m; i++) { 793 jcnt = 0; 794 for (j=0; j<A->cmap->n; j++) { 795 if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 796 value = a->a[cnt++]; 797 jcnt++; 798 } else { 799 value = 0.0; 800 } 801 #if defined(PETSC_USE_COMPLEX) 802 if (realonly) { 803 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)PetscRealPart(value));CHKERRQ(ierr); 804 } else { 805 ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",(double)PetscRealPart(value),(double)PetscImaginaryPart(value));CHKERRQ(ierr); 806 } 807 #else 808 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)value);CHKERRQ(ierr); 809 #endif 810 } 811 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 812 } 813 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 814 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 815 PetscInt fshift=1; 816 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 817 #if defined(PETSC_USE_COMPLEX) 818 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate complex general\n");CHKERRQ(ierr); 819 #else 820 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate real general\n");CHKERRQ(ierr); 821 #endif 822 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); 823 for (i=0; i<m; i++) { 824 for (j=a->i[i]; j<a->i[i+1]; j++) { 825 #if defined(PETSC_USE_COMPLEX) 826 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g %g\n", i+fshift,a->j[j]+fshift,(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 827 #else 828 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g\n", i+fshift, a->j[j]+fshift, (double)a->a[j]);CHKERRQ(ierr); 829 #endif 830 } 831 } 832 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 833 } else { 834 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 835 if (A->factortype) { 836 for (i=0; i<m; i++) { 837 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 838 /* L part */ 839 for (j=a->i[i]; j<a->i[i+1]; j++) { 840 #if defined(PETSC_USE_COMPLEX) 841 if (PetscImaginaryPart(a->a[j]) > 0.0) { 842 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 843 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 844 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 845 } else { 846 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 847 } 848 #else 849 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 850 #endif 851 } 852 /* diagonal */ 853 j = a->diag[i]; 854 #if defined(PETSC_USE_COMPLEX) 855 if (PetscImaginaryPart(a->a[j]) > 0.0) { 856 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(1.0/a->a[j]),(double)PetscImaginaryPart(1.0/a->a[j]));CHKERRQ(ierr); 857 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 858 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(1.0/a->a[j]),(double)(-PetscImaginaryPart(1.0/a->a[j])));CHKERRQ(ierr); 859 } else { 860 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(1.0/a->a[j]));CHKERRQ(ierr); 861 } 862 #else 863 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)(1.0/a->a[j]));CHKERRQ(ierr); 864 #endif 865 866 /* U part */ 867 for (j=a->diag[i+1]+1; j<a->diag[i]; j++) { 868 #if defined(PETSC_USE_COMPLEX) 869 if (PetscImaginaryPart(a->a[j]) > 0.0) { 870 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 871 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 872 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 873 } else { 874 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 875 } 876 #else 877 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 878 #endif 879 } 880 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 881 } 882 } else { 883 for (i=0; i<m; i++) { 884 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 885 for (j=a->i[i]; j<a->i[i+1]; j++) { 886 #if defined(PETSC_USE_COMPLEX) 887 if (PetscImaginaryPart(a->a[j]) > 0.0) { 888 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 889 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 890 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 891 } else { 892 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 893 } 894 #else 895 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 896 #endif 897 } 898 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 899 } 900 } 901 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 902 } 903 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 904 PetscFunctionReturn(0); 905 } 906 907 #include <petscdraw.h> 908 PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 909 { 910 Mat A = (Mat) Aa; 911 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 912 PetscErrorCode ierr; 913 PetscInt i,j,m = A->rmap->n; 914 int color; 915 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 916 PetscViewer viewer; 917 PetscViewerFormat format; 918 919 PetscFunctionBegin; 920 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 921 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 922 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 923 924 /* loop over matrix elements drawing boxes */ 925 926 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 927 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 928 /* Blue for negative, Cyan for zero and Red for positive */ 929 color = PETSC_DRAW_BLUE; 930 for (i=0; i<m; i++) { 931 y_l = m - i - 1.0; y_r = y_l + 1.0; 932 for (j=a->i[i]; j<a->i[i+1]; j++) { 933 x_l = a->j[j]; x_r = x_l + 1.0; 934 if (PetscRealPart(a->a[j]) >= 0.) continue; 935 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 936 } 937 } 938 color = PETSC_DRAW_CYAN; 939 for (i=0; i<m; i++) { 940 y_l = m - i - 1.0; y_r = y_l + 1.0; 941 for (j=a->i[i]; j<a->i[i+1]; j++) { 942 x_l = a->j[j]; x_r = x_l + 1.0; 943 if (a->a[j] != 0.) continue; 944 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 945 } 946 } 947 color = PETSC_DRAW_RED; 948 for (i=0; i<m; i++) { 949 y_l = m - i - 1.0; y_r = y_l + 1.0; 950 for (j=a->i[i]; j<a->i[i+1]; j++) { 951 x_l = a->j[j]; x_r = x_l + 1.0; 952 if (PetscRealPart(a->a[j]) <= 0.) continue; 953 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 954 } 955 } 956 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 957 } else { 958 /* use contour shading to indicate magnitude of values */ 959 /* first determine max of all nonzero values */ 960 PetscReal minv = 0.0, maxv = 0.0; 961 PetscInt nz = a->nz, count = 0; 962 PetscDraw popup; 963 964 for (i=0; i<nz; i++) { 965 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 966 } 967 if (minv >= maxv) maxv = minv + PETSC_SMALL; 968 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 969 ierr = PetscDrawScalePopup(popup,minv,maxv);CHKERRQ(ierr); 970 971 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 972 for (i=0; i<m; i++) { 973 y_l = m - i - 1.0; 974 y_r = y_l + 1.0; 975 for (j=a->i[i]; j<a->i[i+1]; j++) { 976 x_l = a->j[j]; 977 x_r = x_l + 1.0; 978 color = PetscDrawRealToColor(PetscAbsScalar(a->a[count]),minv,maxv); 979 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 980 count++; 981 } 982 } 983 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 984 } 985 PetscFunctionReturn(0); 986 } 987 988 #include <petscdraw.h> 989 PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) 990 { 991 PetscErrorCode ierr; 992 PetscDraw draw; 993 PetscReal xr,yr,xl,yl,h,w; 994 PetscBool isnull; 995 996 PetscFunctionBegin; 997 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 998 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 999 if (isnull) PetscFunctionReturn(0); 1000 1001 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 1002 xr += w; yr += h; xl = -w; yl = -h; 1003 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 1004 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 1005 ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); 1006 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 1007 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 1008 PetscFunctionReturn(0); 1009 } 1010 1011 PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) 1012 { 1013 PetscErrorCode ierr; 1014 PetscBool iascii,isbinary,isdraw; 1015 1016 PetscFunctionBegin; 1017 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1018 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1019 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1020 if (iascii) { 1021 ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); 1022 } else if (isbinary) { 1023 ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); 1024 } else if (isdraw) { 1025 ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); 1026 } 1027 ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); 1028 PetscFunctionReturn(0); 1029 } 1030 1031 PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 1032 { 1033 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1034 PetscErrorCode ierr; 1035 PetscInt fshift = 0,i,*ai = a->i,*aj = a->j,*imax = a->imax; 1036 PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; 1037 MatScalar *aa = a->a,*ap; 1038 PetscReal ratio = 0.6; 1039 1040 PetscFunctionBegin; 1041 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 1042 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1043 if (A->was_assembled && A->ass_nonzerostate == A->nonzerostate) PetscFunctionReturn(0); 1044 1045 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 1046 for (i=1; i<m; i++) { 1047 /* move each row back by the amount of empty slots (fshift) before it*/ 1048 fshift += imax[i-1] - ailen[i-1]; 1049 rmax = PetscMax(rmax,ailen[i]); 1050 if (fshift) { 1051 ip = aj + ai[i]; 1052 ap = aa + ai[i]; 1053 N = ailen[i]; 1054 ierr = PetscArraymove(ip-fshift,ip,N);CHKERRQ(ierr); 1055 if (!A->structure_only) { 1056 ierr = PetscArraymove(ap-fshift,ap,N);CHKERRQ(ierr); 1057 } 1058 } 1059 ai[i] = ai[i-1] + ailen[i-1]; 1060 } 1061 if (m) { 1062 fshift += imax[m-1] - ailen[m-1]; 1063 ai[m] = ai[m-1] + ailen[m-1]; 1064 } 1065 1066 /* reset ilen and imax for each row */ 1067 a->nonzerorowcnt = 0; 1068 if (A->structure_only) { 1069 ierr = PetscFree(a->imax);CHKERRQ(ierr); 1070 ierr = PetscFree(a->ilen);CHKERRQ(ierr); 1071 } else { /* !A->structure_only */ 1072 for (i=0; i<m; i++) { 1073 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1074 a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0); 1075 } 1076 } 1077 a->nz = ai[m]; 1078 if (fshift && a->nounused == -1) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D, %D unneeded", m, A->cmap->n, fshift); 1079 1080 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1081 ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); 1082 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); 1083 ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); 1084 1085 A->info.mallocs += a->reallocs; 1086 a->reallocs = 0; 1087 A->info.nz_unneeded = (PetscReal)fshift; 1088 a->rmax = rmax; 1089 1090 if (!A->structure_only) { 1091 ierr = MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); 1092 } 1093 ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); 1094 PetscFunctionReturn(0); 1095 } 1096 1097 PetscErrorCode MatRealPart_SeqAIJ(Mat A) 1098 { 1099 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1100 PetscInt i,nz = a->nz; 1101 MatScalar *aa = a->a; 1102 PetscErrorCode ierr; 1103 1104 PetscFunctionBegin; 1105 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1106 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1107 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 1108 if (A->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) A->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 1109 #endif 1110 PetscFunctionReturn(0); 1111 } 1112 1113 PetscErrorCode MatImaginaryPart_SeqAIJ(Mat A) 1114 { 1115 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1116 PetscInt i,nz = a->nz; 1117 MatScalar *aa = a->a; 1118 PetscErrorCode ierr; 1119 1120 PetscFunctionBegin; 1121 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1122 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1123 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 1124 if (A->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) A->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 1125 #endif 1126 PetscFunctionReturn(0); 1127 } 1128 1129 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1130 { 1131 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1132 PetscErrorCode ierr; 1133 1134 PetscFunctionBegin; 1135 ierr = PetscArrayzero(a->a,a->i[A->rmap->n]);CHKERRQ(ierr); 1136 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1137 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 1138 if (A->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) A->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 1139 #endif 1140 PetscFunctionReturn(0); 1141 } 1142 1143 PetscErrorCode MatDestroy_SeqAIJ(Mat A) 1144 { 1145 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1146 PetscErrorCode ierr; 1147 1148 PetscFunctionBegin; 1149 #if defined(PETSC_USE_LOG) 1150 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); 1151 #endif 1152 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1153 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1154 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1155 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1156 ierr = PetscFree(a->ibdiag);CHKERRQ(ierr); 1157 ierr = PetscFree(a->imax);CHKERRQ(ierr); 1158 ierr = PetscFree(a->ilen);CHKERRQ(ierr); 1159 ierr = PetscFree(a->ipre);CHKERRQ(ierr); 1160 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 1161 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1162 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1163 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1164 ierr = ISColoringDestroy(&a->coloring);CHKERRQ(ierr); 1165 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1166 ierr = PetscFree(a->matmult_abdense);CHKERRQ(ierr); 1167 1168 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 1169 ierr = PetscFree(A->data);CHKERRQ(ierr); 1170 1171 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1172 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1173 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1174 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1175 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1176 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); 1177 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); 1178 #if defined(PETSC_HAVE_ELEMENTAL) 1179 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_elemental_C",NULL);CHKERRQ(ierr); 1180 #endif 1181 #if defined(PETSC_HAVE_HYPRE) 1182 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_hypre_C",NULL);CHKERRQ(ierr); 1183 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMatMatMult_transpose_seqaij_seqaij_C",NULL);CHKERRQ(ierr); 1184 #endif 1185 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1186 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsell_C",NULL);CHKERRQ(ierr); 1187 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_is_C",NULL);CHKERRQ(ierr); 1188 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1189 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1190 ierr = PetscObjectComposeFunction((PetscObject)A,"MatResetPreallocation_C",NULL);CHKERRQ(ierr); 1191 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1192 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1193 ierr = PetscObjectComposeFunction((PetscObject)A,"MatPtAP_is_seqaij_C",NULL);CHKERRQ(ierr); 1194 PetscFunctionReturn(0); 1195 } 1196 1197 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1198 { 1199 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1200 PetscErrorCode ierr; 1201 1202 PetscFunctionBegin; 1203 switch (op) { 1204 case MAT_ROW_ORIENTED: 1205 a->roworiented = flg; 1206 break; 1207 case MAT_KEEP_NONZERO_PATTERN: 1208 a->keepnonzeropattern = flg; 1209 break; 1210 case MAT_NEW_NONZERO_LOCATIONS: 1211 a->nonew = (flg ? 0 : 1); 1212 break; 1213 case MAT_NEW_NONZERO_LOCATION_ERR: 1214 a->nonew = (flg ? -1 : 0); 1215 break; 1216 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1217 a->nonew = (flg ? -2 : 0); 1218 break; 1219 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1220 a->nounused = (flg ? -1 : 0); 1221 break; 1222 case MAT_IGNORE_ZERO_ENTRIES: 1223 a->ignorezeroentries = flg; 1224 break; 1225 case MAT_SPD: 1226 case MAT_SYMMETRIC: 1227 case MAT_STRUCTURALLY_SYMMETRIC: 1228 case MAT_HERMITIAN: 1229 case MAT_SYMMETRY_ETERNAL: 1230 case MAT_STRUCTURE_ONLY: 1231 /* These options are handled directly by MatSetOption() */ 1232 break; 1233 case MAT_NEW_DIAGONALS: 1234 case MAT_IGNORE_OFF_PROC_ENTRIES: 1235 case MAT_USE_HASH_TABLE: 1236 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1237 break; 1238 case MAT_USE_INODES: 1239 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1240 break; 1241 case MAT_SUBMAT_SINGLEIS: 1242 A->submat_singleis = flg; 1243 break; 1244 case MAT_SORTED_FULL: 1245 if (flg) A->ops->setvalues = MatSetValues_SeqAIJ_SortedFull; 1246 else A->ops->setvalues = MatSetValues_SeqAIJ; 1247 break; 1248 default: 1249 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1250 } 1251 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1252 PetscFunctionReturn(0); 1253 } 1254 1255 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1256 { 1257 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1258 PetscErrorCode ierr; 1259 PetscInt i,j,n,*ai=a->i,*aj=a->j; 1260 PetscScalar *aa=a->a,*x; 1261 1262 PetscFunctionBegin; 1263 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1264 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1265 1266 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1267 PetscInt *diag=a->diag; 1268 ierr = VecGetArrayWrite(v,&x);CHKERRQ(ierr); 1269 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1270 ierr = VecRestoreArrayWrite(v,&x);CHKERRQ(ierr); 1271 PetscFunctionReturn(0); 1272 } 1273 1274 ierr = VecGetArrayWrite(v,&x);CHKERRQ(ierr); 1275 for (i=0; i<n; i++) { 1276 x[i] = 0.0; 1277 for (j=ai[i]; j<ai[i+1]; j++) { 1278 if (aj[j] == i) { 1279 x[i] = aa[j]; 1280 break; 1281 } 1282 } 1283 } 1284 ierr = VecRestoreArrayWrite(v,&x);CHKERRQ(ierr); 1285 PetscFunctionReturn(0); 1286 } 1287 1288 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1289 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1290 { 1291 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1292 PetscScalar *y; 1293 const PetscScalar *x; 1294 PetscErrorCode ierr; 1295 PetscInt m = A->rmap->n; 1296 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1297 const MatScalar *v; 1298 PetscScalar alpha; 1299 PetscInt n,i,j; 1300 const PetscInt *idx,*ii,*ridx=NULL; 1301 Mat_CompressedRow cprow = a->compressedrow; 1302 PetscBool usecprow = cprow.use; 1303 #endif 1304 1305 PetscFunctionBegin; 1306 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1307 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1308 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1309 1310 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1311 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1312 #else 1313 if (usecprow) { 1314 m = cprow.nrows; 1315 ii = cprow.i; 1316 ridx = cprow.rindex; 1317 } else { 1318 ii = a->i; 1319 } 1320 for (i=0; i<m; i++) { 1321 idx = a->j + ii[i]; 1322 v = a->a + ii[i]; 1323 n = ii[i+1] - ii[i]; 1324 if (usecprow) { 1325 alpha = x[ridx[i]]; 1326 } else { 1327 alpha = x[i]; 1328 } 1329 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1330 } 1331 #endif 1332 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1333 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1334 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1335 PetscFunctionReturn(0); 1336 } 1337 1338 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1339 { 1340 PetscErrorCode ierr; 1341 1342 PetscFunctionBegin; 1343 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1344 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1345 PetscFunctionReturn(0); 1346 } 1347 1348 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1349 1350 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1351 { 1352 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1353 PetscScalar *y; 1354 const PetscScalar *x; 1355 const MatScalar *aa; 1356 PetscErrorCode ierr; 1357 PetscInt m=A->rmap->n; 1358 const PetscInt *aj,*ii,*ridx=NULL; 1359 PetscInt n,i; 1360 PetscScalar sum; 1361 PetscBool usecprow=a->compressedrow.use; 1362 1363 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1364 #pragma disjoint(*x,*y,*aa) 1365 #endif 1366 1367 PetscFunctionBegin; 1368 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1369 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1370 ii = a->i; 1371 if (usecprow) { /* use compressed row format */ 1372 ierr = PetscArrayzero(y,m);CHKERRQ(ierr); 1373 m = a->compressedrow.nrows; 1374 ii = a->compressedrow.i; 1375 ridx = a->compressedrow.rindex; 1376 for (i=0; i<m; i++) { 1377 n = ii[i+1] - ii[i]; 1378 aj = a->j + ii[i]; 1379 aa = a->a + ii[i]; 1380 sum = 0.0; 1381 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1382 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1383 y[*ridx++] = sum; 1384 } 1385 } else { /* do not use compressed row format */ 1386 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1387 aj = a->j; 1388 aa = a->a; 1389 fortranmultaij_(&m,x,ii,aj,aa,y); 1390 #else 1391 for (i=0; i<m; i++) { 1392 n = ii[i+1] - ii[i]; 1393 aj = a->j + ii[i]; 1394 aa = a->a + ii[i]; 1395 sum = 0.0; 1396 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1397 y[i] = sum; 1398 } 1399 #endif 1400 } 1401 ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); 1402 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1403 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1404 PetscFunctionReturn(0); 1405 } 1406 1407 PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) 1408 { 1409 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1410 PetscScalar *y; 1411 const PetscScalar *x; 1412 const MatScalar *aa; 1413 PetscErrorCode ierr; 1414 PetscInt m=A->rmap->n; 1415 const PetscInt *aj,*ii,*ridx=NULL; 1416 PetscInt n,i,nonzerorow=0; 1417 PetscScalar sum; 1418 PetscBool usecprow=a->compressedrow.use; 1419 1420 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1421 #pragma disjoint(*x,*y,*aa) 1422 #endif 1423 1424 PetscFunctionBegin; 1425 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1426 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1427 if (usecprow) { /* use compressed row format */ 1428 m = a->compressedrow.nrows; 1429 ii = a->compressedrow.i; 1430 ridx = a->compressedrow.rindex; 1431 for (i=0; i<m; i++) { 1432 n = ii[i+1] - ii[i]; 1433 aj = a->j + ii[i]; 1434 aa = a->a + ii[i]; 1435 sum = 0.0; 1436 nonzerorow += (n>0); 1437 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1438 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1439 y[*ridx++] = sum; 1440 } 1441 } else { /* do not use compressed row format */ 1442 ii = a->i; 1443 for (i=0; i<m; i++) { 1444 n = ii[i+1] - ii[i]; 1445 aj = a->j + ii[i]; 1446 aa = a->a + ii[i]; 1447 sum = 0.0; 1448 nonzerorow += (n>0); 1449 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1450 y[i] = sum; 1451 } 1452 } 1453 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1454 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1455 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1456 PetscFunctionReturn(0); 1457 } 1458 1459 PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1460 { 1461 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1462 PetscScalar *y,*z; 1463 const PetscScalar *x; 1464 const MatScalar *aa; 1465 PetscErrorCode ierr; 1466 PetscInt m = A->rmap->n,*aj,*ii; 1467 PetscInt n,i,*ridx=NULL; 1468 PetscScalar sum; 1469 PetscBool usecprow=a->compressedrow.use; 1470 1471 PetscFunctionBegin; 1472 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1473 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1474 if (usecprow) { /* use compressed row format */ 1475 if (zz != yy) { 1476 ierr = PetscArraycpy(z,y,m);CHKERRQ(ierr); 1477 } 1478 m = a->compressedrow.nrows; 1479 ii = a->compressedrow.i; 1480 ridx = a->compressedrow.rindex; 1481 for (i=0; i<m; i++) { 1482 n = ii[i+1] - ii[i]; 1483 aj = a->j + ii[i]; 1484 aa = a->a + ii[i]; 1485 sum = y[*ridx]; 1486 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1487 z[*ridx++] = sum; 1488 } 1489 } else { /* do not use compressed row format */ 1490 ii = a->i; 1491 for (i=0; i<m; i++) { 1492 n = ii[i+1] - ii[i]; 1493 aj = a->j + ii[i]; 1494 aa = a->a + ii[i]; 1495 sum = y[i]; 1496 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1497 z[i] = sum; 1498 } 1499 } 1500 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1501 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1502 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1503 PetscFunctionReturn(0); 1504 } 1505 1506 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 1507 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1508 { 1509 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1510 PetscScalar *y,*z; 1511 const PetscScalar *x; 1512 const MatScalar *aa; 1513 PetscErrorCode ierr; 1514 const PetscInt *aj,*ii,*ridx=NULL; 1515 PetscInt m = A->rmap->n,n,i; 1516 PetscScalar sum; 1517 PetscBool usecprow=a->compressedrow.use; 1518 1519 PetscFunctionBegin; 1520 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1521 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1522 if (usecprow) { /* use compressed row format */ 1523 if (zz != yy) { 1524 ierr = PetscArraycpy(z,y,m);CHKERRQ(ierr); 1525 } 1526 m = a->compressedrow.nrows; 1527 ii = a->compressedrow.i; 1528 ridx = a->compressedrow.rindex; 1529 for (i=0; i<m; i++) { 1530 n = ii[i+1] - ii[i]; 1531 aj = a->j + ii[i]; 1532 aa = a->a + ii[i]; 1533 sum = y[*ridx]; 1534 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1535 z[*ridx++] = sum; 1536 } 1537 } else { /* do not use compressed row format */ 1538 ii = a->i; 1539 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1540 aj = a->j; 1541 aa = a->a; 1542 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1543 #else 1544 for (i=0; i<m; i++) { 1545 n = ii[i+1] - ii[i]; 1546 aj = a->j + ii[i]; 1547 aa = a->a + ii[i]; 1548 sum = y[i]; 1549 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1550 z[i] = sum; 1551 } 1552 #endif 1553 } 1554 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1555 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1556 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1557 PetscFunctionReturn(0); 1558 } 1559 1560 /* 1561 Adds diagonal pointers to sparse matrix structure. 1562 */ 1563 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1564 { 1565 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1566 PetscErrorCode ierr; 1567 PetscInt i,j,m = A->rmap->n; 1568 1569 PetscFunctionBegin; 1570 if (!a->diag) { 1571 ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); 1572 ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); 1573 } 1574 for (i=0; i<A->rmap->n; i++) { 1575 a->diag[i] = a->i[i+1]; 1576 for (j=a->i[i]; j<a->i[i+1]; j++) { 1577 if (a->j[j] == i) { 1578 a->diag[i] = j; 1579 break; 1580 } 1581 } 1582 } 1583 PetscFunctionReturn(0); 1584 } 1585 1586 PetscErrorCode MatShift_SeqAIJ(Mat A,PetscScalar v) 1587 { 1588 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1589 const PetscInt *diag = (const PetscInt*)a->diag; 1590 const PetscInt *ii = (const PetscInt*) a->i; 1591 PetscInt i,*mdiag = NULL; 1592 PetscErrorCode ierr; 1593 PetscInt cnt = 0; /* how many diagonals are missing */ 1594 1595 PetscFunctionBegin; 1596 if (!A->preallocated || !a->nz) { 1597 ierr = MatSeqAIJSetPreallocation(A,1,NULL);CHKERRQ(ierr); 1598 ierr = MatShift_Basic(A,v);CHKERRQ(ierr); 1599 PetscFunctionReturn(0); 1600 } 1601 1602 if (a->diagonaldense) { 1603 cnt = 0; 1604 } else { 1605 ierr = PetscCalloc1(A->rmap->n,&mdiag);CHKERRQ(ierr); 1606 for (i=0; i<A->rmap->n; i++) { 1607 if (diag[i] >= ii[i+1]) { 1608 cnt++; 1609 mdiag[i] = 1; 1610 } 1611 } 1612 } 1613 if (!cnt) { 1614 ierr = MatShift_Basic(A,v);CHKERRQ(ierr); 1615 } else { 1616 PetscScalar *olda = a->a; /* preserve pointers to current matrix nonzeros structure and values */ 1617 PetscInt *oldj = a->j, *oldi = a->i; 1618 PetscBool singlemalloc = a->singlemalloc,free_a = a->free_a,free_ij = a->free_ij; 1619 1620 a->a = NULL; 1621 a->j = NULL; 1622 a->i = NULL; 1623 /* increase the values in imax for each row where a diagonal is being inserted then reallocate the matrix data structures */ 1624 for (i=0; i<A->rmap->n; i++) { 1625 a->imax[i] += mdiag[i]; 1626 a->imax[i] = PetscMin(a->imax[i],A->cmap->n); 1627 } 1628 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,0,a->imax);CHKERRQ(ierr); 1629 1630 /* copy old values into new matrix data structure */ 1631 for (i=0; i<A->rmap->n; i++) { 1632 ierr = MatSetValues(A,1,&i,a->imax[i] - mdiag[i],&oldj[oldi[i]],&olda[oldi[i]],ADD_VALUES);CHKERRQ(ierr); 1633 if (i < A->cmap->n) { 1634 ierr = MatSetValue(A,i,i,v,ADD_VALUES);CHKERRQ(ierr); 1635 } 1636 } 1637 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1638 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1639 if (singlemalloc) { 1640 ierr = PetscFree3(olda,oldj,oldi);CHKERRQ(ierr); 1641 } else { 1642 if (free_a) {ierr = PetscFree(olda);CHKERRQ(ierr);} 1643 if (free_ij) {ierr = PetscFree(oldj);CHKERRQ(ierr);} 1644 if (free_ij) {ierr = PetscFree(oldi);CHKERRQ(ierr);} 1645 } 1646 } 1647 ierr = PetscFree(mdiag);CHKERRQ(ierr); 1648 a->diagonaldense = PETSC_TRUE; 1649 PetscFunctionReturn(0); 1650 } 1651 1652 /* 1653 Checks for missing diagonals 1654 */ 1655 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) 1656 { 1657 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1658 PetscInt *diag,*ii = a->i,i; 1659 PetscErrorCode ierr; 1660 1661 PetscFunctionBegin; 1662 *missing = PETSC_FALSE; 1663 if (A->rmap->n > 0 && !ii) { 1664 *missing = PETSC_TRUE; 1665 if (d) *d = 0; 1666 ierr = PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n");CHKERRQ(ierr); 1667 } else { 1668 PetscInt n; 1669 n = PetscMin(A->rmap->n, A->cmap->n); 1670 diag = a->diag; 1671 for (i=0; i<n; i++) { 1672 if (diag[i] >= ii[i+1]) { 1673 *missing = PETSC_TRUE; 1674 if (d) *d = i; 1675 ierr = PetscInfo1(A,"Matrix is missing diagonal number %D\n",i);CHKERRQ(ierr); 1676 break; 1677 } 1678 } 1679 } 1680 PetscFunctionReturn(0); 1681 } 1682 1683 #include <petscblaslapack.h> 1684 #include <petsc/private/kernels/blockinvert.h> 1685 1686 /* 1687 Note that values is allocated externally by the PC and then passed into this routine 1688 */ 1689 PetscErrorCode MatInvertVariableBlockDiagonal_SeqAIJ(Mat A,PetscInt nblocks,const PetscInt *bsizes,PetscScalar *diag) 1690 { 1691 PetscErrorCode ierr; 1692 PetscInt n = A->rmap->n, i, ncnt = 0, *indx,j,bsizemax = 0,*v_pivots; 1693 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 1694 const PetscReal shift = 0.0; 1695 PetscInt ipvt[5]; 1696 PetscScalar work[25],*v_work; 1697 1698 PetscFunctionBegin; 1699 allowzeropivot = PetscNot(A->erroriffailure); 1700 for (i=0; i<nblocks; i++) ncnt += bsizes[i]; 1701 if (ncnt != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Total blocksizes %D doesn't match number matrix rows %D",ncnt,n); 1702 for (i=0; i<nblocks; i++) { 1703 bsizemax = PetscMax(bsizemax,bsizes[i]); 1704 } 1705 ierr = PetscMalloc1(bsizemax,&indx);CHKERRQ(ierr); 1706 if (bsizemax > 7) { 1707 ierr = PetscMalloc2(bsizemax,&v_work,bsizemax,&v_pivots);CHKERRQ(ierr); 1708 } 1709 ncnt = 0; 1710 for (i=0; i<nblocks; i++) { 1711 for (j=0; j<bsizes[i]; j++) indx[j] = ncnt+j; 1712 ierr = MatGetValues(A,bsizes[i],indx,bsizes[i],indx,diag);CHKERRQ(ierr); 1713 switch (bsizes[i]) { 1714 case 1: 1715 *diag = 1.0/(*diag); 1716 break; 1717 case 2: 1718 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1719 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1720 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 1721 break; 1722 case 3: 1723 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1724 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1725 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 1726 break; 1727 case 4: 1728 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1729 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1730 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 1731 break; 1732 case 5: 1733 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1734 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1735 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 1736 break; 1737 case 6: 1738 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1739 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1740 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 1741 break; 1742 case 7: 1743 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1744 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1745 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 1746 break; 1747 default: 1748 ierr = PetscKernel_A_gets_inverse_A(bsizes[i],diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1749 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1750 ierr = PetscKernel_A_gets_transpose_A_N(diag,bsizes[i]);CHKERRQ(ierr); 1751 } 1752 ncnt += bsizes[i]; 1753 diag += bsizes[i]*bsizes[i]; 1754 } 1755 if (bsizemax > 7) { 1756 ierr = PetscFree2(v_work,v_pivots);CHKERRQ(ierr); 1757 } 1758 ierr = PetscFree(indx);CHKERRQ(ierr); 1759 PetscFunctionReturn(0); 1760 } 1761 1762 /* 1763 Negative shift indicates do not generate an error if there is a zero diagonal, just invert it anyways 1764 */ 1765 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1766 { 1767 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1768 PetscErrorCode ierr; 1769 PetscInt i,*diag,m = A->rmap->n; 1770 MatScalar *v = a->a; 1771 PetscScalar *idiag,*mdiag; 1772 1773 PetscFunctionBegin; 1774 if (a->idiagvalid) PetscFunctionReturn(0); 1775 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1776 diag = a->diag; 1777 if (!a->idiag) { 1778 ierr = PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);CHKERRQ(ierr); 1779 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1780 v = a->a; 1781 } 1782 mdiag = a->mdiag; 1783 idiag = a->idiag; 1784 1785 if (omega == 1.0 && PetscRealPart(fshift) <= 0.0) { 1786 for (i=0; i<m; i++) { 1787 mdiag[i] = v[diag[i]]; 1788 if (!PetscAbsScalar(mdiag[i])) { /* zero diagonal */ 1789 if (PetscRealPart(fshift)) { 1790 ierr = PetscInfo1(A,"Zero diagonal on row %D\n",i);CHKERRQ(ierr); 1791 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1792 A->factorerror_zeropivot_value = 0.0; 1793 A->factorerror_zeropivot_row = i; 1794 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1795 } 1796 idiag[i] = 1.0/v[diag[i]]; 1797 } 1798 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1799 } else { 1800 for (i=0; i<m; i++) { 1801 mdiag[i] = v[diag[i]]; 1802 idiag[i] = omega/(fshift + v[diag[i]]); 1803 } 1804 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1805 } 1806 a->idiagvalid = PETSC_TRUE; 1807 PetscFunctionReturn(0); 1808 } 1809 1810 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1811 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1812 { 1813 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1814 PetscScalar *x,d,sum,*t,scale; 1815 const MatScalar *v,*idiag=0,*mdiag; 1816 const PetscScalar *b, *bs,*xb, *ts; 1817 PetscErrorCode ierr; 1818 PetscInt n,m = A->rmap->n,i; 1819 const PetscInt *idx,*diag; 1820 1821 PetscFunctionBegin; 1822 its = its*lits; 1823 1824 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1825 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1826 a->fshift = fshift; 1827 a->omega = omega; 1828 1829 diag = a->diag; 1830 t = a->ssor_work; 1831 idiag = a->idiag; 1832 mdiag = a->mdiag; 1833 1834 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1835 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1836 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1837 if (flag == SOR_APPLY_UPPER) { 1838 /* apply (U + D/omega) to the vector */ 1839 bs = b; 1840 for (i=0; i<m; i++) { 1841 d = fshift + mdiag[i]; 1842 n = a->i[i+1] - diag[i] - 1; 1843 idx = a->j + diag[i] + 1; 1844 v = a->a + diag[i] + 1; 1845 sum = b[i]*d/omega; 1846 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1847 x[i] = sum; 1848 } 1849 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1850 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1851 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1852 PetscFunctionReturn(0); 1853 } 1854 1855 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1856 else if (flag & SOR_EISENSTAT) { 1857 /* Let A = L + U + D; where L is lower triangular, 1858 U is upper triangular, E = D/omega; This routine applies 1859 1860 (L + E)^{-1} A (U + E)^{-1} 1861 1862 to a vector efficiently using Eisenstat's trick. 1863 */ 1864 scale = (2.0/omega) - 1.0; 1865 1866 /* x = (E + U)^{-1} b */ 1867 for (i=m-1; i>=0; i--) { 1868 n = a->i[i+1] - diag[i] - 1; 1869 idx = a->j + diag[i] + 1; 1870 v = a->a + diag[i] + 1; 1871 sum = b[i]; 1872 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1873 x[i] = sum*idiag[i]; 1874 } 1875 1876 /* t = b - (2*E - D)x */ 1877 v = a->a; 1878 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1879 1880 /* t = (E + L)^{-1}t */ 1881 ts = t; 1882 diag = a->diag; 1883 for (i=0; i<m; i++) { 1884 n = diag[i] - a->i[i]; 1885 idx = a->j + a->i[i]; 1886 v = a->a + a->i[i]; 1887 sum = t[i]; 1888 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1889 t[i] = sum*idiag[i]; 1890 /* x = x + t */ 1891 x[i] += t[i]; 1892 } 1893 1894 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1895 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1896 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1897 PetscFunctionReturn(0); 1898 } 1899 if (flag & SOR_ZERO_INITIAL_GUESS) { 1900 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1901 for (i=0; i<m; i++) { 1902 n = diag[i] - a->i[i]; 1903 idx = a->j + a->i[i]; 1904 v = a->a + a->i[i]; 1905 sum = b[i]; 1906 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1907 t[i] = sum; 1908 x[i] = sum*idiag[i]; 1909 } 1910 xb = t; 1911 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1912 } else xb = b; 1913 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1914 for (i=m-1; i>=0; i--) { 1915 n = a->i[i+1] - diag[i] - 1; 1916 idx = a->j + diag[i] + 1; 1917 v = a->a + diag[i] + 1; 1918 sum = xb[i]; 1919 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1920 if (xb == b) { 1921 x[i] = sum*idiag[i]; 1922 } else { 1923 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1924 } 1925 } 1926 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1927 } 1928 its--; 1929 } 1930 while (its--) { 1931 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1932 for (i=0; i<m; i++) { 1933 /* lower */ 1934 n = diag[i] - a->i[i]; 1935 idx = a->j + a->i[i]; 1936 v = a->a + a->i[i]; 1937 sum = b[i]; 1938 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1939 t[i] = sum; /* save application of the lower-triangular part */ 1940 /* upper */ 1941 n = a->i[i+1] - diag[i] - 1; 1942 idx = a->j + diag[i] + 1; 1943 v = a->a + diag[i] + 1; 1944 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1945 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1946 } 1947 xb = t; 1948 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1949 } else xb = b; 1950 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1951 for (i=m-1; i>=0; i--) { 1952 sum = xb[i]; 1953 if (xb == b) { 1954 /* whole matrix (no checkpointing available) */ 1955 n = a->i[i+1] - a->i[i]; 1956 idx = a->j + a->i[i]; 1957 v = a->a + a->i[i]; 1958 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1959 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1960 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1961 n = a->i[i+1] - diag[i] - 1; 1962 idx = a->j + diag[i] + 1; 1963 v = a->a + diag[i] + 1; 1964 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1965 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1966 } 1967 } 1968 if (xb == b) { 1969 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1970 } else { 1971 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1972 } 1973 } 1974 } 1975 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1976 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1977 PetscFunctionReturn(0); 1978 } 1979 1980 1981 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1982 { 1983 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1984 1985 PetscFunctionBegin; 1986 info->block_size = 1.0; 1987 info->nz_allocated = (double)a->maxnz; 1988 info->nz_used = (double)a->nz; 1989 info->nz_unneeded = (double)(a->maxnz - a->nz); 1990 info->assemblies = (double)A->num_ass; 1991 info->mallocs = (double)A->info.mallocs; 1992 info->memory = ((PetscObject)A)->mem; 1993 if (A->factortype) { 1994 info->fill_ratio_given = A->info.fill_ratio_given; 1995 info->fill_ratio_needed = A->info.fill_ratio_needed; 1996 info->factor_mallocs = A->info.factor_mallocs; 1997 } else { 1998 info->fill_ratio_given = 0; 1999 info->fill_ratio_needed = 0; 2000 info->factor_mallocs = 0; 2001 } 2002 PetscFunctionReturn(0); 2003 } 2004 2005 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 2006 { 2007 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2008 PetscInt i,m = A->rmap->n - 1; 2009 PetscErrorCode ierr; 2010 const PetscScalar *xx; 2011 PetscScalar *bb; 2012 PetscInt d = 0; 2013 2014 PetscFunctionBegin; 2015 if (x && b) { 2016 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 2017 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 2018 for (i=0; i<N; i++) { 2019 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2020 if (rows[i] >= A->cmap->n) continue; 2021 bb[rows[i]] = diag*xx[rows[i]]; 2022 } 2023 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2024 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2025 } 2026 2027 if (a->keepnonzeropattern) { 2028 for (i=0; i<N; i++) { 2029 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2030 ierr = PetscArrayzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]);CHKERRQ(ierr); 2031 } 2032 if (diag != 0.0) { 2033 for (i=0; i<N; i++) { 2034 d = rows[i]; 2035 if (rows[i] >= A->cmap->n) continue; 2036 if (a->diag[d] >= a->i[d+1]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in the zeroed row %D",d); 2037 } 2038 for (i=0; i<N; i++) { 2039 if (rows[i] >= A->cmap->n) continue; 2040 a->a[a->diag[rows[i]]] = diag; 2041 } 2042 } 2043 } else { 2044 if (diag != 0.0) { 2045 for (i=0; i<N; i++) { 2046 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2047 if (a->ilen[rows[i]] > 0) { 2048 if (rows[i] >= A->cmap->n) { 2049 a->ilen[rows[i]] = 0; 2050 } else { 2051 a->ilen[rows[i]] = 1; 2052 a->a[a->i[rows[i]]] = diag; 2053 a->j[a->i[rows[i]]] = rows[i]; 2054 } 2055 } else if (rows[i] < A->cmap->n) { /* in case row was completely empty */ 2056 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 2057 } 2058 } 2059 } else { 2060 for (i=0; i<N; i++) { 2061 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2062 a->ilen[rows[i]] = 0; 2063 } 2064 } 2065 A->nonzerostate++; 2066 } 2067 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2068 if (A->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) A->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 2069 #endif 2070 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2071 PetscFunctionReturn(0); 2072 } 2073 2074 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 2075 { 2076 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2077 PetscInt i,j,m = A->rmap->n - 1,d = 0; 2078 PetscErrorCode ierr; 2079 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 2080 const PetscScalar *xx; 2081 PetscScalar *bb; 2082 2083 PetscFunctionBegin; 2084 if (x && b) { 2085 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 2086 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 2087 vecs = PETSC_TRUE; 2088 } 2089 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 2090 for (i=0; i<N; i++) { 2091 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2092 ierr = PetscArrayzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]);CHKERRQ(ierr); 2093 2094 zeroed[rows[i]] = PETSC_TRUE; 2095 } 2096 for (i=0; i<A->rmap->n; i++) { 2097 if (!zeroed[i]) { 2098 for (j=a->i[i]; j<a->i[i+1]; j++) { 2099 if (a->j[j] < A->rmap->n && zeroed[a->j[j]]) { 2100 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 2101 a->a[j] = 0.0; 2102 } 2103 } 2104 } else if (vecs && i < A->cmap->N) bb[i] = diag*xx[i]; 2105 } 2106 if (x && b) { 2107 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2108 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2109 } 2110 ierr = PetscFree(zeroed);CHKERRQ(ierr); 2111 if (diag != 0.0) { 2112 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 2113 if (missing) { 2114 for (i=0; i<N; i++) { 2115 if (rows[i] >= A->cmap->N) continue; 2116 if (a->nonew && rows[i] >= d) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D (%D)",d,rows[i]); 2117 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 2118 } 2119 } else { 2120 for (i=0; i<N; i++) { 2121 a->a[a->diag[rows[i]]] = diag; 2122 } 2123 } 2124 } 2125 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2126 if (A->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) A->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 2127 #endif 2128 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2129 PetscFunctionReturn(0); 2130 } 2131 2132 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2133 { 2134 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2135 PetscInt *itmp; 2136 2137 PetscFunctionBegin; 2138 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 2139 2140 *nz = a->i[row+1] - a->i[row]; 2141 if (v) *v = a->a + a->i[row]; 2142 if (idx) { 2143 itmp = a->j + a->i[row]; 2144 if (*nz) *idx = itmp; 2145 else *idx = 0; 2146 } 2147 PetscFunctionReturn(0); 2148 } 2149 2150 /* remove this function? */ 2151 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2152 { 2153 PetscFunctionBegin; 2154 PetscFunctionReturn(0); 2155 } 2156 2157 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 2158 { 2159 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2160 MatScalar *v = a->a; 2161 PetscReal sum = 0.0; 2162 PetscErrorCode ierr; 2163 PetscInt i,j; 2164 2165 PetscFunctionBegin; 2166 if (type == NORM_FROBENIUS) { 2167 #if defined(PETSC_USE_REAL___FP16) 2168 PetscBLASInt one = 1,nz = a->nz; 2169 *nrm = BLASnrm2_(&nz,v,&one); 2170 #else 2171 for (i=0; i<a->nz; i++) { 2172 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2173 } 2174 *nrm = PetscSqrtReal(sum); 2175 #endif 2176 ierr = PetscLogFlops(2*a->nz);CHKERRQ(ierr); 2177 } else if (type == NORM_1) { 2178 PetscReal *tmp; 2179 PetscInt *jj = a->j; 2180 ierr = PetscCalloc1(A->cmap->n+1,&tmp);CHKERRQ(ierr); 2181 *nrm = 0.0; 2182 for (j=0; j<a->nz; j++) { 2183 tmp[*jj++] += PetscAbsScalar(*v); v++; 2184 } 2185 for (j=0; j<A->cmap->n; j++) { 2186 if (tmp[j] > *nrm) *nrm = tmp[j]; 2187 } 2188 ierr = PetscFree(tmp);CHKERRQ(ierr); 2189 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 2190 } else if (type == NORM_INFINITY) { 2191 *nrm = 0.0; 2192 for (j=0; j<A->rmap->n; j++) { 2193 v = a->a + a->i[j]; 2194 sum = 0.0; 2195 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 2196 sum += PetscAbsScalar(*v); v++; 2197 } 2198 if (sum > *nrm) *nrm = sum; 2199 } 2200 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 2201 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 2202 PetscFunctionReturn(0); 2203 } 2204 2205 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 2206 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 2207 { 2208 PetscErrorCode ierr; 2209 PetscInt i,j,anzj; 2210 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 2211 PetscInt an=A->cmap->N,am=A->rmap->N; 2212 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 2213 2214 PetscFunctionBegin; 2215 /* Allocate space for symbolic transpose info and work array */ 2216 ierr = PetscCalloc1(an+1,&ati);CHKERRQ(ierr); 2217 ierr = PetscMalloc1(ai[am],&atj);CHKERRQ(ierr); 2218 ierr = PetscMalloc1(an,&atfill);CHKERRQ(ierr); 2219 2220 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 2221 /* Note: offset by 1 for fast conversion into csr format. */ 2222 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2223 /* Form ati for csr format of A^T. */ 2224 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2225 2226 /* Copy ati into atfill so we have locations of the next free space in atj */ 2227 ierr = PetscArraycpy(atfill,ati,an);CHKERRQ(ierr); 2228 2229 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2230 for (i=0;i<am;i++) { 2231 anzj = ai[i+1] - ai[i]; 2232 for (j=0;j<anzj;j++) { 2233 atj[atfill[*aj]] = i; 2234 atfill[*aj++] += 1; 2235 } 2236 } 2237 2238 /* Clean up temporary space and complete requests. */ 2239 ierr = PetscFree(atfill);CHKERRQ(ierr); 2240 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2241 ierr = MatSetBlockSizes(*B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2242 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2243 2244 b = (Mat_SeqAIJ*)((*B)->data); 2245 b->free_a = PETSC_FALSE; 2246 b->free_ij = PETSC_TRUE; 2247 b->nonew = 0; 2248 PetscFunctionReturn(0); 2249 } 2250 2251 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2252 { 2253 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2254 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2255 MatScalar *va,*vb; 2256 PetscErrorCode ierr; 2257 PetscInt ma,na,mb,nb, i; 2258 2259 PetscFunctionBegin; 2260 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2261 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2262 if (ma!=nb || na!=mb) { 2263 *f = PETSC_FALSE; 2264 PetscFunctionReturn(0); 2265 } 2266 aii = aij->i; bii = bij->i; 2267 adx = aij->j; bdx = bij->j; 2268 va = aij->a; vb = bij->a; 2269 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2270 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2271 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2272 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2273 2274 *f = PETSC_TRUE; 2275 for (i=0; i<ma; i++) { 2276 while (aptr[i]<aii[i+1]) { 2277 PetscInt idc,idr; 2278 PetscScalar vc,vr; 2279 /* column/row index/value */ 2280 idc = adx[aptr[i]]; 2281 idr = bdx[bptr[idc]]; 2282 vc = va[aptr[i]]; 2283 vr = vb[bptr[idc]]; 2284 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2285 *f = PETSC_FALSE; 2286 goto done; 2287 } else { 2288 aptr[i]++; 2289 if (B || i!=idc) bptr[idc]++; 2290 } 2291 } 2292 } 2293 done: 2294 ierr = PetscFree(aptr);CHKERRQ(ierr); 2295 ierr = PetscFree(bptr);CHKERRQ(ierr); 2296 PetscFunctionReturn(0); 2297 } 2298 2299 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2300 { 2301 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2302 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2303 MatScalar *va,*vb; 2304 PetscErrorCode ierr; 2305 PetscInt ma,na,mb,nb, i; 2306 2307 PetscFunctionBegin; 2308 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2309 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2310 if (ma!=nb || na!=mb) { 2311 *f = PETSC_FALSE; 2312 PetscFunctionReturn(0); 2313 } 2314 aii = aij->i; bii = bij->i; 2315 adx = aij->j; bdx = bij->j; 2316 va = aij->a; vb = bij->a; 2317 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2318 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2319 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2320 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2321 2322 *f = PETSC_TRUE; 2323 for (i=0; i<ma; i++) { 2324 while (aptr[i]<aii[i+1]) { 2325 PetscInt idc,idr; 2326 PetscScalar vc,vr; 2327 /* column/row index/value */ 2328 idc = adx[aptr[i]]; 2329 idr = bdx[bptr[idc]]; 2330 vc = va[aptr[i]]; 2331 vr = vb[bptr[idc]]; 2332 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2333 *f = PETSC_FALSE; 2334 goto done; 2335 } else { 2336 aptr[i]++; 2337 if (B || i!=idc) bptr[idc]++; 2338 } 2339 } 2340 } 2341 done: 2342 ierr = PetscFree(aptr);CHKERRQ(ierr); 2343 ierr = PetscFree(bptr);CHKERRQ(ierr); 2344 PetscFunctionReturn(0); 2345 } 2346 2347 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2348 { 2349 PetscErrorCode ierr; 2350 2351 PetscFunctionBegin; 2352 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2353 PetscFunctionReturn(0); 2354 } 2355 2356 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2357 { 2358 PetscErrorCode ierr; 2359 2360 PetscFunctionBegin; 2361 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2362 PetscFunctionReturn(0); 2363 } 2364 2365 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2366 { 2367 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2368 const PetscScalar *l,*r; 2369 PetscScalar x; 2370 MatScalar *v; 2371 PetscErrorCode ierr; 2372 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz; 2373 const PetscInt *jj; 2374 2375 PetscFunctionBegin; 2376 if (ll) { 2377 /* The local size is used so that VecMPI can be passed to this routine 2378 by MatDiagonalScale_MPIAIJ */ 2379 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2380 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2381 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 2382 v = a->a; 2383 for (i=0; i<m; i++) { 2384 x = l[i]; 2385 M = a->i[i+1] - a->i[i]; 2386 for (j=0; j<M; j++) (*v++) *= x; 2387 } 2388 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 2389 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2390 } 2391 if (rr) { 2392 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2393 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2394 ierr = VecGetArrayRead(rr,&r);CHKERRQ(ierr); 2395 v = a->a; jj = a->j; 2396 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2397 ierr = VecRestoreArrayRead(rr,&r);CHKERRQ(ierr); 2398 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2399 } 2400 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2401 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2402 if (A->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) A->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 2403 #endif 2404 PetscFunctionReturn(0); 2405 } 2406 2407 PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2408 { 2409 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2410 PetscErrorCode ierr; 2411 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2412 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2413 const PetscInt *irow,*icol; 2414 PetscInt nrows,ncols; 2415 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2416 MatScalar *a_new,*mat_a; 2417 Mat C; 2418 PetscBool stride; 2419 2420 PetscFunctionBegin; 2421 2422 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2423 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2424 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2425 2426 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2427 if (stride) { 2428 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2429 } else { 2430 first = 0; 2431 step = 0; 2432 } 2433 if (stride && step == 1) { 2434 /* special case of contiguous rows */ 2435 ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); 2436 /* loop over new rows determining lens and starting points */ 2437 for (i=0; i<nrows; i++) { 2438 kstart = ai[irow[i]]; 2439 kend = kstart + ailen[irow[i]]; 2440 starts[i] = kstart; 2441 for (k=kstart; k<kend; k++) { 2442 if (aj[k] >= first) { 2443 starts[i] = k; 2444 break; 2445 } 2446 } 2447 sum = 0; 2448 while (k < kend) { 2449 if (aj[k++] >= first+ncols) break; 2450 sum++; 2451 } 2452 lens[i] = sum; 2453 } 2454 /* create submatrix */ 2455 if (scall == MAT_REUSE_MATRIX) { 2456 PetscInt n_cols,n_rows; 2457 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2458 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2459 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2460 C = *B; 2461 } else { 2462 PetscInt rbs,cbs; 2463 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2464 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2465 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2466 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2467 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2468 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2469 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2470 } 2471 c = (Mat_SeqAIJ*)C->data; 2472 2473 /* loop over rows inserting into submatrix */ 2474 a_new = c->a; 2475 j_new = c->j; 2476 i_new = c->i; 2477 2478 for (i=0; i<nrows; i++) { 2479 ii = starts[i]; 2480 lensi = lens[i]; 2481 for (k=0; k<lensi; k++) { 2482 *j_new++ = aj[ii+k] - first; 2483 } 2484 ierr = PetscArraycpy(a_new,a->a + starts[i],lensi);CHKERRQ(ierr); 2485 a_new += lensi; 2486 i_new[i+1] = i_new[i] + lensi; 2487 c->ilen[i] = lensi; 2488 } 2489 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2490 } else { 2491 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2492 ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); 2493 ierr = PetscMalloc1(1+nrows,&lens);CHKERRQ(ierr); 2494 for (i=0; i<ncols; i++) { 2495 #if defined(PETSC_USE_DEBUG) 2496 if (icol[i] >= oldcols) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Requesting column beyond largest column icol[%D] %D <= A->cmap->n %D",i,icol[i],oldcols); 2497 #endif 2498 smap[icol[i]] = i+1; 2499 } 2500 2501 /* determine lens of each row */ 2502 for (i=0; i<nrows; i++) { 2503 kstart = ai[irow[i]]; 2504 kend = kstart + a->ilen[irow[i]]; 2505 lens[i] = 0; 2506 for (k=kstart; k<kend; k++) { 2507 if (smap[aj[k]]) { 2508 lens[i]++; 2509 } 2510 } 2511 } 2512 /* Create and fill new matrix */ 2513 if (scall == MAT_REUSE_MATRIX) { 2514 PetscBool equal; 2515 2516 c = (Mat_SeqAIJ*)((*B)->data); 2517 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2518 ierr = PetscArraycmp(c->ilen,lens,(*B)->rmap->n,&equal);CHKERRQ(ierr); 2519 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2520 ierr = PetscArrayzero(c->ilen,(*B)->rmap->n);CHKERRQ(ierr); 2521 C = *B; 2522 } else { 2523 PetscInt rbs,cbs; 2524 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2525 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2526 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2527 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2528 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2529 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2530 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2531 } 2532 c = (Mat_SeqAIJ*)(C->data); 2533 for (i=0; i<nrows; i++) { 2534 row = irow[i]; 2535 kstart = ai[row]; 2536 kend = kstart + a->ilen[row]; 2537 mat_i = c->i[i]; 2538 mat_j = c->j + mat_i; 2539 mat_a = c->a + mat_i; 2540 mat_ilen = c->ilen + i; 2541 for (k=kstart; k<kend; k++) { 2542 if ((tcol=smap[a->j[k]])) { 2543 *mat_j++ = tcol - 1; 2544 *mat_a++ = a->a[k]; 2545 (*mat_ilen)++; 2546 2547 } 2548 } 2549 } 2550 /* Free work space */ 2551 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2552 ierr = PetscFree(smap);CHKERRQ(ierr); 2553 ierr = PetscFree(lens);CHKERRQ(ierr); 2554 /* sort */ 2555 for (i = 0; i < nrows; i++) { 2556 PetscInt ilen; 2557 2558 mat_i = c->i[i]; 2559 mat_j = c->j + mat_i; 2560 mat_a = c->a + mat_i; 2561 ilen = c->ilen[i]; 2562 ierr = PetscSortIntWithScalarArray(ilen,mat_j,mat_a);CHKERRQ(ierr); 2563 } 2564 } 2565 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2566 ierr = MatPinToCPU(C,A->pinnedtocpu);CHKERRQ(ierr); 2567 #endif 2568 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2569 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2570 2571 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2572 *B = C; 2573 PetscFunctionReturn(0); 2574 } 2575 2576 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2577 { 2578 PetscErrorCode ierr; 2579 Mat B; 2580 2581 PetscFunctionBegin; 2582 if (scall == MAT_INITIAL_MATRIX) { 2583 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2584 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2585 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2586 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2587 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2588 *subMat = B; 2589 } else { 2590 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2591 } 2592 PetscFunctionReturn(0); 2593 } 2594 2595 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2596 { 2597 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2598 PetscErrorCode ierr; 2599 Mat outA; 2600 PetscBool row_identity,col_identity; 2601 2602 PetscFunctionBegin; 2603 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2604 2605 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2606 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2607 2608 outA = inA; 2609 outA->factortype = MAT_FACTOR_LU; 2610 ierr = PetscFree(inA->solvertype);CHKERRQ(ierr); 2611 ierr = PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);CHKERRQ(ierr); 2612 2613 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2614 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2615 2616 a->row = row; 2617 2618 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2619 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2620 2621 a->col = col; 2622 2623 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2624 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2625 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2626 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2627 2628 if (!a->solve_work) { /* this matrix may have been factored before */ 2629 ierr = PetscMalloc1(inA->rmap->n+1,&a->solve_work);CHKERRQ(ierr); 2630 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2631 } 2632 2633 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2634 if (row_identity && col_identity) { 2635 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2636 } else { 2637 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2638 } 2639 PetscFunctionReturn(0); 2640 } 2641 2642 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2643 { 2644 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2645 PetscScalar oalpha = alpha; 2646 PetscErrorCode ierr; 2647 PetscBLASInt one = 1,bnz; 2648 2649 PetscFunctionBegin; 2650 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2651 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2652 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2653 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2654 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2655 if (inA->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) inA->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 2656 #endif 2657 PetscFunctionReturn(0); 2658 } 2659 2660 PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt *submatj) 2661 { 2662 PetscErrorCode ierr; 2663 PetscInt i; 2664 2665 PetscFunctionBegin; 2666 if (!submatj->id) { /* delete data that are linked only to submats[id=0] */ 2667 ierr = PetscFree4(submatj->sbuf1,submatj->ptr,submatj->tmp,submatj->ctr);CHKERRQ(ierr); 2668 2669 for (i=0; i<submatj->nrqr; ++i) { 2670 ierr = PetscFree(submatj->sbuf2[i]);CHKERRQ(ierr); 2671 } 2672 ierr = PetscFree3(submatj->sbuf2,submatj->req_size,submatj->req_source1);CHKERRQ(ierr); 2673 2674 if (submatj->rbuf1) { 2675 ierr = PetscFree(submatj->rbuf1[0]);CHKERRQ(ierr); 2676 ierr = PetscFree(submatj->rbuf1);CHKERRQ(ierr); 2677 } 2678 2679 for (i=0; i<submatj->nrqs; ++i) { 2680 ierr = PetscFree(submatj->rbuf3[i]);CHKERRQ(ierr); 2681 } 2682 ierr = PetscFree3(submatj->req_source2,submatj->rbuf2,submatj->rbuf3);CHKERRQ(ierr); 2683 ierr = PetscFree(submatj->pa);CHKERRQ(ierr); 2684 } 2685 2686 #if defined(PETSC_USE_CTABLE) 2687 ierr = PetscTableDestroy((PetscTable*)&submatj->rmap);CHKERRQ(ierr); 2688 if (submatj->cmap_loc) {ierr = PetscFree(submatj->cmap_loc);CHKERRQ(ierr);} 2689 ierr = PetscFree(submatj->rmap_loc);CHKERRQ(ierr); 2690 #else 2691 ierr = PetscFree(submatj->rmap);CHKERRQ(ierr); 2692 #endif 2693 2694 if (!submatj->allcolumns) { 2695 #if defined(PETSC_USE_CTABLE) 2696 ierr = PetscTableDestroy((PetscTable*)&submatj->cmap);CHKERRQ(ierr); 2697 #else 2698 ierr = PetscFree(submatj->cmap);CHKERRQ(ierr); 2699 #endif 2700 } 2701 ierr = PetscFree(submatj->row2proc);CHKERRQ(ierr); 2702 2703 ierr = PetscFree(submatj);CHKERRQ(ierr); 2704 PetscFunctionReturn(0); 2705 } 2706 2707 PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat C) 2708 { 2709 PetscErrorCode ierr; 2710 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2711 Mat_SubSppt *submatj = c->submatis1; 2712 2713 PetscFunctionBegin; 2714 ierr = (*submatj->destroy)(C);CHKERRQ(ierr); 2715 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2716 PetscFunctionReturn(0); 2717 } 2718 2719 PetscErrorCode MatDestroySubMatrices_SeqAIJ(PetscInt n,Mat *mat[]) 2720 { 2721 PetscErrorCode ierr; 2722 PetscInt i; 2723 Mat C; 2724 Mat_SeqAIJ *c; 2725 Mat_SubSppt *submatj; 2726 2727 PetscFunctionBegin; 2728 for (i=0; i<n; i++) { 2729 C = (*mat)[i]; 2730 c = (Mat_SeqAIJ*)C->data; 2731 submatj = c->submatis1; 2732 if (submatj) { 2733 if (--((PetscObject)C)->refct <= 0) { 2734 ierr = (*submatj->destroy)(C);CHKERRQ(ierr); 2735 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2736 ierr = PetscFree(C->defaultvectype);CHKERRQ(ierr); 2737 ierr = PetscLayoutDestroy(&C->rmap);CHKERRQ(ierr); 2738 ierr = PetscLayoutDestroy(&C->cmap);CHKERRQ(ierr); 2739 ierr = PetscHeaderDestroy(&C);CHKERRQ(ierr); 2740 } 2741 } else { 2742 ierr = MatDestroy(&C);CHKERRQ(ierr); 2743 } 2744 } 2745 2746 /* Destroy Dummy submatrices created for reuse */ 2747 ierr = MatDestroySubMatrices_Dummy(n,mat);CHKERRQ(ierr); 2748 2749 ierr = PetscFree(*mat);CHKERRQ(ierr); 2750 PetscFunctionReturn(0); 2751 } 2752 2753 PetscErrorCode MatCreateSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2754 { 2755 PetscErrorCode ierr; 2756 PetscInt i; 2757 2758 PetscFunctionBegin; 2759 if (scall == MAT_INITIAL_MATRIX) { 2760 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 2761 } 2762 2763 for (i=0; i<n; i++) { 2764 ierr = MatCreateSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2765 } 2766 PetscFunctionReturn(0); 2767 } 2768 2769 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2770 { 2771 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2772 PetscErrorCode ierr; 2773 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2774 const PetscInt *idx; 2775 PetscInt start,end,*ai,*aj; 2776 PetscBT table; 2777 2778 PetscFunctionBegin; 2779 m = A->rmap->n; 2780 ai = a->i; 2781 aj = a->j; 2782 2783 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2784 2785 ierr = PetscMalloc1(m+1,&nidx);CHKERRQ(ierr); 2786 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2787 2788 for (i=0; i<is_max; i++) { 2789 /* Initialize the two local arrays */ 2790 isz = 0; 2791 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2792 2793 /* Extract the indices, assume there can be duplicate entries */ 2794 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2795 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2796 2797 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2798 for (j=0; j<n; ++j) { 2799 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2800 } 2801 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2802 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2803 2804 k = 0; 2805 for (j=0; j<ov; j++) { /* for each overlap */ 2806 n = isz; 2807 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2808 row = nidx[k]; 2809 start = ai[row]; 2810 end = ai[row+1]; 2811 for (l = start; l<end; l++) { 2812 val = aj[l]; 2813 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2814 } 2815 } 2816 } 2817 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2818 } 2819 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2820 ierr = PetscFree(nidx);CHKERRQ(ierr); 2821 PetscFunctionReturn(0); 2822 } 2823 2824 /* -------------------------------------------------------------- */ 2825 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2826 { 2827 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2828 PetscErrorCode ierr; 2829 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2830 const PetscInt *row,*col; 2831 PetscInt *cnew,j,*lens; 2832 IS icolp,irowp; 2833 PetscInt *cwork = NULL; 2834 PetscScalar *vwork = NULL; 2835 2836 PetscFunctionBegin; 2837 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2838 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2839 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2840 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2841 2842 /* determine lengths of permuted rows */ 2843 ierr = PetscMalloc1(m+1,&lens);CHKERRQ(ierr); 2844 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2845 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2846 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2847 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2848 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2849 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2850 ierr = PetscFree(lens);CHKERRQ(ierr); 2851 2852 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2853 for (i=0; i<m; i++) { 2854 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2855 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2856 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2857 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2858 } 2859 ierr = PetscFree(cnew);CHKERRQ(ierr); 2860 2861 (*B)->assembled = PETSC_FALSE; 2862 2863 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2864 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2865 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2866 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2867 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2868 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2869 PetscFunctionReturn(0); 2870 } 2871 2872 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2873 { 2874 PetscErrorCode ierr; 2875 2876 PetscFunctionBegin; 2877 /* If the two matrices have the same copy implementation, use fast copy. */ 2878 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2879 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2880 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2881 2882 if (a->i[A->rmap->n] != b->i[B->rmap->n]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzeros in two matrices are different"); 2883 ierr = PetscArraycpy(b->a,a->a,a->i[A->rmap->n]);CHKERRQ(ierr); 2884 ierr = PetscObjectStateIncrease((PetscObject)B);CHKERRQ(ierr); 2885 } else { 2886 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2887 } 2888 PetscFunctionReturn(0); 2889 } 2890 2891 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2892 { 2893 PetscErrorCode ierr; 2894 2895 PetscFunctionBegin; 2896 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2897 PetscFunctionReturn(0); 2898 } 2899 2900 PETSC_INTERN PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2901 { 2902 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2903 2904 PetscFunctionBegin; 2905 *array = a->a; 2906 PetscFunctionReturn(0); 2907 } 2908 2909 PETSC_INTERN PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2910 { 2911 PetscFunctionBegin; 2912 *array = NULL; 2913 PetscFunctionReturn(0); 2914 } 2915 2916 /* 2917 Computes the number of nonzeros per row needed for preallocation when X and Y 2918 have different nonzero structure. 2919 */ 2920 PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *yi,const PetscInt *yj,PetscInt *nnz) 2921 { 2922 PetscInt i,j,k,nzx,nzy; 2923 2924 PetscFunctionBegin; 2925 /* Set the number of nonzeros in the new matrix */ 2926 for (i=0; i<m; i++) { 2927 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2928 nzx = xi[i+1] - xi[i]; 2929 nzy = yi[i+1] - yi[i]; 2930 nnz[i] = 0; 2931 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2932 for (; k<nzy && yjj[k]<xjj[j]; k++) nnz[i]++; /* Catch up to X */ 2933 if (k<nzy && yjj[k]==xjj[j]) k++; /* Skip duplicate */ 2934 nnz[i]++; 2935 } 2936 for (; k<nzy; k++) nnz[i]++; 2937 } 2938 PetscFunctionReturn(0); 2939 } 2940 2941 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2942 { 2943 PetscInt m = Y->rmap->N; 2944 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2945 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2946 PetscErrorCode ierr; 2947 2948 PetscFunctionBegin; 2949 /* Set the number of nonzeros in the new matrix */ 2950 ierr = MatAXPYGetPreallocation_SeqX_private(m,x->i,x->j,y->i,y->j,nnz);CHKERRQ(ierr); 2951 PetscFunctionReturn(0); 2952 } 2953 2954 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2955 { 2956 PetscErrorCode ierr; 2957 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 2958 PetscBLASInt one=1,bnz; 2959 2960 PetscFunctionBegin; 2961 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2962 if (str == SAME_NONZERO_PATTERN) { 2963 PetscScalar alpha = a; 2964 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2965 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 2966 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2967 /* the MatAXPY_Basic* subroutines calls MatAssembly, so the matrix on the GPU 2968 will be updated */ 2969 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2970 if (Y->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) { 2971 Y->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 2972 } 2973 #endif 2974 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2975 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2976 } else { 2977 Mat B; 2978 PetscInt *nnz; 2979 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2980 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2981 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2982 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2983 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2984 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2985 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 2986 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 2987 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2988 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2989 ierr = PetscFree(nnz);CHKERRQ(ierr); 2990 } 2991 PetscFunctionReturn(0); 2992 } 2993 2994 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 2995 { 2996 #if defined(PETSC_USE_COMPLEX) 2997 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 2998 PetscInt i,nz; 2999 PetscScalar *a; 3000 3001 PetscFunctionBegin; 3002 nz = aij->nz; 3003 a = aij->a; 3004 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 3005 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 3006 if (mat->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) mat->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 3007 #endif 3008 #else 3009 PetscFunctionBegin; 3010 #endif 3011 PetscFunctionReturn(0); 3012 } 3013 3014 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3015 { 3016 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3017 PetscErrorCode ierr; 3018 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3019 PetscReal atmp; 3020 PetscScalar *x; 3021 MatScalar *aa; 3022 3023 PetscFunctionBegin; 3024 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3025 aa = a->a; 3026 ai = a->i; 3027 aj = a->j; 3028 3029 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3030 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3031 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3032 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3033 for (i=0; i<m; i++) { 3034 ncols = ai[1] - ai[0]; ai++; 3035 x[i] = 0.0; 3036 for (j=0; j<ncols; j++) { 3037 atmp = PetscAbsScalar(*aa); 3038 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3039 aa++; aj++; 3040 } 3041 } 3042 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3043 PetscFunctionReturn(0); 3044 } 3045 3046 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3047 { 3048 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3049 PetscErrorCode ierr; 3050 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3051 PetscScalar *x; 3052 MatScalar *aa; 3053 3054 PetscFunctionBegin; 3055 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3056 aa = a->a; 3057 ai = a->i; 3058 aj = a->j; 3059 3060 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3061 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3062 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3063 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3064 for (i=0; i<m; i++) { 3065 ncols = ai[1] - ai[0]; ai++; 3066 if (ncols == A->cmap->n) { /* row is dense */ 3067 x[i] = *aa; if (idx) idx[i] = 0; 3068 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 3069 x[i] = 0.0; 3070 if (idx) { 3071 idx[i] = 0; /* in case ncols is zero */ 3072 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 3073 if (aj[j] > j) { 3074 idx[i] = j; 3075 break; 3076 } 3077 } 3078 } 3079 } 3080 for (j=0; j<ncols; j++) { 3081 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3082 aa++; aj++; 3083 } 3084 } 3085 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3086 PetscFunctionReturn(0); 3087 } 3088 3089 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3090 { 3091 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3092 PetscErrorCode ierr; 3093 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3094 PetscReal atmp; 3095 PetscScalar *x; 3096 MatScalar *aa; 3097 3098 PetscFunctionBegin; 3099 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3100 aa = a->a; 3101 ai = a->i; 3102 aj = a->j; 3103 3104 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3105 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3106 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3107 if (n != A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector, %D vs. %D rows", A->rmap->n, n); 3108 for (i=0; i<m; i++) { 3109 ncols = ai[1] - ai[0]; ai++; 3110 if (ncols) { 3111 /* Get first nonzero */ 3112 for (j = 0; j < ncols; j++) { 3113 atmp = PetscAbsScalar(aa[j]); 3114 if (atmp > 1.0e-12) { 3115 x[i] = atmp; 3116 if (idx) idx[i] = aj[j]; 3117 break; 3118 } 3119 } 3120 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 3121 } else { 3122 x[i] = 0.0; if (idx) idx[i] = 0; 3123 } 3124 for (j = 0; j < ncols; j++) { 3125 atmp = PetscAbsScalar(*aa); 3126 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3127 aa++; aj++; 3128 } 3129 } 3130 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3131 PetscFunctionReturn(0); 3132 } 3133 3134 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3135 { 3136 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3137 PetscErrorCode ierr; 3138 PetscInt i,j,m = A->rmap->n,ncols,n; 3139 const PetscInt *ai,*aj; 3140 PetscScalar *x; 3141 const MatScalar *aa; 3142 3143 PetscFunctionBegin; 3144 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3145 aa = a->a; 3146 ai = a->i; 3147 aj = a->j; 3148 3149 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3150 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3151 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3152 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3153 for (i=0; i<m; i++) { 3154 ncols = ai[1] - ai[0]; ai++; 3155 if (ncols == A->cmap->n) { /* row is dense */ 3156 x[i] = *aa; if (idx) idx[i] = 0; 3157 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3158 x[i] = 0.0; 3159 if (idx) { /* find first implicit 0.0 in the row */ 3160 idx[i] = 0; /* in case ncols is zero */ 3161 for (j=0; j<ncols; j++) { 3162 if (aj[j] > j) { 3163 idx[i] = j; 3164 break; 3165 } 3166 } 3167 } 3168 } 3169 for (j=0; j<ncols; j++) { 3170 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3171 aa++; aj++; 3172 } 3173 } 3174 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3175 PetscFunctionReturn(0); 3176 } 3177 3178 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3179 { 3180 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3181 PetscErrorCode ierr; 3182 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3183 MatScalar *diag,work[25],*v_work; 3184 const PetscReal shift = 0.0; 3185 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 3186 3187 PetscFunctionBegin; 3188 allowzeropivot = PetscNot(A->erroriffailure); 3189 if (a->ibdiagvalid) { 3190 if (values) *values = a->ibdiag; 3191 PetscFunctionReturn(0); 3192 } 3193 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3194 if (!a->ibdiag) { 3195 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 3196 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3197 } 3198 diag = a->ibdiag; 3199 if (values) *values = a->ibdiag; 3200 /* factor and invert each block */ 3201 switch (bs) { 3202 case 1: 3203 for (i=0; i<mbs; i++) { 3204 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3205 if (PetscAbsScalar(diag[i] + shift) < PETSC_MACHINE_EPSILON) { 3206 if (allowzeropivot) { 3207 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3208 A->factorerror_zeropivot_value = PetscAbsScalar(diag[i]); 3209 A->factorerror_zeropivot_row = i; 3210 ierr = PetscInfo3(A,"Zero pivot, row %D pivot %g tolerance %g\n",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON);CHKERRQ(ierr); 3211 } else SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot, row %D pivot %g tolerance %g",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON); 3212 } 3213 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3214 } 3215 break; 3216 case 2: 3217 for (i=0; i<mbs; i++) { 3218 ij[0] = 2*i; ij[1] = 2*i + 1; 3219 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3220 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3221 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3222 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3223 diag += 4; 3224 } 3225 break; 3226 case 3: 3227 for (i=0; i<mbs; i++) { 3228 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3229 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3230 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3231 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3232 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3233 diag += 9; 3234 } 3235 break; 3236 case 4: 3237 for (i=0; i<mbs; i++) { 3238 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3239 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3240 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3241 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3242 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3243 diag += 16; 3244 } 3245 break; 3246 case 5: 3247 for (i=0; i<mbs; i++) { 3248 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3249 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3250 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3251 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3252 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3253 diag += 25; 3254 } 3255 break; 3256 case 6: 3257 for (i=0; i<mbs; i++) { 3258 ij[0] = 6*i; ij[1] = 6*i + 1; ij[2] = 6*i + 2; ij[3] = 6*i + 3; ij[4] = 6*i + 4; ij[5] = 6*i + 5; 3259 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3260 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3261 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3262 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3263 diag += 36; 3264 } 3265 break; 3266 case 7: 3267 for (i=0; i<mbs; i++) { 3268 ij[0] = 7*i; ij[1] = 7*i + 1; ij[2] = 7*i + 2; ij[3] = 7*i + 3; ij[4] = 7*i + 4; ij[5] = 7*i + 5; ij[5] = 7*i + 6; 3269 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3270 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3271 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3272 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3273 diag += 49; 3274 } 3275 break; 3276 default: 3277 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3278 for (i=0; i<mbs; i++) { 3279 for (j=0; j<bs; j++) { 3280 IJ[j] = bs*i + j; 3281 } 3282 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3283 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3284 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3285 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3286 diag += bs2; 3287 } 3288 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3289 } 3290 a->ibdiagvalid = PETSC_TRUE; 3291 PetscFunctionReturn(0); 3292 } 3293 3294 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3295 { 3296 PetscErrorCode ierr; 3297 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3298 PetscScalar a; 3299 PetscInt m,n,i,j,col; 3300 3301 PetscFunctionBegin; 3302 if (!x->assembled) { 3303 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3304 for (i=0; i<m; i++) { 3305 for (j=0; j<aij->imax[i]; j++) { 3306 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3307 col = (PetscInt)(n*PetscRealPart(a)); 3308 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3309 } 3310 } 3311 } else { 3312 for (i=0; i<aij->nz; i++) {ierr = PetscRandomGetValue(rctx,aij->a+i);CHKERRQ(ierr);} 3313 } 3314 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3315 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3316 PetscFunctionReturn(0); 3317 } 3318 3319 /* Like MatSetRandom_SeqAIJ, but do not set values on columns in range of [low, high) */ 3320 PetscErrorCode MatSetRandomSkipColumnRange_SeqAIJ_Private(Mat x,PetscInt low,PetscInt high,PetscRandom rctx) 3321 { 3322 PetscErrorCode ierr; 3323 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3324 PetscScalar a; 3325 PetscInt m,n,i,j,col,nskip; 3326 3327 PetscFunctionBegin; 3328 nskip = high - low; 3329 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3330 n -= nskip; /* shrink number of columns where nonzeros can be set */ 3331 for (i=0; i<m; i++) { 3332 for (j=0; j<aij->imax[i]; j++) { 3333 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3334 col = (PetscInt)(n*PetscRealPart(a)); 3335 if (col >= low) col += nskip; /* shift col rightward to skip the hole */ 3336 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3337 } 3338 } 3339 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3340 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3341 PetscFunctionReturn(0); 3342 } 3343 3344 3345 /* -------------------------------------------------------------------*/ 3346 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3347 MatGetRow_SeqAIJ, 3348 MatRestoreRow_SeqAIJ, 3349 MatMult_SeqAIJ, 3350 /* 4*/ MatMultAdd_SeqAIJ, 3351 MatMultTranspose_SeqAIJ, 3352 MatMultTransposeAdd_SeqAIJ, 3353 0, 3354 0, 3355 0, 3356 /* 10*/ 0, 3357 MatLUFactor_SeqAIJ, 3358 0, 3359 MatSOR_SeqAIJ, 3360 MatTranspose_SeqAIJ, 3361 /*1 5*/ MatGetInfo_SeqAIJ, 3362 MatEqual_SeqAIJ, 3363 MatGetDiagonal_SeqAIJ, 3364 MatDiagonalScale_SeqAIJ, 3365 MatNorm_SeqAIJ, 3366 /* 20*/ 0, 3367 MatAssemblyEnd_SeqAIJ, 3368 MatSetOption_SeqAIJ, 3369 MatZeroEntries_SeqAIJ, 3370 /* 24*/ MatZeroRows_SeqAIJ, 3371 0, 3372 0, 3373 0, 3374 0, 3375 /* 29*/ MatSetUp_SeqAIJ, 3376 0, 3377 0, 3378 0, 3379 0, 3380 /* 34*/ MatDuplicate_SeqAIJ, 3381 0, 3382 0, 3383 MatILUFactor_SeqAIJ, 3384 0, 3385 /* 39*/ MatAXPY_SeqAIJ, 3386 MatCreateSubMatrices_SeqAIJ, 3387 MatIncreaseOverlap_SeqAIJ, 3388 MatGetValues_SeqAIJ, 3389 MatCopy_SeqAIJ, 3390 /* 44*/ MatGetRowMax_SeqAIJ, 3391 MatScale_SeqAIJ, 3392 MatShift_SeqAIJ, 3393 MatDiagonalSet_SeqAIJ, 3394 MatZeroRowsColumns_SeqAIJ, 3395 /* 49*/ MatSetRandom_SeqAIJ, 3396 MatGetRowIJ_SeqAIJ, 3397 MatRestoreRowIJ_SeqAIJ, 3398 MatGetColumnIJ_SeqAIJ, 3399 MatRestoreColumnIJ_SeqAIJ, 3400 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3401 0, 3402 0, 3403 MatPermute_SeqAIJ, 3404 0, 3405 /* 59*/ 0, 3406 MatDestroy_SeqAIJ, 3407 MatView_SeqAIJ, 3408 0, 3409 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3410 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3411 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3412 0, 3413 0, 3414 0, 3415 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3416 MatGetRowMinAbs_SeqAIJ, 3417 0, 3418 0, 3419 0, 3420 /* 74*/ 0, 3421 MatFDColoringApply_AIJ, 3422 0, 3423 0, 3424 0, 3425 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3426 0, 3427 0, 3428 0, 3429 MatLoad_SeqAIJ, 3430 /* 84*/ MatIsSymmetric_SeqAIJ, 3431 MatIsHermitian_SeqAIJ, 3432 0, 3433 0, 3434 0, 3435 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3436 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3437 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3438 MatPtAP_SeqAIJ_SeqAIJ, 3439 MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy, 3440 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy, 3441 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3442 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3443 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3444 0, 3445 /* 99*/ 0, 3446 0, 3447 0, 3448 MatConjugate_SeqAIJ, 3449 0, 3450 /*104*/ MatSetValuesRow_SeqAIJ, 3451 MatRealPart_SeqAIJ, 3452 MatImaginaryPart_SeqAIJ, 3453 0, 3454 0, 3455 /*109*/ MatMatSolve_SeqAIJ, 3456 0, 3457 MatGetRowMin_SeqAIJ, 3458 0, 3459 MatMissingDiagonal_SeqAIJ, 3460 /*114*/ 0, 3461 0, 3462 0, 3463 0, 3464 0, 3465 /*119*/ 0, 3466 0, 3467 0, 3468 0, 3469 MatGetMultiProcBlock_SeqAIJ, 3470 /*124*/ MatFindNonzeroRows_SeqAIJ, 3471 MatGetColumnNorms_SeqAIJ, 3472 MatInvertBlockDiagonal_SeqAIJ, 3473 MatInvertVariableBlockDiagonal_SeqAIJ, 3474 0, 3475 /*129*/ 0, 3476 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3477 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3478 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3479 MatTransposeColoringCreate_SeqAIJ, 3480 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3481 MatTransColoringApplyDenToSp_SeqAIJ, 3482 MatRARt_SeqAIJ_SeqAIJ, 3483 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3484 MatRARtNumeric_SeqAIJ_SeqAIJ, 3485 /*139*/0, 3486 0, 3487 0, 3488 MatFDColoringSetUp_SeqXAIJ, 3489 MatFindOffBlockDiagonalEntries_SeqAIJ, 3490 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqAIJ, 3491 MatDestroySubMatrices_SeqAIJ 3492 }; 3493 3494 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3495 { 3496 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3497 PetscInt i,nz,n; 3498 3499 PetscFunctionBegin; 3500 nz = aij->maxnz; 3501 n = mat->rmap->n; 3502 for (i=0; i<nz; i++) { 3503 aij->j[i] = indices[i]; 3504 } 3505 aij->nz = nz; 3506 for (i=0; i<n; i++) { 3507 aij->ilen[i] = aij->imax[i]; 3508 } 3509 PetscFunctionReturn(0); 3510 } 3511 3512 /* 3513 * When a sparse matrix has many zero columns, we should compact them out to save the space 3514 * This happens in MatPtAPSymbolic_MPIAIJ_MPIAIJ_scalable() 3515 * */ 3516 PetscErrorCode MatSeqAIJCompactOutExtraColumns_SeqAIJ(Mat mat, ISLocalToGlobalMapping *mapping) 3517 { 3518 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3519 PetscTable gid1_lid1; 3520 PetscTablePosition tpos; 3521 PetscInt gid,lid,i,j,ncols,ec; 3522 PetscInt *garray; 3523 PetscErrorCode ierr; 3524 3525 PetscFunctionBegin; 3526 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3527 PetscValidPointer(mapping,2); 3528 /* use a table */ 3529 ierr = PetscTableCreate(mat->rmap->n,mat->cmap->N+1,&gid1_lid1);CHKERRQ(ierr); 3530 ec = 0; 3531 for (i=0; i<mat->rmap->n; i++) { 3532 ncols = aij->i[i+1] - aij->i[i]; 3533 for (j=0; j<ncols; j++) { 3534 PetscInt data,gid1 = aij->j[aij->i[i] + j] + 1; 3535 ierr = PetscTableFind(gid1_lid1,gid1,&data);CHKERRQ(ierr); 3536 if (!data) { 3537 /* one based table */ 3538 ierr = PetscTableAdd(gid1_lid1,gid1,++ec,INSERT_VALUES);CHKERRQ(ierr); 3539 } 3540 } 3541 } 3542 /* form array of columns we need */ 3543 ierr = PetscMalloc1(ec+1,&garray);CHKERRQ(ierr); 3544 ierr = PetscTableGetHeadPosition(gid1_lid1,&tpos);CHKERRQ(ierr); 3545 while (tpos) { 3546 ierr = PetscTableGetNext(gid1_lid1,&tpos,&gid,&lid);CHKERRQ(ierr); 3547 gid--; 3548 lid--; 3549 garray[lid] = gid; 3550 } 3551 ierr = PetscSortInt(ec,garray);CHKERRQ(ierr); /* sort, and rebuild */ 3552 ierr = PetscTableRemoveAll(gid1_lid1);CHKERRQ(ierr); 3553 for (i=0; i<ec; i++) { 3554 ierr = PetscTableAdd(gid1_lid1,garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 3555 } 3556 /* compact out the extra columns in B */ 3557 for (i=0; i<mat->rmap->n; i++) { 3558 ncols = aij->i[i+1] - aij->i[i]; 3559 for (j=0; j<ncols; j++) { 3560 PetscInt gid1 = aij->j[aij->i[i] + j] + 1; 3561 ierr = PetscTableFind(gid1_lid1,gid1,&lid);CHKERRQ(ierr); 3562 lid--; 3563 aij->j[aij->i[i] + j] = lid; 3564 } 3565 } 3566 ierr = PetscLayoutDestroy(&mat->cmap);CHKERRQ(ierr); 3567 ierr = PetscLayoutCreateFromSizes(PetscObjectComm((PetscObject)mat),ec,ec,1,&mat->cmap);CHKERRQ(ierr); 3568 ierr = PetscTableDestroy(&gid1_lid1);CHKERRQ(ierr); 3569 ierr = ISLocalToGlobalMappingCreate(PETSC_COMM_SELF,mat->cmap->bs,mat->cmap->n,garray,PETSC_OWN_POINTER,mapping);CHKERRQ(ierr); 3570 ierr = ISLocalToGlobalMappingSetType(*mapping,ISLOCALTOGLOBALMAPPINGHASH);CHKERRQ(ierr); 3571 PetscFunctionReturn(0); 3572 } 3573 3574 /*@ 3575 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3576 in the matrix. 3577 3578 Input Parameters: 3579 + mat - the SeqAIJ matrix 3580 - indices - the column indices 3581 3582 Level: advanced 3583 3584 Notes: 3585 This can be called if you have precomputed the nonzero structure of the 3586 matrix and want to provide it to the matrix object to improve the performance 3587 of the MatSetValues() operation. 3588 3589 You MUST have set the correct numbers of nonzeros per row in the call to 3590 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3591 3592 MUST be called before any calls to MatSetValues(); 3593 3594 The indices should start with zero, not one. 3595 3596 @*/ 3597 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3598 { 3599 PetscErrorCode ierr; 3600 3601 PetscFunctionBegin; 3602 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3603 PetscValidPointer(indices,2); 3604 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3605 PetscFunctionReturn(0); 3606 } 3607 3608 /* ----------------------------------------------------------------------------------------*/ 3609 3610 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3611 { 3612 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3613 PetscErrorCode ierr; 3614 size_t nz = aij->i[mat->rmap->n]; 3615 3616 PetscFunctionBegin; 3617 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3618 3619 /* allocate space for values if not already there */ 3620 if (!aij->saved_values) { 3621 ierr = PetscMalloc1(nz+1,&aij->saved_values);CHKERRQ(ierr); 3622 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3623 } 3624 3625 /* copy values over */ 3626 ierr = PetscArraycpy(aij->saved_values,aij->a,nz);CHKERRQ(ierr); 3627 PetscFunctionReturn(0); 3628 } 3629 3630 /*@ 3631 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3632 example, reuse of the linear part of a Jacobian, while recomputing the 3633 nonlinear portion. 3634 3635 Collect on Mat 3636 3637 Input Parameters: 3638 . mat - the matrix (currently only AIJ matrices support this option) 3639 3640 Level: advanced 3641 3642 Common Usage, with SNESSolve(): 3643 $ Create Jacobian matrix 3644 $ Set linear terms into matrix 3645 $ Apply boundary conditions to matrix, at this time matrix must have 3646 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3647 $ boundary conditions again will not change the nonzero structure 3648 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3649 $ ierr = MatStoreValues(mat); 3650 $ Call SNESSetJacobian() with matrix 3651 $ In your Jacobian routine 3652 $ ierr = MatRetrieveValues(mat); 3653 $ Set nonlinear terms in matrix 3654 3655 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3656 $ // build linear portion of Jacobian 3657 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3658 $ ierr = MatStoreValues(mat); 3659 $ loop over nonlinear iterations 3660 $ ierr = MatRetrieveValues(mat); 3661 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3662 $ // call MatAssemblyBegin/End() on matrix 3663 $ Solve linear system with Jacobian 3664 $ endloop 3665 3666 Notes: 3667 Matrix must already be assemblied before calling this routine 3668 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3669 calling this routine. 3670 3671 When this is called multiple times it overwrites the previous set of stored values 3672 and does not allocated additional space. 3673 3674 .seealso: MatRetrieveValues() 3675 3676 @*/ 3677 PetscErrorCode MatStoreValues(Mat mat) 3678 { 3679 PetscErrorCode ierr; 3680 3681 PetscFunctionBegin; 3682 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3683 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3684 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3685 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3686 PetscFunctionReturn(0); 3687 } 3688 3689 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3690 { 3691 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3692 PetscErrorCode ierr; 3693 PetscInt nz = aij->i[mat->rmap->n]; 3694 3695 PetscFunctionBegin; 3696 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3697 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3698 /* copy values over */ 3699 ierr = PetscArraycpy(aij->a,aij->saved_values,nz);CHKERRQ(ierr); 3700 PetscFunctionReturn(0); 3701 } 3702 3703 /*@ 3704 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3705 example, reuse of the linear part of a Jacobian, while recomputing the 3706 nonlinear portion. 3707 3708 Collect on Mat 3709 3710 Input Parameters: 3711 . mat - the matrix (currently only AIJ matrices support this option) 3712 3713 Level: advanced 3714 3715 .seealso: MatStoreValues() 3716 3717 @*/ 3718 PetscErrorCode MatRetrieveValues(Mat mat) 3719 { 3720 PetscErrorCode ierr; 3721 3722 PetscFunctionBegin; 3723 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3724 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3725 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3726 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3727 PetscFunctionReturn(0); 3728 } 3729 3730 3731 /* --------------------------------------------------------------------------------*/ 3732 /*@C 3733 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3734 (the default parallel PETSc format). For good matrix assembly performance 3735 the user should preallocate the matrix storage by setting the parameter nz 3736 (or the array nnz). By setting these parameters accurately, performance 3737 during matrix assembly can be increased by more than a factor of 50. 3738 3739 Collective 3740 3741 Input Parameters: 3742 + comm - MPI communicator, set to PETSC_COMM_SELF 3743 . m - number of rows 3744 . n - number of columns 3745 . nz - number of nonzeros per row (same for all rows) 3746 - nnz - array containing the number of nonzeros in the various rows 3747 (possibly different for each row) or NULL 3748 3749 Output Parameter: 3750 . A - the matrix 3751 3752 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3753 MatXXXXSetPreallocation() paradigm instead of this routine directly. 3754 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3755 3756 Notes: 3757 If nnz is given then nz is ignored 3758 3759 The AIJ format (also called the Yale sparse matrix format or 3760 compressed row storage), is fully compatible with standard Fortran 77 3761 storage. That is, the stored row and column indices can begin at 3762 either one (as in Fortran) or zero. See the users' manual for details. 3763 3764 Specify the preallocated storage with either nz or nnz (not both). 3765 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3766 allocation. For large problems you MUST preallocate memory or you 3767 will get TERRIBLE performance, see the users' manual chapter on matrices. 3768 3769 By default, this format uses inodes (identical nodes) when possible, to 3770 improve numerical efficiency of matrix-vector products and solves. We 3771 search for consecutive rows with the same nonzero structure, thereby 3772 reusing matrix information to achieve increased efficiency. 3773 3774 Options Database Keys: 3775 + -mat_no_inode - Do not use inodes 3776 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3777 3778 Level: intermediate 3779 3780 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3781 3782 @*/ 3783 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3784 { 3785 PetscErrorCode ierr; 3786 3787 PetscFunctionBegin; 3788 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3789 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3790 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3791 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3792 PetscFunctionReturn(0); 3793 } 3794 3795 /*@C 3796 MatSeqAIJSetPreallocation - For good matrix assembly performance 3797 the user should preallocate the matrix storage by setting the parameter nz 3798 (or the array nnz). By setting these parameters accurately, performance 3799 during matrix assembly can be increased by more than a factor of 50. 3800 3801 Collective 3802 3803 Input Parameters: 3804 + B - The matrix 3805 . nz - number of nonzeros per row (same for all rows) 3806 - nnz - array containing the number of nonzeros in the various rows 3807 (possibly different for each row) or NULL 3808 3809 Notes: 3810 If nnz is given then nz is ignored 3811 3812 The AIJ format (also called the Yale sparse matrix format or 3813 compressed row storage), is fully compatible with standard Fortran 77 3814 storage. That is, the stored row and column indices can begin at 3815 either one (as in Fortran) or zero. See the users' manual for details. 3816 3817 Specify the preallocated storage with either nz or nnz (not both). 3818 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3819 allocation. For large problems you MUST preallocate memory or you 3820 will get TERRIBLE performance, see the users' manual chapter on matrices. 3821 3822 You can call MatGetInfo() to get information on how effective the preallocation was; 3823 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3824 You can also run with the option -info and look for messages with the string 3825 malloc in them to see if additional memory allocation was needed. 3826 3827 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3828 entries or columns indices 3829 3830 By default, this format uses inodes (identical nodes) when possible, to 3831 improve numerical efficiency of matrix-vector products and solves. We 3832 search for consecutive rows with the same nonzero structure, thereby 3833 reusing matrix information to achieve increased efficiency. 3834 3835 Options Database Keys: 3836 + -mat_no_inode - Do not use inodes 3837 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3838 3839 Level: intermediate 3840 3841 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3842 3843 @*/ 3844 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3845 { 3846 PetscErrorCode ierr; 3847 3848 PetscFunctionBegin; 3849 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3850 PetscValidType(B,1); 3851 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3852 PetscFunctionReturn(0); 3853 } 3854 3855 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3856 { 3857 Mat_SeqAIJ *b; 3858 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3859 PetscErrorCode ierr; 3860 PetscInt i; 3861 3862 PetscFunctionBegin; 3863 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3864 if (nz == MAT_SKIP_ALLOCATION) { 3865 skipallocation = PETSC_TRUE; 3866 nz = 0; 3867 } 3868 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3869 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3870 3871 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3872 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 3873 #if defined(PETSC_USE_DEBUG) 3874 if (nnz) { 3875 for (i=0; i<B->rmap->n; i++) { 3876 if (nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %D value %D",i,nnz[i]); 3877 if (nnz[i] > B->cmap->n) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than row length: local row %D value %d rowlength %D",i,nnz[i],B->cmap->n); 3878 } 3879 } 3880 #endif 3881 3882 B->preallocated = PETSC_TRUE; 3883 3884 b = (Mat_SeqAIJ*)B->data; 3885 3886 if (!skipallocation) { 3887 if (!b->imax) { 3888 ierr = PetscMalloc1(B->rmap->n,&b->imax);CHKERRQ(ierr); 3889 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3890 } 3891 if (!b->ilen) { 3892 /* b->ilen will count nonzeros in each row so far. */ 3893 ierr = PetscCalloc1(B->rmap->n,&b->ilen);CHKERRQ(ierr); 3894 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3895 } else { 3896 ierr = PetscMemzero(b->ilen,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3897 } 3898 if (!b->ipre) { 3899 ierr = PetscMalloc1(B->rmap->n,&b->ipre);CHKERRQ(ierr); 3900 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3901 } 3902 if (!nnz) { 3903 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3904 else if (nz < 0) nz = 1; 3905 nz = PetscMin(nz,B->cmap->n); 3906 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3907 nz = nz*B->rmap->n; 3908 } else { 3909 PetscInt64 nz64 = 0; 3910 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz64 += nnz[i];} 3911 ierr = PetscIntCast(nz64,&nz);CHKERRQ(ierr); 3912 } 3913 3914 /* allocate the matrix space */ 3915 /* FIXME: should B's old memory be unlogged? */ 3916 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3917 if (B->structure_only) { 3918 ierr = PetscMalloc1(nz,&b->j);CHKERRQ(ierr); 3919 ierr = PetscMalloc1(B->rmap->n+1,&b->i);CHKERRQ(ierr); 3920 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));CHKERRQ(ierr); 3921 } else { 3922 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3923 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3924 } 3925 b->i[0] = 0; 3926 for (i=1; i<B->rmap->n+1; i++) { 3927 b->i[i] = b->i[i-1] + b->imax[i-1]; 3928 } 3929 if (B->structure_only) { 3930 b->singlemalloc = PETSC_FALSE; 3931 b->free_a = PETSC_FALSE; 3932 } else { 3933 b->singlemalloc = PETSC_TRUE; 3934 b->free_a = PETSC_TRUE; 3935 } 3936 b->free_ij = PETSC_TRUE; 3937 } else { 3938 b->free_a = PETSC_FALSE; 3939 b->free_ij = PETSC_FALSE; 3940 } 3941 3942 if (b->ipre && nnz != b->ipre && b->imax) { 3943 /* reserve user-requested sparsity */ 3944 ierr = PetscArraycpy(b->ipre,b->imax,B->rmap->n);CHKERRQ(ierr); 3945 } 3946 3947 3948 b->nz = 0; 3949 b->maxnz = nz; 3950 B->info.nz_unneeded = (double)b->maxnz; 3951 if (realalloc) { 3952 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3953 } 3954 B->was_assembled = PETSC_FALSE; 3955 B->assembled = PETSC_FALSE; 3956 PetscFunctionReturn(0); 3957 } 3958 3959 3960 PetscErrorCode MatResetPreallocation_SeqAIJ(Mat A) 3961 { 3962 Mat_SeqAIJ *a; 3963 PetscInt i; 3964 PetscErrorCode ierr; 3965 3966 PetscFunctionBegin; 3967 PetscValidHeaderSpecific(A,MAT_CLASSID,1); 3968 3969 /* Check local size. If zero, then return */ 3970 if (!A->rmap->n) PetscFunctionReturn(0); 3971 3972 a = (Mat_SeqAIJ*)A->data; 3973 /* if no saved info, we error out */ 3974 if (!a->ipre) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"No saved preallocation info \n"); 3975 3976 if (!a->i || !a->j || !a->a || !a->imax || !a->ilen) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"Memory info is incomplete, and can not reset preallocation \n"); 3977 3978 ierr = PetscArraycpy(a->imax,a->ipre,A->rmap->n);CHKERRQ(ierr); 3979 ierr = PetscArrayzero(a->ilen,A->rmap->n);CHKERRQ(ierr); 3980 a->i[0] = 0; 3981 for (i=1; i<A->rmap->n+1; i++) { 3982 a->i[i] = a->i[i-1] + a->imax[i-1]; 3983 } 3984 A->preallocated = PETSC_TRUE; 3985 a->nz = 0; 3986 a->maxnz = a->i[A->rmap->n]; 3987 A->info.nz_unneeded = (double)a->maxnz; 3988 A->was_assembled = PETSC_FALSE; 3989 A->assembled = PETSC_FALSE; 3990 PetscFunctionReturn(0); 3991 } 3992 3993 /*@ 3994 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3995 3996 Input Parameters: 3997 + B - the matrix 3998 . i - the indices into j for the start of each row (starts with zero) 3999 . j - the column indices for each row (starts with zero) these must be sorted for each row 4000 - v - optional values in the matrix 4001 4002 Level: developer 4003 4004 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 4005 4006 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), MATSEQAIJ 4007 @*/ 4008 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 4009 { 4010 PetscErrorCode ierr; 4011 4012 PetscFunctionBegin; 4013 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4014 PetscValidType(B,1); 4015 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 4016 PetscFunctionReturn(0); 4017 } 4018 4019 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 4020 { 4021 PetscInt i; 4022 PetscInt m,n; 4023 PetscInt nz; 4024 PetscInt *nnz, nz_max = 0; 4025 PetscErrorCode ierr; 4026 4027 PetscFunctionBegin; 4028 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 4029 4030 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 4031 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 4032 4033 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 4034 ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); 4035 for (i = 0; i < m; i++) { 4036 nz = Ii[i+1]- Ii[i]; 4037 nz_max = PetscMax(nz_max, nz); 4038 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 4039 nnz[i] = nz; 4040 } 4041 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 4042 ierr = PetscFree(nnz);CHKERRQ(ierr); 4043 4044 for (i = 0; i < m; i++) { 4045 ierr = MatSetValues_SeqAIJ(B, 1, &i, Ii[i+1] - Ii[i], J+Ii[i], v ? v + Ii[i] : NULL, INSERT_VALUES);CHKERRQ(ierr); 4046 } 4047 4048 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4049 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4050 4051 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 4052 PetscFunctionReturn(0); 4053 } 4054 4055 #include <../src/mat/impls/dense/seq/dense.h> 4056 #include <petsc/private/kernels/petscaxpy.h> 4057 4058 /* 4059 Computes (B'*A')' since computing B*A directly is untenable 4060 4061 n p p 4062 ( ) ( ) ( ) 4063 m ( A ) * n ( B ) = m ( C ) 4064 ( ) ( ) ( ) 4065 4066 */ 4067 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 4068 { 4069 PetscErrorCode ierr; 4070 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 4071 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 4072 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 4073 PetscInt i,n,m,q,p; 4074 const PetscInt *ii,*idx; 4075 const PetscScalar *b,*a,*a_q; 4076 PetscScalar *c,*c_q; 4077 4078 PetscFunctionBegin; 4079 m = A->rmap->n; 4080 n = A->cmap->n; 4081 p = B->cmap->n; 4082 a = sub_a->v; 4083 b = sub_b->a; 4084 c = sub_c->v; 4085 ierr = PetscArrayzero(c,m*p);CHKERRQ(ierr); 4086 4087 ii = sub_b->i; 4088 idx = sub_b->j; 4089 for (i=0; i<n; i++) { 4090 q = ii[i+1] - ii[i]; 4091 while (q-->0) { 4092 c_q = c + m*(*idx); 4093 a_q = a + m*i; 4094 PetscKernelAXPY(c_q,*b,a_q,m); 4095 idx++; 4096 b++; 4097 } 4098 } 4099 PetscFunctionReturn(0); 4100 } 4101 4102 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4103 { 4104 PetscErrorCode ierr; 4105 PetscInt m=A->rmap->n,n=B->cmap->n; 4106 Mat Cmat; 4107 4108 PetscFunctionBegin; 4109 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); 4110 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4111 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 4112 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 4113 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 4114 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4115 4116 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 4117 4118 *C = Cmat; 4119 PetscFunctionReturn(0); 4120 } 4121 4122 /* ----------------------------------------------------------------*/ 4123 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4124 { 4125 PetscErrorCode ierr; 4126 4127 PetscFunctionBegin; 4128 if (scall == MAT_INITIAL_MATRIX) { 4129 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4130 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 4131 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4132 } 4133 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4134 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 4135 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4136 PetscFunctionReturn(0); 4137 } 4138 4139 4140 /*MC 4141 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 4142 based on compressed sparse row format. 4143 4144 Options Database Keys: 4145 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 4146 4147 Level: beginner 4148 4149 Notes: 4150 MatSetValues() may be called for this matrix type with a NULL argument for the numerical values, 4151 in this case the values associated with the rows and columns one passes in are set to zero 4152 in the matrix 4153 4154 MatSetOptions(,MAT_STRUCTURE_ONLY,PETSC_TRUE) may be called for this matrix type. In this no 4155 space is allocated for the nonzero entries and any entries passed with MatSetValues() are ignored 4156 4157 Developer Notes: 4158 It would be nice if all matrix formats supported passing NULL in for the numerical values 4159 4160 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 4161 M*/ 4162 4163 /*MC 4164 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 4165 4166 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 4167 and MATMPIAIJ otherwise. As a result, for single process communicators, 4168 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation() is supported 4169 for communicators controlling multiple processes. It is recommended that you call both of 4170 the above preallocation routines for simplicity. 4171 4172 Options Database Keys: 4173 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 4174 4175 Developer Notes: 4176 Subclasses include MATAIJCUSPARSE, MATAIJPERM, MATAIJSELL, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when 4177 enough exist. 4178 4179 Level: beginner 4180 4181 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 4182 M*/ 4183 4184 /*MC 4185 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 4186 4187 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 4188 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 4189 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 4190 for communicators controlling multiple processes. It is recommended that you call both of 4191 the above preallocation routines for simplicity. 4192 4193 Options Database Keys: 4194 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 4195 4196 Level: beginner 4197 4198 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 4199 M*/ 4200 4201 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 4202 #if defined(PETSC_HAVE_ELEMENTAL) 4203 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4204 #endif 4205 #if defined(PETSC_HAVE_HYPRE) 4206 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat A,MatType,MatReuse,Mat*); 4207 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 4208 #endif 4209 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*); 4210 4211 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqSELL(Mat,MatType,MatReuse,Mat*); 4212 PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*); 4213 PETSC_INTERN PetscErrorCode MatPtAP_IS_XAIJ(Mat,Mat,MatReuse,PetscReal,Mat*); 4214 4215 /*@C 4216 MatSeqAIJGetArray - gives read/write access to the array where the data for a MATSEQAIJ matrix is stored 4217 4218 Not Collective 4219 4220 Input Parameter: 4221 . mat - a MATSEQAIJ matrix 4222 4223 Output Parameter: 4224 . array - pointer to the data 4225 4226 Level: intermediate 4227 4228 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4229 @*/ 4230 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4231 { 4232 PetscErrorCode ierr; 4233 4234 PetscFunctionBegin; 4235 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4236 PetscFunctionReturn(0); 4237 } 4238 4239 /*@C 4240 MatSeqAIJGetArrayRead - gives read-only access to the array where the data for a MATSEQAIJ matrix is stored 4241 4242 Not Collective 4243 4244 Input Parameter: 4245 . mat - a MATSEQAIJ matrix 4246 4247 Output Parameter: 4248 . array - pointer to the data 4249 4250 Level: intermediate 4251 4252 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayRead() 4253 @*/ 4254 PetscErrorCode MatSeqAIJGetArrayRead(Mat A,const PetscScalar **array) 4255 { 4256 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4257 PetscOffloadFlag oval; 4258 #endif 4259 PetscErrorCode ierr; 4260 4261 PetscFunctionBegin; 4262 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4263 oval = A->valid_GPU_matrix; 4264 #endif 4265 ierr = MatSeqAIJGetArray(A,(PetscScalar**)array);CHKERRQ(ierr); 4266 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4267 if (oval == PETSC_OFFLOAD_GPU || oval == PETSC_OFFLOAD_BOTH) A->valid_GPU_matrix = PETSC_OFFLOAD_BOTH; 4268 #endif 4269 PetscFunctionReturn(0); 4270 } 4271 4272 /*@C 4273 MatSeqAIJRestoreArrayRead - restore the read-only access array obtained from MatSeqAIJGetArrayRead 4274 4275 Not Collective 4276 4277 Input Parameter: 4278 . mat - a MATSEQAIJ matrix 4279 4280 Output Parameter: 4281 . array - pointer to the data 4282 4283 Level: intermediate 4284 4285 .seealso: MatSeqAIJGetArray(), MatSeqAIJGetArrayRead() 4286 @*/ 4287 PetscErrorCode MatSeqAIJRestoreArrayRead(Mat A,const PetscScalar **array) 4288 { 4289 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4290 PetscOffloadFlag oval; 4291 #endif 4292 PetscErrorCode ierr; 4293 4294 PetscFunctionBegin; 4295 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4296 oval = A->valid_GPU_matrix; 4297 #endif 4298 ierr = MatSeqAIJRestoreArray(A,(PetscScalar**)array);CHKERRQ(ierr); 4299 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4300 A->valid_GPU_matrix = oval; 4301 #endif 4302 PetscFunctionReturn(0); 4303 } 4304 4305 /*@C 4306 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 4307 4308 Not Collective 4309 4310 Input Parameter: 4311 . mat - a MATSEQAIJ matrix 4312 4313 Output Parameter: 4314 . nz - the maximum number of nonzeros in any row 4315 4316 Level: intermediate 4317 4318 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4319 @*/ 4320 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 4321 { 4322 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 4323 4324 PetscFunctionBegin; 4325 *nz = aij->rmax; 4326 PetscFunctionReturn(0); 4327 } 4328 4329 /*@C 4330 MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() 4331 4332 Not Collective 4333 4334 Input Parameters: 4335 + mat - a MATSEQAIJ matrix 4336 - array - pointer to the data 4337 4338 Level: intermediate 4339 4340 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4341 @*/ 4342 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4343 { 4344 PetscErrorCode ierr; 4345 4346 PetscFunctionBegin; 4347 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4348 PetscFunctionReturn(0); 4349 } 4350 4351 #if defined(PETSC_HAVE_CUDA) 4352 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCUSPARSE(Mat); 4353 #endif 4354 4355 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4356 { 4357 Mat_SeqAIJ *b; 4358 PetscErrorCode ierr; 4359 PetscMPIInt size; 4360 4361 PetscFunctionBegin; 4362 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4363 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4364 4365 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 4366 4367 B->data = (void*)b; 4368 4369 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4370 if (B->sortedfull) B->ops->setvalues = MatSetValues_SeqAIJ_SortedFull; 4371 4372 b->row = 0; 4373 b->col = 0; 4374 b->icol = 0; 4375 b->reallocs = 0; 4376 b->ignorezeroentries = PETSC_FALSE; 4377 b->roworiented = PETSC_TRUE; 4378 b->nonew = 0; 4379 b->diag = 0; 4380 b->solve_work = 0; 4381 B->spptr = 0; 4382 b->saved_values = 0; 4383 b->idiag = 0; 4384 b->mdiag = 0; 4385 b->ssor_work = 0; 4386 b->omega = 1.0; 4387 b->fshift = 0.0; 4388 b->idiagvalid = PETSC_FALSE; 4389 b->ibdiagvalid = PETSC_FALSE; 4390 b->keepnonzeropattern = PETSC_FALSE; 4391 4392 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4393 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4394 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4395 4396 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4397 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4398 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4399 #endif 4400 4401 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4402 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4403 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4404 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4405 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4406 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4407 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijsell_C",MatConvert_SeqAIJ_SeqAIJSELL);CHKERRQ(ierr); 4408 #if defined(PETSC_HAVE_MKL_SPARSE) 4409 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijmkl_C",MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 4410 #endif 4411 #if defined(PETSC_HAVE_CUDA) 4412 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcusparse_C",MatConvert_SeqAIJ_SeqAIJCUSPARSE);CHKERRQ(ierr); 4413 #endif 4414 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4415 #if defined(PETSC_HAVE_ELEMENTAL) 4416 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); 4417 #endif 4418 #if defined(PETSC_HAVE_HYPRE) 4419 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 4420 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_seqaij_seqaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 4421 #endif 4422 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); 4423 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsell_C",MatConvert_SeqAIJ_SeqSELL);CHKERRQ(ierr); 4424 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_is_C",MatConvert_XAIJ_IS);CHKERRQ(ierr); 4425 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4426 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4427 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4428 ierr = PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_SeqAIJ);CHKERRQ(ierr); 4429 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4430 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4431 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4432 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4433 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4434 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_is_seqaij_C",MatPtAP_IS_XAIJ);CHKERRQ(ierr); 4435 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4436 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4437 ierr = MatSeqAIJSetTypeFromOptions(B);CHKERRQ(ierr); /* this allows changing the matrix subtype to say MATSEQAIJPERM */ 4438 PetscFunctionReturn(0); 4439 } 4440 4441 /* 4442 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4443 */ 4444 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4445 { 4446 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4447 PetscErrorCode ierr; 4448 PetscInt m = A->rmap->n,i; 4449 4450 PetscFunctionBegin; 4451 c = (Mat_SeqAIJ*)C->data; 4452 4453 C->factortype = A->factortype; 4454 c->row = 0; 4455 c->col = 0; 4456 c->icol = 0; 4457 c->reallocs = 0; 4458 4459 C->assembled = PETSC_TRUE; 4460 4461 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4462 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4463 4464 ierr = PetscMalloc1(m,&c->imax);CHKERRQ(ierr); 4465 ierr = PetscMemcpy(c->imax,a->imax,m*sizeof(PetscInt));CHKERRQ(ierr); 4466 ierr = PetscMalloc1(m,&c->ilen);CHKERRQ(ierr); 4467 ierr = PetscMemcpy(c->ilen,a->ilen,m*sizeof(PetscInt));CHKERRQ(ierr); 4468 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4469 4470 /* allocate the matrix space */ 4471 if (mallocmatspace) { 4472 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4473 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4474 4475 c->singlemalloc = PETSC_TRUE; 4476 4477 ierr = PetscArraycpy(c->i,a->i,m+1);CHKERRQ(ierr); 4478 if (m > 0) { 4479 ierr = PetscArraycpy(c->j,a->j,a->i[m]);CHKERRQ(ierr); 4480 if (cpvalues == MAT_COPY_VALUES) { 4481 ierr = PetscArraycpy(c->a,a->a,a->i[m]);CHKERRQ(ierr); 4482 } else { 4483 ierr = PetscArrayzero(c->a,a->i[m]);CHKERRQ(ierr); 4484 } 4485 } 4486 } 4487 4488 c->ignorezeroentries = a->ignorezeroentries; 4489 c->roworiented = a->roworiented; 4490 c->nonew = a->nonew; 4491 if (a->diag) { 4492 ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); 4493 ierr = PetscMemcpy(c->diag,a->diag,m*sizeof(PetscInt));CHKERRQ(ierr); 4494 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4495 } else c->diag = NULL; 4496 4497 c->solve_work = 0; 4498 c->saved_values = 0; 4499 c->idiag = 0; 4500 c->ssor_work = 0; 4501 c->keepnonzeropattern = a->keepnonzeropattern; 4502 c->free_a = PETSC_TRUE; 4503 c->free_ij = PETSC_TRUE; 4504 4505 c->rmax = a->rmax; 4506 c->nz = a->nz; 4507 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4508 C->preallocated = PETSC_TRUE; 4509 4510 c->compressedrow.use = a->compressedrow.use; 4511 c->compressedrow.nrows = a->compressedrow.nrows; 4512 if (a->compressedrow.use) { 4513 i = a->compressedrow.nrows; 4514 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4515 ierr = PetscArraycpy(c->compressedrow.i,a->compressedrow.i,i+1);CHKERRQ(ierr); 4516 ierr = PetscArraycpy(c->compressedrow.rindex,a->compressedrow.rindex,i);CHKERRQ(ierr); 4517 } else { 4518 c->compressedrow.use = PETSC_FALSE; 4519 c->compressedrow.i = NULL; 4520 c->compressedrow.rindex = NULL; 4521 } 4522 c->nonzerorowcnt = a->nonzerorowcnt; 4523 C->nonzerostate = A->nonzerostate; 4524 4525 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4526 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4527 PetscFunctionReturn(0); 4528 } 4529 4530 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4531 { 4532 PetscErrorCode ierr; 4533 4534 PetscFunctionBegin; 4535 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4536 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4537 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4538 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4539 } 4540 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4541 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4542 PetscFunctionReturn(0); 4543 } 4544 4545 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4546 { 4547 PetscBool isbinary, ishdf5; 4548 PetscErrorCode ierr; 4549 4550 PetscFunctionBegin; 4551 PetscValidHeaderSpecific(newMat,MAT_CLASSID,1); 4552 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 4553 /* force binary viewer to load .info file if it has not yet done so */ 4554 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4555 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 4556 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERHDF5, &ishdf5);CHKERRQ(ierr); 4557 if (isbinary) { 4558 ierr = MatLoad_SeqAIJ_Binary(newMat,viewer);CHKERRQ(ierr); 4559 } else if (ishdf5) { 4560 #if defined(PETSC_HAVE_HDF5) 4561 ierr = MatLoad_AIJ_HDF5(newMat,viewer);CHKERRQ(ierr); 4562 #else 4563 SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"HDF5 not supported in this build.\nPlease reconfigure using --download-hdf5"); 4564 #endif 4565 } else { 4566 SETERRQ2(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newMat)->type_name); 4567 } 4568 PetscFunctionReturn(0); 4569 } 4570 4571 PetscErrorCode MatLoad_SeqAIJ_Binary(Mat newMat, PetscViewer viewer) 4572 { 4573 Mat_SeqAIJ *a; 4574 PetscErrorCode ierr; 4575 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4576 int fd; 4577 PetscMPIInt size; 4578 MPI_Comm comm; 4579 PetscInt bs = newMat->rmap->bs; 4580 4581 PetscFunctionBegin; 4582 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4583 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4584 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4585 4586 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4587 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4588 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4589 if (bs < 0) bs = 1; 4590 ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr); 4591 4592 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4593 ierr = PetscBinaryRead(fd,header,4,NULL,PETSC_INT);CHKERRQ(ierr); 4594 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4595 M = header[1]; N = header[2]; nz = header[3]; 4596 4597 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4598 4599 /* read in row lengths */ 4600 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4601 ierr = PetscBinaryRead(fd,rowlengths,M,NULL,PETSC_INT);CHKERRQ(ierr); 4602 4603 /* check if sum of rowlengths is same as nz */ 4604 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4605 if (sum != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_READ,"Inconsistant matrix data in file. no-nonzeros = %dD, sum-row-lengths = %D\n",nz,sum); 4606 4607 /* set global size if not set already*/ 4608 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4609 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4610 } else { 4611 /* if sizes and type are already set, check if the matrix global sizes are correct */ 4612 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4613 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4614 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4615 } 4616 if (M != rows || N != cols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different length (%D, %D) than the input matrix (%D, %D)",M,N,rows,cols); 4617 } 4618 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4619 a = (Mat_SeqAIJ*)newMat->data; 4620 4621 ierr = PetscBinaryRead(fd,a->j,nz,NULL,PETSC_INT);CHKERRQ(ierr); 4622 4623 /* read in nonzero values */ 4624 ierr = PetscBinaryRead(fd,a->a,nz,NULL,PETSC_SCALAR);CHKERRQ(ierr); 4625 4626 /* set matrix "i" values */ 4627 a->i[0] = 0; 4628 for (i=1; i<= M; i++) { 4629 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4630 a->ilen[i-1] = rowlengths[i-1]; 4631 } 4632 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4633 4634 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4635 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4636 PetscFunctionReturn(0); 4637 } 4638 4639 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4640 { 4641 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4642 PetscErrorCode ierr; 4643 #if defined(PETSC_USE_COMPLEX) 4644 PetscInt k; 4645 #endif 4646 4647 PetscFunctionBegin; 4648 /* If the matrix dimensions are not equal,or no of nonzeros */ 4649 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4650 *flg = PETSC_FALSE; 4651 PetscFunctionReturn(0); 4652 } 4653 4654 /* if the a->i are the same */ 4655 ierr = PetscArraycmp(a->i,b->i,A->rmap->n+1,flg);CHKERRQ(ierr); 4656 if (!*flg) PetscFunctionReturn(0); 4657 4658 /* if a->j are the same */ 4659 ierr = PetscArraycmp(a->j,b->j,a->nz,flg);CHKERRQ(ierr); 4660 if (!*flg) PetscFunctionReturn(0); 4661 4662 /* if a->a are the same */ 4663 #if defined(PETSC_USE_COMPLEX) 4664 for (k=0; k<a->nz; k++) { 4665 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4666 *flg = PETSC_FALSE; 4667 PetscFunctionReturn(0); 4668 } 4669 } 4670 #else 4671 ierr = PetscArraycmp(a->a,b->a,a->nz,flg);CHKERRQ(ierr); 4672 #endif 4673 PetscFunctionReturn(0); 4674 } 4675 4676 /*@ 4677 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4678 provided by the user. 4679 4680 Collective 4681 4682 Input Parameters: 4683 + comm - must be an MPI communicator of size 1 4684 . m - number of rows 4685 . n - number of columns 4686 . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix 4687 . j - column indices 4688 - a - matrix values 4689 4690 Output Parameter: 4691 . mat - the matrix 4692 4693 Level: intermediate 4694 4695 Notes: 4696 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4697 once the matrix is destroyed and not before 4698 4699 You cannot set new nonzero locations into this matrix, that will generate an error. 4700 4701 The i and j indices are 0 based 4702 4703 The format which is used for the sparse matrix input, is equivalent to a 4704 row-major ordering.. i.e for the following matrix, the input data expected is 4705 as shown 4706 4707 $ 1 0 0 4708 $ 2 0 3 4709 $ 4 5 6 4710 $ 4711 $ i = {0,1,3,6} [size = nrow+1 = 3+1] 4712 $ j = {0,0,2,0,1,2} [size = 6]; values must be sorted for each row 4713 $ v = {1,2,3,4,5,6} [size = 6] 4714 4715 4716 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4717 4718 @*/ 4719 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat) 4720 { 4721 PetscErrorCode ierr; 4722 PetscInt ii; 4723 Mat_SeqAIJ *aij; 4724 #if defined(PETSC_USE_DEBUG) 4725 PetscInt jj; 4726 #endif 4727 4728 PetscFunctionBegin; 4729 if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4730 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4731 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4732 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4733 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4734 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4735 aij = (Mat_SeqAIJ*)(*mat)->data; 4736 ierr = PetscMalloc1(m,&aij->imax);CHKERRQ(ierr); 4737 ierr = PetscMalloc1(m,&aij->ilen);CHKERRQ(ierr); 4738 4739 aij->i = i; 4740 aij->j = j; 4741 aij->a = a; 4742 aij->singlemalloc = PETSC_FALSE; 4743 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4744 aij->free_a = PETSC_FALSE; 4745 aij->free_ij = PETSC_FALSE; 4746 4747 for (ii=0; ii<m; ii++) { 4748 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4749 #if defined(PETSC_USE_DEBUG) 4750 if (i[ii+1] - i[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row length in i (row indices) row = %D length = %D",ii,i[ii+1] - i[ii]); 4751 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4752 if (j[jj] < j[jj-1]) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column entry number %D (actual column %D) in row %D is not sorted",jj-i[ii],j[jj],ii); 4753 if (j[jj] == j[jj-1]) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column entry number %D (actual column %D) in row %D is identical to previous entry",jj-i[ii],j[jj],ii); 4754 } 4755 #endif 4756 } 4757 #if defined(PETSC_USE_DEBUG) 4758 for (ii=0; ii<aij->i[m]; ii++) { 4759 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4760 if (j[ii] > n - 1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column index to large at location = %D index = %D",ii,j[ii]); 4761 } 4762 #endif 4763 4764 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4765 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4766 PetscFunctionReturn(0); 4767 } 4768 /*@C 4769 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4770 provided by the user. 4771 4772 Collective 4773 4774 Input Parameters: 4775 + comm - must be an MPI communicator of size 1 4776 . m - number of rows 4777 . n - number of columns 4778 . i - row indices 4779 . j - column indices 4780 . a - matrix values 4781 . nz - number of nonzeros 4782 - idx - 0 or 1 based 4783 4784 Output Parameter: 4785 . mat - the matrix 4786 4787 Level: intermediate 4788 4789 Notes: 4790 The i and j indices are 0 based 4791 4792 The format which is used for the sparse matrix input, is equivalent to a 4793 row-major ordering.. i.e for the following matrix, the input data expected is 4794 as shown: 4795 4796 1 0 0 4797 2 0 3 4798 4 5 6 4799 4800 i = {0,1,1,2,2,2} 4801 j = {0,0,2,0,1,2} 4802 v = {1,2,3,4,5,6} 4803 4804 4805 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4806 4807 @*/ 4808 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat,PetscInt nz,PetscBool idx) 4809 { 4810 PetscErrorCode ierr; 4811 PetscInt ii, *nnz, one = 1,row,col; 4812 4813 4814 PetscFunctionBegin; 4815 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4816 for (ii = 0; ii < nz; ii++) { 4817 nnz[i[ii] - !!idx] += 1; 4818 } 4819 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4820 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4821 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4822 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4823 for (ii = 0; ii < nz; ii++) { 4824 if (idx) { 4825 row = i[ii] - 1; 4826 col = j[ii] - 1; 4827 } else { 4828 row = i[ii]; 4829 col = j[ii]; 4830 } 4831 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4832 } 4833 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4834 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4835 ierr = PetscFree(nnz);CHKERRQ(ierr); 4836 PetscFunctionReturn(0); 4837 } 4838 4839 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4840 { 4841 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4842 PetscErrorCode ierr; 4843 4844 PetscFunctionBegin; 4845 a->idiagvalid = PETSC_FALSE; 4846 a->ibdiagvalid = PETSC_FALSE; 4847 4848 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4849 PetscFunctionReturn(0); 4850 } 4851 4852 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4853 { 4854 PetscErrorCode ierr; 4855 PetscMPIInt size; 4856 4857 PetscFunctionBegin; 4858 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4859 if (size == 1) { 4860 if (scall == MAT_INITIAL_MATRIX) { 4861 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4862 } else { 4863 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4864 } 4865 } else { 4866 ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); 4867 } 4868 PetscFunctionReturn(0); 4869 } 4870 4871 /* 4872 Permute A into C's *local* index space using rowemb,colemb. 4873 The embedding are supposed to be injections and the above implies that the range of rowemb is a subset 4874 of [0,m), colemb is in [0,n). 4875 If pattern == DIFFERENT_NONZERO_PATTERN, C is preallocated according to A. 4876 */ 4877 PetscErrorCode MatSetSeqMat_SeqAIJ(Mat C,IS rowemb,IS colemb,MatStructure pattern,Mat B) 4878 { 4879 /* If making this function public, change the error returned in this function away from _PLIB. */ 4880 PetscErrorCode ierr; 4881 Mat_SeqAIJ *Baij; 4882 PetscBool seqaij; 4883 PetscInt m,n,*nz,i,j,count; 4884 PetscScalar v; 4885 const PetscInt *rowindices,*colindices; 4886 4887 PetscFunctionBegin; 4888 if (!B) PetscFunctionReturn(0); 4889 /* Check to make sure the target matrix (and embeddings) are compatible with C and each other. */ 4890 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQAIJ,&seqaij);CHKERRQ(ierr); 4891 if (!seqaij) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is of wrong type"); 4892 if (rowemb) { 4893 ierr = ISGetLocalSize(rowemb,&m);CHKERRQ(ierr); 4894 if (m != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Row IS of size %D is incompatible with matrix row size %D",m,B->rmap->n); 4895 } else { 4896 if (C->rmap->n != B->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is row-incompatible with the target matrix"); 4897 } 4898 if (colemb) { 4899 ierr = ISGetLocalSize(colemb,&n);CHKERRQ(ierr); 4900 if (n != B->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Diag col IS of size %D is incompatible with input matrix col size %D",n,B->cmap->n); 4901 } else { 4902 if (C->cmap->n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is col-incompatible with the target matrix"); 4903 } 4904 4905 Baij = (Mat_SeqAIJ*)(B->data); 4906 if (pattern == DIFFERENT_NONZERO_PATTERN) { 4907 ierr = PetscMalloc1(B->rmap->n,&nz);CHKERRQ(ierr); 4908 for (i=0; i<B->rmap->n; i++) { 4909 nz[i] = Baij->i[i+1] - Baij->i[i]; 4910 } 4911 ierr = MatSeqAIJSetPreallocation(C,0,nz);CHKERRQ(ierr); 4912 ierr = PetscFree(nz);CHKERRQ(ierr); 4913 } 4914 if (pattern == SUBSET_NONZERO_PATTERN) { 4915 ierr = MatZeroEntries(C);CHKERRQ(ierr); 4916 } 4917 count = 0; 4918 rowindices = NULL; 4919 colindices = NULL; 4920 if (rowemb) { 4921 ierr = ISGetIndices(rowemb,&rowindices);CHKERRQ(ierr); 4922 } 4923 if (colemb) { 4924 ierr = ISGetIndices(colemb,&colindices);CHKERRQ(ierr); 4925 } 4926 for (i=0; i<B->rmap->n; i++) { 4927 PetscInt row; 4928 row = i; 4929 if (rowindices) row = rowindices[i]; 4930 for (j=Baij->i[i]; j<Baij->i[i+1]; j++) { 4931 PetscInt col; 4932 col = Baij->j[count]; 4933 if (colindices) col = colindices[col]; 4934 v = Baij->a[count]; 4935 ierr = MatSetValues(C,1,&row,1,&col,&v,INSERT_VALUES);CHKERRQ(ierr); 4936 ++count; 4937 } 4938 } 4939 /* FIXME: set C's nonzerostate correctly. */ 4940 /* Assembly for C is necessary. */ 4941 C->preallocated = PETSC_TRUE; 4942 C->assembled = PETSC_TRUE; 4943 C->was_assembled = PETSC_FALSE; 4944 PetscFunctionReturn(0); 4945 } 4946 4947 PetscFunctionList MatSeqAIJList = NULL; 4948 4949 /*@C 4950 MatSeqAIJSetType - Converts a MATSEQAIJ matrix to a subtype 4951 4952 Collective on Mat 4953 4954 Input Parameters: 4955 + mat - the matrix object 4956 - matype - matrix type 4957 4958 Options Database Key: 4959 . -mat_seqai_type <method> - for example seqaijcrl 4960 4961 4962 Level: intermediate 4963 4964 .seealso: PCSetType(), VecSetType(), MatCreate(), MatType, Mat 4965 @*/ 4966 PetscErrorCode MatSeqAIJSetType(Mat mat, MatType matype) 4967 { 4968 PetscErrorCode ierr,(*r)(Mat,MatType,MatReuse,Mat*); 4969 PetscBool sametype; 4970 4971 PetscFunctionBegin; 4972 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 4973 ierr = PetscObjectTypeCompare((PetscObject)mat,matype,&sametype);CHKERRQ(ierr); 4974 if (sametype) PetscFunctionReturn(0); 4975 4976 ierr = PetscFunctionListFind(MatSeqAIJList,matype,&r);CHKERRQ(ierr); 4977 if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown Mat type given: %s",matype); 4978 ierr = (*r)(mat,matype,MAT_INPLACE_MATRIX,&mat);CHKERRQ(ierr); 4979 PetscFunctionReturn(0); 4980 } 4981 4982 4983 /*@C 4984 MatSeqAIJRegister - - Adds a new sub-matrix type for sequential AIJ matrices 4985 4986 Not Collective 4987 4988 Input Parameters: 4989 + name - name of a new user-defined matrix type, for example MATSEQAIJCRL 4990 - function - routine to convert to subtype 4991 4992 Notes: 4993 MatSeqAIJRegister() may be called multiple times to add several user-defined solvers. 4994 4995 4996 Then, your matrix can be chosen with the procedural interface at runtime via the option 4997 $ -mat_seqaij_type my_mat 4998 4999 Level: advanced 5000 5001 .seealso: MatSeqAIJRegisterAll() 5002 5003 5004 Level: advanced 5005 @*/ 5006 PetscErrorCode MatSeqAIJRegister(const char sname[],PetscErrorCode (*function)(Mat,MatType,MatReuse,Mat *)) 5007 { 5008 PetscErrorCode ierr; 5009 5010 PetscFunctionBegin; 5011 ierr = MatInitializePackage();CHKERRQ(ierr); 5012 ierr = PetscFunctionListAdd(&MatSeqAIJList,sname,function);CHKERRQ(ierr); 5013 PetscFunctionReturn(0); 5014 } 5015 5016 PetscBool MatSeqAIJRegisterAllCalled = PETSC_FALSE; 5017 5018 /*@C 5019 MatSeqAIJRegisterAll - Registers all of the matrix subtypes of SeqAIJ 5020 5021 Not Collective 5022 5023 Level: advanced 5024 5025 Developers Note: CUSP and CUSPARSE do not yet support the MatConvert_SeqAIJ..() paradigm and thus cannot be registered here 5026 5027 .seealso: MatRegisterAll(), MatSeqAIJRegister() 5028 @*/ 5029 PetscErrorCode MatSeqAIJRegisterAll(void) 5030 { 5031 PetscErrorCode ierr; 5032 5033 PetscFunctionBegin; 5034 if (MatSeqAIJRegisterAllCalled) PetscFunctionReturn(0); 5035 MatSeqAIJRegisterAllCalled = PETSC_TRUE; 5036 5037 ierr = MatSeqAIJRegister(MATSEQAIJCRL, MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 5038 ierr = MatSeqAIJRegister(MATSEQAIJPERM, MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 5039 ierr = MatSeqAIJRegister(MATSEQAIJSELL, MatConvert_SeqAIJ_SeqAIJSELL);CHKERRQ(ierr); 5040 #if defined(PETSC_HAVE_MKL_SPARSE) 5041 ierr = MatSeqAIJRegister(MATSEQAIJMKL, MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 5042 #endif 5043 #if defined(PETSC_HAVE_VIENNACL) && defined(PETSC_HAVE_VIENNACL_NO_CUDA) 5044 ierr = MatSeqAIJRegister(MATMPIAIJVIENNACL, MatConvert_SeqAIJ_SeqAIJViennaCL);CHKERRQ(ierr); 5045 #endif 5046 PetscFunctionReturn(0); 5047 } 5048 5049 /* 5050 Special version for direct calls from Fortran 5051 */ 5052 #include <petsc/private/fortranimpl.h> 5053 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5054 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 5055 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5056 #define matsetvaluesseqaij_ matsetvaluesseqaij 5057 #endif 5058 5059 /* Change these macros so can be used in void function */ 5060 #undef CHKERRQ 5061 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 5062 #undef SETERRQ2 5063 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5064 #undef SETERRQ3 5065 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5066 5067 PETSC_EXTERN void PETSC_STDCALL matsetvaluesseqaij_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[],InsertMode *isis, PetscErrorCode *_ierr) 5068 { 5069 Mat A = *AA; 5070 PetscInt m = *mm, n = *nn; 5071 InsertMode is = *isis; 5072 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5073 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 5074 PetscInt *imax,*ai,*ailen; 5075 PetscErrorCode ierr; 5076 PetscInt *aj,nonew = a->nonew,lastcol = -1; 5077 MatScalar *ap,value,*aa; 5078 PetscBool ignorezeroentries = a->ignorezeroentries; 5079 PetscBool roworiented = a->roworiented; 5080 5081 PetscFunctionBegin; 5082 MatCheckPreallocated(A,1); 5083 imax = a->imax; 5084 ai = a->i; 5085 ailen = a->ilen; 5086 aj = a->j; 5087 aa = a->a; 5088 5089 for (k=0; k<m; k++) { /* loop over added rows */ 5090 row = im[k]; 5091 if (row < 0) continue; 5092 #if defined(PETSC_USE_DEBUG) 5093 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 5094 #endif 5095 rp = aj + ai[row]; ap = aa + ai[row]; 5096 rmax = imax[row]; nrow = ailen[row]; 5097 low = 0; 5098 high = nrow; 5099 for (l=0; l<n; l++) { /* loop over added columns */ 5100 if (in[l] < 0) continue; 5101 #if defined(PETSC_USE_DEBUG) 5102 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 5103 #endif 5104 col = in[l]; 5105 if (roworiented) value = v[l + k*n]; 5106 else value = v[k + l*m]; 5107 5108 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 5109 5110 if (col <= lastcol) low = 0; 5111 else high = nrow; 5112 lastcol = col; 5113 while (high-low > 5) { 5114 t = (low+high)/2; 5115 if (rp[t] > col) high = t; 5116 else low = t; 5117 } 5118 for (i=low; i<high; i++) { 5119 if (rp[i] > col) break; 5120 if (rp[i] == col) { 5121 if (is == ADD_VALUES) ap[i] += value; 5122 else ap[i] = value; 5123 goto noinsert; 5124 } 5125 } 5126 if (value == 0.0 && ignorezeroentries) goto noinsert; 5127 if (nonew == 1) goto noinsert; 5128 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 5129 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 5130 N = nrow++ - 1; a->nz++; high++; 5131 /* shift up all the later entries in this row */ 5132 for (ii=N; ii>=i; ii--) { 5133 rp[ii+1] = rp[ii]; 5134 ap[ii+1] = ap[ii]; 5135 } 5136 rp[i] = col; 5137 ap[i] = value; 5138 A->nonzerostate++; 5139 noinsert:; 5140 low = i + 1; 5141 } 5142 ailen[row] = nrow; 5143 } 5144 PetscFunctionReturnVoid(); 5145 } 5146