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 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2566 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2567 2568 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2569 *B = C; 2570 PetscFunctionReturn(0); 2571 } 2572 2573 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2574 { 2575 PetscErrorCode ierr; 2576 Mat B; 2577 2578 PetscFunctionBegin; 2579 if (scall == MAT_INITIAL_MATRIX) { 2580 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2581 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2582 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2583 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2584 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2585 *subMat = B; 2586 } else { 2587 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2588 } 2589 PetscFunctionReturn(0); 2590 } 2591 2592 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2593 { 2594 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2595 PetscErrorCode ierr; 2596 Mat outA; 2597 PetscBool row_identity,col_identity; 2598 2599 PetscFunctionBegin; 2600 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2601 2602 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2603 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2604 2605 outA = inA; 2606 outA->factortype = MAT_FACTOR_LU; 2607 ierr = PetscFree(inA->solvertype);CHKERRQ(ierr); 2608 ierr = PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);CHKERRQ(ierr); 2609 2610 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2611 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2612 2613 a->row = row; 2614 2615 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2616 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2617 2618 a->col = col; 2619 2620 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2621 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2622 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2623 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2624 2625 if (!a->solve_work) { /* this matrix may have been factored before */ 2626 ierr = PetscMalloc1(inA->rmap->n+1,&a->solve_work);CHKERRQ(ierr); 2627 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2628 } 2629 2630 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2631 if (row_identity && col_identity) { 2632 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2633 } else { 2634 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2635 } 2636 PetscFunctionReturn(0); 2637 } 2638 2639 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2640 { 2641 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2642 PetscScalar oalpha = alpha; 2643 PetscErrorCode ierr; 2644 PetscBLASInt one = 1,bnz; 2645 2646 PetscFunctionBegin; 2647 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2648 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2649 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2650 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2651 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2652 if (inA->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) inA->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 2653 #endif 2654 PetscFunctionReturn(0); 2655 } 2656 2657 PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt *submatj) 2658 { 2659 PetscErrorCode ierr; 2660 PetscInt i; 2661 2662 PetscFunctionBegin; 2663 if (!submatj->id) { /* delete data that are linked only to submats[id=0] */ 2664 ierr = PetscFree4(submatj->sbuf1,submatj->ptr,submatj->tmp,submatj->ctr);CHKERRQ(ierr); 2665 2666 for (i=0; i<submatj->nrqr; ++i) { 2667 ierr = PetscFree(submatj->sbuf2[i]);CHKERRQ(ierr); 2668 } 2669 ierr = PetscFree3(submatj->sbuf2,submatj->req_size,submatj->req_source1);CHKERRQ(ierr); 2670 2671 if (submatj->rbuf1) { 2672 ierr = PetscFree(submatj->rbuf1[0]);CHKERRQ(ierr); 2673 ierr = PetscFree(submatj->rbuf1);CHKERRQ(ierr); 2674 } 2675 2676 for (i=0; i<submatj->nrqs; ++i) { 2677 ierr = PetscFree(submatj->rbuf3[i]);CHKERRQ(ierr); 2678 } 2679 ierr = PetscFree3(submatj->req_source2,submatj->rbuf2,submatj->rbuf3);CHKERRQ(ierr); 2680 ierr = PetscFree(submatj->pa);CHKERRQ(ierr); 2681 } 2682 2683 #if defined(PETSC_USE_CTABLE) 2684 ierr = PetscTableDestroy((PetscTable*)&submatj->rmap);CHKERRQ(ierr); 2685 if (submatj->cmap_loc) {ierr = PetscFree(submatj->cmap_loc);CHKERRQ(ierr);} 2686 ierr = PetscFree(submatj->rmap_loc);CHKERRQ(ierr); 2687 #else 2688 ierr = PetscFree(submatj->rmap);CHKERRQ(ierr); 2689 #endif 2690 2691 if (!submatj->allcolumns) { 2692 #if defined(PETSC_USE_CTABLE) 2693 ierr = PetscTableDestroy((PetscTable*)&submatj->cmap);CHKERRQ(ierr); 2694 #else 2695 ierr = PetscFree(submatj->cmap);CHKERRQ(ierr); 2696 #endif 2697 } 2698 ierr = PetscFree(submatj->row2proc);CHKERRQ(ierr); 2699 2700 ierr = PetscFree(submatj);CHKERRQ(ierr); 2701 PetscFunctionReturn(0); 2702 } 2703 2704 PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat C) 2705 { 2706 PetscErrorCode ierr; 2707 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2708 Mat_SubSppt *submatj = c->submatis1; 2709 2710 PetscFunctionBegin; 2711 ierr = (*submatj->destroy)(C);CHKERRQ(ierr); 2712 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2713 PetscFunctionReturn(0); 2714 } 2715 2716 PetscErrorCode MatDestroySubMatrices_SeqAIJ(PetscInt n,Mat *mat[]) 2717 { 2718 PetscErrorCode ierr; 2719 PetscInt i; 2720 Mat C; 2721 Mat_SeqAIJ *c; 2722 Mat_SubSppt *submatj; 2723 2724 PetscFunctionBegin; 2725 for (i=0; i<n; i++) { 2726 C = (*mat)[i]; 2727 c = (Mat_SeqAIJ*)C->data; 2728 submatj = c->submatis1; 2729 if (submatj) { 2730 if (--((PetscObject)C)->refct <= 0) { 2731 ierr = (*submatj->destroy)(C);CHKERRQ(ierr); 2732 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2733 ierr = PetscFree(C->defaultvectype);CHKERRQ(ierr); 2734 ierr = PetscLayoutDestroy(&C->rmap);CHKERRQ(ierr); 2735 ierr = PetscLayoutDestroy(&C->cmap);CHKERRQ(ierr); 2736 ierr = PetscHeaderDestroy(&C);CHKERRQ(ierr); 2737 } 2738 } else { 2739 ierr = MatDestroy(&C);CHKERRQ(ierr); 2740 } 2741 } 2742 2743 /* Destroy Dummy submatrices created for reuse */ 2744 ierr = MatDestroySubMatrices_Dummy(n,mat);CHKERRQ(ierr); 2745 2746 ierr = PetscFree(*mat);CHKERRQ(ierr); 2747 PetscFunctionReturn(0); 2748 } 2749 2750 PetscErrorCode MatCreateSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2751 { 2752 PetscErrorCode ierr; 2753 PetscInt i; 2754 2755 PetscFunctionBegin; 2756 if (scall == MAT_INITIAL_MATRIX) { 2757 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 2758 } 2759 2760 for (i=0; i<n; i++) { 2761 ierr = MatCreateSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2762 } 2763 PetscFunctionReturn(0); 2764 } 2765 2766 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2767 { 2768 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2769 PetscErrorCode ierr; 2770 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2771 const PetscInt *idx; 2772 PetscInt start,end,*ai,*aj; 2773 PetscBT table; 2774 2775 PetscFunctionBegin; 2776 m = A->rmap->n; 2777 ai = a->i; 2778 aj = a->j; 2779 2780 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2781 2782 ierr = PetscMalloc1(m+1,&nidx);CHKERRQ(ierr); 2783 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2784 2785 for (i=0; i<is_max; i++) { 2786 /* Initialize the two local arrays */ 2787 isz = 0; 2788 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2789 2790 /* Extract the indices, assume there can be duplicate entries */ 2791 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2792 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2793 2794 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2795 for (j=0; j<n; ++j) { 2796 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2797 } 2798 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2799 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2800 2801 k = 0; 2802 for (j=0; j<ov; j++) { /* for each overlap */ 2803 n = isz; 2804 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2805 row = nidx[k]; 2806 start = ai[row]; 2807 end = ai[row+1]; 2808 for (l = start; l<end; l++) { 2809 val = aj[l]; 2810 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2811 } 2812 } 2813 } 2814 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2815 } 2816 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2817 ierr = PetscFree(nidx);CHKERRQ(ierr); 2818 PetscFunctionReturn(0); 2819 } 2820 2821 /* -------------------------------------------------------------- */ 2822 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2823 { 2824 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2825 PetscErrorCode ierr; 2826 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2827 const PetscInt *row,*col; 2828 PetscInt *cnew,j,*lens; 2829 IS icolp,irowp; 2830 PetscInt *cwork = NULL; 2831 PetscScalar *vwork = NULL; 2832 2833 PetscFunctionBegin; 2834 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2835 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2836 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2837 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2838 2839 /* determine lengths of permuted rows */ 2840 ierr = PetscMalloc1(m+1,&lens);CHKERRQ(ierr); 2841 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2842 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2843 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2844 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2845 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2846 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2847 ierr = PetscFree(lens);CHKERRQ(ierr); 2848 2849 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2850 for (i=0; i<m; i++) { 2851 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2852 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2853 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2854 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2855 } 2856 ierr = PetscFree(cnew);CHKERRQ(ierr); 2857 2858 (*B)->assembled = PETSC_FALSE; 2859 2860 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2861 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2862 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2863 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2864 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2865 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2866 PetscFunctionReturn(0); 2867 } 2868 2869 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2870 { 2871 PetscErrorCode ierr; 2872 2873 PetscFunctionBegin; 2874 /* If the two matrices have the same copy implementation, use fast copy. */ 2875 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2876 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2877 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2878 2879 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"); 2880 ierr = PetscArraycpy(b->a,a->a,a->i[A->rmap->n]);CHKERRQ(ierr); 2881 ierr = PetscObjectStateIncrease((PetscObject)B);CHKERRQ(ierr); 2882 } else { 2883 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2884 } 2885 PetscFunctionReturn(0); 2886 } 2887 2888 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2889 { 2890 PetscErrorCode ierr; 2891 2892 PetscFunctionBegin; 2893 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2894 PetscFunctionReturn(0); 2895 } 2896 2897 PETSC_INTERN PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2898 { 2899 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2900 2901 PetscFunctionBegin; 2902 *array = a->a; 2903 PetscFunctionReturn(0); 2904 } 2905 2906 PETSC_INTERN PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2907 { 2908 PetscFunctionBegin; 2909 *array = NULL; 2910 PetscFunctionReturn(0); 2911 } 2912 2913 /* 2914 Computes the number of nonzeros per row needed for preallocation when X and Y 2915 have different nonzero structure. 2916 */ 2917 PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *yi,const PetscInt *yj,PetscInt *nnz) 2918 { 2919 PetscInt i,j,k,nzx,nzy; 2920 2921 PetscFunctionBegin; 2922 /* Set the number of nonzeros in the new matrix */ 2923 for (i=0; i<m; i++) { 2924 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2925 nzx = xi[i+1] - xi[i]; 2926 nzy = yi[i+1] - yi[i]; 2927 nnz[i] = 0; 2928 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2929 for (; k<nzy && yjj[k]<xjj[j]; k++) nnz[i]++; /* Catch up to X */ 2930 if (k<nzy && yjj[k]==xjj[j]) k++; /* Skip duplicate */ 2931 nnz[i]++; 2932 } 2933 for (; k<nzy; k++) nnz[i]++; 2934 } 2935 PetscFunctionReturn(0); 2936 } 2937 2938 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2939 { 2940 PetscInt m = Y->rmap->N; 2941 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2942 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2943 PetscErrorCode ierr; 2944 2945 PetscFunctionBegin; 2946 /* Set the number of nonzeros in the new matrix */ 2947 ierr = MatAXPYGetPreallocation_SeqX_private(m,x->i,x->j,y->i,y->j,nnz);CHKERRQ(ierr); 2948 PetscFunctionReturn(0); 2949 } 2950 2951 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2952 { 2953 PetscErrorCode ierr; 2954 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 2955 PetscBLASInt one=1,bnz; 2956 2957 PetscFunctionBegin; 2958 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2959 if (str == SAME_NONZERO_PATTERN) { 2960 PetscScalar alpha = a; 2961 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2962 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 2963 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2964 /* the MatAXPY_Basic* subroutines calls MatAssembly, so the matrix on the GPU 2965 will be updated */ 2966 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2967 if (Y->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) { 2968 Y->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 2969 } 2970 #endif 2971 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2972 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2973 } else { 2974 Mat B; 2975 PetscInt *nnz; 2976 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2977 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2978 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2979 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2980 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2981 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2982 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 2983 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 2984 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2985 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2986 ierr = PetscFree(nnz);CHKERRQ(ierr); 2987 } 2988 PetscFunctionReturn(0); 2989 } 2990 2991 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 2992 { 2993 #if defined(PETSC_USE_COMPLEX) 2994 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 2995 PetscInt i,nz; 2996 PetscScalar *a; 2997 2998 PetscFunctionBegin; 2999 nz = aij->nz; 3000 a = aij->a; 3001 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 3002 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 3003 if (mat->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) mat->valid_GPU_matrix = PETSC_OFFLOAD_CPU; 3004 #endif 3005 #else 3006 PetscFunctionBegin; 3007 #endif 3008 PetscFunctionReturn(0); 3009 } 3010 3011 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3012 { 3013 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3014 PetscErrorCode ierr; 3015 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3016 PetscReal atmp; 3017 PetscScalar *x; 3018 MatScalar *aa; 3019 3020 PetscFunctionBegin; 3021 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3022 aa = a->a; 3023 ai = a->i; 3024 aj = a->j; 3025 3026 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3027 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3028 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3029 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3030 for (i=0; i<m; i++) { 3031 ncols = ai[1] - ai[0]; ai++; 3032 x[i] = 0.0; 3033 for (j=0; j<ncols; j++) { 3034 atmp = PetscAbsScalar(*aa); 3035 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3036 aa++; aj++; 3037 } 3038 } 3039 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3040 PetscFunctionReturn(0); 3041 } 3042 3043 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3044 { 3045 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3046 PetscErrorCode ierr; 3047 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3048 PetscScalar *x; 3049 MatScalar *aa; 3050 3051 PetscFunctionBegin; 3052 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3053 aa = a->a; 3054 ai = a->i; 3055 aj = a->j; 3056 3057 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3058 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3059 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3060 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3061 for (i=0; i<m; i++) { 3062 ncols = ai[1] - ai[0]; ai++; 3063 if (ncols == A->cmap->n) { /* row is dense */ 3064 x[i] = *aa; if (idx) idx[i] = 0; 3065 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 3066 x[i] = 0.0; 3067 if (idx) { 3068 idx[i] = 0; /* in case ncols is zero */ 3069 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 3070 if (aj[j] > j) { 3071 idx[i] = j; 3072 break; 3073 } 3074 } 3075 } 3076 } 3077 for (j=0; j<ncols; j++) { 3078 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3079 aa++; aj++; 3080 } 3081 } 3082 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3083 PetscFunctionReturn(0); 3084 } 3085 3086 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3087 { 3088 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3089 PetscErrorCode ierr; 3090 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3091 PetscReal atmp; 3092 PetscScalar *x; 3093 MatScalar *aa; 3094 3095 PetscFunctionBegin; 3096 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3097 aa = a->a; 3098 ai = a->i; 3099 aj = a->j; 3100 3101 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3102 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3103 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3104 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); 3105 for (i=0; i<m; i++) { 3106 ncols = ai[1] - ai[0]; ai++; 3107 if (ncols) { 3108 /* Get first nonzero */ 3109 for (j = 0; j < ncols; j++) { 3110 atmp = PetscAbsScalar(aa[j]); 3111 if (atmp > 1.0e-12) { 3112 x[i] = atmp; 3113 if (idx) idx[i] = aj[j]; 3114 break; 3115 } 3116 } 3117 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 3118 } else { 3119 x[i] = 0.0; if (idx) idx[i] = 0; 3120 } 3121 for (j = 0; j < ncols; j++) { 3122 atmp = PetscAbsScalar(*aa); 3123 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3124 aa++; aj++; 3125 } 3126 } 3127 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3128 PetscFunctionReturn(0); 3129 } 3130 3131 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3132 { 3133 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3134 PetscErrorCode ierr; 3135 PetscInt i,j,m = A->rmap->n,ncols,n; 3136 const PetscInt *ai,*aj; 3137 PetscScalar *x; 3138 const MatScalar *aa; 3139 3140 PetscFunctionBegin; 3141 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3142 aa = a->a; 3143 ai = a->i; 3144 aj = a->j; 3145 3146 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3147 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3148 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3149 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3150 for (i=0; i<m; i++) { 3151 ncols = ai[1] - ai[0]; ai++; 3152 if (ncols == A->cmap->n) { /* row is dense */ 3153 x[i] = *aa; if (idx) idx[i] = 0; 3154 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3155 x[i] = 0.0; 3156 if (idx) { /* find first implicit 0.0 in the row */ 3157 idx[i] = 0; /* in case ncols is zero */ 3158 for (j=0; j<ncols; j++) { 3159 if (aj[j] > j) { 3160 idx[i] = j; 3161 break; 3162 } 3163 } 3164 } 3165 } 3166 for (j=0; j<ncols; j++) { 3167 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3168 aa++; aj++; 3169 } 3170 } 3171 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3172 PetscFunctionReturn(0); 3173 } 3174 3175 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3176 { 3177 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3178 PetscErrorCode ierr; 3179 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3180 MatScalar *diag,work[25],*v_work; 3181 const PetscReal shift = 0.0; 3182 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 3183 3184 PetscFunctionBegin; 3185 allowzeropivot = PetscNot(A->erroriffailure); 3186 if (a->ibdiagvalid) { 3187 if (values) *values = a->ibdiag; 3188 PetscFunctionReturn(0); 3189 } 3190 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3191 if (!a->ibdiag) { 3192 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 3193 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3194 } 3195 diag = a->ibdiag; 3196 if (values) *values = a->ibdiag; 3197 /* factor and invert each block */ 3198 switch (bs) { 3199 case 1: 3200 for (i=0; i<mbs; i++) { 3201 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3202 if (PetscAbsScalar(diag[i] + shift) < PETSC_MACHINE_EPSILON) { 3203 if (allowzeropivot) { 3204 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3205 A->factorerror_zeropivot_value = PetscAbsScalar(diag[i]); 3206 A->factorerror_zeropivot_row = i; 3207 ierr = PetscInfo3(A,"Zero pivot, row %D pivot %g tolerance %g\n",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON);CHKERRQ(ierr); 3208 } 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); 3209 } 3210 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3211 } 3212 break; 3213 case 2: 3214 for (i=0; i<mbs; i++) { 3215 ij[0] = 2*i; ij[1] = 2*i + 1; 3216 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3217 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3218 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3219 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3220 diag += 4; 3221 } 3222 break; 3223 case 3: 3224 for (i=0; i<mbs; i++) { 3225 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3226 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3227 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3228 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3229 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3230 diag += 9; 3231 } 3232 break; 3233 case 4: 3234 for (i=0; i<mbs; i++) { 3235 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3236 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3237 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3238 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3239 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3240 diag += 16; 3241 } 3242 break; 3243 case 5: 3244 for (i=0; i<mbs; i++) { 3245 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3246 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3247 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3248 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3249 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3250 diag += 25; 3251 } 3252 break; 3253 case 6: 3254 for (i=0; i<mbs; i++) { 3255 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; 3256 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3257 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3258 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3259 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3260 diag += 36; 3261 } 3262 break; 3263 case 7: 3264 for (i=0; i<mbs; i++) { 3265 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; 3266 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3267 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3268 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3269 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3270 diag += 49; 3271 } 3272 break; 3273 default: 3274 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3275 for (i=0; i<mbs; i++) { 3276 for (j=0; j<bs; j++) { 3277 IJ[j] = bs*i + j; 3278 } 3279 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3280 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3281 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3282 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3283 diag += bs2; 3284 } 3285 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3286 } 3287 a->ibdiagvalid = PETSC_TRUE; 3288 PetscFunctionReturn(0); 3289 } 3290 3291 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3292 { 3293 PetscErrorCode ierr; 3294 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3295 PetscScalar a; 3296 PetscInt m,n,i,j,col; 3297 3298 PetscFunctionBegin; 3299 if (!x->assembled) { 3300 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3301 for (i=0; i<m; i++) { 3302 for (j=0; j<aij->imax[i]; j++) { 3303 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3304 col = (PetscInt)(n*PetscRealPart(a)); 3305 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3306 } 3307 } 3308 } else { 3309 for (i=0; i<aij->nz; i++) {ierr = PetscRandomGetValue(rctx,aij->a+i);CHKERRQ(ierr);} 3310 } 3311 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3312 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3313 PetscFunctionReturn(0); 3314 } 3315 3316 /* Like MatSetRandom_SeqAIJ, but do not set values on columns in range of [low, high) */ 3317 PetscErrorCode MatSetRandomSkipColumnRange_SeqAIJ_Private(Mat x,PetscInt low,PetscInt high,PetscRandom rctx) 3318 { 3319 PetscErrorCode ierr; 3320 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3321 PetscScalar a; 3322 PetscInt m,n,i,j,col,nskip; 3323 3324 PetscFunctionBegin; 3325 nskip = high - low; 3326 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3327 n -= nskip; /* shrink number of columns where nonzeros can be set */ 3328 for (i=0; i<m; i++) { 3329 for (j=0; j<aij->imax[i]; j++) { 3330 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3331 col = (PetscInt)(n*PetscRealPart(a)); 3332 if (col >= low) col += nskip; /* shift col rightward to skip the hole */ 3333 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3334 } 3335 } 3336 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3337 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3338 PetscFunctionReturn(0); 3339 } 3340 3341 3342 /* -------------------------------------------------------------------*/ 3343 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3344 MatGetRow_SeqAIJ, 3345 MatRestoreRow_SeqAIJ, 3346 MatMult_SeqAIJ, 3347 /* 4*/ MatMultAdd_SeqAIJ, 3348 MatMultTranspose_SeqAIJ, 3349 MatMultTransposeAdd_SeqAIJ, 3350 0, 3351 0, 3352 0, 3353 /* 10*/ 0, 3354 MatLUFactor_SeqAIJ, 3355 0, 3356 MatSOR_SeqAIJ, 3357 MatTranspose_SeqAIJ, 3358 /*1 5*/ MatGetInfo_SeqAIJ, 3359 MatEqual_SeqAIJ, 3360 MatGetDiagonal_SeqAIJ, 3361 MatDiagonalScale_SeqAIJ, 3362 MatNorm_SeqAIJ, 3363 /* 20*/ 0, 3364 MatAssemblyEnd_SeqAIJ, 3365 MatSetOption_SeqAIJ, 3366 MatZeroEntries_SeqAIJ, 3367 /* 24*/ MatZeroRows_SeqAIJ, 3368 0, 3369 0, 3370 0, 3371 0, 3372 /* 29*/ MatSetUp_SeqAIJ, 3373 0, 3374 0, 3375 0, 3376 0, 3377 /* 34*/ MatDuplicate_SeqAIJ, 3378 0, 3379 0, 3380 MatILUFactor_SeqAIJ, 3381 0, 3382 /* 39*/ MatAXPY_SeqAIJ, 3383 MatCreateSubMatrices_SeqAIJ, 3384 MatIncreaseOverlap_SeqAIJ, 3385 MatGetValues_SeqAIJ, 3386 MatCopy_SeqAIJ, 3387 /* 44*/ MatGetRowMax_SeqAIJ, 3388 MatScale_SeqAIJ, 3389 MatShift_SeqAIJ, 3390 MatDiagonalSet_SeqAIJ, 3391 MatZeroRowsColumns_SeqAIJ, 3392 /* 49*/ MatSetRandom_SeqAIJ, 3393 MatGetRowIJ_SeqAIJ, 3394 MatRestoreRowIJ_SeqAIJ, 3395 MatGetColumnIJ_SeqAIJ, 3396 MatRestoreColumnIJ_SeqAIJ, 3397 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3398 0, 3399 0, 3400 MatPermute_SeqAIJ, 3401 0, 3402 /* 59*/ 0, 3403 MatDestroy_SeqAIJ, 3404 MatView_SeqAIJ, 3405 0, 3406 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3407 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3408 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3409 0, 3410 0, 3411 0, 3412 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3413 MatGetRowMinAbs_SeqAIJ, 3414 0, 3415 0, 3416 0, 3417 /* 74*/ 0, 3418 MatFDColoringApply_AIJ, 3419 0, 3420 0, 3421 0, 3422 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3423 0, 3424 0, 3425 0, 3426 MatLoad_SeqAIJ, 3427 /* 84*/ MatIsSymmetric_SeqAIJ, 3428 MatIsHermitian_SeqAIJ, 3429 0, 3430 0, 3431 0, 3432 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3433 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3434 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3435 MatPtAP_SeqAIJ_SeqAIJ, 3436 MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy, 3437 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy, 3438 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3439 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3440 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3441 0, 3442 /* 99*/ 0, 3443 0, 3444 0, 3445 MatConjugate_SeqAIJ, 3446 0, 3447 /*104*/ MatSetValuesRow_SeqAIJ, 3448 MatRealPart_SeqAIJ, 3449 MatImaginaryPart_SeqAIJ, 3450 0, 3451 0, 3452 /*109*/ MatMatSolve_SeqAIJ, 3453 0, 3454 MatGetRowMin_SeqAIJ, 3455 0, 3456 MatMissingDiagonal_SeqAIJ, 3457 /*114*/ 0, 3458 0, 3459 0, 3460 0, 3461 0, 3462 /*119*/ 0, 3463 0, 3464 0, 3465 0, 3466 MatGetMultiProcBlock_SeqAIJ, 3467 /*124*/ MatFindNonzeroRows_SeqAIJ, 3468 MatGetColumnNorms_SeqAIJ, 3469 MatInvertBlockDiagonal_SeqAIJ, 3470 MatInvertVariableBlockDiagonal_SeqAIJ, 3471 0, 3472 /*129*/ 0, 3473 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3474 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3475 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3476 MatTransposeColoringCreate_SeqAIJ, 3477 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3478 MatTransColoringApplyDenToSp_SeqAIJ, 3479 MatRARt_SeqAIJ_SeqAIJ, 3480 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3481 MatRARtNumeric_SeqAIJ_SeqAIJ, 3482 /*139*/0, 3483 0, 3484 0, 3485 MatFDColoringSetUp_SeqXAIJ, 3486 MatFindOffBlockDiagonalEntries_SeqAIJ, 3487 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqAIJ, 3488 MatDestroySubMatrices_SeqAIJ 3489 }; 3490 3491 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3492 { 3493 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3494 PetscInt i,nz,n; 3495 3496 PetscFunctionBegin; 3497 nz = aij->maxnz; 3498 n = mat->rmap->n; 3499 for (i=0; i<nz; i++) { 3500 aij->j[i] = indices[i]; 3501 } 3502 aij->nz = nz; 3503 for (i=0; i<n; i++) { 3504 aij->ilen[i] = aij->imax[i]; 3505 } 3506 PetscFunctionReturn(0); 3507 } 3508 3509 /* 3510 * When a sparse matrix has many zero columns, we should compact them out to save the space 3511 * This happens in MatPtAPSymbolic_MPIAIJ_MPIAIJ_scalable() 3512 * */ 3513 PetscErrorCode MatSeqAIJCompactOutExtraColumns_SeqAIJ(Mat mat, ISLocalToGlobalMapping *mapping) 3514 { 3515 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3516 PetscTable gid1_lid1; 3517 PetscTablePosition tpos; 3518 PetscInt gid,lid,i,j,ncols,ec; 3519 PetscInt *garray; 3520 PetscErrorCode ierr; 3521 3522 PetscFunctionBegin; 3523 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3524 PetscValidPointer(mapping,2); 3525 /* use a table */ 3526 ierr = PetscTableCreate(mat->rmap->n,mat->cmap->N+1,&gid1_lid1);CHKERRQ(ierr); 3527 ec = 0; 3528 for (i=0; i<mat->rmap->n; i++) { 3529 ncols = aij->i[i+1] - aij->i[i]; 3530 for (j=0; j<ncols; j++) { 3531 PetscInt data,gid1 = aij->j[aij->i[i] + j] + 1; 3532 ierr = PetscTableFind(gid1_lid1,gid1,&data);CHKERRQ(ierr); 3533 if (!data) { 3534 /* one based table */ 3535 ierr = PetscTableAdd(gid1_lid1,gid1,++ec,INSERT_VALUES);CHKERRQ(ierr); 3536 } 3537 } 3538 } 3539 /* form array of columns we need */ 3540 ierr = PetscMalloc1(ec+1,&garray);CHKERRQ(ierr); 3541 ierr = PetscTableGetHeadPosition(gid1_lid1,&tpos);CHKERRQ(ierr); 3542 while (tpos) { 3543 ierr = PetscTableGetNext(gid1_lid1,&tpos,&gid,&lid);CHKERRQ(ierr); 3544 gid--; 3545 lid--; 3546 garray[lid] = gid; 3547 } 3548 ierr = PetscSortInt(ec,garray);CHKERRQ(ierr); /* sort, and rebuild */ 3549 ierr = PetscTableRemoveAll(gid1_lid1);CHKERRQ(ierr); 3550 for (i=0; i<ec; i++) { 3551 ierr = PetscTableAdd(gid1_lid1,garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 3552 } 3553 /* compact out the extra columns in B */ 3554 for (i=0; i<mat->rmap->n; i++) { 3555 ncols = aij->i[i+1] - aij->i[i]; 3556 for (j=0; j<ncols; j++) { 3557 PetscInt gid1 = aij->j[aij->i[i] + j] + 1; 3558 ierr = PetscTableFind(gid1_lid1,gid1,&lid);CHKERRQ(ierr); 3559 lid--; 3560 aij->j[aij->i[i] + j] = lid; 3561 } 3562 } 3563 ierr = PetscLayoutDestroy(&mat->cmap);CHKERRQ(ierr); 3564 ierr = PetscLayoutCreateFromSizes(PetscObjectComm((PetscObject)mat),ec,ec,1,&mat->cmap);CHKERRQ(ierr); 3565 ierr = PetscTableDestroy(&gid1_lid1);CHKERRQ(ierr); 3566 ierr = ISLocalToGlobalMappingCreate(PETSC_COMM_SELF,mat->cmap->bs,mat->cmap->n,garray,PETSC_OWN_POINTER,mapping);CHKERRQ(ierr); 3567 ierr = ISLocalToGlobalMappingSetType(*mapping,ISLOCALTOGLOBALMAPPINGHASH);CHKERRQ(ierr); 3568 PetscFunctionReturn(0); 3569 } 3570 3571 /*@ 3572 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3573 in the matrix. 3574 3575 Input Parameters: 3576 + mat - the SeqAIJ matrix 3577 - indices - the column indices 3578 3579 Level: advanced 3580 3581 Notes: 3582 This can be called if you have precomputed the nonzero structure of the 3583 matrix and want to provide it to the matrix object to improve the performance 3584 of the MatSetValues() operation. 3585 3586 You MUST have set the correct numbers of nonzeros per row in the call to 3587 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3588 3589 MUST be called before any calls to MatSetValues(); 3590 3591 The indices should start with zero, not one. 3592 3593 @*/ 3594 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3595 { 3596 PetscErrorCode ierr; 3597 3598 PetscFunctionBegin; 3599 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3600 PetscValidPointer(indices,2); 3601 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3602 PetscFunctionReturn(0); 3603 } 3604 3605 /* ----------------------------------------------------------------------------------------*/ 3606 3607 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3608 { 3609 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3610 PetscErrorCode ierr; 3611 size_t nz = aij->i[mat->rmap->n]; 3612 3613 PetscFunctionBegin; 3614 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3615 3616 /* allocate space for values if not already there */ 3617 if (!aij->saved_values) { 3618 ierr = PetscMalloc1(nz+1,&aij->saved_values);CHKERRQ(ierr); 3619 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3620 } 3621 3622 /* copy values over */ 3623 ierr = PetscArraycpy(aij->saved_values,aij->a,nz);CHKERRQ(ierr); 3624 PetscFunctionReturn(0); 3625 } 3626 3627 /*@ 3628 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3629 example, reuse of the linear part of a Jacobian, while recomputing the 3630 nonlinear portion. 3631 3632 Collect on Mat 3633 3634 Input Parameters: 3635 . mat - the matrix (currently only AIJ matrices support this option) 3636 3637 Level: advanced 3638 3639 Common Usage, with SNESSolve(): 3640 $ Create Jacobian matrix 3641 $ Set linear terms into matrix 3642 $ Apply boundary conditions to matrix, at this time matrix must have 3643 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3644 $ boundary conditions again will not change the nonzero structure 3645 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3646 $ ierr = MatStoreValues(mat); 3647 $ Call SNESSetJacobian() with matrix 3648 $ In your Jacobian routine 3649 $ ierr = MatRetrieveValues(mat); 3650 $ Set nonlinear terms in matrix 3651 3652 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3653 $ // build linear portion of Jacobian 3654 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3655 $ ierr = MatStoreValues(mat); 3656 $ loop over nonlinear iterations 3657 $ ierr = MatRetrieveValues(mat); 3658 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3659 $ // call MatAssemblyBegin/End() on matrix 3660 $ Solve linear system with Jacobian 3661 $ endloop 3662 3663 Notes: 3664 Matrix must already be assemblied before calling this routine 3665 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3666 calling this routine. 3667 3668 When this is called multiple times it overwrites the previous set of stored values 3669 and does not allocated additional space. 3670 3671 .seealso: MatRetrieveValues() 3672 3673 @*/ 3674 PetscErrorCode MatStoreValues(Mat mat) 3675 { 3676 PetscErrorCode ierr; 3677 3678 PetscFunctionBegin; 3679 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3680 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3681 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3682 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3683 PetscFunctionReturn(0); 3684 } 3685 3686 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3687 { 3688 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3689 PetscErrorCode ierr; 3690 PetscInt nz = aij->i[mat->rmap->n]; 3691 3692 PetscFunctionBegin; 3693 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3694 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3695 /* copy values over */ 3696 ierr = PetscArraycpy(aij->a,aij->saved_values,nz);CHKERRQ(ierr); 3697 PetscFunctionReturn(0); 3698 } 3699 3700 /*@ 3701 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3702 example, reuse of the linear part of a Jacobian, while recomputing the 3703 nonlinear portion. 3704 3705 Collect on Mat 3706 3707 Input Parameters: 3708 . mat - the matrix (currently only AIJ matrices support this option) 3709 3710 Level: advanced 3711 3712 .seealso: MatStoreValues() 3713 3714 @*/ 3715 PetscErrorCode MatRetrieveValues(Mat mat) 3716 { 3717 PetscErrorCode ierr; 3718 3719 PetscFunctionBegin; 3720 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3721 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3722 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3723 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3724 PetscFunctionReturn(0); 3725 } 3726 3727 3728 /* --------------------------------------------------------------------------------*/ 3729 /*@C 3730 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3731 (the default parallel PETSc format). For good matrix assembly performance 3732 the user should preallocate the matrix storage by setting the parameter nz 3733 (or the array nnz). By setting these parameters accurately, performance 3734 during matrix assembly can be increased by more than a factor of 50. 3735 3736 Collective 3737 3738 Input Parameters: 3739 + comm - MPI communicator, set to PETSC_COMM_SELF 3740 . m - number of rows 3741 . n - number of columns 3742 . nz - number of nonzeros per row (same for all rows) 3743 - nnz - array containing the number of nonzeros in the various rows 3744 (possibly different for each row) or NULL 3745 3746 Output Parameter: 3747 . A - the matrix 3748 3749 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3750 MatXXXXSetPreallocation() paradigm instead of this routine directly. 3751 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3752 3753 Notes: 3754 If nnz is given then nz is ignored 3755 3756 The AIJ format (also called the Yale sparse matrix format or 3757 compressed row storage), is fully compatible with standard Fortran 77 3758 storage. That is, the stored row and column indices can begin at 3759 either one (as in Fortran) or zero. See the users' manual for details. 3760 3761 Specify the preallocated storage with either nz or nnz (not both). 3762 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3763 allocation. For large problems you MUST preallocate memory or you 3764 will get TERRIBLE performance, see the users' manual chapter on matrices. 3765 3766 By default, this format uses inodes (identical nodes) when possible, to 3767 improve numerical efficiency of matrix-vector products and solves. We 3768 search for consecutive rows with the same nonzero structure, thereby 3769 reusing matrix information to achieve increased efficiency. 3770 3771 Options Database Keys: 3772 + -mat_no_inode - Do not use inodes 3773 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3774 3775 Level: intermediate 3776 3777 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3778 3779 @*/ 3780 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3781 { 3782 PetscErrorCode ierr; 3783 3784 PetscFunctionBegin; 3785 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3786 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3787 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3788 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3789 PetscFunctionReturn(0); 3790 } 3791 3792 /*@C 3793 MatSeqAIJSetPreallocation - For good matrix assembly performance 3794 the user should preallocate the matrix storage by setting the parameter nz 3795 (or the array nnz). By setting these parameters accurately, performance 3796 during matrix assembly can be increased by more than a factor of 50. 3797 3798 Collective 3799 3800 Input Parameters: 3801 + B - The matrix 3802 . nz - number of nonzeros per row (same for all rows) 3803 - nnz - array containing the number of nonzeros in the various rows 3804 (possibly different for each row) or NULL 3805 3806 Notes: 3807 If nnz is given then nz is ignored 3808 3809 The AIJ format (also called the Yale sparse matrix format or 3810 compressed row storage), is fully compatible with standard Fortran 77 3811 storage. That is, the stored row and column indices can begin at 3812 either one (as in Fortran) or zero. See the users' manual for details. 3813 3814 Specify the preallocated storage with either nz or nnz (not both). 3815 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3816 allocation. For large problems you MUST preallocate memory or you 3817 will get TERRIBLE performance, see the users' manual chapter on matrices. 3818 3819 You can call MatGetInfo() to get information on how effective the preallocation was; 3820 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3821 You can also run with the option -info and look for messages with the string 3822 malloc in them to see if additional memory allocation was needed. 3823 3824 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3825 entries or columns indices 3826 3827 By default, this format uses inodes (identical nodes) when possible, to 3828 improve numerical efficiency of matrix-vector products and solves. We 3829 search for consecutive rows with the same nonzero structure, thereby 3830 reusing matrix information to achieve increased efficiency. 3831 3832 Options Database Keys: 3833 + -mat_no_inode - Do not use inodes 3834 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3835 3836 Level: intermediate 3837 3838 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3839 3840 @*/ 3841 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3842 { 3843 PetscErrorCode ierr; 3844 3845 PetscFunctionBegin; 3846 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3847 PetscValidType(B,1); 3848 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3849 PetscFunctionReturn(0); 3850 } 3851 3852 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3853 { 3854 Mat_SeqAIJ *b; 3855 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3856 PetscErrorCode ierr; 3857 PetscInt i; 3858 3859 PetscFunctionBegin; 3860 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3861 if (nz == MAT_SKIP_ALLOCATION) { 3862 skipallocation = PETSC_TRUE; 3863 nz = 0; 3864 } 3865 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3866 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3867 3868 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3869 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 3870 #if defined(PETSC_USE_DEBUG) 3871 if (nnz) { 3872 for (i=0; i<B->rmap->n; i++) { 3873 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]); 3874 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); 3875 } 3876 } 3877 #endif 3878 3879 B->preallocated = PETSC_TRUE; 3880 3881 b = (Mat_SeqAIJ*)B->data; 3882 3883 if (!skipallocation) { 3884 if (!b->imax) { 3885 ierr = PetscMalloc1(B->rmap->n,&b->imax);CHKERRQ(ierr); 3886 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3887 } 3888 if (!b->ilen) { 3889 /* b->ilen will count nonzeros in each row so far. */ 3890 ierr = PetscCalloc1(B->rmap->n,&b->ilen);CHKERRQ(ierr); 3891 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3892 } else { 3893 ierr = PetscMemzero(b->ilen,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3894 } 3895 if (!b->ipre) { 3896 ierr = PetscMalloc1(B->rmap->n,&b->ipre);CHKERRQ(ierr); 3897 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3898 } 3899 if (!nnz) { 3900 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3901 else if (nz < 0) nz = 1; 3902 nz = PetscMin(nz,B->cmap->n); 3903 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3904 nz = nz*B->rmap->n; 3905 } else { 3906 PetscInt64 nz64 = 0; 3907 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz64 += nnz[i];} 3908 ierr = PetscIntCast(nz64,&nz);CHKERRQ(ierr); 3909 } 3910 3911 /* allocate the matrix space */ 3912 /* FIXME: should B's old memory be unlogged? */ 3913 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3914 if (B->structure_only) { 3915 ierr = PetscMalloc1(nz,&b->j);CHKERRQ(ierr); 3916 ierr = PetscMalloc1(B->rmap->n+1,&b->i);CHKERRQ(ierr); 3917 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));CHKERRQ(ierr); 3918 } else { 3919 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3920 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3921 } 3922 b->i[0] = 0; 3923 for (i=1; i<B->rmap->n+1; i++) { 3924 b->i[i] = b->i[i-1] + b->imax[i-1]; 3925 } 3926 if (B->structure_only) { 3927 b->singlemalloc = PETSC_FALSE; 3928 b->free_a = PETSC_FALSE; 3929 } else { 3930 b->singlemalloc = PETSC_TRUE; 3931 b->free_a = PETSC_TRUE; 3932 } 3933 b->free_ij = PETSC_TRUE; 3934 } else { 3935 b->free_a = PETSC_FALSE; 3936 b->free_ij = PETSC_FALSE; 3937 } 3938 3939 if (b->ipre && nnz != b->ipre && b->imax) { 3940 /* reserve user-requested sparsity */ 3941 ierr = PetscArraycpy(b->ipre,b->imax,B->rmap->n);CHKERRQ(ierr); 3942 } 3943 3944 3945 b->nz = 0; 3946 b->maxnz = nz; 3947 B->info.nz_unneeded = (double)b->maxnz; 3948 if (realalloc) { 3949 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3950 } 3951 B->was_assembled = PETSC_FALSE; 3952 B->assembled = PETSC_FALSE; 3953 PetscFunctionReturn(0); 3954 } 3955 3956 3957 PetscErrorCode MatResetPreallocation_SeqAIJ(Mat A) 3958 { 3959 Mat_SeqAIJ *a; 3960 PetscInt i; 3961 PetscErrorCode ierr; 3962 3963 PetscFunctionBegin; 3964 PetscValidHeaderSpecific(A,MAT_CLASSID,1); 3965 3966 /* Check local size. If zero, then return */ 3967 if (!A->rmap->n) PetscFunctionReturn(0); 3968 3969 a = (Mat_SeqAIJ*)A->data; 3970 /* if no saved info, we error out */ 3971 if (!a->ipre) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"No saved preallocation info \n"); 3972 3973 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"); 3974 3975 ierr = PetscArraycpy(a->imax,a->ipre,A->rmap->n);CHKERRQ(ierr); 3976 ierr = PetscArrayzero(a->ilen,A->rmap->n);CHKERRQ(ierr); 3977 a->i[0] = 0; 3978 for (i=1; i<A->rmap->n+1; i++) { 3979 a->i[i] = a->i[i-1] + a->imax[i-1]; 3980 } 3981 A->preallocated = PETSC_TRUE; 3982 a->nz = 0; 3983 a->maxnz = a->i[A->rmap->n]; 3984 A->info.nz_unneeded = (double)a->maxnz; 3985 A->was_assembled = PETSC_FALSE; 3986 A->assembled = PETSC_FALSE; 3987 PetscFunctionReturn(0); 3988 } 3989 3990 /*@ 3991 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3992 3993 Input Parameters: 3994 + B - the matrix 3995 . i - the indices into j for the start of each row (starts with zero) 3996 . j - the column indices for each row (starts with zero) these must be sorted for each row 3997 - v - optional values in the matrix 3998 3999 Level: developer 4000 4001 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 4002 4003 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), MATSEQAIJ 4004 @*/ 4005 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 4006 { 4007 PetscErrorCode ierr; 4008 4009 PetscFunctionBegin; 4010 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4011 PetscValidType(B,1); 4012 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 4013 PetscFunctionReturn(0); 4014 } 4015 4016 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 4017 { 4018 PetscInt i; 4019 PetscInt m,n; 4020 PetscInt nz; 4021 PetscInt *nnz, nz_max = 0; 4022 PetscErrorCode ierr; 4023 4024 PetscFunctionBegin; 4025 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 4026 4027 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 4028 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 4029 4030 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 4031 ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); 4032 for (i = 0; i < m; i++) { 4033 nz = Ii[i+1]- Ii[i]; 4034 nz_max = PetscMax(nz_max, nz); 4035 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 4036 nnz[i] = nz; 4037 } 4038 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 4039 ierr = PetscFree(nnz);CHKERRQ(ierr); 4040 4041 for (i = 0; i < m; i++) { 4042 ierr = MatSetValues_SeqAIJ(B, 1, &i, Ii[i+1] - Ii[i], J+Ii[i], v ? v + Ii[i] : NULL, INSERT_VALUES);CHKERRQ(ierr); 4043 } 4044 4045 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4046 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4047 4048 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 4049 PetscFunctionReturn(0); 4050 } 4051 4052 #include <../src/mat/impls/dense/seq/dense.h> 4053 #include <petsc/private/kernels/petscaxpy.h> 4054 4055 /* 4056 Computes (B'*A')' since computing B*A directly is untenable 4057 4058 n p p 4059 ( ) ( ) ( ) 4060 m ( A ) * n ( B ) = m ( C ) 4061 ( ) ( ) ( ) 4062 4063 */ 4064 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 4065 { 4066 PetscErrorCode ierr; 4067 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 4068 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 4069 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 4070 PetscInt i,n,m,q,p; 4071 const PetscInt *ii,*idx; 4072 const PetscScalar *b,*a,*a_q; 4073 PetscScalar *c,*c_q; 4074 4075 PetscFunctionBegin; 4076 m = A->rmap->n; 4077 n = A->cmap->n; 4078 p = B->cmap->n; 4079 a = sub_a->v; 4080 b = sub_b->a; 4081 c = sub_c->v; 4082 ierr = PetscArrayzero(c,m*p);CHKERRQ(ierr); 4083 4084 ii = sub_b->i; 4085 idx = sub_b->j; 4086 for (i=0; i<n; i++) { 4087 q = ii[i+1] - ii[i]; 4088 while (q-->0) { 4089 c_q = c + m*(*idx); 4090 a_q = a + m*i; 4091 PetscKernelAXPY(c_q,*b,a_q,m); 4092 idx++; 4093 b++; 4094 } 4095 } 4096 PetscFunctionReturn(0); 4097 } 4098 4099 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4100 { 4101 PetscErrorCode ierr; 4102 PetscInt m=A->rmap->n,n=B->cmap->n; 4103 Mat Cmat; 4104 4105 PetscFunctionBegin; 4106 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); 4107 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4108 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 4109 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 4110 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 4111 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4112 4113 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 4114 4115 *C = Cmat; 4116 PetscFunctionReturn(0); 4117 } 4118 4119 /* ----------------------------------------------------------------*/ 4120 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4121 { 4122 PetscErrorCode ierr; 4123 4124 PetscFunctionBegin; 4125 if (scall == MAT_INITIAL_MATRIX) { 4126 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4127 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 4128 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4129 } 4130 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4131 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 4132 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4133 PetscFunctionReturn(0); 4134 } 4135 4136 4137 /*MC 4138 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 4139 based on compressed sparse row format. 4140 4141 Options Database Keys: 4142 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 4143 4144 Level: beginner 4145 4146 Notes: 4147 MatSetValues() may be called for this matrix type with a NULL argument for the numerical values, 4148 in this case the values associated with the rows and columns one passes in are set to zero 4149 in the matrix 4150 4151 MatSetOptions(,MAT_STRUCTURE_ONLY,PETSC_TRUE) may be called for this matrix type. In this no 4152 space is allocated for the nonzero entries and any entries passed with MatSetValues() are ignored 4153 4154 Developer Notes: 4155 It would be nice if all matrix formats supported passing NULL in for the numerical values 4156 4157 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 4158 M*/ 4159 4160 /*MC 4161 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 4162 4163 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 4164 and MATMPIAIJ otherwise. As a result, for single process communicators, 4165 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation() is supported 4166 for communicators controlling multiple processes. It is recommended that you call both of 4167 the above preallocation routines for simplicity. 4168 4169 Options Database Keys: 4170 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 4171 4172 Developer Notes: 4173 Subclasses include MATAIJCUSPARSE, MATAIJPERM, MATAIJSELL, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when 4174 enough exist. 4175 4176 Level: beginner 4177 4178 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 4179 M*/ 4180 4181 /*MC 4182 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 4183 4184 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 4185 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 4186 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 4187 for communicators controlling multiple processes. It is recommended that you call both of 4188 the above preallocation routines for simplicity. 4189 4190 Options Database Keys: 4191 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 4192 4193 Level: beginner 4194 4195 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 4196 M*/ 4197 4198 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 4199 #if defined(PETSC_HAVE_ELEMENTAL) 4200 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4201 #endif 4202 #if defined(PETSC_HAVE_HYPRE) 4203 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat A,MatType,MatReuse,Mat*); 4204 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 4205 #endif 4206 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*); 4207 4208 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqSELL(Mat,MatType,MatReuse,Mat*); 4209 PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*); 4210 PETSC_INTERN PetscErrorCode MatPtAP_IS_XAIJ(Mat,Mat,MatReuse,PetscReal,Mat*); 4211 4212 /*@C 4213 MatSeqAIJGetArray - gives access to the array where the data for a MATSEQAIJ matrix is stored 4214 4215 Not Collective 4216 4217 Input Parameter: 4218 . mat - a MATSEQAIJ matrix 4219 4220 Output Parameter: 4221 . array - pointer to the data 4222 4223 Level: intermediate 4224 4225 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4226 @*/ 4227 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4228 { 4229 PetscErrorCode ierr; 4230 4231 PetscFunctionBegin; 4232 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4233 PetscFunctionReturn(0); 4234 } 4235 4236 /*@C 4237 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 4238 4239 Not Collective 4240 4241 Input Parameter: 4242 . mat - a MATSEQAIJ matrix 4243 4244 Output Parameter: 4245 . nz - the maximum number of nonzeros in any row 4246 4247 Level: intermediate 4248 4249 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4250 @*/ 4251 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 4252 { 4253 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 4254 4255 PetscFunctionBegin; 4256 *nz = aij->rmax; 4257 PetscFunctionReturn(0); 4258 } 4259 4260 /*@C 4261 MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() 4262 4263 Not Collective 4264 4265 Input Parameters: 4266 + mat - a MATSEQAIJ matrix 4267 - array - pointer to the data 4268 4269 Level: intermediate 4270 4271 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4272 @*/ 4273 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4274 { 4275 PetscErrorCode ierr; 4276 4277 PetscFunctionBegin; 4278 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4279 PetscFunctionReturn(0); 4280 } 4281 4282 #if defined(PETSC_HAVE_CUDA) 4283 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCUSPARSE(Mat); 4284 #endif 4285 4286 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4287 { 4288 Mat_SeqAIJ *b; 4289 PetscErrorCode ierr; 4290 PetscMPIInt size; 4291 4292 PetscFunctionBegin; 4293 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4294 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4295 4296 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 4297 4298 B->data = (void*)b; 4299 4300 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4301 if (B->sortedfull) B->ops->setvalues = MatSetValues_SeqAIJ_SortedFull; 4302 4303 b->row = 0; 4304 b->col = 0; 4305 b->icol = 0; 4306 b->reallocs = 0; 4307 b->ignorezeroentries = PETSC_FALSE; 4308 b->roworiented = PETSC_TRUE; 4309 b->nonew = 0; 4310 b->diag = 0; 4311 b->solve_work = 0; 4312 B->spptr = 0; 4313 b->saved_values = 0; 4314 b->idiag = 0; 4315 b->mdiag = 0; 4316 b->ssor_work = 0; 4317 b->omega = 1.0; 4318 b->fshift = 0.0; 4319 b->idiagvalid = PETSC_FALSE; 4320 b->ibdiagvalid = PETSC_FALSE; 4321 b->keepnonzeropattern = PETSC_FALSE; 4322 4323 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4324 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4325 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4326 4327 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4328 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4329 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4330 #endif 4331 4332 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4333 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4334 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4335 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4336 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4337 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4338 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijsell_C",MatConvert_SeqAIJ_SeqAIJSELL);CHKERRQ(ierr); 4339 #if defined(PETSC_HAVE_MKL_SPARSE) 4340 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijmkl_C",MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 4341 #endif 4342 #if defined(PETSC_HAVE_CUDA) 4343 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcusparse_C",MatConvert_SeqAIJ_SeqAIJCUSPARSE);CHKERRQ(ierr); 4344 #endif 4345 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4346 #if defined(PETSC_HAVE_ELEMENTAL) 4347 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); 4348 #endif 4349 #if defined(PETSC_HAVE_HYPRE) 4350 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 4351 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_seqaij_seqaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 4352 #endif 4353 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); 4354 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsell_C",MatConvert_SeqAIJ_SeqSELL);CHKERRQ(ierr); 4355 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_is_C",MatConvert_XAIJ_IS);CHKERRQ(ierr); 4356 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4357 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4358 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4359 ierr = PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_SeqAIJ);CHKERRQ(ierr); 4360 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4361 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4362 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4363 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4364 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4365 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_is_seqaij_C",MatPtAP_IS_XAIJ);CHKERRQ(ierr); 4366 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4367 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4368 ierr = MatSeqAIJSetTypeFromOptions(B);CHKERRQ(ierr); /* this allows changing the matrix subtype to say MATSEQAIJPERM */ 4369 PetscFunctionReturn(0); 4370 } 4371 4372 /* 4373 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4374 */ 4375 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4376 { 4377 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4378 PetscErrorCode ierr; 4379 PetscInt m = A->rmap->n,i; 4380 4381 PetscFunctionBegin; 4382 c = (Mat_SeqAIJ*)C->data; 4383 4384 C->factortype = A->factortype; 4385 c->row = 0; 4386 c->col = 0; 4387 c->icol = 0; 4388 c->reallocs = 0; 4389 4390 C->assembled = PETSC_TRUE; 4391 4392 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4393 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4394 4395 ierr = PetscMalloc1(m,&c->imax);CHKERRQ(ierr); 4396 ierr = PetscMemcpy(c->imax,a->imax,m*sizeof(PetscInt));CHKERRQ(ierr); 4397 ierr = PetscMalloc1(m,&c->ilen);CHKERRQ(ierr); 4398 ierr = PetscMemcpy(c->ilen,a->ilen,m*sizeof(PetscInt));CHKERRQ(ierr); 4399 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4400 4401 /* allocate the matrix space */ 4402 if (mallocmatspace) { 4403 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4404 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4405 4406 c->singlemalloc = PETSC_TRUE; 4407 4408 ierr = PetscArraycpy(c->i,a->i,m+1);CHKERRQ(ierr); 4409 if (m > 0) { 4410 ierr = PetscArraycpy(c->j,a->j,a->i[m]);CHKERRQ(ierr); 4411 if (cpvalues == MAT_COPY_VALUES) { 4412 ierr = PetscArraycpy(c->a,a->a,a->i[m]);CHKERRQ(ierr); 4413 } else { 4414 ierr = PetscArrayzero(c->a,a->i[m]);CHKERRQ(ierr); 4415 } 4416 } 4417 } 4418 4419 c->ignorezeroentries = a->ignorezeroentries; 4420 c->roworiented = a->roworiented; 4421 c->nonew = a->nonew; 4422 if (a->diag) { 4423 ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); 4424 ierr = PetscMemcpy(c->diag,a->diag,m*sizeof(PetscInt));CHKERRQ(ierr); 4425 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4426 } else c->diag = NULL; 4427 4428 c->solve_work = 0; 4429 c->saved_values = 0; 4430 c->idiag = 0; 4431 c->ssor_work = 0; 4432 c->keepnonzeropattern = a->keepnonzeropattern; 4433 c->free_a = PETSC_TRUE; 4434 c->free_ij = PETSC_TRUE; 4435 4436 c->rmax = a->rmax; 4437 c->nz = a->nz; 4438 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4439 C->preallocated = PETSC_TRUE; 4440 4441 c->compressedrow.use = a->compressedrow.use; 4442 c->compressedrow.nrows = a->compressedrow.nrows; 4443 if (a->compressedrow.use) { 4444 i = a->compressedrow.nrows; 4445 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4446 ierr = PetscArraycpy(c->compressedrow.i,a->compressedrow.i,i+1);CHKERRQ(ierr); 4447 ierr = PetscArraycpy(c->compressedrow.rindex,a->compressedrow.rindex,i);CHKERRQ(ierr); 4448 } else { 4449 c->compressedrow.use = PETSC_FALSE; 4450 c->compressedrow.i = NULL; 4451 c->compressedrow.rindex = NULL; 4452 } 4453 c->nonzerorowcnt = a->nonzerorowcnt; 4454 C->nonzerostate = A->nonzerostate; 4455 4456 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4457 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4458 PetscFunctionReturn(0); 4459 } 4460 4461 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4462 { 4463 PetscErrorCode ierr; 4464 4465 PetscFunctionBegin; 4466 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4467 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4468 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4469 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4470 } 4471 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4472 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4473 PetscFunctionReturn(0); 4474 } 4475 4476 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4477 { 4478 PetscBool isbinary, ishdf5; 4479 PetscErrorCode ierr; 4480 4481 PetscFunctionBegin; 4482 PetscValidHeaderSpecific(newMat,MAT_CLASSID,1); 4483 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 4484 /* force binary viewer to load .info file if it has not yet done so */ 4485 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4486 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 4487 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERHDF5, &ishdf5);CHKERRQ(ierr); 4488 if (isbinary) { 4489 ierr = MatLoad_SeqAIJ_Binary(newMat,viewer);CHKERRQ(ierr); 4490 } else if (ishdf5) { 4491 #if defined(PETSC_HAVE_HDF5) 4492 ierr = MatLoad_AIJ_HDF5(newMat,viewer);CHKERRQ(ierr); 4493 #else 4494 SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"HDF5 not supported in this build.\nPlease reconfigure using --download-hdf5"); 4495 #endif 4496 } else { 4497 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); 4498 } 4499 PetscFunctionReturn(0); 4500 } 4501 4502 PetscErrorCode MatLoad_SeqAIJ_Binary(Mat newMat, PetscViewer viewer) 4503 { 4504 Mat_SeqAIJ *a; 4505 PetscErrorCode ierr; 4506 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4507 int fd; 4508 PetscMPIInt size; 4509 MPI_Comm comm; 4510 PetscInt bs = newMat->rmap->bs; 4511 4512 PetscFunctionBegin; 4513 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4514 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4515 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4516 4517 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4518 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4519 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4520 if (bs < 0) bs = 1; 4521 ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr); 4522 4523 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4524 ierr = PetscBinaryRead(fd,header,4,NULL,PETSC_INT);CHKERRQ(ierr); 4525 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4526 M = header[1]; N = header[2]; nz = header[3]; 4527 4528 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4529 4530 /* read in row lengths */ 4531 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4532 ierr = PetscBinaryRead(fd,rowlengths,M,NULL,PETSC_INT);CHKERRQ(ierr); 4533 4534 /* check if sum of rowlengths is same as nz */ 4535 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4536 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); 4537 4538 /* set global size if not set already*/ 4539 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4540 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4541 } else { 4542 /* if sizes and type are already set, check if the matrix global sizes are correct */ 4543 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4544 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4545 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4546 } 4547 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); 4548 } 4549 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4550 a = (Mat_SeqAIJ*)newMat->data; 4551 4552 ierr = PetscBinaryRead(fd,a->j,nz,NULL,PETSC_INT);CHKERRQ(ierr); 4553 4554 /* read in nonzero values */ 4555 ierr = PetscBinaryRead(fd,a->a,nz,NULL,PETSC_SCALAR);CHKERRQ(ierr); 4556 4557 /* set matrix "i" values */ 4558 a->i[0] = 0; 4559 for (i=1; i<= M; i++) { 4560 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4561 a->ilen[i-1] = rowlengths[i-1]; 4562 } 4563 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4564 4565 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4566 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4567 PetscFunctionReturn(0); 4568 } 4569 4570 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4571 { 4572 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4573 PetscErrorCode ierr; 4574 #if defined(PETSC_USE_COMPLEX) 4575 PetscInt k; 4576 #endif 4577 4578 PetscFunctionBegin; 4579 /* If the matrix dimensions are not equal,or no of nonzeros */ 4580 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4581 *flg = PETSC_FALSE; 4582 PetscFunctionReturn(0); 4583 } 4584 4585 /* if the a->i are the same */ 4586 ierr = PetscArraycmp(a->i,b->i,A->rmap->n+1,flg);CHKERRQ(ierr); 4587 if (!*flg) PetscFunctionReturn(0); 4588 4589 /* if a->j are the same */ 4590 ierr = PetscArraycmp(a->j,b->j,a->nz,flg);CHKERRQ(ierr); 4591 if (!*flg) PetscFunctionReturn(0); 4592 4593 /* if a->a are the same */ 4594 #if defined(PETSC_USE_COMPLEX) 4595 for (k=0; k<a->nz; k++) { 4596 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4597 *flg = PETSC_FALSE; 4598 PetscFunctionReturn(0); 4599 } 4600 } 4601 #else 4602 ierr = PetscArraycmp(a->a,b->a,a->nz,flg);CHKERRQ(ierr); 4603 #endif 4604 PetscFunctionReturn(0); 4605 } 4606 4607 /*@ 4608 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4609 provided by the user. 4610 4611 Collective 4612 4613 Input Parameters: 4614 + comm - must be an MPI communicator of size 1 4615 . m - number of rows 4616 . n - number of columns 4617 . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix 4618 . j - column indices 4619 - a - matrix values 4620 4621 Output Parameter: 4622 . mat - the matrix 4623 4624 Level: intermediate 4625 4626 Notes: 4627 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4628 once the matrix is destroyed and not before 4629 4630 You cannot set new nonzero locations into this matrix, that will generate an error. 4631 4632 The i and j indices are 0 based 4633 4634 The format which is used for the sparse matrix input, is equivalent to a 4635 row-major ordering.. i.e for the following matrix, the input data expected is 4636 as shown 4637 4638 $ 1 0 0 4639 $ 2 0 3 4640 $ 4 5 6 4641 $ 4642 $ i = {0,1,3,6} [size = nrow+1 = 3+1] 4643 $ j = {0,0,2,0,1,2} [size = 6]; values must be sorted for each row 4644 $ v = {1,2,3,4,5,6} [size = 6] 4645 4646 4647 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4648 4649 @*/ 4650 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat) 4651 { 4652 PetscErrorCode ierr; 4653 PetscInt ii; 4654 Mat_SeqAIJ *aij; 4655 #if defined(PETSC_USE_DEBUG) 4656 PetscInt jj; 4657 #endif 4658 4659 PetscFunctionBegin; 4660 if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4661 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4662 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4663 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4664 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4665 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4666 aij = (Mat_SeqAIJ*)(*mat)->data; 4667 ierr = PetscMalloc1(m,&aij->imax);CHKERRQ(ierr); 4668 ierr = PetscMalloc1(m,&aij->ilen);CHKERRQ(ierr); 4669 4670 aij->i = i; 4671 aij->j = j; 4672 aij->a = a; 4673 aij->singlemalloc = PETSC_FALSE; 4674 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4675 aij->free_a = PETSC_FALSE; 4676 aij->free_ij = PETSC_FALSE; 4677 4678 for (ii=0; ii<m; ii++) { 4679 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4680 #if defined(PETSC_USE_DEBUG) 4681 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]); 4682 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4683 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); 4684 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); 4685 } 4686 #endif 4687 } 4688 #if defined(PETSC_USE_DEBUG) 4689 for (ii=0; ii<aij->i[m]; ii++) { 4690 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4691 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]); 4692 } 4693 #endif 4694 4695 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4696 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4697 PetscFunctionReturn(0); 4698 } 4699 /*@C 4700 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4701 provided by the user. 4702 4703 Collective 4704 4705 Input Parameters: 4706 + comm - must be an MPI communicator of size 1 4707 . m - number of rows 4708 . n - number of columns 4709 . i - row indices 4710 . j - column indices 4711 . a - matrix values 4712 . nz - number of nonzeros 4713 - idx - 0 or 1 based 4714 4715 Output Parameter: 4716 . mat - the matrix 4717 4718 Level: intermediate 4719 4720 Notes: 4721 The i and j indices are 0 based 4722 4723 The format which is used for the sparse matrix input, is equivalent to a 4724 row-major ordering.. i.e for the following matrix, the input data expected is 4725 as shown: 4726 4727 1 0 0 4728 2 0 3 4729 4 5 6 4730 4731 i = {0,1,1,2,2,2} 4732 j = {0,0,2,0,1,2} 4733 v = {1,2,3,4,5,6} 4734 4735 4736 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4737 4738 @*/ 4739 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat,PetscInt nz,PetscBool idx) 4740 { 4741 PetscErrorCode ierr; 4742 PetscInt ii, *nnz, one = 1,row,col; 4743 4744 4745 PetscFunctionBegin; 4746 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4747 for (ii = 0; ii < nz; ii++) { 4748 nnz[i[ii] - !!idx] += 1; 4749 } 4750 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4751 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4752 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4753 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4754 for (ii = 0; ii < nz; ii++) { 4755 if (idx) { 4756 row = i[ii] - 1; 4757 col = j[ii] - 1; 4758 } else { 4759 row = i[ii]; 4760 col = j[ii]; 4761 } 4762 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4763 } 4764 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4765 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4766 ierr = PetscFree(nnz);CHKERRQ(ierr); 4767 PetscFunctionReturn(0); 4768 } 4769 4770 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4771 { 4772 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4773 PetscErrorCode ierr; 4774 4775 PetscFunctionBegin; 4776 a->idiagvalid = PETSC_FALSE; 4777 a->ibdiagvalid = PETSC_FALSE; 4778 4779 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4780 PetscFunctionReturn(0); 4781 } 4782 4783 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4784 { 4785 PetscErrorCode ierr; 4786 PetscMPIInt size; 4787 4788 PetscFunctionBegin; 4789 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4790 if (size == 1) { 4791 if (scall == MAT_INITIAL_MATRIX) { 4792 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4793 } else { 4794 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4795 } 4796 } else { 4797 ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); 4798 } 4799 PetscFunctionReturn(0); 4800 } 4801 4802 /* 4803 Permute A into C's *local* index space using rowemb,colemb. 4804 The embedding are supposed to be injections and the above implies that the range of rowemb is a subset 4805 of [0,m), colemb is in [0,n). 4806 If pattern == DIFFERENT_NONZERO_PATTERN, C is preallocated according to A. 4807 */ 4808 PetscErrorCode MatSetSeqMat_SeqAIJ(Mat C,IS rowemb,IS colemb,MatStructure pattern,Mat B) 4809 { 4810 /* If making this function public, change the error returned in this function away from _PLIB. */ 4811 PetscErrorCode ierr; 4812 Mat_SeqAIJ *Baij; 4813 PetscBool seqaij; 4814 PetscInt m,n,*nz,i,j,count; 4815 PetscScalar v; 4816 const PetscInt *rowindices,*colindices; 4817 4818 PetscFunctionBegin; 4819 if (!B) PetscFunctionReturn(0); 4820 /* Check to make sure the target matrix (and embeddings) are compatible with C and each other. */ 4821 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQAIJ,&seqaij);CHKERRQ(ierr); 4822 if (!seqaij) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is of wrong type"); 4823 if (rowemb) { 4824 ierr = ISGetLocalSize(rowemb,&m);CHKERRQ(ierr); 4825 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); 4826 } else { 4827 if (C->rmap->n != B->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is row-incompatible with the target matrix"); 4828 } 4829 if (colemb) { 4830 ierr = ISGetLocalSize(colemb,&n);CHKERRQ(ierr); 4831 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); 4832 } else { 4833 if (C->cmap->n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is col-incompatible with the target matrix"); 4834 } 4835 4836 Baij = (Mat_SeqAIJ*)(B->data); 4837 if (pattern == DIFFERENT_NONZERO_PATTERN) { 4838 ierr = PetscMalloc1(B->rmap->n,&nz);CHKERRQ(ierr); 4839 for (i=0; i<B->rmap->n; i++) { 4840 nz[i] = Baij->i[i+1] - Baij->i[i]; 4841 } 4842 ierr = MatSeqAIJSetPreallocation(C,0,nz);CHKERRQ(ierr); 4843 ierr = PetscFree(nz);CHKERRQ(ierr); 4844 } 4845 if (pattern == SUBSET_NONZERO_PATTERN) { 4846 ierr = MatZeroEntries(C);CHKERRQ(ierr); 4847 } 4848 count = 0; 4849 rowindices = NULL; 4850 colindices = NULL; 4851 if (rowemb) { 4852 ierr = ISGetIndices(rowemb,&rowindices);CHKERRQ(ierr); 4853 } 4854 if (colemb) { 4855 ierr = ISGetIndices(colemb,&colindices);CHKERRQ(ierr); 4856 } 4857 for (i=0; i<B->rmap->n; i++) { 4858 PetscInt row; 4859 row = i; 4860 if (rowindices) row = rowindices[i]; 4861 for (j=Baij->i[i]; j<Baij->i[i+1]; j++) { 4862 PetscInt col; 4863 col = Baij->j[count]; 4864 if (colindices) col = colindices[col]; 4865 v = Baij->a[count]; 4866 ierr = MatSetValues(C,1,&row,1,&col,&v,INSERT_VALUES);CHKERRQ(ierr); 4867 ++count; 4868 } 4869 } 4870 /* FIXME: set C's nonzerostate correctly. */ 4871 /* Assembly for C is necessary. */ 4872 C->preallocated = PETSC_TRUE; 4873 C->assembled = PETSC_TRUE; 4874 C->was_assembled = PETSC_FALSE; 4875 PetscFunctionReturn(0); 4876 } 4877 4878 PetscFunctionList MatSeqAIJList = NULL; 4879 4880 /*@C 4881 MatSeqAIJSetType - Converts a MATSEQAIJ matrix to a subtype 4882 4883 Collective on Mat 4884 4885 Input Parameters: 4886 + mat - the matrix object 4887 - matype - matrix type 4888 4889 Options Database Key: 4890 . -mat_seqai_type <method> - for example seqaijcrl 4891 4892 4893 Level: intermediate 4894 4895 .seealso: PCSetType(), VecSetType(), MatCreate(), MatType, Mat 4896 @*/ 4897 PetscErrorCode MatSeqAIJSetType(Mat mat, MatType matype) 4898 { 4899 PetscErrorCode ierr,(*r)(Mat,MatType,MatReuse,Mat*); 4900 PetscBool sametype; 4901 4902 PetscFunctionBegin; 4903 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 4904 ierr = PetscObjectTypeCompare((PetscObject)mat,matype,&sametype);CHKERRQ(ierr); 4905 if (sametype) PetscFunctionReturn(0); 4906 4907 ierr = PetscFunctionListFind(MatSeqAIJList,matype,&r);CHKERRQ(ierr); 4908 if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown Mat type given: %s",matype); 4909 ierr = (*r)(mat,matype,MAT_INPLACE_MATRIX,&mat);CHKERRQ(ierr); 4910 PetscFunctionReturn(0); 4911 } 4912 4913 4914 /*@C 4915 MatSeqAIJRegister - - Adds a new sub-matrix type for sequential AIJ matrices 4916 4917 Not Collective 4918 4919 Input Parameters: 4920 + name - name of a new user-defined matrix type, for example MATSEQAIJCRL 4921 - function - routine to convert to subtype 4922 4923 Notes: 4924 MatSeqAIJRegister() may be called multiple times to add several user-defined solvers. 4925 4926 4927 Then, your matrix can be chosen with the procedural interface at runtime via the option 4928 $ -mat_seqaij_type my_mat 4929 4930 Level: advanced 4931 4932 .seealso: MatSeqAIJRegisterAll() 4933 4934 4935 Level: advanced 4936 @*/ 4937 PetscErrorCode MatSeqAIJRegister(const char sname[],PetscErrorCode (*function)(Mat,MatType,MatReuse,Mat *)) 4938 { 4939 PetscErrorCode ierr; 4940 4941 PetscFunctionBegin; 4942 ierr = MatInitializePackage();CHKERRQ(ierr); 4943 ierr = PetscFunctionListAdd(&MatSeqAIJList,sname,function);CHKERRQ(ierr); 4944 PetscFunctionReturn(0); 4945 } 4946 4947 PetscBool MatSeqAIJRegisterAllCalled = PETSC_FALSE; 4948 4949 /*@C 4950 MatSeqAIJRegisterAll - Registers all of the matrix subtypes of SeqAIJ 4951 4952 Not Collective 4953 4954 Level: advanced 4955 4956 Developers Note: CUSP and CUSPARSE do not yet support the MatConvert_SeqAIJ..() paradigm and thus cannot be registered here 4957 4958 .seealso: MatRegisterAll(), MatSeqAIJRegister() 4959 @*/ 4960 PetscErrorCode MatSeqAIJRegisterAll(void) 4961 { 4962 PetscErrorCode ierr; 4963 4964 PetscFunctionBegin; 4965 if (MatSeqAIJRegisterAllCalled) PetscFunctionReturn(0); 4966 MatSeqAIJRegisterAllCalled = PETSC_TRUE; 4967 4968 ierr = MatSeqAIJRegister(MATSEQAIJCRL, MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4969 ierr = MatSeqAIJRegister(MATSEQAIJPERM, MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4970 ierr = MatSeqAIJRegister(MATSEQAIJSELL, MatConvert_SeqAIJ_SeqAIJSELL);CHKERRQ(ierr); 4971 #if defined(PETSC_HAVE_MKL_SPARSE) 4972 ierr = MatSeqAIJRegister(MATSEQAIJMKL, MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 4973 #endif 4974 #if defined(PETSC_HAVE_VIENNACL) && defined(PETSC_HAVE_VIENNACL_NO_CUDA) 4975 ierr = MatSeqAIJRegister(MATMPIAIJVIENNACL, MatConvert_SeqAIJ_SeqAIJViennaCL);CHKERRQ(ierr); 4976 #endif 4977 PetscFunctionReturn(0); 4978 } 4979 4980 /* 4981 Special version for direct calls from Fortran 4982 */ 4983 #include <petsc/private/fortranimpl.h> 4984 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4985 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4986 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4987 #define matsetvaluesseqaij_ matsetvaluesseqaij 4988 #endif 4989 4990 /* Change these macros so can be used in void function */ 4991 #undef CHKERRQ 4992 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4993 #undef SETERRQ2 4994 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4995 #undef SETERRQ3 4996 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4997 4998 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) 4999 { 5000 Mat A = *AA; 5001 PetscInt m = *mm, n = *nn; 5002 InsertMode is = *isis; 5003 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5004 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 5005 PetscInt *imax,*ai,*ailen; 5006 PetscErrorCode ierr; 5007 PetscInt *aj,nonew = a->nonew,lastcol = -1; 5008 MatScalar *ap,value,*aa; 5009 PetscBool ignorezeroentries = a->ignorezeroentries; 5010 PetscBool roworiented = a->roworiented; 5011 5012 PetscFunctionBegin; 5013 MatCheckPreallocated(A,1); 5014 imax = a->imax; 5015 ai = a->i; 5016 ailen = a->ilen; 5017 aj = a->j; 5018 aa = a->a; 5019 5020 for (k=0; k<m; k++) { /* loop over added rows */ 5021 row = im[k]; 5022 if (row < 0) continue; 5023 #if defined(PETSC_USE_DEBUG) 5024 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 5025 #endif 5026 rp = aj + ai[row]; ap = aa + ai[row]; 5027 rmax = imax[row]; nrow = ailen[row]; 5028 low = 0; 5029 high = nrow; 5030 for (l=0; l<n; l++) { /* loop over added columns */ 5031 if (in[l] < 0) continue; 5032 #if defined(PETSC_USE_DEBUG) 5033 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 5034 #endif 5035 col = in[l]; 5036 if (roworiented) value = v[l + k*n]; 5037 else value = v[k + l*m]; 5038 5039 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 5040 5041 if (col <= lastcol) low = 0; 5042 else high = nrow; 5043 lastcol = col; 5044 while (high-low > 5) { 5045 t = (low+high)/2; 5046 if (rp[t] > col) high = t; 5047 else low = t; 5048 } 5049 for (i=low; i<high; i++) { 5050 if (rp[i] > col) break; 5051 if (rp[i] == col) { 5052 if (is == ADD_VALUES) ap[i] += value; 5053 else ap[i] = value; 5054 goto noinsert; 5055 } 5056 } 5057 if (value == 0.0 && ignorezeroentries) goto noinsert; 5058 if (nonew == 1) goto noinsert; 5059 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 5060 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 5061 N = nrow++ - 1; a->nz++; high++; 5062 /* shift up all the later entries in this row */ 5063 for (ii=N; ii>=i; ii--) { 5064 rp[ii+1] = rp[ii]; 5065 ap[ii+1] = ap[ii]; 5066 } 5067 rp[i] = col; 5068 ap[i] = value; 5069 A->nonzerostate++; 5070 noinsert:; 5071 low = i + 1; 5072 } 5073 ailen[row] = nrow; 5074 } 5075 PetscFunctionReturnVoid(); 5076 } 5077