1 /* 2 Defines the basic matrix operations for the AIJ (compressed row) 3 matrix storage format. 4 */ 5 6 7 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 8 #include <petscblaslapack.h> 9 #include <petscbt.h> 10 #include <petsc/private/kernels/blocktranspose.h> 11 12 PetscErrorCode MatSeqAIJSetTypeFromOptions(Mat A) 13 { 14 PetscErrorCode ierr; 15 PetscBool flg; 16 char type[256]; 17 18 PetscFunctionBegin; 19 ierr = PetscObjectOptionsBegin((PetscObject)A); 20 ierr = PetscOptionsFList("-mat_seqaij_type","Matrix SeqAIJ type","MatSeqAIJSetType",MatSeqAIJList,"seqaij",type,256,&flg);CHKERRQ(ierr); 21 if (flg) { 22 ierr = MatSeqAIJSetType(A,type);CHKERRQ(ierr); 23 } 24 ierr = PetscOptionsEnd();CHKERRQ(ierr); 25 PetscFunctionReturn(0); 26 } 27 28 PetscErrorCode MatGetColumnNorms_SeqAIJ(Mat A,NormType type,PetscReal *norms) 29 { 30 PetscErrorCode ierr; 31 PetscInt i,m,n; 32 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 33 34 PetscFunctionBegin; 35 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 36 ierr = PetscArrayzero(norms,n);CHKERRQ(ierr); 37 if (type == NORM_2) { 38 for (i=0; i<aij->i[m]; i++) { 39 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]*aij->a[i]); 40 } 41 } else if (type == NORM_1) { 42 for (i=0; i<aij->i[m]; i++) { 43 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]); 44 } 45 } else if (type == NORM_INFINITY) { 46 for (i=0; i<aij->i[m]; i++) { 47 norms[aij->j[i]] = PetscMax(PetscAbsScalar(aij->a[i]),norms[aij->j[i]]); 48 } 49 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown NormType"); 50 51 if (type == NORM_2) { 52 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 53 } 54 PetscFunctionReturn(0); 55 } 56 57 PetscErrorCode MatFindOffBlockDiagonalEntries_SeqAIJ(Mat A,IS *is) 58 { 59 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 60 PetscInt i,m=A->rmap->n,cnt = 0, bs = A->rmap->bs; 61 const PetscInt *jj = a->j,*ii = a->i; 62 PetscInt *rows; 63 PetscErrorCode ierr; 64 65 PetscFunctionBegin; 66 for (i=0; i<m; i++) { 67 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 68 cnt++; 69 } 70 } 71 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 72 cnt = 0; 73 for (i=0; i<m; i++) { 74 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 75 rows[cnt] = i; 76 cnt++; 77 } 78 } 79 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 80 PetscFunctionReturn(0); 81 } 82 83 PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat A,PetscInt *nrows,PetscInt **zrows) 84 { 85 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 86 const MatScalar *aa = a->a; 87 PetscInt i,m=A->rmap->n,cnt = 0; 88 const PetscInt *ii = a->i,*jj = a->j,*diag; 89 PetscInt *rows; 90 PetscErrorCode ierr; 91 92 PetscFunctionBegin; 93 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 94 diag = a->diag; 95 for (i=0; i<m; i++) { 96 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 97 cnt++; 98 } 99 } 100 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 101 cnt = 0; 102 for (i=0; i<m; i++) { 103 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 104 rows[cnt++] = i; 105 } 106 } 107 *nrows = cnt; 108 *zrows = rows; 109 PetscFunctionReturn(0); 110 } 111 112 PetscErrorCode MatFindZeroDiagonals_SeqAIJ(Mat A,IS *zrows) 113 { 114 PetscInt nrows,*rows; 115 PetscErrorCode ierr; 116 117 PetscFunctionBegin; 118 *zrows = NULL; 119 ierr = MatFindZeroDiagonals_SeqAIJ_Private(A,&nrows,&rows);CHKERRQ(ierr); 120 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 121 PetscFunctionReturn(0); 122 } 123 124 PetscErrorCode MatFindNonzeroRows_SeqAIJ(Mat A,IS *keptrows) 125 { 126 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 127 const MatScalar *aa; 128 PetscInt m=A->rmap->n,cnt = 0; 129 const PetscInt *ii; 130 PetscInt n,i,j,*rows; 131 PetscErrorCode ierr; 132 133 PetscFunctionBegin; 134 *keptrows = NULL; 135 ii = a->i; 136 for (i=0; i<m; i++) { 137 n = ii[i+1] - ii[i]; 138 if (!n) { 139 cnt++; 140 goto ok1; 141 } 142 aa = a->a + ii[i]; 143 for (j=0; j<n; j++) { 144 if (aa[j] != 0.0) goto ok1; 145 } 146 cnt++; 147 ok1:; 148 } 149 if (!cnt) PetscFunctionReturn(0); 150 ierr = PetscMalloc1(A->rmap->n-cnt,&rows);CHKERRQ(ierr); 151 cnt = 0; 152 for (i=0; i<m; i++) { 153 n = ii[i+1] - ii[i]; 154 if (!n) continue; 155 aa = a->a + ii[i]; 156 for (j=0; j<n; j++) { 157 if (aa[j] != 0.0) { 158 rows[cnt++] = i; 159 break; 160 } 161 } 162 } 163 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 164 PetscFunctionReturn(0); 165 } 166 167 PetscErrorCode MatDiagonalSet_SeqAIJ(Mat Y,Vec D,InsertMode is) 168 { 169 PetscErrorCode ierr; 170 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) Y->data; 171 PetscInt i,m = Y->rmap->n; 172 const PetscInt *diag; 173 MatScalar *aa = aij->a; 174 const PetscScalar *v; 175 PetscBool missing; 176 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 177 PetscBool inserted = PETSC_FALSE; 178 #endif 179 180 PetscFunctionBegin; 181 if (Y->assembled) { 182 ierr = MatMissingDiagonal_SeqAIJ(Y,&missing,NULL);CHKERRQ(ierr); 183 if (!missing) { 184 diag = aij->diag; 185 ierr = VecGetArrayRead(D,&v);CHKERRQ(ierr); 186 if (is == INSERT_VALUES) { 187 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 188 inserted = PETSC_TRUE; 189 #endif 190 for (i=0; i<m; i++) { 191 aa[diag[i]] = v[i]; 192 } 193 } else { 194 for (i=0; i<m; i++) { 195 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 196 if (v[i] != 0.0) inserted = PETSC_TRUE; 197 #endif 198 aa[diag[i]] += v[i]; 199 } 200 } 201 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 202 if (inserted) Y->offloadmask = PETSC_OFFLOAD_CPU; 203 #endif 204 ierr = VecRestoreArrayRead(D,&v);CHKERRQ(ierr); 205 PetscFunctionReturn(0); 206 } 207 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 208 } 209 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 210 PetscFunctionReturn(0); 211 } 212 213 PetscErrorCode MatGetRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *m,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 214 { 215 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 216 PetscErrorCode ierr; 217 PetscInt i,ishift; 218 219 PetscFunctionBegin; 220 *m = A->rmap->n; 221 if (!ia) PetscFunctionReturn(0); 222 ishift = 0; 223 if (symmetric && !A->structurally_symmetric) { 224 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,ishift,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 225 } else if (oshift == 1) { 226 PetscInt *tia; 227 PetscInt nz = a->i[A->rmap->n]; 228 /* malloc space and add 1 to i and j indices */ 229 ierr = PetscMalloc1(A->rmap->n+1,&tia);CHKERRQ(ierr); 230 for (i=0; i<A->rmap->n+1; i++) tia[i] = a->i[i] + 1; 231 *ia = tia; 232 if (ja) { 233 PetscInt *tja; 234 ierr = PetscMalloc1(nz+1,&tja);CHKERRQ(ierr); 235 for (i=0; i<nz; i++) tja[i] = a->j[i] + 1; 236 *ja = tja; 237 } 238 } else { 239 *ia = a->i; 240 if (ja) *ja = a->j; 241 } 242 PetscFunctionReturn(0); 243 } 244 245 PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 246 { 247 PetscErrorCode ierr; 248 249 PetscFunctionBegin; 250 if (!ia) PetscFunctionReturn(0); 251 if ((symmetric && !A->structurally_symmetric) || oshift == 1) { 252 ierr = PetscFree(*ia);CHKERRQ(ierr); 253 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 254 } 255 PetscFunctionReturn(0); 256 } 257 258 PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 259 { 260 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 261 PetscErrorCode ierr; 262 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 263 PetscInt nz = a->i[m],row,*jj,mr,col; 264 265 PetscFunctionBegin; 266 *nn = n; 267 if (!ia) PetscFunctionReturn(0); 268 if (symmetric) { 269 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 270 } else { 271 ierr = PetscCalloc1(n,&collengths);CHKERRQ(ierr); 272 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 273 ierr = PetscMalloc1(nz,&cja);CHKERRQ(ierr); 274 jj = a->j; 275 for (i=0; i<nz; i++) { 276 collengths[jj[i]]++; 277 } 278 cia[0] = oshift; 279 for (i=0; i<n; i++) { 280 cia[i+1] = cia[i] + collengths[i]; 281 } 282 ierr = PetscArrayzero(collengths,n);CHKERRQ(ierr); 283 jj = a->j; 284 for (row=0; row<m; row++) { 285 mr = a->i[row+1] - a->i[row]; 286 for (i=0; i<mr; i++) { 287 col = *jj++; 288 289 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 290 } 291 } 292 ierr = PetscFree(collengths);CHKERRQ(ierr); 293 *ia = cia; *ja = cja; 294 } 295 PetscFunctionReturn(0); 296 } 297 298 PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 299 { 300 PetscErrorCode ierr; 301 302 PetscFunctionBegin; 303 if (!ia) PetscFunctionReturn(0); 304 305 ierr = PetscFree(*ia);CHKERRQ(ierr); 306 ierr = PetscFree(*ja);CHKERRQ(ierr); 307 PetscFunctionReturn(0); 308 } 309 310 /* 311 MatGetColumnIJ_SeqAIJ_Color() and MatRestoreColumnIJ_SeqAIJ_Color() are customized from 312 MatGetColumnIJ_SeqAIJ() and MatRestoreColumnIJ_SeqAIJ() by adding an output 313 spidx[], index of a->a, to be used in MatTransposeColoringCreate_SeqAIJ() and MatFDColoringCreate_SeqXAIJ() 314 */ 315 PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 316 { 317 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 318 PetscErrorCode ierr; 319 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 320 PetscInt nz = a->i[m],row,mr,col,tmp; 321 PetscInt *cspidx; 322 const PetscInt *jj; 323 324 PetscFunctionBegin; 325 *nn = n; 326 if (!ia) PetscFunctionReturn(0); 327 328 ierr = PetscCalloc1(n,&collengths);CHKERRQ(ierr); 329 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 330 ierr = PetscMalloc1(nz,&cja);CHKERRQ(ierr); 331 ierr = PetscMalloc1(nz,&cspidx);CHKERRQ(ierr); 332 jj = a->j; 333 for (i=0; i<nz; i++) { 334 collengths[jj[i]]++; 335 } 336 cia[0] = oshift; 337 for (i=0; i<n; i++) { 338 cia[i+1] = cia[i] + collengths[i]; 339 } 340 ierr = PetscArrayzero(collengths,n);CHKERRQ(ierr); 341 jj = a->j; 342 for (row=0; row<m; row++) { 343 mr = a->i[row+1] - a->i[row]; 344 for (i=0; i<mr; i++) { 345 col = *jj++; 346 tmp = cia[col] + collengths[col]++ - oshift; 347 cspidx[tmp] = a->i[row] + i; /* index of a->j */ 348 cja[tmp] = row + oshift; 349 } 350 } 351 ierr = PetscFree(collengths);CHKERRQ(ierr); 352 *ia = cia; 353 *ja = cja; 354 *spidx = cspidx; 355 PetscFunctionReturn(0); 356 } 357 358 PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 359 { 360 PetscErrorCode ierr; 361 362 PetscFunctionBegin; 363 ierr = MatRestoreColumnIJ_SeqAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);CHKERRQ(ierr); 364 ierr = PetscFree(*spidx);CHKERRQ(ierr); 365 PetscFunctionReturn(0); 366 } 367 368 PetscErrorCode MatSetValuesRow_SeqAIJ(Mat A,PetscInt row,const PetscScalar v[]) 369 { 370 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 371 PetscInt *ai = a->i; 372 PetscErrorCode ierr; 373 374 PetscFunctionBegin; 375 ierr = PetscArraycpy(a->a+ai[row],v,ai[row+1]-ai[row]);CHKERRQ(ierr); 376 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 377 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && ai[row+1]-ai[row]) A->offloadmask = PETSC_OFFLOAD_CPU; 378 #endif 379 PetscFunctionReturn(0); 380 } 381 382 /* 383 MatSeqAIJSetValuesLocalFast - An optimized version of MatSetValuesLocal() for SeqAIJ matrices with several assumptions 384 385 - a single row of values is set with each call 386 - no row or column indices are negative or (in error) larger than the number of rows or columns 387 - the values are always added to the matrix, not set 388 - no new locations are introduced in the nonzero structure of the matrix 389 390 This does NOT assume the global column indices are sorted 391 392 */ 393 394 #include <petsc/private/isimpl.h> 395 PetscErrorCode MatSeqAIJSetValuesLocalFast(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 396 { 397 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 398 PetscInt low,high,t,row,nrow,i,col,l; 399 const PetscInt *rp,*ai = a->i,*ailen = a->ilen,*aj = a->j; 400 PetscInt lastcol = -1; 401 MatScalar *ap,value,*aa = a->a; 402 const PetscInt *ridx = A->rmap->mapping->indices,*cidx = A->cmap->mapping->indices; 403 404 row = ridx[im[0]]; 405 rp = aj + ai[row]; 406 ap = aa + ai[row]; 407 nrow = ailen[row]; 408 low = 0; 409 high = nrow; 410 for (l=0; l<n; l++) { /* loop over added columns */ 411 col = cidx[in[l]]; 412 value = v[l]; 413 414 if (col <= lastcol) low = 0; 415 else high = nrow; 416 lastcol = col; 417 while (high-low > 5) { 418 t = (low+high)/2; 419 if (rp[t] > col) high = t; 420 else low = t; 421 } 422 for (i=low; i<high; i++) { 423 if (rp[i] == col) { 424 ap[i] += value; 425 low = i + 1; 426 break; 427 } 428 } 429 } 430 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 431 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && m && n) A->offloadmask = PETSC_OFFLOAD_CPU; 432 #endif 433 return 0; 434 } 435 436 PetscErrorCode MatSetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 437 { 438 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 439 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 440 PetscInt *imax = a->imax,*ai = a->i,*ailen = a->ilen; 441 PetscErrorCode ierr; 442 PetscInt *aj = a->j,nonew = a->nonew,lastcol = -1; 443 MatScalar *ap=NULL,value=0.0,*aa = a->a; 444 PetscBool ignorezeroentries = a->ignorezeroentries; 445 PetscBool roworiented = a->roworiented; 446 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 447 PetscBool inserted = PETSC_FALSE; 448 #endif 449 450 PetscFunctionBegin; 451 for (k=0; k<m; k++) { /* loop over added rows */ 452 row = im[k]; 453 if (row < 0) continue; 454 if (PetscUnlikelyDebug(row >= A->rmap->n)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); 455 rp = aj + ai[row]; 456 if (!A->structure_only) ap = aa + ai[row]; 457 rmax = imax[row]; nrow = ailen[row]; 458 low = 0; 459 high = nrow; 460 for (l=0; l<n; l++) { /* loop over added columns */ 461 if (in[l] < 0) continue; 462 if (PetscUnlikelyDebug(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); 463 col = in[l]; 464 if (v && !A->structure_only) value = roworiented ? v[l + k*n] : v[k + l*m]; 465 if (!A->structure_only && value == 0.0 && ignorezeroentries && is == ADD_VALUES && row != col) continue; 466 467 if (col <= lastcol) low = 0; 468 else high = nrow; 469 lastcol = col; 470 while (high-low > 5) { 471 t = (low+high)/2; 472 if (rp[t] > col) high = t; 473 else low = t; 474 } 475 for (i=low; i<high; i++) { 476 if (rp[i] > col) break; 477 if (rp[i] == col) { 478 if (!A->structure_only) { 479 if (is == ADD_VALUES) { 480 ap[i] += value; 481 (void)PetscLogFlops(1.0); 482 } 483 else ap[i] = value; 484 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 485 inserted = PETSC_TRUE; 486 #endif 487 } 488 low = i + 1; 489 goto noinsert; 490 } 491 } 492 if (value == 0.0 && ignorezeroentries && row != col) goto noinsert; 493 if (nonew == 1) goto noinsert; 494 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); 495 if (A->structure_only) { 496 MatSeqXAIJReallocateAIJ_structure_only(A,A->rmap->n,1,nrow,row,col,rmax,ai,aj,rp,imax,nonew,MatScalar); 497 } else { 498 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 499 } 500 N = nrow++ - 1; a->nz++; high++; 501 /* shift up all the later entries in this row */ 502 ierr = PetscArraymove(rp+i+1,rp+i,N-i+1);CHKERRQ(ierr); 503 rp[i] = col; 504 if (!A->structure_only){ 505 ierr = PetscArraymove(ap+i+1,ap+i,N-i+1);CHKERRQ(ierr); 506 ap[i] = value; 507 } 508 low = i + 1; 509 A->nonzerostate++; 510 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 511 inserted = PETSC_TRUE; 512 #endif 513 noinsert:; 514 } 515 ailen[row] = nrow; 516 } 517 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 518 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && inserted) A->offloadmask = PETSC_OFFLOAD_CPU; 519 #endif 520 PetscFunctionReturn(0); 521 } 522 523 524 PetscErrorCode MatSetValues_SeqAIJ_SortedFullNoPreallocation(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 525 { 526 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 527 PetscInt *rp,k,row; 528 PetscInt *ai = a->i; 529 PetscErrorCode ierr; 530 PetscInt *aj = a->j; 531 MatScalar *aa = a->a,*ap; 532 533 PetscFunctionBegin; 534 if (A->was_assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot call on assembled matrix."); 535 if (m*n+a->nz > a->maxnz) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Number of entries in matrix will be larger than maximum nonzeros allocated for %D in MatSeqAIJSetTotalPreallocation()",a->maxnz); 536 for (k=0; k<m; k++) { /* loop over added rows */ 537 row = im[k]; 538 rp = aj + ai[row]; 539 ap = aa + ai[row]; 540 541 ierr = PetscMemcpy(rp,in,n*sizeof(PetscInt));CHKERRQ(ierr); 542 if (!A->structure_only) { 543 if (v) { 544 ierr = PetscMemcpy(ap,v,n*sizeof(PetscScalar));CHKERRQ(ierr); 545 v += n; 546 } else { 547 ierr = PetscMemzero(ap,n*sizeof(PetscScalar));CHKERRQ(ierr); 548 } 549 } 550 a->ilen[row] = n; 551 a->imax[row] = n; 552 a->i[row+1] = a->i[row]+n; 553 a->nz += n; 554 } 555 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 556 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && m && n) A->offloadmask = PETSC_OFFLOAD_CPU; 557 #endif 558 PetscFunctionReturn(0); 559 } 560 561 /*@ 562 MatSeqAIJSetTotalPreallocation - Sets an upper bound on the total number of expected nonzeros in the matrix. 563 564 Input Parameters: 565 + A - the SeqAIJ matrix 566 - nztotal - bound on the number of nonzeros 567 568 Level: advanced 569 570 Notes: 571 This can be called if you will be provided the matrix row by row (from row zero) with sorted column indices for each row. 572 Simply call MatSetValues() after this call to provide the matrix entries in the usual manner. This matrix may be used 573 as always with multiple matrix assemblies. 574 575 .seealso: MatSetOption(), MAT_SORTED_FULL, MatSetValues(), MatSeqAIJSetPreallocation() 576 @*/ 577 578 PetscErrorCode MatSeqAIJSetTotalPreallocation(Mat A,PetscInt nztotal) 579 { 580 PetscErrorCode ierr; 581 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 582 583 PetscFunctionBegin; 584 ierr = PetscLayoutSetUp(A->rmap);CHKERRQ(ierr); 585 ierr = PetscLayoutSetUp(A->cmap);CHKERRQ(ierr); 586 a->maxnz = nztotal; 587 if (!a->imax) { 588 ierr = PetscMalloc1(A->rmap->n,&a->imax);CHKERRQ(ierr); 589 ierr = PetscLogObjectMemory((PetscObject)A,A->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 590 } 591 if (!a->ilen) { 592 ierr = PetscMalloc1(A->rmap->n,&a->ilen);CHKERRQ(ierr); 593 ierr = PetscLogObjectMemory((PetscObject)A,A->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 594 } else { 595 ierr = PetscMemzero(a->ilen,A->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 596 } 597 598 /* allocate the matrix space */ 599 if (A->structure_only) { 600 ierr = PetscMalloc1(nztotal,&a->j);CHKERRQ(ierr); 601 ierr = PetscMalloc1(A->rmap->n+1,&a->i);CHKERRQ(ierr); 602 ierr = PetscLogObjectMemory((PetscObject)A,(A->rmap->n+1)*sizeof(PetscInt)+nztotal*sizeof(PetscInt));CHKERRQ(ierr); 603 } else { 604 ierr = PetscMalloc3(nztotal,&a->a,nztotal,&a->j,A->rmap->n+1,&a->i);CHKERRQ(ierr); 605 ierr = PetscLogObjectMemory((PetscObject)A,(A->rmap->n+1)*sizeof(PetscInt)+nztotal*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 606 } 607 a->i[0] = 0; 608 if (A->structure_only) { 609 a->singlemalloc = PETSC_FALSE; 610 a->free_a = PETSC_FALSE; 611 } else { 612 a->singlemalloc = PETSC_TRUE; 613 a->free_a = PETSC_TRUE; 614 } 615 a->free_ij = PETSC_TRUE; 616 A->ops->setvalues = MatSetValues_SeqAIJ_SortedFullNoPreallocation; 617 A->preallocated = PETSC_TRUE; 618 PetscFunctionReturn(0); 619 } 620 621 PetscErrorCode MatSetValues_SeqAIJ_SortedFull(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 622 { 623 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 624 PetscInt *rp,k,row; 625 PetscInt *ai = a->i,*ailen = a->ilen; 626 PetscErrorCode ierr; 627 PetscInt *aj = a->j; 628 MatScalar *aa = a->a,*ap; 629 630 PetscFunctionBegin; 631 for (k=0; k<m; k++) { /* loop over added rows */ 632 row = im[k]; 633 if (PetscUnlikelyDebug(n > a->imax[row])) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Preallocation for row %D does not match number of columns provided",n); 634 rp = aj + ai[row]; 635 ap = aa + ai[row]; 636 if (!A->was_assembled) { 637 ierr = PetscMemcpy(rp,in,n*sizeof(PetscInt));CHKERRQ(ierr); 638 } 639 if (!A->structure_only) { 640 if (v) { 641 ierr = PetscMemcpy(ap,v,n*sizeof(PetscScalar));CHKERRQ(ierr); 642 v += n; 643 } else { 644 ierr = PetscMemzero(ap,n*sizeof(PetscScalar));CHKERRQ(ierr); 645 } 646 } 647 ailen[row] = n; 648 a->nz += n; 649 } 650 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 651 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && m && n) A->offloadmask = PETSC_OFFLOAD_CPU; 652 #endif 653 PetscFunctionReturn(0); 654 } 655 656 657 PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 658 { 659 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 660 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 661 PetscInt *ai = a->i,*ailen = a->ilen; 662 MatScalar *ap,*aa = a->a; 663 664 PetscFunctionBegin; 665 for (k=0; k<m; k++) { /* loop over rows */ 666 row = im[k]; 667 if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */ 668 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); 669 rp = aj + ai[row]; ap = aa + ai[row]; 670 nrow = ailen[row]; 671 for (l=0; l<n; l++) { /* loop over columns */ 672 if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */ 673 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); 674 col = in[l]; 675 high = nrow; low = 0; /* assume unsorted */ 676 while (high-low > 5) { 677 t = (low+high)/2; 678 if (rp[t] > col) high = t; 679 else low = t; 680 } 681 for (i=low; i<high; i++) { 682 if (rp[i] > col) break; 683 if (rp[i] == col) { 684 *v++ = ap[i]; 685 goto finished; 686 } 687 } 688 *v++ = 0.0; 689 finished:; 690 } 691 } 692 PetscFunctionReturn(0); 693 } 694 695 PetscErrorCode MatView_SeqAIJ_Binary(Mat mat,PetscViewer viewer) 696 { 697 Mat_SeqAIJ *A = (Mat_SeqAIJ*)mat->data; 698 PetscInt header[4],M,N,m,nz,i; 699 PetscInt *rowlens; 700 PetscErrorCode ierr; 701 702 PetscFunctionBegin; 703 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 704 705 M = mat->rmap->N; 706 N = mat->cmap->N; 707 m = mat->rmap->n; 708 nz = A->nz; 709 710 /* write matrix header */ 711 header[0] = MAT_FILE_CLASSID; 712 header[1] = M; header[2] = N; header[3] = nz; 713 ierr = PetscViewerBinaryWrite(viewer,header,4,PETSC_INT);CHKERRQ(ierr); 714 715 /* fill in and store row lengths */ 716 ierr = PetscMalloc1(m,&rowlens);CHKERRQ(ierr); 717 for (i=0; i<m; i++) rowlens[i] = A->i[i+1] - A->i[i]; 718 ierr = PetscViewerBinaryWrite(viewer,rowlens,m,PETSC_INT);CHKERRQ(ierr); 719 ierr = PetscFree(rowlens);CHKERRQ(ierr); 720 /* store column indices */ 721 ierr = PetscViewerBinaryWrite(viewer,A->j,nz,PETSC_INT);CHKERRQ(ierr); 722 /* store nonzero values */ 723 ierr = PetscViewerBinaryWrite(viewer,A->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 724 725 /* write block size option to the viewer's .info file */ 726 ierr = MatView_Binary_BlockSizes(mat,viewer);CHKERRQ(ierr); 727 PetscFunctionReturn(0); 728 } 729 730 static PetscErrorCode MatView_SeqAIJ_ASCII_structonly(Mat A,PetscViewer viewer) 731 { 732 PetscErrorCode ierr; 733 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 734 PetscInt i,k,m=A->rmap->N; 735 736 PetscFunctionBegin; 737 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 738 for (i=0; i<m; i++) { 739 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 740 for (k=a->i[i]; k<a->i[i+1]; k++) { 741 ierr = PetscViewerASCIIPrintf(viewer," (%D) ",a->j[k]);CHKERRQ(ierr); 742 } 743 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 744 } 745 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 746 PetscFunctionReturn(0); 747 } 748 749 extern PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); 750 751 PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) 752 { 753 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 754 PetscErrorCode ierr; 755 PetscInt i,j,m = A->rmap->n; 756 const char *name; 757 PetscViewerFormat format; 758 759 PetscFunctionBegin; 760 if (A->structure_only) { 761 ierr = MatView_SeqAIJ_ASCII_structonly(A,viewer);CHKERRQ(ierr); 762 PetscFunctionReturn(0); 763 } 764 765 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 766 if (format == PETSC_VIEWER_ASCII_MATLAB) { 767 PetscInt nofinalvalue = 0; 768 if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-1))) { 769 /* Need a dummy value to ensure the dimension of the matrix. */ 770 nofinalvalue = 1; 771 } 772 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 773 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); 774 ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); 775 #if defined(PETSC_USE_COMPLEX) 776 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,4);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 777 #else 778 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 779 #endif 780 ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); 781 782 for (i=0; i<m; i++) { 783 for (j=a->i[i]; j<a->i[i+1]; j++) { 784 #if defined(PETSC_USE_COMPLEX) 785 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); 786 #else 787 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+1,(double)a->a[j]);CHKERRQ(ierr); 788 #endif 789 } 790 } 791 if (nofinalvalue) { 792 #if defined(PETSC_USE_COMPLEX) 793 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",m,A->cmap->n,0.,0.);CHKERRQ(ierr); 794 #else 795 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); 796 #endif 797 } 798 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 799 ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); 800 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 801 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 802 PetscFunctionReturn(0); 803 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 804 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 805 for (i=0; i<m; i++) { 806 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 807 for (j=a->i[i]; j<a->i[i+1]; j++) { 808 #if defined(PETSC_USE_COMPLEX) 809 if (PetscImaginaryPart(a->a[j]) > 0.0 && PetscRealPart(a->a[j]) != 0.0) { 810 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 811 } else if (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { 812 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 813 } else if (PetscRealPart(a->a[j]) != 0.0) { 814 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 815 } 816 #else 817 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr);} 818 #endif 819 } 820 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 821 } 822 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 823 } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { 824 PetscInt nzd=0,fshift=1,*sptr; 825 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 826 ierr = PetscMalloc1(m+1,&sptr);CHKERRQ(ierr); 827 for (i=0; i<m; i++) { 828 sptr[i] = nzd+1; 829 for (j=a->i[i]; j<a->i[i+1]; j++) { 830 if (a->j[j] >= i) { 831 #if defined(PETSC_USE_COMPLEX) 832 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; 833 #else 834 if (a->a[j] != 0.0) nzd++; 835 #endif 836 } 837 } 838 } 839 sptr[m] = nzd+1; 840 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); 841 for (i=0; i<m+1; i+=6) { 842 if (i+4<m) { 843 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); 844 } else if (i+3<m) { 845 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); 846 } else if (i+2<m) { 847 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]);CHKERRQ(ierr); 848 } else if (i+1<m) { 849 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2]);CHKERRQ(ierr); 850 } else if (i<m) { 851 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n",sptr[i],sptr[i+1]);CHKERRQ(ierr); 852 } else { 853 ierr = PetscViewerASCIIPrintf(viewer," %D\n",sptr[i]);CHKERRQ(ierr); 854 } 855 } 856 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 857 ierr = PetscFree(sptr);CHKERRQ(ierr); 858 for (i=0; i<m; i++) { 859 for (j=a->i[i]; j<a->i[i+1]; j++) { 860 if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} 861 } 862 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 863 } 864 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 865 for (i=0; i<m; i++) { 866 for (j=a->i[i]; j<a->i[i+1]; j++) { 867 if (a->j[j] >= i) { 868 #if defined(PETSC_USE_COMPLEX) 869 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { 870 ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 871 } 872 #else 873 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",(double)a->a[j]);CHKERRQ(ierr);} 874 #endif 875 } 876 } 877 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 878 } 879 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 880 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 881 PetscInt cnt = 0,jcnt; 882 PetscScalar value; 883 #if defined(PETSC_USE_COMPLEX) 884 PetscBool realonly = PETSC_TRUE; 885 886 for (i=0; i<a->i[m]; i++) { 887 if (PetscImaginaryPart(a->a[i]) != 0.0) { 888 realonly = PETSC_FALSE; 889 break; 890 } 891 } 892 #endif 893 894 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 895 for (i=0; i<m; i++) { 896 jcnt = 0; 897 for (j=0; j<A->cmap->n; j++) { 898 if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 899 value = a->a[cnt++]; 900 jcnt++; 901 } else { 902 value = 0.0; 903 } 904 #if defined(PETSC_USE_COMPLEX) 905 if (realonly) { 906 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)PetscRealPart(value));CHKERRQ(ierr); 907 } else { 908 ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",(double)PetscRealPart(value),(double)PetscImaginaryPart(value));CHKERRQ(ierr); 909 } 910 #else 911 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)value);CHKERRQ(ierr); 912 #endif 913 } 914 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 915 } 916 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 917 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 918 PetscInt fshift=1; 919 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 920 #if defined(PETSC_USE_COMPLEX) 921 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate complex general\n");CHKERRQ(ierr); 922 #else 923 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate real general\n");CHKERRQ(ierr); 924 #endif 925 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); 926 for (i=0; i<m; i++) { 927 for (j=a->i[i]; j<a->i[i+1]; j++) { 928 #if defined(PETSC_USE_COMPLEX) 929 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); 930 #else 931 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g\n", i+fshift, a->j[j]+fshift, (double)a->a[j]);CHKERRQ(ierr); 932 #endif 933 } 934 } 935 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 936 } else { 937 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 938 if (A->factortype) { 939 for (i=0; i<m; i++) { 940 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 941 /* L part */ 942 for (j=a->i[i]; j<a->i[i+1]; j++) { 943 #if defined(PETSC_USE_COMPLEX) 944 if (PetscImaginaryPart(a->a[j]) > 0.0) { 945 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 946 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 947 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 948 } else { 949 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 950 } 951 #else 952 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 953 #endif 954 } 955 /* diagonal */ 956 j = a->diag[i]; 957 #if defined(PETSC_USE_COMPLEX) 958 if (PetscImaginaryPart(a->a[j]) > 0.0) { 959 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); 960 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 961 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); 962 } else { 963 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(1.0/a->a[j]));CHKERRQ(ierr); 964 } 965 #else 966 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)(1.0/a->a[j]));CHKERRQ(ierr); 967 #endif 968 969 /* U part */ 970 for (j=a->diag[i+1]+1; j<a->diag[i]; j++) { 971 #if defined(PETSC_USE_COMPLEX) 972 if (PetscImaginaryPart(a->a[j]) > 0.0) { 973 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 974 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 975 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 976 } else { 977 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 978 } 979 #else 980 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 981 #endif 982 } 983 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 984 } 985 } else { 986 for (i=0; i<m; i++) { 987 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 988 for (j=a->i[i]; j<a->i[i+1]; j++) { 989 #if defined(PETSC_USE_COMPLEX) 990 if (PetscImaginaryPart(a->a[j]) > 0.0) { 991 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 992 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 993 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 994 } else { 995 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 996 } 997 #else 998 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 999 #endif 1000 } 1001 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1002 } 1003 } 1004 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1005 } 1006 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1007 PetscFunctionReturn(0); 1008 } 1009 1010 #include <petscdraw.h> 1011 PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 1012 { 1013 Mat A = (Mat) Aa; 1014 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1015 PetscErrorCode ierr; 1016 PetscInt i,j,m = A->rmap->n; 1017 int color; 1018 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 1019 PetscViewer viewer; 1020 PetscViewerFormat format; 1021 1022 PetscFunctionBegin; 1023 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 1024 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1025 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 1026 1027 /* loop over matrix elements drawing boxes */ 1028 1029 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 1030 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 1031 /* Blue for negative, Cyan for zero and Red for positive */ 1032 color = PETSC_DRAW_BLUE; 1033 for (i=0; i<m; i++) { 1034 y_l = m - i - 1.0; y_r = y_l + 1.0; 1035 for (j=a->i[i]; j<a->i[i+1]; j++) { 1036 x_l = a->j[j]; x_r = x_l + 1.0; 1037 if (PetscRealPart(a->a[j]) >= 0.) continue; 1038 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1039 } 1040 } 1041 color = PETSC_DRAW_CYAN; 1042 for (i=0; i<m; i++) { 1043 y_l = m - i - 1.0; y_r = y_l + 1.0; 1044 for (j=a->i[i]; j<a->i[i+1]; j++) { 1045 x_l = a->j[j]; x_r = x_l + 1.0; 1046 if (a->a[j] != 0.) continue; 1047 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1048 } 1049 } 1050 color = PETSC_DRAW_RED; 1051 for (i=0; i<m; i++) { 1052 y_l = m - i - 1.0; y_r = y_l + 1.0; 1053 for (j=a->i[i]; j<a->i[i+1]; j++) { 1054 x_l = a->j[j]; x_r = x_l + 1.0; 1055 if (PetscRealPart(a->a[j]) <= 0.) continue; 1056 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1057 } 1058 } 1059 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 1060 } else { 1061 /* use contour shading to indicate magnitude of values */ 1062 /* first determine max of all nonzero values */ 1063 PetscReal minv = 0.0, maxv = 0.0; 1064 PetscInt nz = a->nz, count = 0; 1065 PetscDraw popup; 1066 1067 for (i=0; i<nz; i++) { 1068 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 1069 } 1070 if (minv >= maxv) maxv = minv + PETSC_SMALL; 1071 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 1072 ierr = PetscDrawScalePopup(popup,minv,maxv);CHKERRQ(ierr); 1073 1074 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 1075 for (i=0; i<m; i++) { 1076 y_l = m - i - 1.0; 1077 y_r = y_l + 1.0; 1078 for (j=a->i[i]; j<a->i[i+1]; j++) { 1079 x_l = a->j[j]; 1080 x_r = x_l + 1.0; 1081 color = PetscDrawRealToColor(PetscAbsScalar(a->a[count]),minv,maxv); 1082 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1083 count++; 1084 } 1085 } 1086 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 1087 } 1088 PetscFunctionReturn(0); 1089 } 1090 1091 #include <petscdraw.h> 1092 PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) 1093 { 1094 PetscErrorCode ierr; 1095 PetscDraw draw; 1096 PetscReal xr,yr,xl,yl,h,w; 1097 PetscBool isnull; 1098 1099 PetscFunctionBegin; 1100 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1101 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1102 if (isnull) PetscFunctionReturn(0); 1103 1104 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 1105 xr += w; yr += h; xl = -w; yl = -h; 1106 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 1107 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 1108 ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); 1109 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 1110 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 1111 PetscFunctionReturn(0); 1112 } 1113 1114 PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) 1115 { 1116 PetscErrorCode ierr; 1117 PetscBool iascii,isbinary,isdraw; 1118 1119 PetscFunctionBegin; 1120 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1121 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1122 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1123 if (iascii) { 1124 ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); 1125 } else if (isbinary) { 1126 ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); 1127 } else if (isdraw) { 1128 ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); 1129 } 1130 ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); 1131 PetscFunctionReturn(0); 1132 } 1133 1134 PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 1135 { 1136 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1137 PetscErrorCode ierr; 1138 PetscInt fshift = 0,i,*ai = a->i,*aj = a->j,*imax = a->imax; 1139 PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; 1140 MatScalar *aa = a->a,*ap; 1141 PetscReal ratio = 0.6; 1142 1143 PetscFunctionBegin; 1144 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 1145 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1146 if (A->was_assembled && A->ass_nonzerostate == A->nonzerostate) PetscFunctionReturn(0); 1147 1148 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 1149 for (i=1; i<m; i++) { 1150 /* move each row back by the amount of empty slots (fshift) before it*/ 1151 fshift += imax[i-1] - ailen[i-1]; 1152 rmax = PetscMax(rmax,ailen[i]); 1153 if (fshift) { 1154 ip = aj + ai[i]; 1155 ap = aa + ai[i]; 1156 N = ailen[i]; 1157 ierr = PetscArraymove(ip-fshift,ip,N);CHKERRQ(ierr); 1158 if (!A->structure_only) { 1159 ierr = PetscArraymove(ap-fshift,ap,N);CHKERRQ(ierr); 1160 } 1161 } 1162 ai[i] = ai[i-1] + ailen[i-1]; 1163 } 1164 if (m) { 1165 fshift += imax[m-1] - ailen[m-1]; 1166 ai[m] = ai[m-1] + ailen[m-1]; 1167 } 1168 1169 /* reset ilen and imax for each row */ 1170 a->nonzerorowcnt = 0; 1171 if (A->structure_only) { 1172 ierr = PetscFree(a->imax);CHKERRQ(ierr); 1173 ierr = PetscFree(a->ilen);CHKERRQ(ierr); 1174 } else { /* !A->structure_only */ 1175 for (i=0; i<m; i++) { 1176 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1177 a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0); 1178 } 1179 } 1180 a->nz = ai[m]; 1181 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); 1182 1183 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1184 ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); 1185 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); 1186 ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); 1187 1188 A->info.mallocs += a->reallocs; 1189 a->reallocs = 0; 1190 A->info.nz_unneeded = (PetscReal)fshift; 1191 a->rmax = rmax; 1192 1193 if (!A->structure_only) { 1194 ierr = MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); 1195 } 1196 ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); 1197 PetscFunctionReturn(0); 1198 } 1199 1200 PetscErrorCode MatRealPart_SeqAIJ(Mat A) 1201 { 1202 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1203 PetscInt i,nz = a->nz; 1204 MatScalar *aa = a->a; 1205 PetscErrorCode ierr; 1206 1207 PetscFunctionBegin; 1208 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1209 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1210 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 1211 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED) A->offloadmask = PETSC_OFFLOAD_CPU; 1212 #endif 1213 PetscFunctionReturn(0); 1214 } 1215 1216 PetscErrorCode MatImaginaryPart_SeqAIJ(Mat A) 1217 { 1218 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1219 PetscInt i,nz = a->nz; 1220 MatScalar *aa = a->a; 1221 PetscErrorCode ierr; 1222 1223 PetscFunctionBegin; 1224 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1225 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1226 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 1227 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED) A->offloadmask = PETSC_OFFLOAD_CPU; 1228 #endif 1229 PetscFunctionReturn(0); 1230 } 1231 1232 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1233 { 1234 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1235 PetscErrorCode ierr; 1236 1237 PetscFunctionBegin; 1238 ierr = PetscArrayzero(a->a,a->i[A->rmap->n]);CHKERRQ(ierr); 1239 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1240 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 1241 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED) A->offloadmask = PETSC_OFFLOAD_CPU; 1242 #endif 1243 PetscFunctionReturn(0); 1244 } 1245 1246 PetscErrorCode MatDestroy_SeqAIJ(Mat A) 1247 { 1248 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1249 PetscErrorCode ierr; 1250 1251 PetscFunctionBegin; 1252 #if defined(PETSC_USE_LOG) 1253 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); 1254 #endif 1255 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1256 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1257 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1258 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1259 ierr = PetscFree(a->ibdiag);CHKERRQ(ierr); 1260 ierr = PetscFree(a->imax);CHKERRQ(ierr); 1261 ierr = PetscFree(a->ilen);CHKERRQ(ierr); 1262 ierr = PetscFree(a->ipre);CHKERRQ(ierr); 1263 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 1264 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1265 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1266 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1267 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1268 1269 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 1270 ierr = PetscFree(A->data);CHKERRQ(ierr); 1271 1272 /* MatMatMultNumeric_SeqAIJ_SeqAIJ_Sorted may allocate this. 1273 That function is so heavily used (sometimes in an hidden way through multnumeric function pointers) 1274 that is hard to properly add this data to the MatProduct data. We free it here to avoid 1275 users reusing the matrix object with different data to incur in obscure segmentation faults 1276 due to different matrix sizes */ 1277 ierr = PetscObjectCompose((PetscObject)A,"__PETSc__ab_dense",NULL);CHKERRQ(ierr); 1278 1279 ierr = PetscObjectChangeTypeName((PetscObject)A,NULL);CHKERRQ(ierr); 1280 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1281 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1282 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1283 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1284 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); 1285 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); 1286 1287 #if defined(PETSC_HAVE_CUDA) 1288 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijcusparse_C",NULL);CHKERRQ(ierr); 1289 ierr = PetscObjectComposeFunction((PetscObject)A,"MatProductSetFromOptions_seqaijcusparse_seqaij_C",NULL);CHKERRQ(ierr); 1290 #endif 1291 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijcrl_C",NULL);CHKERRQ(ierr); 1292 #if defined(PETSC_HAVE_ELEMENTAL) 1293 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_elemental_C",NULL);CHKERRQ(ierr); 1294 #endif 1295 #if defined(PETSC_HAVE_SCALAPACK) 1296 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_scalapack_C",NULL);CHKERRQ(ierr); 1297 #endif 1298 #if defined(PETSC_HAVE_HYPRE) 1299 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_hypre_C",NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)A,"MatProductSetFromOptions_transpose_seqaij_seqaij_C",NULL);CHKERRQ(ierr); 1301 #endif 1302 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1303 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsell_C",NULL);CHKERRQ(ierr); 1304 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_is_C",NULL);CHKERRQ(ierr); 1305 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1306 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1307 ierr = PetscObjectComposeFunction((PetscObject)A,"MatResetPreallocation_C",NULL);CHKERRQ(ierr); 1308 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1309 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1310 ierr = PetscObjectComposeFunction((PetscObject)A,"MatProductSetFromOptions_is_seqaij_C",NULL);CHKERRQ(ierr); 1311 ierr = PetscObjectComposeFunction((PetscObject)A,"MatProductSetFromOptions_seqdense_seqaij_C",NULL);CHKERRQ(ierr); 1312 ierr = PetscObjectComposeFunction((PetscObject)A,"MatProductSetFromOptions_seqaij_seqaij_C",NULL);CHKERRQ(ierr); 1313 PetscFunctionReturn(0); 1314 } 1315 1316 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1317 { 1318 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1319 PetscErrorCode ierr; 1320 1321 PetscFunctionBegin; 1322 switch (op) { 1323 case MAT_ROW_ORIENTED: 1324 a->roworiented = flg; 1325 break; 1326 case MAT_KEEP_NONZERO_PATTERN: 1327 a->keepnonzeropattern = flg; 1328 break; 1329 case MAT_NEW_NONZERO_LOCATIONS: 1330 a->nonew = (flg ? 0 : 1); 1331 break; 1332 case MAT_NEW_NONZERO_LOCATION_ERR: 1333 a->nonew = (flg ? -1 : 0); 1334 break; 1335 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1336 a->nonew = (flg ? -2 : 0); 1337 break; 1338 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1339 a->nounused = (flg ? -1 : 0); 1340 break; 1341 case MAT_IGNORE_ZERO_ENTRIES: 1342 a->ignorezeroentries = flg; 1343 break; 1344 case MAT_SPD: 1345 case MAT_SYMMETRIC: 1346 case MAT_STRUCTURALLY_SYMMETRIC: 1347 case MAT_HERMITIAN: 1348 case MAT_SYMMETRY_ETERNAL: 1349 case MAT_STRUCTURE_ONLY: 1350 /* These options are handled directly by MatSetOption() */ 1351 break; 1352 case MAT_NEW_DIAGONALS: 1353 case MAT_IGNORE_OFF_PROC_ENTRIES: 1354 case MAT_USE_HASH_TABLE: 1355 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1356 break; 1357 case MAT_USE_INODES: 1358 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1359 break; 1360 case MAT_SUBMAT_SINGLEIS: 1361 A->submat_singleis = flg; 1362 break; 1363 case MAT_SORTED_FULL: 1364 if (flg) A->ops->setvalues = MatSetValues_SeqAIJ_SortedFull; 1365 else A->ops->setvalues = MatSetValues_SeqAIJ; 1366 break; 1367 default: 1368 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1369 } 1370 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1371 PetscFunctionReturn(0); 1372 } 1373 1374 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1375 { 1376 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1377 PetscErrorCode ierr; 1378 PetscInt i,j,n,*ai=a->i,*aj=a->j; 1379 PetscScalar *aa=a->a,*x; 1380 1381 PetscFunctionBegin; 1382 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1383 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1384 1385 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1386 PetscInt *diag=a->diag; 1387 ierr = VecGetArrayWrite(v,&x);CHKERRQ(ierr); 1388 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1389 ierr = VecRestoreArrayWrite(v,&x);CHKERRQ(ierr); 1390 PetscFunctionReturn(0); 1391 } 1392 1393 ierr = VecGetArrayWrite(v,&x);CHKERRQ(ierr); 1394 for (i=0; i<n; i++) { 1395 x[i] = 0.0; 1396 for (j=ai[i]; j<ai[i+1]; j++) { 1397 if (aj[j] == i) { 1398 x[i] = aa[j]; 1399 break; 1400 } 1401 } 1402 } 1403 ierr = VecRestoreArrayWrite(v,&x);CHKERRQ(ierr); 1404 PetscFunctionReturn(0); 1405 } 1406 1407 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1408 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1409 { 1410 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1411 PetscScalar *y; 1412 const PetscScalar *x; 1413 PetscErrorCode ierr; 1414 PetscInt m = A->rmap->n; 1415 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1416 const MatScalar *v; 1417 PetscScalar alpha; 1418 PetscInt n,i,j; 1419 const PetscInt *idx,*ii,*ridx=NULL; 1420 Mat_CompressedRow cprow = a->compressedrow; 1421 PetscBool usecprow = cprow.use; 1422 #endif 1423 1424 PetscFunctionBegin; 1425 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1426 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1427 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1428 1429 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1430 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1431 #else 1432 if (usecprow) { 1433 m = cprow.nrows; 1434 ii = cprow.i; 1435 ridx = cprow.rindex; 1436 } else { 1437 ii = a->i; 1438 } 1439 for (i=0; i<m; i++) { 1440 idx = a->j + ii[i]; 1441 v = a->a + ii[i]; 1442 n = ii[i+1] - ii[i]; 1443 if (usecprow) { 1444 alpha = x[ridx[i]]; 1445 } else { 1446 alpha = x[i]; 1447 } 1448 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1449 } 1450 #endif 1451 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1452 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1453 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1454 PetscFunctionReturn(0); 1455 } 1456 1457 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1458 { 1459 PetscErrorCode ierr; 1460 1461 PetscFunctionBegin; 1462 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1463 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1464 PetscFunctionReturn(0); 1465 } 1466 1467 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1468 1469 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1470 { 1471 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1472 PetscScalar *y; 1473 const PetscScalar *x; 1474 const MatScalar *aa; 1475 PetscErrorCode ierr; 1476 PetscInt m=A->rmap->n; 1477 const PetscInt *aj,*ii,*ridx=NULL; 1478 PetscInt n,i; 1479 PetscScalar sum; 1480 PetscBool usecprow=a->compressedrow.use; 1481 1482 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1483 #pragma disjoint(*x,*y,*aa) 1484 #endif 1485 1486 PetscFunctionBegin; 1487 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1488 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1489 ii = a->i; 1490 if (usecprow) { /* use compressed row format */ 1491 ierr = PetscArrayzero(y,m);CHKERRQ(ierr); 1492 m = a->compressedrow.nrows; 1493 ii = a->compressedrow.i; 1494 ridx = a->compressedrow.rindex; 1495 for (i=0; i<m; i++) { 1496 n = ii[i+1] - ii[i]; 1497 aj = a->j + ii[i]; 1498 aa = a->a + ii[i]; 1499 sum = 0.0; 1500 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1501 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1502 y[*ridx++] = sum; 1503 } 1504 } else { /* do not use compressed row format */ 1505 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1506 aj = a->j; 1507 aa = a->a; 1508 fortranmultaij_(&m,x,ii,aj,aa,y); 1509 #else 1510 for (i=0; i<m; i++) { 1511 n = ii[i+1] - ii[i]; 1512 aj = a->j + ii[i]; 1513 aa = a->a + ii[i]; 1514 sum = 0.0; 1515 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1516 y[i] = sum; 1517 } 1518 #endif 1519 } 1520 ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); 1521 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1522 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1523 PetscFunctionReturn(0); 1524 } 1525 1526 PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) 1527 { 1528 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1529 PetscScalar *y; 1530 const PetscScalar *x; 1531 const MatScalar *aa; 1532 PetscErrorCode ierr; 1533 PetscInt m=A->rmap->n; 1534 const PetscInt *aj,*ii,*ridx=NULL; 1535 PetscInt n,i,nonzerorow=0; 1536 PetscScalar sum; 1537 PetscBool usecprow=a->compressedrow.use; 1538 1539 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1540 #pragma disjoint(*x,*y,*aa) 1541 #endif 1542 1543 PetscFunctionBegin; 1544 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1545 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1546 if (usecprow) { /* use compressed row format */ 1547 m = a->compressedrow.nrows; 1548 ii = a->compressedrow.i; 1549 ridx = a->compressedrow.rindex; 1550 for (i=0; i<m; i++) { 1551 n = ii[i+1] - ii[i]; 1552 aj = a->j + ii[i]; 1553 aa = a->a + ii[i]; 1554 sum = 0.0; 1555 nonzerorow += (n>0); 1556 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1557 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1558 y[*ridx++] = sum; 1559 } 1560 } else { /* do not use compressed row format */ 1561 ii = a->i; 1562 for (i=0; i<m; i++) { 1563 n = ii[i+1] - ii[i]; 1564 aj = a->j + ii[i]; 1565 aa = a->a + ii[i]; 1566 sum = 0.0; 1567 nonzerorow += (n>0); 1568 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1569 y[i] = sum; 1570 } 1571 } 1572 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1573 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1574 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1575 PetscFunctionReturn(0); 1576 } 1577 1578 PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1579 { 1580 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1581 PetscScalar *y,*z; 1582 const PetscScalar *x; 1583 const MatScalar *aa; 1584 PetscErrorCode ierr; 1585 PetscInt m = A->rmap->n,*aj,*ii; 1586 PetscInt n,i,*ridx=NULL; 1587 PetscScalar sum; 1588 PetscBool usecprow=a->compressedrow.use; 1589 1590 PetscFunctionBegin; 1591 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1592 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1593 if (usecprow) { /* use compressed row format */ 1594 if (zz != yy) { 1595 ierr = PetscArraycpy(z,y,m);CHKERRQ(ierr); 1596 } 1597 m = a->compressedrow.nrows; 1598 ii = a->compressedrow.i; 1599 ridx = a->compressedrow.rindex; 1600 for (i=0; i<m; i++) { 1601 n = ii[i+1] - ii[i]; 1602 aj = a->j + ii[i]; 1603 aa = a->a + ii[i]; 1604 sum = y[*ridx]; 1605 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1606 z[*ridx++] = sum; 1607 } 1608 } else { /* do not use compressed row format */ 1609 ii = a->i; 1610 for (i=0; i<m; i++) { 1611 n = ii[i+1] - ii[i]; 1612 aj = a->j + ii[i]; 1613 aa = a->a + ii[i]; 1614 sum = y[i]; 1615 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1616 z[i] = sum; 1617 } 1618 } 1619 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1620 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1621 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1622 PetscFunctionReturn(0); 1623 } 1624 1625 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 1626 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1627 { 1628 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1629 PetscScalar *y,*z; 1630 const PetscScalar *x; 1631 const MatScalar *aa; 1632 PetscErrorCode ierr; 1633 const PetscInt *aj,*ii,*ridx=NULL; 1634 PetscInt m = A->rmap->n,n,i; 1635 PetscScalar sum; 1636 PetscBool usecprow=a->compressedrow.use; 1637 1638 PetscFunctionBegin; 1639 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1640 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1641 if (usecprow) { /* use compressed row format */ 1642 if (zz != yy) { 1643 ierr = PetscArraycpy(z,y,m);CHKERRQ(ierr); 1644 } 1645 m = a->compressedrow.nrows; 1646 ii = a->compressedrow.i; 1647 ridx = a->compressedrow.rindex; 1648 for (i=0; i<m; i++) { 1649 n = ii[i+1] - ii[i]; 1650 aj = a->j + ii[i]; 1651 aa = a->a + ii[i]; 1652 sum = y[*ridx]; 1653 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1654 z[*ridx++] = sum; 1655 } 1656 } else { /* do not use compressed row format */ 1657 ii = a->i; 1658 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1659 aj = a->j; 1660 aa = a->a; 1661 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1662 #else 1663 for (i=0; i<m; i++) { 1664 n = ii[i+1] - ii[i]; 1665 aj = a->j + ii[i]; 1666 aa = a->a + ii[i]; 1667 sum = y[i]; 1668 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1669 z[i] = sum; 1670 } 1671 #endif 1672 } 1673 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1674 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1675 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1676 PetscFunctionReturn(0); 1677 } 1678 1679 /* 1680 Adds diagonal pointers to sparse matrix structure. 1681 */ 1682 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1683 { 1684 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1685 PetscErrorCode ierr; 1686 PetscInt i,j,m = A->rmap->n; 1687 1688 PetscFunctionBegin; 1689 if (!a->diag) { 1690 ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); 1691 ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); 1692 } 1693 for (i=0; i<A->rmap->n; i++) { 1694 a->diag[i] = a->i[i+1]; 1695 for (j=a->i[i]; j<a->i[i+1]; j++) { 1696 if (a->j[j] == i) { 1697 a->diag[i] = j; 1698 break; 1699 } 1700 } 1701 } 1702 PetscFunctionReturn(0); 1703 } 1704 1705 PetscErrorCode MatShift_SeqAIJ(Mat A,PetscScalar v) 1706 { 1707 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1708 const PetscInt *diag = (const PetscInt*)a->diag; 1709 const PetscInt *ii = (const PetscInt*) a->i; 1710 PetscInt i,*mdiag = NULL; 1711 PetscErrorCode ierr; 1712 PetscInt cnt = 0; /* how many diagonals are missing */ 1713 1714 PetscFunctionBegin; 1715 if (!A->preallocated || !a->nz) { 1716 ierr = MatSeqAIJSetPreallocation(A,1,NULL);CHKERRQ(ierr); 1717 ierr = MatShift_Basic(A,v);CHKERRQ(ierr); 1718 PetscFunctionReturn(0); 1719 } 1720 1721 if (a->diagonaldense) { 1722 cnt = 0; 1723 } else { 1724 ierr = PetscCalloc1(A->rmap->n,&mdiag);CHKERRQ(ierr); 1725 for (i=0; i<A->rmap->n; i++) { 1726 if (diag[i] >= ii[i+1]) { 1727 cnt++; 1728 mdiag[i] = 1; 1729 } 1730 } 1731 } 1732 if (!cnt) { 1733 ierr = MatShift_Basic(A,v);CHKERRQ(ierr); 1734 } else { 1735 PetscScalar *olda = a->a; /* preserve pointers to current matrix nonzeros structure and values */ 1736 PetscInt *oldj = a->j, *oldi = a->i; 1737 PetscBool singlemalloc = a->singlemalloc,free_a = a->free_a,free_ij = a->free_ij; 1738 1739 a->a = NULL; 1740 a->j = NULL; 1741 a->i = NULL; 1742 /* increase the values in imax for each row where a diagonal is being inserted then reallocate the matrix data structures */ 1743 for (i=0; i<A->rmap->n; i++) { 1744 a->imax[i] += mdiag[i]; 1745 a->imax[i] = PetscMin(a->imax[i],A->cmap->n); 1746 } 1747 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,0,a->imax);CHKERRQ(ierr); 1748 1749 /* copy old values into new matrix data structure */ 1750 for (i=0; i<A->rmap->n; i++) { 1751 ierr = MatSetValues(A,1,&i,a->imax[i] - mdiag[i],&oldj[oldi[i]],&olda[oldi[i]],ADD_VALUES);CHKERRQ(ierr); 1752 if (i < A->cmap->n) { 1753 ierr = MatSetValue(A,i,i,v,ADD_VALUES);CHKERRQ(ierr); 1754 } 1755 } 1756 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1757 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1758 if (singlemalloc) { 1759 ierr = PetscFree3(olda,oldj,oldi);CHKERRQ(ierr); 1760 } else { 1761 if (free_a) {ierr = PetscFree(olda);CHKERRQ(ierr);} 1762 if (free_ij) {ierr = PetscFree(oldj);CHKERRQ(ierr);} 1763 if (free_ij) {ierr = PetscFree(oldi);CHKERRQ(ierr);} 1764 } 1765 } 1766 ierr = PetscFree(mdiag);CHKERRQ(ierr); 1767 a->diagonaldense = PETSC_TRUE; 1768 PetscFunctionReturn(0); 1769 } 1770 1771 /* 1772 Checks for missing diagonals 1773 */ 1774 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) 1775 { 1776 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1777 PetscInt *diag,*ii = a->i,i; 1778 PetscErrorCode ierr; 1779 1780 PetscFunctionBegin; 1781 *missing = PETSC_FALSE; 1782 if (A->rmap->n > 0 && !ii) { 1783 *missing = PETSC_TRUE; 1784 if (d) *d = 0; 1785 ierr = PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n");CHKERRQ(ierr); 1786 } else { 1787 PetscInt n; 1788 n = PetscMin(A->rmap->n, A->cmap->n); 1789 diag = a->diag; 1790 for (i=0; i<n; i++) { 1791 if (diag[i] >= ii[i+1]) { 1792 *missing = PETSC_TRUE; 1793 if (d) *d = i; 1794 ierr = PetscInfo1(A,"Matrix is missing diagonal number %D\n",i);CHKERRQ(ierr); 1795 break; 1796 } 1797 } 1798 } 1799 PetscFunctionReturn(0); 1800 } 1801 1802 #include <petscblaslapack.h> 1803 #include <petsc/private/kernels/blockinvert.h> 1804 1805 /* 1806 Note that values is allocated externally by the PC and then passed into this routine 1807 */ 1808 PetscErrorCode MatInvertVariableBlockDiagonal_SeqAIJ(Mat A,PetscInt nblocks,const PetscInt *bsizes,PetscScalar *diag) 1809 { 1810 PetscErrorCode ierr; 1811 PetscInt n = A->rmap->n, i, ncnt = 0, *indx,j,bsizemax = 0,*v_pivots; 1812 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 1813 const PetscReal shift = 0.0; 1814 PetscInt ipvt[5]; 1815 PetscScalar work[25],*v_work; 1816 1817 PetscFunctionBegin; 1818 allowzeropivot = PetscNot(A->erroriffailure); 1819 for (i=0; i<nblocks; i++) ncnt += bsizes[i]; 1820 if (ncnt != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Total blocksizes %D doesn't match number matrix rows %D",ncnt,n); 1821 for (i=0; i<nblocks; i++) { 1822 bsizemax = PetscMax(bsizemax,bsizes[i]); 1823 } 1824 ierr = PetscMalloc1(bsizemax,&indx);CHKERRQ(ierr); 1825 if (bsizemax > 7) { 1826 ierr = PetscMalloc2(bsizemax,&v_work,bsizemax,&v_pivots);CHKERRQ(ierr); 1827 } 1828 ncnt = 0; 1829 for (i=0; i<nblocks; i++) { 1830 for (j=0; j<bsizes[i]; j++) indx[j] = ncnt+j; 1831 ierr = MatGetValues(A,bsizes[i],indx,bsizes[i],indx,diag);CHKERRQ(ierr); 1832 switch (bsizes[i]) { 1833 case 1: 1834 *diag = 1.0/(*diag); 1835 break; 1836 case 2: 1837 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1838 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1839 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 1840 break; 1841 case 3: 1842 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1843 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1844 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 1845 break; 1846 case 4: 1847 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1848 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1849 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 1850 break; 1851 case 5: 1852 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1853 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1854 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 1855 break; 1856 case 6: 1857 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1858 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1859 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 1860 break; 1861 case 7: 1862 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1863 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1864 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 1865 break; 1866 default: 1867 ierr = PetscKernel_A_gets_inverse_A(bsizes[i],diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1868 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1869 ierr = PetscKernel_A_gets_transpose_A_N(diag,bsizes[i]);CHKERRQ(ierr); 1870 } 1871 ncnt += bsizes[i]; 1872 diag += bsizes[i]*bsizes[i]; 1873 } 1874 if (bsizemax > 7) { 1875 ierr = PetscFree2(v_work,v_pivots);CHKERRQ(ierr); 1876 } 1877 ierr = PetscFree(indx);CHKERRQ(ierr); 1878 PetscFunctionReturn(0); 1879 } 1880 1881 /* 1882 Negative shift indicates do not generate an error if there is a zero diagonal, just invert it anyways 1883 */ 1884 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1885 { 1886 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1887 PetscErrorCode ierr; 1888 PetscInt i,*diag,m = A->rmap->n; 1889 MatScalar *v = a->a; 1890 PetscScalar *idiag,*mdiag; 1891 1892 PetscFunctionBegin; 1893 if (a->idiagvalid) PetscFunctionReturn(0); 1894 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1895 diag = a->diag; 1896 if (!a->idiag) { 1897 ierr = PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);CHKERRQ(ierr); 1898 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1899 v = a->a; 1900 } 1901 mdiag = a->mdiag; 1902 idiag = a->idiag; 1903 1904 if (omega == 1.0 && PetscRealPart(fshift) <= 0.0) { 1905 for (i=0; i<m; i++) { 1906 mdiag[i] = v[diag[i]]; 1907 if (!PetscAbsScalar(mdiag[i])) { /* zero diagonal */ 1908 if (PetscRealPart(fshift)) { 1909 ierr = PetscInfo1(A,"Zero diagonal on row %D\n",i);CHKERRQ(ierr); 1910 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1911 A->factorerror_zeropivot_value = 0.0; 1912 A->factorerror_zeropivot_row = i; 1913 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1914 } 1915 idiag[i] = 1.0/v[diag[i]]; 1916 } 1917 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1918 } else { 1919 for (i=0; i<m; i++) { 1920 mdiag[i] = v[diag[i]]; 1921 idiag[i] = omega/(fshift + v[diag[i]]); 1922 } 1923 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1924 } 1925 a->idiagvalid = PETSC_TRUE; 1926 PetscFunctionReturn(0); 1927 } 1928 1929 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1930 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1931 { 1932 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1933 PetscScalar *x,d,sum,*t,scale; 1934 const MatScalar *v,*idiag=NULL,*mdiag; 1935 const PetscScalar *b, *bs,*xb, *ts; 1936 PetscErrorCode ierr; 1937 PetscInt n,m = A->rmap->n,i; 1938 const PetscInt *idx,*diag; 1939 1940 PetscFunctionBegin; 1941 its = its*lits; 1942 1943 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1944 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1945 a->fshift = fshift; 1946 a->omega = omega; 1947 1948 diag = a->diag; 1949 t = a->ssor_work; 1950 idiag = a->idiag; 1951 mdiag = a->mdiag; 1952 1953 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1954 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1955 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1956 if (flag == SOR_APPLY_UPPER) { 1957 /* apply (U + D/omega) to the vector */ 1958 bs = b; 1959 for (i=0; i<m; i++) { 1960 d = fshift + mdiag[i]; 1961 n = a->i[i+1] - diag[i] - 1; 1962 idx = a->j + diag[i] + 1; 1963 v = a->a + diag[i] + 1; 1964 sum = b[i]*d/omega; 1965 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1966 x[i] = sum; 1967 } 1968 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1969 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1970 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1971 PetscFunctionReturn(0); 1972 } 1973 1974 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1975 else if (flag & SOR_EISENSTAT) { 1976 /* Let A = L + U + D; where L is lower triangular, 1977 U is upper triangular, E = D/omega; This routine applies 1978 1979 (L + E)^{-1} A (U + E)^{-1} 1980 1981 to a vector efficiently using Eisenstat's trick. 1982 */ 1983 scale = (2.0/omega) - 1.0; 1984 1985 /* x = (E + U)^{-1} b */ 1986 for (i=m-1; i>=0; i--) { 1987 n = a->i[i+1] - diag[i] - 1; 1988 idx = a->j + diag[i] + 1; 1989 v = a->a + diag[i] + 1; 1990 sum = b[i]; 1991 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1992 x[i] = sum*idiag[i]; 1993 } 1994 1995 /* t = b - (2*E - D)x */ 1996 v = a->a; 1997 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1998 1999 /* t = (E + L)^{-1}t */ 2000 ts = t; 2001 diag = a->diag; 2002 for (i=0; i<m; i++) { 2003 n = diag[i] - a->i[i]; 2004 idx = a->j + a->i[i]; 2005 v = a->a + a->i[i]; 2006 sum = t[i]; 2007 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 2008 t[i] = sum*idiag[i]; 2009 /* x = x + t */ 2010 x[i] += t[i]; 2011 } 2012 2013 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 2014 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2015 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2016 PetscFunctionReturn(0); 2017 } 2018 if (flag & SOR_ZERO_INITIAL_GUESS) { 2019 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 2020 for (i=0; i<m; i++) { 2021 n = diag[i] - a->i[i]; 2022 idx = a->j + a->i[i]; 2023 v = a->a + a->i[i]; 2024 sum = b[i]; 2025 PetscSparseDenseMinusDot(sum,x,v,idx,n); 2026 t[i] = sum; 2027 x[i] = sum*idiag[i]; 2028 } 2029 xb = t; 2030 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2031 } else xb = b; 2032 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 2033 for (i=m-1; i>=0; i--) { 2034 n = a->i[i+1] - diag[i] - 1; 2035 idx = a->j + diag[i] + 1; 2036 v = a->a + diag[i] + 1; 2037 sum = xb[i]; 2038 PetscSparseDenseMinusDot(sum,x,v,idx,n); 2039 if (xb == b) { 2040 x[i] = sum*idiag[i]; 2041 } else { 2042 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 2043 } 2044 } 2045 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 2046 } 2047 its--; 2048 } 2049 while (its--) { 2050 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 2051 for (i=0; i<m; i++) { 2052 /* lower */ 2053 n = diag[i] - a->i[i]; 2054 idx = a->j + a->i[i]; 2055 v = a->a + a->i[i]; 2056 sum = b[i]; 2057 PetscSparseDenseMinusDot(sum,x,v,idx,n); 2058 t[i] = sum; /* save application of the lower-triangular part */ 2059 /* upper */ 2060 n = a->i[i+1] - diag[i] - 1; 2061 idx = a->j + diag[i] + 1; 2062 v = a->a + diag[i] + 1; 2063 PetscSparseDenseMinusDot(sum,x,v,idx,n); 2064 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 2065 } 2066 xb = t; 2067 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 2068 } else xb = b; 2069 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 2070 for (i=m-1; i>=0; i--) { 2071 sum = xb[i]; 2072 if (xb == b) { 2073 /* whole matrix (no checkpointing available) */ 2074 n = a->i[i+1] - a->i[i]; 2075 idx = a->j + a->i[i]; 2076 v = a->a + a->i[i]; 2077 PetscSparseDenseMinusDot(sum,x,v,idx,n); 2078 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 2079 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 2080 n = a->i[i+1] - diag[i] - 1; 2081 idx = a->j + diag[i] + 1; 2082 v = a->a + diag[i] + 1; 2083 PetscSparseDenseMinusDot(sum,x,v,idx,n); 2084 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 2085 } 2086 } 2087 if (xb == b) { 2088 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 2089 } else { 2090 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 2091 } 2092 } 2093 } 2094 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 2095 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 2096 PetscFunctionReturn(0); 2097 } 2098 2099 2100 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 2101 { 2102 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2103 2104 PetscFunctionBegin; 2105 info->block_size = 1.0; 2106 info->nz_allocated = a->maxnz; 2107 info->nz_used = a->nz; 2108 info->nz_unneeded = (a->maxnz - a->nz); 2109 info->assemblies = A->num_ass; 2110 info->mallocs = A->info.mallocs; 2111 info->memory = ((PetscObject)A)->mem; 2112 if (A->factortype) { 2113 info->fill_ratio_given = A->info.fill_ratio_given; 2114 info->fill_ratio_needed = A->info.fill_ratio_needed; 2115 info->factor_mallocs = A->info.factor_mallocs; 2116 } else { 2117 info->fill_ratio_given = 0; 2118 info->fill_ratio_needed = 0; 2119 info->factor_mallocs = 0; 2120 } 2121 PetscFunctionReturn(0); 2122 } 2123 2124 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 2125 { 2126 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2127 PetscInt i,m = A->rmap->n - 1; 2128 PetscErrorCode ierr; 2129 const PetscScalar *xx; 2130 PetscScalar *bb; 2131 PetscInt d = 0; 2132 2133 PetscFunctionBegin; 2134 if (x && b) { 2135 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 2136 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 2137 for (i=0; i<N; i++) { 2138 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2139 if (rows[i] >= A->cmap->n) continue; 2140 bb[rows[i]] = diag*xx[rows[i]]; 2141 } 2142 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2143 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2144 } 2145 2146 if (a->keepnonzeropattern) { 2147 for (i=0; i<N; i++) { 2148 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2149 ierr = PetscArrayzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]);CHKERRQ(ierr); 2150 } 2151 if (diag != 0.0) { 2152 for (i=0; i<N; i++) { 2153 d = rows[i]; 2154 if (rows[i] >= A->cmap->n) continue; 2155 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); 2156 } 2157 for (i=0; i<N; i++) { 2158 if (rows[i] >= A->cmap->n) continue; 2159 a->a[a->diag[rows[i]]] = diag; 2160 } 2161 } 2162 } else { 2163 if (diag != 0.0) { 2164 for (i=0; i<N; i++) { 2165 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2166 if (a->ilen[rows[i]] > 0) { 2167 if (rows[i] >= A->cmap->n) { 2168 a->ilen[rows[i]] = 0; 2169 } else { 2170 a->ilen[rows[i]] = 1; 2171 a->a[a->i[rows[i]]] = diag; 2172 a->j[a->i[rows[i]]] = rows[i]; 2173 } 2174 } else if (rows[i] < A->cmap->n) { /* in case row was completely empty */ 2175 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 2176 } 2177 } 2178 } else { 2179 for (i=0; i<N; i++) { 2180 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2181 a->ilen[rows[i]] = 0; 2182 } 2183 } 2184 A->nonzerostate++; 2185 } 2186 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2187 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED) A->offloadmask = PETSC_OFFLOAD_CPU; 2188 #endif 2189 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2190 PetscFunctionReturn(0); 2191 } 2192 2193 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 2194 { 2195 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2196 PetscInt i,j,m = A->rmap->n - 1,d = 0; 2197 PetscErrorCode ierr; 2198 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 2199 const PetscScalar *xx; 2200 PetscScalar *bb; 2201 2202 PetscFunctionBegin; 2203 if (x && b) { 2204 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 2205 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 2206 vecs = PETSC_TRUE; 2207 } 2208 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 2209 for (i=0; i<N; i++) { 2210 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2211 ierr = PetscArrayzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]);CHKERRQ(ierr); 2212 2213 zeroed[rows[i]] = PETSC_TRUE; 2214 } 2215 for (i=0; i<A->rmap->n; i++) { 2216 if (!zeroed[i]) { 2217 for (j=a->i[i]; j<a->i[i+1]; j++) { 2218 if (a->j[j] < A->rmap->n && zeroed[a->j[j]]) { 2219 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 2220 a->a[j] = 0.0; 2221 } 2222 } 2223 } else if (vecs && i < A->cmap->N) bb[i] = diag*xx[i]; 2224 } 2225 if (x && b) { 2226 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2227 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2228 } 2229 ierr = PetscFree(zeroed);CHKERRQ(ierr); 2230 if (diag != 0.0) { 2231 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 2232 if (missing) { 2233 for (i=0; i<N; i++) { 2234 if (rows[i] >= A->cmap->N) continue; 2235 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]); 2236 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 2237 } 2238 } else { 2239 for (i=0; i<N; i++) { 2240 a->a[a->diag[rows[i]]] = diag; 2241 } 2242 } 2243 } 2244 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2245 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED) A->offloadmask = PETSC_OFFLOAD_CPU; 2246 #endif 2247 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2248 PetscFunctionReturn(0); 2249 } 2250 2251 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2252 { 2253 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2254 PetscInt *itmp; 2255 2256 PetscFunctionBegin; 2257 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 2258 2259 *nz = a->i[row+1] - a->i[row]; 2260 if (v) *v = a->a + a->i[row]; 2261 if (idx) { 2262 itmp = a->j + a->i[row]; 2263 if (*nz) *idx = itmp; 2264 else *idx = NULL; 2265 } 2266 PetscFunctionReturn(0); 2267 } 2268 2269 /* remove this function? */ 2270 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2271 { 2272 PetscFunctionBegin; 2273 PetscFunctionReturn(0); 2274 } 2275 2276 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 2277 { 2278 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2279 MatScalar *v = a->a; 2280 PetscReal sum = 0.0; 2281 PetscErrorCode ierr; 2282 PetscInt i,j; 2283 2284 PetscFunctionBegin; 2285 if (type == NORM_FROBENIUS) { 2286 #if defined(PETSC_USE_REAL___FP16) 2287 PetscBLASInt one = 1,nz = a->nz; 2288 *nrm = BLASnrm2_(&nz,v,&one); 2289 #else 2290 for (i=0; i<a->nz; i++) { 2291 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2292 } 2293 *nrm = PetscSqrtReal(sum); 2294 #endif 2295 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 2296 } else if (type == NORM_1) { 2297 PetscReal *tmp; 2298 PetscInt *jj = a->j; 2299 ierr = PetscCalloc1(A->cmap->n+1,&tmp);CHKERRQ(ierr); 2300 *nrm = 0.0; 2301 for (j=0; j<a->nz; j++) { 2302 tmp[*jj++] += PetscAbsScalar(*v); v++; 2303 } 2304 for (j=0; j<A->cmap->n; j++) { 2305 if (tmp[j] > *nrm) *nrm = tmp[j]; 2306 } 2307 ierr = PetscFree(tmp);CHKERRQ(ierr); 2308 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 2309 } else if (type == NORM_INFINITY) { 2310 *nrm = 0.0; 2311 for (j=0; j<A->rmap->n; j++) { 2312 v = a->a + a->i[j]; 2313 sum = 0.0; 2314 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 2315 sum += PetscAbsScalar(*v); v++; 2316 } 2317 if (sum > *nrm) *nrm = sum; 2318 } 2319 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 2320 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 2321 PetscFunctionReturn(0); 2322 } 2323 2324 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 2325 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 2326 { 2327 PetscErrorCode ierr; 2328 PetscInt i,j,anzj; 2329 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 2330 PetscInt an=A->cmap->N,am=A->rmap->N; 2331 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 2332 2333 PetscFunctionBegin; 2334 /* Allocate space for symbolic transpose info and work array */ 2335 ierr = PetscCalloc1(an+1,&ati);CHKERRQ(ierr); 2336 ierr = PetscMalloc1(ai[am],&atj);CHKERRQ(ierr); 2337 ierr = PetscMalloc1(an,&atfill);CHKERRQ(ierr); 2338 2339 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 2340 /* Note: offset by 1 for fast conversion into csr format. */ 2341 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2342 /* Form ati for csr format of A^T. */ 2343 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2344 2345 /* Copy ati into atfill so we have locations of the next free space in atj */ 2346 ierr = PetscArraycpy(atfill,ati,an);CHKERRQ(ierr); 2347 2348 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2349 for (i=0;i<am;i++) { 2350 anzj = ai[i+1] - ai[i]; 2351 for (j=0;j<anzj;j++) { 2352 atj[atfill[*aj]] = i; 2353 atfill[*aj++] += 1; 2354 } 2355 } 2356 2357 /* Clean up temporary space and complete requests. */ 2358 ierr = PetscFree(atfill);CHKERRQ(ierr); 2359 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2360 ierr = MatSetBlockSizes(*B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2361 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2362 2363 b = (Mat_SeqAIJ*)((*B)->data); 2364 b->free_a = PETSC_FALSE; 2365 b->free_ij = PETSC_TRUE; 2366 b->nonew = 0; 2367 PetscFunctionReturn(0); 2368 } 2369 2370 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2371 { 2372 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2373 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2374 MatScalar *va,*vb; 2375 PetscErrorCode ierr; 2376 PetscInt ma,na,mb,nb, i; 2377 2378 PetscFunctionBegin; 2379 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2380 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2381 if (ma!=nb || na!=mb) { 2382 *f = PETSC_FALSE; 2383 PetscFunctionReturn(0); 2384 } 2385 aii = aij->i; bii = bij->i; 2386 adx = aij->j; bdx = bij->j; 2387 va = aij->a; vb = bij->a; 2388 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2389 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2390 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2391 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2392 2393 *f = PETSC_TRUE; 2394 for (i=0; i<ma; i++) { 2395 while (aptr[i]<aii[i+1]) { 2396 PetscInt idc,idr; 2397 PetscScalar vc,vr; 2398 /* column/row index/value */ 2399 idc = adx[aptr[i]]; 2400 idr = bdx[bptr[idc]]; 2401 vc = va[aptr[i]]; 2402 vr = vb[bptr[idc]]; 2403 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2404 *f = PETSC_FALSE; 2405 goto done; 2406 } else { 2407 aptr[i]++; 2408 if (B || i!=idc) bptr[idc]++; 2409 } 2410 } 2411 } 2412 done: 2413 ierr = PetscFree(aptr);CHKERRQ(ierr); 2414 ierr = PetscFree(bptr);CHKERRQ(ierr); 2415 PetscFunctionReturn(0); 2416 } 2417 2418 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2419 { 2420 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2421 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2422 MatScalar *va,*vb; 2423 PetscErrorCode ierr; 2424 PetscInt ma,na,mb,nb, i; 2425 2426 PetscFunctionBegin; 2427 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2428 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2429 if (ma!=nb || na!=mb) { 2430 *f = PETSC_FALSE; 2431 PetscFunctionReturn(0); 2432 } 2433 aii = aij->i; bii = bij->i; 2434 adx = aij->j; bdx = bij->j; 2435 va = aij->a; vb = bij->a; 2436 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2437 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2438 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2439 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2440 2441 *f = PETSC_TRUE; 2442 for (i=0; i<ma; i++) { 2443 while (aptr[i]<aii[i+1]) { 2444 PetscInt idc,idr; 2445 PetscScalar vc,vr; 2446 /* column/row index/value */ 2447 idc = adx[aptr[i]]; 2448 idr = bdx[bptr[idc]]; 2449 vc = va[aptr[i]]; 2450 vr = vb[bptr[idc]]; 2451 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2452 *f = PETSC_FALSE; 2453 goto done; 2454 } else { 2455 aptr[i]++; 2456 if (B || i!=idc) bptr[idc]++; 2457 } 2458 } 2459 } 2460 done: 2461 ierr = PetscFree(aptr);CHKERRQ(ierr); 2462 ierr = PetscFree(bptr);CHKERRQ(ierr); 2463 PetscFunctionReturn(0); 2464 } 2465 2466 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2467 { 2468 PetscErrorCode ierr; 2469 2470 PetscFunctionBegin; 2471 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2472 PetscFunctionReturn(0); 2473 } 2474 2475 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2476 { 2477 PetscErrorCode ierr; 2478 2479 PetscFunctionBegin; 2480 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2481 PetscFunctionReturn(0); 2482 } 2483 2484 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2485 { 2486 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2487 const PetscScalar *l,*r; 2488 PetscScalar x; 2489 MatScalar *v; 2490 PetscErrorCode ierr; 2491 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz; 2492 const PetscInt *jj; 2493 2494 PetscFunctionBegin; 2495 if (ll) { 2496 /* The local size is used so that VecMPI can be passed to this routine 2497 by MatDiagonalScale_MPIAIJ */ 2498 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2499 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2500 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 2501 v = a->a; 2502 for (i=0; i<m; i++) { 2503 x = l[i]; 2504 M = a->i[i+1] - a->i[i]; 2505 for (j=0; j<M; j++) (*v++) *= x; 2506 } 2507 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 2508 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2509 } 2510 if (rr) { 2511 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2512 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2513 ierr = VecGetArrayRead(rr,&r);CHKERRQ(ierr); 2514 v = a->a; jj = a->j; 2515 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2516 ierr = VecRestoreArrayRead(rr,&r);CHKERRQ(ierr); 2517 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2518 } 2519 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2520 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2521 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED) A->offloadmask = PETSC_OFFLOAD_CPU; 2522 #endif 2523 PetscFunctionReturn(0); 2524 } 2525 2526 PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2527 { 2528 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2529 PetscErrorCode ierr; 2530 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2531 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2532 const PetscInt *irow,*icol; 2533 PetscInt nrows,ncols; 2534 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2535 MatScalar *a_new,*mat_a; 2536 Mat C; 2537 PetscBool stride; 2538 2539 PetscFunctionBegin; 2540 2541 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2542 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2543 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2544 2545 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2546 if (stride) { 2547 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2548 } else { 2549 first = 0; 2550 step = 0; 2551 } 2552 if (stride && step == 1) { 2553 /* special case of contiguous rows */ 2554 ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); 2555 /* loop over new rows determining lens and starting points */ 2556 for (i=0; i<nrows; i++) { 2557 kstart = ai[irow[i]]; 2558 kend = kstart + ailen[irow[i]]; 2559 starts[i] = kstart; 2560 for (k=kstart; k<kend; k++) { 2561 if (aj[k] >= first) { 2562 starts[i] = k; 2563 break; 2564 } 2565 } 2566 sum = 0; 2567 while (k < kend) { 2568 if (aj[k++] >= first+ncols) break; 2569 sum++; 2570 } 2571 lens[i] = sum; 2572 } 2573 /* create submatrix */ 2574 if (scall == MAT_REUSE_MATRIX) { 2575 PetscInt n_cols,n_rows; 2576 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2577 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2578 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2579 C = *B; 2580 } else { 2581 PetscInt rbs,cbs; 2582 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2583 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2584 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2585 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2586 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2587 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2588 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2589 } 2590 c = (Mat_SeqAIJ*)C->data; 2591 2592 /* loop over rows inserting into submatrix */ 2593 a_new = c->a; 2594 j_new = c->j; 2595 i_new = c->i; 2596 2597 for (i=0; i<nrows; i++) { 2598 ii = starts[i]; 2599 lensi = lens[i]; 2600 for (k=0; k<lensi; k++) { 2601 *j_new++ = aj[ii+k] - first; 2602 } 2603 ierr = PetscArraycpy(a_new,a->a + starts[i],lensi);CHKERRQ(ierr); 2604 a_new += lensi; 2605 i_new[i+1] = i_new[i] + lensi; 2606 c->ilen[i] = lensi; 2607 } 2608 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2609 } else { 2610 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2611 ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); 2612 ierr = PetscMalloc1(1+nrows,&lens);CHKERRQ(ierr); 2613 for (i=0; i<ncols; i++) { 2614 if (PetscUnlikelyDebug(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); 2615 smap[icol[i]] = i+1; 2616 } 2617 2618 /* determine lens of each row */ 2619 for (i=0; i<nrows; i++) { 2620 kstart = ai[irow[i]]; 2621 kend = kstart + a->ilen[irow[i]]; 2622 lens[i] = 0; 2623 for (k=kstart; k<kend; k++) { 2624 if (smap[aj[k]]) { 2625 lens[i]++; 2626 } 2627 } 2628 } 2629 /* Create and fill new matrix */ 2630 if (scall == MAT_REUSE_MATRIX) { 2631 PetscBool equal; 2632 2633 c = (Mat_SeqAIJ*)((*B)->data); 2634 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2635 ierr = PetscArraycmp(c->ilen,lens,(*B)->rmap->n,&equal);CHKERRQ(ierr); 2636 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2637 ierr = PetscArrayzero(c->ilen,(*B)->rmap->n);CHKERRQ(ierr); 2638 C = *B; 2639 } else { 2640 PetscInt rbs,cbs; 2641 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2642 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2643 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2644 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2645 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2646 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2647 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2648 } 2649 c = (Mat_SeqAIJ*)(C->data); 2650 for (i=0; i<nrows; i++) { 2651 row = irow[i]; 2652 kstart = ai[row]; 2653 kend = kstart + a->ilen[row]; 2654 mat_i = c->i[i]; 2655 mat_j = c->j + mat_i; 2656 mat_a = c->a + mat_i; 2657 mat_ilen = c->ilen + i; 2658 for (k=kstart; k<kend; k++) { 2659 if ((tcol=smap[a->j[k]])) { 2660 *mat_j++ = tcol - 1; 2661 *mat_a++ = a->a[k]; 2662 (*mat_ilen)++; 2663 2664 } 2665 } 2666 } 2667 /* Free work space */ 2668 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2669 ierr = PetscFree(smap);CHKERRQ(ierr); 2670 ierr = PetscFree(lens);CHKERRQ(ierr); 2671 /* sort */ 2672 for (i = 0; i < nrows; i++) { 2673 PetscInt ilen; 2674 2675 mat_i = c->i[i]; 2676 mat_j = c->j + mat_i; 2677 mat_a = c->a + mat_i; 2678 ilen = c->ilen[i]; 2679 ierr = PetscSortIntWithScalarArray(ilen,mat_j,mat_a);CHKERRQ(ierr); 2680 } 2681 } 2682 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2683 ierr = MatBindToCPU(C,A->boundtocpu);CHKERRQ(ierr); 2684 #endif 2685 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2686 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2687 2688 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2689 *B = C; 2690 PetscFunctionReturn(0); 2691 } 2692 2693 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2694 { 2695 PetscErrorCode ierr; 2696 Mat B; 2697 2698 PetscFunctionBegin; 2699 if (scall == MAT_INITIAL_MATRIX) { 2700 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2701 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2702 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2703 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2704 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2705 *subMat = B; 2706 } else { 2707 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2708 } 2709 PetscFunctionReturn(0); 2710 } 2711 2712 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2713 { 2714 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2715 PetscErrorCode ierr; 2716 Mat outA; 2717 PetscBool row_identity,col_identity; 2718 2719 PetscFunctionBegin; 2720 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2721 2722 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2723 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2724 2725 outA = inA; 2726 outA->factortype = MAT_FACTOR_LU; 2727 ierr = PetscFree(inA->solvertype);CHKERRQ(ierr); 2728 ierr = PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);CHKERRQ(ierr); 2729 2730 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2731 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2732 2733 a->row = row; 2734 2735 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2736 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2737 2738 a->col = col; 2739 2740 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2741 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2742 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2743 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2744 2745 if (!a->solve_work) { /* this matrix may have been factored before */ 2746 ierr = PetscMalloc1(inA->rmap->n+1,&a->solve_work);CHKERRQ(ierr); 2747 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2748 } 2749 2750 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2751 if (row_identity && col_identity) { 2752 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2753 } else { 2754 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2755 } 2756 PetscFunctionReturn(0); 2757 } 2758 2759 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2760 { 2761 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2762 PetscScalar oalpha = alpha; 2763 PetscErrorCode ierr; 2764 PetscBLASInt one = 1,bnz; 2765 2766 PetscFunctionBegin; 2767 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2768 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2769 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2770 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2771 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2772 if (inA->offloadmask != PETSC_OFFLOAD_UNALLOCATED) inA->offloadmask = PETSC_OFFLOAD_CPU; 2773 #endif 2774 PetscFunctionReturn(0); 2775 } 2776 2777 PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt *submatj) 2778 { 2779 PetscErrorCode ierr; 2780 PetscInt i; 2781 2782 PetscFunctionBegin; 2783 if (!submatj->id) { /* delete data that are linked only to submats[id=0] */ 2784 ierr = PetscFree4(submatj->sbuf1,submatj->ptr,submatj->tmp,submatj->ctr);CHKERRQ(ierr); 2785 2786 for (i=0; i<submatj->nrqr; ++i) { 2787 ierr = PetscFree(submatj->sbuf2[i]);CHKERRQ(ierr); 2788 } 2789 ierr = PetscFree3(submatj->sbuf2,submatj->req_size,submatj->req_source1);CHKERRQ(ierr); 2790 2791 if (submatj->rbuf1) { 2792 ierr = PetscFree(submatj->rbuf1[0]);CHKERRQ(ierr); 2793 ierr = PetscFree(submatj->rbuf1);CHKERRQ(ierr); 2794 } 2795 2796 for (i=0; i<submatj->nrqs; ++i) { 2797 ierr = PetscFree(submatj->rbuf3[i]);CHKERRQ(ierr); 2798 } 2799 ierr = PetscFree3(submatj->req_source2,submatj->rbuf2,submatj->rbuf3);CHKERRQ(ierr); 2800 ierr = PetscFree(submatj->pa);CHKERRQ(ierr); 2801 } 2802 2803 #if defined(PETSC_USE_CTABLE) 2804 ierr = PetscTableDestroy((PetscTable*)&submatj->rmap);CHKERRQ(ierr); 2805 if (submatj->cmap_loc) {ierr = PetscFree(submatj->cmap_loc);CHKERRQ(ierr);} 2806 ierr = PetscFree(submatj->rmap_loc);CHKERRQ(ierr); 2807 #else 2808 ierr = PetscFree(submatj->rmap);CHKERRQ(ierr); 2809 #endif 2810 2811 if (!submatj->allcolumns) { 2812 #if defined(PETSC_USE_CTABLE) 2813 ierr = PetscTableDestroy((PetscTable*)&submatj->cmap);CHKERRQ(ierr); 2814 #else 2815 ierr = PetscFree(submatj->cmap);CHKERRQ(ierr); 2816 #endif 2817 } 2818 ierr = PetscFree(submatj->row2proc);CHKERRQ(ierr); 2819 2820 ierr = PetscFree(submatj);CHKERRQ(ierr); 2821 PetscFunctionReturn(0); 2822 } 2823 2824 PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat C) 2825 { 2826 PetscErrorCode ierr; 2827 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2828 Mat_SubSppt *submatj = c->submatis1; 2829 2830 PetscFunctionBegin; 2831 ierr = (*submatj->destroy)(C);CHKERRQ(ierr); 2832 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2833 PetscFunctionReturn(0); 2834 } 2835 2836 PetscErrorCode MatDestroySubMatrices_SeqAIJ(PetscInt n,Mat *mat[]) 2837 { 2838 PetscErrorCode ierr; 2839 PetscInt i; 2840 Mat C; 2841 Mat_SeqAIJ *c; 2842 Mat_SubSppt *submatj; 2843 2844 PetscFunctionBegin; 2845 for (i=0; i<n; i++) { 2846 C = (*mat)[i]; 2847 c = (Mat_SeqAIJ*)C->data; 2848 submatj = c->submatis1; 2849 if (submatj) { 2850 if (--((PetscObject)C)->refct <= 0) { 2851 ierr = (*submatj->destroy)(C);CHKERRQ(ierr); 2852 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2853 ierr = PetscFree(C->defaultvectype);CHKERRQ(ierr); 2854 ierr = PetscLayoutDestroy(&C->rmap);CHKERRQ(ierr); 2855 ierr = PetscLayoutDestroy(&C->cmap);CHKERRQ(ierr); 2856 ierr = PetscHeaderDestroy(&C);CHKERRQ(ierr); 2857 } 2858 } else { 2859 ierr = MatDestroy(&C);CHKERRQ(ierr); 2860 } 2861 } 2862 2863 /* Destroy Dummy submatrices created for reuse */ 2864 ierr = MatDestroySubMatrices_Dummy(n,mat);CHKERRQ(ierr); 2865 2866 ierr = PetscFree(*mat);CHKERRQ(ierr); 2867 PetscFunctionReturn(0); 2868 } 2869 2870 PetscErrorCode MatCreateSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2871 { 2872 PetscErrorCode ierr; 2873 PetscInt i; 2874 2875 PetscFunctionBegin; 2876 if (scall == MAT_INITIAL_MATRIX) { 2877 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 2878 } 2879 2880 for (i=0; i<n; i++) { 2881 ierr = MatCreateSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2882 } 2883 PetscFunctionReturn(0); 2884 } 2885 2886 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2887 { 2888 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2889 PetscErrorCode ierr; 2890 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2891 const PetscInt *idx; 2892 PetscInt start,end,*ai,*aj; 2893 PetscBT table; 2894 2895 PetscFunctionBegin; 2896 m = A->rmap->n; 2897 ai = a->i; 2898 aj = a->j; 2899 2900 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2901 2902 ierr = PetscMalloc1(m+1,&nidx);CHKERRQ(ierr); 2903 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2904 2905 for (i=0; i<is_max; i++) { 2906 /* Initialize the two local arrays */ 2907 isz = 0; 2908 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2909 2910 /* Extract the indices, assume there can be duplicate entries */ 2911 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2912 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2913 2914 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2915 for (j=0; j<n; ++j) { 2916 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2917 } 2918 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2919 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2920 2921 k = 0; 2922 for (j=0; j<ov; j++) { /* for each overlap */ 2923 n = isz; 2924 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2925 row = nidx[k]; 2926 start = ai[row]; 2927 end = ai[row+1]; 2928 for (l = start; l<end; l++) { 2929 val = aj[l]; 2930 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2931 } 2932 } 2933 } 2934 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2935 } 2936 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2937 ierr = PetscFree(nidx);CHKERRQ(ierr); 2938 PetscFunctionReturn(0); 2939 } 2940 2941 /* -------------------------------------------------------------- */ 2942 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2943 { 2944 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2945 PetscErrorCode ierr; 2946 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2947 const PetscInt *row,*col; 2948 PetscInt *cnew,j,*lens; 2949 IS icolp,irowp; 2950 PetscInt *cwork = NULL; 2951 PetscScalar *vwork = NULL; 2952 2953 PetscFunctionBegin; 2954 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2955 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2956 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2957 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2958 2959 /* determine lengths of permuted rows */ 2960 ierr = PetscMalloc1(m+1,&lens);CHKERRQ(ierr); 2961 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2962 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2963 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2964 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2965 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2966 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2967 ierr = PetscFree(lens);CHKERRQ(ierr); 2968 2969 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2970 for (i=0; i<m; i++) { 2971 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2972 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2973 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2974 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2975 } 2976 ierr = PetscFree(cnew);CHKERRQ(ierr); 2977 2978 (*B)->assembled = PETSC_FALSE; 2979 2980 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 2981 ierr = MatBindToCPU(*B,A->boundtocpu);CHKERRQ(ierr); 2982 #endif 2983 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2984 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2985 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2986 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2987 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2988 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2989 if (rowp == colp) { 2990 if (A->symmetric) { 2991 ierr = MatSetOption(*B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2992 } 2993 if (A->hermitian) { 2994 ierr = MatSetOption(*B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2995 } 2996 } 2997 PetscFunctionReturn(0); 2998 } 2999 3000 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 3001 { 3002 PetscErrorCode ierr; 3003 3004 PetscFunctionBegin; 3005 /* If the two matrices have the same copy implementation, use fast copy. */ 3006 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 3007 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3008 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 3009 3010 if (a->i[A->rmap->n] != b->i[B->rmap->n]) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzeros in two matrices are different %D != %D",a->i[A->rmap->n],b->i[B->rmap->n]); 3011 ierr = PetscArraycpy(b->a,a->a,a->i[A->rmap->n]);CHKERRQ(ierr); 3012 ierr = PetscObjectStateIncrease((PetscObject)B);CHKERRQ(ierr); 3013 } else { 3014 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 3015 } 3016 PetscFunctionReturn(0); 3017 } 3018 3019 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 3020 { 3021 PetscErrorCode ierr; 3022 3023 PetscFunctionBegin; 3024 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,NULL);CHKERRQ(ierr); 3025 PetscFunctionReturn(0); 3026 } 3027 3028 PETSC_INTERN PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 3029 { 3030 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3031 3032 PetscFunctionBegin; 3033 *array = a->a; 3034 PetscFunctionReturn(0); 3035 } 3036 3037 PETSC_INTERN PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 3038 { 3039 PetscFunctionBegin; 3040 *array = NULL; 3041 PetscFunctionReturn(0); 3042 } 3043 3044 /* 3045 Computes the number of nonzeros per row needed for preallocation when X and Y 3046 have different nonzero structure. 3047 */ 3048 PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *yi,const PetscInt *yj,PetscInt *nnz) 3049 { 3050 PetscInt i,j,k,nzx,nzy; 3051 3052 PetscFunctionBegin; 3053 /* Set the number of nonzeros in the new matrix */ 3054 for (i=0; i<m; i++) { 3055 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 3056 nzx = xi[i+1] - xi[i]; 3057 nzy = yi[i+1] - yi[i]; 3058 nnz[i] = 0; 3059 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 3060 for (; k<nzy && yjj[k]<xjj[j]; k++) nnz[i]++; /* Catch up to X */ 3061 if (k<nzy && yjj[k]==xjj[j]) k++; /* Skip duplicate */ 3062 nnz[i]++; 3063 } 3064 for (; k<nzy; k++) nnz[i]++; 3065 } 3066 PetscFunctionReturn(0); 3067 } 3068 3069 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 3070 { 3071 PetscInt m = Y->rmap->N; 3072 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 3073 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 3074 PetscErrorCode ierr; 3075 3076 PetscFunctionBegin; 3077 /* Set the number of nonzeros in the new matrix */ 3078 ierr = MatAXPYGetPreallocation_SeqX_private(m,x->i,x->j,y->i,y->j,nnz);CHKERRQ(ierr); 3079 PetscFunctionReturn(0); 3080 } 3081 3082 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 3083 { 3084 PetscErrorCode ierr; 3085 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 3086 3087 PetscFunctionBegin; 3088 if (str == DIFFERENT_NONZERO_PATTERN) { 3089 if (x->nz == y->nz) { 3090 PetscBool e; 3091 ierr = PetscArraycmp(x->i,y->i,Y->rmap->n+1,&e);CHKERRQ(ierr); 3092 if (e) { 3093 ierr = PetscArraycmp(x->j,y->j,y->nz,&e);CHKERRQ(ierr); 3094 if (e) { 3095 str = SAME_NONZERO_PATTERN; 3096 } 3097 } 3098 } 3099 } 3100 if (str == SAME_NONZERO_PATTERN) { 3101 PetscScalar alpha = a; 3102 PetscBLASInt one = 1,bnz; 3103 3104 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 3105 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 3106 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 3107 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 3108 /* the MatAXPY_Basic* subroutines calls MatAssembly, so the matrix on the GPU will be updated */ 3109 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 3110 if (Y->offloadmask != PETSC_OFFLOAD_UNALLOCATED) { 3111 Y->offloadmask = PETSC_OFFLOAD_CPU; 3112 } 3113 #endif 3114 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 3115 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 3116 } else { 3117 Mat B; 3118 PetscInt *nnz; 3119 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 3120 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 3121 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 3122 ierr = MatSetLayouts(B,Y->rmap,Y->cmap);CHKERRQ(ierr); 3123 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 3124 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 3125 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 3126 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 3127 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 3128 ierr = PetscFree(nnz);CHKERRQ(ierr); 3129 } 3130 PetscFunctionReturn(0); 3131 } 3132 3133 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 3134 { 3135 #if defined(PETSC_USE_COMPLEX) 3136 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3137 PetscInt i,nz; 3138 PetscScalar *a; 3139 3140 PetscFunctionBegin; 3141 nz = aij->nz; 3142 a = aij->a; 3143 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 3144 #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA) 3145 if (mat->offloadmask != PETSC_OFFLOAD_UNALLOCATED) mat->offloadmask = PETSC_OFFLOAD_CPU; 3146 #endif 3147 #else 3148 PetscFunctionBegin; 3149 #endif 3150 PetscFunctionReturn(0); 3151 } 3152 3153 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3154 { 3155 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3156 PetscErrorCode ierr; 3157 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3158 PetscReal atmp; 3159 PetscScalar *x; 3160 MatScalar *aa; 3161 3162 PetscFunctionBegin; 3163 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3164 aa = a->a; 3165 ai = a->i; 3166 aj = a->j; 3167 3168 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3169 ierr = VecGetArrayWrite(v,&x);CHKERRQ(ierr); 3170 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3171 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3172 for (i=0; i<m; i++) { 3173 ncols = ai[1] - ai[0]; ai++; 3174 for (j=0; j<ncols; j++) { 3175 atmp = PetscAbsScalar(*aa); 3176 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3177 aa++; aj++; 3178 } 3179 } 3180 ierr = VecRestoreArrayWrite(v,&x);CHKERRQ(ierr); 3181 PetscFunctionReturn(0); 3182 } 3183 3184 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3185 { 3186 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3187 PetscErrorCode ierr; 3188 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3189 PetscScalar *x; 3190 MatScalar *aa; 3191 3192 PetscFunctionBegin; 3193 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3194 aa = a->a; 3195 ai = a->i; 3196 aj = a->j; 3197 3198 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3199 ierr = VecGetArrayWrite(v,&x);CHKERRQ(ierr); 3200 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3201 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3202 for (i=0; i<m; i++) { 3203 ncols = ai[1] - ai[0]; ai++; 3204 if (ncols == A->cmap->n) { /* row is dense */ 3205 x[i] = *aa; if (idx) idx[i] = 0; 3206 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 3207 x[i] = 0.0; 3208 if (idx) { 3209 for (j=0; j<ncols; j++) { /* find first implicit 0.0 in the row */ 3210 if (aj[j] > j) { 3211 idx[i] = j; 3212 break; 3213 } 3214 } 3215 /* in case first implicit 0.0 in the row occurs at ncols-th column */ 3216 if (j==ncols && j < A->cmap->n) idx[i] = j; 3217 } 3218 } 3219 for (j=0; j<ncols; j++) { 3220 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3221 aa++; aj++; 3222 } 3223 } 3224 ierr = VecRestoreArrayWrite(v,&x);CHKERRQ(ierr); 3225 PetscFunctionReturn(0); 3226 } 3227 3228 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3229 { 3230 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3231 PetscErrorCode ierr; 3232 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3233 PetscReal atmp; 3234 PetscScalar *x; 3235 MatScalar *aa; 3236 3237 PetscFunctionBegin; 3238 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3239 aa = a->a; 3240 ai = a->i; 3241 aj = a->j; 3242 3243 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3244 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3245 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3246 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); 3247 for (i=0; i<m; i++) { 3248 ncols = ai[1] - ai[0]; ai++; 3249 if (ncols) { 3250 /* Get first nonzero */ 3251 for (j = 0; j < ncols; j++) { 3252 atmp = PetscAbsScalar(aa[j]); 3253 if (atmp > 1.0e-12) { 3254 x[i] = atmp; 3255 if (idx) idx[i] = aj[j]; 3256 break; 3257 } 3258 } 3259 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 3260 } else { 3261 x[i] = 0.0; if (idx) idx[i] = 0; 3262 } 3263 for (j = 0; j < ncols; j++) { 3264 atmp = PetscAbsScalar(*aa); 3265 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3266 aa++; aj++; 3267 } 3268 } 3269 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3270 PetscFunctionReturn(0); 3271 } 3272 3273 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3274 { 3275 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3276 PetscErrorCode ierr; 3277 PetscInt i,j,m = A->rmap->n,ncols,n; 3278 const PetscInt *ai,*aj; 3279 PetscScalar *x; 3280 const MatScalar *aa; 3281 3282 PetscFunctionBegin; 3283 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3284 aa = a->a; 3285 ai = a->i; 3286 aj = a->j; 3287 3288 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3289 ierr = VecGetArrayWrite(v,&x);CHKERRQ(ierr); 3290 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3291 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3292 for (i=0; i<m; i++) { 3293 ncols = ai[1] - ai[0]; ai++; 3294 if (ncols == A->cmap->n) { /* row is dense */ 3295 x[i] = *aa; if (idx) idx[i] = 0; 3296 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3297 x[i] = 0.0; 3298 if (idx) { /* find first implicit 0.0 in the row */ 3299 for (j=0; j<ncols; j++) { 3300 if (aj[j] > j) { 3301 idx[i] = j; 3302 break; 3303 } 3304 } 3305 /* in case first implicit 0.0 in the row occurs at ncols-th column */ 3306 if (j==ncols && j < A->cmap->n) idx[i] = j; 3307 } 3308 } 3309 for (j=0; j<ncols; j++) { 3310 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3311 aa++; aj++; 3312 } 3313 } 3314 ierr = VecRestoreArrayWrite(v,&x);CHKERRQ(ierr); 3315 PetscFunctionReturn(0); 3316 } 3317 3318 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3319 { 3320 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3321 PetscErrorCode ierr; 3322 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3323 MatScalar *diag,work[25],*v_work; 3324 const PetscReal shift = 0.0; 3325 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 3326 3327 PetscFunctionBegin; 3328 allowzeropivot = PetscNot(A->erroriffailure); 3329 if (a->ibdiagvalid) { 3330 if (values) *values = a->ibdiag; 3331 PetscFunctionReturn(0); 3332 } 3333 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3334 if (!a->ibdiag) { 3335 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 3336 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3337 } 3338 diag = a->ibdiag; 3339 if (values) *values = a->ibdiag; 3340 /* factor and invert each block */ 3341 switch (bs) { 3342 case 1: 3343 for (i=0; i<mbs; i++) { 3344 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3345 if (PetscAbsScalar(diag[i] + shift) < PETSC_MACHINE_EPSILON) { 3346 if (allowzeropivot) { 3347 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3348 A->factorerror_zeropivot_value = PetscAbsScalar(diag[i]); 3349 A->factorerror_zeropivot_row = i; 3350 ierr = PetscInfo3(A,"Zero pivot, row %D pivot %g tolerance %g\n",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON);CHKERRQ(ierr); 3351 } 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); 3352 } 3353 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3354 } 3355 break; 3356 case 2: 3357 for (i=0; i<mbs; i++) { 3358 ij[0] = 2*i; ij[1] = 2*i + 1; 3359 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3360 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3361 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3362 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3363 diag += 4; 3364 } 3365 break; 3366 case 3: 3367 for (i=0; i<mbs; i++) { 3368 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3369 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3370 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3371 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3372 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3373 diag += 9; 3374 } 3375 break; 3376 case 4: 3377 for (i=0; i<mbs; i++) { 3378 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3379 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3380 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3381 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3382 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3383 diag += 16; 3384 } 3385 break; 3386 case 5: 3387 for (i=0; i<mbs; i++) { 3388 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3389 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3390 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3391 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3392 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3393 diag += 25; 3394 } 3395 break; 3396 case 6: 3397 for (i=0; i<mbs; i++) { 3398 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; 3399 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3400 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3401 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3402 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3403 diag += 36; 3404 } 3405 break; 3406 case 7: 3407 for (i=0; i<mbs; i++) { 3408 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; 3409 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3410 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3411 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3412 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3413 diag += 49; 3414 } 3415 break; 3416 default: 3417 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3418 for (i=0; i<mbs; i++) { 3419 for (j=0; j<bs; j++) { 3420 IJ[j] = bs*i + j; 3421 } 3422 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3423 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3424 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3425 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3426 diag += bs2; 3427 } 3428 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3429 } 3430 a->ibdiagvalid = PETSC_TRUE; 3431 PetscFunctionReturn(0); 3432 } 3433 3434 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3435 { 3436 PetscErrorCode ierr; 3437 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3438 PetscScalar a; 3439 PetscInt m,n,i,j,col; 3440 3441 PetscFunctionBegin; 3442 if (!x->assembled) { 3443 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3444 for (i=0; i<m; i++) { 3445 for (j=0; j<aij->imax[i]; j++) { 3446 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3447 col = (PetscInt)(n*PetscRealPart(a)); 3448 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3449 } 3450 } 3451 } else { 3452 for (i=0; i<aij->nz; i++) {ierr = PetscRandomGetValue(rctx,aij->a+i);CHKERRQ(ierr);} 3453 } 3454 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3455 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3456 PetscFunctionReturn(0); 3457 } 3458 3459 /* Like MatSetRandom_SeqAIJ, but do not set values on columns in range of [low, high) */ 3460 PetscErrorCode MatSetRandomSkipColumnRange_SeqAIJ_Private(Mat x,PetscInt low,PetscInt high,PetscRandom rctx) 3461 { 3462 PetscErrorCode ierr; 3463 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3464 PetscScalar a; 3465 PetscInt m,n,i,j,col,nskip; 3466 3467 PetscFunctionBegin; 3468 nskip = high - low; 3469 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3470 n -= nskip; /* shrink number of columns where nonzeros can be set */ 3471 for (i=0; i<m; i++) { 3472 for (j=0; j<aij->imax[i]; j++) { 3473 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3474 col = (PetscInt)(n*PetscRealPart(a)); 3475 if (col >= low) col += nskip; /* shift col rightward to skip the hole */ 3476 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3477 } 3478 } 3479 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3480 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3481 PetscFunctionReturn(0); 3482 } 3483 3484 3485 /* -------------------------------------------------------------------*/ 3486 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3487 MatGetRow_SeqAIJ, 3488 MatRestoreRow_SeqAIJ, 3489 MatMult_SeqAIJ, 3490 /* 4*/ MatMultAdd_SeqAIJ, 3491 MatMultTranspose_SeqAIJ, 3492 MatMultTransposeAdd_SeqAIJ, 3493 NULL, 3494 NULL, 3495 NULL, 3496 /* 10*/ NULL, 3497 MatLUFactor_SeqAIJ, 3498 NULL, 3499 MatSOR_SeqAIJ, 3500 MatTranspose_SeqAIJ, 3501 /*1 5*/ MatGetInfo_SeqAIJ, 3502 MatEqual_SeqAIJ, 3503 MatGetDiagonal_SeqAIJ, 3504 MatDiagonalScale_SeqAIJ, 3505 MatNorm_SeqAIJ, 3506 /* 20*/ NULL, 3507 MatAssemblyEnd_SeqAIJ, 3508 MatSetOption_SeqAIJ, 3509 MatZeroEntries_SeqAIJ, 3510 /* 24*/ MatZeroRows_SeqAIJ, 3511 NULL, 3512 NULL, 3513 NULL, 3514 NULL, 3515 /* 29*/ MatSetUp_SeqAIJ, 3516 NULL, 3517 NULL, 3518 NULL, 3519 NULL, 3520 /* 34*/ MatDuplicate_SeqAIJ, 3521 NULL, 3522 NULL, 3523 MatILUFactor_SeqAIJ, 3524 NULL, 3525 /* 39*/ MatAXPY_SeqAIJ, 3526 MatCreateSubMatrices_SeqAIJ, 3527 MatIncreaseOverlap_SeqAIJ, 3528 MatGetValues_SeqAIJ, 3529 MatCopy_SeqAIJ, 3530 /* 44*/ MatGetRowMax_SeqAIJ, 3531 MatScale_SeqAIJ, 3532 MatShift_SeqAIJ, 3533 MatDiagonalSet_SeqAIJ, 3534 MatZeroRowsColumns_SeqAIJ, 3535 /* 49*/ MatSetRandom_SeqAIJ, 3536 MatGetRowIJ_SeqAIJ, 3537 MatRestoreRowIJ_SeqAIJ, 3538 MatGetColumnIJ_SeqAIJ, 3539 MatRestoreColumnIJ_SeqAIJ, 3540 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3541 NULL, 3542 NULL, 3543 MatPermute_SeqAIJ, 3544 NULL, 3545 /* 59*/ NULL, 3546 MatDestroy_SeqAIJ, 3547 MatView_SeqAIJ, 3548 NULL, 3549 NULL, 3550 /* 64*/ NULL, 3551 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3552 NULL, 3553 NULL, 3554 NULL, 3555 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3556 MatGetRowMinAbs_SeqAIJ, 3557 NULL, 3558 NULL, 3559 NULL, 3560 /* 74*/ NULL, 3561 MatFDColoringApply_AIJ, 3562 NULL, 3563 NULL, 3564 NULL, 3565 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3566 NULL, 3567 NULL, 3568 NULL, 3569 MatLoad_SeqAIJ, 3570 /* 84*/ MatIsSymmetric_SeqAIJ, 3571 MatIsHermitian_SeqAIJ, 3572 NULL, 3573 NULL, 3574 NULL, 3575 /* 89*/ NULL, 3576 NULL, 3577 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3578 NULL, 3579 NULL, 3580 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy, 3581 NULL, 3582 NULL, 3583 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3584 NULL, 3585 /* 99*/ MatProductSetFromOptions_SeqAIJ, 3586 NULL, 3587 NULL, 3588 MatConjugate_SeqAIJ, 3589 NULL, 3590 /*104*/ MatSetValuesRow_SeqAIJ, 3591 MatRealPart_SeqAIJ, 3592 MatImaginaryPart_SeqAIJ, 3593 NULL, 3594 NULL, 3595 /*109*/ MatMatSolve_SeqAIJ, 3596 NULL, 3597 MatGetRowMin_SeqAIJ, 3598 NULL, 3599 MatMissingDiagonal_SeqAIJ, 3600 /*114*/ NULL, 3601 NULL, 3602 NULL, 3603 NULL, 3604 NULL, 3605 /*119*/ NULL, 3606 NULL, 3607 NULL, 3608 NULL, 3609 MatGetMultiProcBlock_SeqAIJ, 3610 /*124*/ MatFindNonzeroRows_SeqAIJ, 3611 MatGetColumnNorms_SeqAIJ, 3612 MatInvertBlockDiagonal_SeqAIJ, 3613 MatInvertVariableBlockDiagonal_SeqAIJ, 3614 NULL, 3615 /*129*/ NULL, 3616 NULL, 3617 NULL, 3618 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3619 MatTransposeColoringCreate_SeqAIJ, 3620 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3621 MatTransColoringApplyDenToSp_SeqAIJ, 3622 NULL, 3623 NULL, 3624 MatRARtNumeric_SeqAIJ_SeqAIJ, 3625 /*139*/NULL, 3626 NULL, 3627 NULL, 3628 MatFDColoringSetUp_SeqXAIJ, 3629 MatFindOffBlockDiagonalEntries_SeqAIJ, 3630 MatCreateMPIMatConcatenateSeqMat_SeqAIJ, 3631 /*145*/MatDestroySubMatrices_SeqAIJ, 3632 NULL, 3633 NULL 3634 }; 3635 3636 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3637 { 3638 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3639 PetscInt i,nz,n; 3640 3641 PetscFunctionBegin; 3642 nz = aij->maxnz; 3643 n = mat->rmap->n; 3644 for (i=0; i<nz; i++) { 3645 aij->j[i] = indices[i]; 3646 } 3647 aij->nz = nz; 3648 for (i=0; i<n; i++) { 3649 aij->ilen[i] = aij->imax[i]; 3650 } 3651 PetscFunctionReturn(0); 3652 } 3653 3654 /* 3655 * When a sparse matrix has many zero columns, we should compact them out to save the space 3656 * This happens in MatPtAPSymbolic_MPIAIJ_MPIAIJ_scalable() 3657 * */ 3658 PetscErrorCode MatSeqAIJCompactOutExtraColumns_SeqAIJ(Mat mat, ISLocalToGlobalMapping *mapping) 3659 { 3660 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3661 PetscTable gid1_lid1; 3662 PetscTablePosition tpos; 3663 PetscInt gid,lid,i,j,ncols,ec; 3664 PetscInt *garray; 3665 PetscErrorCode ierr; 3666 3667 PetscFunctionBegin; 3668 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3669 PetscValidPointer(mapping,2); 3670 /* use a table */ 3671 ierr = PetscTableCreate(mat->rmap->n,mat->cmap->N+1,&gid1_lid1);CHKERRQ(ierr); 3672 ec = 0; 3673 for (i=0; i<mat->rmap->n; i++) { 3674 ncols = aij->i[i+1] - aij->i[i]; 3675 for (j=0; j<ncols; j++) { 3676 PetscInt data,gid1 = aij->j[aij->i[i] + j] + 1; 3677 ierr = PetscTableFind(gid1_lid1,gid1,&data);CHKERRQ(ierr); 3678 if (!data) { 3679 /* one based table */ 3680 ierr = PetscTableAdd(gid1_lid1,gid1,++ec,INSERT_VALUES);CHKERRQ(ierr); 3681 } 3682 } 3683 } 3684 /* form array of columns we need */ 3685 ierr = PetscMalloc1(ec+1,&garray);CHKERRQ(ierr); 3686 ierr = PetscTableGetHeadPosition(gid1_lid1,&tpos);CHKERRQ(ierr); 3687 while (tpos) { 3688 ierr = PetscTableGetNext(gid1_lid1,&tpos,&gid,&lid);CHKERRQ(ierr); 3689 gid--; 3690 lid--; 3691 garray[lid] = gid; 3692 } 3693 ierr = PetscSortInt(ec,garray);CHKERRQ(ierr); /* sort, and rebuild */ 3694 ierr = PetscTableRemoveAll(gid1_lid1);CHKERRQ(ierr); 3695 for (i=0; i<ec; i++) { 3696 ierr = PetscTableAdd(gid1_lid1,garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 3697 } 3698 /* compact out the extra columns in B */ 3699 for (i=0; i<mat->rmap->n; i++) { 3700 ncols = aij->i[i+1] - aij->i[i]; 3701 for (j=0; j<ncols; j++) { 3702 PetscInt gid1 = aij->j[aij->i[i] + j] + 1; 3703 ierr = PetscTableFind(gid1_lid1,gid1,&lid);CHKERRQ(ierr); 3704 lid--; 3705 aij->j[aij->i[i] + j] = lid; 3706 } 3707 } 3708 ierr = PetscLayoutDestroy(&mat->cmap);CHKERRQ(ierr); 3709 ierr = PetscLayoutCreateFromSizes(PetscObjectComm((PetscObject)mat),ec,ec,1,&mat->cmap);CHKERRQ(ierr); 3710 ierr = PetscTableDestroy(&gid1_lid1);CHKERRQ(ierr); 3711 ierr = ISLocalToGlobalMappingCreate(PETSC_COMM_SELF,mat->cmap->bs,mat->cmap->n,garray,PETSC_OWN_POINTER,mapping);CHKERRQ(ierr); 3712 ierr = ISLocalToGlobalMappingSetType(*mapping,ISLOCALTOGLOBALMAPPINGHASH);CHKERRQ(ierr); 3713 PetscFunctionReturn(0); 3714 } 3715 3716 /*@ 3717 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3718 in the matrix. 3719 3720 Input Parameters: 3721 + mat - the SeqAIJ matrix 3722 - indices - the column indices 3723 3724 Level: advanced 3725 3726 Notes: 3727 This can be called if you have precomputed the nonzero structure of the 3728 matrix and want to provide it to the matrix object to improve the performance 3729 of the MatSetValues() operation. 3730 3731 You MUST have set the correct numbers of nonzeros per row in the call to 3732 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3733 3734 MUST be called before any calls to MatSetValues(); 3735 3736 The indices should start with zero, not one. 3737 3738 @*/ 3739 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3740 { 3741 PetscErrorCode ierr; 3742 3743 PetscFunctionBegin; 3744 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3745 PetscValidPointer(indices,2); 3746 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3747 PetscFunctionReturn(0); 3748 } 3749 3750 /* ----------------------------------------------------------------------------------------*/ 3751 3752 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3753 { 3754 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3755 PetscErrorCode ierr; 3756 size_t nz = aij->i[mat->rmap->n]; 3757 3758 PetscFunctionBegin; 3759 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3760 3761 /* allocate space for values if not already there */ 3762 if (!aij->saved_values) { 3763 ierr = PetscMalloc1(nz+1,&aij->saved_values);CHKERRQ(ierr); 3764 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3765 } 3766 3767 /* copy values over */ 3768 ierr = PetscArraycpy(aij->saved_values,aij->a,nz);CHKERRQ(ierr); 3769 PetscFunctionReturn(0); 3770 } 3771 3772 /*@ 3773 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3774 example, reuse of the linear part of a Jacobian, while recomputing the 3775 nonlinear portion. 3776 3777 Collect on Mat 3778 3779 Input Parameters: 3780 . mat - the matrix (currently only AIJ matrices support this option) 3781 3782 Level: advanced 3783 3784 Common Usage, with SNESSolve(): 3785 $ Create Jacobian matrix 3786 $ Set linear terms into matrix 3787 $ Apply boundary conditions to matrix, at this time matrix must have 3788 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3789 $ boundary conditions again will not change the nonzero structure 3790 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3791 $ ierr = MatStoreValues(mat); 3792 $ Call SNESSetJacobian() with matrix 3793 $ In your Jacobian routine 3794 $ ierr = MatRetrieveValues(mat); 3795 $ Set nonlinear terms in matrix 3796 3797 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3798 $ // build linear portion of Jacobian 3799 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3800 $ ierr = MatStoreValues(mat); 3801 $ loop over nonlinear iterations 3802 $ ierr = MatRetrieveValues(mat); 3803 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3804 $ // call MatAssemblyBegin/End() on matrix 3805 $ Solve linear system with Jacobian 3806 $ endloop 3807 3808 Notes: 3809 Matrix must already be assemblied before calling this routine 3810 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3811 calling this routine. 3812 3813 When this is called multiple times it overwrites the previous set of stored values 3814 and does not allocated additional space. 3815 3816 .seealso: MatRetrieveValues() 3817 3818 @*/ 3819 PetscErrorCode MatStoreValues(Mat mat) 3820 { 3821 PetscErrorCode ierr; 3822 3823 PetscFunctionBegin; 3824 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3825 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3826 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3827 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3828 PetscFunctionReturn(0); 3829 } 3830 3831 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3832 { 3833 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3834 PetscErrorCode ierr; 3835 PetscInt nz = aij->i[mat->rmap->n]; 3836 3837 PetscFunctionBegin; 3838 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3839 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3840 /* copy values over */ 3841 ierr = PetscArraycpy(aij->a,aij->saved_values,nz);CHKERRQ(ierr); 3842 PetscFunctionReturn(0); 3843 } 3844 3845 /*@ 3846 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3847 example, reuse of the linear part of a Jacobian, while recomputing the 3848 nonlinear portion. 3849 3850 Collect on Mat 3851 3852 Input Parameters: 3853 . mat - the matrix (currently only AIJ matrices support this option) 3854 3855 Level: advanced 3856 3857 .seealso: MatStoreValues() 3858 3859 @*/ 3860 PetscErrorCode MatRetrieveValues(Mat mat) 3861 { 3862 PetscErrorCode ierr; 3863 3864 PetscFunctionBegin; 3865 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3866 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3867 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3868 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3869 PetscFunctionReturn(0); 3870 } 3871 3872 3873 /* --------------------------------------------------------------------------------*/ 3874 /*@C 3875 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3876 (the default parallel PETSc format). For good matrix assembly performance 3877 the user should preallocate the matrix storage by setting the parameter nz 3878 (or the array nnz). By setting these parameters accurately, performance 3879 during matrix assembly can be increased by more than a factor of 50. 3880 3881 Collective 3882 3883 Input Parameters: 3884 + comm - MPI communicator, set to PETSC_COMM_SELF 3885 . m - number of rows 3886 . n - number of columns 3887 . nz - number of nonzeros per row (same for all rows) 3888 - nnz - array containing the number of nonzeros in the various rows 3889 (possibly different for each row) or NULL 3890 3891 Output Parameter: 3892 . A - the matrix 3893 3894 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3895 MatXXXXSetPreallocation() paradigm instead of this routine directly. 3896 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3897 3898 Notes: 3899 If nnz is given then nz is ignored 3900 3901 The AIJ format (also called the Yale sparse matrix format or 3902 compressed row storage), is fully compatible with standard Fortran 77 3903 storage. That is, the stored row and column indices can begin at 3904 either one (as in Fortran) or zero. See the users' manual for details. 3905 3906 Specify the preallocated storage with either nz or nnz (not both). 3907 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3908 allocation. For large problems you MUST preallocate memory or you 3909 will get TERRIBLE performance, see the users' manual chapter on matrices. 3910 3911 By default, this format uses inodes (identical nodes) when possible, to 3912 improve numerical efficiency of matrix-vector products and solves. We 3913 search for consecutive rows with the same nonzero structure, thereby 3914 reusing matrix information to achieve increased efficiency. 3915 3916 Options Database Keys: 3917 + -mat_no_inode - Do not use inodes 3918 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3919 3920 Level: intermediate 3921 3922 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3923 3924 @*/ 3925 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3926 { 3927 PetscErrorCode ierr; 3928 3929 PetscFunctionBegin; 3930 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3931 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3932 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3933 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3934 PetscFunctionReturn(0); 3935 } 3936 3937 /*@C 3938 MatSeqAIJSetPreallocation - For good matrix assembly performance 3939 the user should preallocate the matrix storage by setting the parameter nz 3940 (or the array nnz). By setting these parameters accurately, performance 3941 during matrix assembly can be increased by more than a factor of 50. 3942 3943 Collective 3944 3945 Input Parameters: 3946 + B - The matrix 3947 . nz - number of nonzeros per row (same for all rows) 3948 - nnz - array containing the number of nonzeros in the various rows 3949 (possibly different for each row) or NULL 3950 3951 Notes: 3952 If nnz is given then nz is ignored 3953 3954 The AIJ format (also called the Yale sparse matrix format or 3955 compressed row storage), is fully compatible with standard Fortran 77 3956 storage. That is, the stored row and column indices can begin at 3957 either one (as in Fortran) or zero. See the users' manual for details. 3958 3959 Specify the preallocated storage with either nz or nnz (not both). 3960 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3961 allocation. For large problems you MUST preallocate memory or you 3962 will get TERRIBLE performance, see the users' manual chapter on matrices. 3963 3964 You can call MatGetInfo() to get information on how effective the preallocation was; 3965 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3966 You can also run with the option -info and look for messages with the string 3967 malloc in them to see if additional memory allocation was needed. 3968 3969 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3970 entries or columns indices 3971 3972 By default, this format uses inodes (identical nodes) when possible, to 3973 improve numerical efficiency of matrix-vector products and solves. We 3974 search for consecutive rows with the same nonzero structure, thereby 3975 reusing matrix information to achieve increased efficiency. 3976 3977 Options Database Keys: 3978 + -mat_no_inode - Do not use inodes 3979 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3980 3981 Level: intermediate 3982 3983 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo(), 3984 MatSeqAIJSetTotalPreallocation() 3985 3986 @*/ 3987 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3988 { 3989 PetscErrorCode ierr; 3990 3991 PetscFunctionBegin; 3992 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3993 PetscValidType(B,1); 3994 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3995 PetscFunctionReturn(0); 3996 } 3997 3998 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3999 { 4000 Mat_SeqAIJ *b; 4001 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 4002 PetscErrorCode ierr; 4003 PetscInt i; 4004 4005 PetscFunctionBegin; 4006 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 4007 if (nz == MAT_SKIP_ALLOCATION) { 4008 skipallocation = PETSC_TRUE; 4009 nz = 0; 4010 } 4011 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 4012 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 4013 4014 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 4015 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 4016 if (PetscUnlikelyDebug(nnz)) { 4017 for (i=0; i<B->rmap->n; i++) { 4018 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]); 4019 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); 4020 } 4021 } 4022 4023 B->preallocated = PETSC_TRUE; 4024 4025 b = (Mat_SeqAIJ*)B->data; 4026 4027 if (!skipallocation) { 4028 if (!b->imax) { 4029 ierr = PetscMalloc1(B->rmap->n,&b->imax);CHKERRQ(ierr); 4030 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 4031 } 4032 if (!b->ilen) { 4033 /* b->ilen will count nonzeros in each row so far. */ 4034 ierr = PetscCalloc1(B->rmap->n,&b->ilen);CHKERRQ(ierr); 4035 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 4036 } else { 4037 ierr = PetscMemzero(b->ilen,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 4038 } 4039 if (!b->ipre) { 4040 ierr = PetscMalloc1(B->rmap->n,&b->ipre);CHKERRQ(ierr); 4041 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 4042 } 4043 if (!nnz) { 4044 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 4045 else if (nz < 0) nz = 1; 4046 nz = PetscMin(nz,B->cmap->n); 4047 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 4048 nz = nz*B->rmap->n; 4049 } else { 4050 PetscInt64 nz64 = 0; 4051 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz64 += nnz[i];} 4052 ierr = PetscIntCast(nz64,&nz);CHKERRQ(ierr); 4053 } 4054 4055 /* allocate the matrix space */ 4056 /* FIXME: should B's old memory be unlogged? */ 4057 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 4058 if (B->structure_only) { 4059 ierr = PetscMalloc1(nz,&b->j);CHKERRQ(ierr); 4060 ierr = PetscMalloc1(B->rmap->n+1,&b->i);CHKERRQ(ierr); 4061 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));CHKERRQ(ierr); 4062 } else { 4063 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 4064 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 4065 } 4066 b->i[0] = 0; 4067 for (i=1; i<B->rmap->n+1; i++) { 4068 b->i[i] = b->i[i-1] + b->imax[i-1]; 4069 } 4070 if (B->structure_only) { 4071 b->singlemalloc = PETSC_FALSE; 4072 b->free_a = PETSC_FALSE; 4073 } else { 4074 b->singlemalloc = PETSC_TRUE; 4075 b->free_a = PETSC_TRUE; 4076 } 4077 b->free_ij = PETSC_TRUE; 4078 } else { 4079 b->free_a = PETSC_FALSE; 4080 b->free_ij = PETSC_FALSE; 4081 } 4082 4083 if (b->ipre && nnz != b->ipre && b->imax) { 4084 /* reserve user-requested sparsity */ 4085 ierr = PetscArraycpy(b->ipre,b->imax,B->rmap->n);CHKERRQ(ierr); 4086 } 4087 4088 4089 b->nz = 0; 4090 b->maxnz = nz; 4091 B->info.nz_unneeded = (double)b->maxnz; 4092 if (realalloc) { 4093 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 4094 } 4095 B->was_assembled = PETSC_FALSE; 4096 B->assembled = PETSC_FALSE; 4097 PetscFunctionReturn(0); 4098 } 4099 4100 4101 PetscErrorCode MatResetPreallocation_SeqAIJ(Mat A) 4102 { 4103 Mat_SeqAIJ *a; 4104 PetscInt i; 4105 PetscErrorCode ierr; 4106 4107 PetscFunctionBegin; 4108 PetscValidHeaderSpecific(A,MAT_CLASSID,1); 4109 4110 /* Check local size. If zero, then return */ 4111 if (!A->rmap->n) PetscFunctionReturn(0); 4112 4113 a = (Mat_SeqAIJ*)A->data; 4114 /* if no saved info, we error out */ 4115 if (!a->ipre) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"No saved preallocation info \n"); 4116 4117 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"); 4118 4119 ierr = PetscArraycpy(a->imax,a->ipre,A->rmap->n);CHKERRQ(ierr); 4120 ierr = PetscArrayzero(a->ilen,A->rmap->n);CHKERRQ(ierr); 4121 a->i[0] = 0; 4122 for (i=1; i<A->rmap->n+1; i++) { 4123 a->i[i] = a->i[i-1] + a->imax[i-1]; 4124 } 4125 A->preallocated = PETSC_TRUE; 4126 a->nz = 0; 4127 a->maxnz = a->i[A->rmap->n]; 4128 A->info.nz_unneeded = (double)a->maxnz; 4129 A->was_assembled = PETSC_FALSE; 4130 A->assembled = PETSC_FALSE; 4131 PetscFunctionReturn(0); 4132 } 4133 4134 /*@ 4135 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 4136 4137 Input Parameters: 4138 + B - the matrix 4139 . i - the indices into j for the start of each row (starts with zero) 4140 . j - the column indices for each row (starts with zero) these must be sorted for each row 4141 - v - optional values in the matrix 4142 4143 Level: developer 4144 4145 Notes: 4146 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 4147 4148 This routine may be called multiple times with different nonzero patterns (or the same nonzero pattern). The nonzero 4149 structure will be the union of all the previous nonzero structures. 4150 4151 Developer Notes: 4152 An optimization could be added to the implementation where it checks if the i, and j are identical to the current i and j and 4153 then just copies the v values directly with PetscMemcpy(). 4154 4155 This routine could also take a PetscCopyMode argument to allow sharing the values instead of always copying them. 4156 4157 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), MATSEQAIJ, MatResetPreallocation() 4158 @*/ 4159 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 4160 { 4161 PetscErrorCode ierr; 4162 4163 PetscFunctionBegin; 4164 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4165 PetscValidType(B,1); 4166 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 4167 PetscFunctionReturn(0); 4168 } 4169 4170 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 4171 { 4172 PetscInt i; 4173 PetscInt m,n; 4174 PetscInt nz; 4175 PetscInt *nnz; 4176 PetscErrorCode ierr; 4177 4178 PetscFunctionBegin; 4179 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 4180 4181 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 4182 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 4183 4184 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 4185 ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); 4186 for (i = 0; i < m; i++) { 4187 nz = Ii[i+1]- Ii[i]; 4188 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 4189 nnz[i] = nz; 4190 } 4191 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 4192 ierr = PetscFree(nnz);CHKERRQ(ierr); 4193 4194 for (i = 0; i < m; i++) { 4195 ierr = MatSetValues_SeqAIJ(B, 1, &i, Ii[i+1] - Ii[i], J+Ii[i], v ? v + Ii[i] : NULL, INSERT_VALUES);CHKERRQ(ierr); 4196 } 4197 4198 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4199 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4200 4201 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 4202 PetscFunctionReturn(0); 4203 } 4204 4205 #include <../src/mat/impls/dense/seq/dense.h> 4206 #include <petsc/private/kernels/petscaxpy.h> 4207 4208 /* 4209 Computes (B'*A')' since computing B*A directly is untenable 4210 4211 n p p 4212 [ ] [ ] [ ] 4213 m [ A ] * n [ B ] = m [ C ] 4214 [ ] [ ] [ ] 4215 4216 */ 4217 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 4218 { 4219 PetscErrorCode ierr; 4220 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 4221 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 4222 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 4223 PetscInt i,j,n,m,q,p; 4224 const PetscInt *ii,*idx; 4225 const PetscScalar *b,*a,*a_q; 4226 PetscScalar *c,*c_q; 4227 PetscInt clda = sub_c->lda; 4228 PetscInt alda = sub_a->lda; 4229 4230 PetscFunctionBegin; 4231 m = A->rmap->n; 4232 n = A->cmap->n; 4233 p = B->cmap->n; 4234 a = sub_a->v; 4235 b = sub_b->a; 4236 c = sub_c->v; 4237 if (clda == m) { 4238 ierr = PetscArrayzero(c,m*p);CHKERRQ(ierr); 4239 } else { 4240 for (j=0;j<p;j++) 4241 for (i=0;i<m;i++) 4242 c[j*clda + i] = 0.0; 4243 } 4244 ii = sub_b->i; 4245 idx = sub_b->j; 4246 for (i=0; i<n; i++) { 4247 q = ii[i+1] - ii[i]; 4248 while (q-->0) { 4249 c_q = c + clda*(*idx); 4250 a_q = a + alda*i; 4251 PetscKernelAXPY(c_q,*b,a_q,m); 4252 idx++; 4253 b++; 4254 } 4255 } 4256 PetscFunctionReturn(0); 4257 } 4258 4259 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat C) 4260 { 4261 PetscErrorCode ierr; 4262 PetscInt m=A->rmap->n,n=B->cmap->n; 4263 PetscBool cisdense; 4264 4265 PetscFunctionBegin; 4266 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); 4267 ierr = MatSetSizes(C,m,n,m,n);CHKERRQ(ierr); 4268 ierr = MatSetBlockSizesFromMats(C,A,B);CHKERRQ(ierr); 4269 ierr = PetscObjectTypeCompareAny((PetscObject)C,&cisdense,MATSEQDENSE,MATSEQDENSECUDA,"");CHKERRQ(ierr); 4270 if (!cisdense) { 4271 ierr = MatSetType(C,MATDENSE);CHKERRQ(ierr); 4272 } 4273 ierr = MatSetUp(C);CHKERRQ(ierr); 4274 4275 C->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 4276 PetscFunctionReturn(0); 4277 } 4278 4279 /* ----------------------------------------------------------------*/ 4280 /*MC 4281 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 4282 based on compressed sparse row format. 4283 4284 Options Database Keys: 4285 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 4286 4287 Level: beginner 4288 4289 Notes: 4290 MatSetValues() may be called for this matrix type with a NULL argument for the numerical values, 4291 in this case the values associated with the rows and columns one passes in are set to zero 4292 in the matrix 4293 4294 MatSetOptions(,MAT_STRUCTURE_ONLY,PETSC_TRUE) may be called for this matrix type. In this no 4295 space is allocated for the nonzero entries and any entries passed with MatSetValues() are ignored 4296 4297 Developer Notes: 4298 It would be nice if all matrix formats supported passing NULL in for the numerical values 4299 4300 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 4301 M*/ 4302 4303 /*MC 4304 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 4305 4306 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 4307 and MATMPIAIJ otherwise. As a result, for single process communicators, 4308 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation() is supported 4309 for communicators controlling multiple processes. It is recommended that you call both of 4310 the above preallocation routines for simplicity. 4311 4312 Options Database Keys: 4313 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 4314 4315 Developer Notes: 4316 Subclasses include MATAIJCUSPARSE, MATAIJPERM, MATAIJSELL, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when 4317 enough exist. 4318 4319 Level: beginner 4320 4321 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 4322 M*/ 4323 4324 /*MC 4325 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 4326 4327 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 4328 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 4329 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 4330 for communicators controlling multiple processes. It is recommended that you call both of 4331 the above preallocation routines for simplicity. 4332 4333 Options Database Keys: 4334 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 4335 4336 Level: beginner 4337 4338 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 4339 M*/ 4340 4341 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 4342 #if defined(PETSC_HAVE_ELEMENTAL) 4343 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4344 #endif 4345 #if defined(PETSC_HAVE_SCALAPACK) 4346 PETSC_INTERN PetscErrorCode MatConvert_AIJ_ScaLAPACK(Mat,MatType,MatReuse,Mat*); 4347 #endif 4348 #if defined(PETSC_HAVE_HYPRE) 4349 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat A,MatType,MatReuse,Mat*); 4350 #endif 4351 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*); 4352 4353 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqSELL(Mat,MatType,MatReuse,Mat*); 4354 PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*); 4355 PETSC_INTERN PetscErrorCode MatProductSetFromOptions_IS_XAIJ(Mat); 4356 4357 /*@C 4358 MatSeqAIJGetArray - gives read/write access to the array where the data for a MATSEQAIJ matrix is stored 4359 4360 Not Collective 4361 4362 Input Parameter: 4363 . mat - a MATSEQAIJ matrix 4364 4365 Output Parameter: 4366 . array - pointer to the data 4367 4368 Level: intermediate 4369 4370 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4371 @*/ 4372 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4373 { 4374 PetscErrorCode ierr; 4375 4376 PetscFunctionBegin; 4377 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4378 PetscFunctionReturn(0); 4379 } 4380 4381 /*@C 4382 MatSeqAIJGetArrayRead - gives read-only access to the array where the data for a MATSEQAIJ matrix is stored 4383 4384 Not Collective 4385 4386 Input Parameter: 4387 . mat - a MATSEQAIJ matrix 4388 4389 Output Parameter: 4390 . array - pointer to the data 4391 4392 Level: intermediate 4393 4394 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayRead() 4395 @*/ 4396 PetscErrorCode MatSeqAIJGetArrayRead(Mat A,const PetscScalar **array) 4397 { 4398 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4399 PetscOffloadMask oval; 4400 #endif 4401 PetscErrorCode ierr; 4402 4403 PetscFunctionBegin; 4404 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4405 oval = A->offloadmask; 4406 #endif 4407 ierr = MatSeqAIJGetArray(A,(PetscScalar**)array);CHKERRQ(ierr); 4408 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4409 if (oval == PETSC_OFFLOAD_GPU || oval == PETSC_OFFLOAD_BOTH) A->offloadmask = PETSC_OFFLOAD_BOTH; 4410 #endif 4411 PetscFunctionReturn(0); 4412 } 4413 4414 /*@C 4415 MatSeqAIJRestoreArrayRead - restore the read-only access array obtained from MatSeqAIJGetArrayRead 4416 4417 Not Collective 4418 4419 Input Parameter: 4420 . mat - a MATSEQAIJ matrix 4421 4422 Output Parameter: 4423 . array - pointer to the data 4424 4425 Level: intermediate 4426 4427 .seealso: MatSeqAIJGetArray(), MatSeqAIJGetArrayRead() 4428 @*/ 4429 PetscErrorCode MatSeqAIJRestoreArrayRead(Mat A,const PetscScalar **array) 4430 { 4431 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4432 PetscOffloadMask oval; 4433 #endif 4434 PetscErrorCode ierr; 4435 4436 PetscFunctionBegin; 4437 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4438 oval = A->offloadmask; 4439 #endif 4440 ierr = MatSeqAIJRestoreArray(A,(PetscScalar**)array);CHKERRQ(ierr); 4441 #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL) 4442 A->offloadmask = oval; 4443 #endif 4444 PetscFunctionReturn(0); 4445 } 4446 4447 /*@C 4448 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 4449 4450 Not Collective 4451 4452 Input Parameter: 4453 . mat - a MATSEQAIJ matrix 4454 4455 Output Parameter: 4456 . nz - the maximum number of nonzeros in any row 4457 4458 Level: intermediate 4459 4460 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4461 @*/ 4462 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 4463 { 4464 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 4465 4466 PetscFunctionBegin; 4467 *nz = aij->rmax; 4468 PetscFunctionReturn(0); 4469 } 4470 4471 /*@C 4472 MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() 4473 4474 Not Collective 4475 4476 Input Parameters: 4477 + mat - a MATSEQAIJ matrix 4478 - array - pointer to the data 4479 4480 Level: intermediate 4481 4482 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4483 @*/ 4484 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4485 { 4486 PetscErrorCode ierr; 4487 4488 PetscFunctionBegin; 4489 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4490 PetscFunctionReturn(0); 4491 } 4492 4493 #if defined(PETSC_HAVE_CUDA) 4494 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCUSPARSE(Mat); 4495 #endif 4496 4497 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4498 { 4499 Mat_SeqAIJ *b; 4500 PetscErrorCode ierr; 4501 PetscMPIInt size; 4502 4503 PetscFunctionBegin; 4504 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4505 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4506 4507 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 4508 4509 B->data = (void*)b; 4510 4511 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4512 if (B->sortedfull) B->ops->setvalues = MatSetValues_SeqAIJ_SortedFull; 4513 4514 b->row = NULL; 4515 b->col = NULL; 4516 b->icol = NULL; 4517 b->reallocs = 0; 4518 b->ignorezeroentries = PETSC_FALSE; 4519 b->roworiented = PETSC_TRUE; 4520 b->nonew = 0; 4521 b->diag = NULL; 4522 b->solve_work = NULL; 4523 B->spptr = NULL; 4524 b->saved_values = NULL; 4525 b->idiag = NULL; 4526 b->mdiag = NULL; 4527 b->ssor_work = NULL; 4528 b->omega = 1.0; 4529 b->fshift = 0.0; 4530 b->idiagvalid = PETSC_FALSE; 4531 b->ibdiagvalid = PETSC_FALSE; 4532 b->keepnonzeropattern = PETSC_FALSE; 4533 4534 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4535 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4536 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4537 4538 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4539 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4540 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4541 #endif 4542 4543 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4544 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4545 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4546 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4547 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4548 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4549 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijsell_C",MatConvert_SeqAIJ_SeqAIJSELL);CHKERRQ(ierr); 4550 #if defined(PETSC_HAVE_MKL_SPARSE) 4551 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijmkl_C",MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 4552 #endif 4553 #if defined(PETSC_HAVE_CUDA) 4554 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcusparse_C",MatConvert_SeqAIJ_SeqAIJCUSPARSE);CHKERRQ(ierr); 4555 ierr = PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_seqaijcusparse_seqaij_C",MatProductSetFromOptions_SeqAIJ);CHKERRQ(ierr); 4556 #endif 4557 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4558 #if defined(PETSC_HAVE_ELEMENTAL) 4559 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); 4560 #endif 4561 #if defined(PETSC_HAVE_SCALAPACK) 4562 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_scalapack_C",MatConvert_AIJ_ScaLAPACK);CHKERRQ(ierr); 4563 #endif 4564 #if defined(PETSC_HAVE_HYPRE) 4565 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 4566 ierr = PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_transpose_seqaij_seqaij_C",MatProductSetFromOptions_Transpose_AIJ_AIJ);CHKERRQ(ierr); 4567 #endif 4568 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); 4569 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsell_C",MatConvert_SeqAIJ_SeqSELL);CHKERRQ(ierr); 4570 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_is_C",MatConvert_XAIJ_IS);CHKERRQ(ierr); 4571 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4572 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4573 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4574 ierr = PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_SeqAIJ);CHKERRQ(ierr); 4575 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4576 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4577 ierr = PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_is_seqaij_C",MatProductSetFromOptions_IS_XAIJ);CHKERRQ(ierr); 4578 ierr = PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_seqdense_seqaij_C",MatProductSetFromOptions_SeqDense_SeqAIJ);CHKERRQ(ierr); 4579 ierr = PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_seqaij_seqaij_C",MatProductSetFromOptions_SeqAIJ);CHKERRQ(ierr); 4580 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4581 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4582 ierr = MatSeqAIJSetTypeFromOptions(B);CHKERRQ(ierr); /* this allows changing the matrix subtype to say MATSEQAIJPERM */ 4583 PetscFunctionReturn(0); 4584 } 4585 4586 /* 4587 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4588 */ 4589 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4590 { 4591 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data,*a = (Mat_SeqAIJ*)A->data; 4592 PetscErrorCode ierr; 4593 PetscInt m = A->rmap->n,i; 4594 4595 PetscFunctionBegin; 4596 if (!A->assembled && cpvalues!=MAT_DO_NOT_COPY_VALUES) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot duplicate unassembled matrix"); 4597 4598 C->factortype = A->factortype; 4599 c->row = NULL; 4600 c->col = NULL; 4601 c->icol = NULL; 4602 c->reallocs = 0; 4603 4604 C->assembled = PETSC_TRUE; 4605 4606 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4607 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4608 4609 ierr = PetscMalloc1(m,&c->imax);CHKERRQ(ierr); 4610 ierr = PetscMemcpy(c->imax,a->imax,m*sizeof(PetscInt));CHKERRQ(ierr); 4611 ierr = PetscMalloc1(m,&c->ilen);CHKERRQ(ierr); 4612 ierr = PetscMemcpy(c->ilen,a->ilen,m*sizeof(PetscInt));CHKERRQ(ierr); 4613 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4614 4615 /* allocate the matrix space */ 4616 if (mallocmatspace) { 4617 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4618 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4619 4620 c->singlemalloc = PETSC_TRUE; 4621 4622 ierr = PetscArraycpy(c->i,a->i,m+1);CHKERRQ(ierr); 4623 if (m > 0) { 4624 ierr = PetscArraycpy(c->j,a->j,a->i[m]);CHKERRQ(ierr); 4625 if (cpvalues == MAT_COPY_VALUES) { 4626 ierr = PetscArraycpy(c->a,a->a,a->i[m]);CHKERRQ(ierr); 4627 } else { 4628 ierr = PetscArrayzero(c->a,a->i[m]);CHKERRQ(ierr); 4629 } 4630 } 4631 } 4632 4633 c->ignorezeroentries = a->ignorezeroentries; 4634 c->roworiented = a->roworiented; 4635 c->nonew = a->nonew; 4636 if (a->diag) { 4637 ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); 4638 ierr = PetscMemcpy(c->diag,a->diag,m*sizeof(PetscInt));CHKERRQ(ierr); 4639 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4640 } else c->diag = NULL; 4641 4642 c->solve_work = NULL; 4643 c->saved_values = NULL; 4644 c->idiag = NULL; 4645 c->ssor_work = NULL; 4646 c->keepnonzeropattern = a->keepnonzeropattern; 4647 c->free_a = PETSC_TRUE; 4648 c->free_ij = PETSC_TRUE; 4649 4650 c->rmax = a->rmax; 4651 c->nz = a->nz; 4652 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4653 C->preallocated = PETSC_TRUE; 4654 4655 c->compressedrow.use = a->compressedrow.use; 4656 c->compressedrow.nrows = a->compressedrow.nrows; 4657 if (a->compressedrow.use) { 4658 i = a->compressedrow.nrows; 4659 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4660 ierr = PetscArraycpy(c->compressedrow.i,a->compressedrow.i,i+1);CHKERRQ(ierr); 4661 ierr = PetscArraycpy(c->compressedrow.rindex,a->compressedrow.rindex,i);CHKERRQ(ierr); 4662 } else { 4663 c->compressedrow.use = PETSC_FALSE; 4664 c->compressedrow.i = NULL; 4665 c->compressedrow.rindex = NULL; 4666 } 4667 c->nonzerorowcnt = a->nonzerorowcnt; 4668 C->nonzerostate = A->nonzerostate; 4669 4670 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4671 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4672 PetscFunctionReturn(0); 4673 } 4674 4675 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4676 { 4677 PetscErrorCode ierr; 4678 4679 PetscFunctionBegin; 4680 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4681 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4682 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4683 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4684 } 4685 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4686 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4687 PetscFunctionReturn(0); 4688 } 4689 4690 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4691 { 4692 PetscBool isbinary, ishdf5; 4693 PetscErrorCode ierr; 4694 4695 PetscFunctionBegin; 4696 PetscValidHeaderSpecific(newMat,MAT_CLASSID,1); 4697 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 4698 /* force binary viewer to load .info file if it has not yet done so */ 4699 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4700 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 4701 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERHDF5, &ishdf5);CHKERRQ(ierr); 4702 if (isbinary) { 4703 ierr = MatLoad_SeqAIJ_Binary(newMat,viewer);CHKERRQ(ierr); 4704 } else if (ishdf5) { 4705 #if defined(PETSC_HAVE_HDF5) 4706 ierr = MatLoad_AIJ_HDF5(newMat,viewer);CHKERRQ(ierr); 4707 #else 4708 SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"HDF5 not supported in this build.\nPlease reconfigure using --download-hdf5"); 4709 #endif 4710 } else { 4711 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); 4712 } 4713 PetscFunctionReturn(0); 4714 } 4715 4716 PetscErrorCode MatLoad_SeqAIJ_Binary(Mat mat, PetscViewer viewer) 4717 { 4718 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->data; 4719 PetscErrorCode ierr; 4720 PetscInt header[4],*rowlens,M,N,nz,sum,rows,cols,i; 4721 4722 PetscFunctionBegin; 4723 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4724 4725 /* read in matrix header */ 4726 ierr = PetscViewerBinaryRead(viewer,header,4,NULL,PETSC_INT);CHKERRQ(ierr); 4727 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Not a matrix object in file"); 4728 M = header[1]; N = header[2]; nz = header[3]; 4729 if (M < 0) SETERRQ1(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Matrix row size (%D) in file is negative",M); 4730 if (N < 0) SETERRQ1(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Matrix column size (%D) in file is negative",N); 4731 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk, cannot load as SeqAIJ"); 4732 4733 /* set block sizes from the viewer's .info file */ 4734 ierr = MatLoad_Binary_BlockSizes(mat,viewer);CHKERRQ(ierr); 4735 /* set local and global sizes if not set already */ 4736 if (mat->rmap->n < 0) mat->rmap->n = M; 4737 if (mat->cmap->n < 0) mat->cmap->n = N; 4738 if (mat->rmap->N < 0) mat->rmap->N = M; 4739 if (mat->cmap->N < 0) mat->cmap->N = N; 4740 ierr = PetscLayoutSetUp(mat->rmap);CHKERRQ(ierr); 4741 ierr = PetscLayoutSetUp(mat->cmap);CHKERRQ(ierr); 4742 4743 /* check if the matrix sizes are correct */ 4744 ierr = MatGetSize(mat,&rows,&cols);CHKERRQ(ierr); 4745 if (M != rows || N != cols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different sizes (%D, %D) than the input matrix (%D, %D)",M,N,rows,cols); 4746 4747 /* read in row lengths */ 4748 ierr = PetscMalloc1(M,&rowlens);CHKERRQ(ierr); 4749 ierr = PetscViewerBinaryRead(viewer,rowlens,M,NULL,PETSC_INT);CHKERRQ(ierr); 4750 /* check if sum(rowlens) is same as nz */ 4751 sum = 0; for (i=0; i<M; i++) sum += rowlens[i]; 4752 if (sum != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent matrix data in file: nonzeros = %D, sum-row-lengths = %D\n",nz,sum); 4753 /* preallocate and check sizes */ 4754 ierr = MatSeqAIJSetPreallocation_SeqAIJ(mat,0,rowlens);CHKERRQ(ierr); 4755 ierr = MatGetSize(mat,&rows,&cols);CHKERRQ(ierr); 4756 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); 4757 /* store row lengths */ 4758 ierr = PetscArraycpy(a->ilen,rowlens,M);CHKERRQ(ierr); 4759 ierr = PetscFree(rowlens);CHKERRQ(ierr); 4760 4761 /* fill in "i" row pointers */ 4762 a->i[0] = 0; for (i=0; i<M; i++) a->i[i+1] = a->i[i] + a->ilen[i]; 4763 /* read in "j" column indices */ 4764 ierr = PetscViewerBinaryRead(viewer,a->j,nz,NULL,PETSC_INT);CHKERRQ(ierr); 4765 /* read in "a" nonzero values */ 4766 ierr = PetscViewerBinaryRead(viewer,a->a,nz,NULL,PETSC_SCALAR);CHKERRQ(ierr); 4767 4768 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4769 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4770 PetscFunctionReturn(0); 4771 } 4772 4773 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4774 { 4775 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4776 PetscErrorCode ierr; 4777 #if defined(PETSC_USE_COMPLEX) 4778 PetscInt k; 4779 #endif 4780 4781 PetscFunctionBegin; 4782 /* If the matrix dimensions are not equal,or no of nonzeros */ 4783 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4784 *flg = PETSC_FALSE; 4785 PetscFunctionReturn(0); 4786 } 4787 4788 /* if the a->i are the same */ 4789 ierr = PetscArraycmp(a->i,b->i,A->rmap->n+1,flg);CHKERRQ(ierr); 4790 if (!*flg) PetscFunctionReturn(0); 4791 4792 /* if a->j are the same */ 4793 ierr = PetscArraycmp(a->j,b->j,a->nz,flg);CHKERRQ(ierr); 4794 if (!*flg) PetscFunctionReturn(0); 4795 4796 /* if a->a are the same */ 4797 #if defined(PETSC_USE_COMPLEX) 4798 for (k=0; k<a->nz; k++) { 4799 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4800 *flg = PETSC_FALSE; 4801 PetscFunctionReturn(0); 4802 } 4803 } 4804 #else 4805 ierr = PetscArraycmp(a->a,b->a,a->nz,flg);CHKERRQ(ierr); 4806 #endif 4807 PetscFunctionReturn(0); 4808 } 4809 4810 /*@ 4811 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4812 provided by the user. 4813 4814 Collective 4815 4816 Input Parameters: 4817 + comm - must be an MPI communicator of size 1 4818 . m - number of rows 4819 . n - number of columns 4820 . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix 4821 . j - column indices 4822 - a - matrix values 4823 4824 Output Parameter: 4825 . mat - the matrix 4826 4827 Level: intermediate 4828 4829 Notes: 4830 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4831 once the matrix is destroyed and not before 4832 4833 You cannot set new nonzero locations into this matrix, that will generate an error. 4834 4835 The i and j indices are 0 based 4836 4837 The format which is used for the sparse matrix input, is equivalent to a 4838 row-major ordering.. i.e for the following matrix, the input data expected is 4839 as shown 4840 4841 $ 1 0 0 4842 $ 2 0 3 4843 $ 4 5 6 4844 $ 4845 $ i = {0,1,3,6} [size = nrow+1 = 3+1] 4846 $ j = {0,0,2,0,1,2} [size = 6]; values must be sorted for each row 4847 $ v = {1,2,3,4,5,6} [size = 6] 4848 4849 4850 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4851 4852 @*/ 4853 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat) 4854 { 4855 PetscErrorCode ierr; 4856 PetscInt ii; 4857 Mat_SeqAIJ *aij; 4858 PetscInt jj; 4859 4860 PetscFunctionBegin; 4861 if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4862 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4863 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4864 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4865 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4866 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr); 4867 aij = (Mat_SeqAIJ*)(*mat)->data; 4868 ierr = PetscMalloc1(m,&aij->imax);CHKERRQ(ierr); 4869 ierr = PetscMalloc1(m,&aij->ilen);CHKERRQ(ierr); 4870 4871 aij->i = i; 4872 aij->j = j; 4873 aij->a = a; 4874 aij->singlemalloc = PETSC_FALSE; 4875 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4876 aij->free_a = PETSC_FALSE; 4877 aij->free_ij = PETSC_FALSE; 4878 4879 for (ii=0; ii<m; ii++) { 4880 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4881 if (PetscDefined(USE_DEBUG)) { 4882 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]); 4883 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4884 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); 4885 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); 4886 } 4887 } 4888 } 4889 if (PetscDefined(USE_DEBUG)) { 4890 for (ii=0; ii<aij->i[m]; ii++) { 4891 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4892 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]); 4893 } 4894 } 4895 4896 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4897 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4898 PetscFunctionReturn(0); 4899 } 4900 /*@C 4901 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4902 provided by the user. 4903 4904 Collective 4905 4906 Input Parameters: 4907 + comm - must be an MPI communicator of size 1 4908 . m - number of rows 4909 . n - number of columns 4910 . i - row indices 4911 . j - column indices 4912 . a - matrix values 4913 . nz - number of nonzeros 4914 - idx - 0 or 1 based 4915 4916 Output Parameter: 4917 . mat - the matrix 4918 4919 Level: intermediate 4920 4921 Notes: 4922 The i and j indices are 0 based 4923 4924 The format which is used for the sparse matrix input, is equivalent to a 4925 row-major ordering.. i.e for the following matrix, the input data expected is 4926 as shown: 4927 4928 1 0 0 4929 2 0 3 4930 4 5 6 4931 4932 i = {0,1,1,2,2,2} 4933 j = {0,0,2,0,1,2} 4934 v = {1,2,3,4,5,6} 4935 4936 4937 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4938 4939 @*/ 4940 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat,PetscInt nz,PetscBool idx) 4941 { 4942 PetscErrorCode ierr; 4943 PetscInt ii, *nnz, one = 1,row,col; 4944 4945 4946 PetscFunctionBegin; 4947 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4948 for (ii = 0; ii < nz; ii++) { 4949 nnz[i[ii] - !!idx] += 1; 4950 } 4951 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4952 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4953 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4954 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4955 for (ii = 0; ii < nz; ii++) { 4956 if (idx) { 4957 row = i[ii] - 1; 4958 col = j[ii] - 1; 4959 } else { 4960 row = i[ii]; 4961 col = j[ii]; 4962 } 4963 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4964 } 4965 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4966 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4967 ierr = PetscFree(nnz);CHKERRQ(ierr); 4968 PetscFunctionReturn(0); 4969 } 4970 4971 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4972 { 4973 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4974 PetscErrorCode ierr; 4975 4976 PetscFunctionBegin; 4977 a->idiagvalid = PETSC_FALSE; 4978 a->ibdiagvalid = PETSC_FALSE; 4979 4980 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4981 PetscFunctionReturn(0); 4982 } 4983 4984 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4985 { 4986 PetscErrorCode ierr; 4987 PetscMPIInt size; 4988 4989 PetscFunctionBegin; 4990 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4991 if (size == 1) { 4992 if (scall == MAT_INITIAL_MATRIX) { 4993 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4994 } else { 4995 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4996 } 4997 } else { 4998 ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); 4999 } 5000 PetscFunctionReturn(0); 5001 } 5002 5003 /* 5004 Permute A into C's *local* index space using rowemb,colemb. 5005 The embedding are supposed to be injections and the above implies that the range of rowemb is a subset 5006 of [0,m), colemb is in [0,n). 5007 If pattern == DIFFERENT_NONZERO_PATTERN, C is preallocated according to A. 5008 */ 5009 PetscErrorCode MatSetSeqMat_SeqAIJ(Mat C,IS rowemb,IS colemb,MatStructure pattern,Mat B) 5010 { 5011 /* If making this function public, change the error returned in this function away from _PLIB. */ 5012 PetscErrorCode ierr; 5013 Mat_SeqAIJ *Baij; 5014 PetscBool seqaij; 5015 PetscInt m,n,*nz,i,j,count; 5016 PetscScalar v; 5017 const PetscInt *rowindices,*colindices; 5018 5019 PetscFunctionBegin; 5020 if (!B) PetscFunctionReturn(0); 5021 /* Check to make sure the target matrix (and embeddings) are compatible with C and each other. */ 5022 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQAIJ,&seqaij);CHKERRQ(ierr); 5023 if (!seqaij) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is of wrong type"); 5024 if (rowemb) { 5025 ierr = ISGetLocalSize(rowemb,&m);CHKERRQ(ierr); 5026 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); 5027 } else { 5028 if (C->rmap->n != B->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is row-incompatible with the target matrix"); 5029 } 5030 if (colemb) { 5031 ierr = ISGetLocalSize(colemb,&n);CHKERRQ(ierr); 5032 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); 5033 } else { 5034 if (C->cmap->n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is col-incompatible with the target matrix"); 5035 } 5036 5037 Baij = (Mat_SeqAIJ*)(B->data); 5038 if (pattern == DIFFERENT_NONZERO_PATTERN) { 5039 ierr = PetscMalloc1(B->rmap->n,&nz);CHKERRQ(ierr); 5040 for (i=0; i<B->rmap->n; i++) { 5041 nz[i] = Baij->i[i+1] - Baij->i[i]; 5042 } 5043 ierr = MatSeqAIJSetPreallocation(C,0,nz);CHKERRQ(ierr); 5044 ierr = PetscFree(nz);CHKERRQ(ierr); 5045 } 5046 if (pattern == SUBSET_NONZERO_PATTERN) { 5047 ierr = MatZeroEntries(C);CHKERRQ(ierr); 5048 } 5049 count = 0; 5050 rowindices = NULL; 5051 colindices = NULL; 5052 if (rowemb) { 5053 ierr = ISGetIndices(rowemb,&rowindices);CHKERRQ(ierr); 5054 } 5055 if (colemb) { 5056 ierr = ISGetIndices(colemb,&colindices);CHKERRQ(ierr); 5057 } 5058 for (i=0; i<B->rmap->n; i++) { 5059 PetscInt row; 5060 row = i; 5061 if (rowindices) row = rowindices[i]; 5062 for (j=Baij->i[i]; j<Baij->i[i+1]; j++) { 5063 PetscInt col; 5064 col = Baij->j[count]; 5065 if (colindices) col = colindices[col]; 5066 v = Baij->a[count]; 5067 ierr = MatSetValues(C,1,&row,1,&col,&v,INSERT_VALUES);CHKERRQ(ierr); 5068 ++count; 5069 } 5070 } 5071 /* FIXME: set C's nonzerostate correctly. */ 5072 /* Assembly for C is necessary. */ 5073 C->preallocated = PETSC_TRUE; 5074 C->assembled = PETSC_TRUE; 5075 C->was_assembled = PETSC_FALSE; 5076 PetscFunctionReturn(0); 5077 } 5078 5079 PetscFunctionList MatSeqAIJList = NULL; 5080 5081 /*@C 5082 MatSeqAIJSetType - Converts a MATSEQAIJ matrix to a subtype 5083 5084 Collective on Mat 5085 5086 Input Parameters: 5087 + mat - the matrix object 5088 - matype - matrix type 5089 5090 Options Database Key: 5091 . -mat_seqai_type <method> - for example seqaijcrl 5092 5093 5094 Level: intermediate 5095 5096 .seealso: PCSetType(), VecSetType(), MatCreate(), MatType, Mat 5097 @*/ 5098 PetscErrorCode MatSeqAIJSetType(Mat mat, MatType matype) 5099 { 5100 PetscErrorCode ierr,(*r)(Mat,MatType,MatReuse,Mat*); 5101 PetscBool sametype; 5102 5103 PetscFunctionBegin; 5104 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 5105 ierr = PetscObjectTypeCompare((PetscObject)mat,matype,&sametype);CHKERRQ(ierr); 5106 if (sametype) PetscFunctionReturn(0); 5107 5108 ierr = PetscFunctionListFind(MatSeqAIJList,matype,&r);CHKERRQ(ierr); 5109 if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown Mat type given: %s",matype); 5110 ierr = (*r)(mat,matype,MAT_INPLACE_MATRIX,&mat);CHKERRQ(ierr); 5111 PetscFunctionReturn(0); 5112 } 5113 5114 5115 /*@C 5116 MatSeqAIJRegister - - Adds a new sub-matrix type for sequential AIJ matrices 5117 5118 Not Collective 5119 5120 Input Parameters: 5121 + name - name of a new user-defined matrix type, for example MATSEQAIJCRL 5122 - function - routine to convert to subtype 5123 5124 Notes: 5125 MatSeqAIJRegister() may be called multiple times to add several user-defined solvers. 5126 5127 5128 Then, your matrix can be chosen with the procedural interface at runtime via the option 5129 $ -mat_seqaij_type my_mat 5130 5131 Level: advanced 5132 5133 .seealso: MatSeqAIJRegisterAll() 5134 5135 5136 Level: advanced 5137 @*/ 5138 PetscErrorCode MatSeqAIJRegister(const char sname[],PetscErrorCode (*function)(Mat,MatType,MatReuse,Mat *)) 5139 { 5140 PetscErrorCode ierr; 5141 5142 PetscFunctionBegin; 5143 ierr = MatInitializePackage();CHKERRQ(ierr); 5144 ierr = PetscFunctionListAdd(&MatSeqAIJList,sname,function);CHKERRQ(ierr); 5145 PetscFunctionReturn(0); 5146 } 5147 5148 PetscBool MatSeqAIJRegisterAllCalled = PETSC_FALSE; 5149 5150 /*@C 5151 MatSeqAIJRegisterAll - Registers all of the matrix subtypes of SeqAIJ 5152 5153 Not Collective 5154 5155 Level: advanced 5156 5157 Developers Note: CUSP and CUSPARSE do not yet support the MatConvert_SeqAIJ..() paradigm and thus cannot be registered here 5158 5159 .seealso: MatRegisterAll(), MatSeqAIJRegister() 5160 @*/ 5161 PetscErrorCode MatSeqAIJRegisterAll(void) 5162 { 5163 PetscErrorCode ierr; 5164 5165 PetscFunctionBegin; 5166 if (MatSeqAIJRegisterAllCalled) PetscFunctionReturn(0); 5167 MatSeqAIJRegisterAllCalled = PETSC_TRUE; 5168 5169 ierr = MatSeqAIJRegister(MATSEQAIJCRL, MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 5170 ierr = MatSeqAIJRegister(MATSEQAIJPERM, MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 5171 ierr = MatSeqAIJRegister(MATSEQAIJSELL, MatConvert_SeqAIJ_SeqAIJSELL);CHKERRQ(ierr); 5172 #if defined(PETSC_HAVE_MKL_SPARSE) 5173 ierr = MatSeqAIJRegister(MATSEQAIJMKL, MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 5174 #endif 5175 #if defined(PETSC_HAVE_VIENNACL) && defined(PETSC_HAVE_VIENNACL_NO_CUDA) 5176 ierr = MatSeqAIJRegister(MATMPIAIJVIENNACL, MatConvert_SeqAIJ_SeqAIJViennaCL);CHKERRQ(ierr); 5177 #endif 5178 PetscFunctionReturn(0); 5179 } 5180 5181 /* 5182 Special version for direct calls from Fortran 5183 */ 5184 #include <petsc/private/fortranimpl.h> 5185 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5186 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 5187 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5188 #define matsetvaluesseqaij_ matsetvaluesseqaij 5189 #endif 5190 5191 /* Change these macros so can be used in void function */ 5192 #undef CHKERRQ 5193 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 5194 #undef SETERRQ2 5195 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5196 #undef SETERRQ3 5197 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5198 5199 PETSC_EXTERN void matsetvaluesseqaij_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[],InsertMode *isis, PetscErrorCode *_ierr) 5200 { 5201 Mat A = *AA; 5202 PetscInt m = *mm, n = *nn; 5203 InsertMode is = *isis; 5204 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5205 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 5206 PetscInt *imax,*ai,*ailen; 5207 PetscErrorCode ierr; 5208 PetscInt *aj,nonew = a->nonew,lastcol = -1; 5209 MatScalar *ap,value,*aa; 5210 PetscBool ignorezeroentries = a->ignorezeroentries; 5211 PetscBool roworiented = a->roworiented; 5212 5213 PetscFunctionBegin; 5214 MatCheckPreallocated(A,1); 5215 imax = a->imax; 5216 ai = a->i; 5217 ailen = a->ilen; 5218 aj = a->j; 5219 aa = a->a; 5220 5221 for (k=0; k<m; k++) { /* loop over added rows */ 5222 row = im[k]; 5223 if (row < 0) continue; 5224 if (PetscUnlikelyDebug(row >= A->rmap->n)) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 5225 rp = aj + ai[row]; ap = aa + ai[row]; 5226 rmax = imax[row]; nrow = ailen[row]; 5227 low = 0; 5228 high = nrow; 5229 for (l=0; l<n; l++) { /* loop over added columns */ 5230 if (in[l] < 0) continue; 5231 if (PetscUnlikelyDebug(in[l] >= A->cmap->n)) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 5232 col = in[l]; 5233 if (roworiented) value = v[l + k*n]; 5234 else value = v[k + l*m]; 5235 5236 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 5237 5238 if (col <= lastcol) low = 0; 5239 else high = nrow; 5240 lastcol = col; 5241 while (high-low > 5) { 5242 t = (low+high)/2; 5243 if (rp[t] > col) high = t; 5244 else low = t; 5245 } 5246 for (i=low; i<high; i++) { 5247 if (rp[i] > col) break; 5248 if (rp[i] == col) { 5249 if (is == ADD_VALUES) ap[i] += value; 5250 else ap[i] = value; 5251 goto noinsert; 5252 } 5253 } 5254 if (value == 0.0 && ignorezeroentries) goto noinsert; 5255 if (nonew == 1) goto noinsert; 5256 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 5257 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 5258 N = nrow++ - 1; a->nz++; high++; 5259 /* shift up all the later entries in this row */ 5260 for (ii=N; ii>=i; ii--) { 5261 rp[ii+1] = rp[ii]; 5262 ap[ii+1] = ap[ii]; 5263 } 5264 rp[i] = col; 5265 ap[i] = value; 5266 A->nonzerostate++; 5267 noinsert:; 5268 low = i + 1; 5269 } 5270 ailen[row] = nrow; 5271 } 5272 PetscFunctionReturnVoid(); 5273 } 5274