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_DEVICE) 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_DEVICE) 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_DEVICE) 196 if (v[i] != 0.0) inserted = PETSC_TRUE; 197 #endif 198 aa[diag[i]] += v[i]; 199 } 200 } 201 #if defined(PETSC_HAVE_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 511 inserted = PETSC_TRUE; 512 #endif 513 noinsert:; 514 } 515 ailen[row] = nrow; 516 } 517 #if defined(PETSC_HAVE_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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_DEVICE) 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 PetscScalar *x,*aa; 3234 3235 PetscFunctionBegin; 3236 aa = a->a; 3237 ai = a->i; 3238 aj = a->j; 3239 3240 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3241 ierr = VecGetArrayWrite(v,&x);CHKERRQ(ierr); 3242 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3243 if (n != m) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector, %D vs. %D rows", m, n); 3244 for (i=0; i<m; i++) { 3245 ncols = ai[1] - ai[0]; ai++; 3246 if (ncols == A->cmap->n) { /* row is dense */ 3247 x[i] = *aa; if (idx) idx[i] = 0; 3248 } else { /* row is sparse so already KNOW minimum is 0.0 or higher */ 3249 x[i] = 0.0; 3250 if (idx) { /* find first implicit 0.0 in the row */ 3251 for (j=0; j<ncols; j++) { 3252 if (aj[j] > j) { 3253 idx[i] = j; 3254 break; 3255 } 3256 } 3257 /* in case first implicit 0.0 in the row occurs at ncols-th column */ 3258 if (j==ncols && j < A->cmap->n) idx[i] = j; 3259 } 3260 } 3261 for (j=0; j<ncols; j++) { 3262 if (PetscAbsScalar(x[i]) > PetscAbsScalar(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3263 aa++; aj++; 3264 } 3265 } 3266 ierr = VecRestoreArrayWrite(v,&x);CHKERRQ(ierr); 3267 PetscFunctionReturn(0); 3268 } 3269 3270 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3271 { 3272 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3273 PetscErrorCode ierr; 3274 PetscInt i,j,m = A->rmap->n,ncols,n; 3275 const PetscInt *ai,*aj; 3276 PetscScalar *x; 3277 const MatScalar *aa; 3278 3279 PetscFunctionBegin; 3280 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3281 aa = a->a; 3282 ai = a->i; 3283 aj = a->j; 3284 3285 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3286 ierr = VecGetArrayWrite(v,&x);CHKERRQ(ierr); 3287 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3288 if (n != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3289 for (i=0; i<m; i++) { 3290 ncols = ai[1] - ai[0]; ai++; 3291 if (ncols == A->cmap->n) { /* row is dense */ 3292 x[i] = *aa; if (idx) idx[i] = 0; 3293 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3294 x[i] = 0.0; 3295 if (idx) { /* find first implicit 0.0 in the row */ 3296 for (j=0; j<ncols; j++) { 3297 if (aj[j] > j) { 3298 idx[i] = j; 3299 break; 3300 } 3301 } 3302 /* in case first implicit 0.0 in the row occurs at ncols-th column */ 3303 if (j==ncols && j < A->cmap->n) idx[i] = j; 3304 } 3305 } 3306 for (j=0; j<ncols; j++) { 3307 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3308 aa++; aj++; 3309 } 3310 } 3311 ierr = VecRestoreArrayWrite(v,&x);CHKERRQ(ierr); 3312 PetscFunctionReturn(0); 3313 } 3314 3315 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3316 { 3317 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3318 PetscErrorCode ierr; 3319 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3320 MatScalar *diag,work[25],*v_work; 3321 const PetscReal shift = 0.0; 3322 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 3323 3324 PetscFunctionBegin; 3325 allowzeropivot = PetscNot(A->erroriffailure); 3326 if (a->ibdiagvalid) { 3327 if (values) *values = a->ibdiag; 3328 PetscFunctionReturn(0); 3329 } 3330 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3331 if (!a->ibdiag) { 3332 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 3333 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3334 } 3335 diag = a->ibdiag; 3336 if (values) *values = a->ibdiag; 3337 /* factor and invert each block */ 3338 switch (bs) { 3339 case 1: 3340 for (i=0; i<mbs; i++) { 3341 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3342 if (PetscAbsScalar(diag[i] + shift) < PETSC_MACHINE_EPSILON) { 3343 if (allowzeropivot) { 3344 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3345 A->factorerror_zeropivot_value = PetscAbsScalar(diag[i]); 3346 A->factorerror_zeropivot_row = i; 3347 ierr = PetscInfo3(A,"Zero pivot, row %D pivot %g tolerance %g\n",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON);CHKERRQ(ierr); 3348 } 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); 3349 } 3350 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3351 } 3352 break; 3353 case 2: 3354 for (i=0; i<mbs; i++) { 3355 ij[0] = 2*i; ij[1] = 2*i + 1; 3356 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3357 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3358 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3359 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3360 diag += 4; 3361 } 3362 break; 3363 case 3: 3364 for (i=0; i<mbs; i++) { 3365 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3366 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3367 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3368 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3369 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3370 diag += 9; 3371 } 3372 break; 3373 case 4: 3374 for (i=0; i<mbs; i++) { 3375 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3376 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3377 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3378 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3379 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3380 diag += 16; 3381 } 3382 break; 3383 case 5: 3384 for (i=0; i<mbs; i++) { 3385 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3386 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3387 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3388 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3389 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3390 diag += 25; 3391 } 3392 break; 3393 case 6: 3394 for (i=0; i<mbs; i++) { 3395 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; 3396 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3397 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3398 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3399 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3400 diag += 36; 3401 } 3402 break; 3403 case 7: 3404 for (i=0; i<mbs; i++) { 3405 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; 3406 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3407 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3408 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3409 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3410 diag += 49; 3411 } 3412 break; 3413 default: 3414 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3415 for (i=0; i<mbs; i++) { 3416 for (j=0; j<bs; j++) { 3417 IJ[j] = bs*i + j; 3418 } 3419 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3420 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3421 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3422 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3423 diag += bs2; 3424 } 3425 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3426 } 3427 a->ibdiagvalid = PETSC_TRUE; 3428 PetscFunctionReturn(0); 3429 } 3430 3431 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3432 { 3433 PetscErrorCode ierr; 3434 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3435 PetscScalar a; 3436 PetscInt m,n,i,j,col; 3437 3438 PetscFunctionBegin; 3439 if (!x->assembled) { 3440 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3441 for (i=0; i<m; i++) { 3442 for (j=0; j<aij->imax[i]; j++) { 3443 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3444 col = (PetscInt)(n*PetscRealPart(a)); 3445 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3446 } 3447 } 3448 } else { 3449 for (i=0; i<aij->nz; i++) {ierr = PetscRandomGetValue(rctx,aij->a+i);CHKERRQ(ierr);} 3450 } 3451 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3452 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3453 PetscFunctionReturn(0); 3454 } 3455 3456 /* Like MatSetRandom_SeqAIJ, but do not set values on columns in range of [low, high) */ 3457 PetscErrorCode MatSetRandomSkipColumnRange_SeqAIJ_Private(Mat x,PetscInt low,PetscInt high,PetscRandom rctx) 3458 { 3459 PetscErrorCode ierr; 3460 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3461 PetscScalar a; 3462 PetscInt m,n,i,j,col,nskip; 3463 3464 PetscFunctionBegin; 3465 nskip = high - low; 3466 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3467 n -= nskip; /* shrink number of columns where nonzeros can be set */ 3468 for (i=0; i<m; i++) { 3469 for (j=0; j<aij->imax[i]; j++) { 3470 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3471 col = (PetscInt)(n*PetscRealPart(a)); 3472 if (col >= low) col += nskip; /* shift col rightward to skip the hole */ 3473 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3474 } 3475 } 3476 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3477 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3478 PetscFunctionReturn(0); 3479 } 3480 3481 3482 /* -------------------------------------------------------------------*/ 3483 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3484 MatGetRow_SeqAIJ, 3485 MatRestoreRow_SeqAIJ, 3486 MatMult_SeqAIJ, 3487 /* 4*/ MatMultAdd_SeqAIJ, 3488 MatMultTranspose_SeqAIJ, 3489 MatMultTransposeAdd_SeqAIJ, 3490 NULL, 3491 NULL, 3492 NULL, 3493 /* 10*/ NULL, 3494 MatLUFactor_SeqAIJ, 3495 NULL, 3496 MatSOR_SeqAIJ, 3497 MatTranspose_SeqAIJ, 3498 /*1 5*/ MatGetInfo_SeqAIJ, 3499 MatEqual_SeqAIJ, 3500 MatGetDiagonal_SeqAIJ, 3501 MatDiagonalScale_SeqAIJ, 3502 MatNorm_SeqAIJ, 3503 /* 20*/ NULL, 3504 MatAssemblyEnd_SeqAIJ, 3505 MatSetOption_SeqAIJ, 3506 MatZeroEntries_SeqAIJ, 3507 /* 24*/ MatZeroRows_SeqAIJ, 3508 NULL, 3509 NULL, 3510 NULL, 3511 NULL, 3512 /* 29*/ MatSetUp_SeqAIJ, 3513 NULL, 3514 NULL, 3515 NULL, 3516 NULL, 3517 /* 34*/ MatDuplicate_SeqAIJ, 3518 NULL, 3519 NULL, 3520 MatILUFactor_SeqAIJ, 3521 NULL, 3522 /* 39*/ MatAXPY_SeqAIJ, 3523 MatCreateSubMatrices_SeqAIJ, 3524 MatIncreaseOverlap_SeqAIJ, 3525 MatGetValues_SeqAIJ, 3526 MatCopy_SeqAIJ, 3527 /* 44*/ MatGetRowMax_SeqAIJ, 3528 MatScale_SeqAIJ, 3529 MatShift_SeqAIJ, 3530 MatDiagonalSet_SeqAIJ, 3531 MatZeroRowsColumns_SeqAIJ, 3532 /* 49*/ MatSetRandom_SeqAIJ, 3533 MatGetRowIJ_SeqAIJ, 3534 MatRestoreRowIJ_SeqAIJ, 3535 MatGetColumnIJ_SeqAIJ, 3536 MatRestoreColumnIJ_SeqAIJ, 3537 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3538 NULL, 3539 NULL, 3540 MatPermute_SeqAIJ, 3541 NULL, 3542 /* 59*/ NULL, 3543 MatDestroy_SeqAIJ, 3544 MatView_SeqAIJ, 3545 NULL, 3546 NULL, 3547 /* 64*/ NULL, 3548 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3549 NULL, 3550 NULL, 3551 NULL, 3552 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3553 MatGetRowMinAbs_SeqAIJ, 3554 NULL, 3555 NULL, 3556 NULL, 3557 /* 74*/ NULL, 3558 MatFDColoringApply_AIJ, 3559 NULL, 3560 NULL, 3561 NULL, 3562 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3563 NULL, 3564 NULL, 3565 NULL, 3566 MatLoad_SeqAIJ, 3567 /* 84*/ MatIsSymmetric_SeqAIJ, 3568 MatIsHermitian_SeqAIJ, 3569 NULL, 3570 NULL, 3571 NULL, 3572 /* 89*/ NULL, 3573 NULL, 3574 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3575 NULL, 3576 NULL, 3577 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy, 3578 NULL, 3579 NULL, 3580 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3581 NULL, 3582 /* 99*/ MatProductSetFromOptions_SeqAIJ, 3583 NULL, 3584 NULL, 3585 MatConjugate_SeqAIJ, 3586 NULL, 3587 /*104*/ MatSetValuesRow_SeqAIJ, 3588 MatRealPart_SeqAIJ, 3589 MatImaginaryPart_SeqAIJ, 3590 NULL, 3591 NULL, 3592 /*109*/ MatMatSolve_SeqAIJ, 3593 NULL, 3594 MatGetRowMin_SeqAIJ, 3595 NULL, 3596 MatMissingDiagonal_SeqAIJ, 3597 /*114*/ NULL, 3598 NULL, 3599 NULL, 3600 NULL, 3601 NULL, 3602 /*119*/ NULL, 3603 NULL, 3604 NULL, 3605 NULL, 3606 MatGetMultiProcBlock_SeqAIJ, 3607 /*124*/ MatFindNonzeroRows_SeqAIJ, 3608 MatGetColumnNorms_SeqAIJ, 3609 MatInvertBlockDiagonal_SeqAIJ, 3610 MatInvertVariableBlockDiagonal_SeqAIJ, 3611 NULL, 3612 /*129*/ NULL, 3613 NULL, 3614 NULL, 3615 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3616 MatTransposeColoringCreate_SeqAIJ, 3617 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3618 MatTransColoringApplyDenToSp_SeqAIJ, 3619 NULL, 3620 NULL, 3621 MatRARtNumeric_SeqAIJ_SeqAIJ, 3622 /*139*/NULL, 3623 NULL, 3624 NULL, 3625 MatFDColoringSetUp_SeqXAIJ, 3626 MatFindOffBlockDiagonalEntries_SeqAIJ, 3627 MatCreateMPIMatConcatenateSeqMat_SeqAIJ, 3628 /*145*/MatDestroySubMatrices_SeqAIJ, 3629 NULL, 3630 NULL 3631 }; 3632 3633 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3634 { 3635 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3636 PetscInt i,nz,n; 3637 3638 PetscFunctionBegin; 3639 nz = aij->maxnz; 3640 n = mat->rmap->n; 3641 for (i=0; i<nz; i++) { 3642 aij->j[i] = indices[i]; 3643 } 3644 aij->nz = nz; 3645 for (i=0; i<n; i++) { 3646 aij->ilen[i] = aij->imax[i]; 3647 } 3648 PetscFunctionReturn(0); 3649 } 3650 3651 /* 3652 * When a sparse matrix has many zero columns, we should compact them out to save the space 3653 * This happens in MatPtAPSymbolic_MPIAIJ_MPIAIJ_scalable() 3654 * */ 3655 PetscErrorCode MatSeqAIJCompactOutExtraColumns_SeqAIJ(Mat mat, ISLocalToGlobalMapping *mapping) 3656 { 3657 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3658 PetscTable gid1_lid1; 3659 PetscTablePosition tpos; 3660 PetscInt gid,lid,i,j,ncols,ec; 3661 PetscInt *garray; 3662 PetscErrorCode ierr; 3663 3664 PetscFunctionBegin; 3665 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3666 PetscValidPointer(mapping,2); 3667 /* use a table */ 3668 ierr = PetscTableCreate(mat->rmap->n,mat->cmap->N+1,&gid1_lid1);CHKERRQ(ierr); 3669 ec = 0; 3670 for (i=0; i<mat->rmap->n; i++) { 3671 ncols = aij->i[i+1] - aij->i[i]; 3672 for (j=0; j<ncols; j++) { 3673 PetscInt data,gid1 = aij->j[aij->i[i] + j] + 1; 3674 ierr = PetscTableFind(gid1_lid1,gid1,&data);CHKERRQ(ierr); 3675 if (!data) { 3676 /* one based table */ 3677 ierr = PetscTableAdd(gid1_lid1,gid1,++ec,INSERT_VALUES);CHKERRQ(ierr); 3678 } 3679 } 3680 } 3681 /* form array of columns we need */ 3682 ierr = PetscMalloc1(ec+1,&garray);CHKERRQ(ierr); 3683 ierr = PetscTableGetHeadPosition(gid1_lid1,&tpos);CHKERRQ(ierr); 3684 while (tpos) { 3685 ierr = PetscTableGetNext(gid1_lid1,&tpos,&gid,&lid);CHKERRQ(ierr); 3686 gid--; 3687 lid--; 3688 garray[lid] = gid; 3689 } 3690 ierr = PetscSortInt(ec,garray);CHKERRQ(ierr); /* sort, and rebuild */ 3691 ierr = PetscTableRemoveAll(gid1_lid1);CHKERRQ(ierr); 3692 for (i=0; i<ec; i++) { 3693 ierr = PetscTableAdd(gid1_lid1,garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 3694 } 3695 /* compact out the extra columns in B */ 3696 for (i=0; i<mat->rmap->n; i++) { 3697 ncols = aij->i[i+1] - aij->i[i]; 3698 for (j=0; j<ncols; j++) { 3699 PetscInt gid1 = aij->j[aij->i[i] + j] + 1; 3700 ierr = PetscTableFind(gid1_lid1,gid1,&lid);CHKERRQ(ierr); 3701 lid--; 3702 aij->j[aij->i[i] + j] = lid; 3703 } 3704 } 3705 ierr = PetscLayoutDestroy(&mat->cmap);CHKERRQ(ierr); 3706 ierr = PetscLayoutCreateFromSizes(PetscObjectComm((PetscObject)mat),ec,ec,1,&mat->cmap);CHKERRQ(ierr); 3707 ierr = PetscTableDestroy(&gid1_lid1);CHKERRQ(ierr); 3708 ierr = ISLocalToGlobalMappingCreate(PETSC_COMM_SELF,mat->cmap->bs,mat->cmap->n,garray,PETSC_OWN_POINTER,mapping);CHKERRQ(ierr); 3709 ierr = ISLocalToGlobalMappingSetType(*mapping,ISLOCALTOGLOBALMAPPINGHASH);CHKERRQ(ierr); 3710 PetscFunctionReturn(0); 3711 } 3712 3713 /*@ 3714 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3715 in the matrix. 3716 3717 Input Parameters: 3718 + mat - the SeqAIJ matrix 3719 - indices - the column indices 3720 3721 Level: advanced 3722 3723 Notes: 3724 This can be called if you have precomputed the nonzero structure of the 3725 matrix and want to provide it to the matrix object to improve the performance 3726 of the MatSetValues() operation. 3727 3728 You MUST have set the correct numbers of nonzeros per row in the call to 3729 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3730 3731 MUST be called before any calls to MatSetValues(); 3732 3733 The indices should start with zero, not one. 3734 3735 @*/ 3736 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3737 { 3738 PetscErrorCode ierr; 3739 3740 PetscFunctionBegin; 3741 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3742 PetscValidPointer(indices,2); 3743 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3744 PetscFunctionReturn(0); 3745 } 3746 3747 /* ----------------------------------------------------------------------------------------*/ 3748 3749 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3750 { 3751 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3752 PetscErrorCode ierr; 3753 size_t nz = aij->i[mat->rmap->n]; 3754 3755 PetscFunctionBegin; 3756 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3757 3758 /* allocate space for values if not already there */ 3759 if (!aij->saved_values) { 3760 ierr = PetscMalloc1(nz+1,&aij->saved_values);CHKERRQ(ierr); 3761 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3762 } 3763 3764 /* copy values over */ 3765 ierr = PetscArraycpy(aij->saved_values,aij->a,nz);CHKERRQ(ierr); 3766 PetscFunctionReturn(0); 3767 } 3768 3769 /*@ 3770 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3771 example, reuse of the linear part of a Jacobian, while recomputing the 3772 nonlinear portion. 3773 3774 Collect on Mat 3775 3776 Input Parameters: 3777 . mat - the matrix (currently only AIJ matrices support this option) 3778 3779 Level: advanced 3780 3781 Common Usage, with SNESSolve(): 3782 $ Create Jacobian matrix 3783 $ Set linear terms into matrix 3784 $ Apply boundary conditions to matrix, at this time matrix must have 3785 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3786 $ boundary conditions again will not change the nonzero structure 3787 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3788 $ ierr = MatStoreValues(mat); 3789 $ Call SNESSetJacobian() with matrix 3790 $ In your Jacobian routine 3791 $ ierr = MatRetrieveValues(mat); 3792 $ Set nonlinear terms in matrix 3793 3794 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3795 $ // build linear portion of Jacobian 3796 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3797 $ ierr = MatStoreValues(mat); 3798 $ loop over nonlinear iterations 3799 $ ierr = MatRetrieveValues(mat); 3800 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3801 $ // call MatAssemblyBegin/End() on matrix 3802 $ Solve linear system with Jacobian 3803 $ endloop 3804 3805 Notes: 3806 Matrix must already be assemblied before calling this routine 3807 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3808 calling this routine. 3809 3810 When this is called multiple times it overwrites the previous set of stored values 3811 and does not allocated additional space. 3812 3813 .seealso: MatRetrieveValues() 3814 3815 @*/ 3816 PetscErrorCode MatStoreValues(Mat mat) 3817 { 3818 PetscErrorCode ierr; 3819 3820 PetscFunctionBegin; 3821 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3822 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3823 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3824 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3825 PetscFunctionReturn(0); 3826 } 3827 3828 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3829 { 3830 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3831 PetscErrorCode ierr; 3832 PetscInt nz = aij->i[mat->rmap->n]; 3833 3834 PetscFunctionBegin; 3835 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3836 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3837 /* copy values over */ 3838 ierr = PetscArraycpy(aij->a,aij->saved_values,nz);CHKERRQ(ierr); 3839 PetscFunctionReturn(0); 3840 } 3841 3842 /*@ 3843 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3844 example, reuse of the linear part of a Jacobian, while recomputing the 3845 nonlinear portion. 3846 3847 Collect on Mat 3848 3849 Input Parameters: 3850 . mat - the matrix (currently only AIJ matrices support this option) 3851 3852 Level: advanced 3853 3854 .seealso: MatStoreValues() 3855 3856 @*/ 3857 PetscErrorCode MatRetrieveValues(Mat mat) 3858 { 3859 PetscErrorCode ierr; 3860 3861 PetscFunctionBegin; 3862 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3863 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3864 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3865 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3866 PetscFunctionReturn(0); 3867 } 3868 3869 3870 /* --------------------------------------------------------------------------------*/ 3871 /*@C 3872 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3873 (the default parallel PETSc format). For good matrix assembly performance 3874 the user should preallocate the matrix storage by setting the parameter nz 3875 (or the array nnz). By setting these parameters accurately, performance 3876 during matrix assembly can be increased by more than a factor of 50. 3877 3878 Collective 3879 3880 Input Parameters: 3881 + comm - MPI communicator, set to PETSC_COMM_SELF 3882 . m - number of rows 3883 . n - number of columns 3884 . nz - number of nonzeros per row (same for all rows) 3885 - nnz - array containing the number of nonzeros in the various rows 3886 (possibly different for each row) or NULL 3887 3888 Output Parameter: 3889 . A - the matrix 3890 3891 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3892 MatXXXXSetPreallocation() paradigm instead of this routine directly. 3893 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3894 3895 Notes: 3896 If nnz is given then nz is ignored 3897 3898 The AIJ format (also called the Yale sparse matrix format or 3899 compressed row storage), is fully compatible with standard Fortran 77 3900 storage. That is, the stored row and column indices can begin at 3901 either one (as in Fortran) or zero. See the users' manual for details. 3902 3903 Specify the preallocated storage with either nz or nnz (not both). 3904 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3905 allocation. For large problems you MUST preallocate memory or you 3906 will get TERRIBLE performance, see the users' manual chapter on matrices. 3907 3908 By default, this format uses inodes (identical nodes) when possible, to 3909 improve numerical efficiency of matrix-vector products and solves. We 3910 search for consecutive rows with the same nonzero structure, thereby 3911 reusing matrix information to achieve increased efficiency. 3912 3913 Options Database Keys: 3914 + -mat_no_inode - Do not use inodes 3915 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3916 3917 Level: intermediate 3918 3919 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3920 3921 @*/ 3922 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3923 { 3924 PetscErrorCode ierr; 3925 3926 PetscFunctionBegin; 3927 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3928 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3929 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3930 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3931 PetscFunctionReturn(0); 3932 } 3933 3934 /*@C 3935 MatSeqAIJSetPreallocation - For good matrix assembly performance 3936 the user should preallocate the matrix storage by setting the parameter nz 3937 (or the array nnz). By setting these parameters accurately, performance 3938 during matrix assembly can be increased by more than a factor of 50. 3939 3940 Collective 3941 3942 Input Parameters: 3943 + B - The matrix 3944 . nz - number of nonzeros per row (same for all rows) 3945 - nnz - array containing the number of nonzeros in the various rows 3946 (possibly different for each row) or NULL 3947 3948 Notes: 3949 If nnz is given then nz is ignored 3950 3951 The AIJ format (also called the Yale sparse matrix format or 3952 compressed row storage), is fully compatible with standard Fortran 77 3953 storage. That is, the stored row and column indices can begin at 3954 either one (as in Fortran) or zero. See the users' manual for details. 3955 3956 Specify the preallocated storage with either nz or nnz (not both). 3957 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3958 allocation. For large problems you MUST preallocate memory or you 3959 will get TERRIBLE performance, see the users' manual chapter on matrices. 3960 3961 You can call MatGetInfo() to get information on how effective the preallocation was; 3962 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3963 You can also run with the option -info and look for messages with the string 3964 malloc in them to see if additional memory allocation was needed. 3965 3966 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3967 entries or columns indices 3968 3969 By default, this format uses inodes (identical nodes) when possible, to 3970 improve numerical efficiency of matrix-vector products and solves. We 3971 search for consecutive rows with the same nonzero structure, thereby 3972 reusing matrix information to achieve increased efficiency. 3973 3974 Options Database Keys: 3975 + -mat_no_inode - Do not use inodes 3976 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3977 3978 Level: intermediate 3979 3980 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo(), 3981 MatSeqAIJSetTotalPreallocation() 3982 3983 @*/ 3984 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3985 { 3986 PetscErrorCode ierr; 3987 3988 PetscFunctionBegin; 3989 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3990 PetscValidType(B,1); 3991 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3992 PetscFunctionReturn(0); 3993 } 3994 3995 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3996 { 3997 Mat_SeqAIJ *b; 3998 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3999 PetscErrorCode ierr; 4000 PetscInt i; 4001 4002 PetscFunctionBegin; 4003 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 4004 if (nz == MAT_SKIP_ALLOCATION) { 4005 skipallocation = PETSC_TRUE; 4006 nz = 0; 4007 } 4008 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 4009 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 4010 4011 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 4012 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 4013 if (PetscUnlikelyDebug(nnz)) { 4014 for (i=0; i<B->rmap->n; i++) { 4015 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]); 4016 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); 4017 } 4018 } 4019 4020 B->preallocated = PETSC_TRUE; 4021 4022 b = (Mat_SeqAIJ*)B->data; 4023 4024 if (!skipallocation) { 4025 if (!b->imax) { 4026 ierr = PetscMalloc1(B->rmap->n,&b->imax);CHKERRQ(ierr); 4027 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 4028 } 4029 if (!b->ilen) { 4030 /* b->ilen will count nonzeros in each row so far. */ 4031 ierr = PetscCalloc1(B->rmap->n,&b->ilen);CHKERRQ(ierr); 4032 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 4033 } else { 4034 ierr = PetscMemzero(b->ilen,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 4035 } 4036 if (!b->ipre) { 4037 ierr = PetscMalloc1(B->rmap->n,&b->ipre);CHKERRQ(ierr); 4038 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 4039 } 4040 if (!nnz) { 4041 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 4042 else if (nz < 0) nz = 1; 4043 nz = PetscMin(nz,B->cmap->n); 4044 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 4045 nz = nz*B->rmap->n; 4046 } else { 4047 PetscInt64 nz64 = 0; 4048 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz64 += nnz[i];} 4049 ierr = PetscIntCast(nz64,&nz);CHKERRQ(ierr); 4050 } 4051 4052 /* allocate the matrix space */ 4053 /* FIXME: should B's old memory be unlogged? */ 4054 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 4055 if (B->structure_only) { 4056 ierr = PetscMalloc1(nz,&b->j);CHKERRQ(ierr); 4057 ierr = PetscMalloc1(B->rmap->n+1,&b->i);CHKERRQ(ierr); 4058 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));CHKERRQ(ierr); 4059 } else { 4060 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 4061 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 4062 } 4063 b->i[0] = 0; 4064 for (i=1; i<B->rmap->n+1; i++) { 4065 b->i[i] = b->i[i-1] + b->imax[i-1]; 4066 } 4067 if (B->structure_only) { 4068 b->singlemalloc = PETSC_FALSE; 4069 b->free_a = PETSC_FALSE; 4070 } else { 4071 b->singlemalloc = PETSC_TRUE; 4072 b->free_a = PETSC_TRUE; 4073 } 4074 b->free_ij = PETSC_TRUE; 4075 } else { 4076 b->free_a = PETSC_FALSE; 4077 b->free_ij = PETSC_FALSE; 4078 } 4079 4080 if (b->ipre && nnz != b->ipre && b->imax) { 4081 /* reserve user-requested sparsity */ 4082 ierr = PetscArraycpy(b->ipre,b->imax,B->rmap->n);CHKERRQ(ierr); 4083 } 4084 4085 4086 b->nz = 0; 4087 b->maxnz = nz; 4088 B->info.nz_unneeded = (double)b->maxnz; 4089 if (realalloc) { 4090 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 4091 } 4092 B->was_assembled = PETSC_FALSE; 4093 B->assembled = PETSC_FALSE; 4094 PetscFunctionReturn(0); 4095 } 4096 4097 4098 PetscErrorCode MatResetPreallocation_SeqAIJ(Mat A) 4099 { 4100 Mat_SeqAIJ *a; 4101 PetscInt i; 4102 PetscErrorCode ierr; 4103 4104 PetscFunctionBegin; 4105 PetscValidHeaderSpecific(A,MAT_CLASSID,1); 4106 4107 /* Check local size. If zero, then return */ 4108 if (!A->rmap->n) PetscFunctionReturn(0); 4109 4110 a = (Mat_SeqAIJ*)A->data; 4111 /* if no saved info, we error out */ 4112 if (!a->ipre) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NULL,"No saved preallocation info \n"); 4113 4114 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"); 4115 4116 ierr = PetscArraycpy(a->imax,a->ipre,A->rmap->n);CHKERRQ(ierr); 4117 ierr = PetscArrayzero(a->ilen,A->rmap->n);CHKERRQ(ierr); 4118 a->i[0] = 0; 4119 for (i=1; i<A->rmap->n+1; i++) { 4120 a->i[i] = a->i[i-1] + a->imax[i-1]; 4121 } 4122 A->preallocated = PETSC_TRUE; 4123 a->nz = 0; 4124 a->maxnz = a->i[A->rmap->n]; 4125 A->info.nz_unneeded = (double)a->maxnz; 4126 A->was_assembled = PETSC_FALSE; 4127 A->assembled = PETSC_FALSE; 4128 PetscFunctionReturn(0); 4129 } 4130 4131 /*@ 4132 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 4133 4134 Input Parameters: 4135 + B - the matrix 4136 . i - the indices into j for the start of each row (starts with zero) 4137 . j - the column indices for each row (starts with zero) these must be sorted for each row 4138 - v - optional values in the matrix 4139 4140 Level: developer 4141 4142 Notes: 4143 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 4144 4145 This routine may be called multiple times with different nonzero patterns (or the same nonzero pattern). The nonzero 4146 structure will be the union of all the previous nonzero structures. 4147 4148 Developer Notes: 4149 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 4150 then just copies the v values directly with PetscMemcpy(). 4151 4152 This routine could also take a PetscCopyMode argument to allow sharing the values instead of always copying them. 4153 4154 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), MATSEQAIJ, MatResetPreallocation() 4155 @*/ 4156 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 4157 { 4158 PetscErrorCode ierr; 4159 4160 PetscFunctionBegin; 4161 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4162 PetscValidType(B,1); 4163 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 4164 PetscFunctionReturn(0); 4165 } 4166 4167 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 4168 { 4169 PetscInt i; 4170 PetscInt m,n; 4171 PetscInt nz; 4172 PetscInt *nnz; 4173 PetscErrorCode ierr; 4174 4175 PetscFunctionBegin; 4176 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 4177 4178 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 4179 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 4180 4181 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 4182 ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); 4183 for (i = 0; i < m; i++) { 4184 nz = Ii[i+1]- Ii[i]; 4185 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 4186 nnz[i] = nz; 4187 } 4188 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 4189 ierr = PetscFree(nnz);CHKERRQ(ierr); 4190 4191 for (i = 0; i < m; i++) { 4192 ierr = MatSetValues_SeqAIJ(B, 1, &i, Ii[i+1] - Ii[i], J+Ii[i], v ? v + Ii[i] : NULL, INSERT_VALUES);CHKERRQ(ierr); 4193 } 4194 4195 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4196 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4197 4198 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 4199 PetscFunctionReturn(0); 4200 } 4201 4202 #include <../src/mat/impls/dense/seq/dense.h> 4203 #include <petsc/private/kernels/petscaxpy.h> 4204 4205 /* 4206 Computes (B'*A')' since computing B*A directly is untenable 4207 4208 n p p 4209 [ ] [ ] [ ] 4210 m [ A ] * n [ B ] = m [ C ] 4211 [ ] [ ] [ ] 4212 4213 */ 4214 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 4215 { 4216 PetscErrorCode ierr; 4217 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 4218 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 4219 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 4220 PetscInt i,j,n,m,q,p; 4221 const PetscInt *ii,*idx; 4222 const PetscScalar *b,*a,*a_q; 4223 PetscScalar *c,*c_q; 4224 PetscInt clda = sub_c->lda; 4225 PetscInt alda = sub_a->lda; 4226 4227 PetscFunctionBegin; 4228 m = A->rmap->n; 4229 n = A->cmap->n; 4230 p = B->cmap->n; 4231 a = sub_a->v; 4232 b = sub_b->a; 4233 c = sub_c->v; 4234 if (clda == m) { 4235 ierr = PetscArrayzero(c,m*p);CHKERRQ(ierr); 4236 } else { 4237 for (j=0;j<p;j++) 4238 for (i=0;i<m;i++) 4239 c[j*clda + i] = 0.0; 4240 } 4241 ii = sub_b->i; 4242 idx = sub_b->j; 4243 for (i=0; i<n; i++) { 4244 q = ii[i+1] - ii[i]; 4245 while (q-->0) { 4246 c_q = c + clda*(*idx); 4247 a_q = a + alda*i; 4248 PetscKernelAXPY(c_q,*b,a_q,m); 4249 idx++; 4250 b++; 4251 } 4252 } 4253 PetscFunctionReturn(0); 4254 } 4255 4256 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat C) 4257 { 4258 PetscErrorCode ierr; 4259 PetscInt m=A->rmap->n,n=B->cmap->n; 4260 PetscBool cisdense; 4261 4262 PetscFunctionBegin; 4263 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); 4264 ierr = MatSetSizes(C,m,n,m,n);CHKERRQ(ierr); 4265 ierr = MatSetBlockSizesFromMats(C,A,B);CHKERRQ(ierr); 4266 ierr = PetscObjectTypeCompareAny((PetscObject)C,&cisdense,MATSEQDENSE,MATSEQDENSECUDA,"");CHKERRQ(ierr); 4267 if (!cisdense) { 4268 ierr = MatSetType(C,MATDENSE);CHKERRQ(ierr); 4269 } 4270 ierr = MatSetUp(C);CHKERRQ(ierr); 4271 4272 C->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 4273 PetscFunctionReturn(0); 4274 } 4275 4276 /* ----------------------------------------------------------------*/ 4277 /*MC 4278 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 4279 based on compressed sparse row format. 4280 4281 Options Database Keys: 4282 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 4283 4284 Level: beginner 4285 4286 Notes: 4287 MatSetValues() may be called for this matrix type with a NULL argument for the numerical values, 4288 in this case the values associated with the rows and columns one passes in are set to zero 4289 in the matrix 4290 4291 MatSetOptions(,MAT_STRUCTURE_ONLY,PETSC_TRUE) may be called for this matrix type. In this no 4292 space is allocated for the nonzero entries and any entries passed with MatSetValues() are ignored 4293 4294 Developer Notes: 4295 It would be nice if all matrix formats supported passing NULL in for the numerical values 4296 4297 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 4298 M*/ 4299 4300 /*MC 4301 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 4302 4303 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 4304 and MATMPIAIJ otherwise. As a result, for single process communicators, 4305 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation() is supported 4306 for communicators controlling multiple processes. It is recommended that you call both of 4307 the above preallocation routines for simplicity. 4308 4309 Options Database Keys: 4310 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 4311 4312 Developer Notes: 4313 Subclasses include MATAIJCUSPARSE, MATAIJPERM, MATAIJSELL, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when 4314 enough exist. 4315 4316 Level: beginner 4317 4318 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 4319 M*/ 4320 4321 /*MC 4322 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 4323 4324 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 4325 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 4326 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 4327 for communicators controlling multiple processes. It is recommended that you call both of 4328 the above preallocation routines for simplicity. 4329 4330 Options Database Keys: 4331 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 4332 4333 Level: beginner 4334 4335 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 4336 M*/ 4337 4338 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 4339 #if defined(PETSC_HAVE_ELEMENTAL) 4340 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4341 #endif 4342 #if defined(PETSC_HAVE_SCALAPACK) 4343 PETSC_INTERN PetscErrorCode MatConvert_AIJ_ScaLAPACK(Mat,MatType,MatReuse,Mat*); 4344 #endif 4345 #if defined(PETSC_HAVE_HYPRE) 4346 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat A,MatType,MatReuse,Mat*); 4347 #endif 4348 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*); 4349 4350 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqSELL(Mat,MatType,MatReuse,Mat*); 4351 PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*); 4352 PETSC_INTERN PetscErrorCode MatProductSetFromOptions_IS_XAIJ(Mat); 4353 4354 /*@C 4355 MatSeqAIJGetArray - gives read/write access to the array where the data for a MATSEQAIJ matrix is stored 4356 4357 Not Collective 4358 4359 Input Parameter: 4360 . mat - a MATSEQAIJ matrix 4361 4362 Output Parameter: 4363 . array - pointer to the data 4364 4365 Level: intermediate 4366 4367 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4368 @*/ 4369 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4370 { 4371 PetscErrorCode ierr; 4372 4373 PetscFunctionBegin; 4374 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4375 PetscFunctionReturn(0); 4376 } 4377 4378 /*@C 4379 MatSeqAIJGetArrayRead - gives read-only access to the array where the data for a MATSEQAIJ matrix is stored 4380 4381 Not Collective 4382 4383 Input Parameter: 4384 . mat - a MATSEQAIJ matrix 4385 4386 Output Parameter: 4387 . array - pointer to the data 4388 4389 Level: intermediate 4390 4391 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayRead() 4392 @*/ 4393 PetscErrorCode MatSeqAIJGetArrayRead(Mat A,const PetscScalar **array) 4394 { 4395 #if defined(PETSC_HAVE_DEVICE) 4396 PetscOffloadMask oval; 4397 #endif 4398 PetscErrorCode ierr; 4399 4400 PetscFunctionBegin; 4401 #if defined(PETSC_HAVE_DEVICE) 4402 oval = A->offloadmask; 4403 #endif 4404 ierr = MatSeqAIJGetArray(A,(PetscScalar**)array);CHKERRQ(ierr); 4405 #if defined(PETSC_HAVE_DEVICE) 4406 if (oval == PETSC_OFFLOAD_GPU || oval == PETSC_OFFLOAD_BOTH) A->offloadmask = PETSC_OFFLOAD_BOTH; 4407 #endif 4408 PetscFunctionReturn(0); 4409 } 4410 4411 /*@C 4412 MatSeqAIJRestoreArrayRead - restore the read-only access array obtained from MatSeqAIJGetArrayRead 4413 4414 Not Collective 4415 4416 Input Parameter: 4417 . mat - a MATSEQAIJ matrix 4418 4419 Output Parameter: 4420 . array - pointer to the data 4421 4422 Level: intermediate 4423 4424 .seealso: MatSeqAIJGetArray(), MatSeqAIJGetArrayRead() 4425 @*/ 4426 PetscErrorCode MatSeqAIJRestoreArrayRead(Mat A,const PetscScalar **array) 4427 { 4428 #if defined(PETSC_HAVE_DEVICE) 4429 PetscOffloadMask oval; 4430 #endif 4431 PetscErrorCode ierr; 4432 4433 PetscFunctionBegin; 4434 #if defined(PETSC_HAVE_DEVICE) 4435 oval = A->offloadmask; 4436 #endif 4437 ierr = MatSeqAIJRestoreArray(A,(PetscScalar**)array);CHKERRQ(ierr); 4438 #if defined(PETSC_HAVE_DEVICE) 4439 A->offloadmask = oval; 4440 #endif 4441 PetscFunctionReturn(0); 4442 } 4443 4444 /*@C 4445 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 4446 4447 Not Collective 4448 4449 Input Parameter: 4450 . mat - a MATSEQAIJ matrix 4451 4452 Output Parameter: 4453 . nz - the maximum number of nonzeros in any row 4454 4455 Level: intermediate 4456 4457 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4458 @*/ 4459 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 4460 { 4461 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 4462 4463 PetscFunctionBegin; 4464 *nz = aij->rmax; 4465 PetscFunctionReturn(0); 4466 } 4467 4468 /*@C 4469 MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() 4470 4471 Not Collective 4472 4473 Input Parameters: 4474 + mat - a MATSEQAIJ matrix 4475 - array - pointer to the data 4476 4477 Level: intermediate 4478 4479 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4480 @*/ 4481 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4482 { 4483 PetscErrorCode ierr; 4484 4485 PetscFunctionBegin; 4486 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4487 PetscFunctionReturn(0); 4488 } 4489 4490 #if defined(PETSC_HAVE_CUDA) 4491 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCUSPARSE(Mat); 4492 #endif 4493 4494 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4495 { 4496 Mat_SeqAIJ *b; 4497 PetscErrorCode ierr; 4498 PetscMPIInt size; 4499 4500 PetscFunctionBegin; 4501 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4502 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4503 4504 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 4505 4506 B->data = (void*)b; 4507 4508 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4509 if (B->sortedfull) B->ops->setvalues = MatSetValues_SeqAIJ_SortedFull; 4510 4511 b->row = NULL; 4512 b->col = NULL; 4513 b->icol = NULL; 4514 b->reallocs = 0; 4515 b->ignorezeroentries = PETSC_FALSE; 4516 b->roworiented = PETSC_TRUE; 4517 b->nonew = 0; 4518 b->diag = NULL; 4519 b->solve_work = NULL; 4520 B->spptr = NULL; 4521 b->saved_values = NULL; 4522 b->idiag = NULL; 4523 b->mdiag = NULL; 4524 b->ssor_work = NULL; 4525 b->omega = 1.0; 4526 b->fshift = 0.0; 4527 b->idiagvalid = PETSC_FALSE; 4528 b->ibdiagvalid = PETSC_FALSE; 4529 b->keepnonzeropattern = PETSC_FALSE; 4530 4531 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4532 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4533 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4534 4535 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4536 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4537 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4538 #endif 4539 4540 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4541 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4542 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4543 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4544 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4545 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4546 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijsell_C",MatConvert_SeqAIJ_SeqAIJSELL);CHKERRQ(ierr); 4547 #if defined(PETSC_HAVE_MKL_SPARSE) 4548 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijmkl_C",MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 4549 #endif 4550 #if defined(PETSC_HAVE_CUDA) 4551 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcusparse_C",MatConvert_SeqAIJ_SeqAIJCUSPARSE);CHKERRQ(ierr); 4552 ierr = PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_seqaijcusparse_seqaij_C",MatProductSetFromOptions_SeqAIJ);CHKERRQ(ierr); 4553 #endif 4554 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4555 #if defined(PETSC_HAVE_ELEMENTAL) 4556 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); 4557 #endif 4558 #if defined(PETSC_HAVE_SCALAPACK) 4559 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_scalapack_C",MatConvert_AIJ_ScaLAPACK);CHKERRQ(ierr); 4560 #endif 4561 #if defined(PETSC_HAVE_HYPRE) 4562 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 4563 ierr = PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_transpose_seqaij_seqaij_C",MatProductSetFromOptions_Transpose_AIJ_AIJ);CHKERRQ(ierr); 4564 #endif 4565 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); 4566 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsell_C",MatConvert_SeqAIJ_SeqSELL);CHKERRQ(ierr); 4567 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_is_C",MatConvert_XAIJ_IS);CHKERRQ(ierr); 4568 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4569 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4570 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4571 ierr = PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_SeqAIJ);CHKERRQ(ierr); 4572 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4573 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4574 ierr = PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_is_seqaij_C",MatProductSetFromOptions_IS_XAIJ);CHKERRQ(ierr); 4575 ierr = PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_seqdense_seqaij_C",MatProductSetFromOptions_SeqDense_SeqAIJ);CHKERRQ(ierr); 4576 ierr = PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_seqaij_seqaij_C",MatProductSetFromOptions_SeqAIJ);CHKERRQ(ierr); 4577 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4578 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4579 ierr = MatSeqAIJSetTypeFromOptions(B);CHKERRQ(ierr); /* this allows changing the matrix subtype to say MATSEQAIJPERM */ 4580 PetscFunctionReturn(0); 4581 } 4582 4583 /* 4584 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4585 */ 4586 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4587 { 4588 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data,*a = (Mat_SeqAIJ*)A->data; 4589 PetscErrorCode ierr; 4590 PetscInt m = A->rmap->n,i; 4591 4592 PetscFunctionBegin; 4593 if (!A->assembled && cpvalues!=MAT_DO_NOT_COPY_VALUES) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot duplicate unassembled matrix"); 4594 4595 C->factortype = A->factortype; 4596 c->row = NULL; 4597 c->col = NULL; 4598 c->icol = NULL; 4599 c->reallocs = 0; 4600 4601 C->assembled = PETSC_TRUE; 4602 4603 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4604 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4605 4606 ierr = PetscMalloc1(m,&c->imax);CHKERRQ(ierr); 4607 ierr = PetscMemcpy(c->imax,a->imax,m*sizeof(PetscInt));CHKERRQ(ierr); 4608 ierr = PetscMalloc1(m,&c->ilen);CHKERRQ(ierr); 4609 ierr = PetscMemcpy(c->ilen,a->ilen,m*sizeof(PetscInt));CHKERRQ(ierr); 4610 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4611 4612 /* allocate the matrix space */ 4613 if (mallocmatspace) { 4614 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4615 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4616 4617 c->singlemalloc = PETSC_TRUE; 4618 4619 ierr = PetscArraycpy(c->i,a->i,m+1);CHKERRQ(ierr); 4620 if (m > 0) { 4621 ierr = PetscArraycpy(c->j,a->j,a->i[m]);CHKERRQ(ierr); 4622 if (cpvalues == MAT_COPY_VALUES) { 4623 ierr = PetscArraycpy(c->a,a->a,a->i[m]);CHKERRQ(ierr); 4624 } else { 4625 ierr = PetscArrayzero(c->a,a->i[m]);CHKERRQ(ierr); 4626 } 4627 } 4628 } 4629 4630 c->ignorezeroentries = a->ignorezeroentries; 4631 c->roworiented = a->roworiented; 4632 c->nonew = a->nonew; 4633 if (a->diag) { 4634 ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); 4635 ierr = PetscMemcpy(c->diag,a->diag,m*sizeof(PetscInt));CHKERRQ(ierr); 4636 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4637 } else c->diag = NULL; 4638 4639 c->solve_work = NULL; 4640 c->saved_values = NULL; 4641 c->idiag = NULL; 4642 c->ssor_work = NULL; 4643 c->keepnonzeropattern = a->keepnonzeropattern; 4644 c->free_a = PETSC_TRUE; 4645 c->free_ij = PETSC_TRUE; 4646 4647 c->rmax = a->rmax; 4648 c->nz = a->nz; 4649 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4650 C->preallocated = PETSC_TRUE; 4651 4652 c->compressedrow.use = a->compressedrow.use; 4653 c->compressedrow.nrows = a->compressedrow.nrows; 4654 if (a->compressedrow.use) { 4655 i = a->compressedrow.nrows; 4656 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4657 ierr = PetscArraycpy(c->compressedrow.i,a->compressedrow.i,i+1);CHKERRQ(ierr); 4658 ierr = PetscArraycpy(c->compressedrow.rindex,a->compressedrow.rindex,i);CHKERRQ(ierr); 4659 } else { 4660 c->compressedrow.use = PETSC_FALSE; 4661 c->compressedrow.i = NULL; 4662 c->compressedrow.rindex = NULL; 4663 } 4664 c->nonzerorowcnt = a->nonzerorowcnt; 4665 C->nonzerostate = A->nonzerostate; 4666 4667 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4668 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4669 PetscFunctionReturn(0); 4670 } 4671 4672 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4673 { 4674 PetscErrorCode ierr; 4675 4676 PetscFunctionBegin; 4677 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4678 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4679 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4680 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4681 } 4682 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4683 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4684 PetscFunctionReturn(0); 4685 } 4686 4687 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4688 { 4689 PetscBool isbinary, ishdf5; 4690 PetscErrorCode ierr; 4691 4692 PetscFunctionBegin; 4693 PetscValidHeaderSpecific(newMat,MAT_CLASSID,1); 4694 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 4695 /* force binary viewer to load .info file if it has not yet done so */ 4696 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4697 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 4698 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERHDF5, &ishdf5);CHKERRQ(ierr); 4699 if (isbinary) { 4700 ierr = MatLoad_SeqAIJ_Binary(newMat,viewer);CHKERRQ(ierr); 4701 } else if (ishdf5) { 4702 #if defined(PETSC_HAVE_HDF5) 4703 ierr = MatLoad_AIJ_HDF5(newMat,viewer);CHKERRQ(ierr); 4704 #else 4705 SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"HDF5 not supported in this build.\nPlease reconfigure using --download-hdf5"); 4706 #endif 4707 } else { 4708 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); 4709 } 4710 PetscFunctionReturn(0); 4711 } 4712 4713 PetscErrorCode MatLoad_SeqAIJ_Binary(Mat mat, PetscViewer viewer) 4714 { 4715 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->data; 4716 PetscErrorCode ierr; 4717 PetscInt header[4],*rowlens,M,N,nz,sum,rows,cols,i; 4718 4719 PetscFunctionBegin; 4720 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4721 4722 /* read in matrix header */ 4723 ierr = PetscViewerBinaryRead(viewer,header,4,NULL,PETSC_INT);CHKERRQ(ierr); 4724 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Not a matrix object in file"); 4725 M = header[1]; N = header[2]; nz = header[3]; 4726 if (M < 0) SETERRQ1(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Matrix row size (%D) in file is negative",M); 4727 if (N < 0) SETERRQ1(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Matrix column size (%D) in file is negative",N); 4728 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk, cannot load as SeqAIJ"); 4729 4730 /* set block sizes from the viewer's .info file */ 4731 ierr = MatLoad_Binary_BlockSizes(mat,viewer);CHKERRQ(ierr); 4732 /* set local and global sizes if not set already */ 4733 if (mat->rmap->n < 0) mat->rmap->n = M; 4734 if (mat->cmap->n < 0) mat->cmap->n = N; 4735 if (mat->rmap->N < 0) mat->rmap->N = M; 4736 if (mat->cmap->N < 0) mat->cmap->N = N; 4737 ierr = PetscLayoutSetUp(mat->rmap);CHKERRQ(ierr); 4738 ierr = PetscLayoutSetUp(mat->cmap);CHKERRQ(ierr); 4739 4740 /* check if the matrix sizes are correct */ 4741 ierr = MatGetSize(mat,&rows,&cols);CHKERRQ(ierr); 4742 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); 4743 4744 /* read in row lengths */ 4745 ierr = PetscMalloc1(M,&rowlens);CHKERRQ(ierr); 4746 ierr = PetscViewerBinaryRead(viewer,rowlens,M,NULL,PETSC_INT);CHKERRQ(ierr); 4747 /* check if sum(rowlens) is same as nz */ 4748 sum = 0; for (i=0; i<M; i++) sum += rowlens[i]; 4749 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); 4750 /* preallocate and check sizes */ 4751 ierr = MatSeqAIJSetPreallocation_SeqAIJ(mat,0,rowlens);CHKERRQ(ierr); 4752 ierr = MatGetSize(mat,&rows,&cols);CHKERRQ(ierr); 4753 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); 4754 /* store row lengths */ 4755 ierr = PetscArraycpy(a->ilen,rowlens,M);CHKERRQ(ierr); 4756 ierr = PetscFree(rowlens);CHKERRQ(ierr); 4757 4758 /* fill in "i" row pointers */ 4759 a->i[0] = 0; for (i=0; i<M; i++) a->i[i+1] = a->i[i] + a->ilen[i]; 4760 /* read in "j" column indices */ 4761 ierr = PetscViewerBinaryRead(viewer,a->j,nz,NULL,PETSC_INT);CHKERRQ(ierr); 4762 /* read in "a" nonzero values */ 4763 ierr = PetscViewerBinaryRead(viewer,a->a,nz,NULL,PETSC_SCALAR);CHKERRQ(ierr); 4764 4765 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4766 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4767 PetscFunctionReturn(0); 4768 } 4769 4770 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4771 { 4772 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4773 PetscErrorCode ierr; 4774 #if defined(PETSC_USE_COMPLEX) 4775 PetscInt k; 4776 #endif 4777 4778 PetscFunctionBegin; 4779 /* If the matrix dimensions are not equal,or no of nonzeros */ 4780 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4781 *flg = PETSC_FALSE; 4782 PetscFunctionReturn(0); 4783 } 4784 4785 /* if the a->i are the same */ 4786 ierr = PetscArraycmp(a->i,b->i,A->rmap->n+1,flg);CHKERRQ(ierr); 4787 if (!*flg) PetscFunctionReturn(0); 4788 4789 /* if a->j are the same */ 4790 ierr = PetscArraycmp(a->j,b->j,a->nz,flg);CHKERRQ(ierr); 4791 if (!*flg) PetscFunctionReturn(0); 4792 4793 /* if a->a are the same */ 4794 #if defined(PETSC_USE_COMPLEX) 4795 for (k=0; k<a->nz; k++) { 4796 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4797 *flg = PETSC_FALSE; 4798 PetscFunctionReturn(0); 4799 } 4800 } 4801 #else 4802 ierr = PetscArraycmp(a->a,b->a,a->nz,flg);CHKERRQ(ierr); 4803 #endif 4804 PetscFunctionReturn(0); 4805 } 4806 4807 /*@ 4808 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4809 provided by the user. 4810 4811 Collective 4812 4813 Input Parameters: 4814 + comm - must be an MPI communicator of size 1 4815 . m - number of rows 4816 . n - number of columns 4817 . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix 4818 . j - column indices 4819 - a - matrix values 4820 4821 Output Parameter: 4822 . mat - the matrix 4823 4824 Level: intermediate 4825 4826 Notes: 4827 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4828 once the matrix is destroyed and not before 4829 4830 You cannot set new nonzero locations into this matrix, that will generate an error. 4831 4832 The i and j indices are 0 based 4833 4834 The format which is used for the sparse matrix input, is equivalent to a 4835 row-major ordering.. i.e for the following matrix, the input data expected is 4836 as shown 4837 4838 $ 1 0 0 4839 $ 2 0 3 4840 $ 4 5 6 4841 $ 4842 $ i = {0,1,3,6} [size = nrow+1 = 3+1] 4843 $ j = {0,0,2,0,1,2} [size = 6]; values must be sorted for each row 4844 $ v = {1,2,3,4,5,6} [size = 6] 4845 4846 4847 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4848 4849 @*/ 4850 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat) 4851 { 4852 PetscErrorCode ierr; 4853 PetscInt ii; 4854 Mat_SeqAIJ *aij; 4855 PetscInt jj; 4856 4857 PetscFunctionBegin; 4858 if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4859 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4860 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4861 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4862 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4863 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr); 4864 aij = (Mat_SeqAIJ*)(*mat)->data; 4865 ierr = PetscMalloc1(m,&aij->imax);CHKERRQ(ierr); 4866 ierr = PetscMalloc1(m,&aij->ilen);CHKERRQ(ierr); 4867 4868 aij->i = i; 4869 aij->j = j; 4870 aij->a = a; 4871 aij->singlemalloc = PETSC_FALSE; 4872 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4873 aij->free_a = PETSC_FALSE; 4874 aij->free_ij = PETSC_FALSE; 4875 4876 for (ii=0; ii<m; ii++) { 4877 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4878 if (PetscDefined(USE_DEBUG)) { 4879 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]); 4880 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4881 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); 4882 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); 4883 } 4884 } 4885 } 4886 if (PetscDefined(USE_DEBUG)) { 4887 for (ii=0; ii<aij->i[m]; ii++) { 4888 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4889 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]); 4890 } 4891 } 4892 4893 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4894 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4895 PetscFunctionReturn(0); 4896 } 4897 /*@C 4898 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4899 provided by the user. 4900 4901 Collective 4902 4903 Input Parameters: 4904 + comm - must be an MPI communicator of size 1 4905 . m - number of rows 4906 . n - number of columns 4907 . i - row indices 4908 . j - column indices 4909 . a - matrix values 4910 . nz - number of nonzeros 4911 - idx - 0 or 1 based 4912 4913 Output Parameter: 4914 . mat - the matrix 4915 4916 Level: intermediate 4917 4918 Notes: 4919 The i and j indices are 0 based 4920 4921 The format which is used for the sparse matrix input, is equivalent to a 4922 row-major ordering.. i.e for the following matrix, the input data expected is 4923 as shown: 4924 4925 1 0 0 4926 2 0 3 4927 4 5 6 4928 4929 i = {0,1,1,2,2,2} 4930 j = {0,0,2,0,1,2} 4931 v = {1,2,3,4,5,6} 4932 4933 4934 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4935 4936 @*/ 4937 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat,PetscInt nz,PetscBool idx) 4938 { 4939 PetscErrorCode ierr; 4940 PetscInt ii, *nnz, one = 1,row,col; 4941 4942 4943 PetscFunctionBegin; 4944 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4945 for (ii = 0; ii < nz; ii++) { 4946 nnz[i[ii] - !!idx] += 1; 4947 } 4948 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4949 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4950 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4951 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4952 for (ii = 0; ii < nz; ii++) { 4953 if (idx) { 4954 row = i[ii] - 1; 4955 col = j[ii] - 1; 4956 } else { 4957 row = i[ii]; 4958 col = j[ii]; 4959 } 4960 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4961 } 4962 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4963 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4964 ierr = PetscFree(nnz);CHKERRQ(ierr); 4965 PetscFunctionReturn(0); 4966 } 4967 4968 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4969 { 4970 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4971 PetscErrorCode ierr; 4972 4973 PetscFunctionBegin; 4974 a->idiagvalid = PETSC_FALSE; 4975 a->ibdiagvalid = PETSC_FALSE; 4976 4977 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4978 PetscFunctionReturn(0); 4979 } 4980 4981 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4982 { 4983 PetscErrorCode ierr; 4984 PetscMPIInt size; 4985 4986 PetscFunctionBegin; 4987 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4988 if (size == 1) { 4989 if (scall == MAT_INITIAL_MATRIX) { 4990 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4991 } else { 4992 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4993 } 4994 } else { 4995 ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); 4996 } 4997 PetscFunctionReturn(0); 4998 } 4999 5000 /* 5001 Permute A into C's *local* index space using rowemb,colemb. 5002 The embedding are supposed to be injections and the above implies that the range of rowemb is a subset 5003 of [0,m), colemb is in [0,n). 5004 If pattern == DIFFERENT_NONZERO_PATTERN, C is preallocated according to A. 5005 */ 5006 PetscErrorCode MatSetSeqMat_SeqAIJ(Mat C,IS rowemb,IS colemb,MatStructure pattern,Mat B) 5007 { 5008 /* If making this function public, change the error returned in this function away from _PLIB. */ 5009 PetscErrorCode ierr; 5010 Mat_SeqAIJ *Baij; 5011 PetscBool seqaij; 5012 PetscInt m,n,*nz,i,j,count; 5013 PetscScalar v; 5014 const PetscInt *rowindices,*colindices; 5015 5016 PetscFunctionBegin; 5017 if (!B) PetscFunctionReturn(0); 5018 /* Check to make sure the target matrix (and embeddings) are compatible with C and each other. */ 5019 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQAIJ,&seqaij);CHKERRQ(ierr); 5020 if (!seqaij) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is of wrong type"); 5021 if (rowemb) { 5022 ierr = ISGetLocalSize(rowemb,&m);CHKERRQ(ierr); 5023 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); 5024 } else { 5025 if (C->rmap->n != B->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is row-incompatible with the target matrix"); 5026 } 5027 if (colemb) { 5028 ierr = ISGetLocalSize(colemb,&n);CHKERRQ(ierr); 5029 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); 5030 } else { 5031 if (C->cmap->n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is col-incompatible with the target matrix"); 5032 } 5033 5034 Baij = (Mat_SeqAIJ*)(B->data); 5035 if (pattern == DIFFERENT_NONZERO_PATTERN) { 5036 ierr = PetscMalloc1(B->rmap->n,&nz);CHKERRQ(ierr); 5037 for (i=0; i<B->rmap->n; i++) { 5038 nz[i] = Baij->i[i+1] - Baij->i[i]; 5039 } 5040 ierr = MatSeqAIJSetPreallocation(C,0,nz);CHKERRQ(ierr); 5041 ierr = PetscFree(nz);CHKERRQ(ierr); 5042 } 5043 if (pattern == SUBSET_NONZERO_PATTERN) { 5044 ierr = MatZeroEntries(C);CHKERRQ(ierr); 5045 } 5046 count = 0; 5047 rowindices = NULL; 5048 colindices = NULL; 5049 if (rowemb) { 5050 ierr = ISGetIndices(rowemb,&rowindices);CHKERRQ(ierr); 5051 } 5052 if (colemb) { 5053 ierr = ISGetIndices(colemb,&colindices);CHKERRQ(ierr); 5054 } 5055 for (i=0; i<B->rmap->n; i++) { 5056 PetscInt row; 5057 row = i; 5058 if (rowindices) row = rowindices[i]; 5059 for (j=Baij->i[i]; j<Baij->i[i+1]; j++) { 5060 PetscInt col; 5061 col = Baij->j[count]; 5062 if (colindices) col = colindices[col]; 5063 v = Baij->a[count]; 5064 ierr = MatSetValues(C,1,&row,1,&col,&v,INSERT_VALUES);CHKERRQ(ierr); 5065 ++count; 5066 } 5067 } 5068 /* FIXME: set C's nonzerostate correctly. */ 5069 /* Assembly for C is necessary. */ 5070 C->preallocated = PETSC_TRUE; 5071 C->assembled = PETSC_TRUE; 5072 C->was_assembled = PETSC_FALSE; 5073 PetscFunctionReturn(0); 5074 } 5075 5076 PetscFunctionList MatSeqAIJList = NULL; 5077 5078 /*@C 5079 MatSeqAIJSetType - Converts a MATSEQAIJ matrix to a subtype 5080 5081 Collective on Mat 5082 5083 Input Parameters: 5084 + mat - the matrix object 5085 - matype - matrix type 5086 5087 Options Database Key: 5088 . -mat_seqai_type <method> - for example seqaijcrl 5089 5090 5091 Level: intermediate 5092 5093 .seealso: PCSetType(), VecSetType(), MatCreate(), MatType, Mat 5094 @*/ 5095 PetscErrorCode MatSeqAIJSetType(Mat mat, MatType matype) 5096 { 5097 PetscErrorCode ierr,(*r)(Mat,MatType,MatReuse,Mat*); 5098 PetscBool sametype; 5099 5100 PetscFunctionBegin; 5101 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 5102 ierr = PetscObjectTypeCompare((PetscObject)mat,matype,&sametype);CHKERRQ(ierr); 5103 if (sametype) PetscFunctionReturn(0); 5104 5105 ierr = PetscFunctionListFind(MatSeqAIJList,matype,&r);CHKERRQ(ierr); 5106 if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown Mat type given: %s",matype); 5107 ierr = (*r)(mat,matype,MAT_INPLACE_MATRIX,&mat);CHKERRQ(ierr); 5108 PetscFunctionReturn(0); 5109 } 5110 5111 5112 /*@C 5113 MatSeqAIJRegister - - Adds a new sub-matrix type for sequential AIJ matrices 5114 5115 Not Collective 5116 5117 Input Parameters: 5118 + name - name of a new user-defined matrix type, for example MATSEQAIJCRL 5119 - function - routine to convert to subtype 5120 5121 Notes: 5122 MatSeqAIJRegister() may be called multiple times to add several user-defined solvers. 5123 5124 5125 Then, your matrix can be chosen with the procedural interface at runtime via the option 5126 $ -mat_seqaij_type my_mat 5127 5128 Level: advanced 5129 5130 .seealso: MatSeqAIJRegisterAll() 5131 5132 5133 Level: advanced 5134 @*/ 5135 PetscErrorCode MatSeqAIJRegister(const char sname[],PetscErrorCode (*function)(Mat,MatType,MatReuse,Mat *)) 5136 { 5137 PetscErrorCode ierr; 5138 5139 PetscFunctionBegin; 5140 ierr = MatInitializePackage();CHKERRQ(ierr); 5141 ierr = PetscFunctionListAdd(&MatSeqAIJList,sname,function);CHKERRQ(ierr); 5142 PetscFunctionReturn(0); 5143 } 5144 5145 PetscBool MatSeqAIJRegisterAllCalled = PETSC_FALSE; 5146 5147 /*@C 5148 MatSeqAIJRegisterAll - Registers all of the matrix subtypes of SeqAIJ 5149 5150 Not Collective 5151 5152 Level: advanced 5153 5154 Developers Note: CUSP and CUSPARSE do not yet support the MatConvert_SeqAIJ..() paradigm and thus cannot be registered here 5155 5156 .seealso: MatRegisterAll(), MatSeqAIJRegister() 5157 @*/ 5158 PetscErrorCode MatSeqAIJRegisterAll(void) 5159 { 5160 PetscErrorCode ierr; 5161 5162 PetscFunctionBegin; 5163 if (MatSeqAIJRegisterAllCalled) PetscFunctionReturn(0); 5164 MatSeqAIJRegisterAllCalled = PETSC_TRUE; 5165 5166 ierr = MatSeqAIJRegister(MATSEQAIJCRL, MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 5167 ierr = MatSeqAIJRegister(MATSEQAIJPERM, MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 5168 ierr = MatSeqAIJRegister(MATSEQAIJSELL, MatConvert_SeqAIJ_SeqAIJSELL);CHKERRQ(ierr); 5169 #if defined(PETSC_HAVE_MKL_SPARSE) 5170 ierr = MatSeqAIJRegister(MATSEQAIJMKL, MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 5171 #endif 5172 #if defined(PETSC_HAVE_VIENNACL) && defined(PETSC_HAVE_VIENNACL_NO_CUDA) 5173 ierr = MatSeqAIJRegister(MATMPIAIJVIENNACL, MatConvert_SeqAIJ_SeqAIJViennaCL);CHKERRQ(ierr); 5174 #endif 5175 PetscFunctionReturn(0); 5176 } 5177 5178 /* 5179 Special version for direct calls from Fortran 5180 */ 5181 #include <petsc/private/fortranimpl.h> 5182 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5183 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 5184 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5185 #define matsetvaluesseqaij_ matsetvaluesseqaij 5186 #endif 5187 5188 /* Change these macros so can be used in void function */ 5189 #undef CHKERRQ 5190 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 5191 #undef SETERRQ2 5192 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5193 #undef SETERRQ3 5194 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5195 5196 PETSC_EXTERN void matsetvaluesseqaij_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[],InsertMode *isis, PetscErrorCode *_ierr) 5197 { 5198 Mat A = *AA; 5199 PetscInt m = *mm, n = *nn; 5200 InsertMode is = *isis; 5201 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5202 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 5203 PetscInt *imax,*ai,*ailen; 5204 PetscErrorCode ierr; 5205 PetscInt *aj,nonew = a->nonew,lastcol = -1; 5206 MatScalar *ap,value,*aa; 5207 PetscBool ignorezeroentries = a->ignorezeroentries; 5208 PetscBool roworiented = a->roworiented; 5209 5210 PetscFunctionBegin; 5211 MatCheckPreallocated(A,1); 5212 imax = a->imax; 5213 ai = a->i; 5214 ailen = a->ilen; 5215 aj = a->j; 5216 aa = a->a; 5217 5218 for (k=0; k<m; k++) { /* loop over added rows */ 5219 row = im[k]; 5220 if (row < 0) continue; 5221 if (PetscUnlikelyDebug(row >= A->rmap->n)) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 5222 rp = aj + ai[row]; ap = aa + ai[row]; 5223 rmax = imax[row]; nrow = ailen[row]; 5224 low = 0; 5225 high = nrow; 5226 for (l=0; l<n; l++) { /* loop over added columns */ 5227 if (in[l] < 0) continue; 5228 if (PetscUnlikelyDebug(in[l] >= A->cmap->n)) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 5229 col = in[l]; 5230 if (roworiented) value = v[l + k*n]; 5231 else value = v[k + l*m]; 5232 5233 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 5234 5235 if (col <= lastcol) low = 0; 5236 else high = nrow; 5237 lastcol = col; 5238 while (high-low > 5) { 5239 t = (low+high)/2; 5240 if (rp[t] > col) high = t; 5241 else low = t; 5242 } 5243 for (i=low; i<high; i++) { 5244 if (rp[i] > col) break; 5245 if (rp[i] == col) { 5246 if (is == ADD_VALUES) ap[i] += value; 5247 else ap[i] = value; 5248 goto noinsert; 5249 } 5250 } 5251 if (value == 0.0 && ignorezeroentries) goto noinsert; 5252 if (nonew == 1) goto noinsert; 5253 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 5254 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 5255 N = nrow++ - 1; a->nz++; high++; 5256 /* shift up all the later entries in this row */ 5257 for (ii=N; ii>=i; ii--) { 5258 rp[ii+1] = rp[ii]; 5259 ap[ii+1] = ap[ii]; 5260 } 5261 rp[i] = col; 5262 ap[i] = value; 5263 A->nonzerostate++; 5264 noinsert:; 5265 low = i + 1; 5266 } 5267 ailen[row] = nrow; 5268 } 5269 PetscFunctionReturnVoid(); 5270 } 5271