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