1 #include <../src/mat/impls/baij/mpi/mpibaij.h> /*I "petscmat.h" I*/ 2 #include <../src/mat/impls/sbaij/mpi/mpisbaij.h> 3 #include <../src/mat/impls/sbaij/seq/sbaij.h> 4 #include <petscblaslapack.h> 5 6 static PetscErrorCode MatDestroy_MPISBAIJ(Mat mat) 7 { 8 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data; 9 10 PetscFunctionBegin; 11 PetscCall(PetscLogObjectState((PetscObject)mat, "Rows=%" PetscInt_FMT ",Cols=%" PetscInt_FMT, mat->rmap->N, mat->cmap->N)); 12 PetscCall(MatStashDestroy_Private(&mat->stash)); 13 PetscCall(MatStashDestroy_Private(&mat->bstash)); 14 PetscCall(MatDestroy(&baij->A)); 15 PetscCall(MatDestroy(&baij->B)); 16 #if defined(PETSC_USE_CTABLE) 17 PetscCall(PetscHMapIDestroy(&baij->colmap)); 18 #else 19 PetscCall(PetscFree(baij->colmap)); 20 #endif 21 PetscCall(PetscFree(baij->garray)); 22 PetscCall(VecDestroy(&baij->lvec)); 23 PetscCall(VecScatterDestroy(&baij->Mvctx)); 24 PetscCall(VecDestroy(&baij->slvec0)); 25 PetscCall(VecDestroy(&baij->slvec0b)); 26 PetscCall(VecDestroy(&baij->slvec1)); 27 PetscCall(VecDestroy(&baij->slvec1a)); 28 PetscCall(VecDestroy(&baij->slvec1b)); 29 PetscCall(VecScatterDestroy(&baij->sMvctx)); 30 PetscCall(PetscFree2(baij->rowvalues, baij->rowindices)); 31 PetscCall(PetscFree(baij->barray)); 32 PetscCall(PetscFree(baij->hd)); 33 PetscCall(VecDestroy(&baij->diag)); 34 PetscCall(VecDestroy(&baij->bb1)); 35 PetscCall(VecDestroy(&baij->xx1)); 36 #if defined(PETSC_USE_REAL_MAT_SINGLE) 37 PetscCall(PetscFree(baij->setvaluescopy)); 38 #endif 39 PetscCall(PetscFree(baij->in_loc)); 40 PetscCall(PetscFree(baij->v_loc)); 41 PetscCall(PetscFree(baij->rangebs)); 42 PetscCall(PetscFree(mat->data)); 43 44 PetscCall(PetscObjectChangeTypeName((PetscObject)mat, NULL)); 45 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatStoreValues_C", NULL)); 46 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatRetrieveValues_C", NULL)); 47 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatMPISBAIJSetPreallocation_C", NULL)); 48 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatMPISBAIJSetPreallocationCSR_C", NULL)); 49 #if defined(PETSC_HAVE_ELEMENTAL) 50 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpisbaij_elemental_C", NULL)); 51 #endif 52 #if defined(PETSC_HAVE_SCALAPACK) 53 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpisbaij_scalapack_C", NULL)); 54 #endif 55 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpisbaij_mpiaij_C", NULL)); 56 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpisbaij_mpibaij_C", NULL)); 57 PetscFunctionReturn(PETSC_SUCCESS); 58 } 59 60 /* defines MatSetValues_MPI_Hash(), MatAssemblyBegin_MPI_Hash(), MatAssemblyEnd_MPI_Hash(), MatSetUp_MPI_Hash() */ 61 #define TYPE SBAIJ 62 #define TYPE_SBAIJ 63 #include "../src/mat/impls/aij/mpi/mpihashmat.h" 64 #undef TYPE 65 #undef TYPE_SBAIJ 66 67 #if defined(PETSC_HAVE_ELEMENTAL) 68 PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Elemental(Mat, MatType, MatReuse, Mat *); 69 #endif 70 #if defined(PETSC_HAVE_SCALAPACK) 71 PETSC_INTERN PetscErrorCode MatConvert_SBAIJ_ScaLAPACK(Mat, MatType, MatReuse, Mat *); 72 #endif 73 74 /* This could be moved to matimpl.h */ 75 static PetscErrorCode MatPreallocateWithMats_Private(Mat B, PetscInt nm, Mat X[], PetscBool symm[], PetscBool fill) 76 { 77 Mat preallocator; 78 PetscInt r, rstart, rend; 79 PetscInt bs, i, m, n, M, N; 80 PetscBool cong = PETSC_TRUE; 81 82 PetscFunctionBegin; 83 PetscValidHeaderSpecific(B, MAT_CLASSID, 1); 84 PetscValidLogicalCollectiveInt(B, nm, 2); 85 for (i = 0; i < nm; i++) { 86 PetscValidHeaderSpecific(X[i], MAT_CLASSID, 3); 87 PetscCall(PetscLayoutCompare(B->rmap, X[i]->rmap, &cong)); 88 PetscCheck(cong, PetscObjectComm((PetscObject)B), PETSC_ERR_SUP, "Not for different layouts"); 89 } 90 PetscValidLogicalCollectiveBool(B, fill, 5); 91 PetscCall(MatGetBlockSize(B, &bs)); 92 PetscCall(MatGetSize(B, &M, &N)); 93 PetscCall(MatGetLocalSize(B, &m, &n)); 94 PetscCall(MatCreate(PetscObjectComm((PetscObject)B), &preallocator)); 95 PetscCall(MatSetType(preallocator, MATPREALLOCATOR)); 96 PetscCall(MatSetBlockSize(preallocator, bs)); 97 PetscCall(MatSetSizes(preallocator, m, n, M, N)); 98 PetscCall(MatSetUp(preallocator)); 99 PetscCall(MatGetOwnershipRange(preallocator, &rstart, &rend)); 100 for (r = rstart; r < rend; ++r) { 101 PetscInt ncols; 102 const PetscInt *row; 103 const PetscScalar *vals; 104 105 for (i = 0; i < nm; i++) { 106 PetscCall(MatGetRow(X[i], r, &ncols, &row, &vals)); 107 PetscCall(MatSetValues(preallocator, 1, &r, ncols, row, vals, INSERT_VALUES)); 108 if (symm && symm[i]) PetscCall(MatSetValues(preallocator, ncols, row, 1, &r, vals, INSERT_VALUES)); 109 PetscCall(MatRestoreRow(X[i], r, &ncols, &row, &vals)); 110 } 111 } 112 PetscCall(MatAssemblyBegin(preallocator, MAT_FINAL_ASSEMBLY)); 113 PetscCall(MatAssemblyEnd(preallocator, MAT_FINAL_ASSEMBLY)); 114 PetscCall(MatPreallocatorPreallocate(preallocator, fill, B)); 115 PetscCall(MatDestroy(&preallocator)); 116 PetscFunctionReturn(PETSC_SUCCESS); 117 } 118 119 PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Basic(Mat A, MatType newtype, MatReuse reuse, Mat *newmat) 120 { 121 Mat B; 122 PetscInt r; 123 124 PetscFunctionBegin; 125 if (reuse != MAT_REUSE_MATRIX) { 126 PetscBool symm = PETSC_TRUE, isdense; 127 PetscInt bs; 128 129 PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B)); 130 PetscCall(MatSetSizes(B, A->rmap->n, A->cmap->n, A->rmap->N, A->cmap->N)); 131 PetscCall(MatSetType(B, newtype)); 132 PetscCall(MatGetBlockSize(A, &bs)); 133 PetscCall(MatSetBlockSize(B, bs)); 134 PetscCall(PetscLayoutSetUp(B->rmap)); 135 PetscCall(PetscLayoutSetUp(B->cmap)); 136 PetscCall(PetscObjectTypeCompareAny((PetscObject)B, &isdense, MATSEQDENSE, MATMPIDENSE, MATSEQDENSECUDA, "")); 137 if (!isdense) { 138 PetscCall(MatGetRowUpperTriangular(A)); 139 PetscCall(MatPreallocateWithMats_Private(B, 1, &A, &symm, PETSC_TRUE)); 140 PetscCall(MatRestoreRowUpperTriangular(A)); 141 } else { 142 PetscCall(MatSetUp(B)); 143 } 144 } else { 145 B = *newmat; 146 PetscCall(MatZeroEntries(B)); 147 } 148 149 PetscCall(MatGetRowUpperTriangular(A)); 150 for (r = A->rmap->rstart; r < A->rmap->rend; r++) { 151 PetscInt ncols; 152 const PetscInt *row; 153 const PetscScalar *vals; 154 155 PetscCall(MatGetRow(A, r, &ncols, &row, &vals)); 156 PetscCall(MatSetValues(B, 1, &r, ncols, row, vals, INSERT_VALUES)); 157 #if defined(PETSC_USE_COMPLEX) 158 if (A->hermitian == PETSC_BOOL3_TRUE) { 159 PetscInt i; 160 for (i = 0; i < ncols; i++) PetscCall(MatSetValue(B, row[i], r, PetscConj(vals[i]), INSERT_VALUES)); 161 } else { 162 PetscCall(MatSetValues(B, ncols, row, 1, &r, vals, INSERT_VALUES)); 163 } 164 #else 165 PetscCall(MatSetValues(B, ncols, row, 1, &r, vals, INSERT_VALUES)); 166 #endif 167 PetscCall(MatRestoreRow(A, r, &ncols, &row, &vals)); 168 } 169 PetscCall(MatRestoreRowUpperTriangular(A)); 170 PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY)); 171 PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY)); 172 173 if (reuse == MAT_INPLACE_MATRIX) { 174 PetscCall(MatHeaderReplace(A, &B)); 175 } else { 176 *newmat = B; 177 } 178 PetscFunctionReturn(PETSC_SUCCESS); 179 } 180 181 static PetscErrorCode MatStoreValues_MPISBAIJ(Mat mat) 182 { 183 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 184 185 PetscFunctionBegin; 186 PetscCall(MatStoreValues(aij->A)); 187 PetscCall(MatStoreValues(aij->B)); 188 PetscFunctionReturn(PETSC_SUCCESS); 189 } 190 191 static PetscErrorCode MatRetrieveValues_MPISBAIJ(Mat mat) 192 { 193 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 194 195 PetscFunctionBegin; 196 PetscCall(MatRetrieveValues(aij->A)); 197 PetscCall(MatRetrieveValues(aij->B)); 198 PetscFunctionReturn(PETSC_SUCCESS); 199 } 200 201 #define MatSetValues_SeqSBAIJ_A_Private(row, col, value, addv, orow, ocol) \ 202 do { \ 203 brow = row / bs; \ 204 rp = aj + ai[brow]; \ 205 ap = aa + bs2 * ai[brow]; \ 206 rmax = aimax[brow]; \ 207 nrow = ailen[brow]; \ 208 bcol = col / bs; \ 209 ridx = row % bs; \ 210 cidx = col % bs; \ 211 low = 0; \ 212 high = nrow; \ 213 while (high - low > 3) { \ 214 t = (low + high) / 2; \ 215 if (rp[t] > bcol) high = t; \ 216 else low = t; \ 217 } \ 218 for (_i = low; _i < high; _i++) { \ 219 if (rp[_i] > bcol) break; \ 220 if (rp[_i] == bcol) { \ 221 bap = ap + bs2 * _i + bs * cidx + ridx; \ 222 if (addv == ADD_VALUES) *bap += value; \ 223 else *bap = value; \ 224 goto a_noinsert; \ 225 } \ 226 } \ 227 if (a->nonew == 1) goto a_noinsert; \ 228 PetscCheck(a->nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero at global row/column (%" PetscInt_FMT ", %" PetscInt_FMT ") into matrix", orow, ocol); \ 229 MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, brow, bcol, rmax, aa, ai, aj, rp, ap, aimax, a->nonew, MatScalar); \ 230 N = nrow++ - 1; \ 231 /* shift up all the later entries in this row */ \ 232 PetscCall(PetscArraymove(rp + _i + 1, rp + _i, N - _i + 1)); \ 233 PetscCall(PetscArraymove(ap + bs2 * (_i + 1), ap + bs2 * _i, bs2 * (N - _i + 1))); \ 234 PetscCall(PetscArrayzero(ap + bs2 * _i, bs2)); \ 235 rp[_i] = bcol; \ 236 ap[bs2 * _i + bs * cidx + ridx] = value; \ 237 A->nonzerostate++; \ 238 a_noinsert:; \ 239 ailen[brow] = nrow; \ 240 } while (0) 241 242 #define MatSetValues_SeqSBAIJ_B_Private(row, col, value, addv, orow, ocol) \ 243 do { \ 244 brow = row / bs; \ 245 rp = bj + bi[brow]; \ 246 ap = ba + bs2 * bi[brow]; \ 247 rmax = bimax[brow]; \ 248 nrow = bilen[brow]; \ 249 bcol = col / bs; \ 250 ridx = row % bs; \ 251 cidx = col % bs; \ 252 low = 0; \ 253 high = nrow; \ 254 while (high - low > 3) { \ 255 t = (low + high) / 2; \ 256 if (rp[t] > bcol) high = t; \ 257 else low = t; \ 258 } \ 259 for (_i = low; _i < high; _i++) { \ 260 if (rp[_i] > bcol) break; \ 261 if (rp[_i] == bcol) { \ 262 bap = ap + bs2 * _i + bs * cidx + ridx; \ 263 if (addv == ADD_VALUES) *bap += value; \ 264 else *bap = value; \ 265 goto b_noinsert; \ 266 } \ 267 } \ 268 if (b->nonew == 1) goto b_noinsert; \ 269 PetscCheck(b->nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero at global row/column (%" PetscInt_FMT ", %" PetscInt_FMT ") into matrix", orow, ocol); \ 270 MatSeqXAIJReallocateAIJ(B, b->mbs, bs2, nrow, brow, bcol, rmax, ba, bi, bj, rp, ap, bimax, b->nonew, MatScalar); \ 271 N = nrow++ - 1; \ 272 /* shift up all the later entries in this row */ \ 273 PetscCall(PetscArraymove(rp + _i + 1, rp + _i, N - _i + 1)); \ 274 PetscCall(PetscArraymove(ap + bs2 * (_i + 1), ap + bs2 * _i, bs2 * (N - _i + 1))); \ 275 PetscCall(PetscArrayzero(ap + bs2 * _i, bs2)); \ 276 rp[_i] = bcol; \ 277 ap[bs2 * _i + bs * cidx + ridx] = value; \ 278 B->nonzerostate++; \ 279 b_noinsert:; \ 280 bilen[brow] = nrow; \ 281 } while (0) 282 283 /* Only add/insert a(i,j) with i<=j (blocks). 284 Any a(i,j) with i>j input by user is ignored or generates an error 285 */ 286 static PetscErrorCode MatSetValues_MPISBAIJ(Mat mat, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode addv) 287 { 288 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data; 289 MatScalar value; 290 PetscBool roworiented = baij->roworiented; 291 PetscInt i, j, row, col; 292 PetscInt rstart_orig = mat->rmap->rstart; 293 PetscInt rend_orig = mat->rmap->rend, cstart_orig = mat->cmap->rstart; 294 PetscInt cend_orig = mat->cmap->rend, bs = mat->rmap->bs; 295 296 /* Some Variables required in the macro */ 297 Mat A = baij->A; 298 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)(A)->data; 299 PetscInt *aimax = a->imax, *ai = a->i, *ailen = a->ilen, *aj = a->j; 300 MatScalar *aa = a->a; 301 302 Mat B = baij->B; 303 Mat_SeqBAIJ *b = (Mat_SeqBAIJ *)(B)->data; 304 PetscInt *bimax = b->imax, *bi = b->i, *bilen = b->ilen, *bj = b->j; 305 MatScalar *ba = b->a; 306 307 PetscInt *rp, ii, nrow, _i, rmax, N, brow, bcol; 308 PetscInt low, high, t, ridx, cidx, bs2 = a->bs2; 309 MatScalar *ap, *bap; 310 311 /* for stash */ 312 PetscInt n_loc, *in_loc = NULL; 313 MatScalar *v_loc = NULL; 314 315 PetscFunctionBegin; 316 if (!baij->donotstash) { 317 if (n > baij->n_loc) { 318 PetscCall(PetscFree(baij->in_loc)); 319 PetscCall(PetscFree(baij->v_loc)); 320 PetscCall(PetscMalloc1(n, &baij->in_loc)); 321 PetscCall(PetscMalloc1(n, &baij->v_loc)); 322 323 baij->n_loc = n; 324 } 325 in_loc = baij->in_loc; 326 v_loc = baij->v_loc; 327 } 328 329 for (i = 0; i < m; i++) { 330 if (im[i] < 0) continue; 331 PetscCheck(im[i] < mat->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, im[i], mat->rmap->N - 1); 332 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 333 row = im[i] - rstart_orig; /* local row index */ 334 for (j = 0; j < n; j++) { 335 if (im[i] / bs > in[j] / bs) { 336 if (a->ignore_ltriangular) { 337 continue; /* ignore lower triangular blocks */ 338 } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_USER, "Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)"); 339 } 340 if (in[j] >= cstart_orig && in[j] < cend_orig) { /* diag entry (A) */ 341 col = in[j] - cstart_orig; /* local col index */ 342 brow = row / bs; 343 bcol = col / bs; 344 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 345 if (roworiented) value = v[i * n + j]; 346 else value = v[i + j * m]; 347 MatSetValues_SeqSBAIJ_A_Private(row, col, value, addv, im[i], in[j]); 348 /* PetscCall(MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv)); */ 349 } else if (in[j] < 0) { 350 continue; 351 } else { 352 PetscCheck(in[j] < mat->cmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, in[j], mat->cmap->N - 1); 353 /* off-diag entry (B) */ 354 if (mat->was_assembled) { 355 if (!baij->colmap) PetscCall(MatCreateColmap_MPIBAIJ_Private(mat)); 356 #if defined(PETSC_USE_CTABLE) 357 PetscCall(PetscHMapIGetWithDefault(baij->colmap, in[j] / bs + 1, 0, &col)); 358 col = col - 1; 359 #else 360 col = baij->colmap[in[j] / bs] - 1; 361 #endif 362 if (col < 0 && !((Mat_SeqSBAIJ *)(baij->A->data))->nonew) { 363 PetscCall(MatDisAssemble_MPISBAIJ(mat)); 364 col = in[j]; 365 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 366 B = baij->B; 367 b = (Mat_SeqBAIJ *)(B)->data; 368 bimax = b->imax; 369 bi = b->i; 370 bilen = b->ilen; 371 bj = b->j; 372 ba = b->a; 373 } else col += in[j] % bs; 374 } else col = in[j]; 375 if (roworiented) value = v[i * n + j]; 376 else value = v[i + j * m]; 377 MatSetValues_SeqSBAIJ_B_Private(row, col, value, addv, im[i], in[j]); 378 /* PetscCall(MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv)); */ 379 } 380 } 381 } else { /* off processor entry */ 382 PetscCheck(!mat->nooffprocentries, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Setting off process row %" PetscInt_FMT " even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set", im[i]); 383 if (!baij->donotstash) { 384 mat->assembled = PETSC_FALSE; 385 n_loc = 0; 386 for (j = 0; j < n; j++) { 387 if (im[i] / bs > in[j] / bs) continue; /* ignore lower triangular blocks */ 388 in_loc[n_loc] = in[j]; 389 if (roworiented) { 390 v_loc[n_loc] = v[i * n + j]; 391 } else { 392 v_loc[n_loc] = v[j * m + i]; 393 } 394 n_loc++; 395 } 396 PetscCall(MatStashValuesRow_Private(&mat->stash, im[i], n_loc, in_loc, v_loc, PETSC_FALSE)); 397 } 398 } 399 } 400 PetscFunctionReturn(PETSC_SUCCESS); 401 } 402 403 static inline PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_Inlined(Mat A, PetscInt row, PetscInt col, const PetscScalar v[], InsertMode is, PetscInt orow, PetscInt ocol) 404 { 405 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)A->data; 406 PetscInt *rp, low, high, t, ii, jj, nrow, i, rmax, N; 407 PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen; 408 PetscInt *aj = a->j, nonew = a->nonew, bs2 = a->bs2, bs = A->rmap->bs; 409 PetscBool roworiented = a->roworiented; 410 const PetscScalar *value = v; 411 MatScalar *ap, *aa = a->a, *bap; 412 413 PetscFunctionBegin; 414 if (col < row) { 415 if (a->ignore_ltriangular) PetscFunctionReturn(PETSC_SUCCESS); /* ignore lower triangular block */ 416 else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_USER, "Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)"); 417 } 418 rp = aj + ai[row]; 419 ap = aa + bs2 * ai[row]; 420 rmax = imax[row]; 421 nrow = ailen[row]; 422 value = v; 423 low = 0; 424 high = nrow; 425 426 while (high - low > 7) { 427 t = (low + high) / 2; 428 if (rp[t] > col) high = t; 429 else low = t; 430 } 431 for (i = low; i < high; i++) { 432 if (rp[i] > col) break; 433 if (rp[i] == col) { 434 bap = ap + bs2 * i; 435 if (roworiented) { 436 if (is == ADD_VALUES) { 437 for (ii = 0; ii < bs; ii++) { 438 for (jj = ii; jj < bs2; jj += bs) bap[jj] += *value++; 439 } 440 } else { 441 for (ii = 0; ii < bs; ii++) { 442 for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++; 443 } 444 } 445 } else { 446 if (is == ADD_VALUES) { 447 for (ii = 0; ii < bs; ii++) { 448 for (jj = 0; jj < bs; jj++) *bap++ += *value++; 449 } 450 } else { 451 for (ii = 0; ii < bs; ii++) { 452 for (jj = 0; jj < bs; jj++) *bap++ = *value++; 453 } 454 } 455 } 456 goto noinsert2; 457 } 458 } 459 if (nonew == 1) goto noinsert2; 460 PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new block index nonzero block (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", orow, ocol); 461 MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, row, col, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar); 462 N = nrow++ - 1; 463 high++; 464 /* shift up all the later entries in this row */ 465 PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1)); 466 PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1))); 467 rp[i] = col; 468 bap = ap + bs2 * i; 469 if (roworiented) { 470 for (ii = 0; ii < bs; ii++) { 471 for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++; 472 } 473 } else { 474 for (ii = 0; ii < bs; ii++) { 475 for (jj = 0; jj < bs; jj++) *bap++ = *value++; 476 } 477 } 478 noinsert2:; 479 ailen[row] = nrow; 480 PetscFunctionReturn(PETSC_SUCCESS); 481 } 482 483 /* 484 This routine is exactly duplicated in mpibaij.c 485 */ 486 static inline PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A, PetscInt row, PetscInt col, const PetscScalar v[], InsertMode is, PetscInt orow, PetscInt ocol) 487 { 488 Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data; 489 PetscInt *rp, low, high, t, ii, jj, nrow, i, rmax, N; 490 PetscInt *imax = a->imax, *ai = a->i, *ailen = a->ilen; 491 PetscInt *aj = a->j, nonew = a->nonew, bs2 = a->bs2, bs = A->rmap->bs; 492 PetscBool roworiented = a->roworiented; 493 const PetscScalar *value = v; 494 MatScalar *ap, *aa = a->a, *bap; 495 496 PetscFunctionBegin; 497 rp = aj + ai[row]; 498 ap = aa + bs2 * ai[row]; 499 rmax = imax[row]; 500 nrow = ailen[row]; 501 low = 0; 502 high = nrow; 503 value = v; 504 while (high - low > 7) { 505 t = (low + high) / 2; 506 if (rp[t] > col) high = t; 507 else low = t; 508 } 509 for (i = low; i < high; i++) { 510 if (rp[i] > col) break; 511 if (rp[i] == col) { 512 bap = ap + bs2 * i; 513 if (roworiented) { 514 if (is == ADD_VALUES) { 515 for (ii = 0; ii < bs; ii++) { 516 for (jj = ii; jj < bs2; jj += bs) bap[jj] += *value++; 517 } 518 } else { 519 for (ii = 0; ii < bs; ii++) { 520 for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++; 521 } 522 } 523 } else { 524 if (is == ADD_VALUES) { 525 for (ii = 0; ii < bs; ii++, value += bs) { 526 for (jj = 0; jj < bs; jj++) bap[jj] += value[jj]; 527 bap += bs; 528 } 529 } else { 530 for (ii = 0; ii < bs; ii++, value += bs) { 531 for (jj = 0; jj < bs; jj++) bap[jj] = value[jj]; 532 bap += bs; 533 } 534 } 535 } 536 goto noinsert2; 537 } 538 } 539 if (nonew == 1) goto noinsert2; 540 PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new global block indexed nonzero block (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", orow, ocol); 541 MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, row, col, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar); 542 N = nrow++ - 1; 543 high++; 544 /* shift up all the later entries in this row */ 545 PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1)); 546 PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1))); 547 rp[i] = col; 548 bap = ap + bs2 * i; 549 if (roworiented) { 550 for (ii = 0; ii < bs; ii++) { 551 for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++; 552 } 553 } else { 554 for (ii = 0; ii < bs; ii++) { 555 for (jj = 0; jj < bs; jj++) *bap++ = *value++; 556 } 557 } 558 noinsert2:; 559 ailen[row] = nrow; 560 PetscFunctionReturn(PETSC_SUCCESS); 561 } 562 563 /* 564 This routine could be optimized by removing the need for the block copy below and passing stride information 565 to the above inline routines; similarly in MatSetValuesBlocked_MPIBAIJ() 566 */ 567 static PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const MatScalar v[], InsertMode addv) 568 { 569 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data; 570 const MatScalar *value; 571 MatScalar *barray = baij->barray; 572 PetscBool roworiented = baij->roworiented, ignore_ltriangular = ((Mat_SeqSBAIJ *)baij->A->data)->ignore_ltriangular; 573 PetscInt i, j, ii, jj, row, col, rstart = baij->rstartbs; 574 PetscInt rend = baij->rendbs, cstart = baij->cstartbs, stepval; 575 PetscInt cend = baij->cendbs, bs = mat->rmap->bs, bs2 = baij->bs2; 576 577 PetscFunctionBegin; 578 if (!barray) { 579 PetscCall(PetscMalloc1(bs2, &barray)); 580 baij->barray = barray; 581 } 582 583 if (roworiented) { 584 stepval = (n - 1) * bs; 585 } else { 586 stepval = (m - 1) * bs; 587 } 588 for (i = 0; i < m; i++) { 589 if (im[i] < 0) continue; 590 PetscCheck(im[i] < baij->Mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block indexed row too large %" PetscInt_FMT " max %" PetscInt_FMT, im[i], baij->Mbs - 1); 591 if (im[i] >= rstart && im[i] < rend) { 592 row = im[i] - rstart; 593 for (j = 0; j < n; j++) { 594 if (im[i] > in[j]) { 595 if (ignore_ltriangular) continue; /* ignore lower triangular blocks */ 596 else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_USER, "Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)"); 597 } 598 /* If NumCol = 1 then a copy is not required */ 599 if ((roworiented) && (n == 1)) { 600 barray = (MatScalar *)v + i * bs2; 601 } else if ((!roworiented) && (m == 1)) { 602 barray = (MatScalar *)v + j * bs2; 603 } else { /* Here a copy is required */ 604 if (roworiented) { 605 value = v + i * (stepval + bs) * bs + j * bs; 606 } else { 607 value = v + j * (stepval + bs) * bs + i * bs; 608 } 609 for (ii = 0; ii < bs; ii++, value += stepval) { 610 for (jj = 0; jj < bs; jj++) *barray++ = *value++; 611 } 612 barray -= bs2; 613 } 614 615 if (in[j] >= cstart && in[j] < cend) { 616 col = in[j] - cstart; 617 PetscCall(MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A, row, col, barray, addv, im[i], in[j])); 618 } else if (in[j] < 0) { 619 continue; 620 } else { 621 PetscCheck(in[j] < baij->Nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block indexed column too large %" PetscInt_FMT " max %" PetscInt_FMT, in[j], baij->Nbs - 1); 622 if (mat->was_assembled) { 623 if (!baij->colmap) PetscCall(MatCreateColmap_MPIBAIJ_Private(mat)); 624 625 #if defined(PETSC_USE_DEBUG) 626 #if defined(PETSC_USE_CTABLE) 627 { 628 PetscInt data; 629 PetscCall(PetscHMapIGetWithDefault(baij->colmap, in[j] + 1, 0, &data)); 630 PetscCheck((data - 1) % bs == 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Incorrect colmap"); 631 } 632 #else 633 PetscCheck((baij->colmap[in[j]] - 1) % bs == 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Incorrect colmap"); 634 #endif 635 #endif 636 #if defined(PETSC_USE_CTABLE) 637 PetscCall(PetscHMapIGetWithDefault(baij->colmap, in[j] + 1, 0, &col)); 638 col = (col - 1) / bs; 639 #else 640 col = (baij->colmap[in[j]] - 1) / bs; 641 #endif 642 if (col < 0 && !((Mat_SeqBAIJ *)(baij->A->data))->nonew) { 643 PetscCall(MatDisAssemble_MPISBAIJ(mat)); 644 col = in[j]; 645 } 646 } else col = in[j]; 647 PetscCall(MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B, row, col, barray, addv, im[i], in[j])); 648 } 649 } 650 } else { 651 PetscCheck(!mat->nooffprocentries, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Setting off process block indexed row %" PetscInt_FMT " even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set", im[i]); 652 if (!baij->donotstash) { 653 if (roworiented) { 654 PetscCall(MatStashValuesRowBlocked_Private(&mat->bstash, im[i], n, in, v, m, n, i)); 655 } else { 656 PetscCall(MatStashValuesColBlocked_Private(&mat->bstash, im[i], n, in, v, m, n, i)); 657 } 658 } 659 } 660 } 661 PetscFunctionReturn(PETSC_SUCCESS); 662 } 663 664 static PetscErrorCode MatGetValues_MPISBAIJ(Mat mat, PetscInt m, const PetscInt idxm[], PetscInt n, const PetscInt idxn[], PetscScalar v[]) 665 { 666 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data; 667 PetscInt bs = mat->rmap->bs, i, j, bsrstart = mat->rmap->rstart, bsrend = mat->rmap->rend; 668 PetscInt bscstart = mat->cmap->rstart, bscend = mat->cmap->rend, row, col, data; 669 670 PetscFunctionBegin; 671 for (i = 0; i < m; i++) { 672 if (idxm[i] < 0) continue; /* negative row */ 673 PetscCheck(idxm[i] < mat->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, idxm[i], mat->rmap->N - 1); 674 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 675 row = idxm[i] - bsrstart; 676 for (j = 0; j < n; j++) { 677 if (idxn[j] < 0) continue; /* negative column */ 678 PetscCheck(idxn[j] < mat->cmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, idxn[j], mat->cmap->N - 1); 679 if (idxn[j] >= bscstart && idxn[j] < bscend) { 680 col = idxn[j] - bscstart; 681 PetscCall(MatGetValues_SeqSBAIJ(baij->A, 1, &row, 1, &col, v + i * n + j)); 682 } else { 683 if (!baij->colmap) PetscCall(MatCreateColmap_MPIBAIJ_Private(mat)); 684 #if defined(PETSC_USE_CTABLE) 685 PetscCall(PetscHMapIGetWithDefault(baij->colmap, idxn[j] / bs + 1, 0, &data)); 686 data--; 687 #else 688 data = baij->colmap[idxn[j] / bs] - 1; 689 #endif 690 if ((data < 0) || (baij->garray[data / bs] != idxn[j] / bs)) *(v + i * n + j) = 0.0; 691 else { 692 col = data + idxn[j] % bs; 693 PetscCall(MatGetValues_SeqBAIJ(baij->B, 1, &row, 1, &col, v + i * n + j)); 694 } 695 } 696 } 697 } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Only local values currently supported"); 698 } 699 PetscFunctionReturn(PETSC_SUCCESS); 700 } 701 702 static PetscErrorCode MatNorm_MPISBAIJ(Mat mat, NormType type, PetscReal *norm) 703 { 704 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data; 705 PetscReal sum[2], *lnorm2; 706 707 PetscFunctionBegin; 708 if (baij->size == 1) { 709 PetscCall(MatNorm(baij->A, type, norm)); 710 } else { 711 if (type == NORM_FROBENIUS) { 712 PetscCall(PetscMalloc1(2, &lnorm2)); 713 PetscCall(MatNorm(baij->A, type, lnorm2)); 714 *lnorm2 = (*lnorm2) * (*lnorm2); 715 lnorm2++; /* squar power of norm(A) */ 716 PetscCall(MatNorm(baij->B, type, lnorm2)); 717 *lnorm2 = (*lnorm2) * (*lnorm2); 718 lnorm2--; /* squar power of norm(B) */ 719 PetscCall(MPIU_Allreduce(lnorm2, sum, 2, MPIU_REAL, MPIU_SUM, PetscObjectComm((PetscObject)mat))); 720 *norm = PetscSqrtReal(sum[0] + 2 * sum[1]); 721 PetscCall(PetscFree(lnorm2)); 722 } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */ 723 Mat_SeqSBAIJ *amat = (Mat_SeqSBAIJ *)baij->A->data; 724 Mat_SeqBAIJ *bmat = (Mat_SeqBAIJ *)baij->B->data; 725 PetscReal *rsum, *rsum2, vabs; 726 PetscInt *jj, *garray = baij->garray, rstart = baij->rstartbs, nz; 727 PetscInt brow, bcol, col, bs = baij->A->rmap->bs, row, grow, gcol, mbs = amat->mbs; 728 MatScalar *v; 729 730 PetscCall(PetscMalloc2(mat->cmap->N, &rsum, mat->cmap->N, &rsum2)); 731 PetscCall(PetscArrayzero(rsum, mat->cmap->N)); 732 /* Amat */ 733 v = amat->a; 734 jj = amat->j; 735 for (brow = 0; brow < mbs; brow++) { 736 grow = bs * (rstart + brow); 737 nz = amat->i[brow + 1] - amat->i[brow]; 738 for (bcol = 0; bcol < nz; bcol++) { 739 gcol = bs * (rstart + *jj); 740 jj++; 741 for (col = 0; col < bs; col++) { 742 for (row = 0; row < bs; row++) { 743 vabs = PetscAbsScalar(*v); 744 v++; 745 rsum[gcol + col] += vabs; 746 /* non-diagonal block */ 747 if (bcol > 0 && vabs > 0.0) rsum[grow + row] += vabs; 748 } 749 } 750 } 751 PetscCall(PetscLogFlops(nz * bs * bs)); 752 } 753 /* Bmat */ 754 v = bmat->a; 755 jj = bmat->j; 756 for (brow = 0; brow < mbs; brow++) { 757 grow = bs * (rstart + brow); 758 nz = bmat->i[brow + 1] - bmat->i[brow]; 759 for (bcol = 0; bcol < nz; bcol++) { 760 gcol = bs * garray[*jj]; 761 jj++; 762 for (col = 0; col < bs; col++) { 763 for (row = 0; row < bs; row++) { 764 vabs = PetscAbsScalar(*v); 765 v++; 766 rsum[gcol + col] += vabs; 767 rsum[grow + row] += vabs; 768 } 769 } 770 } 771 PetscCall(PetscLogFlops(nz * bs * bs)); 772 } 773 PetscCall(MPIU_Allreduce(rsum, rsum2, mat->cmap->N, MPIU_REAL, MPIU_SUM, PetscObjectComm((PetscObject)mat))); 774 *norm = 0.0; 775 for (col = 0; col < mat->cmap->N; col++) { 776 if (rsum2[col] > *norm) *norm = rsum2[col]; 777 } 778 PetscCall(PetscFree2(rsum, rsum2)); 779 } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "No support for this norm yet"); 780 } 781 PetscFunctionReturn(PETSC_SUCCESS); 782 } 783 784 static PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat, MatAssemblyType mode) 785 { 786 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data; 787 PetscInt nstash, reallocs; 788 789 PetscFunctionBegin; 790 if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(PETSC_SUCCESS); 791 792 PetscCall(MatStashScatterBegin_Private(mat, &mat->stash, mat->rmap->range)); 793 PetscCall(MatStashScatterBegin_Private(mat, &mat->bstash, baij->rangebs)); 794 PetscCall(MatStashGetInfo_Private(&mat->stash, &nstash, &reallocs)); 795 PetscCall(PetscInfo(mat, "Stash has %" PetscInt_FMT " entries,uses %" PetscInt_FMT " mallocs.\n", nstash, reallocs)); 796 PetscCall(MatStashGetInfo_Private(&mat->stash, &nstash, &reallocs)); 797 PetscCall(PetscInfo(mat, "Block-Stash has %" PetscInt_FMT " entries, uses %" PetscInt_FMT " mallocs.\n", nstash, reallocs)); 798 PetscFunctionReturn(PETSC_SUCCESS); 799 } 800 801 static PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat, MatAssemblyType mode) 802 { 803 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data; 804 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)baij->A->data; 805 PetscInt i, j, rstart, ncols, flg, bs2 = baij->bs2; 806 PetscInt *row, *col; 807 PetscBool other_disassembled; 808 PetscMPIInt n; 809 PetscBool r1, r2, r3; 810 MatScalar *val; 811 812 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 813 PetscFunctionBegin; 814 if (!baij->donotstash && !mat->nooffprocentries) { 815 while (1) { 816 PetscCall(MatStashScatterGetMesg_Private(&mat->stash, &n, &row, &col, &val, &flg)); 817 if (!flg) break; 818 819 for (i = 0; i < n;) { 820 /* Now identify the consecutive vals belonging to the same row */ 821 for (j = i, rstart = row[j]; j < n; j++) { 822 if (row[j] != rstart) break; 823 } 824 if (j < n) ncols = j - i; 825 else ncols = n - i; 826 /* Now assemble all these values with a single function call */ 827 PetscCall(MatSetValues_MPISBAIJ(mat, 1, row + i, ncols, col + i, val + i, mat->insertmode)); 828 i = j; 829 } 830 } 831 PetscCall(MatStashScatterEnd_Private(&mat->stash)); 832 /* Now process the block-stash. Since the values are stashed column-oriented, 833 set the roworiented flag to column oriented, and after MatSetValues() 834 restore the original flags */ 835 r1 = baij->roworiented; 836 r2 = a->roworiented; 837 r3 = ((Mat_SeqBAIJ *)baij->B->data)->roworiented; 838 839 baij->roworiented = PETSC_FALSE; 840 a->roworiented = PETSC_FALSE; 841 842 ((Mat_SeqBAIJ *)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */ 843 while (1) { 844 PetscCall(MatStashScatterGetMesg_Private(&mat->bstash, &n, &row, &col, &val, &flg)); 845 if (!flg) break; 846 847 for (i = 0; i < n;) { 848 /* Now identify the consecutive vals belonging to the same row */ 849 for (j = i, rstart = row[j]; j < n; j++) { 850 if (row[j] != rstart) break; 851 } 852 if (j < n) ncols = j - i; 853 else ncols = n - i; 854 PetscCall(MatSetValuesBlocked_MPISBAIJ(mat, 1, row + i, ncols, col + i, val + i * bs2, mat->insertmode)); 855 i = j; 856 } 857 } 858 PetscCall(MatStashScatterEnd_Private(&mat->bstash)); 859 860 baij->roworiented = r1; 861 a->roworiented = r2; 862 863 ((Mat_SeqBAIJ *)baij->B->data)->roworiented = r3; /* b->roworinted */ 864 } 865 866 PetscCall(MatAssemblyBegin(baij->A, mode)); 867 PetscCall(MatAssemblyEnd(baij->A, mode)); 868 869 /* determine if any processor has disassembled, if so we must 870 also disassemble ourselves, in order that we may reassemble. */ 871 /* 872 if nonzero structure of submatrix B cannot change then we know that 873 no processor disassembled thus we can skip this stuff 874 */ 875 if (!((Mat_SeqBAIJ *)baij->B->data)->nonew) { 876 PetscCall(MPIU_Allreduce(&mat->was_assembled, &other_disassembled, 1, MPIU_BOOL, MPI_LAND, PetscObjectComm((PetscObject)mat))); 877 if (mat->was_assembled && !other_disassembled) PetscCall(MatDisAssemble_MPISBAIJ(mat)); 878 } 879 880 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { PetscCall(MatSetUpMultiply_MPISBAIJ(mat)); /* setup Mvctx and sMvctx */ } 881 PetscCall(MatAssemblyBegin(baij->B, mode)); 882 PetscCall(MatAssemblyEnd(baij->B, mode)); 883 884 PetscCall(PetscFree2(baij->rowvalues, baij->rowindices)); 885 886 baij->rowvalues = NULL; 887 888 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 889 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ *)(baij->A->data))->nonew) { 890 PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate; 891 PetscCall(MPIU_Allreduce(&state, &mat->nonzerostate, 1, MPIU_INT64, MPI_SUM, PetscObjectComm((PetscObject)mat))); 892 } 893 PetscFunctionReturn(PETSC_SUCCESS); 894 } 895 896 extern PetscErrorCode MatSetValues_MPIBAIJ(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], const PetscScalar[], InsertMode); 897 #include <petscdraw.h> 898 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat, PetscViewer viewer) 899 { 900 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data; 901 PetscInt bs = mat->rmap->bs; 902 PetscMPIInt rank = baij->rank; 903 PetscBool iascii, isdraw; 904 PetscViewer sviewer; 905 PetscViewerFormat format; 906 907 PetscFunctionBegin; 908 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii)); 909 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw)); 910 if (iascii) { 911 PetscCall(PetscViewerGetFormat(viewer, &format)); 912 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 913 MatInfo info; 914 PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)mat), &rank)); 915 PetscCall(MatGetInfo(mat, MAT_LOCAL, &info)); 916 PetscCall(PetscViewerASCIIPushSynchronized(viewer)); 917 PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] Local rows %" PetscInt_FMT " nz %" PetscInt_FMT " nz alloced %" PetscInt_FMT " bs %" PetscInt_FMT " mem %g\n", rank, mat->rmap->n, (PetscInt)info.nz_used, (PetscInt)info.nz_allocated, 918 mat->rmap->bs, (double)info.memory)); 919 PetscCall(MatGetInfo(baij->A, MAT_LOCAL, &info)); 920 PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] on-diagonal part: nz %" PetscInt_FMT " \n", rank, (PetscInt)info.nz_used)); 921 PetscCall(MatGetInfo(baij->B, MAT_LOCAL, &info)); 922 PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] off-diagonal part: nz %" PetscInt_FMT " \n", rank, (PetscInt)info.nz_used)); 923 PetscCall(PetscViewerFlush(viewer)); 924 PetscCall(PetscViewerASCIIPopSynchronized(viewer)); 925 PetscCall(PetscViewerASCIIPrintf(viewer, "Information on VecScatter used in matrix-vector product: \n")); 926 PetscCall(VecScatterView(baij->Mvctx, viewer)); 927 PetscFunctionReturn(PETSC_SUCCESS); 928 } else if (format == PETSC_VIEWER_ASCII_INFO) { 929 PetscCall(PetscViewerASCIIPrintf(viewer, " block size is %" PetscInt_FMT "\n", bs)); 930 PetscFunctionReturn(PETSC_SUCCESS); 931 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 932 PetscFunctionReturn(PETSC_SUCCESS); 933 } 934 } 935 936 if (isdraw) { 937 PetscDraw draw; 938 PetscBool isnull; 939 PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw)); 940 PetscCall(PetscDrawIsNull(draw, &isnull)); 941 if (isnull) PetscFunctionReturn(PETSC_SUCCESS); 942 } 943 944 { 945 /* assemble the entire matrix onto first processor. */ 946 Mat A; 947 Mat_SeqSBAIJ *Aloc; 948 Mat_SeqBAIJ *Bloc; 949 PetscInt M = mat->rmap->N, N = mat->cmap->N, *ai, *aj, col, i, j, k, *rvals, mbs = baij->mbs; 950 MatScalar *a; 951 const char *matname; 952 953 /* Should this be the same type as mat? */ 954 PetscCall(MatCreate(PetscObjectComm((PetscObject)mat), &A)); 955 if (rank == 0) { 956 PetscCall(MatSetSizes(A, M, N, M, N)); 957 } else { 958 PetscCall(MatSetSizes(A, 0, 0, M, N)); 959 } 960 PetscCall(MatSetType(A, MATMPISBAIJ)); 961 PetscCall(MatMPISBAIJSetPreallocation(A, mat->rmap->bs, 0, NULL, 0, NULL)); 962 PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_FALSE)); 963 964 /* copy over the A part */ 965 Aloc = (Mat_SeqSBAIJ *)baij->A->data; 966 ai = Aloc->i; 967 aj = Aloc->j; 968 a = Aloc->a; 969 PetscCall(PetscMalloc1(bs, &rvals)); 970 971 for (i = 0; i < mbs; i++) { 972 rvals[0] = bs * (baij->rstartbs + i); 973 for (j = 1; j < bs; j++) rvals[j] = rvals[j - 1] + 1; 974 for (j = ai[i]; j < ai[i + 1]; j++) { 975 col = (baij->cstartbs + aj[j]) * bs; 976 for (k = 0; k < bs; k++) { 977 PetscCall(MatSetValues_MPISBAIJ(A, bs, rvals, 1, &col, a, INSERT_VALUES)); 978 col++; 979 a += bs; 980 } 981 } 982 } 983 /* copy over the B part */ 984 Bloc = (Mat_SeqBAIJ *)baij->B->data; 985 ai = Bloc->i; 986 aj = Bloc->j; 987 a = Bloc->a; 988 for (i = 0; i < mbs; i++) { 989 rvals[0] = bs * (baij->rstartbs + i); 990 for (j = 1; j < bs; j++) rvals[j] = rvals[j - 1] + 1; 991 for (j = ai[i]; j < ai[i + 1]; j++) { 992 col = baij->garray[aj[j]] * bs; 993 for (k = 0; k < bs; k++) { 994 PetscCall(MatSetValues_MPIBAIJ(A, bs, rvals, 1, &col, a, INSERT_VALUES)); 995 col++; 996 a += bs; 997 } 998 } 999 } 1000 PetscCall(PetscFree(rvals)); 1001 PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY)); 1002 PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY)); 1003 /* 1004 Everyone has to call to draw the matrix since the graphics waits are 1005 synchronized across all processors that share the PetscDraw object 1006 */ 1007 PetscCall(PetscViewerGetSubViewer(viewer, PETSC_COMM_SELF, &sviewer)); 1008 if (((PetscObject)mat)->name) PetscCall(PetscObjectGetName((PetscObject)mat, &matname)); 1009 if (rank == 0) { 1010 if (((PetscObject)mat)->name) PetscCall(PetscObjectSetName((PetscObject)((Mat_MPISBAIJ *)(A->data))->A, matname)); 1011 PetscCall(MatView_SeqSBAIJ(((Mat_MPISBAIJ *)(A->data))->A, sviewer)); 1012 } 1013 PetscCall(PetscViewerRestoreSubViewer(viewer, PETSC_COMM_SELF, &sviewer)); 1014 PetscCall(PetscViewerFlush(viewer)); 1015 PetscCall(MatDestroy(&A)); 1016 } 1017 PetscFunctionReturn(PETSC_SUCCESS); 1018 } 1019 1020 /* Used for both MPIBAIJ and MPISBAIJ matrices */ 1021 #define MatView_MPISBAIJ_Binary MatView_MPIBAIJ_Binary 1022 1023 static PetscErrorCode MatView_MPISBAIJ(Mat mat, PetscViewer viewer) 1024 { 1025 PetscBool iascii, isdraw, issocket, isbinary; 1026 1027 PetscFunctionBegin; 1028 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii)); 1029 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw)); 1030 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSOCKET, &issocket)); 1031 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary)); 1032 if (iascii || isdraw || issocket) { 1033 PetscCall(MatView_MPISBAIJ_ASCIIorDraworSocket(mat, viewer)); 1034 } else if (isbinary) PetscCall(MatView_MPISBAIJ_Binary(mat, viewer)); 1035 PetscFunctionReturn(PETSC_SUCCESS); 1036 } 1037 1038 PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A, Vec xx, Vec yy) 1039 { 1040 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1041 PetscInt mbs = a->mbs, bs = A->rmap->bs; 1042 PetscScalar *from; 1043 const PetscScalar *x; 1044 1045 PetscFunctionBegin; 1046 /* diagonal part */ 1047 PetscCall((*a->A->ops->mult)(a->A, xx, a->slvec1a)); 1048 /* since a->slvec1b shares memory (dangerously) with a->slec1 changes to a->slec1 will affect it */ 1049 PetscCall(PetscObjectStateIncrease((PetscObject)a->slvec1b)); 1050 PetscCall(VecZeroEntries(a->slvec1b)); 1051 1052 /* subdiagonal part */ 1053 PetscCheck(a->B->ops->multhermitiantranspose, PetscObjectComm((PetscObject)a->B), PETSC_ERR_SUP, "Not for type %s", ((PetscObject)a->B)->type_name); 1054 PetscCall((*a->B->ops->multhermitiantranspose)(a->B, xx, a->slvec0b)); 1055 1056 /* copy x into the vec slvec0 */ 1057 PetscCall(VecGetArray(a->slvec0, &from)); 1058 PetscCall(VecGetArrayRead(xx, &x)); 1059 1060 PetscCall(PetscArraycpy(from, x, bs * mbs)); 1061 PetscCall(VecRestoreArray(a->slvec0, &from)); 1062 PetscCall(VecRestoreArrayRead(xx, &x)); 1063 1064 PetscCall(VecScatterBegin(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD)); 1065 PetscCall(VecScatterEnd(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD)); 1066 /* supperdiagonal part */ 1067 PetscCall((*a->B->ops->multadd)(a->B, a->slvec1b, a->slvec1a, yy)); 1068 PetscFunctionReturn(PETSC_SUCCESS); 1069 } 1070 1071 static PetscErrorCode MatMult_MPISBAIJ(Mat A, Vec xx, Vec yy) 1072 { 1073 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1074 PetscInt mbs = a->mbs, bs = A->rmap->bs; 1075 PetscScalar *from; 1076 const PetscScalar *x; 1077 1078 PetscFunctionBegin; 1079 /* diagonal part */ 1080 PetscCall((*a->A->ops->mult)(a->A, xx, a->slvec1a)); 1081 /* since a->slvec1b shares memory (dangerously) with a->slec1 changes to a->slec1 will affect it */ 1082 PetscCall(PetscObjectStateIncrease((PetscObject)a->slvec1b)); 1083 PetscCall(VecZeroEntries(a->slvec1b)); 1084 1085 /* subdiagonal part */ 1086 PetscCall((*a->B->ops->multtranspose)(a->B, xx, a->slvec0b)); 1087 1088 /* copy x into the vec slvec0 */ 1089 PetscCall(VecGetArray(a->slvec0, &from)); 1090 PetscCall(VecGetArrayRead(xx, &x)); 1091 1092 PetscCall(PetscArraycpy(from, x, bs * mbs)); 1093 PetscCall(VecRestoreArray(a->slvec0, &from)); 1094 PetscCall(VecRestoreArrayRead(xx, &x)); 1095 1096 PetscCall(VecScatterBegin(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD)); 1097 PetscCall(VecScatterEnd(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD)); 1098 /* supperdiagonal part */ 1099 PetscCall((*a->B->ops->multadd)(a->B, a->slvec1b, a->slvec1a, yy)); 1100 PetscFunctionReturn(PETSC_SUCCESS); 1101 } 1102 1103 #if PetscDefined(USE_COMPLEX) 1104 static PetscErrorCode MatMultAdd_MPISBAIJ_Hermitian(Mat A, Vec xx, Vec yy, Vec zz) 1105 { 1106 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1107 PetscInt mbs = a->mbs, bs = A->rmap->bs; 1108 PetscScalar *from; 1109 const PetscScalar *x; 1110 1111 PetscFunctionBegin; 1112 /* diagonal part */ 1113 PetscCall((*a->A->ops->multadd)(a->A, xx, yy, a->slvec1a)); 1114 PetscCall(PetscObjectStateIncrease((PetscObject)a->slvec1b)); 1115 PetscCall(VecZeroEntries(a->slvec1b)); 1116 1117 /* subdiagonal part */ 1118 PetscCheck(a->B->ops->multhermitiantranspose, PetscObjectComm((PetscObject)a->B), PETSC_ERR_SUP, "Not for type %s", ((PetscObject)a->B)->type_name); 1119 PetscCall((*a->B->ops->multhermitiantranspose)(a->B, xx, a->slvec0b)); 1120 1121 /* copy x into the vec slvec0 */ 1122 PetscCall(VecGetArray(a->slvec0, &from)); 1123 PetscCall(VecGetArrayRead(xx, &x)); 1124 PetscCall(PetscArraycpy(from, x, bs * mbs)); 1125 PetscCall(VecRestoreArray(a->slvec0, &from)); 1126 1127 PetscCall(VecScatterBegin(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD)); 1128 PetscCall(VecRestoreArrayRead(xx, &x)); 1129 PetscCall(VecScatterEnd(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD)); 1130 1131 /* supperdiagonal part */ 1132 PetscCall((*a->B->ops->multadd)(a->B, a->slvec1b, a->slvec1a, zz)); 1133 PetscFunctionReturn(PETSC_SUCCESS); 1134 } 1135 #endif 1136 1137 static PetscErrorCode MatMultAdd_MPISBAIJ(Mat A, Vec xx, Vec yy, Vec zz) 1138 { 1139 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1140 PetscInt mbs = a->mbs, bs = A->rmap->bs; 1141 PetscScalar *from; 1142 const PetscScalar *x; 1143 1144 PetscFunctionBegin; 1145 /* diagonal part */ 1146 PetscCall((*a->A->ops->multadd)(a->A, xx, yy, a->slvec1a)); 1147 PetscCall(PetscObjectStateIncrease((PetscObject)a->slvec1b)); 1148 PetscCall(VecZeroEntries(a->slvec1b)); 1149 1150 /* subdiagonal part */ 1151 PetscCall((*a->B->ops->multtranspose)(a->B, xx, a->slvec0b)); 1152 1153 /* copy x into the vec slvec0 */ 1154 PetscCall(VecGetArray(a->slvec0, &from)); 1155 PetscCall(VecGetArrayRead(xx, &x)); 1156 PetscCall(PetscArraycpy(from, x, bs * mbs)); 1157 PetscCall(VecRestoreArray(a->slvec0, &from)); 1158 1159 PetscCall(VecScatterBegin(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD)); 1160 PetscCall(VecRestoreArrayRead(xx, &x)); 1161 PetscCall(VecScatterEnd(a->sMvctx, a->slvec0, a->slvec1, ADD_VALUES, SCATTER_FORWARD)); 1162 1163 /* supperdiagonal part */ 1164 PetscCall((*a->B->ops->multadd)(a->B, a->slvec1b, a->slvec1a, zz)); 1165 PetscFunctionReturn(PETSC_SUCCESS); 1166 } 1167 1168 /* 1169 This only works correctly for square matrices where the subblock A->A is the 1170 diagonal block 1171 */ 1172 static PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A, Vec v) 1173 { 1174 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1175 1176 PetscFunctionBegin; 1177 /* PetscCheck(a->rmap->N == a->cmap->N,PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 1178 PetscCall(MatGetDiagonal(a->A, v)); 1179 PetscFunctionReturn(PETSC_SUCCESS); 1180 } 1181 1182 static PetscErrorCode MatScale_MPISBAIJ(Mat A, PetscScalar aa) 1183 { 1184 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1185 1186 PetscFunctionBegin; 1187 PetscCall(MatScale(a->A, aa)); 1188 PetscCall(MatScale(a->B, aa)); 1189 PetscFunctionReturn(PETSC_SUCCESS); 1190 } 1191 1192 static PetscErrorCode MatGetRow_MPISBAIJ(Mat matin, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v) 1193 { 1194 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ *)matin->data; 1195 PetscScalar *vworkA, *vworkB, **pvA, **pvB, *v_p; 1196 PetscInt bs = matin->rmap->bs, bs2 = mat->bs2, i, *cworkA, *cworkB, **pcA, **pcB; 1197 PetscInt nztot, nzA, nzB, lrow, brstart = matin->rmap->rstart, brend = matin->rmap->rend; 1198 PetscInt *cmap, *idx_p, cstart = mat->rstartbs; 1199 1200 PetscFunctionBegin; 1201 PetscCheck(!mat->getrowactive, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Already active"); 1202 mat->getrowactive = PETSC_TRUE; 1203 1204 if (!mat->rowvalues && (idx || v)) { 1205 /* 1206 allocate enough space to hold information from the longest row. 1207 */ 1208 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ *)mat->A->data; 1209 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ *)mat->B->data; 1210 PetscInt max = 1, mbs = mat->mbs, tmp; 1211 for (i = 0; i < mbs; i++) { 1212 tmp = Aa->i[i + 1] - Aa->i[i] + Ba->i[i + 1] - Ba->i[i]; /* row length */ 1213 if (max < tmp) max = tmp; 1214 } 1215 PetscCall(PetscMalloc2(max * bs2, &mat->rowvalues, max * bs2, &mat->rowindices)); 1216 } 1217 1218 PetscCheck(row >= brstart && row < brend, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only local rows"); 1219 lrow = row - brstart; /* local row index */ 1220 1221 pvA = &vworkA; 1222 pcA = &cworkA; 1223 pvB = &vworkB; 1224 pcB = &cworkB; 1225 if (!v) { 1226 pvA = NULL; 1227 pvB = NULL; 1228 } 1229 if (!idx) { 1230 pcA = NULL; 1231 if (!v) pcB = NULL; 1232 } 1233 PetscCall((*mat->A->ops->getrow)(mat->A, lrow, &nzA, pcA, pvA)); 1234 PetscCall((*mat->B->ops->getrow)(mat->B, lrow, &nzB, pcB, pvB)); 1235 nztot = nzA + nzB; 1236 1237 cmap = mat->garray; 1238 if (v || idx) { 1239 if (nztot) { 1240 /* Sort by increasing column numbers, assuming A and B already sorted */ 1241 PetscInt imark = -1; 1242 if (v) { 1243 *v = v_p = mat->rowvalues; 1244 for (i = 0; i < nzB; i++) { 1245 if (cmap[cworkB[i] / bs] < cstart) v_p[i] = vworkB[i]; 1246 else break; 1247 } 1248 imark = i; 1249 for (i = 0; i < nzA; i++) v_p[imark + i] = vworkA[i]; 1250 for (i = imark; i < nzB; i++) v_p[nzA + i] = vworkB[i]; 1251 } 1252 if (idx) { 1253 *idx = idx_p = mat->rowindices; 1254 if (imark > -1) { 1255 for (i = 0; i < imark; i++) idx_p[i] = cmap[cworkB[i] / bs] * bs + cworkB[i] % bs; 1256 } else { 1257 for (i = 0; i < nzB; i++) { 1258 if (cmap[cworkB[i] / bs] < cstart) idx_p[i] = cmap[cworkB[i] / bs] * bs + cworkB[i] % bs; 1259 else break; 1260 } 1261 imark = i; 1262 } 1263 for (i = 0; i < nzA; i++) idx_p[imark + i] = cstart * bs + cworkA[i]; 1264 for (i = imark; i < nzB; i++) idx_p[nzA + i] = cmap[cworkB[i] / bs] * bs + cworkB[i] % bs; 1265 } 1266 } else { 1267 if (idx) *idx = NULL; 1268 if (v) *v = NULL; 1269 } 1270 } 1271 *nz = nztot; 1272 PetscCall((*mat->A->ops->restorerow)(mat->A, lrow, &nzA, pcA, pvA)); 1273 PetscCall((*mat->B->ops->restorerow)(mat->B, lrow, &nzB, pcB, pvB)); 1274 PetscFunctionReturn(PETSC_SUCCESS); 1275 } 1276 1277 static PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v) 1278 { 1279 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data; 1280 1281 PetscFunctionBegin; 1282 PetscCheck(baij->getrowactive, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "MatGetRow() must be called first"); 1283 baij->getrowactive = PETSC_FALSE; 1284 PetscFunctionReturn(PETSC_SUCCESS); 1285 } 1286 1287 static PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A) 1288 { 1289 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1290 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ *)a->A->data; 1291 1292 PetscFunctionBegin; 1293 aA->getrow_utriangular = PETSC_TRUE; 1294 PetscFunctionReturn(PETSC_SUCCESS); 1295 } 1296 static PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A) 1297 { 1298 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1299 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ *)a->A->data; 1300 1301 PetscFunctionBegin; 1302 aA->getrow_utriangular = PETSC_FALSE; 1303 PetscFunctionReturn(PETSC_SUCCESS); 1304 } 1305 1306 static PetscErrorCode MatConjugate_MPISBAIJ(Mat mat) 1307 { 1308 PetscFunctionBegin; 1309 if (PetscDefined(USE_COMPLEX)) { 1310 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)mat->data; 1311 1312 PetscCall(MatConjugate(a->A)); 1313 PetscCall(MatConjugate(a->B)); 1314 } 1315 PetscFunctionReturn(PETSC_SUCCESS); 1316 } 1317 1318 static PetscErrorCode MatRealPart_MPISBAIJ(Mat A) 1319 { 1320 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1321 1322 PetscFunctionBegin; 1323 PetscCall(MatRealPart(a->A)); 1324 PetscCall(MatRealPart(a->B)); 1325 PetscFunctionReturn(PETSC_SUCCESS); 1326 } 1327 1328 static PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A) 1329 { 1330 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1331 1332 PetscFunctionBegin; 1333 PetscCall(MatImaginaryPart(a->A)); 1334 PetscCall(MatImaginaryPart(a->B)); 1335 PetscFunctionReturn(PETSC_SUCCESS); 1336 } 1337 1338 /* Check if isrow is a subset of iscol_local, called by MatCreateSubMatrix_MPISBAIJ() 1339 Input: isrow - distributed(parallel), 1340 iscol_local - locally owned (seq) 1341 */ 1342 static PetscErrorCode ISEqual_private(IS isrow, IS iscol_local, PetscBool *flg) 1343 { 1344 PetscInt sz1, sz2, *a1, *a2, i, j, k, nmatch; 1345 const PetscInt *ptr1, *ptr2; 1346 1347 PetscFunctionBegin; 1348 *flg = PETSC_FALSE; 1349 PetscCall(ISGetLocalSize(isrow, &sz1)); 1350 PetscCall(ISGetLocalSize(iscol_local, &sz2)); 1351 if (sz1 > sz2) PetscFunctionReturn(PETSC_SUCCESS); 1352 1353 PetscCall(ISGetIndices(isrow, &ptr1)); 1354 PetscCall(ISGetIndices(iscol_local, &ptr2)); 1355 1356 PetscCall(PetscMalloc1(sz1, &a1)); 1357 PetscCall(PetscMalloc1(sz2, &a2)); 1358 PetscCall(PetscArraycpy(a1, ptr1, sz1)); 1359 PetscCall(PetscArraycpy(a2, ptr2, sz2)); 1360 PetscCall(PetscSortInt(sz1, a1)); 1361 PetscCall(PetscSortInt(sz2, a2)); 1362 1363 nmatch = 0; 1364 k = 0; 1365 for (i = 0; i < sz1; i++) { 1366 for (j = k; j < sz2; j++) { 1367 if (a1[i] == a2[j]) { 1368 k = j; 1369 nmatch++; 1370 break; 1371 } 1372 } 1373 } 1374 PetscCall(ISRestoreIndices(isrow, &ptr1)); 1375 PetscCall(ISRestoreIndices(iscol_local, &ptr2)); 1376 PetscCall(PetscFree(a1)); 1377 PetscCall(PetscFree(a2)); 1378 if (nmatch < sz1) { 1379 *flg = PETSC_FALSE; 1380 } else { 1381 *flg = PETSC_TRUE; 1382 } 1383 PetscFunctionReturn(PETSC_SUCCESS); 1384 } 1385 1386 static PetscErrorCode MatCreateSubMatrix_MPISBAIJ(Mat mat, IS isrow, IS iscol, MatReuse call, Mat *newmat) 1387 { 1388 IS iscol_local; 1389 PetscInt csize; 1390 1391 PetscFunctionBegin; 1392 PetscCall(ISGetLocalSize(iscol, &csize)); 1393 if (call == MAT_REUSE_MATRIX) { 1394 PetscCall(PetscObjectQuery((PetscObject)*newmat, "ISAllGather", (PetscObject *)&iscol_local)); 1395 PetscCheck(iscol_local, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Submatrix passed in was not used before, cannot reuse"); 1396 } else { 1397 PetscBool issorted, isequal; 1398 1399 PetscCall(ISAllGather(iscol, &iscol_local)); 1400 PetscCall(ISEqual_private(isrow, iscol_local, &isequal)); 1401 PetscCall(ISSorted(iscol_local, &issorted)); 1402 PetscCheck(isequal && issorted, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "For symmetric format, iscol must equal isrow and be sorted"); 1403 } 1404 1405 /* now call MatCreateSubMatrix_MPIBAIJ() */ 1406 PetscCall(MatCreateSubMatrix_MPIBAIJ_Private(mat, isrow, iscol_local, csize, call, newmat)); 1407 if (call == MAT_INITIAL_MATRIX) { 1408 PetscCall(PetscObjectCompose((PetscObject)*newmat, "ISAllGather", (PetscObject)iscol_local)); 1409 PetscCall(ISDestroy(&iscol_local)); 1410 } 1411 PetscFunctionReturn(PETSC_SUCCESS); 1412 } 1413 1414 static PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A) 1415 { 1416 Mat_MPISBAIJ *l = (Mat_MPISBAIJ *)A->data; 1417 1418 PetscFunctionBegin; 1419 PetscCall(MatZeroEntries(l->A)); 1420 PetscCall(MatZeroEntries(l->B)); 1421 PetscFunctionReturn(PETSC_SUCCESS); 1422 } 1423 1424 static PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin, MatInfoType flag, MatInfo *info) 1425 { 1426 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)matin->data; 1427 Mat A = a->A, B = a->B; 1428 PetscLogDouble isend[5], irecv[5]; 1429 1430 PetscFunctionBegin; 1431 info->block_size = (PetscReal)matin->rmap->bs; 1432 1433 PetscCall(MatGetInfo(A, MAT_LOCAL, info)); 1434 1435 isend[0] = info->nz_used; 1436 isend[1] = info->nz_allocated; 1437 isend[2] = info->nz_unneeded; 1438 isend[3] = info->memory; 1439 isend[4] = info->mallocs; 1440 1441 PetscCall(MatGetInfo(B, MAT_LOCAL, info)); 1442 1443 isend[0] += info->nz_used; 1444 isend[1] += info->nz_allocated; 1445 isend[2] += info->nz_unneeded; 1446 isend[3] += info->memory; 1447 isend[4] += info->mallocs; 1448 if (flag == MAT_LOCAL) { 1449 info->nz_used = isend[0]; 1450 info->nz_allocated = isend[1]; 1451 info->nz_unneeded = isend[2]; 1452 info->memory = isend[3]; 1453 info->mallocs = isend[4]; 1454 } else if (flag == MAT_GLOBAL_MAX) { 1455 PetscCall(MPIU_Allreduce(isend, irecv, 5, MPIU_PETSCLOGDOUBLE, MPI_MAX, PetscObjectComm((PetscObject)matin))); 1456 1457 info->nz_used = irecv[0]; 1458 info->nz_allocated = irecv[1]; 1459 info->nz_unneeded = irecv[2]; 1460 info->memory = irecv[3]; 1461 info->mallocs = irecv[4]; 1462 } else if (flag == MAT_GLOBAL_SUM) { 1463 PetscCall(MPIU_Allreduce(isend, irecv, 5, MPIU_PETSCLOGDOUBLE, MPI_SUM, PetscObjectComm((PetscObject)matin))); 1464 1465 info->nz_used = irecv[0]; 1466 info->nz_allocated = irecv[1]; 1467 info->nz_unneeded = irecv[2]; 1468 info->memory = irecv[3]; 1469 info->mallocs = irecv[4]; 1470 } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Unknown MatInfoType argument %d", (int)flag); 1471 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1472 info->fill_ratio_needed = 0; 1473 info->factor_mallocs = 0; 1474 PetscFunctionReturn(PETSC_SUCCESS); 1475 } 1476 1477 static PetscErrorCode MatSetOption_MPISBAIJ(Mat A, MatOption op, PetscBool flg) 1478 { 1479 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1480 Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ *)a->A->data; 1481 1482 PetscFunctionBegin; 1483 switch (op) { 1484 case MAT_NEW_NONZERO_LOCATIONS: 1485 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1486 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1487 case MAT_KEEP_NONZERO_PATTERN: 1488 case MAT_SUBMAT_SINGLEIS: 1489 case MAT_NEW_NONZERO_LOCATION_ERR: 1490 MatCheckPreallocated(A, 1); 1491 PetscCall(MatSetOption(a->A, op, flg)); 1492 PetscCall(MatSetOption(a->B, op, flg)); 1493 break; 1494 case MAT_ROW_ORIENTED: 1495 MatCheckPreallocated(A, 1); 1496 a->roworiented = flg; 1497 1498 PetscCall(MatSetOption(a->A, op, flg)); 1499 PetscCall(MatSetOption(a->B, op, flg)); 1500 break; 1501 case MAT_FORCE_DIAGONAL_ENTRIES: 1502 case MAT_SORTED_FULL: 1503 PetscCall(PetscInfo(A, "Option %s ignored\n", MatOptions[op])); 1504 break; 1505 case MAT_IGNORE_OFF_PROC_ENTRIES: 1506 a->donotstash = flg; 1507 break; 1508 case MAT_USE_HASH_TABLE: 1509 a->ht_flag = flg; 1510 break; 1511 case MAT_HERMITIAN: 1512 MatCheckPreallocated(A, 1); 1513 PetscCall(MatSetOption(a->A, op, flg)); 1514 #if defined(PETSC_USE_COMPLEX) 1515 if (flg) { /* need different mat-vec ops */ 1516 A->ops->mult = MatMult_MPISBAIJ_Hermitian; 1517 A->ops->multadd = MatMultAdd_MPISBAIJ_Hermitian; 1518 A->ops->multtranspose = NULL; 1519 A->ops->multtransposeadd = NULL; 1520 A->symmetric = PETSC_BOOL3_FALSE; 1521 } 1522 #endif 1523 break; 1524 case MAT_SPD: 1525 case MAT_SYMMETRIC: 1526 MatCheckPreallocated(A, 1); 1527 PetscCall(MatSetOption(a->A, op, flg)); 1528 #if defined(PETSC_USE_COMPLEX) 1529 if (flg) { /* restore to use default mat-vec ops */ 1530 A->ops->mult = MatMult_MPISBAIJ; 1531 A->ops->multadd = MatMultAdd_MPISBAIJ; 1532 A->ops->multtranspose = MatMult_MPISBAIJ; 1533 A->ops->multtransposeadd = MatMultAdd_MPISBAIJ; 1534 } 1535 #endif 1536 break; 1537 case MAT_STRUCTURALLY_SYMMETRIC: 1538 MatCheckPreallocated(A, 1); 1539 PetscCall(MatSetOption(a->A, op, flg)); 1540 break; 1541 case MAT_SYMMETRY_ETERNAL: 1542 case MAT_STRUCTURAL_SYMMETRY_ETERNAL: 1543 PetscCheck(flg, PETSC_COMM_SELF, PETSC_ERR_SUP, "Matrix must be symmetric"); 1544 PetscCall(PetscInfo(A, "Option %s ignored\n", MatOptions[op])); 1545 break; 1546 case MAT_SPD_ETERNAL: 1547 break; 1548 case MAT_IGNORE_LOWER_TRIANGULAR: 1549 aA->ignore_ltriangular = flg; 1550 break; 1551 case MAT_ERROR_LOWER_TRIANGULAR: 1552 aA->ignore_ltriangular = flg; 1553 break; 1554 case MAT_GETROW_UPPERTRIANGULAR: 1555 aA->getrow_utriangular = flg; 1556 break; 1557 default: 1558 SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "unknown option %d", op); 1559 } 1560 PetscFunctionReturn(PETSC_SUCCESS); 1561 } 1562 1563 static PetscErrorCode MatTranspose_MPISBAIJ(Mat A, MatReuse reuse, Mat *B) 1564 { 1565 PetscFunctionBegin; 1566 if (reuse == MAT_REUSE_MATRIX) PetscCall(MatTransposeCheckNonzeroState_Private(A, *B)); 1567 if (reuse == MAT_INITIAL_MATRIX) { 1568 PetscCall(MatDuplicate(A, MAT_COPY_VALUES, B)); 1569 } else if (reuse == MAT_REUSE_MATRIX) { 1570 PetscCall(MatCopy(A, *B, SAME_NONZERO_PATTERN)); 1571 } 1572 PetscFunctionReturn(PETSC_SUCCESS); 1573 } 1574 1575 static PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat, Vec ll, Vec rr) 1576 { 1577 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ *)mat->data; 1578 Mat a = baij->A, b = baij->B; 1579 PetscInt nv, m, n; 1580 PetscBool flg; 1581 1582 PetscFunctionBegin; 1583 if (ll != rr) { 1584 PetscCall(VecEqual(ll, rr, &flg)); 1585 PetscCheck(flg, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "For symmetric format, left and right scaling vectors must be same"); 1586 } 1587 if (!ll) PetscFunctionReturn(PETSC_SUCCESS); 1588 1589 PetscCall(MatGetLocalSize(mat, &m, &n)); 1590 PetscCheck(m == n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "For symmetric format, local size %" PetscInt_FMT " %" PetscInt_FMT " must be same", m, n); 1591 1592 PetscCall(VecGetLocalSize(rr, &nv)); 1593 PetscCheck(nv == n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Left and right vector non-conforming local size"); 1594 1595 PetscCall(VecScatterBegin(baij->Mvctx, rr, baij->lvec, INSERT_VALUES, SCATTER_FORWARD)); 1596 1597 /* left diagonalscale the off-diagonal part */ 1598 PetscUseTypeMethod(b, diagonalscale, ll, NULL); 1599 1600 /* scale the diagonal part */ 1601 PetscUseTypeMethod(a, diagonalscale, ll, rr); 1602 1603 /* right diagonalscale the off-diagonal part */ 1604 PetscCall(VecScatterEnd(baij->Mvctx, rr, baij->lvec, INSERT_VALUES, SCATTER_FORWARD)); 1605 PetscUseTypeMethod(b, diagonalscale, NULL, baij->lvec); 1606 PetscFunctionReturn(PETSC_SUCCESS); 1607 } 1608 1609 static PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A) 1610 { 1611 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1612 1613 PetscFunctionBegin; 1614 PetscCall(MatSetUnfactored(a->A)); 1615 PetscFunctionReturn(PETSC_SUCCESS); 1616 } 1617 1618 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat, MatDuplicateOption, Mat *); 1619 1620 static PetscErrorCode MatEqual_MPISBAIJ(Mat A, Mat B, PetscBool *flag) 1621 { 1622 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ *)B->data, *matA = (Mat_MPISBAIJ *)A->data; 1623 Mat a, b, c, d; 1624 PetscBool flg; 1625 1626 PetscFunctionBegin; 1627 a = matA->A; 1628 b = matA->B; 1629 c = matB->A; 1630 d = matB->B; 1631 1632 PetscCall(MatEqual(a, c, &flg)); 1633 if (flg) PetscCall(MatEqual(b, d, &flg)); 1634 PetscCall(MPIU_Allreduce(&flg, flag, 1, MPIU_BOOL, MPI_LAND, PetscObjectComm((PetscObject)A))); 1635 PetscFunctionReturn(PETSC_SUCCESS); 1636 } 1637 1638 static PetscErrorCode MatCopy_MPISBAIJ(Mat A, Mat B, MatStructure str) 1639 { 1640 PetscBool isbaij; 1641 1642 PetscFunctionBegin; 1643 PetscCall(PetscObjectTypeCompareAny((PetscObject)B, &isbaij, MATSEQSBAIJ, MATMPISBAIJ, "")); 1644 PetscCheck(isbaij, PetscObjectComm((PetscObject)B), PETSC_ERR_SUP, "Not for matrix type %s", ((PetscObject)B)->type_name); 1645 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1646 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1647 PetscCall(MatGetRowUpperTriangular(A)); 1648 PetscCall(MatCopy_Basic(A, B, str)); 1649 PetscCall(MatRestoreRowUpperTriangular(A)); 1650 } else { 1651 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1652 Mat_MPISBAIJ *b = (Mat_MPISBAIJ *)B->data; 1653 1654 PetscCall(MatCopy(a->A, b->A, str)); 1655 PetscCall(MatCopy(a->B, b->B, str)); 1656 } 1657 PetscCall(PetscObjectStateIncrease((PetscObject)B)); 1658 PetscFunctionReturn(PETSC_SUCCESS); 1659 } 1660 1661 static PetscErrorCode MatAXPY_MPISBAIJ(Mat Y, PetscScalar a, Mat X, MatStructure str) 1662 { 1663 Mat_MPISBAIJ *xx = (Mat_MPISBAIJ *)X->data, *yy = (Mat_MPISBAIJ *)Y->data; 1664 PetscBLASInt bnz, one = 1; 1665 Mat_SeqSBAIJ *xa, *ya; 1666 Mat_SeqBAIJ *xb, *yb; 1667 1668 PetscFunctionBegin; 1669 if (str == SAME_NONZERO_PATTERN) { 1670 PetscScalar alpha = a; 1671 xa = (Mat_SeqSBAIJ *)xx->A->data; 1672 ya = (Mat_SeqSBAIJ *)yy->A->data; 1673 PetscCall(PetscBLASIntCast(xa->nz, &bnz)); 1674 PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, xa->a, &one, ya->a, &one)); 1675 xb = (Mat_SeqBAIJ *)xx->B->data; 1676 yb = (Mat_SeqBAIJ *)yy->B->data; 1677 PetscCall(PetscBLASIntCast(xb->nz, &bnz)); 1678 PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, xb->a, &one, yb->a, &one)); 1679 PetscCall(PetscObjectStateIncrease((PetscObject)Y)); 1680 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 1681 PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_TRUE)); 1682 PetscCall(MatAXPY_Basic(Y, a, X, str)); 1683 PetscCall(MatSetOption(X, MAT_GETROW_UPPERTRIANGULAR, PETSC_FALSE)); 1684 } else { 1685 Mat B; 1686 PetscInt *nnz_d, *nnz_o, bs = Y->rmap->bs; 1687 PetscCheck(bs == X->rmap->bs, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Matrices must have same block size"); 1688 PetscCall(MatGetRowUpperTriangular(X)); 1689 PetscCall(MatGetRowUpperTriangular(Y)); 1690 PetscCall(PetscMalloc1(yy->A->rmap->N, &nnz_d)); 1691 PetscCall(PetscMalloc1(yy->B->rmap->N, &nnz_o)); 1692 PetscCall(MatCreate(PetscObjectComm((PetscObject)Y), &B)); 1693 PetscCall(PetscObjectSetName((PetscObject)B, ((PetscObject)Y)->name)); 1694 PetscCall(MatSetSizes(B, Y->rmap->n, Y->cmap->n, Y->rmap->N, Y->cmap->N)); 1695 PetscCall(MatSetBlockSizesFromMats(B, Y, Y)); 1696 PetscCall(MatSetType(B, MATMPISBAIJ)); 1697 PetscCall(MatAXPYGetPreallocation_SeqSBAIJ(yy->A, xx->A, nnz_d)); 1698 PetscCall(MatAXPYGetPreallocation_MPIBAIJ(yy->B, yy->garray, xx->B, xx->garray, nnz_o)); 1699 PetscCall(MatMPISBAIJSetPreallocation(B, bs, 0, nnz_d, 0, nnz_o)); 1700 PetscCall(MatAXPY_BasicWithPreallocation(B, Y, a, X, str)); 1701 PetscCall(MatHeaderMerge(Y, &B)); 1702 PetscCall(PetscFree(nnz_d)); 1703 PetscCall(PetscFree(nnz_o)); 1704 PetscCall(MatRestoreRowUpperTriangular(X)); 1705 PetscCall(MatRestoreRowUpperTriangular(Y)); 1706 } 1707 PetscFunctionReturn(PETSC_SUCCESS); 1708 } 1709 1710 static PetscErrorCode MatCreateSubMatrices_MPISBAIJ(Mat A, PetscInt n, const IS irow[], const IS icol[], MatReuse scall, Mat *B[]) 1711 { 1712 PetscInt i; 1713 PetscBool flg; 1714 1715 PetscFunctionBegin; 1716 PetscCall(MatCreateSubMatrices_MPIBAIJ(A, n, irow, icol, scall, B)); /* B[] are sbaij matrices */ 1717 for (i = 0; i < n; i++) { 1718 PetscCall(ISEqual(irow[i], icol[i], &flg)); 1719 if (!flg) PetscCall(MatSeqSBAIJZeroOps_Private(*B[i])); 1720 } 1721 PetscFunctionReturn(PETSC_SUCCESS); 1722 } 1723 1724 static PetscErrorCode MatShift_MPISBAIJ(Mat Y, PetscScalar a) 1725 { 1726 Mat_MPISBAIJ *maij = (Mat_MPISBAIJ *)Y->data; 1727 Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ *)maij->A->data; 1728 1729 PetscFunctionBegin; 1730 if (!Y->preallocated) { 1731 PetscCall(MatMPISBAIJSetPreallocation(Y, Y->rmap->bs, 1, NULL, 0, NULL)); 1732 } else if (!aij->nz) { 1733 PetscInt nonew = aij->nonew; 1734 PetscCall(MatSeqSBAIJSetPreallocation(maij->A, Y->rmap->bs, 1, NULL)); 1735 aij->nonew = nonew; 1736 } 1737 PetscCall(MatShift_Basic(Y, a)); 1738 PetscFunctionReturn(PETSC_SUCCESS); 1739 } 1740 1741 static PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A, PetscBool *missing, PetscInt *d) 1742 { 1743 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1744 1745 PetscFunctionBegin; 1746 PetscCheck(A->rmap->n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only works for square matrices"); 1747 PetscCall(MatMissingDiagonal(a->A, missing, d)); 1748 if (d) { 1749 PetscInt rstart; 1750 PetscCall(MatGetOwnershipRange(A, &rstart, NULL)); 1751 *d += rstart / A->rmap->bs; 1752 } 1753 PetscFunctionReturn(PETSC_SUCCESS); 1754 } 1755 1756 static PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A, Mat *a) 1757 { 1758 PetscFunctionBegin; 1759 *a = ((Mat_MPISBAIJ *)A->data)->A; 1760 PetscFunctionReturn(PETSC_SUCCESS); 1761 } 1762 1763 static PetscErrorCode MatEliminateZeros_MPISBAIJ(Mat A, PetscBool keep) 1764 { 1765 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 1766 1767 PetscFunctionBegin; 1768 PetscCall(MatEliminateZeros_SeqSBAIJ(a->A, keep)); // possibly keep zero diagonal coefficients 1769 PetscCall(MatEliminateZeros_SeqBAIJ(a->B, PETSC_FALSE)); // never keep zero diagonal coefficients 1770 PetscFunctionReturn(PETSC_SUCCESS); 1771 } 1772 1773 static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ, 1774 MatGetRow_MPISBAIJ, 1775 MatRestoreRow_MPISBAIJ, 1776 MatMult_MPISBAIJ, 1777 /* 4*/ MatMultAdd_MPISBAIJ, 1778 MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */ 1779 MatMultAdd_MPISBAIJ, 1780 NULL, 1781 NULL, 1782 NULL, 1783 /* 10*/ NULL, 1784 NULL, 1785 NULL, 1786 MatSOR_MPISBAIJ, 1787 MatTranspose_MPISBAIJ, 1788 /* 15*/ MatGetInfo_MPISBAIJ, 1789 MatEqual_MPISBAIJ, 1790 MatGetDiagonal_MPISBAIJ, 1791 MatDiagonalScale_MPISBAIJ, 1792 MatNorm_MPISBAIJ, 1793 /* 20*/ MatAssemblyBegin_MPISBAIJ, 1794 MatAssemblyEnd_MPISBAIJ, 1795 MatSetOption_MPISBAIJ, 1796 MatZeroEntries_MPISBAIJ, 1797 /* 24*/ NULL, 1798 NULL, 1799 NULL, 1800 NULL, 1801 NULL, 1802 /* 29*/ MatSetUp_MPI_Hash, 1803 NULL, 1804 NULL, 1805 MatGetDiagonalBlock_MPISBAIJ, 1806 NULL, 1807 /* 34*/ MatDuplicate_MPISBAIJ, 1808 NULL, 1809 NULL, 1810 NULL, 1811 NULL, 1812 /* 39*/ MatAXPY_MPISBAIJ, 1813 MatCreateSubMatrices_MPISBAIJ, 1814 MatIncreaseOverlap_MPISBAIJ, 1815 MatGetValues_MPISBAIJ, 1816 MatCopy_MPISBAIJ, 1817 /* 44*/ NULL, 1818 MatScale_MPISBAIJ, 1819 MatShift_MPISBAIJ, 1820 NULL, 1821 NULL, 1822 /* 49*/ NULL, 1823 NULL, 1824 NULL, 1825 NULL, 1826 NULL, 1827 /* 54*/ NULL, 1828 NULL, 1829 MatSetUnfactored_MPISBAIJ, 1830 NULL, 1831 MatSetValuesBlocked_MPISBAIJ, 1832 /* 59*/ MatCreateSubMatrix_MPISBAIJ, 1833 NULL, 1834 NULL, 1835 NULL, 1836 NULL, 1837 /* 64*/ NULL, 1838 NULL, 1839 NULL, 1840 NULL, 1841 NULL, 1842 /* 69*/ MatGetRowMaxAbs_MPISBAIJ, 1843 NULL, 1844 MatConvert_MPISBAIJ_Basic, 1845 NULL, 1846 NULL, 1847 /* 74*/ NULL, 1848 NULL, 1849 NULL, 1850 NULL, 1851 NULL, 1852 /* 79*/ NULL, 1853 NULL, 1854 NULL, 1855 NULL, 1856 MatLoad_MPISBAIJ, 1857 /* 84*/ NULL, 1858 NULL, 1859 NULL, 1860 NULL, 1861 NULL, 1862 /* 89*/ NULL, 1863 NULL, 1864 NULL, 1865 NULL, 1866 NULL, 1867 /* 94*/ NULL, 1868 NULL, 1869 NULL, 1870 NULL, 1871 NULL, 1872 /* 99*/ NULL, 1873 NULL, 1874 NULL, 1875 MatConjugate_MPISBAIJ, 1876 NULL, 1877 /*104*/ NULL, 1878 MatRealPart_MPISBAIJ, 1879 MatImaginaryPart_MPISBAIJ, 1880 MatGetRowUpperTriangular_MPISBAIJ, 1881 MatRestoreRowUpperTriangular_MPISBAIJ, 1882 /*109*/ NULL, 1883 NULL, 1884 NULL, 1885 NULL, 1886 MatMissingDiagonal_MPISBAIJ, 1887 /*114*/ NULL, 1888 NULL, 1889 NULL, 1890 NULL, 1891 NULL, 1892 /*119*/ NULL, 1893 NULL, 1894 NULL, 1895 NULL, 1896 NULL, 1897 /*124*/ NULL, 1898 NULL, 1899 NULL, 1900 NULL, 1901 NULL, 1902 /*129*/ NULL, 1903 NULL, 1904 NULL, 1905 NULL, 1906 NULL, 1907 /*134*/ NULL, 1908 NULL, 1909 NULL, 1910 NULL, 1911 NULL, 1912 /*139*/ MatSetBlockSizes_Default, 1913 NULL, 1914 NULL, 1915 NULL, 1916 NULL, 1917 /*144*/ MatCreateMPIMatConcatenateSeqMat_MPISBAIJ, 1918 NULL, 1919 NULL, 1920 NULL, 1921 NULL, 1922 NULL, 1923 /*150*/ NULL, 1924 MatEliminateZeros_MPISBAIJ}; 1925 1926 static PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B, PetscInt bs, PetscInt d_nz, const PetscInt *d_nnz, PetscInt o_nz, const PetscInt *o_nnz) 1927 { 1928 Mat_MPISBAIJ *b = (Mat_MPISBAIJ *)B->data; 1929 PetscInt i, mbs, Mbs; 1930 PetscMPIInt size; 1931 1932 PetscFunctionBegin; 1933 if (B->hash_active) { 1934 B->ops[0] = b->cops; 1935 B->hash_active = PETSC_FALSE; 1936 } 1937 if (!B->preallocated) PetscCall(MatStashCreate_Private(PetscObjectComm((PetscObject)B), bs, &B->bstash)); 1938 PetscCall(MatSetBlockSize(B, PetscAbs(bs))); 1939 PetscCall(PetscLayoutSetUp(B->rmap)); 1940 PetscCall(PetscLayoutSetUp(B->cmap)); 1941 PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs)); 1942 PetscCheck(B->rmap->N <= B->cmap->N, PetscObjectComm((PetscObject)B), PETSC_ERR_SUP, "MPISBAIJ matrix cannot have more rows %" PetscInt_FMT " than columns %" PetscInt_FMT, B->rmap->N, B->cmap->N); 1943 PetscCheck(B->rmap->n <= B->cmap->n, PETSC_COMM_SELF, PETSC_ERR_SUP, "MPISBAIJ matrix cannot have more local rows %" PetscInt_FMT " than columns %" PetscInt_FMT, B->rmap->n, B->cmap->n); 1944 1945 mbs = B->rmap->n / bs; 1946 Mbs = B->rmap->N / bs; 1947 PetscCheck(mbs * bs == B->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "No of local rows %" PetscInt_FMT " must be divisible by blocksize %" PetscInt_FMT, B->rmap->N, bs); 1948 1949 B->rmap->bs = bs; 1950 b->bs2 = bs * bs; 1951 b->mbs = mbs; 1952 b->Mbs = Mbs; 1953 b->nbs = B->cmap->n / bs; 1954 b->Nbs = B->cmap->N / bs; 1955 1956 for (i = 0; i <= b->size; i++) b->rangebs[i] = B->rmap->range[i] / bs; 1957 b->rstartbs = B->rmap->rstart / bs; 1958 b->rendbs = B->rmap->rend / bs; 1959 1960 b->cstartbs = B->cmap->rstart / bs; 1961 b->cendbs = B->cmap->rend / bs; 1962 1963 #if defined(PETSC_USE_CTABLE) 1964 PetscCall(PetscHMapIDestroy(&b->colmap)); 1965 #else 1966 PetscCall(PetscFree(b->colmap)); 1967 #endif 1968 PetscCall(PetscFree(b->garray)); 1969 PetscCall(VecDestroy(&b->lvec)); 1970 PetscCall(VecScatterDestroy(&b->Mvctx)); 1971 PetscCall(VecDestroy(&b->slvec0)); 1972 PetscCall(VecDestroy(&b->slvec0b)); 1973 PetscCall(VecDestroy(&b->slvec1)); 1974 PetscCall(VecDestroy(&b->slvec1a)); 1975 PetscCall(VecDestroy(&b->slvec1b)); 1976 PetscCall(VecScatterDestroy(&b->sMvctx)); 1977 1978 PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &size)); 1979 PetscCall(MatDestroy(&b->B)); 1980 PetscCall(MatCreate(PETSC_COMM_SELF, &b->B)); 1981 PetscCall(MatSetSizes(b->B, B->rmap->n, size > 1 ? B->cmap->N : 0, B->rmap->n, size > 1 ? B->cmap->N : 0)); 1982 PetscCall(MatSetType(b->B, MATSEQBAIJ)); 1983 1984 PetscCall(MatDestroy(&b->A)); 1985 PetscCall(MatCreate(PETSC_COMM_SELF, &b->A)); 1986 PetscCall(MatSetSizes(b->A, B->rmap->n, B->cmap->n, B->rmap->n, B->cmap->n)); 1987 PetscCall(MatSetType(b->A, MATSEQSBAIJ)); 1988 1989 PetscCall(MatSeqSBAIJSetPreallocation(b->A, bs, d_nz, d_nnz)); 1990 PetscCall(MatSeqBAIJSetPreallocation(b->B, bs, o_nz, o_nnz)); 1991 1992 B->preallocated = PETSC_TRUE; 1993 B->was_assembled = PETSC_FALSE; 1994 B->assembled = PETSC_FALSE; 1995 PetscFunctionReturn(PETSC_SUCCESS); 1996 } 1997 1998 static PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B, PetscInt bs, const PetscInt ii[], const PetscInt jj[], const PetscScalar V[]) 1999 { 2000 PetscInt m, rstart, cend; 2001 PetscInt i, j, d, nz, bd, nz_max = 0, *d_nnz = NULL, *o_nnz = NULL; 2002 const PetscInt *JJ = NULL; 2003 PetscScalar *values = NULL; 2004 PetscBool roworiented = ((Mat_MPISBAIJ *)B->data)->roworiented; 2005 PetscBool nooffprocentries; 2006 2007 PetscFunctionBegin; 2008 PetscCheck(bs >= 1, PetscObjectComm((PetscObject)B), PETSC_ERR_ARG_OUTOFRANGE, "Invalid block size specified, must be positive but it is %" PetscInt_FMT, bs); 2009 PetscCall(PetscLayoutSetBlockSize(B->rmap, bs)); 2010 PetscCall(PetscLayoutSetBlockSize(B->cmap, bs)); 2011 PetscCall(PetscLayoutSetUp(B->rmap)); 2012 PetscCall(PetscLayoutSetUp(B->cmap)); 2013 PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs)); 2014 m = B->rmap->n / bs; 2015 rstart = B->rmap->rstart / bs; 2016 cend = B->cmap->rend / bs; 2017 2018 PetscCheck(!ii[0], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %" PetscInt_FMT, ii[0]); 2019 PetscCall(PetscMalloc2(m, &d_nnz, m, &o_nnz)); 2020 for (i = 0; i < m; i++) { 2021 nz = ii[i + 1] - ii[i]; 2022 PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Local row %" PetscInt_FMT " has a negative number of columns %" PetscInt_FMT, i, nz); 2023 /* count the ones on the diagonal and above, split into diagonal and off diagonal portions. */ 2024 JJ = jj + ii[i]; 2025 bd = 0; 2026 for (j = 0; j < nz; j++) { 2027 if (*JJ >= i + rstart) break; 2028 JJ++; 2029 bd++; 2030 } 2031 d = 0; 2032 for (; j < nz; j++) { 2033 if (*JJ++ >= cend) break; 2034 d++; 2035 } 2036 d_nnz[i] = d; 2037 o_nnz[i] = nz - d - bd; 2038 nz = nz - bd; 2039 nz_max = PetscMax(nz_max, nz); 2040 } 2041 PetscCall(MatMPISBAIJSetPreallocation(B, bs, 0, d_nnz, 0, o_nnz)); 2042 PetscCall(MatSetOption(B, MAT_IGNORE_LOWER_TRIANGULAR, PETSC_TRUE)); 2043 PetscCall(PetscFree2(d_nnz, o_nnz)); 2044 2045 values = (PetscScalar *)V; 2046 if (!values) PetscCall(PetscCalloc1(bs * bs * nz_max, &values)); 2047 for (i = 0; i < m; i++) { 2048 PetscInt row = i + rstart; 2049 PetscInt ncols = ii[i + 1] - ii[i]; 2050 const PetscInt *icols = jj + ii[i]; 2051 if (bs == 1 || !roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */ 2052 const PetscScalar *svals = values + (V ? (bs * bs * ii[i]) : 0); 2053 PetscCall(MatSetValuesBlocked_MPISBAIJ(B, 1, &row, ncols, icols, svals, INSERT_VALUES)); 2054 } else { /* block ordering does not match so we can only insert one block at a time. */ 2055 PetscInt j; 2056 for (j = 0; j < ncols; j++) { 2057 const PetscScalar *svals = values + (V ? (bs * bs * (ii[i] + j)) : 0); 2058 PetscCall(MatSetValuesBlocked_MPISBAIJ(B, 1, &row, 1, &icols[j], svals, INSERT_VALUES)); 2059 } 2060 } 2061 } 2062 2063 if (!V) PetscCall(PetscFree(values)); 2064 nooffprocentries = B->nooffprocentries; 2065 B->nooffprocentries = PETSC_TRUE; 2066 PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY)); 2067 PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY)); 2068 B->nooffprocentries = nooffprocentries; 2069 2070 PetscCall(MatSetOption(B, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE)); 2071 PetscFunctionReturn(PETSC_SUCCESS); 2072 } 2073 2074 /*MC 2075 MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices, 2076 based on block compressed sparse row format. Only the upper triangular portion of the "diagonal" portion of 2077 the matrix is stored. 2078 2079 For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you 2080 can call `MatSetOption`(`Mat`, `MAT_HERMITIAN`); 2081 2082 Options Database Key: 2083 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to `MatSetFromOptions()` 2084 2085 Level: beginner 2086 2087 Note: 2088 The number of rows in the matrix must be less than or equal to the number of columns. Similarly the number of rows in the 2089 diagonal portion of the matrix of each process has to less than or equal the number of columns. 2090 2091 .seealso: [](ch_matrices), `Mat`, `MATSBAIJ`, `MATBAIJ`, `MatCreateBAIJ()`, `MATSEQSBAIJ`, `MatType` 2092 M*/ 2093 2094 PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B) 2095 { 2096 Mat_MPISBAIJ *b; 2097 PetscBool flg = PETSC_FALSE; 2098 2099 PetscFunctionBegin; 2100 PetscCall(PetscNew(&b)); 2101 B->data = (void *)b; 2102 B->ops[0] = MatOps_Values; 2103 2104 B->ops->destroy = MatDestroy_MPISBAIJ; 2105 B->ops->view = MatView_MPISBAIJ; 2106 B->assembled = PETSC_FALSE; 2107 B->insertmode = NOT_SET_VALUES; 2108 2109 PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)B), &b->rank)); 2110 PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &b->size)); 2111 2112 /* build local table of row and column ownerships */ 2113 PetscCall(PetscMalloc1(b->size + 2, &b->rangebs)); 2114 2115 /* build cache for off array entries formed */ 2116 PetscCall(MatStashCreate_Private(PetscObjectComm((PetscObject)B), 1, &B->stash)); 2117 2118 b->donotstash = PETSC_FALSE; 2119 b->colmap = NULL; 2120 b->garray = NULL; 2121 b->roworiented = PETSC_TRUE; 2122 2123 /* stuff used in block assembly */ 2124 b->barray = NULL; 2125 2126 /* stuff used for matrix vector multiply */ 2127 b->lvec = NULL; 2128 b->Mvctx = NULL; 2129 b->slvec0 = NULL; 2130 b->slvec0b = NULL; 2131 b->slvec1 = NULL; 2132 b->slvec1a = NULL; 2133 b->slvec1b = NULL; 2134 b->sMvctx = NULL; 2135 2136 /* stuff for MatGetRow() */ 2137 b->rowindices = NULL; 2138 b->rowvalues = NULL; 2139 b->getrowactive = PETSC_FALSE; 2140 2141 /* hash table stuff */ 2142 b->ht = NULL; 2143 b->hd = NULL; 2144 b->ht_size = 0; 2145 b->ht_flag = PETSC_FALSE; 2146 b->ht_fact = 0; 2147 b->ht_total_ct = 0; 2148 b->ht_insert_ct = 0; 2149 2150 /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */ 2151 b->ijonly = PETSC_FALSE; 2152 2153 b->in_loc = NULL; 2154 b->v_loc = NULL; 2155 b->n_loc = 0; 2156 2157 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatStoreValues_C", MatStoreValues_MPISBAIJ)); 2158 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatRetrieveValues_C", MatRetrieveValues_MPISBAIJ)); 2159 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatMPISBAIJSetPreallocation_C", MatMPISBAIJSetPreallocation_MPISBAIJ)); 2160 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatMPISBAIJSetPreallocationCSR_C", MatMPISBAIJSetPreallocationCSR_MPISBAIJ)); 2161 #if defined(PETSC_HAVE_ELEMENTAL) 2162 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpisbaij_elemental_C", MatConvert_MPISBAIJ_Elemental)); 2163 #endif 2164 #if defined(PETSC_HAVE_SCALAPACK) 2165 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpisbaij_scalapack_C", MatConvert_SBAIJ_ScaLAPACK)); 2166 #endif 2167 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpisbaij_mpiaij_C", MatConvert_MPISBAIJ_Basic)); 2168 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpisbaij_mpibaij_C", MatConvert_MPISBAIJ_Basic)); 2169 2170 B->symmetric = PETSC_BOOL3_TRUE; 2171 B->structurally_symmetric = PETSC_BOOL3_TRUE; 2172 B->symmetry_eternal = PETSC_TRUE; 2173 B->structural_symmetry_eternal = PETSC_TRUE; 2174 #if defined(PETSC_USE_COMPLEX) 2175 B->hermitian = PETSC_BOOL3_FALSE; 2176 #else 2177 B->hermitian = PETSC_BOOL3_TRUE; 2178 #endif 2179 2180 PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATMPISBAIJ)); 2181 PetscOptionsBegin(PetscObjectComm((PetscObject)B), NULL, "Options for loading MPISBAIJ matrix 1", "Mat"); 2182 PetscCall(PetscOptionsBool("-mat_use_hash_table", "Use hash table to save memory in constructing matrix", "MatSetOption", flg, &flg, NULL)); 2183 if (flg) { 2184 PetscReal fact = 1.39; 2185 PetscCall(MatSetOption(B, MAT_USE_HASH_TABLE, PETSC_TRUE)); 2186 PetscCall(PetscOptionsReal("-mat_use_hash_table", "Use hash table factor", "MatMPIBAIJSetHashTableFactor", fact, &fact, NULL)); 2187 if (fact <= 1.0) fact = 1.39; 2188 PetscCall(MatMPIBAIJSetHashTableFactor(B, fact)); 2189 PetscCall(PetscInfo(B, "Hash table Factor used %5.2g\n", (double)fact)); 2190 } 2191 PetscOptionsEnd(); 2192 PetscFunctionReturn(PETSC_SUCCESS); 2193 } 2194 2195 // PetscClangLinter pragma disable: -fdoc-section-header-unknown 2196 /*MC 2197 MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices. 2198 2199 This matrix type is identical to `MATSEQSBAIJ` when constructed with a single process communicator, 2200 and `MATMPISBAIJ` otherwise. 2201 2202 Options Database Key: 2203 . -mat_type sbaij - sets the matrix type to `MATSBAIJ` during a call to `MatSetFromOptions()` 2204 2205 Level: beginner 2206 2207 .seealso: [](ch_matrices), `Mat`, `MATSEQSBAIJ`, `MATMPISBAIJ`, `MatCreateSBAIJ()`, `MATSEQSBAIJ`, `MATMPISBAIJ` 2208 M*/ 2209 2210 /*@C 2211 MatMPISBAIJSetPreallocation - For good matrix assembly performance 2212 the user should preallocate the matrix storage by setting the parameters 2213 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2214 performance can be increased by more than a factor of 50. 2215 2216 Collective 2217 2218 Input Parameters: 2219 + B - the matrix 2220 . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row 2221 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs() 2222 . d_nz - number of block nonzeros per block row in diagonal portion of local 2223 submatrix (same for all local rows) 2224 . d_nnz - array containing the number of block nonzeros in the various block rows 2225 in the upper triangular and diagonal part of the in diagonal portion of the local 2226 (possibly different for each block row) or `NULL`. If you plan to factor the matrix you must leave room 2227 for the diagonal entry and set a value even if it is zero. 2228 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 2229 submatrix (same for all local rows). 2230 - o_nnz - array containing the number of nonzeros in the various block rows of the 2231 off-diagonal portion of the local submatrix that is right of the diagonal 2232 (possibly different for each block row) or `NULL`. 2233 2234 Options Database Keys: 2235 + -mat_no_unroll - uses code that does not unroll the loops in the 2236 block calculations (much slower) 2237 - -mat_block_size - size of the blocks to use 2238 2239 Level: intermediate 2240 2241 Notes: 2242 2243 If `PETSC_DECIDE` or `PETSC_DETERMINE` is used for a particular argument on one processor 2244 than it must be used on all processors that share the object for that argument. 2245 2246 If the *_nnz parameter is given then the *_nz parameter is ignored 2247 2248 Storage Information: 2249 For a square global matrix we define each processor's diagonal portion 2250 to be its local rows and the corresponding columns (a square submatrix); 2251 each processor's off-diagonal portion encompasses the remainder of the 2252 local matrix (a rectangular submatrix). 2253 2254 The user can specify preallocated storage for the diagonal part of 2255 the local submatrix with either `d_nz` or `d_nnz` (not both). Set 2256 `d_nz` = `PETSC_DEFAULT` and `d_nnz` = `NULL` for PETSc to control dynamic 2257 memory allocation. Likewise, specify preallocated storage for the 2258 off-diagonal part of the local submatrix with `o_nz` or `o_nnz` (not both). 2259 2260 You can call `MatGetInfo()` to get information on how effective the preallocation was; 2261 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 2262 You can also run with the option `-info` and look for messages with the string 2263 malloc in them to see if additional memory allocation was needed. 2264 2265 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2266 the figure below we depict these three local rows and all columns (0-11). 2267 2268 .vb 2269 0 1 2 3 4 5 6 7 8 9 10 11 2270 -------------------------- 2271 row 3 |. . . d d d o o o o o o 2272 row 4 |. . . d d d o o o o o o 2273 row 5 |. . . d d d o o o o o o 2274 -------------------------- 2275 .ve 2276 2277 Thus, any entries in the d locations are stored in the d (diagonal) 2278 submatrix, and any entries in the o locations are stored in the 2279 o (off-diagonal) submatrix. Note that the d matrix is stored in 2280 `MATSEQSBAIJ` format and the o submatrix in `MATSEQBAIJ` format. 2281 2282 Now `d_nz` should indicate the number of block nonzeros per row in the upper triangular 2283 plus the diagonal part of the d matrix, 2284 and `o_nz` should indicate the number of block nonzeros per row in the o matrix 2285 2286 In general, for PDE problems in which most nonzeros are near the diagonal, 2287 one expects `d_nz` >> `o_nz`. 2288 2289 .seealso: [](ch_matrices), `Mat`, `MATMPISBAIJ`, `MATSBAIJ`, `MatCreate()`, `MatCreateSeqSBAIJ()`, `MatSetValues()`, `MatCreateBAIJ()`, `PetscSplitOwnership()` 2290 @*/ 2291 PetscErrorCode MatMPISBAIJSetPreallocation(Mat B, PetscInt bs, PetscInt d_nz, const PetscInt d_nnz[], PetscInt o_nz, const PetscInt o_nnz[]) 2292 { 2293 PetscFunctionBegin; 2294 PetscValidHeaderSpecific(B, MAT_CLASSID, 1); 2295 PetscValidType(B, 1); 2296 PetscValidLogicalCollectiveInt(B, bs, 2); 2297 PetscTryMethod(B, "MatMPISBAIJSetPreallocation_C", (Mat, PetscInt, PetscInt, const PetscInt[], PetscInt, const PetscInt[]), (B, bs, d_nz, d_nnz, o_nz, o_nnz)); 2298 PetscFunctionReturn(PETSC_SUCCESS); 2299 } 2300 2301 // PetscClangLinter pragma disable: -fdoc-section-header-unknown 2302 /*@C 2303 MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format, `MATSBAIJ`, 2304 (block compressed row). For good matrix assembly performance 2305 the user should preallocate the matrix storage by setting the parameters 2306 `d_nz` (or `d_nnz`) and `o_nz` (or `o_nnz`). 2307 2308 Collective 2309 2310 Input Parameters: 2311 + comm - MPI communicator 2312 . bs - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row 2313 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with `MatCreateVecs()` 2314 . m - number of local rows (or `PETSC_DECIDE` to have calculated if `M` is given) 2315 This value should be the same as the local size used in creating the 2316 y vector for the matrix-vector product y = Ax. 2317 . n - number of local columns (or `PETSC_DECIDE` to have calculated if `N` is given) 2318 This value should be the same as the local size used in creating the 2319 x vector for the matrix-vector product y = Ax. 2320 . M - number of global rows (or `PETSC_DETERMINE` to have calculated if `m` is given) 2321 . N - number of global columns (or `PETSC_DETERMINE` to have calculated if `n` is given) 2322 . d_nz - number of block nonzeros per block row in diagonal portion of local 2323 submatrix (same for all local rows) 2324 . d_nnz - array containing the number of block nonzeros in the various block rows 2325 in the upper triangular portion of the in diagonal portion of the local 2326 (possibly different for each block block row) or `NULL`. 2327 If you plan to factor the matrix you must leave room for the diagonal entry and 2328 set its value even if it is zero. 2329 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 2330 submatrix (same for all local rows). 2331 - o_nnz - array containing the number of nonzeros in the various block rows of the 2332 off-diagonal portion of the local submatrix (possibly different for 2333 each block row) or `NULL`. 2334 2335 Output Parameter: 2336 . A - the matrix 2337 2338 Options Database Keys: 2339 + -mat_no_unroll - uses code that does not unroll the loops in the 2340 block calculations (much slower) 2341 . -mat_block_size - size of the blocks to use 2342 - -mat_mpi - use the parallel matrix data structures even on one processor 2343 (defaults to using SeqBAIJ format on one processor) 2344 2345 Level: intermediate 2346 2347 Notes: 2348 It is recommended that one use `MatCreateFromOptions()` or the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()`, 2349 MatXXXXSetPreallocation() paradigm instead of this routine directly. 2350 [MatXXXXSetPreallocation() is, for example, `MatSeqAIJSetPreallocation()`] 2351 2352 The number of rows and columns must be divisible by blocksize. 2353 This matrix type does not support complex Hermitian operation. 2354 2355 The user MUST specify either the local or global matrix dimensions 2356 (possibly both). 2357 2358 If `PETSC_DECIDE` or `PETSC_DETERMINE` is used for a particular argument on one processor 2359 than it must be used on all processors that share the object for that argument. 2360 2361 If the *_nnz parameter is given then the *_nz parameter is ignored 2362 2363 Storage Information: 2364 For a square global matrix we define each processor's diagonal portion 2365 to be its local rows and the corresponding columns (a square submatrix); 2366 each processor's off-diagonal portion encompasses the remainder of the 2367 local matrix (a rectangular submatrix). 2368 2369 The user can specify preallocated storage for the diagonal part of 2370 the local submatrix with either `d_nz` or `d_nnz` (not both). Set 2371 `d_nz` = `PETSC_DEFAULT` and `d_nnz` = `NULL` for PETSc to control dynamic 2372 memory allocation. Likewise, specify preallocated storage for the 2373 off-diagonal part of the local submatrix with `o_nz` or `o_nnz` (not both). 2374 2375 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 2376 the figure below we depict these three local rows and all columns (0-11). 2377 2378 .vb 2379 0 1 2 3 4 5 6 7 8 9 10 11 2380 -------------------------- 2381 row 3 |. . . d d d o o o o o o 2382 row 4 |. . . d d d o o o o o o 2383 row 5 |. . . d d d o o o o o o 2384 -------------------------- 2385 .ve 2386 2387 Thus, any entries in the d locations are stored in the d (diagonal) 2388 submatrix, and any entries in the o locations are stored in the 2389 o (off-diagonal) submatrix. Note that the d matrix is stored in 2390 `MATSEQSBAIJ` format and the o submatrix in `MATSEQBAIJ` format. 2391 2392 Now `d_nz` should indicate the number of block nonzeros per row in the upper triangular 2393 plus the diagonal part of the d matrix, 2394 and `o_nz` should indicate the number of block nonzeros per row in the o matrix. 2395 In general, for PDE problems in which most nonzeros are near the diagonal, 2396 one expects `d_nz` >> `o_nz`. 2397 2398 .seealso: [](ch_matrices), `Mat`, `MATSBAIJ`, `MatCreate()`, `MatCreateSeqSBAIJ()`, `MatSetValues()`, `MatCreateBAIJ()` 2399 @*/ 2400 PetscErrorCode MatCreateSBAIJ(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt M, PetscInt N, PetscInt d_nz, const PetscInt d_nnz[], PetscInt o_nz, const PetscInt o_nnz[], Mat *A) 2401 { 2402 PetscMPIInt size; 2403 2404 PetscFunctionBegin; 2405 PetscCall(MatCreate(comm, A)); 2406 PetscCall(MatSetSizes(*A, m, n, M, N)); 2407 PetscCallMPI(MPI_Comm_size(comm, &size)); 2408 if (size > 1) { 2409 PetscCall(MatSetType(*A, MATMPISBAIJ)); 2410 PetscCall(MatMPISBAIJSetPreallocation(*A, bs, d_nz, d_nnz, o_nz, o_nnz)); 2411 } else { 2412 PetscCall(MatSetType(*A, MATSEQSBAIJ)); 2413 PetscCall(MatSeqSBAIJSetPreallocation(*A, bs, d_nz, d_nnz)); 2414 } 2415 PetscFunctionReturn(PETSC_SUCCESS); 2416 } 2417 2418 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin, MatDuplicateOption cpvalues, Mat *newmat) 2419 { 2420 Mat mat; 2421 Mat_MPISBAIJ *a, *oldmat = (Mat_MPISBAIJ *)matin->data; 2422 PetscInt len = 0, nt, bs = matin->rmap->bs, mbs = oldmat->mbs; 2423 PetscScalar *array; 2424 2425 PetscFunctionBegin; 2426 *newmat = NULL; 2427 2428 PetscCall(MatCreate(PetscObjectComm((PetscObject)matin), &mat)); 2429 PetscCall(MatSetSizes(mat, matin->rmap->n, matin->cmap->n, matin->rmap->N, matin->cmap->N)); 2430 PetscCall(MatSetType(mat, ((PetscObject)matin)->type_name)); 2431 PetscCall(PetscLayoutReference(matin->rmap, &mat->rmap)); 2432 PetscCall(PetscLayoutReference(matin->cmap, &mat->cmap)); 2433 2434 mat->factortype = matin->factortype; 2435 mat->preallocated = PETSC_TRUE; 2436 mat->assembled = PETSC_TRUE; 2437 mat->insertmode = NOT_SET_VALUES; 2438 2439 a = (Mat_MPISBAIJ *)mat->data; 2440 a->bs2 = oldmat->bs2; 2441 a->mbs = oldmat->mbs; 2442 a->nbs = oldmat->nbs; 2443 a->Mbs = oldmat->Mbs; 2444 a->Nbs = oldmat->Nbs; 2445 2446 a->size = oldmat->size; 2447 a->rank = oldmat->rank; 2448 a->donotstash = oldmat->donotstash; 2449 a->roworiented = oldmat->roworiented; 2450 a->rowindices = NULL; 2451 a->rowvalues = NULL; 2452 a->getrowactive = PETSC_FALSE; 2453 a->barray = NULL; 2454 a->rstartbs = oldmat->rstartbs; 2455 a->rendbs = oldmat->rendbs; 2456 a->cstartbs = oldmat->cstartbs; 2457 a->cendbs = oldmat->cendbs; 2458 2459 /* hash table stuff */ 2460 a->ht = NULL; 2461 a->hd = NULL; 2462 a->ht_size = 0; 2463 a->ht_flag = oldmat->ht_flag; 2464 a->ht_fact = oldmat->ht_fact; 2465 a->ht_total_ct = 0; 2466 a->ht_insert_ct = 0; 2467 2468 PetscCall(PetscArraycpy(a->rangebs, oldmat->rangebs, a->size + 2)); 2469 if (oldmat->colmap) { 2470 #if defined(PETSC_USE_CTABLE) 2471 PetscCall(PetscHMapIDuplicate(oldmat->colmap, &a->colmap)); 2472 #else 2473 PetscCall(PetscMalloc1(a->Nbs, &a->colmap)); 2474 PetscCall(PetscArraycpy(a->colmap, oldmat->colmap, a->Nbs)); 2475 #endif 2476 } else a->colmap = NULL; 2477 2478 if (oldmat->garray && (len = ((Mat_SeqBAIJ *)(oldmat->B->data))->nbs)) { 2479 PetscCall(PetscMalloc1(len, &a->garray)); 2480 PetscCall(PetscArraycpy(a->garray, oldmat->garray, len)); 2481 } else a->garray = NULL; 2482 2483 PetscCall(MatStashCreate_Private(PetscObjectComm((PetscObject)matin), matin->rmap->bs, &mat->bstash)); 2484 PetscCall(VecDuplicate(oldmat->lvec, &a->lvec)); 2485 PetscCall(VecScatterCopy(oldmat->Mvctx, &a->Mvctx)); 2486 2487 PetscCall(VecDuplicate(oldmat->slvec0, &a->slvec0)); 2488 PetscCall(VecDuplicate(oldmat->slvec1, &a->slvec1)); 2489 2490 PetscCall(VecGetLocalSize(a->slvec1, &nt)); 2491 PetscCall(VecGetArray(a->slvec1, &array)); 2492 PetscCall(VecCreateSeqWithArray(PETSC_COMM_SELF, 1, bs * mbs, array, &a->slvec1a)); 2493 PetscCall(VecCreateSeqWithArray(PETSC_COMM_SELF, 1, nt - bs * mbs, array + bs * mbs, &a->slvec1b)); 2494 PetscCall(VecRestoreArray(a->slvec1, &array)); 2495 PetscCall(VecGetArray(a->slvec0, &array)); 2496 PetscCall(VecCreateSeqWithArray(PETSC_COMM_SELF, 1, nt - bs * mbs, array + bs * mbs, &a->slvec0b)); 2497 PetscCall(VecRestoreArray(a->slvec0, &array)); 2498 2499 /* ierr = VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */ 2500 PetscCall(PetscObjectReference((PetscObject)oldmat->sMvctx)); 2501 a->sMvctx = oldmat->sMvctx; 2502 2503 PetscCall(MatDuplicate(oldmat->A, cpvalues, &a->A)); 2504 PetscCall(MatDuplicate(oldmat->B, cpvalues, &a->B)); 2505 PetscCall(PetscFunctionListDuplicate(((PetscObject)matin)->qlist, &((PetscObject)mat)->qlist)); 2506 *newmat = mat; 2507 PetscFunctionReturn(PETSC_SUCCESS); 2508 } 2509 2510 /* Used for both MPIBAIJ and MPISBAIJ matrices */ 2511 #define MatLoad_MPISBAIJ_Binary MatLoad_MPIBAIJ_Binary 2512 2513 PetscErrorCode MatLoad_MPISBAIJ(Mat mat, PetscViewer viewer) 2514 { 2515 PetscBool isbinary; 2516 2517 PetscFunctionBegin; 2518 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary)); 2519 PetscCheck(isbinary, PetscObjectComm((PetscObject)viewer), PETSC_ERR_SUP, "Viewer type %s not yet supported for reading %s matrices", ((PetscObject)viewer)->type_name, ((PetscObject)mat)->type_name); 2520 PetscCall(MatLoad_MPISBAIJ_Binary(mat, viewer)); 2521 PetscFunctionReturn(PETSC_SUCCESS); 2522 } 2523 2524 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A, Vec v, PetscInt idx[]) 2525 { 2526 Mat_MPISBAIJ *a = (Mat_MPISBAIJ *)A->data; 2527 Mat_SeqBAIJ *b = (Mat_SeqBAIJ *)(a->B)->data; 2528 PetscReal atmp; 2529 PetscReal *work, *svalues, *rvalues; 2530 PetscInt i, bs, mbs, *bi, *bj, brow, j, ncols, krow, kcol, col, row, Mbs, bcol; 2531 PetscMPIInt rank, size; 2532 PetscInt *rowners_bs, dest, count, source; 2533 PetscScalar *va; 2534 MatScalar *ba; 2535 MPI_Status stat; 2536 2537 PetscFunctionBegin; 2538 PetscCheck(!idx, PETSC_COMM_SELF, PETSC_ERR_SUP, "Send email to petsc-maint@mcs.anl.gov"); 2539 PetscCall(MatGetRowMaxAbs(a->A, v, NULL)); 2540 PetscCall(VecGetArray(v, &va)); 2541 2542 PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size)); 2543 PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)A), &rank)); 2544 2545 bs = A->rmap->bs; 2546 mbs = a->mbs; 2547 Mbs = a->Mbs; 2548 ba = b->a; 2549 bi = b->i; 2550 bj = b->j; 2551 2552 /* find ownerships */ 2553 rowners_bs = A->rmap->range; 2554 2555 /* each proc creates an array to be distributed */ 2556 PetscCall(PetscCalloc1(bs * Mbs, &work)); 2557 2558 /* row_max for B */ 2559 if (rank != size - 1) { 2560 for (i = 0; i < mbs; i++) { 2561 ncols = bi[1] - bi[0]; 2562 bi++; 2563 brow = bs * i; 2564 for (j = 0; j < ncols; j++) { 2565 bcol = bs * (*bj); 2566 for (kcol = 0; kcol < bs; kcol++) { 2567 col = bcol + kcol; /* local col index */ 2568 col += rowners_bs[rank + 1]; /* global col index */ 2569 for (krow = 0; krow < bs; krow++) { 2570 atmp = PetscAbsScalar(*ba); 2571 ba++; 2572 row = brow + krow; /* local row index */ 2573 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2574 if (work[col] < atmp) work[col] = atmp; 2575 } 2576 } 2577 bj++; 2578 } 2579 } 2580 2581 /* send values to its owners */ 2582 for (dest = rank + 1; dest < size; dest++) { 2583 svalues = work + rowners_bs[dest]; 2584 count = rowners_bs[dest + 1] - rowners_bs[dest]; 2585 PetscCallMPI(MPI_Send(svalues, count, MPIU_REAL, dest, rank, PetscObjectComm((PetscObject)A))); 2586 } 2587 } 2588 2589 /* receive values */ 2590 if (rank) { 2591 rvalues = work; 2592 count = rowners_bs[rank + 1] - rowners_bs[rank]; 2593 for (source = 0; source < rank; source++) { 2594 PetscCallMPI(MPI_Recv(rvalues, count, MPIU_REAL, MPI_ANY_SOURCE, MPI_ANY_TAG, PetscObjectComm((PetscObject)A), &stat)); 2595 /* process values */ 2596 for (i = 0; i < count; i++) { 2597 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2598 } 2599 } 2600 } 2601 2602 PetscCall(VecRestoreArray(v, &va)); 2603 PetscCall(PetscFree(work)); 2604 PetscFunctionReturn(PETSC_SUCCESS); 2605 } 2606 2607 PetscErrorCode MatSOR_MPISBAIJ(Mat matin, Vec bb, PetscReal omega, MatSORType flag, PetscReal fshift, PetscInt its, PetscInt lits, Vec xx) 2608 { 2609 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ *)matin->data; 2610 PetscInt mbs = mat->mbs, bs = matin->rmap->bs; 2611 PetscScalar *x, *ptr, *from; 2612 Vec bb1; 2613 const PetscScalar *b; 2614 2615 PetscFunctionBegin; 2616 PetscCheck(its > 0 && lits > 0, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Relaxation requires global its %" PetscInt_FMT " and local its %" PetscInt_FMT " both positive", its, lits); 2617 PetscCheck(bs <= 1, PETSC_COMM_SELF, PETSC_ERR_SUP, "SSOR for block size > 1 is not yet implemented"); 2618 2619 if (flag == SOR_APPLY_UPPER) { 2620 PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx)); 2621 PetscFunctionReturn(PETSC_SUCCESS); 2622 } 2623 2624 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2625 if (flag & SOR_ZERO_INITIAL_GUESS) { 2626 PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, lits, xx)); 2627 its--; 2628 } 2629 2630 PetscCall(VecDuplicate(bb, &bb1)); 2631 while (its--) { 2632 /* lower triangular part: slvec0b = - B^T*xx */ 2633 PetscCall((*mat->B->ops->multtranspose)(mat->B, xx, mat->slvec0b)); 2634 2635 /* copy xx into slvec0a */ 2636 PetscCall(VecGetArray(mat->slvec0, &ptr)); 2637 PetscCall(VecGetArray(xx, &x)); 2638 PetscCall(PetscArraycpy(ptr, x, bs * mbs)); 2639 PetscCall(VecRestoreArray(mat->slvec0, &ptr)); 2640 2641 PetscCall(VecScale(mat->slvec0, -1.0)); 2642 2643 /* copy bb into slvec1a */ 2644 PetscCall(VecGetArray(mat->slvec1, &ptr)); 2645 PetscCall(VecGetArrayRead(bb, &b)); 2646 PetscCall(PetscArraycpy(ptr, b, bs * mbs)); 2647 PetscCall(VecRestoreArray(mat->slvec1, &ptr)); 2648 2649 /* set slvec1b = 0 */ 2650 PetscCall(PetscObjectStateIncrease((PetscObject)mat->slvec1b)); 2651 PetscCall(VecZeroEntries(mat->slvec1b)); 2652 2653 PetscCall(VecScatterBegin(mat->sMvctx, mat->slvec0, mat->slvec1, ADD_VALUES, SCATTER_FORWARD)); 2654 PetscCall(VecRestoreArray(xx, &x)); 2655 PetscCall(VecRestoreArrayRead(bb, &b)); 2656 PetscCall(VecScatterEnd(mat->sMvctx, mat->slvec0, mat->slvec1, ADD_VALUES, SCATTER_FORWARD)); 2657 2658 /* upper triangular part: bb1 = bb1 - B*x */ 2659 PetscCall((*mat->B->ops->multadd)(mat->B, mat->slvec1b, mat->slvec1a, bb1)); 2660 2661 /* local diagonal sweep */ 2662 PetscCall((*mat->A->ops->sor)(mat->A, bb1, omega, SOR_SYMMETRIC_SWEEP, fshift, lits, lits, xx)); 2663 } 2664 PetscCall(VecDestroy(&bb1)); 2665 } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2666 PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx)); 2667 } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) { 2668 PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx)); 2669 } else if (flag & SOR_EISENSTAT) { 2670 Vec xx1; 2671 PetscBool hasop; 2672 const PetscScalar *diag; 2673 PetscScalar *sl, scale = (omega - 2.0) / omega; 2674 PetscInt i, n; 2675 2676 if (!mat->xx1) { 2677 PetscCall(VecDuplicate(bb, &mat->xx1)); 2678 PetscCall(VecDuplicate(bb, &mat->bb1)); 2679 } 2680 xx1 = mat->xx1; 2681 bb1 = mat->bb1; 2682 2683 PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, (MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP), fshift, lits, 1, xx)); 2684 2685 if (!mat->diag) { 2686 /* this is wrong for same matrix with new nonzero values */ 2687 PetscCall(MatCreateVecs(matin, &mat->diag, NULL)); 2688 PetscCall(MatGetDiagonal(matin, mat->diag)); 2689 } 2690 PetscCall(MatHasOperation(matin, MATOP_MULT_DIAGONAL_BLOCK, &hasop)); 2691 2692 if (hasop) { 2693 PetscCall(MatMultDiagonalBlock(matin, xx, bb1)); 2694 PetscCall(VecAYPX(mat->slvec1a, scale, bb)); 2695 } else { 2696 /* 2697 These two lines are replaced by code that may be a bit faster for a good compiler 2698 PetscCall(VecPointwiseMult(mat->slvec1a,mat->diag,xx)); 2699 PetscCall(VecAYPX(mat->slvec1a,scale,bb)); 2700 */ 2701 PetscCall(VecGetArray(mat->slvec1a, &sl)); 2702 PetscCall(VecGetArrayRead(mat->diag, &diag)); 2703 PetscCall(VecGetArrayRead(bb, &b)); 2704 PetscCall(VecGetArray(xx, &x)); 2705 PetscCall(VecGetLocalSize(xx, &n)); 2706 if (omega == 1.0) { 2707 for (i = 0; i < n; i++) sl[i] = b[i] - diag[i] * x[i]; 2708 PetscCall(PetscLogFlops(2.0 * n)); 2709 } else { 2710 for (i = 0; i < n; i++) sl[i] = b[i] + scale * diag[i] * x[i]; 2711 PetscCall(PetscLogFlops(3.0 * n)); 2712 } 2713 PetscCall(VecRestoreArray(mat->slvec1a, &sl)); 2714 PetscCall(VecRestoreArrayRead(mat->diag, &diag)); 2715 PetscCall(VecRestoreArrayRead(bb, &b)); 2716 PetscCall(VecRestoreArray(xx, &x)); 2717 } 2718 2719 /* multiply off-diagonal portion of matrix */ 2720 PetscCall(PetscObjectStateIncrease((PetscObject)mat->slvec1b)); 2721 PetscCall(VecZeroEntries(mat->slvec1b)); 2722 PetscCall((*mat->B->ops->multtranspose)(mat->B, xx, mat->slvec0b)); 2723 PetscCall(VecGetArray(mat->slvec0, &from)); 2724 PetscCall(VecGetArray(xx, &x)); 2725 PetscCall(PetscArraycpy(from, x, bs * mbs)); 2726 PetscCall(VecRestoreArray(mat->slvec0, &from)); 2727 PetscCall(VecRestoreArray(xx, &x)); 2728 PetscCall(VecScatterBegin(mat->sMvctx, mat->slvec0, mat->slvec1, ADD_VALUES, SCATTER_FORWARD)); 2729 PetscCall(VecScatterEnd(mat->sMvctx, mat->slvec0, mat->slvec1, ADD_VALUES, SCATTER_FORWARD)); 2730 PetscCall((*mat->B->ops->multadd)(mat->B, mat->slvec1b, mat->slvec1a, mat->slvec1a)); 2731 2732 /* local sweep */ 2733 PetscCall((*mat->A->ops->sor)(mat->A, mat->slvec1a, omega, (MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP), fshift, lits, 1, xx1)); 2734 PetscCall(VecAXPY(xx, 1.0, xx1)); 2735 } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatSORType is not supported for SBAIJ matrix format"); 2736 PetscFunctionReturn(PETSC_SUCCESS); 2737 } 2738 2739 /*@ 2740 MatCreateMPISBAIJWithArrays - creates a `MATMPISBAIJ` matrix using arrays that contain in standard 2741 CSR format the local rows. 2742 2743 Collective 2744 2745 Input Parameters: 2746 + comm - MPI communicator 2747 . bs - the block size, only a block size of 1 is supported 2748 . m - number of local rows (Cannot be `PETSC_DECIDE`) 2749 . n - This value should be the same as the local size used in creating the 2750 x vector for the matrix-vector product y = Ax. (or `PETSC_DECIDE` to have 2751 calculated if `N` is given) For square matrices `n` is almost always `m`. 2752 . M - number of global rows (or `PETSC_DETERMINE` to have calculated if `m` is given) 2753 . N - number of global columns (or `PETSC_DETERMINE` to have calculated if `n` is given) 2754 . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of block elements in that row block row of the matrix 2755 . j - column indices 2756 - a - matrix values 2757 2758 Output Parameter: 2759 . mat - the matrix 2760 2761 Level: intermediate 2762 2763 Notes: 2764 The `i`, `j`, and `a` arrays ARE copied by this routine into the internal format used by PETSc; 2765 thus you CANNOT change the matrix entries by changing the values of `a` after you have 2766 called this routine. Use `MatCreateMPIAIJWithSplitArrays()` to avoid needing to copy the arrays. 2767 2768 The `i` and `j` indices are 0 based, and `i` indices are indices corresponding to the local `j` array. 2769 2770 .seealso: [](ch_matrices), `Mat`, `MATMPISBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatMPIAIJSetPreallocation()`, `MatMPIAIJSetPreallocationCSR()`, 2771 `MPIAIJ`, `MatCreateAIJ()`, `MatCreateMPIAIJWithSplitArrays()` 2772 @*/ 2773 PetscErrorCode MatCreateMPISBAIJWithArrays(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt M, PetscInt N, const PetscInt i[], const PetscInt j[], const PetscScalar a[], Mat *mat) 2774 { 2775 PetscFunctionBegin; 2776 PetscCheck(!i[0], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "i (row indices) must start with 0"); 2777 PetscCheck(m >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "local number of rows (m) cannot be PETSC_DECIDE, or negative"); 2778 PetscCall(MatCreate(comm, mat)); 2779 PetscCall(MatSetSizes(*mat, m, n, M, N)); 2780 PetscCall(MatSetType(*mat, MATMPISBAIJ)); 2781 PetscCall(MatMPISBAIJSetPreallocationCSR(*mat, bs, i, j, a)); 2782 PetscFunctionReturn(PETSC_SUCCESS); 2783 } 2784 2785 /*@C 2786 MatMPISBAIJSetPreallocationCSR - Creates a sparse parallel matrix in `MATMPISBAIJ` format using the given nonzero structure and (optional) numerical values 2787 2788 Collective 2789 2790 Input Parameters: 2791 + B - the matrix 2792 . bs - the block size 2793 . i - the indices into `j` for the start of each local row (starts with zero) 2794 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2795 - v - optional values in the matrix 2796 2797 Level: advanced 2798 2799 Notes: 2800 Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries 2801 and usually the numerical values as well 2802 2803 Any entries below the diagonal are ignored 2804 2805 .seealso: [](ch_matrices), `Mat`, `MATMPISBAIJ`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatMPIBAIJSetPreallocation()`, `MatCreateAIJ()`, `MPIAIJ` 2806 @*/ 2807 PetscErrorCode MatMPISBAIJSetPreallocationCSR(Mat B, PetscInt bs, const PetscInt i[], const PetscInt j[], const PetscScalar v[]) 2808 { 2809 PetscFunctionBegin; 2810 PetscTryMethod(B, "MatMPISBAIJSetPreallocationCSR_C", (Mat, PetscInt, const PetscInt[], const PetscInt[], const PetscScalar[]), (B, bs, i, j, v)); 2811 PetscFunctionReturn(PETSC_SUCCESS); 2812 } 2813 2814 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm, Mat inmat, PetscInt n, MatReuse scall, Mat *outmat) 2815 { 2816 PetscInt m, N, i, rstart, nnz, Ii, bs, cbs; 2817 PetscInt *indx; 2818 PetscScalar *values; 2819 2820 PetscFunctionBegin; 2821 PetscCall(MatGetSize(inmat, &m, &N)); 2822 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 2823 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ *)inmat->data; 2824 PetscInt *dnz, *onz, mbs, Nbs, nbs; 2825 PetscInt *bindx, rmax = a->rmax, j; 2826 PetscMPIInt rank, size; 2827 2828 PetscCall(MatGetBlockSizes(inmat, &bs, &cbs)); 2829 mbs = m / bs; 2830 Nbs = N / cbs; 2831 if (n == PETSC_DECIDE) PetscCall(PetscSplitOwnershipBlock(comm, cbs, &n, &N)); 2832 nbs = n / cbs; 2833 2834 PetscCall(PetscMalloc1(rmax, &bindx)); 2835 MatPreallocateBegin(comm, mbs, nbs, dnz, onz); /* inline function, output __end and __rstart are used below */ 2836 2837 PetscCallMPI(MPI_Comm_rank(comm, &rank)); 2838 PetscCallMPI(MPI_Comm_rank(comm, &size)); 2839 if (rank == size - 1) { 2840 /* Check sum(nbs) = Nbs */ 2841 PetscCheck(__end == Nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Sum of local block columns %" PetscInt_FMT " != global block columns %" PetscInt_FMT, __end, Nbs); 2842 } 2843 2844 rstart = __rstart; /* block rstart of *outmat; see inline function MatPreallocateBegin */ 2845 PetscCall(MatSetOption(inmat, MAT_GETROW_UPPERTRIANGULAR, PETSC_TRUE)); 2846 for (i = 0; i < mbs; i++) { 2847 PetscCall(MatGetRow_SeqSBAIJ(inmat, i * bs, &nnz, &indx, NULL)); /* non-blocked nnz and indx */ 2848 nnz = nnz / bs; 2849 for (j = 0; j < nnz; j++) bindx[j] = indx[j * bs] / bs; 2850 PetscCall(MatPreallocateSet(i + rstart, nnz, bindx, dnz, onz)); 2851 PetscCall(MatRestoreRow_SeqSBAIJ(inmat, i * bs, &nnz, &indx, NULL)); 2852 } 2853 PetscCall(MatSetOption(inmat, MAT_GETROW_UPPERTRIANGULAR, PETSC_FALSE)); 2854 PetscCall(PetscFree(bindx)); 2855 2856 PetscCall(MatCreate(comm, outmat)); 2857 PetscCall(MatSetSizes(*outmat, m, n, PETSC_DETERMINE, PETSC_DETERMINE)); 2858 PetscCall(MatSetBlockSizes(*outmat, bs, cbs)); 2859 PetscCall(MatSetType(*outmat, MATSBAIJ)); 2860 PetscCall(MatSeqSBAIJSetPreallocation(*outmat, bs, 0, dnz)); 2861 PetscCall(MatMPISBAIJSetPreallocation(*outmat, bs, 0, dnz, 0, onz)); 2862 MatPreallocateEnd(dnz, onz); 2863 } 2864 2865 /* numeric phase */ 2866 PetscCall(MatGetBlockSizes(inmat, &bs, &cbs)); 2867 PetscCall(MatGetOwnershipRange(*outmat, &rstart, NULL)); 2868 2869 PetscCall(MatSetOption(inmat, MAT_GETROW_UPPERTRIANGULAR, PETSC_TRUE)); 2870 for (i = 0; i < m; i++) { 2871 PetscCall(MatGetRow_SeqSBAIJ(inmat, i, &nnz, &indx, &values)); 2872 Ii = i + rstart; 2873 PetscCall(MatSetValues(*outmat, 1, &Ii, nnz, indx, values, INSERT_VALUES)); 2874 PetscCall(MatRestoreRow_SeqSBAIJ(inmat, i, &nnz, &indx, &values)); 2875 } 2876 PetscCall(MatSetOption(inmat, MAT_GETROW_UPPERTRIANGULAR, PETSC_FALSE)); 2877 PetscCall(MatAssemblyBegin(*outmat, MAT_FINAL_ASSEMBLY)); 2878 PetscCall(MatAssemblyEnd(*outmat, MAT_FINAL_ASSEMBLY)); 2879 PetscFunctionReturn(PETSC_SUCCESS); 2880 } 2881