1 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 2 #include <../src/mat/impls/sell/mpi/mpisell.h> /*I "petscmat.h" I*/ 3 #include <petsc/private/vecimpl.h> 4 #include <petsc/private/isimpl.h> 5 #include <petscblaslapack.h> 6 #include <petscsf.h> 7 8 /*MC 9 MATSELL - MATSELL = "sell" - A matrix type to be used for sparse matrices. 10 11 This matrix type is identical to `MATSEQSELL` when constructed with a single process communicator, 12 and `MATMPISELL` otherwise. As a result, for single process communicators, 13 `MatSeqSELLSetPreallocation()` is supported, and similarly `MatMPISELLSetPreallocation()` is supported 14 for communicators controlling multiple processes. It is recommended that you call both of 15 the above preallocation routines for simplicity. 16 17 Options Database Keys: 18 . -mat_type sell - sets the matrix type to `MATSELL` during a call to `MatSetFromOptions()` 19 20 Level: beginner 21 22 .seealso: `Mat`, `MATAIJ`, `MATBAIJ`, `MATSBAIJ`, `MatCreateSELL()`, `MatCreateSeqSELL()`, `MATSEQSELL`, `MATMPISELL` 23 M*/ 24 25 static PetscErrorCode MatDiagonalSet_MPISELL(Mat Y, Vec D, InsertMode is) 26 { 27 Mat_MPISELL *sell = (Mat_MPISELL *)Y->data; 28 29 PetscFunctionBegin; 30 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 31 PetscCall(MatDiagonalSet(sell->A, D, is)); 32 } else { 33 PetscCall(MatDiagonalSet_Default(Y, D, is)); 34 } 35 PetscFunctionReturn(PETSC_SUCCESS); 36 } 37 38 /* 39 Local utility routine that creates a mapping from the global column 40 number to the local number in the off-diagonal part of the local 41 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 42 a slightly higher hash table cost; without it it is not scalable (each processor 43 has an order N integer array but is fast to access. 44 */ 45 PetscErrorCode MatCreateColmap_MPISELL_Private(Mat mat) 46 { 47 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 48 PetscInt n = sell->B->cmap->n, i; 49 50 PetscFunctionBegin; 51 PetscCheck(sell->garray, PETSC_COMM_SELF, PETSC_ERR_PLIB, "MPISELL Matrix was assembled but is missing garray"); 52 #if defined(PETSC_USE_CTABLE) 53 PetscCall(PetscHMapICreateWithSize(n, &sell->colmap)); 54 for (i = 0; i < n; i++) PetscCall(PetscHMapISet(sell->colmap, sell->garray[i] + 1, i + 1)); 55 #else 56 PetscCall(PetscCalloc1(mat->cmap->N + 1, &sell->colmap)); 57 for (i = 0; i < n; i++) sell->colmap[sell->garray[i]] = i + 1; 58 #endif 59 PetscFunctionReturn(PETSC_SUCCESS); 60 } 61 62 #define MatSetValues_SeqSELL_A_Private(row, col, value, addv, orow, ocol) \ 63 { \ 64 if (col <= lastcol1) low1 = 0; \ 65 else high1 = nrow1; \ 66 lastcol1 = col; \ 67 while (high1 - low1 > 5) { \ 68 t = (low1 + high1) / 2; \ 69 if (cp1[sliceheight * t] > col) high1 = t; \ 70 else low1 = t; \ 71 } \ 72 for (_i = low1; _i < high1; _i++) { \ 73 if (cp1[sliceheight * _i] > col) break; \ 74 if (cp1[sliceheight * _i] == col) { \ 75 if (addv == ADD_VALUES) vp1[sliceheight * _i] += value; \ 76 else vp1[sliceheight * _i] = value; \ 77 inserted = PETSC_TRUE; \ 78 goto a_noinsert; \ 79 } \ 80 } \ 81 if (value == 0.0 && ignorezeroentries) { \ 82 low1 = 0; \ 83 high1 = nrow1; \ 84 goto a_noinsert; \ 85 } \ 86 if (nonew == 1) { \ 87 low1 = 0; \ 88 high1 = nrow1; \ 89 goto a_noinsert; \ 90 } \ 91 PetscCheck(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); \ 92 MatSeqXSELLReallocateSELL(A, am, 1, nrow1, a->sliidx, a->sliceheight, row / sliceheight, row, col, a->colidx, a->val, cp1, vp1, nonew, MatScalar); \ 93 /* shift up all the later entries in this row */ \ 94 for (ii = nrow1 - 1; ii >= _i; ii--) { \ 95 cp1[sliceheight * (ii + 1)] = cp1[sliceheight * ii]; \ 96 vp1[sliceheight * (ii + 1)] = vp1[sliceheight * ii]; \ 97 } \ 98 cp1[sliceheight * _i] = col; \ 99 vp1[sliceheight * _i] = value; \ 100 a->nz++; \ 101 nrow1++; \ 102 a_noinsert:; \ 103 a->rlen[row] = nrow1; \ 104 } 105 106 #define MatSetValues_SeqSELL_B_Private(row, col, value, addv, orow, ocol) \ 107 { \ 108 if (col <= lastcol2) low2 = 0; \ 109 else high2 = nrow2; \ 110 lastcol2 = col; \ 111 while (high2 - low2 > 5) { \ 112 t = (low2 + high2) / 2; \ 113 if (cp2[sliceheight * t] > col) high2 = t; \ 114 else low2 = t; \ 115 } \ 116 for (_i = low2; _i < high2; _i++) { \ 117 if (cp2[sliceheight * _i] > col) break; \ 118 if (cp2[sliceheight * _i] == col) { \ 119 if (addv == ADD_VALUES) vp2[sliceheight * _i] += value; \ 120 else vp2[sliceheight * _i] = value; \ 121 inserted = PETSC_TRUE; \ 122 goto b_noinsert; \ 123 } \ 124 } \ 125 if (value == 0.0 && ignorezeroentries) { \ 126 low2 = 0; \ 127 high2 = nrow2; \ 128 goto b_noinsert; \ 129 } \ 130 if (nonew == 1) { \ 131 low2 = 0; \ 132 high2 = nrow2; \ 133 goto b_noinsert; \ 134 } \ 135 PetscCheck(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); \ 136 MatSeqXSELLReallocateSELL(B, bm, 1, nrow2, b->sliidx, b->sliceheight, row / sliceheight, row, col, b->colidx, b->val, cp2, vp2, nonew, MatScalar); \ 137 /* shift up all the later entries in this row */ \ 138 for (ii = nrow2 - 1; ii >= _i; ii--) { \ 139 cp2[sliceheight * (ii + 1)] = cp2[sliceheight * ii]; \ 140 vp2[sliceheight * (ii + 1)] = vp2[sliceheight * ii]; \ 141 } \ 142 cp2[sliceheight * _i] = col; \ 143 vp2[sliceheight * _i] = value; \ 144 b->nz++; \ 145 nrow2++; \ 146 b_noinsert:; \ 147 b->rlen[row] = nrow2; \ 148 } 149 150 static PetscErrorCode MatSetValues_MPISELL(Mat mat, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode addv) 151 { 152 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 153 PetscScalar value; 154 PetscInt i, j, rstart = mat->rmap->rstart, rend = mat->rmap->rend, shift1, shift2; 155 PetscInt cstart = mat->cmap->rstart, cend = mat->cmap->rend, row, col; 156 PetscBool roworiented = sell->roworiented; 157 158 /* Some Variables required in the macro */ 159 Mat A = sell->A; 160 Mat_SeqSELL *a = (Mat_SeqSELL *)A->data; 161 PetscBool ignorezeroentries = a->ignorezeroentries, found; 162 Mat B = sell->B; 163 Mat_SeqSELL *b = (Mat_SeqSELL *)B->data; 164 PetscInt *cp1, *cp2, ii, _i, nrow1, nrow2, low1, high1, low2, high2, t, lastcol1, lastcol2, sliceheight = a->sliceheight; 165 MatScalar *vp1, *vp2; 166 167 PetscFunctionBegin; 168 for (i = 0; i < m; i++) { 169 if (im[i] < 0) continue; 170 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); 171 if (im[i] >= rstart && im[i] < rend) { 172 row = im[i] - rstart; 173 lastcol1 = -1; 174 shift1 = a->sliidx[row / sliceheight] + (row % sliceheight); /* starting index of the row */ 175 cp1 = PetscSafePointerPlusOffset(a->colidx, shift1); 176 vp1 = PetscSafePointerPlusOffset(a->val, shift1); 177 nrow1 = a->rlen[row]; 178 low1 = 0; 179 high1 = nrow1; 180 lastcol2 = -1; 181 shift2 = b->sliidx[row / sliceheight] + (row % sliceheight); /* starting index of the row */ 182 cp2 = PetscSafePointerPlusOffset(b->colidx, shift2); 183 vp2 = PetscSafePointerPlusOffset(b->val, shift2); 184 nrow2 = b->rlen[row]; 185 low2 = 0; 186 high2 = nrow2; 187 188 for (j = 0; j < n; j++) { 189 if (roworiented) value = v[i * n + j]; 190 else value = v[i + j * m]; 191 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 192 if (in[j] >= cstart && in[j] < cend) { 193 col = in[j] - cstart; 194 MatSetValue_SeqSELL_Private(A, row, col, value, addv, im[i], in[j], cp1, vp1, lastcol1, low1, high1); /* set one value */ 195 #if defined(PETSC_HAVE_CUDA) 196 if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && found) A->offloadmask = PETSC_OFFLOAD_CPU; 197 #endif 198 } else if (in[j] < 0) { 199 continue; 200 } else { 201 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); 202 if (mat->was_assembled) { 203 if (!sell->colmap) PetscCall(MatCreateColmap_MPISELL_Private(mat)); 204 #if defined(PETSC_USE_CTABLE) 205 PetscCall(PetscHMapIGetWithDefault(sell->colmap, in[j] + 1, 0, &col)); 206 col--; 207 #else 208 col = sell->colmap[in[j]] - 1; 209 #endif 210 if (col < 0 && !((Mat_SeqSELL *)sell->B->data)->nonew) { 211 PetscCall(MatDisAssemble_MPISELL(mat)); 212 col = in[j]; 213 /* Reinitialize the variables required by MatSetValues_SeqSELL_B_Private() */ 214 B = sell->B; 215 b = (Mat_SeqSELL *)B->data; 216 shift2 = b->sliidx[row / sliceheight] + (row % sliceheight); /* starting index of the row */ 217 cp2 = b->colidx + shift2; 218 vp2 = b->val + shift2; 219 nrow2 = b->rlen[row]; 220 low2 = 0; 221 high2 = nrow2; 222 found = PETSC_FALSE; 223 } else { 224 PetscCheck(col >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero at global row/column (%" PetscInt_FMT ", %" PetscInt_FMT ") into matrix", im[i], in[j]); 225 } 226 } else col = in[j]; 227 MatSetValue_SeqSELL_Private(B, row, col, value, addv, im[i], in[j], cp2, vp2, lastcol2, low2, high2); /* set one value */ 228 #if defined(PETSC_HAVE_CUDA) 229 if (B->offloadmask != PETSC_OFFLOAD_UNALLOCATED && found) B->offloadmask = PETSC_OFFLOAD_CPU; 230 #endif 231 } 232 } 233 } else { 234 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]); 235 if (!sell->donotstash) { 236 mat->assembled = PETSC_FALSE; 237 if (roworiented) { 238 PetscCall(MatStashValuesRow_Private(&mat->stash, im[i], n, in, v + i * n, (PetscBool)(ignorezeroentries && (addv == ADD_VALUES)))); 239 } else { 240 PetscCall(MatStashValuesCol_Private(&mat->stash, im[i], n, in, v + i, m, (PetscBool)(ignorezeroentries && (addv == ADD_VALUES)))); 241 } 242 } 243 } 244 } 245 PetscFunctionReturn(PETSC_SUCCESS); 246 } 247 248 static PetscErrorCode MatGetValues_MPISELL(Mat mat, PetscInt m, const PetscInt idxm[], PetscInt n, const PetscInt idxn[], PetscScalar v[]) 249 { 250 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 251 PetscInt i, j, rstart = mat->rmap->rstart, rend = mat->rmap->rend; 252 PetscInt cstart = mat->cmap->rstart, cend = mat->cmap->rend, row, col; 253 254 PetscFunctionBegin; 255 for (i = 0; i < m; i++) { 256 if (idxm[i] < 0) continue; /* negative row */ 257 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); 258 PetscCheck(idxm[i] >= rstart && idxm[i] < rend, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only local values currently supported"); 259 row = idxm[i] - rstart; 260 for (j = 0; j < n; j++) { 261 if (idxn[j] < 0) continue; /* negative column */ 262 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); 263 if (idxn[j] >= cstart && idxn[j] < cend) { 264 col = idxn[j] - cstart; 265 PetscCall(MatGetValues(sell->A, 1, &row, 1, &col, v + i * n + j)); 266 } else { 267 if (!sell->colmap) PetscCall(MatCreateColmap_MPISELL_Private(mat)); 268 #if defined(PETSC_USE_CTABLE) 269 PetscCall(PetscHMapIGetWithDefault(sell->colmap, idxn[j] + 1, 0, &col)); 270 col--; 271 #else 272 col = sell->colmap[idxn[j]] - 1; 273 #endif 274 if (col < 0 || sell->garray[col] != idxn[j]) *(v + i * n + j) = 0.0; 275 else PetscCall(MatGetValues(sell->B, 1, &row, 1, &col, v + i * n + j)); 276 } 277 } 278 } 279 PetscFunctionReturn(PETSC_SUCCESS); 280 } 281 282 static PetscErrorCode MatAssemblyBegin_MPISELL(Mat mat, MatAssemblyType mode) 283 { 284 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 285 PetscInt nstash, reallocs; 286 287 PetscFunctionBegin; 288 if (sell->donotstash || mat->nooffprocentries) PetscFunctionReturn(PETSC_SUCCESS); 289 290 PetscCall(MatStashScatterBegin_Private(mat, &mat->stash, mat->rmap->range)); 291 PetscCall(MatStashGetInfo_Private(&mat->stash, &nstash, &reallocs)); 292 PetscCall(PetscInfo(sell->A, "Stash has %" PetscInt_FMT " entries, uses %" PetscInt_FMT " mallocs.\n", nstash, reallocs)); 293 PetscFunctionReturn(PETSC_SUCCESS); 294 } 295 296 PetscErrorCode MatAssemblyEnd_MPISELL(Mat mat, MatAssemblyType mode) 297 { 298 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 299 PetscMPIInt n; 300 PetscInt i, flg; 301 PetscInt *row, *col; 302 PetscScalar *val; 303 PetscBool all_assembled; 304 /* do not use 'b = (Mat_SeqSELL*)sell->B->data' as B can be reset in disassembly */ 305 PetscFunctionBegin; 306 if (!sell->donotstash && !mat->nooffprocentries) { 307 while (1) { 308 PetscCall(MatStashScatterGetMesg_Private(&mat->stash, &n, &row, &col, &val, &flg)); 309 if (!flg) break; 310 311 for (i = 0; i < n; i++) { /* assemble one by one */ 312 PetscCall(MatSetValues_MPISELL(mat, 1, row + i, 1, col + i, val + i, mat->insertmode)); 313 } 314 } 315 PetscCall(MatStashScatterEnd_Private(&mat->stash)); 316 } 317 #if defined(PETSC_HAVE_CUDA) 318 if (mat->offloadmask == PETSC_OFFLOAD_CPU) sell->A->offloadmask = PETSC_OFFLOAD_CPU; 319 #endif 320 PetscCall(MatAssemblyBegin(sell->A, mode)); 321 PetscCall(MatAssemblyEnd(sell->A, mode)); 322 323 /* 324 determine if any process has disassembled, if so we must 325 also disassemble ourselves, in order that we may reassemble. 326 */ 327 /* 328 if nonzero structure of submatrix B cannot change then we know that 329 no process disassembled thus we can skip this stuff 330 */ 331 if (!((Mat_SeqSELL *)sell->B->data)->nonew) { 332 PetscCallMPI(MPIU_Allreduce(&mat->was_assembled, &all_assembled, 1, MPI_C_BOOL, MPI_LAND, PetscObjectComm((PetscObject)mat))); 333 if (mat->was_assembled && !all_assembled) PetscCall(MatDisAssemble_MPISELL(mat)); 334 } 335 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) PetscCall(MatSetUpMultiply_MPISELL(mat)); 336 #if defined(PETSC_HAVE_CUDA) 337 if (mat->offloadmask == PETSC_OFFLOAD_CPU && sell->B->offloadmask != PETSC_OFFLOAD_UNALLOCATED) sell->B->offloadmask = PETSC_OFFLOAD_CPU; 338 #endif 339 PetscCall(MatAssemblyBegin(sell->B, mode)); 340 PetscCall(MatAssemblyEnd(sell->B, mode)); 341 PetscCall(PetscFree2(sell->rowvalues, sell->rowindices)); 342 sell->rowvalues = NULL; 343 PetscCall(VecDestroy(&sell->diag)); 344 345 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 346 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqSELL *)sell->A->data)->nonew) { 347 PetscObjectState state = sell->A->nonzerostate + sell->B->nonzerostate; 348 PetscCallMPI(MPIU_Allreduce(&state, &mat->nonzerostate, 1, MPIU_INT64, MPI_SUM, PetscObjectComm((PetscObject)mat))); 349 } 350 #if defined(PETSC_HAVE_CUDA) 351 mat->offloadmask = PETSC_OFFLOAD_BOTH; 352 #endif 353 PetscFunctionReturn(PETSC_SUCCESS); 354 } 355 356 static PetscErrorCode MatZeroEntries_MPISELL(Mat A) 357 { 358 Mat_MPISELL *l = (Mat_MPISELL *)A->data; 359 360 PetscFunctionBegin; 361 PetscCall(MatZeroEntries(l->A)); 362 PetscCall(MatZeroEntries(l->B)); 363 PetscFunctionReturn(PETSC_SUCCESS); 364 } 365 366 static PetscErrorCode MatMult_MPISELL(Mat A, Vec xx, Vec yy) 367 { 368 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 369 PetscInt nt; 370 371 PetscFunctionBegin; 372 PetscCall(VecGetLocalSize(xx, &nt)); 373 PetscCheck(nt == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Incompatible partition of A (%" PetscInt_FMT ") and xx (%" PetscInt_FMT ")", A->cmap->n, nt); 374 PetscCall(VecScatterBegin(a->Mvctx, xx, a->lvec, INSERT_VALUES, SCATTER_FORWARD)); 375 PetscCall((*a->A->ops->mult)(a->A, xx, yy)); 376 PetscCall(VecScatterEnd(a->Mvctx, xx, a->lvec, INSERT_VALUES, SCATTER_FORWARD)); 377 PetscCall((*a->B->ops->multadd)(a->B, a->lvec, yy, yy)); 378 PetscFunctionReturn(PETSC_SUCCESS); 379 } 380 381 static PetscErrorCode MatMultDiagonalBlock_MPISELL(Mat A, Vec bb, Vec xx) 382 { 383 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 384 385 PetscFunctionBegin; 386 PetscCall(MatMultDiagonalBlock(a->A, bb, xx)); 387 PetscFunctionReturn(PETSC_SUCCESS); 388 } 389 390 static PetscErrorCode MatMultAdd_MPISELL(Mat A, Vec xx, Vec yy, Vec zz) 391 { 392 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 393 394 PetscFunctionBegin; 395 PetscCall(VecScatterBegin(a->Mvctx, xx, a->lvec, INSERT_VALUES, SCATTER_FORWARD)); 396 PetscCall((*a->A->ops->multadd)(a->A, xx, yy, zz)); 397 PetscCall(VecScatterEnd(a->Mvctx, xx, a->lvec, INSERT_VALUES, SCATTER_FORWARD)); 398 PetscCall((*a->B->ops->multadd)(a->B, a->lvec, zz, zz)); 399 PetscFunctionReturn(PETSC_SUCCESS); 400 } 401 402 static PetscErrorCode MatMultTranspose_MPISELL(Mat A, Vec xx, Vec yy) 403 { 404 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 405 406 PetscFunctionBegin; 407 /* do nondiagonal part */ 408 PetscCall((*a->B->ops->multtranspose)(a->B, xx, a->lvec)); 409 /* do local part */ 410 PetscCall((*a->A->ops->multtranspose)(a->A, xx, yy)); 411 /* add partial results together */ 412 PetscCall(VecScatterBegin(a->Mvctx, a->lvec, yy, ADD_VALUES, SCATTER_REVERSE)); 413 PetscCall(VecScatterEnd(a->Mvctx, a->lvec, yy, ADD_VALUES, SCATTER_REVERSE)); 414 PetscFunctionReturn(PETSC_SUCCESS); 415 } 416 417 static PetscErrorCode MatIsTranspose_MPISELL(Mat Amat, Mat Bmat, PetscReal tol, PetscBool *f) 418 { 419 MPI_Comm comm; 420 Mat_MPISELL *Asell = (Mat_MPISELL *)Amat->data, *Bsell; 421 Mat Adia = Asell->A, Bdia, Aoff, Boff, *Aoffs, *Boffs; 422 IS Me, Notme; 423 PetscInt M, N, first, last, *notme, i; 424 PetscMPIInt size; 425 426 PetscFunctionBegin; 427 /* Easy test: symmetric diagonal block */ 428 Bsell = (Mat_MPISELL *)Bmat->data; 429 Bdia = Bsell->A; 430 PetscCall(MatIsTranspose(Adia, Bdia, tol, f)); 431 if (!*f) PetscFunctionReturn(PETSC_SUCCESS); 432 PetscCall(PetscObjectGetComm((PetscObject)Amat, &comm)); 433 PetscCallMPI(MPI_Comm_size(comm, &size)); 434 if (size == 1) PetscFunctionReturn(PETSC_SUCCESS); 435 436 /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */ 437 PetscCall(MatGetSize(Amat, &M, &N)); 438 PetscCall(MatGetOwnershipRange(Amat, &first, &last)); 439 PetscCall(PetscMalloc1(N - last + first, ¬me)); 440 for (i = 0; i < first; i++) notme[i] = i; 441 for (i = last; i < M; i++) notme[i - last + first] = i; 442 PetscCall(ISCreateGeneral(MPI_COMM_SELF, N - last + first, notme, PETSC_COPY_VALUES, &Notme)); 443 PetscCall(ISCreateStride(MPI_COMM_SELF, last - first, first, 1, &Me)); 444 PetscCall(MatCreateSubMatrices(Amat, 1, &Me, &Notme, MAT_INITIAL_MATRIX, &Aoffs)); 445 Aoff = Aoffs[0]; 446 PetscCall(MatCreateSubMatrices(Bmat, 1, &Notme, &Me, MAT_INITIAL_MATRIX, &Boffs)); 447 Boff = Boffs[0]; 448 PetscCall(MatIsTranspose(Aoff, Boff, tol, f)); 449 PetscCall(MatDestroyMatrices(1, &Aoffs)); 450 PetscCall(MatDestroyMatrices(1, &Boffs)); 451 PetscCall(ISDestroy(&Me)); 452 PetscCall(ISDestroy(&Notme)); 453 PetscCall(PetscFree(notme)); 454 PetscFunctionReturn(PETSC_SUCCESS); 455 } 456 457 static PetscErrorCode MatMultTransposeAdd_MPISELL(Mat A, Vec xx, Vec yy, Vec zz) 458 { 459 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 460 461 PetscFunctionBegin; 462 /* do nondiagonal part */ 463 PetscCall((*a->B->ops->multtranspose)(a->B, xx, a->lvec)); 464 /* do local part */ 465 PetscCall((*a->A->ops->multtransposeadd)(a->A, xx, yy, zz)); 466 /* add partial results together */ 467 PetscCall(VecScatterBegin(a->Mvctx, a->lvec, zz, ADD_VALUES, SCATTER_REVERSE)); 468 PetscCall(VecScatterEnd(a->Mvctx, a->lvec, zz, ADD_VALUES, SCATTER_REVERSE)); 469 PetscFunctionReturn(PETSC_SUCCESS); 470 } 471 472 /* 473 This only works correctly for square matrices where the subblock A->A is the 474 diagonal block 475 */ 476 static PetscErrorCode MatGetDiagonal_MPISELL(Mat A, Vec v) 477 { 478 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 479 480 PetscFunctionBegin; 481 PetscCheck(A->rmap->N == A->cmap->N, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Supports only square matrix where A->A is diag block"); 482 PetscCheck(A->rmap->rstart == A->cmap->rstart && A->rmap->rend == A->cmap->rend, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "row partition must equal col partition"); 483 PetscCall(MatGetDiagonal(a->A, v)); 484 PetscFunctionReturn(PETSC_SUCCESS); 485 } 486 487 static PetscErrorCode MatScale_MPISELL(Mat A, PetscScalar aa) 488 { 489 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 490 491 PetscFunctionBegin; 492 PetscCall(MatScale(a->A, aa)); 493 PetscCall(MatScale(a->B, aa)); 494 PetscFunctionReturn(PETSC_SUCCESS); 495 } 496 497 PetscErrorCode MatDestroy_MPISELL(Mat mat) 498 { 499 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 500 501 PetscFunctionBegin; 502 PetscCall(PetscLogObjectState((PetscObject)mat, "Rows=%" PetscInt_FMT ", Cols=%" PetscInt_FMT, mat->rmap->N, mat->cmap->N)); 503 PetscCall(MatStashDestroy_Private(&mat->stash)); 504 PetscCall(VecDestroy(&sell->diag)); 505 PetscCall(MatDestroy(&sell->A)); 506 PetscCall(MatDestroy(&sell->B)); 507 #if defined(PETSC_USE_CTABLE) 508 PetscCall(PetscHMapIDestroy(&sell->colmap)); 509 #else 510 PetscCall(PetscFree(sell->colmap)); 511 #endif 512 PetscCall(PetscFree(sell->garray)); 513 PetscCall(VecDestroy(&sell->lvec)); 514 PetscCall(VecScatterDestroy(&sell->Mvctx)); 515 PetscCall(PetscFree2(sell->rowvalues, sell->rowindices)); 516 PetscCall(PetscFree(sell->ld)); 517 PetscCall(PetscFree(mat->data)); 518 519 PetscCall(PetscObjectChangeTypeName((PetscObject)mat, NULL)); 520 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatStoreValues_C", NULL)); 521 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatRetrieveValues_C", NULL)); 522 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatIsTranspose_C", NULL)); 523 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatMPISELLSetPreallocation_C", NULL)); 524 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpisell_mpiaij_C", NULL)); 525 #if defined(PETSC_HAVE_CUDA) 526 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpisell_mpisellcuda_C", NULL)); 527 #endif 528 PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDiagonalScaleLocal_C", NULL)); 529 PetscFunctionReturn(PETSC_SUCCESS); 530 } 531 532 #include <petscdraw.h> 533 static PetscErrorCode MatView_MPISELL_ASCIIorDraworSocket(Mat mat, PetscViewer viewer) 534 { 535 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 536 PetscMPIInt rank = sell->rank, size = sell->size; 537 PetscBool isdraw, isascii, isbinary; 538 PetscViewer sviewer; 539 PetscViewerFormat format; 540 541 PetscFunctionBegin; 542 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw)); 543 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii)); 544 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary)); 545 if (isascii) { 546 PetscCall(PetscViewerGetFormat(viewer, &format)); 547 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 548 MatInfo info; 549 PetscInt *inodes; 550 551 PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)mat), &rank)); 552 PetscCall(MatGetInfo(mat, MAT_LOCAL, &info)); 553 PetscCall(MatInodeGetInodeSizes(sell->A, NULL, &inodes, NULL)); 554 PetscCall(PetscViewerASCIIPushSynchronized(viewer)); 555 if (!inodes) { 556 PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] Local rows %" PetscInt_FMT " nz %" PetscInt_FMT " nz alloced %" PetscInt_FMT " mem %" PetscInt_FMT ", not using I-node routines\n", rank, mat->rmap->n, (PetscInt)info.nz_used, 557 (PetscInt)info.nz_allocated, (PetscInt)info.memory)); 558 } else { 559 PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] Local rows %" PetscInt_FMT " nz %" PetscInt_FMT " nz alloced %" PetscInt_FMT " mem %" PetscInt_FMT ", using I-node routines\n", rank, mat->rmap->n, (PetscInt)info.nz_used, 560 (PetscInt)info.nz_allocated, (PetscInt)info.memory)); 561 } 562 PetscCall(MatGetInfo(sell->A, MAT_LOCAL, &info)); 563 PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] on-diagonal part: nz %" PetscInt_FMT " \n", rank, (PetscInt)info.nz_used)); 564 PetscCall(MatGetInfo(sell->B, MAT_LOCAL, &info)); 565 PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] off-diagonal part: nz %" PetscInt_FMT " \n", rank, (PetscInt)info.nz_used)); 566 PetscCall(PetscViewerFlush(viewer)); 567 PetscCall(PetscViewerASCIIPopSynchronized(viewer)); 568 PetscCall(PetscViewerASCIIPrintf(viewer, "Information on VecScatter used in matrix-vector product: \n")); 569 PetscCall(VecScatterView(sell->Mvctx, viewer)); 570 PetscFunctionReturn(PETSC_SUCCESS); 571 } else if (format == PETSC_VIEWER_ASCII_INFO) { 572 PetscInt inodecount, inodelimit, *inodes; 573 PetscCall(MatInodeGetInodeSizes(sell->A, &inodecount, &inodes, &inodelimit)); 574 if (inodes) { 575 PetscCall(PetscViewerASCIIPrintf(viewer, "using I-node (on process 0) routines: found %" PetscInt_FMT " nodes, limit used is %" PetscInt_FMT "\n", inodecount, inodelimit)); 576 } else { 577 PetscCall(PetscViewerASCIIPrintf(viewer, "not using I-node (on process 0) routines\n")); 578 } 579 PetscFunctionReturn(PETSC_SUCCESS); 580 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 581 PetscFunctionReturn(PETSC_SUCCESS); 582 } 583 } else if (isbinary) { 584 if (size == 1) { 585 PetscCall(PetscObjectSetName((PetscObject)sell->A, ((PetscObject)mat)->name)); 586 PetscCall(MatView(sell->A, viewer)); 587 } else { 588 /* PetscCall(MatView_MPISELL_Binary(mat,viewer)); */ 589 } 590 PetscFunctionReturn(PETSC_SUCCESS); 591 } else if (isdraw) { 592 PetscDraw draw; 593 PetscBool isnull; 594 PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw)); 595 PetscCall(PetscDrawIsNull(draw, &isnull)); 596 if (isnull) PetscFunctionReturn(PETSC_SUCCESS); 597 } 598 599 { 600 /* assemble the entire matrix onto first processor. */ 601 Mat A; 602 Mat_SeqSELL *Aloc; 603 PetscInt M = mat->rmap->N, N = mat->cmap->N, *acolidx, row, col, i, j; 604 MatScalar *aval; 605 PetscBool isnonzero; 606 607 PetscCall(MatCreate(PetscObjectComm((PetscObject)mat), &A)); 608 if (rank == 0) { 609 PetscCall(MatSetSizes(A, M, N, M, N)); 610 } else { 611 PetscCall(MatSetSizes(A, 0, 0, M, N)); 612 } 613 /* This is just a temporary matrix, so explicitly using MATMPISELL is probably best */ 614 PetscCall(MatSetType(A, MATMPISELL)); 615 PetscCall(MatMPISELLSetPreallocation(A, 0, NULL, 0, NULL)); 616 PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_FALSE)); 617 618 /* copy over the A part */ 619 Aloc = (Mat_SeqSELL *)sell->A->data; 620 acolidx = Aloc->colidx; 621 aval = Aloc->val; 622 for (i = 0; i < Aloc->totalslices; i++) { /* loop over slices */ 623 for (j = Aloc->sliidx[i]; j < Aloc->sliidx[i + 1]; j++) { 624 isnonzero = (PetscBool)((j - Aloc->sliidx[i]) / Aloc->sliceheight < Aloc->rlen[i * Aloc->sliceheight + j % Aloc->sliceheight]); 625 if (isnonzero) { /* check the mask bit */ 626 row = i * Aloc->sliceheight + j % Aloc->sliceheight + mat->rmap->rstart; 627 col = *acolidx + mat->rmap->rstart; 628 PetscCall(MatSetValues(A, 1, &row, 1, &col, aval, INSERT_VALUES)); 629 } 630 aval++; 631 acolidx++; 632 } 633 } 634 635 /* copy over the B part */ 636 Aloc = (Mat_SeqSELL *)sell->B->data; 637 acolidx = Aloc->colidx; 638 aval = Aloc->val; 639 for (i = 0; i < Aloc->totalslices; i++) { 640 for (j = Aloc->sliidx[i]; j < Aloc->sliidx[i + 1]; j++) { 641 isnonzero = (PetscBool)((j - Aloc->sliidx[i]) / Aloc->sliceheight < Aloc->rlen[i * Aloc->sliceheight + j % Aloc->sliceheight]); 642 if (isnonzero) { 643 row = i * Aloc->sliceheight + j % Aloc->sliceheight + mat->rmap->rstart; 644 col = sell->garray[*acolidx]; 645 PetscCall(MatSetValues(A, 1, &row, 1, &col, aval, INSERT_VALUES)); 646 } 647 aval++; 648 acolidx++; 649 } 650 } 651 652 PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY)); 653 PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY)); 654 /* 655 Everyone has to call to draw the matrix since the graphics waits are 656 synchronized across all processors that share the PetscDraw object 657 */ 658 PetscCall(PetscViewerGetSubViewer(viewer, PETSC_COMM_SELF, &sviewer)); 659 if (rank == 0) { 660 PetscCall(PetscObjectSetName((PetscObject)((Mat_MPISELL *)A->data)->A, ((PetscObject)mat)->name)); 661 PetscCall(MatView_SeqSELL(((Mat_MPISELL *)A->data)->A, sviewer)); 662 } 663 PetscCall(PetscViewerRestoreSubViewer(viewer, PETSC_COMM_SELF, &sviewer)); 664 PetscCall(MatDestroy(&A)); 665 } 666 PetscFunctionReturn(PETSC_SUCCESS); 667 } 668 669 static PetscErrorCode MatView_MPISELL(Mat mat, PetscViewer viewer) 670 { 671 PetscBool isascii, isdraw, issocket, isbinary; 672 673 PetscFunctionBegin; 674 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii)); 675 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw)); 676 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary)); 677 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSOCKET, &issocket)); 678 if (isascii || isdraw || isbinary || issocket) PetscCall(MatView_MPISELL_ASCIIorDraworSocket(mat, viewer)); 679 PetscFunctionReturn(PETSC_SUCCESS); 680 } 681 682 static PetscErrorCode MatGetGhosts_MPISELL(Mat mat, PetscInt *nghosts, const PetscInt *ghosts[]) 683 { 684 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 685 686 PetscFunctionBegin; 687 PetscCall(MatGetSize(sell->B, NULL, nghosts)); 688 if (ghosts) *ghosts = sell->garray; 689 PetscFunctionReturn(PETSC_SUCCESS); 690 } 691 692 static PetscErrorCode MatGetInfo_MPISELL(Mat matin, MatInfoType flag, MatInfo *info) 693 { 694 Mat_MPISELL *mat = (Mat_MPISELL *)matin->data; 695 Mat A = mat->A, B = mat->B; 696 PetscLogDouble isend[5], irecv[5]; 697 698 PetscFunctionBegin; 699 info->block_size = 1.0; 700 PetscCall(MatGetInfo(A, MAT_LOCAL, info)); 701 702 isend[0] = info->nz_used; 703 isend[1] = info->nz_allocated; 704 isend[2] = info->nz_unneeded; 705 isend[3] = info->memory; 706 isend[4] = info->mallocs; 707 708 PetscCall(MatGetInfo(B, MAT_LOCAL, info)); 709 710 isend[0] += info->nz_used; 711 isend[1] += info->nz_allocated; 712 isend[2] += info->nz_unneeded; 713 isend[3] += info->memory; 714 isend[4] += info->mallocs; 715 if (flag == MAT_LOCAL) { 716 info->nz_used = isend[0]; 717 info->nz_allocated = isend[1]; 718 info->nz_unneeded = isend[2]; 719 info->memory = isend[3]; 720 info->mallocs = isend[4]; 721 } else if (flag == MAT_GLOBAL_MAX) { 722 PetscCallMPI(MPIU_Allreduce(isend, irecv, 5, MPIU_PETSCLOGDOUBLE, MPI_MAX, PetscObjectComm((PetscObject)matin))); 723 724 info->nz_used = irecv[0]; 725 info->nz_allocated = irecv[1]; 726 info->nz_unneeded = irecv[2]; 727 info->memory = irecv[3]; 728 info->mallocs = irecv[4]; 729 } else if (flag == MAT_GLOBAL_SUM) { 730 PetscCallMPI(MPIU_Allreduce(isend, irecv, 5, MPIU_PETSCLOGDOUBLE, MPI_SUM, PetscObjectComm((PetscObject)matin))); 731 732 info->nz_used = irecv[0]; 733 info->nz_allocated = irecv[1]; 734 info->nz_unneeded = irecv[2]; 735 info->memory = irecv[3]; 736 info->mallocs = irecv[4]; 737 } 738 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 739 info->fill_ratio_needed = 0; 740 info->factor_mallocs = 0; 741 PetscFunctionReturn(PETSC_SUCCESS); 742 } 743 744 static PetscErrorCode MatSetOption_MPISELL(Mat A, MatOption op, PetscBool flg) 745 { 746 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 747 748 PetscFunctionBegin; 749 switch (op) { 750 case MAT_NEW_NONZERO_LOCATIONS: 751 case MAT_NEW_NONZERO_ALLOCATION_ERR: 752 case MAT_UNUSED_NONZERO_LOCATION_ERR: 753 case MAT_KEEP_NONZERO_PATTERN: 754 case MAT_NEW_NONZERO_LOCATION_ERR: 755 case MAT_USE_INODES: 756 case MAT_IGNORE_ZERO_ENTRIES: 757 MatCheckPreallocated(A, 1); 758 PetscCall(MatSetOption(a->A, op, flg)); 759 PetscCall(MatSetOption(a->B, op, flg)); 760 break; 761 case MAT_ROW_ORIENTED: 762 MatCheckPreallocated(A, 1); 763 a->roworiented = flg; 764 765 PetscCall(MatSetOption(a->A, op, flg)); 766 PetscCall(MatSetOption(a->B, op, flg)); 767 break; 768 case MAT_IGNORE_OFF_PROC_ENTRIES: 769 a->donotstash = flg; 770 break; 771 case MAT_SYMMETRIC: 772 MatCheckPreallocated(A, 1); 773 PetscCall(MatSetOption(a->A, op, flg)); 774 break; 775 case MAT_STRUCTURALLY_SYMMETRIC: 776 MatCheckPreallocated(A, 1); 777 PetscCall(MatSetOption(a->A, op, flg)); 778 break; 779 case MAT_HERMITIAN: 780 MatCheckPreallocated(A, 1); 781 PetscCall(MatSetOption(a->A, op, flg)); 782 break; 783 case MAT_SYMMETRY_ETERNAL: 784 MatCheckPreallocated(A, 1); 785 PetscCall(MatSetOption(a->A, op, flg)); 786 break; 787 case MAT_STRUCTURAL_SYMMETRY_ETERNAL: 788 MatCheckPreallocated(A, 1); 789 PetscCall(MatSetOption(a->A, op, flg)); 790 break; 791 default: 792 break; 793 } 794 PetscFunctionReturn(PETSC_SUCCESS); 795 } 796 797 static PetscErrorCode MatDiagonalScale_MPISELL(Mat mat, Vec ll, Vec rr) 798 { 799 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 800 Mat a = sell->A, b = sell->B; 801 PetscInt s1, s2, s3; 802 803 PetscFunctionBegin; 804 PetscCall(MatGetLocalSize(mat, &s2, &s3)); 805 if (rr) { 806 PetscCall(VecGetLocalSize(rr, &s1)); 807 PetscCheck(s1 == s3, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "right vector non-conforming local size"); 808 /* Overlap communication with computation. */ 809 PetscCall(VecScatterBegin(sell->Mvctx, rr, sell->lvec, INSERT_VALUES, SCATTER_FORWARD)); 810 } 811 if (ll) { 812 PetscCall(VecGetLocalSize(ll, &s1)); 813 PetscCheck(s1 == s2, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "left vector non-conforming local size"); 814 PetscUseTypeMethod(b, diagonalscale, ll, NULL); 815 } 816 /* scale the diagonal block */ 817 PetscUseTypeMethod(a, diagonalscale, ll, rr); 818 819 if (rr) { 820 /* Do a scatter end and then right scale the off-diagonal block */ 821 PetscCall(VecScatterEnd(sell->Mvctx, rr, sell->lvec, INSERT_VALUES, SCATTER_FORWARD)); 822 PetscUseTypeMethod(b, diagonalscale, NULL, sell->lvec); 823 } 824 PetscFunctionReturn(PETSC_SUCCESS); 825 } 826 827 static PetscErrorCode MatSetUnfactored_MPISELL(Mat A) 828 { 829 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 830 831 PetscFunctionBegin; 832 PetscCall(MatSetUnfactored(a->A)); 833 PetscFunctionReturn(PETSC_SUCCESS); 834 } 835 836 static PetscErrorCode MatEqual_MPISELL(Mat A, Mat B, PetscBool *flag) 837 { 838 Mat_MPISELL *matB = (Mat_MPISELL *)B->data, *matA = (Mat_MPISELL *)A->data; 839 Mat a, b, c, d; 840 PetscBool flg; 841 842 PetscFunctionBegin; 843 a = matA->A; 844 b = matA->B; 845 c = matB->A; 846 d = matB->B; 847 848 PetscCall(MatEqual(a, c, &flg)); 849 if (flg) PetscCall(MatEqual(b, d, &flg)); 850 PetscCallMPI(MPIU_Allreduce(&flg, flag, 1, MPI_C_BOOL, MPI_LAND, PetscObjectComm((PetscObject)A))); 851 PetscFunctionReturn(PETSC_SUCCESS); 852 } 853 854 static PetscErrorCode MatCopy_MPISELL(Mat A, Mat B, MatStructure str) 855 { 856 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 857 Mat_MPISELL *b = (Mat_MPISELL *)B->data; 858 859 PetscFunctionBegin; 860 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 861 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 862 /* because of the column compression in the off-processor part of the matrix a->B, 863 the number of columns in a->B and b->B may be different, hence we cannot call 864 the MatCopy() directly on the two parts. If need be, we can provide a more 865 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 866 then copying the submatrices */ 867 PetscCall(MatCopy_Basic(A, B, str)); 868 } else { 869 PetscCall(MatCopy(a->A, b->A, str)); 870 PetscCall(MatCopy(a->B, b->B, str)); 871 } 872 PetscFunctionReturn(PETSC_SUCCESS); 873 } 874 875 static PetscErrorCode MatSetUp_MPISELL(Mat A) 876 { 877 PetscFunctionBegin; 878 PetscCall(MatMPISELLSetPreallocation(A, PETSC_DEFAULT, NULL, PETSC_DEFAULT, NULL)); 879 PetscFunctionReturn(PETSC_SUCCESS); 880 } 881 882 static PetscErrorCode MatConjugate_MPISELL(Mat mat) 883 { 884 PetscFunctionBegin; 885 if (PetscDefined(USE_COMPLEX)) { 886 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 887 888 PetscCall(MatConjugate_SeqSELL(sell->A)); 889 PetscCall(MatConjugate_SeqSELL(sell->B)); 890 } 891 PetscFunctionReturn(PETSC_SUCCESS); 892 } 893 894 static PetscErrorCode MatInvertBlockDiagonal_MPISELL(Mat A, const PetscScalar **values) 895 { 896 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 897 898 PetscFunctionBegin; 899 PetscCall(MatInvertBlockDiagonal(a->A, values)); 900 A->factorerrortype = a->A->factorerrortype; 901 PetscFunctionReturn(PETSC_SUCCESS); 902 } 903 904 static PetscErrorCode MatSetRandom_MPISELL(Mat x, PetscRandom rctx) 905 { 906 Mat_MPISELL *sell = (Mat_MPISELL *)x->data; 907 908 PetscFunctionBegin; 909 PetscCall(MatSetRandom(sell->A, rctx)); 910 PetscCall(MatSetRandom(sell->B, rctx)); 911 PetscCall(MatAssemblyBegin(x, MAT_FINAL_ASSEMBLY)); 912 PetscCall(MatAssemblyEnd(x, MAT_FINAL_ASSEMBLY)); 913 PetscFunctionReturn(PETSC_SUCCESS); 914 } 915 916 static PetscErrorCode MatSetFromOptions_MPISELL(Mat A, PetscOptionItems PetscOptionsObject) 917 { 918 PetscFunctionBegin; 919 PetscOptionsHeadBegin(PetscOptionsObject, "MPISELL options"); 920 PetscOptionsHeadEnd(); 921 PetscFunctionReturn(PETSC_SUCCESS); 922 } 923 924 static PetscErrorCode MatShift_MPISELL(Mat Y, PetscScalar a) 925 { 926 Mat_MPISELL *msell = (Mat_MPISELL *)Y->data; 927 Mat_SeqSELL *sell = (Mat_SeqSELL *)msell->A->data; 928 929 PetscFunctionBegin; 930 if (!Y->preallocated) { 931 PetscCall(MatMPISELLSetPreallocation(Y, 1, NULL, 0, NULL)); 932 } else if (!sell->nz) { 933 PetscInt nonew = sell->nonew; 934 PetscCall(MatSeqSELLSetPreallocation(msell->A, 1, NULL)); 935 sell->nonew = nonew; 936 } 937 PetscCall(MatShift_Basic(Y, a)); 938 PetscFunctionReturn(PETSC_SUCCESS); 939 } 940 941 static PetscErrorCode MatMissingDiagonal_MPISELL(Mat A, PetscBool *missing, PetscInt *d) 942 { 943 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 944 945 PetscFunctionBegin; 946 PetscCheck(A->rmap->n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only works for square matrices"); 947 PetscCall(MatMissingDiagonal(a->A, missing, d)); 948 if (d) { 949 PetscInt rstart; 950 PetscCall(MatGetOwnershipRange(A, &rstart, NULL)); 951 *d += rstart; 952 } 953 PetscFunctionReturn(PETSC_SUCCESS); 954 } 955 956 static PetscErrorCode MatGetDiagonalBlock_MPISELL(Mat A, Mat *a) 957 { 958 PetscFunctionBegin; 959 *a = ((Mat_MPISELL *)A->data)->A; 960 PetscFunctionReturn(PETSC_SUCCESS); 961 } 962 963 static PetscErrorCode MatStoreValues_MPISELL(Mat mat) 964 { 965 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 966 967 PetscFunctionBegin; 968 PetscCall(MatStoreValues(sell->A)); 969 PetscCall(MatStoreValues(sell->B)); 970 PetscFunctionReturn(PETSC_SUCCESS); 971 } 972 973 static PetscErrorCode MatRetrieveValues_MPISELL(Mat mat) 974 { 975 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 976 977 PetscFunctionBegin; 978 PetscCall(MatRetrieveValues(sell->A)); 979 PetscCall(MatRetrieveValues(sell->B)); 980 PetscFunctionReturn(PETSC_SUCCESS); 981 } 982 983 static PetscErrorCode MatMPISELLSetPreallocation_MPISELL(Mat B, PetscInt d_rlenmax, const PetscInt d_rlen[], PetscInt o_rlenmax, const PetscInt o_rlen[]) 984 { 985 Mat_MPISELL *b; 986 987 PetscFunctionBegin; 988 PetscCall(PetscLayoutSetUp(B->rmap)); 989 PetscCall(PetscLayoutSetUp(B->cmap)); 990 b = (Mat_MPISELL *)B->data; 991 992 if (!B->preallocated) { 993 /* Explicitly create 2 MATSEQSELL matrices. */ 994 PetscCall(MatCreate(PETSC_COMM_SELF, &b->A)); 995 PetscCall(MatSetSizes(b->A, B->rmap->n, B->cmap->n, B->rmap->n, B->cmap->n)); 996 PetscCall(MatSetBlockSizesFromMats(b->A, B, B)); 997 PetscCall(MatSetType(b->A, MATSEQSELL)); 998 PetscCall(MatCreate(PETSC_COMM_SELF, &b->B)); 999 PetscCall(MatSetSizes(b->B, B->rmap->n, B->cmap->N, B->rmap->n, B->cmap->N)); 1000 PetscCall(MatSetBlockSizesFromMats(b->B, B, B)); 1001 PetscCall(MatSetType(b->B, MATSEQSELL)); 1002 } 1003 1004 PetscCall(MatSeqSELLSetPreallocation(b->A, d_rlenmax, d_rlen)); 1005 PetscCall(MatSeqSELLSetPreallocation(b->B, o_rlenmax, o_rlen)); 1006 B->preallocated = PETSC_TRUE; 1007 B->was_assembled = PETSC_FALSE; 1008 /* 1009 critical for MatAssemblyEnd to work. 1010 MatAssemblyBegin checks it to set up was_assembled 1011 and MatAssemblyEnd checks was_assembled to determine whether to build garray 1012 */ 1013 B->assembled = PETSC_FALSE; 1014 PetscFunctionReturn(PETSC_SUCCESS); 1015 } 1016 1017 static PetscErrorCode MatDuplicate_MPISELL(Mat matin, MatDuplicateOption cpvalues, Mat *newmat) 1018 { 1019 Mat mat; 1020 Mat_MPISELL *a, *oldmat = (Mat_MPISELL *)matin->data; 1021 1022 PetscFunctionBegin; 1023 *newmat = NULL; 1024 PetscCall(MatCreate(PetscObjectComm((PetscObject)matin), &mat)); 1025 PetscCall(MatSetSizes(mat, matin->rmap->n, matin->cmap->n, matin->rmap->N, matin->cmap->N)); 1026 PetscCall(MatSetBlockSizesFromMats(mat, matin, matin)); 1027 PetscCall(MatSetType(mat, ((PetscObject)matin)->type_name)); 1028 a = (Mat_MPISELL *)mat->data; 1029 1030 mat->factortype = matin->factortype; 1031 mat->assembled = PETSC_TRUE; 1032 mat->insertmode = NOT_SET_VALUES; 1033 mat->preallocated = PETSC_TRUE; 1034 1035 a->size = oldmat->size; 1036 a->rank = oldmat->rank; 1037 a->donotstash = oldmat->donotstash; 1038 a->roworiented = oldmat->roworiented; 1039 a->rowindices = NULL; 1040 a->rowvalues = NULL; 1041 a->getrowactive = PETSC_FALSE; 1042 1043 PetscCall(PetscLayoutReference(matin->rmap, &mat->rmap)); 1044 PetscCall(PetscLayoutReference(matin->cmap, &mat->cmap)); 1045 1046 if (oldmat->colmap) { 1047 #if defined(PETSC_USE_CTABLE) 1048 PetscCall(PetscHMapIDuplicate(oldmat->colmap, &a->colmap)); 1049 #else 1050 PetscCall(PetscMalloc1(mat->cmap->N, &a->colmap)); 1051 PetscCall(PetscArraycpy(a->colmap, oldmat->colmap, mat->cmap->N)); 1052 #endif 1053 } else a->colmap = NULL; 1054 if (oldmat->garray) { 1055 PetscInt len; 1056 len = oldmat->B->cmap->n; 1057 PetscCall(PetscMalloc1(len + 1, &a->garray)); 1058 if (len) PetscCall(PetscArraycpy(a->garray, oldmat->garray, len)); 1059 } else a->garray = NULL; 1060 1061 PetscCall(VecDuplicate(oldmat->lvec, &a->lvec)); 1062 PetscCall(VecScatterCopy(oldmat->Mvctx, &a->Mvctx)); 1063 PetscCall(MatDuplicate(oldmat->A, cpvalues, &a->A)); 1064 PetscCall(MatDuplicate(oldmat->B, cpvalues, &a->B)); 1065 PetscCall(PetscFunctionListDuplicate(((PetscObject)matin)->qlist, &((PetscObject)mat)->qlist)); 1066 *newmat = mat; 1067 PetscFunctionReturn(PETSC_SUCCESS); 1068 } 1069 1070 static const struct _MatOps MatOps_Values = {MatSetValues_MPISELL, 1071 NULL, 1072 NULL, 1073 MatMult_MPISELL, 1074 /* 4*/ MatMultAdd_MPISELL, 1075 MatMultTranspose_MPISELL, 1076 MatMultTransposeAdd_MPISELL, 1077 NULL, 1078 NULL, 1079 NULL, 1080 /*10*/ NULL, 1081 NULL, 1082 NULL, 1083 MatSOR_MPISELL, 1084 NULL, 1085 /*15*/ MatGetInfo_MPISELL, 1086 MatEqual_MPISELL, 1087 MatGetDiagonal_MPISELL, 1088 MatDiagonalScale_MPISELL, 1089 NULL, 1090 /*20*/ MatAssemblyBegin_MPISELL, 1091 MatAssemblyEnd_MPISELL, 1092 MatSetOption_MPISELL, 1093 MatZeroEntries_MPISELL, 1094 /*24*/ NULL, 1095 NULL, 1096 NULL, 1097 NULL, 1098 NULL, 1099 /*29*/ MatSetUp_MPISELL, 1100 NULL, 1101 NULL, 1102 MatGetDiagonalBlock_MPISELL, 1103 NULL, 1104 /*34*/ MatDuplicate_MPISELL, 1105 NULL, 1106 NULL, 1107 NULL, 1108 NULL, 1109 /*39*/ NULL, 1110 NULL, 1111 NULL, 1112 MatGetValues_MPISELL, 1113 MatCopy_MPISELL, 1114 /*44*/ NULL, 1115 MatScale_MPISELL, 1116 MatShift_MPISELL, 1117 MatDiagonalSet_MPISELL, 1118 NULL, 1119 /*49*/ MatSetRandom_MPISELL, 1120 NULL, 1121 NULL, 1122 NULL, 1123 NULL, 1124 /*54*/ MatFDColoringCreate_MPIXAIJ, 1125 NULL, 1126 MatSetUnfactored_MPISELL, 1127 NULL, 1128 NULL, 1129 /*59*/ NULL, 1130 MatDestroy_MPISELL, 1131 MatView_MPISELL, 1132 NULL, 1133 NULL, 1134 /*64*/ NULL, 1135 NULL, 1136 NULL, 1137 NULL, 1138 NULL, 1139 /*69*/ NULL, 1140 NULL, 1141 NULL, 1142 MatFDColoringApply_AIJ, /* reuse AIJ function */ 1143 MatSetFromOptions_MPISELL, 1144 NULL, 1145 /*75*/ NULL, 1146 NULL, 1147 NULL, 1148 NULL, 1149 NULL, 1150 /*80*/ NULL, 1151 NULL, 1152 NULL, 1153 /*83*/ NULL, 1154 NULL, 1155 NULL, 1156 NULL, 1157 NULL, 1158 NULL, 1159 /*89*/ NULL, 1160 NULL, 1161 NULL, 1162 NULL, 1163 MatConjugate_MPISELL, 1164 /*94*/ NULL, 1165 NULL, 1166 NULL, 1167 NULL, 1168 NULL, 1169 /*99*/ NULL, 1170 NULL, 1171 NULL, 1172 NULL, 1173 NULL, 1174 /*104*/ MatMissingDiagonal_MPISELL, 1175 NULL, 1176 NULL, 1177 MatGetGhosts_MPISELL, 1178 NULL, 1179 /*109*/ NULL, 1180 MatMultDiagonalBlock_MPISELL, 1181 NULL, 1182 NULL, 1183 NULL, 1184 /*114*/ NULL, 1185 NULL, 1186 NULL, 1187 MatInvertBlockDiagonal_MPISELL, 1188 NULL, 1189 /*119*/ NULL, 1190 NULL, 1191 NULL, 1192 NULL, 1193 NULL, 1194 /*124*/ NULL, 1195 NULL, 1196 NULL, 1197 NULL, 1198 NULL, 1199 /*129*/ MatFDColoringSetUp_MPIXAIJ, 1200 NULL, 1201 NULL, 1202 NULL, 1203 NULL, 1204 /*134*/ NULL, 1205 NULL, 1206 NULL, 1207 NULL, 1208 NULL, 1209 /*139*/ NULL, 1210 NULL, 1211 NULL, 1212 NULL, 1213 NULL, 1214 NULL}; 1215 1216 /*@C 1217 MatMPISELLSetPreallocation - Preallocates memory for a `MATMPISELL` sparse parallel matrix in sell format. 1218 For good matrix assembly performance the user should preallocate the matrix storage by 1219 setting the parameters `d_nz` (or `d_nnz`) and `o_nz` (or `o_nnz`). 1220 1221 Collective 1222 1223 Input Parameters: 1224 + B - the matrix 1225 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 1226 (same value is used for all local rows) 1227 . d_nnz - array containing the number of nonzeros in the various rows of the 1228 DIAGONAL portion of the local submatrix (possibly different for each row) 1229 or NULL (`PETSC_NULL_INTEGER` in Fortran), if `d_nz` is used to specify the nonzero structure. 1230 The size of this array is equal to the number of local rows, i.e 'm'. 1231 For matrices that will be factored, you must leave room for (and set) 1232 the diagonal entry even if it is zero. 1233 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 1234 submatrix (same value is used for all local rows). 1235 - o_nnz - array containing the number of nonzeros in the various rows of the 1236 OFF-DIAGONAL portion of the local submatrix (possibly different for 1237 each row) or NULL (`PETSC_NULL_INTEGER` in Fortran), if `o_nz` is used to specify the nonzero 1238 structure. The size of this array is equal to the number 1239 of local rows, i.e 'm'. 1240 1241 Example usage: 1242 Consider the following 8x8 matrix with 34 non-zero values, that is 1243 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 1244 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 1245 as follows 1246 1247 .vb 1248 1 2 0 | 0 3 0 | 0 4 1249 Proc0 0 5 6 | 7 0 0 | 8 0 1250 9 0 10 | 11 0 0 | 12 0 1251 ------------------------------------- 1252 13 0 14 | 15 16 17 | 0 0 1253 Proc1 0 18 0 | 19 20 21 | 0 0 1254 0 0 0 | 22 23 0 | 24 0 1255 ------------------------------------- 1256 Proc2 25 26 27 | 0 0 28 | 29 0 1257 30 0 0 | 31 32 33 | 0 34 1258 .ve 1259 1260 This can be represented as a collection of submatrices as 1261 1262 .vb 1263 A B C 1264 D E F 1265 G H I 1266 .ve 1267 1268 Where the submatrices A,B,C are owned by proc0, D,E,F are 1269 owned by proc1, G,H,I are owned by proc2. 1270 1271 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 1272 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 1273 The 'M','N' parameters are 8,8, and have the same values on all procs. 1274 1275 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 1276 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 1277 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 1278 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 1279 part as `MATSEQSELL` matrices. For example, proc1 will store [E] as a `MATSEQSELL` 1280 matrix, and [DF] as another SeqSELL matrix. 1281 1282 When `d_nz`, `o_nz` parameters are specified, `d_nz` storage elements are 1283 allocated for every row of the local DIAGONAL submatrix, and o_nz 1284 storage locations are allocated for every row of the OFF-DIAGONAL submatrix. 1285 One way to choose `d_nz` and `o_nz` is to use the maximum number of nonzeros over 1286 the local rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 1287 In this case, the values of d_nz,o_nz are 1288 .vb 1289 proc0 dnz = 2, o_nz = 2 1290 proc1 dnz = 3, o_nz = 2 1291 proc2 dnz = 1, o_nz = 4 1292 .ve 1293 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 1294 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 1295 for proc3. i.e we are using 12+15+10=37 storage locations to store 1296 34 values. 1297 1298 When `d_nnz`, `o_nnz` parameters are specified, the storage is specified 1299 for every row, corresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 1300 In the above case the values for d_nnz,o_nnz are 1301 .vb 1302 proc0 d_nnz = [2,2,2] and o_nnz = [2,2,2] 1303 proc1 d_nnz = [3,3,2] and o_nnz = [2,1,1] 1304 proc2 d_nnz = [1,1] and o_nnz = [4,4] 1305 .ve 1306 Here the space allocated is according to nz (or maximum values in the nnz 1307 if nnz is provided) for DIAGONAL and OFF-DIAGONAL submatrices, i.e (2+2+3+2)*3+(1+4)*2=37 1308 1309 Level: intermediate 1310 1311 Notes: 1312 If the *_nnz parameter is given then the *_nz parameter is ignored 1313 1314 The stored row and column indices begin with zero. 1315 1316 The parallel matrix is partitioned such that the first m0 rows belong to 1317 process 0, the next m1 rows belong to process 1, the next m2 rows belong 1318 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 1319 1320 The DIAGONAL portion of the local submatrix of a processor can be defined 1321 as the submatrix which is obtained by extraction the part corresponding to 1322 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 1323 first row that belongs to the processor, r2 is the last row belonging to 1324 the this processor, and c1-c2 is range of indices of the local part of a 1325 vector suitable for applying the matrix to. This is an mxn matrix. In the 1326 common case of a square matrix, the row and column ranges are the same and 1327 the DIAGONAL part is also square. The remaining portion of the local 1328 submatrix (mxN) constitute the OFF-DIAGONAL portion. 1329 1330 If `o_nnz`, `d_nnz` are specified, then `o_nz`, and `d_nz` are ignored. 1331 1332 You can call `MatGetInfo()` to get information on how effective the preallocation was; 1333 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 1334 You can also run with the option -info and look for messages with the string 1335 malloc in them to see if additional memory allocation was needed. 1336 1337 .seealso: `Mat`, `MatCreate()`, `MatCreateSeqSELL()`, `MatSetValues()`, `MatCreateSELL()`, 1338 `MATMPISELL`, `MatGetInfo()`, `PetscSplitOwnership()`, `MATSELL` 1339 @*/ 1340 PetscErrorCode MatMPISELLSetPreallocation(Mat B, PetscInt d_nz, const PetscInt d_nnz[], PetscInt o_nz, const PetscInt o_nnz[]) 1341 { 1342 PetscFunctionBegin; 1343 PetscValidHeaderSpecific(B, MAT_CLASSID, 1); 1344 PetscValidType(B, 1); 1345 PetscTryMethod(B, "MatMPISELLSetPreallocation_C", (Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[]), (B, d_nz, d_nnz, o_nz, o_nnz)); 1346 PetscFunctionReturn(PETSC_SUCCESS); 1347 } 1348 1349 /*MC 1350 MATMPISELL - MATMPISELL = "mpisell" - A matrix type to be used for MPI sparse matrices, 1351 based on the sliced Ellpack format 1352 1353 Options Database Key: 1354 . -mat_type sell - sets the matrix type to `MATSELL` during a call to `MatSetFromOptions()` 1355 1356 Level: beginner 1357 1358 .seealso: `Mat`, `MatCreateSELL()`, `MATSEQSELL`, `MATSELL`, `MATSEQAIJ`, `MATAIJ`, `MATMPIAIJ` 1359 M*/ 1360 1361 /*@C 1362 MatCreateSELL - Creates a sparse parallel matrix in `MATSELL` format. 1363 1364 Collective 1365 1366 Input Parameters: 1367 + comm - MPI communicator 1368 . m - number of local rows (or `PETSC_DECIDE` to have calculated if M is given) 1369 This value should be the same as the local size used in creating the 1370 y vector for the matrix-vector product y = Ax. 1371 . n - This value should be the same as the local size used in creating the 1372 x vector for the matrix-vector product y = Ax. (or `PETSC_DECIDE` to have 1373 calculated if `N` is given) For square matrices n is almost always `m`. 1374 . M - number of global rows (or `PETSC_DETERMINE` to have calculated if `m` is given) 1375 . N - number of global columns (or `PETSC_DETERMINE` to have calculated if `n` is given) 1376 . d_rlenmax - max number of nonzeros per row in DIAGONAL portion of local submatrix 1377 (same value is used for all local rows) 1378 . d_rlen - array containing the number of nonzeros in the various rows of the 1379 DIAGONAL portion of the local submatrix (possibly different for each row) 1380 or `NULL`, if d_rlenmax is used to specify the nonzero structure. 1381 The size of this array is equal to the number of local rows, i.e `m`. 1382 . o_rlenmax - max number of nonzeros per row in the OFF-DIAGONAL portion of local 1383 submatrix (same value is used for all local rows). 1384 - o_rlen - array containing the number of nonzeros in the various rows of the 1385 OFF-DIAGONAL portion of the local submatrix (possibly different for 1386 each row) or `NULL`, if `o_rlenmax` is used to specify the nonzero 1387 structure. The size of this array is equal to the number 1388 of local rows, i.e `m`. 1389 1390 Output Parameter: 1391 . A - the matrix 1392 1393 Options Database Key: 1394 . -mat_sell_oneindex - Internally use indexing starting at 1 1395 rather than 0. When calling `MatSetValues()`, 1396 the user still MUST index entries starting at 0! 1397 1398 Example: 1399 Consider the following 8x8 matrix with 34 non-zero values, that is 1400 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 1401 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 1402 as follows 1403 1404 .vb 1405 1 2 0 | 0 3 0 | 0 4 1406 Proc0 0 5 6 | 7 0 0 | 8 0 1407 9 0 10 | 11 0 0 | 12 0 1408 ------------------------------------- 1409 13 0 14 | 15 16 17 | 0 0 1410 Proc1 0 18 0 | 19 20 21 | 0 0 1411 0 0 0 | 22 23 0 | 24 0 1412 ------------------------------------- 1413 Proc2 25 26 27 | 0 0 28 | 29 0 1414 30 0 0 | 31 32 33 | 0 34 1415 .ve 1416 1417 This can be represented as a collection of submatrices as 1418 .vb 1419 A B C 1420 D E F 1421 G H I 1422 .ve 1423 1424 Where the submatrices A,B,C are owned by proc0, D,E,F are 1425 owned by proc1, G,H,I are owned by proc2. 1426 1427 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 1428 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 1429 The 'M','N' parameters are 8,8, and have the same values on all procs. 1430 1431 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 1432 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 1433 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 1434 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 1435 part as `MATSEQSELL` matrices. For example, proc1 will store [E] as a `MATSEQSELL` 1436 matrix, and [DF] as another `MATSEQSELL` matrix. 1437 1438 When d_rlenmax, o_rlenmax parameters are specified, d_rlenmax storage elements are 1439 allocated for every row of the local DIAGONAL submatrix, and o_rlenmax 1440 storage locations are allocated for every row of the OFF-DIAGONAL submatrix. 1441 One way to choose `d_rlenmax` and `o_rlenmax` is to use the maximum number of nonzeros over 1442 the local rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 1443 In this case, the values of d_rlenmax,o_rlenmax are 1444 .vb 1445 proc0 - d_rlenmax = 2, o_rlenmax = 2 1446 proc1 - d_rlenmax = 3, o_rlenmax = 2 1447 proc2 - d_rlenmax = 1, o_rlenmax = 4 1448 .ve 1449 We are allocating m*(d_rlenmax+o_rlenmax) storage locations for every proc. This 1450 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 1451 for proc3. i.e we are using 12+15+10=37 storage locations to store 1452 34 values. 1453 1454 When `d_rlen`, `o_rlen` parameters are specified, the storage is specified 1455 for every row, corresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 1456 In the above case the values for `d_nnz`, `o_nnz` are 1457 .vb 1458 proc0 - d_nnz = [2,2,2] and o_nnz = [2,2,2] 1459 proc1 - d_nnz = [3,3,2] and o_nnz = [2,1,1] 1460 proc2 - d_nnz = [1,1] and o_nnz = [4,4] 1461 .ve 1462 Here the space allocated is still 37 though there are 34 nonzeros because 1463 the allocation is always done according to rlenmax. 1464 1465 Level: intermediate 1466 1467 Notes: 1468 It is recommended that one use the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()`, 1469 MatXXXXSetPreallocation() paradigm instead of this routine directly. 1470 [MatXXXXSetPreallocation() is, for example, `MatSeqSELLSetPreallocation()`] 1471 1472 If the *_rlen parameter is given then the *_rlenmax parameter is ignored 1473 1474 `m`, `n`, `M`, `N` parameters specify the size of the matrix, and its partitioning across 1475 processors, while `d_rlenmax`, `d_rlen`, `o_rlenmax` , `o_rlen` parameters specify the approximate 1476 storage requirements for this matrix. 1477 1478 If `PETSC_DECIDE` or `PETSC_DETERMINE` is used for a particular argument on one 1479 processor than it must be used on all processors that share the object for 1480 that argument. 1481 1482 The user MUST specify either the local or global matrix dimensions 1483 (possibly both). 1484 1485 The parallel matrix is partitioned across processors such that the 1486 first m0 rows belong to process 0, the next m1 rows belong to 1487 process 1, the next m2 rows belong to process 2 etc.. where 1488 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 1489 values corresponding to [`m` x `N`] submatrix. 1490 1491 The columns are logically partitioned with the n0 columns belonging 1492 to 0th partition, the next n1 columns belonging to the next 1493 partition etc.. where n0,n1,n2... are the input parameter `n`. 1494 1495 The DIAGONAL portion of the local submatrix on any given processor 1496 is the submatrix corresponding to the rows and columns `m`, `n` 1497 corresponding to the given processor. i.e diagonal matrix on 1498 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 1499 etc. The remaining portion of the local submatrix [m x (N-n)] 1500 constitute the OFF-DIAGONAL portion. The example below better 1501 illustrates this concept. 1502 1503 For a square global matrix we define each processor's diagonal portion 1504 to be its local rows and the corresponding columns (a square submatrix); 1505 each processor's off-diagonal portion encompasses the remainder of the 1506 local matrix (a rectangular submatrix). 1507 1508 If `o_rlen`, `d_rlen` are specified, then `o_rlenmax`, and `d_rlenmax` are ignored. 1509 1510 When calling this routine with a single process communicator, a matrix of 1511 type `MATSEQSELL` is returned. If a matrix of type `MATMPISELL` is desired for this 1512 type of communicator, use the construction mechanism 1513 .vb 1514 MatCreate(...,&A); 1515 MatSetType(A,MATMPISELL); 1516 MatSetSizes(A, m,n,M,N); 1517 MatMPISELLSetPreallocation(A,...); 1518 .ve 1519 1520 .seealso: `Mat`, `MATSELL`, `MatCreate()`, `MatCreateSeqSELL()`, `MatSetValues()`, `MatMPISELLSetPreallocation()`, `MATMPISELL` 1521 @*/ 1522 PetscErrorCode MatCreateSELL(MPI_Comm comm, PetscInt m, PetscInt n, PetscInt M, PetscInt N, PetscInt d_rlenmax, const PetscInt d_rlen[], PetscInt o_rlenmax, const PetscInt o_rlen[], Mat *A) 1523 { 1524 PetscMPIInt size; 1525 1526 PetscFunctionBegin; 1527 PetscCall(MatCreate(comm, A)); 1528 PetscCall(MatSetSizes(*A, m, n, M, N)); 1529 PetscCallMPI(MPI_Comm_size(comm, &size)); 1530 if (size > 1) { 1531 PetscCall(MatSetType(*A, MATMPISELL)); 1532 PetscCall(MatMPISELLSetPreallocation(*A, d_rlenmax, d_rlen, o_rlenmax, o_rlen)); 1533 } else { 1534 PetscCall(MatSetType(*A, MATSEQSELL)); 1535 PetscCall(MatSeqSELLSetPreallocation(*A, d_rlenmax, d_rlen)); 1536 } 1537 PetscFunctionReturn(PETSC_SUCCESS); 1538 } 1539 1540 /*@C 1541 MatMPISELLGetSeqSELL - Returns the local pieces of this distributed matrix 1542 1543 Not Collective 1544 1545 Input Parameter: 1546 . A - the `MATMPISELL` matrix 1547 1548 Output Parameters: 1549 + Ad - The diagonal portion of `A` 1550 . Ao - The off-diagonal portion of `A` 1551 - colmap - An array mapping local column numbers of `Ao` to global column numbers of the parallel matrix 1552 1553 Level: advanced 1554 1555 .seealso: `Mat`, `MATSEQSELL`, `MATMPISELL` 1556 @*/ 1557 PetscErrorCode MatMPISELLGetSeqSELL(Mat A, Mat *Ad, Mat *Ao, const PetscInt *colmap[]) 1558 { 1559 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 1560 PetscBool flg; 1561 1562 PetscFunctionBegin; 1563 PetscCall(PetscObjectTypeCompare((PetscObject)A, MATMPISELL, &flg)); 1564 PetscCheck(flg, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "This function requires a MATMPISELL matrix as input"); 1565 if (Ad) *Ad = a->A; 1566 if (Ao) *Ao = a->B; 1567 if (colmap) *colmap = a->garray; 1568 PetscFunctionReturn(PETSC_SUCCESS); 1569 } 1570 1571 /*@C 1572 MatMPISELLGetLocalMatCondensed - Creates a `MATSEQSELL` matrix from an `MATMPISELL` matrix by 1573 taking all its local rows and NON-ZERO columns 1574 1575 Not Collective 1576 1577 Input Parameters: 1578 + A - the matrix 1579 . scall - either `MAT_INITIAL_MATRIX` or `MAT_REUSE_MATRIX` 1580 . row - index sets of rows to extract (or `NULL`) 1581 - col - index sets of columns to extract (or `NULL`) 1582 1583 Output Parameter: 1584 . A_loc - the local sequential matrix generated 1585 1586 Level: advanced 1587 1588 .seealso: `Mat`, `MATSEQSELL`, `MATMPISELL`, `MatGetOwnershipRange()`, `MatMPISELLGetLocalMat()` 1589 @*/ 1590 PetscErrorCode MatMPISELLGetLocalMatCondensed(Mat A, MatReuse scall, IS *row, IS *col, Mat *A_loc) 1591 { 1592 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 1593 PetscInt i, start, end, ncols, nzA, nzB, *cmap, imark, *idx; 1594 IS isrowa, iscola; 1595 Mat *aloc; 1596 PetscBool match; 1597 1598 PetscFunctionBegin; 1599 PetscCall(PetscObjectTypeCompare((PetscObject)A, MATMPISELL, &match)); 1600 PetscCheck(match, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Requires MATMPISELL matrix as input"); 1601 PetscCall(PetscLogEventBegin(MAT_Getlocalmatcondensed, A, 0, 0, 0)); 1602 if (!row) { 1603 start = A->rmap->rstart; 1604 end = A->rmap->rend; 1605 PetscCall(ISCreateStride(PETSC_COMM_SELF, end - start, start, 1, &isrowa)); 1606 } else { 1607 isrowa = *row; 1608 } 1609 if (!col) { 1610 start = A->cmap->rstart; 1611 cmap = a->garray; 1612 nzA = a->A->cmap->n; 1613 nzB = a->B->cmap->n; 1614 PetscCall(PetscMalloc1(nzA + nzB, &idx)); 1615 ncols = 0; 1616 for (i = 0; i < nzB; i++) { 1617 if (cmap[i] < start) idx[ncols++] = cmap[i]; 1618 else break; 1619 } 1620 imark = i; 1621 for (i = 0; i < nzA; i++) idx[ncols++] = start + i; 1622 for (i = imark; i < nzB; i++) idx[ncols++] = cmap[i]; 1623 PetscCall(ISCreateGeneral(PETSC_COMM_SELF, ncols, idx, PETSC_OWN_POINTER, &iscola)); 1624 } else { 1625 iscola = *col; 1626 } 1627 if (scall != MAT_INITIAL_MATRIX) { 1628 PetscCall(PetscMalloc1(1, &aloc)); 1629 aloc[0] = *A_loc; 1630 } 1631 PetscCall(MatCreateSubMatrices(A, 1, &isrowa, &iscola, scall, &aloc)); 1632 *A_loc = aloc[0]; 1633 PetscCall(PetscFree(aloc)); 1634 if (!row) PetscCall(ISDestroy(&isrowa)); 1635 if (!col) PetscCall(ISDestroy(&iscola)); 1636 PetscCall(PetscLogEventEnd(MAT_Getlocalmatcondensed, A, 0, 0, 0)); 1637 PetscFunctionReturn(PETSC_SUCCESS); 1638 } 1639 1640 #include <../src/mat/impls/aij/mpi/mpiaij.h> 1641 1642 PetscErrorCode MatConvert_MPISELL_MPIAIJ(Mat A, MatType newtype, MatReuse reuse, Mat *newmat) 1643 { 1644 Mat_MPISELL *a = (Mat_MPISELL *)A->data; 1645 Mat B; 1646 Mat_MPIAIJ *b; 1647 1648 PetscFunctionBegin; 1649 PetscCheck(A->assembled, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Matrix must be assembled"); 1650 1651 if (reuse == MAT_REUSE_MATRIX) { 1652 B = *newmat; 1653 } else { 1654 PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B)); 1655 PetscCall(MatSetType(B, MATMPIAIJ)); 1656 PetscCall(MatSetSizes(B, A->rmap->n, A->cmap->n, A->rmap->N, A->cmap->N)); 1657 PetscCall(MatSetBlockSizes(B, A->rmap->bs, A->cmap->bs)); 1658 PetscCall(MatSeqAIJSetPreallocation(B, 0, NULL)); 1659 PetscCall(MatMPIAIJSetPreallocation(B, 0, NULL, 0, NULL)); 1660 } 1661 b = (Mat_MPIAIJ *)B->data; 1662 1663 if (reuse == MAT_REUSE_MATRIX) { 1664 PetscCall(MatConvert_SeqSELL_SeqAIJ(a->A, MATSEQAIJ, MAT_REUSE_MATRIX, &b->A)); 1665 PetscCall(MatConvert_SeqSELL_SeqAIJ(a->B, MATSEQAIJ, MAT_REUSE_MATRIX, &b->B)); 1666 } else { 1667 PetscCall(MatDestroy(&b->A)); 1668 PetscCall(MatDestroy(&b->B)); 1669 PetscCall(MatDisAssemble_MPISELL(A)); 1670 PetscCall(MatConvert_SeqSELL_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A)); 1671 PetscCall(MatConvert_SeqSELL_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B)); 1672 PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY)); 1673 PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY)); 1674 PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY)); 1675 PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY)); 1676 } 1677 1678 if (reuse == MAT_INPLACE_MATRIX) { 1679 PetscCall(MatHeaderReplace(A, &B)); 1680 } else { 1681 *newmat = B; 1682 } 1683 PetscFunctionReturn(PETSC_SUCCESS); 1684 } 1685 1686 PetscErrorCode MatConvert_MPIAIJ_MPISELL(Mat A, MatType newtype, MatReuse reuse, Mat *newmat) 1687 { 1688 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 1689 Mat B; 1690 Mat_MPISELL *b; 1691 1692 PetscFunctionBegin; 1693 PetscCheck(A->assembled, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Matrix must be assembled"); 1694 1695 if (reuse == MAT_REUSE_MATRIX) { 1696 B = *newmat; 1697 } else { 1698 Mat_SeqAIJ *Aa = (Mat_SeqAIJ *)a->A->data, *Ba = (Mat_SeqAIJ *)a->B->data; 1699 PetscInt i, d_nz = 0, o_nz = 0, m = A->rmap->N, n = A->cmap->N, lm = A->rmap->n, ln = A->cmap->n; 1700 PetscInt *d_nnz, *o_nnz; 1701 PetscCall(PetscMalloc2(lm, &d_nnz, lm, &o_nnz)); 1702 for (i = 0; i < lm; i++) { 1703 d_nnz[i] = Aa->i[i + 1] - Aa->i[i]; 1704 o_nnz[i] = Ba->i[i + 1] - Ba->i[i]; 1705 if (d_nnz[i] > d_nz) d_nz = d_nnz[i]; 1706 if (o_nnz[i] > o_nz) o_nz = o_nnz[i]; 1707 } 1708 PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B)); 1709 PetscCall(MatSetType(B, MATMPISELL)); 1710 PetscCall(MatSetSizes(B, lm, ln, m, n)); 1711 PetscCall(MatSetBlockSizes(B, A->rmap->bs, A->cmap->bs)); 1712 PetscCall(MatSeqSELLSetPreallocation(B, d_nz, d_nnz)); 1713 PetscCall(MatMPISELLSetPreallocation(B, d_nz, d_nnz, o_nz, o_nnz)); 1714 PetscCall(PetscFree2(d_nnz, o_nnz)); 1715 } 1716 b = (Mat_MPISELL *)B->data; 1717 1718 if (reuse == MAT_REUSE_MATRIX) { 1719 PetscCall(MatConvert_SeqAIJ_SeqSELL(a->A, MATSEQSELL, MAT_REUSE_MATRIX, &b->A)); 1720 PetscCall(MatConvert_SeqAIJ_SeqSELL(a->B, MATSEQSELL, MAT_REUSE_MATRIX, &b->B)); 1721 } else { 1722 PetscCall(MatDestroy(&b->A)); 1723 PetscCall(MatDestroy(&b->B)); 1724 PetscCall(MatConvert_SeqAIJ_SeqSELL(a->A, MATSEQSELL, MAT_INITIAL_MATRIX, &b->A)); 1725 PetscCall(MatConvert_SeqAIJ_SeqSELL(a->B, MATSEQSELL, MAT_INITIAL_MATRIX, &b->B)); 1726 PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY)); 1727 PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY)); 1728 PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY)); 1729 PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY)); 1730 } 1731 1732 if (reuse == MAT_INPLACE_MATRIX) { 1733 PetscCall(MatHeaderReplace(A, &B)); 1734 } else { 1735 *newmat = B; 1736 } 1737 PetscFunctionReturn(PETSC_SUCCESS); 1738 } 1739 1740 PetscErrorCode MatSOR_MPISELL(Mat matin, Vec bb, PetscReal omega, MatSORType flag, PetscReal fshift, PetscInt its, PetscInt lits, Vec xx) 1741 { 1742 Mat_MPISELL *mat = (Mat_MPISELL *)matin->data; 1743 Vec bb1 = NULL; 1744 1745 PetscFunctionBegin; 1746 if (flag == SOR_APPLY_UPPER) { 1747 PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx)); 1748 PetscFunctionReturn(PETSC_SUCCESS); 1749 } 1750 1751 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) PetscCall(VecDuplicate(bb, &bb1)); 1752 1753 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1754 if (flag & SOR_ZERO_INITIAL_GUESS) { 1755 PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx)); 1756 its--; 1757 } 1758 1759 while (its--) { 1760 PetscCall(VecScatterBegin(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD)); 1761 PetscCall(VecScatterEnd(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD)); 1762 1763 /* update rhs: bb1 = bb - B*x */ 1764 PetscCall(VecScale(mat->lvec, -1.0)); 1765 PetscCall((*mat->B->ops->multadd)(mat->B, mat->lvec, bb, bb1)); 1766 1767 /* local sweep */ 1768 PetscCall((*mat->A->ops->sor)(mat->A, bb1, omega, SOR_SYMMETRIC_SWEEP, fshift, lits, 1, xx)); 1769 } 1770 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1771 if (flag & SOR_ZERO_INITIAL_GUESS) { 1772 PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx)); 1773 its--; 1774 } 1775 while (its--) { 1776 PetscCall(VecScatterBegin(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD)); 1777 PetscCall(VecScatterEnd(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD)); 1778 1779 /* update rhs: bb1 = bb - B*x */ 1780 PetscCall(VecScale(mat->lvec, -1.0)); 1781 PetscCall((*mat->B->ops->multadd)(mat->B, mat->lvec, bb, bb1)); 1782 1783 /* local sweep */ 1784 PetscCall((*mat->A->ops->sor)(mat->A, bb1, omega, SOR_FORWARD_SWEEP, fshift, lits, 1, xx)); 1785 } 1786 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1787 if (flag & SOR_ZERO_INITIAL_GUESS) { 1788 PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx)); 1789 its--; 1790 } 1791 while (its--) { 1792 PetscCall(VecScatterBegin(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD)); 1793 PetscCall(VecScatterEnd(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD)); 1794 1795 /* update rhs: bb1 = bb - B*x */ 1796 PetscCall(VecScale(mat->lvec, -1.0)); 1797 PetscCall((*mat->B->ops->multadd)(mat->B, mat->lvec, bb, bb1)); 1798 1799 /* local sweep */ 1800 PetscCall((*mat->A->ops->sor)(mat->A, bb1, omega, SOR_BACKWARD_SWEEP, fshift, lits, 1, xx)); 1801 } 1802 } else SETERRQ(PetscObjectComm((PetscObject)matin), PETSC_ERR_SUP, "Parallel SOR not supported"); 1803 1804 PetscCall(VecDestroy(&bb1)); 1805 1806 matin->factorerrortype = mat->A->factorerrortype; 1807 PetscFunctionReturn(PETSC_SUCCESS); 1808 } 1809 1810 #if defined(PETSC_HAVE_CUDA) 1811 PETSC_INTERN PetscErrorCode MatConvert_MPISELL_MPISELLCUDA(Mat, MatType, MatReuse, Mat *); 1812 #endif 1813 1814 /*MC 1815 MATMPISELL - MATMPISELL = "MPISELL" - A matrix type to be used for parallel sparse matrices. 1816 1817 Options Database Keys: 1818 . -mat_type mpisell - sets the matrix type to `MATMPISELL` during a call to `MatSetFromOptions()` 1819 1820 Level: beginner 1821 1822 .seealso: `Mat`, `MATSELL`, `MATSEQSELL` `MatCreateSELL()` 1823 M*/ 1824 PETSC_EXTERN PetscErrorCode MatCreate_MPISELL(Mat B) 1825 { 1826 Mat_MPISELL *b; 1827 PetscMPIInt size; 1828 1829 PetscFunctionBegin; 1830 PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &size)); 1831 PetscCall(PetscNew(&b)); 1832 B->data = (void *)b; 1833 B->ops[0] = MatOps_Values; 1834 B->assembled = PETSC_FALSE; 1835 B->insertmode = NOT_SET_VALUES; 1836 b->size = size; 1837 PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)B), &b->rank)); 1838 /* build cache for off array entries formed */ 1839 PetscCall(MatStashCreate_Private(PetscObjectComm((PetscObject)B), 1, &B->stash)); 1840 1841 b->donotstash = PETSC_FALSE; 1842 b->colmap = NULL; 1843 b->garray = NULL; 1844 b->roworiented = PETSC_TRUE; 1845 1846 /* stuff used for matrix vector multiply */ 1847 b->lvec = NULL; 1848 b->Mvctx = NULL; 1849 1850 /* stuff for MatGetRow() */ 1851 b->rowindices = NULL; 1852 b->rowvalues = NULL; 1853 b->getrowactive = PETSC_FALSE; 1854 1855 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatStoreValues_C", MatStoreValues_MPISELL)); 1856 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatRetrieveValues_C", MatRetrieveValues_MPISELL)); 1857 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatIsTranspose_C", MatIsTranspose_MPISELL)); 1858 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatMPISELLSetPreallocation_C", MatMPISELLSetPreallocation_MPISELL)); 1859 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpisell_mpiaij_C", MatConvert_MPISELL_MPIAIJ)); 1860 #if defined(PETSC_HAVE_CUDA) 1861 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpisell_mpisellcuda_C", MatConvert_MPISELL_MPISELLCUDA)); 1862 #endif 1863 PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDiagonalScaleLocal_C", MatDiagonalScaleLocal_MPISELL)); 1864 PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATMPISELL)); 1865 PetscFunctionReturn(PETSC_SUCCESS); 1866 } 1867