1 #include <../src/ksp/pc/impls/gamg/gamg.h> /*I "petscpc.h" I*/ 2 #include <petscsf.h> 3 4 static PetscFunctionList PCGAMGClassicalProlongatorList = NULL; 5 static PetscBool PCGAMGClassicalPackageInitialized = PETSC_FALSE; 6 7 typedef struct { 8 PetscReal interp_threshold; /* interpolation threshold */ 9 char prolongtype[256]; 10 PetscInt nsmooths; /* number of jacobi smoothings on the prolongator */ 11 } PC_GAMG_Classical; 12 13 /*@ 14 PCGAMGClassicalSetType - Sets the type of classical interpolation to use with `PCGAMG` 15 16 Collective 17 18 Input Parameters: 19 + pc - the preconditioner context 20 - type - the interpolation to use, see `PCGAMGClassicalType()` 21 22 Options Database Key: 23 . -pc_gamg_classical_type <direct,standard> - set type of classical AMG prolongation 24 25 Level: intermediate 26 27 .seealso: [](ch_ksp), `PCGAMG`, `PCGAMGClassicalType`, `PCGAMGClassicalGetType()` 28 @*/ 29 PetscErrorCode PCGAMGClassicalSetType(PC pc, PCGAMGClassicalType type) 30 { 31 PetscFunctionBegin; 32 PetscValidHeaderSpecific(pc, PC_CLASSID, 1); 33 PetscTryMethod(pc, "PCGAMGClassicalSetType_C", (PC, PCGAMGClassicalType), (pc, type)); 34 PetscFunctionReturn(PETSC_SUCCESS); 35 } 36 37 /*@ 38 PCGAMGClassicalGetType - Gets the type of classical interpolation to use with `PCGAMG` 39 40 Collective 41 42 Input Parameter: 43 . pc - the preconditioner context 44 45 Output Parameter: 46 . type - the type used, see `PCGAMGClassicalType()` 47 48 Level: intermediate 49 50 .seealso: [](ch_ksp), `PCGAMG`, `PCGAMGClassicalType`, `PCGAMGClassicalSetType()` 51 @*/ 52 PetscErrorCode PCGAMGClassicalGetType(PC pc, PCGAMGClassicalType *type) 53 { 54 PetscFunctionBegin; 55 PetscValidHeaderSpecific(pc, PC_CLASSID, 1); 56 PetscUseMethod(pc, "PCGAMGClassicalGetType_C", (PC, PCGAMGClassicalType *), (pc, type)); 57 PetscFunctionReturn(PETSC_SUCCESS); 58 } 59 60 static PetscErrorCode PCGAMGClassicalSetType_GAMG(PC pc, PCGAMGClassicalType type) 61 { 62 PC_MG *mg = (PC_MG *)pc->data; 63 PC_GAMG *pc_gamg = (PC_GAMG *)mg->innerctx; 64 PC_GAMG_Classical *cls = (PC_GAMG_Classical *)pc_gamg->subctx; 65 66 PetscFunctionBegin; 67 PetscCall(PetscStrncpy(cls->prolongtype, type, sizeof(cls->prolongtype))); 68 PetscFunctionReturn(PETSC_SUCCESS); 69 } 70 71 static PetscErrorCode PCGAMGClassicalGetType_GAMG(PC pc, PCGAMGClassicalType *type) 72 { 73 PC_MG *mg = (PC_MG *)pc->data; 74 PC_GAMG *pc_gamg = (PC_GAMG *)mg->innerctx; 75 PC_GAMG_Classical *cls = (PC_GAMG_Classical *)pc_gamg->subctx; 76 77 PetscFunctionBegin; 78 *type = cls->prolongtype; 79 PetscFunctionReturn(PETSC_SUCCESS); 80 } 81 82 static PetscErrorCode PCGAMGCreateGraph_Classical(PC pc, Mat A, Mat *G) 83 { 84 PetscInt s, f, n, idx, lidx, gidx; 85 PetscInt r, c, ncols; 86 const PetscInt *rcol; 87 const PetscScalar *rval; 88 PetscInt *gcol; 89 PetscScalar *gval; 90 PetscReal rmax; 91 PetscInt cmax = 0; 92 PC_MG *mg = (PC_MG *)pc->data; 93 PC_GAMG *gamg = (PC_GAMG *)mg->innerctx; 94 PetscInt *gsparse, *lsparse; 95 PetscScalar *Amax; 96 MatType mtype; 97 98 PetscFunctionBegin; 99 PetscCall(MatGetOwnershipRange(A, &s, &f)); 100 n = f - s; 101 PetscCall(PetscMalloc3(n, &lsparse, n, &gsparse, n, &Amax)); 102 103 for (r = 0; r < n; r++) { 104 lsparse[r] = 0; 105 gsparse[r] = 0; 106 } 107 108 for (r = s; r < f; r++) { 109 /* determine the maximum off-diagonal in each row */ 110 rmax = 0.; 111 PetscCall(MatGetRow(A, r, &ncols, &rcol, &rval)); 112 for (c = 0; c < ncols; c++) { 113 if (PetscRealPart(-rval[c]) > rmax && rcol[c] != r) rmax = PetscRealPart(-rval[c]); 114 } 115 Amax[r - s] = rmax; 116 if (ncols > cmax) cmax = ncols; 117 lidx = 0; 118 gidx = 0; 119 /* create the local and global sparsity patterns */ 120 for (c = 0; c < ncols; c++) { 121 if (PetscRealPart(-rval[c]) > gamg->threshold[0] * PetscRealPart(Amax[r - s]) || rcol[c] == r) { 122 if (rcol[c] < f && rcol[c] >= s) { 123 lidx++; 124 } else { 125 gidx++; 126 } 127 } 128 } 129 PetscCall(MatRestoreRow(A, r, &ncols, &rcol, &rval)); 130 lsparse[r - s] = lidx; 131 gsparse[r - s] = gidx; 132 } 133 PetscCall(PetscMalloc2(cmax, &gval, cmax, &gcol)); 134 135 PetscCall(MatCreate(PetscObjectComm((PetscObject)A), G)); 136 PetscCall(MatGetType(A, &mtype)); 137 PetscCall(MatSetType(*G, mtype)); 138 PetscCall(MatSetSizes(*G, n, n, PETSC_DETERMINE, PETSC_DETERMINE)); 139 PetscCall(MatMPIAIJSetPreallocation(*G, 0, lsparse, 0, gsparse)); 140 PetscCall(MatSeqAIJSetPreallocation(*G, 0, lsparse)); 141 for (r = s; r < f; r++) { 142 PetscCall(MatGetRow(A, r, &ncols, &rcol, &rval)); 143 idx = 0; 144 for (c = 0; c < ncols; c++) { 145 /* classical strength of connection */ 146 if (PetscRealPart(-rval[c]) > gamg->threshold[0] * PetscRealPart(Amax[r - s]) || rcol[c] == r) { 147 gcol[idx] = rcol[c]; 148 gval[idx] = rval[c]; 149 idx++; 150 } 151 } 152 PetscCall(MatSetValues(*G, 1, &r, idx, gcol, gval, INSERT_VALUES)); 153 PetscCall(MatRestoreRow(A, r, &ncols, &rcol, &rval)); 154 } 155 PetscCall(MatAssemblyBegin(*G, MAT_FINAL_ASSEMBLY)); 156 PetscCall(MatAssemblyEnd(*G, MAT_FINAL_ASSEMBLY)); 157 158 PetscCall(PetscFree2(gval, gcol)); 159 PetscCall(PetscFree3(lsparse, gsparse, Amax)); 160 PetscFunctionReturn(PETSC_SUCCESS); 161 } 162 163 static PetscErrorCode PCGAMGCoarsen_Classical(PC pc, Mat *G, PetscCoarsenData **agg_lists) 164 { 165 MatCoarsen crs; 166 MPI_Comm fcomm = ((PetscObject)pc)->comm; 167 const char *prefix; 168 169 PetscFunctionBegin; 170 PetscCheck(G, fcomm, PETSC_ERR_ARG_WRONGSTATE, "Must set Graph in PC in PCGAMG before coarsening"); 171 172 PetscCall(MatCoarsenCreate(fcomm, &crs)); 173 PetscCall(PetscObjectGetOptionsPrefix((PetscObject)pc, &prefix)); 174 PetscCall(PetscObjectSetOptionsPrefix((PetscObject)crs, prefix)); 175 PetscCall(PetscObjectAppendOptionsPrefix((PetscObject)crs, "pc_gamg_")); 176 PetscCall(MatCoarsenSetFromOptions(crs)); 177 PetscCall(MatCoarsenSetAdjacency(crs, *G)); 178 PetscCall(MatCoarsenSetStrictAggs(crs, PETSC_TRUE)); 179 PetscCall(MatCoarsenApply(crs)); 180 PetscCall(MatCoarsenGetData(crs, agg_lists)); 181 PetscCall(MatCoarsenDestroy(&crs)); 182 PetscFunctionReturn(PETSC_SUCCESS); 183 } 184 185 static PetscErrorCode PCGAMGProlongator_Classical_Direct(PC pc, Mat A, PetscCoarsenData *agg_lists, Mat *P) 186 { 187 PC_MG *mg = (PC_MG *)pc->data; 188 PC_GAMG *gamg = (PC_GAMG *)mg->innerctx; 189 PetscBool iscoarse, isMPIAIJ, isSEQAIJ; 190 PetscInt fn, cn, fs, fe, cs, ce, i, j, ncols, col, row_f, row_c, cmax = 0, idx, noff; 191 PetscInt *lcid, *gcid, *lsparse, *gsparse, *colmap, *pcols; 192 const PetscInt *rcol; 193 PetscReal *Amax_pos, *Amax_neg; 194 PetscScalar g_pos, g_neg, a_pos, a_neg, diag, invdiag, alpha, beta, pij; 195 PetscScalar *pvals; 196 const PetscScalar *rval; 197 Mat lA, gA = NULL; 198 MatType mtype; 199 Vec C, lvec; 200 PetscLayout clayout; 201 PetscSF sf; 202 Mat_MPIAIJ *mpiaij; 203 204 PetscFunctionBegin; 205 PetscCall(MatGetOwnershipRange(A, &fs, &fe)); 206 fn = fe - fs; 207 PetscCall(PetscObjectTypeCompare((PetscObject)A, MATMPIAIJ, &isMPIAIJ)); 208 PetscCall(PetscObjectTypeCompare((PetscObject)A, MATSEQAIJ, &isSEQAIJ)); 209 PetscCheck(isMPIAIJ || isSEQAIJ, PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Classical AMG requires MPIAIJ matrix"); 210 if (isMPIAIJ) { 211 mpiaij = (Mat_MPIAIJ *)A->data; 212 lA = mpiaij->A; 213 gA = mpiaij->B; 214 lvec = mpiaij->lvec; 215 PetscCall(VecGetSize(lvec, &noff)); 216 colmap = mpiaij->garray; 217 PetscCall(MatGetLayouts(A, NULL, &clayout)); 218 PetscCall(PetscSFCreate(PetscObjectComm((PetscObject)A), &sf)); 219 PetscCall(PetscSFSetGraphLayout(sf, clayout, noff, NULL, PETSC_COPY_VALUES, colmap)); 220 PetscCall(PetscMalloc1(noff, &gcid)); 221 } else { 222 lA = A; 223 } 224 PetscCall(PetscMalloc5(fn, &lsparse, fn, &gsparse, fn, &lcid, fn, &Amax_pos, fn, &Amax_neg)); 225 226 /* count the number of coarse unknowns */ 227 cn = 0; 228 for (i = 0; i < fn; i++) { 229 /* filter out singletons */ 230 PetscCall(PetscCDIsEmptyAt(agg_lists, i, &iscoarse)); 231 lcid[i] = -1; 232 if (!iscoarse) cn++; 233 } 234 235 /* create the coarse vector */ 236 PetscCall(VecCreateMPI(PetscObjectComm((PetscObject)A), cn, PETSC_DECIDE, &C)); 237 PetscCall(VecGetOwnershipRange(C, &cs, &ce)); 238 239 cn = 0; 240 for (i = 0; i < fn; i++) { 241 PetscCall(PetscCDIsEmptyAt(agg_lists, i, &iscoarse)); 242 if (!iscoarse) { 243 lcid[i] = cs + cn; 244 cn++; 245 } else { 246 lcid[i] = -1; 247 } 248 } 249 250 if (gA) { 251 PetscCall(PetscSFBcastBegin(sf, MPIU_INT, lcid, gcid, MPI_REPLACE)); 252 PetscCall(PetscSFBcastEnd(sf, MPIU_INT, lcid, gcid, MPI_REPLACE)); 253 } 254 255 /* determine the largest off-diagonal entries in each row */ 256 for (i = fs; i < fe; i++) { 257 Amax_pos[i - fs] = 0.; 258 Amax_neg[i - fs] = 0.; 259 PetscCall(MatGetRow(A, i, &ncols, &rcol, &rval)); 260 for (j = 0; j < ncols; j++) { 261 if ((PetscRealPart(-rval[j]) > Amax_neg[i - fs]) && i != rcol[j]) Amax_neg[i - fs] = PetscAbsScalar(rval[j]); 262 if ((PetscRealPart(rval[j]) > Amax_pos[i - fs]) && i != rcol[j]) Amax_pos[i - fs] = PetscAbsScalar(rval[j]); 263 } 264 if (ncols > cmax) cmax = ncols; 265 PetscCall(MatRestoreRow(A, i, &ncols, &rcol, &rval)); 266 } 267 PetscCall(PetscMalloc2(cmax, &pcols, cmax, &pvals)); 268 PetscCall(VecDestroy(&C)); 269 270 /* count the on and off processor sparsity patterns for the prolongator */ 271 for (i = 0; i < fn; i++) { 272 /* on */ 273 lsparse[i] = 0; 274 gsparse[i] = 0; 275 if (lcid[i] >= 0) { 276 lsparse[i] = 1; 277 gsparse[i] = 0; 278 } else { 279 PetscCall(MatGetRow(lA, i, &ncols, &rcol, &rval)); 280 for (j = 0; j < ncols; j++) { 281 col = rcol[j]; 282 if (lcid[col] >= 0 && (PetscRealPart(rval[j]) > gamg->threshold[0] * Amax_pos[i] || PetscRealPart(-rval[j]) > gamg->threshold[0] * Amax_neg[i])) lsparse[i] += 1; 283 } 284 PetscCall(MatRestoreRow(lA, i, &ncols, &rcol, &rval)); 285 /* off */ 286 if (gA) { 287 PetscCall(MatGetRow(gA, i, &ncols, &rcol, &rval)); 288 for (j = 0; j < ncols; j++) { 289 col = rcol[j]; 290 if (gcid[col] >= 0 && (PetscRealPart(rval[j]) > gamg->threshold[0] * Amax_pos[i] || PetscRealPart(-rval[j]) > gamg->threshold[0] * Amax_neg[i])) gsparse[i] += 1; 291 } 292 PetscCall(MatRestoreRow(gA, i, &ncols, &rcol, &rval)); 293 } 294 } 295 } 296 297 /* preallocate and create the prolongator */ 298 PetscCall(MatCreate(PetscObjectComm((PetscObject)A), P)); 299 PetscCall(MatGetType(A, &mtype)); 300 PetscCall(MatSetType(*P, mtype)); 301 PetscCall(MatSetSizes(*P, fn, cn, PETSC_DETERMINE, PETSC_DETERMINE)); 302 PetscCall(MatMPIAIJSetPreallocation(*P, 0, lsparse, 0, gsparse)); 303 PetscCall(MatSeqAIJSetPreallocation(*P, 0, lsparse)); 304 305 /* loop over local fine nodes -- get the diagonal, the sum of positive and negative strong and weak weights, and set up the row */ 306 for (i = 0; i < fn; i++) { 307 /* determine on or off */ 308 row_f = i + fs; 309 row_c = lcid[i]; 310 if (row_c >= 0) { 311 pij = 1.; 312 PetscCall(MatSetValues(*P, 1, &row_f, 1, &row_c, &pij, INSERT_VALUES)); 313 } else { 314 g_pos = 0.; 315 g_neg = 0.; 316 a_pos = 0.; 317 a_neg = 0.; 318 diag = 0.; 319 320 /* local connections */ 321 PetscCall(MatGetRow(lA, i, &ncols, &rcol, &rval)); 322 for (j = 0; j < ncols; j++) { 323 col = rcol[j]; 324 if (lcid[col] >= 0 && (PetscRealPart(rval[j]) > gamg->threshold[0] * Amax_pos[i] || PetscRealPart(-rval[j]) > gamg->threshold[0] * Amax_neg[i])) { 325 if (PetscRealPart(rval[j]) > 0.) { 326 g_pos += rval[j]; 327 } else { 328 g_neg += rval[j]; 329 } 330 } 331 if (col != i) { 332 if (PetscRealPart(rval[j]) > 0.) { 333 a_pos += rval[j]; 334 } else { 335 a_neg += rval[j]; 336 } 337 } else { 338 diag = rval[j]; 339 } 340 } 341 PetscCall(MatRestoreRow(lA, i, &ncols, &rcol, &rval)); 342 343 /* ghosted connections */ 344 if (gA) { 345 PetscCall(MatGetRow(gA, i, &ncols, &rcol, &rval)); 346 for (j = 0; j < ncols; j++) { 347 col = rcol[j]; 348 if (gcid[col] >= 0 && (PetscRealPart(rval[j]) > gamg->threshold[0] * Amax_pos[i] || PetscRealPart(-rval[j]) > gamg->threshold[0] * Amax_neg[i])) { 349 if (PetscRealPart(rval[j]) > 0.) { 350 g_pos += rval[j]; 351 } else { 352 g_neg += rval[j]; 353 } 354 } 355 if (PetscRealPart(rval[j]) > 0.) { 356 a_pos += rval[j]; 357 } else { 358 a_neg += rval[j]; 359 } 360 } 361 PetscCall(MatRestoreRow(gA, i, &ncols, &rcol, &rval)); 362 } 363 364 if (g_neg == 0.) { 365 alpha = 0.; 366 } else { 367 alpha = -a_neg / g_neg; 368 } 369 370 if (g_pos == 0.) { 371 diag += a_pos; 372 beta = 0.; 373 } else { 374 beta = -a_pos / g_pos; 375 } 376 if (diag == 0.) { 377 invdiag = 0.; 378 } else invdiag = 1. / diag; 379 /* on */ 380 PetscCall(MatGetRow(lA, i, &ncols, &rcol, &rval)); 381 idx = 0; 382 for (j = 0; j < ncols; j++) { 383 col = rcol[j]; 384 if (lcid[col] >= 0 && (PetscRealPart(rval[j]) > gamg->threshold[0] * Amax_pos[i] || PetscRealPart(-rval[j]) > gamg->threshold[0] * Amax_neg[i])) { 385 row_f = i + fs; 386 row_c = lcid[col]; 387 /* set the values for on-processor ones */ 388 if (PetscRealPart(rval[j]) < 0.) { 389 pij = rval[j] * alpha * invdiag; 390 } else { 391 pij = rval[j] * beta * invdiag; 392 } 393 if (PetscAbsScalar(pij) != 0.) { 394 pvals[idx] = pij; 395 pcols[idx] = row_c; 396 idx++; 397 } 398 } 399 } 400 PetscCall(MatRestoreRow(lA, i, &ncols, &rcol, &rval)); 401 /* off */ 402 if (gA) { 403 PetscCall(MatGetRow(gA, i, &ncols, &rcol, &rval)); 404 for (j = 0; j < ncols; j++) { 405 col = rcol[j]; 406 if (gcid[col] >= 0 && (PetscRealPart(rval[j]) > gamg->threshold[0] * Amax_pos[i] || PetscRealPart(-rval[j]) > gamg->threshold[0] * Amax_neg[i])) { 407 row_f = i + fs; 408 row_c = gcid[col]; 409 /* set the values for on-processor ones */ 410 if (PetscRealPart(rval[j]) < 0.) { 411 pij = rval[j] * alpha * invdiag; 412 } else { 413 pij = rval[j] * beta * invdiag; 414 } 415 if (PetscAbsScalar(pij) != 0.) { 416 pvals[idx] = pij; 417 pcols[idx] = row_c; 418 idx++; 419 } 420 } 421 } 422 PetscCall(MatRestoreRow(gA, i, &ncols, &rcol, &rval)); 423 } 424 PetscCall(MatSetValues(*P, 1, &row_f, idx, pcols, pvals, INSERT_VALUES)); 425 } 426 } 427 428 PetscCall(MatAssemblyBegin(*P, MAT_FINAL_ASSEMBLY)); 429 PetscCall(MatAssemblyEnd(*P, MAT_FINAL_ASSEMBLY)); 430 431 PetscCall(PetscFree5(lsparse, gsparse, lcid, Amax_pos, Amax_neg)); 432 433 PetscCall(PetscFree2(pcols, pvals)); 434 if (gA) { 435 PetscCall(PetscSFDestroy(&sf)); 436 PetscCall(PetscFree(gcid)); 437 } 438 PetscFunctionReturn(PETSC_SUCCESS); 439 } 440 441 static PetscErrorCode PCGAMGTruncateProlongator_Private(PC pc, Mat *P) 442 { 443 PetscInt j, i, ps, pf, pn, pcs, pcf, pcn, idx, cmax; 444 const PetscScalar *pval; 445 const PetscInt *pcol; 446 PetscScalar *pnval; 447 PetscInt *pncol; 448 PetscInt ncols; 449 Mat Pnew; 450 PetscInt *lsparse, *gsparse; 451 PetscReal pmax_pos, pmax_neg, ptot_pos, ptot_neg, pthresh_pos, pthresh_neg; 452 PC_MG *mg = (PC_MG *)pc->data; 453 PC_GAMG *pc_gamg = (PC_GAMG *)mg->innerctx; 454 PC_GAMG_Classical *cls = (PC_GAMG_Classical *)pc_gamg->subctx; 455 MatType mtype; 456 457 PetscFunctionBegin; 458 /* trim and rescale with reallocation */ 459 PetscCall(MatGetOwnershipRange(*P, &ps, &pf)); 460 PetscCall(MatGetOwnershipRangeColumn(*P, &pcs, &pcf)); 461 pn = pf - ps; 462 pcn = pcf - pcs; 463 PetscCall(PetscMalloc2(pn, &lsparse, pn, &gsparse)); 464 /* allocate */ 465 cmax = 0; 466 for (i = ps; i < pf; i++) { 467 lsparse[i - ps] = 0; 468 gsparse[i - ps] = 0; 469 PetscCall(MatGetRow(*P, i, &ncols, &pcol, &pval)); 470 if (ncols > cmax) cmax = ncols; 471 pmax_pos = 0.; 472 pmax_neg = 0.; 473 for (j = 0; j < ncols; j++) { 474 if (PetscRealPart(pval[j]) > pmax_pos) { 475 pmax_pos = PetscRealPart(pval[j]); 476 } else if (PetscRealPart(pval[j]) < pmax_neg) { 477 pmax_neg = PetscRealPart(pval[j]); 478 } 479 } 480 for (j = 0; j < ncols; j++) { 481 if (PetscRealPart(pval[j]) >= pmax_pos * cls->interp_threshold || PetscRealPart(pval[j]) <= pmax_neg * cls->interp_threshold) { 482 if (pcol[j] >= pcs && pcol[j] < pcf) { 483 lsparse[i - ps]++; 484 } else { 485 gsparse[i - ps]++; 486 } 487 } 488 } 489 PetscCall(MatRestoreRow(*P, i, &ncols, &pcol, &pval)); 490 } 491 492 PetscCall(PetscMalloc2(cmax, &pnval, cmax, &pncol)); 493 494 PetscCall(MatGetType(*P, &mtype)); 495 PetscCall(MatCreate(PetscObjectComm((PetscObject)*P), &Pnew)); 496 PetscCall(MatSetType(Pnew, mtype)); 497 PetscCall(MatSetSizes(Pnew, pn, pcn, PETSC_DETERMINE, PETSC_DETERMINE)); 498 PetscCall(MatSeqAIJSetPreallocation(Pnew, 0, lsparse)); 499 PetscCall(MatMPIAIJSetPreallocation(Pnew, 0, lsparse, 0, gsparse)); 500 501 for (i = ps; i < pf; i++) { 502 PetscCall(MatGetRow(*P, i, &ncols, &pcol, &pval)); 503 pmax_pos = 0.; 504 pmax_neg = 0.; 505 for (j = 0; j < ncols; j++) { 506 if (PetscRealPart(pval[j]) > pmax_pos) { 507 pmax_pos = PetscRealPart(pval[j]); 508 } else if (PetscRealPart(pval[j]) < pmax_neg) { 509 pmax_neg = PetscRealPart(pval[j]); 510 } 511 } 512 pthresh_pos = 0.; 513 pthresh_neg = 0.; 514 ptot_pos = 0.; 515 ptot_neg = 0.; 516 for (j = 0; j < ncols; j++) { 517 if (PetscRealPart(pval[j]) >= cls->interp_threshold * pmax_pos) { 518 pthresh_pos += PetscRealPart(pval[j]); 519 } else if (PetscRealPart(pval[j]) <= cls->interp_threshold * pmax_neg) { 520 pthresh_neg += PetscRealPart(pval[j]); 521 } 522 if (PetscRealPart(pval[j]) > 0.) { 523 ptot_pos += PetscRealPart(pval[j]); 524 } else { 525 ptot_neg += PetscRealPart(pval[j]); 526 } 527 } 528 if (PetscAbsReal(pthresh_pos) > 0.) ptot_pos /= pthresh_pos; 529 if (PetscAbsReal(pthresh_neg) > 0.) ptot_neg /= pthresh_neg; 530 idx = 0; 531 for (j = 0; j < ncols; j++) { 532 if (PetscRealPart(pval[j]) >= pmax_pos * cls->interp_threshold) { 533 pnval[idx] = ptot_pos * pval[j]; 534 pncol[idx] = pcol[j]; 535 idx++; 536 } else if (PetscRealPart(pval[j]) <= pmax_neg * cls->interp_threshold) { 537 pnval[idx] = ptot_neg * pval[j]; 538 pncol[idx] = pcol[j]; 539 idx++; 540 } 541 } 542 PetscCall(MatRestoreRow(*P, i, &ncols, &pcol, &pval)); 543 PetscCall(MatSetValues(Pnew, 1, &i, idx, pncol, pnval, INSERT_VALUES)); 544 } 545 546 PetscCall(MatAssemblyBegin(Pnew, MAT_FINAL_ASSEMBLY)); 547 PetscCall(MatAssemblyEnd(Pnew, MAT_FINAL_ASSEMBLY)); 548 PetscCall(MatDestroy(P)); 549 550 *P = Pnew; 551 PetscCall(PetscFree2(lsparse, gsparse)); 552 PetscCall(PetscFree2(pnval, pncol)); 553 PetscFunctionReturn(PETSC_SUCCESS); 554 } 555 556 static PetscErrorCode PCGAMGProlongator_Classical_Standard(PC pc, Mat A, PetscCoarsenData *agg_lists, Mat *P) 557 { 558 Mat lA, *lAs; 559 MatType mtype; 560 Vec cv; 561 PetscInt *gcid, *lcid, *lsparse, *gsparse, *picol; 562 PetscInt fs, fe, cs, ce, nl, i, j, k, li, lni, ci, ncols, maxcols, fn, cn, cid; 563 PetscMPIInt size; 564 const PetscInt *lidx, *icol, *gidx; 565 PetscBool iscoarse; 566 PetscScalar vi, pentry, pjentry; 567 PetscScalar *pcontrib, *pvcol; 568 const PetscScalar *vcol; 569 PetscReal diag, jdiag, jwttotal; 570 PetscInt pncols; 571 PetscSF sf; 572 PetscLayout clayout; 573 IS lis; 574 575 PetscFunctionBegin; 576 PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size)); 577 PetscCall(MatGetOwnershipRange(A, &fs, &fe)); 578 fn = fe - fs; 579 PetscCall(ISCreateStride(PETSC_COMM_SELF, fe - fs, fs, 1, &lis)); 580 if (size > 1) { 581 PetscCall(MatGetLayouts(A, NULL, &clayout)); 582 /* increase the overlap by two to get neighbors of neighbors */ 583 PetscCall(MatIncreaseOverlap(A, 1, &lis, 2)); 584 PetscCall(ISSort(lis)); 585 /* get the local part of A */ 586 PetscCall(MatCreateSubMatrices(A, 1, &lis, &lis, MAT_INITIAL_MATRIX, &lAs)); 587 lA = lAs[0]; 588 /* build an SF out of it */ 589 PetscCall(ISGetLocalSize(lis, &nl)); 590 PetscCall(PetscSFCreate(PetscObjectComm((PetscObject)A), &sf)); 591 PetscCall(ISGetIndices(lis, &lidx)); 592 PetscCall(PetscSFSetGraphLayout(sf, clayout, nl, NULL, PETSC_COPY_VALUES, lidx)); 593 PetscCall(ISRestoreIndices(lis, &lidx)); 594 } else { 595 lA = A; 596 nl = fn; 597 } 598 /* create a communication structure for the overlapped portion and transmit coarse indices */ 599 PetscCall(PetscMalloc3(fn, &lsparse, fn, &gsparse, nl, &pcontrib)); 600 /* create coarse vector */ 601 cn = 0; 602 for (i = 0; i < fn; i++) { 603 PetscCall(PetscCDIsEmptyAt(agg_lists, i, &iscoarse)); 604 if (!iscoarse) cn++; 605 } 606 PetscCall(PetscMalloc1(fn, &gcid)); 607 PetscCall(VecCreateMPI(PetscObjectComm((PetscObject)A), cn, PETSC_DECIDE, &cv)); 608 PetscCall(VecGetOwnershipRange(cv, &cs, &ce)); 609 cn = 0; 610 for (i = 0; i < fn; i++) { 611 PetscCall(PetscCDIsEmptyAt(agg_lists, i, &iscoarse)); 612 if (!iscoarse) { 613 gcid[i] = cs + cn; 614 cn++; 615 } else { 616 gcid[i] = -1; 617 } 618 } 619 if (size > 1) { 620 PetscCall(PetscMalloc1(nl, &lcid)); 621 PetscCall(PetscSFBcastBegin(sf, MPIU_INT, gcid, lcid, MPI_REPLACE)); 622 PetscCall(PetscSFBcastEnd(sf, MPIU_INT, gcid, lcid, MPI_REPLACE)); 623 } else { 624 lcid = gcid; 625 } 626 /* count to preallocate the prolongator */ 627 PetscCall(ISGetIndices(lis, &gidx)); 628 maxcols = 0; 629 /* count the number of unique contributing coarse cells for each fine */ 630 for (i = 0; i < nl; i++) { 631 pcontrib[i] = 0.; 632 PetscCall(MatGetRow(lA, i, &ncols, &icol, NULL)); 633 if (gidx[i] >= fs && gidx[i] < fe) { 634 li = gidx[i] - fs; 635 lsparse[li] = 0; 636 gsparse[li] = 0; 637 cid = lcid[i]; 638 if (cid >= 0) { 639 lsparse[li] = 1; 640 } else { 641 for (j = 0; j < ncols; j++) { 642 if (lcid[icol[j]] >= 0) { 643 pcontrib[icol[j]] = 1.; 644 } else { 645 ci = icol[j]; 646 PetscCall(MatRestoreRow(lA, i, &ncols, &icol, NULL)); 647 PetscCall(MatGetRow(lA, ci, &ncols, &icol, NULL)); 648 for (k = 0; k < ncols; k++) { 649 if (lcid[icol[k]] >= 0) pcontrib[icol[k]] = 1.; 650 } 651 PetscCall(MatRestoreRow(lA, ci, &ncols, &icol, NULL)); 652 PetscCall(MatGetRow(lA, i, &ncols, &icol, NULL)); 653 } 654 } 655 for (j = 0; j < ncols; j++) { 656 if (lcid[icol[j]] >= 0 && pcontrib[icol[j]] != 0.) { 657 lni = lcid[icol[j]]; 658 if (lni >= cs && lni < ce) { 659 lsparse[li]++; 660 } else { 661 gsparse[li]++; 662 } 663 pcontrib[icol[j]] = 0.; 664 } else { 665 ci = icol[j]; 666 PetscCall(MatRestoreRow(lA, i, &ncols, &icol, NULL)); 667 PetscCall(MatGetRow(lA, ci, &ncols, &icol, NULL)); 668 for (k = 0; k < ncols; k++) { 669 if (lcid[icol[k]] >= 0 && pcontrib[icol[k]] != 0.) { 670 lni = lcid[icol[k]]; 671 if (lni >= cs && lni < ce) { 672 lsparse[li]++; 673 } else { 674 gsparse[li]++; 675 } 676 pcontrib[icol[k]] = 0.; 677 } 678 } 679 PetscCall(MatRestoreRow(lA, ci, &ncols, &icol, NULL)); 680 PetscCall(MatGetRow(lA, i, &ncols, &icol, NULL)); 681 } 682 } 683 } 684 if (lsparse[li] + gsparse[li] > maxcols) maxcols = lsparse[li] + gsparse[li]; 685 } 686 PetscCall(MatRestoreRow(lA, i, &ncols, &icol, &vcol)); 687 } 688 PetscCall(PetscMalloc2(maxcols, &picol, maxcols, &pvcol)); 689 PetscCall(MatCreate(PetscObjectComm((PetscObject)A), P)); 690 PetscCall(MatGetType(A, &mtype)); 691 PetscCall(MatSetType(*P, mtype)); 692 PetscCall(MatSetSizes(*P, fn, cn, PETSC_DETERMINE, PETSC_DETERMINE)); 693 PetscCall(MatMPIAIJSetPreallocation(*P, 0, lsparse, 0, gsparse)); 694 PetscCall(MatSeqAIJSetPreallocation(*P, 0, lsparse)); 695 for (i = 0; i < nl; i++) { 696 diag = 0.; 697 if (gidx[i] >= fs && gidx[i] < fe) { 698 pncols = 0; 699 cid = lcid[i]; 700 if (cid >= 0) { 701 pncols = 1; 702 picol[0] = cid; 703 pvcol[0] = 1.; 704 } else { 705 PetscCall(MatGetRow(lA, i, &ncols, &icol, &vcol)); 706 for (j = 0; j < ncols; j++) { 707 pentry = vcol[j]; 708 if (lcid[icol[j]] >= 0) { 709 /* coarse neighbor */ 710 pcontrib[icol[j]] += pentry; 711 } else if (icol[j] != i) { 712 /* the neighbor is a strongly connected fine node */ 713 ci = icol[j]; 714 vi = vcol[j]; 715 PetscCall(MatRestoreRow(lA, i, &ncols, &icol, &vcol)); 716 PetscCall(MatGetRow(lA, ci, &ncols, &icol, &vcol)); 717 jwttotal = 0.; 718 jdiag = 0.; 719 for (k = 0; k < ncols; k++) { 720 if (ci == icol[k]) jdiag = PetscRealPart(vcol[k]); 721 } 722 for (k = 0; k < ncols; k++) { 723 if (lcid[icol[k]] >= 0 && jdiag * PetscRealPart(vcol[k]) < 0.) { 724 pjentry = vcol[k]; 725 jwttotal += PetscRealPart(pjentry); 726 } 727 } 728 if (jwttotal != 0.) { 729 jwttotal = PetscRealPart(vi) / jwttotal; 730 for (k = 0; k < ncols; k++) { 731 if (lcid[icol[k]] >= 0 && jdiag * PetscRealPart(vcol[k]) < 0.) { 732 pjentry = vcol[k] * jwttotal; 733 pcontrib[icol[k]] += pjentry; 734 } 735 } 736 } else { 737 diag += PetscRealPart(vi); 738 } 739 PetscCall(MatRestoreRow(lA, ci, &ncols, &icol, &vcol)); 740 PetscCall(MatGetRow(lA, i, &ncols, &icol, &vcol)); 741 } else { 742 diag += PetscRealPart(vcol[j]); 743 } 744 } 745 if (diag != 0.) { 746 diag = 1. / diag; 747 for (j = 0; j < ncols; j++) { 748 if (lcid[icol[j]] >= 0 && pcontrib[icol[j]] != 0.) { 749 /* the neighbor is a coarse node */ 750 if (PetscAbsScalar(pcontrib[icol[j]]) > 0.0) { 751 lni = lcid[icol[j]]; 752 pvcol[pncols] = -pcontrib[icol[j]] * diag; 753 picol[pncols] = lni; 754 pncols++; 755 } 756 pcontrib[icol[j]] = 0.; 757 } else { 758 /* the neighbor is a strongly connected fine node */ 759 ci = icol[j]; 760 PetscCall(MatRestoreRow(lA, i, &ncols, &icol, &vcol)); 761 PetscCall(MatGetRow(lA, ci, &ncols, &icol, &vcol)); 762 for (k = 0; k < ncols; k++) { 763 if (lcid[icol[k]] >= 0 && pcontrib[icol[k]] != 0.) { 764 if (PetscAbsScalar(pcontrib[icol[k]]) > 0.0) { 765 lni = lcid[icol[k]]; 766 pvcol[pncols] = -pcontrib[icol[k]] * diag; 767 picol[pncols] = lni; 768 pncols++; 769 } 770 pcontrib[icol[k]] = 0.; 771 } 772 } 773 PetscCall(MatRestoreRow(lA, ci, &ncols, &icol, &vcol)); 774 PetscCall(MatGetRow(lA, i, &ncols, &icol, &vcol)); 775 } 776 pcontrib[icol[j]] = 0.; 777 } 778 PetscCall(MatRestoreRow(lA, i, &ncols, &icol, &vcol)); 779 } 780 } 781 ci = gidx[i]; 782 if (pncols > 0) PetscCall(MatSetValues(*P, 1, &ci, pncols, picol, pvcol, INSERT_VALUES)); 783 } 784 } 785 PetscCall(ISRestoreIndices(lis, &gidx)); 786 PetscCall(PetscFree2(picol, pvcol)); 787 PetscCall(PetscFree3(lsparse, gsparse, pcontrib)); 788 PetscCall(ISDestroy(&lis)); 789 PetscCall(PetscFree(gcid)); 790 if (size > 1) { 791 PetscCall(PetscFree(lcid)); 792 PetscCall(MatDestroyMatrices(1, &lAs)); 793 PetscCall(PetscSFDestroy(&sf)); 794 } 795 PetscCall(VecDestroy(&cv)); 796 PetscCall(MatAssemblyBegin(*P, MAT_FINAL_ASSEMBLY)); 797 PetscCall(MatAssemblyEnd(*P, MAT_FINAL_ASSEMBLY)); 798 PetscFunctionReturn(PETSC_SUCCESS); 799 } 800 801 static PetscErrorCode PCGAMGOptProlongator_Classical_Jacobi(PC pc, Mat A, Mat *P) 802 { 803 PetscInt f, s, n, cf, cs, i, idx; 804 PetscInt *coarserows; 805 PetscInt ncols; 806 const PetscInt *pcols; 807 const PetscScalar *pvals; 808 Mat Pnew; 809 Vec diag; 810 PC_MG *mg = (PC_MG *)pc->data; 811 PC_GAMG *pc_gamg = (PC_GAMG *)mg->innerctx; 812 PC_GAMG_Classical *cls = (PC_GAMG_Classical *)pc_gamg->subctx; 813 814 PetscFunctionBegin; 815 if (cls->nsmooths == 0) { 816 PetscCall(PCGAMGTruncateProlongator_Private(pc, P)); 817 PetscFunctionReturn(PETSC_SUCCESS); 818 } 819 PetscCall(MatGetOwnershipRange(*P, &s, &f)); 820 n = f - s; 821 PetscCall(MatGetOwnershipRangeColumn(*P, &cs, &cf)); 822 PetscCall(PetscMalloc1(n, &coarserows)); 823 /* identify the rows corresponding to coarse unknowns */ 824 idx = 0; 825 for (i = s; i < f; i++) { 826 PetscCall(MatGetRow(*P, i, &ncols, &pcols, &pvals)); 827 /* assume, for now, that it's a coarse unknown if it has a single unit entry */ 828 if (ncols == 1) { 829 if (pvals[0] == 1.) { 830 coarserows[idx] = i; 831 idx++; 832 } 833 } 834 PetscCall(MatRestoreRow(*P, i, &ncols, &pcols, &pvals)); 835 } 836 PetscCall(MatCreateVecs(A, &diag, NULL)); 837 PetscCall(MatGetDiagonal(A, diag)); 838 PetscCall(VecReciprocal(diag)); 839 for (i = 0; i < cls->nsmooths; i++) { 840 PetscCall(MatMatMult(A, *P, MAT_INITIAL_MATRIX, PETSC_CURRENT, &Pnew)); 841 PetscCall(MatZeroRows(Pnew, idx, coarserows, 0., NULL, NULL)); 842 PetscCall(MatDiagonalScale(Pnew, diag, NULL)); 843 PetscCall(MatAYPX(Pnew, -1.0, *P, DIFFERENT_NONZERO_PATTERN)); 844 PetscCall(MatDestroy(P)); 845 *P = Pnew; 846 Pnew = NULL; 847 } 848 PetscCall(VecDestroy(&diag)); 849 PetscCall(PetscFree(coarserows)); 850 PetscCall(PCGAMGTruncateProlongator_Private(pc, P)); 851 PetscFunctionReturn(PETSC_SUCCESS); 852 } 853 854 static PetscErrorCode PCGAMGProlongator_Classical(PC pc, Mat A, PetscCoarsenData *agg_lists, Mat *P) 855 { 856 PetscErrorCode (*f)(PC, Mat, PetscCoarsenData *, Mat *); 857 PC_MG *mg = (PC_MG *)pc->data; 858 PC_GAMG *pc_gamg = (PC_GAMG *)mg->innerctx; 859 PC_GAMG_Classical *cls = (PC_GAMG_Classical *)pc_gamg->subctx; 860 861 PetscFunctionBegin; 862 PetscCall(PetscFunctionListFind(PCGAMGClassicalProlongatorList, cls->prolongtype, &f)); 863 PetscCheck(f, PetscObjectComm((PetscObject)pc), PETSC_ERR_ARG_WRONGSTATE, "Cannot find PCGAMG Classical prolongator type"); 864 PetscCall((*f)(pc, A, agg_lists, P)); 865 PetscFunctionReturn(PETSC_SUCCESS); 866 } 867 868 static PetscErrorCode PCGAMGDestroy_Classical(PC pc) 869 { 870 PC_MG *mg = (PC_MG *)pc->data; 871 PC_GAMG *pc_gamg = (PC_GAMG *)mg->innerctx; 872 873 PetscFunctionBegin; 874 PetscCall(PetscFree(pc_gamg->subctx)); 875 PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCGAMGClassicalSetType_C", NULL)); 876 PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCGAMGClassicalGetType_C", NULL)); 877 PetscFunctionReturn(PETSC_SUCCESS); 878 } 879 880 static PetscErrorCode PCGAMGSetFromOptions_Classical(PC pc, PetscOptionItems PetscOptionsObject) 881 { 882 PC_MG *mg = (PC_MG *)pc->data; 883 PC_GAMG *pc_gamg = (PC_GAMG *)mg->innerctx; 884 PC_GAMG_Classical *cls = (PC_GAMG_Classical *)pc_gamg->subctx; 885 char tname[256]; 886 PetscBool flg; 887 888 PetscFunctionBegin; 889 PetscOptionsHeadBegin(PetscOptionsObject, "GAMG-Classical options"); 890 PetscCall(PetscOptionsFList("-pc_gamg_classical_type", "Type of Classical AMG prolongation", "PCGAMGClassicalSetType", PCGAMGClassicalProlongatorList, cls->prolongtype, tname, sizeof(tname), &flg)); 891 if (flg) PetscCall(PCGAMGClassicalSetType(pc, tname)); 892 PetscCall(PetscOptionsReal("-pc_gamg_classical_interp_threshold", "Threshold for classical interpolator entries", "", cls->interp_threshold, &cls->interp_threshold, NULL)); 893 PetscCall(PetscOptionsInt("-pc_gamg_classical_nsmooths", "Threshold for classical interpolator entries", "", cls->nsmooths, &cls->nsmooths, NULL)); 894 PetscOptionsHeadEnd(); 895 PetscFunctionReturn(PETSC_SUCCESS); 896 } 897 898 static PetscErrorCode PCGAMGSetData_Classical(PC pc, Mat A) 899 { 900 PC_MG *mg = (PC_MG *)pc->data; 901 PC_GAMG *pc_gamg = (PC_GAMG *)mg->innerctx; 902 903 PetscFunctionBegin; 904 /* no data for classical AMG */ 905 pc_gamg->data = NULL; 906 pc_gamg->data_cell_cols = 0; 907 pc_gamg->data_cell_rows = 0; 908 pc_gamg->data_sz = 0; 909 PetscFunctionReturn(PETSC_SUCCESS); 910 } 911 912 static PetscErrorCode PCGAMGClassicalFinalizePackage(void) 913 { 914 PetscFunctionBegin; 915 PCGAMGClassicalPackageInitialized = PETSC_FALSE; 916 PetscCall(PetscFunctionListDestroy(&PCGAMGClassicalProlongatorList)); 917 PetscFunctionReturn(PETSC_SUCCESS); 918 } 919 920 static PetscErrorCode PCGAMGClassicalInitializePackage(void) 921 { 922 PetscFunctionBegin; 923 if (PCGAMGClassicalPackageInitialized) PetscFunctionReturn(PETSC_SUCCESS); 924 PetscCall(PetscFunctionListAdd(&PCGAMGClassicalProlongatorList, PCGAMGCLASSICALDIRECT, PCGAMGProlongator_Classical_Direct)); 925 PetscCall(PetscFunctionListAdd(&PCGAMGClassicalProlongatorList, PCGAMGCLASSICALSTANDARD, PCGAMGProlongator_Classical_Standard)); 926 PetscCall(PetscRegisterFinalize(PCGAMGClassicalFinalizePackage)); 927 PetscFunctionReturn(PETSC_SUCCESS); 928 } 929 930 PetscErrorCode PCCreateGAMG_Classical(PC pc) 931 { 932 PC_MG *mg = (PC_MG *)pc->data; 933 PC_GAMG *pc_gamg = (PC_GAMG *)mg->innerctx; 934 PC_GAMG_Classical *pc_gamg_classical; 935 936 PetscFunctionBegin; 937 PetscCall(PCGAMGClassicalInitializePackage()); 938 if (pc_gamg->subctx) { 939 /* call base class */ 940 PetscCall(PCDestroy_GAMG(pc)); 941 } 942 943 /* create sub context for SA */ 944 PetscCall(PetscNew(&pc_gamg_classical)); 945 pc_gamg->subctx = pc_gamg_classical; 946 pc->ops->setfromoptions = PCGAMGSetFromOptions_Classical; 947 /* reset does not do anything; setup not virtual */ 948 949 /* set internal function pointers */ 950 pc_gamg->ops->destroy = PCGAMGDestroy_Classical; 951 pc_gamg->ops->creategraph = PCGAMGCreateGraph_Classical; 952 pc_gamg->ops->coarsen = PCGAMGCoarsen_Classical; 953 pc_gamg->ops->prolongator = PCGAMGProlongator_Classical; 954 pc_gamg->ops->optprolongator = PCGAMGOptProlongator_Classical_Jacobi; 955 pc_gamg->ops->setfromoptions = PCGAMGSetFromOptions_Classical; 956 957 pc_gamg->ops->createdefaultdata = PCGAMGSetData_Classical; 958 pc_gamg_classical->interp_threshold = 0.2; 959 pc_gamg_classical->nsmooths = 0; 960 PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCGAMGClassicalSetType_C", PCGAMGClassicalSetType_GAMG)); 961 PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCGAMGClassicalGetType_C", PCGAMGClassicalGetType_GAMG)); 962 PetscCall(PCGAMGClassicalSetType(pc, PCGAMGCLASSICALSTANDARD)); 963 PetscFunctionReturn(PETSC_SUCCESS); 964 } 965