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