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