1 2 /* 3 Defines the multigrid preconditioner interface. 4 */ 5 #include <petsc/private/pcmgimpl.h> /*I "petscksp.h" I*/ 6 #include <petscdm.h> 7 8 PetscErrorCode PCMGMCycle_Private(PC pc,PC_MG_Levels **mglevelsin,PCRichardsonConvergedReason *reason) 9 { 10 PC_MG *mg = (PC_MG*)pc->data; 11 PC_MG_Levels *mgc,*mglevels = *mglevelsin; 12 PetscErrorCode ierr; 13 PetscInt cycles = (mglevels->level == 1) ? 1 : (PetscInt) mglevels->cycles; 14 PC subpc; 15 PCFailedReason pcreason; 16 17 PetscFunctionBegin; 18 if (mglevels->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 19 ierr = KSPSolve(mglevels->smoothd,mglevels->b,mglevels->x);CHKERRQ(ierr); /* pre-smooth */ 20 ierr = KSPGetPC(mglevels->smoothd,&subpc);CHKERRQ(ierr); 21 ierr = PCGetSetUpFailedReason(subpc,&pcreason);CHKERRQ(ierr); 22 if (pcreason) { 23 pc->failedreason = PC_SUBPC_ERROR; 24 } 25 if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 26 if (mglevels->level) { /* not the coarsest grid */ 27 if (mglevels->eventresidual) {ierr = PetscLogEventBegin(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);} 28 ierr = (*mglevels->residual)(mglevels->A,mglevels->b,mglevels->x,mglevels->r);CHKERRQ(ierr); 29 if (mglevels->eventresidual) {ierr = PetscLogEventEnd(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);} 30 31 /* if on finest level and have convergence criteria set */ 32 if (mglevels->level == mglevels->levels-1 && mg->ttol && reason) { 33 PetscReal rnorm; 34 ierr = VecNorm(mglevels->r,NORM_2,&rnorm);CHKERRQ(ierr); 35 if (rnorm <= mg->ttol) { 36 if (rnorm < mg->abstol) { 37 *reason = PCRICHARDSON_CONVERGED_ATOL; 38 ierr = PetscInfo2(pc,"Linear solver has converged. Residual norm %g is less than absolute tolerance %g\n",(double)rnorm,(double)mg->abstol);CHKERRQ(ierr); 39 } else { 40 *reason = PCRICHARDSON_CONVERGED_RTOL; 41 ierr = PetscInfo2(pc,"Linear solver has converged. Residual norm %g is less than relative tolerance times initial residual norm %g\n",(double)rnorm,(double)mg->ttol);CHKERRQ(ierr); 42 } 43 PetscFunctionReturn(0); 44 } 45 } 46 47 mgc = *(mglevelsin - 1); 48 if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 49 ierr = MatRestrict(mglevels->restrct,mglevels->r,mgc->b);CHKERRQ(ierr); 50 if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 51 ierr = VecSet(mgc->x,0.0);CHKERRQ(ierr); 52 while (cycles--) { 53 ierr = PCMGMCycle_Private(pc,mglevelsin-1,reason);CHKERRQ(ierr); 54 } 55 if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 56 ierr = MatInterpolateAdd(mglevels->interpolate,mgc->x,mglevels->x,mglevels->x);CHKERRQ(ierr); 57 if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 58 if (mglevels->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 59 ierr = KSPSolve(mglevels->smoothu,mglevels->b,mglevels->x);CHKERRQ(ierr); /* post smooth */ 60 if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 61 } 62 PetscFunctionReturn(0); 63 } 64 65 static PetscErrorCode PCApplyRichardson_MG(PC pc,Vec b,Vec x,Vec w,PetscReal rtol,PetscReal abstol, PetscReal dtol,PetscInt its,PetscBool zeroguess,PetscInt *outits,PCRichardsonConvergedReason *reason) 66 { 67 PC_MG *mg = (PC_MG*)pc->data; 68 PC_MG_Levels **mglevels = mg->levels; 69 PetscErrorCode ierr; 70 PetscInt levels = mglevels[0]->levels,i; 71 72 PetscFunctionBegin; 73 /* When the DM is supplying the matrix then it will not exist until here */ 74 for (i=0; i<levels; i++) { 75 if (!mglevels[i]->A) { 76 ierr = KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);CHKERRQ(ierr); 77 ierr = PetscObjectReference((PetscObject)mglevels[i]->A);CHKERRQ(ierr); 78 } 79 } 80 mglevels[levels-1]->b = b; 81 mglevels[levels-1]->x = x; 82 83 mg->rtol = rtol; 84 mg->abstol = abstol; 85 mg->dtol = dtol; 86 if (rtol) { 87 /* compute initial residual norm for relative convergence test */ 88 PetscReal rnorm; 89 if (zeroguess) { 90 ierr = VecNorm(b,NORM_2,&rnorm);CHKERRQ(ierr); 91 } else { 92 ierr = (*mglevels[levels-1]->residual)(mglevels[levels-1]->A,b,x,w);CHKERRQ(ierr); 93 ierr = VecNorm(w,NORM_2,&rnorm);CHKERRQ(ierr); 94 } 95 mg->ttol = PetscMax(rtol*rnorm,abstol); 96 } else if (abstol) mg->ttol = abstol; 97 else mg->ttol = 0.0; 98 99 /* since smoother is applied to full system, not just residual we need to make sure that smoothers don't 100 stop prematurely due to small residual */ 101 for (i=1; i<levels; i++) { 102 ierr = KSPSetTolerances(mglevels[i]->smoothu,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr); 103 if (mglevels[i]->smoothu != mglevels[i]->smoothd) { 104 /* For Richardson the initial guess is nonzero since it is solving in each cycle the original system not just applying as a preconditioner */ 105 ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr); 106 ierr = KSPSetTolerances(mglevels[i]->smoothd,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr); 107 } 108 } 109 110 *reason = (PCRichardsonConvergedReason)0; 111 for (i=0; i<its; i++) { 112 ierr = PCMGMCycle_Private(pc,mglevels+levels-1,reason);CHKERRQ(ierr); 113 if (*reason) break; 114 } 115 if (!*reason) *reason = PCRICHARDSON_CONVERGED_ITS; 116 *outits = i; 117 PetscFunctionReturn(0); 118 } 119 120 PetscErrorCode PCReset_MG(PC pc) 121 { 122 PC_MG *mg = (PC_MG*)pc->data; 123 PC_MG_Levels **mglevels = mg->levels; 124 PetscErrorCode ierr; 125 PetscInt i,n; 126 127 PetscFunctionBegin; 128 if (mglevels) { 129 n = mglevels[0]->levels; 130 for (i=0; i<n-1; i++) { 131 ierr = VecDestroy(&mglevels[i+1]->r);CHKERRQ(ierr); 132 ierr = VecDestroy(&mglevels[i]->b);CHKERRQ(ierr); 133 ierr = VecDestroy(&mglevels[i]->x);CHKERRQ(ierr); 134 ierr = MatDestroy(&mglevels[i+1]->restrct);CHKERRQ(ierr); 135 ierr = MatDestroy(&mglevels[i+1]->interpolate);CHKERRQ(ierr); 136 ierr = VecDestroy(&mglevels[i+1]->rscale);CHKERRQ(ierr); 137 } 138 139 for (i=0; i<n; i++) { 140 ierr = MatDestroy(&mglevels[i]->A);CHKERRQ(ierr); 141 if (mglevels[i]->smoothd != mglevels[i]->smoothu) { 142 ierr = KSPReset(mglevels[i]->smoothd);CHKERRQ(ierr); 143 } 144 ierr = KSPReset(mglevels[i]->smoothu);CHKERRQ(ierr); 145 } 146 } 147 PetscFunctionReturn(0); 148 } 149 150 /*@C 151 PCMGSetLevels - Sets the number of levels to use with MG. 152 Must be called before any other MG routine. 153 154 Logically Collective on PC 155 156 Input Parameters: 157 + pc - the preconditioner context 158 . levels - the number of levels 159 - comms - optional communicators for each level; this is to allow solving the coarser problems 160 on smaller sets of processors. 161 162 Level: intermediate 163 164 Notes: 165 If the number of levels is one then the multigrid uses the -mg_levels prefix 166 for setting the level options rather than the -mg_coarse prefix. 167 168 .keywords: MG, set, levels, multigrid 169 170 .seealso: PCMGSetType(), PCMGGetLevels() 171 @*/ 172 PetscErrorCode PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms) 173 { 174 PetscErrorCode ierr; 175 PC_MG *mg = (PC_MG*)pc->data; 176 MPI_Comm comm; 177 PC_MG_Levels **mglevels = mg->levels; 178 PCMGType mgtype = mg->am; 179 PetscInt mgctype = (PetscInt) PC_MG_CYCLE_V; 180 PetscInt i; 181 PetscMPIInt size; 182 const char *prefix; 183 PC ipc; 184 PetscInt n; 185 186 PetscFunctionBegin; 187 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 188 PetscValidLogicalCollectiveInt(pc,levels,2); 189 ierr = PetscObjectGetComm((PetscObject)pc,&comm);CHKERRQ(ierr); 190 if (mg->nlevels == levels) PetscFunctionReturn(0); 191 if (mglevels) { 192 mgctype = mglevels[0]->cycles; 193 /* changing the number of levels so free up the previous stuff */ 194 ierr = PCReset_MG(pc);CHKERRQ(ierr); 195 n = mglevels[0]->levels; 196 for (i=0; i<n; i++) { 197 if (mglevels[i]->smoothd != mglevels[i]->smoothu) { 198 ierr = KSPDestroy(&mglevels[i]->smoothd);CHKERRQ(ierr); 199 } 200 ierr = KSPDestroy(&mglevels[i]->smoothu);CHKERRQ(ierr); 201 ierr = PetscFree(mglevels[i]);CHKERRQ(ierr); 202 } 203 ierr = PetscFree(mg->levels);CHKERRQ(ierr); 204 } 205 206 mg->nlevels = levels; 207 208 ierr = PetscMalloc1(levels,&mglevels);CHKERRQ(ierr); 209 ierr = PetscLogObjectMemory((PetscObject)pc,levels*(sizeof(PC_MG*)));CHKERRQ(ierr); 210 211 ierr = PCGetOptionsPrefix(pc,&prefix);CHKERRQ(ierr); 212 213 mg->stageApply = 0; 214 for (i=0; i<levels; i++) { 215 ierr = PetscNewLog(pc,&mglevels[i]);CHKERRQ(ierr); 216 217 mglevels[i]->level = i; 218 mglevels[i]->levels = levels; 219 mglevels[i]->cycles = mgctype; 220 mg->default_smoothu = 2; 221 mg->default_smoothd = 2; 222 mglevels[i]->eventsmoothsetup = 0; 223 mglevels[i]->eventsmoothsolve = 0; 224 mglevels[i]->eventresidual = 0; 225 mglevels[i]->eventinterprestrict = 0; 226 227 if (comms) comm = comms[i]; 228 ierr = KSPCreate(comm,&mglevels[i]->smoothd);CHKERRQ(ierr); 229 ierr = KSPSetErrorIfNotConverged(mglevels[i]->smoothd,pc->erroriffailure);CHKERRQ(ierr); 230 ierr = PetscObjectIncrementTabLevel((PetscObject)mglevels[i]->smoothd,(PetscObject)pc,levels-i);CHKERRQ(ierr); 231 ierr = KSPSetOptionsPrefix(mglevels[i]->smoothd,prefix);CHKERRQ(ierr); 232 ierr = PetscObjectComposedDataSetInt((PetscObject) mglevels[i]->smoothd, PetscMGLevelId, mglevels[i]->level);CHKERRQ(ierr); 233 if (i || levels == 1) { 234 char tprefix[128]; 235 236 ierr = KSPSetType(mglevels[i]->smoothd,KSPCHEBYSHEV);CHKERRQ(ierr); 237 ierr = KSPSetConvergenceTest(mglevels[i]->smoothd,KSPConvergedSkip,NULL,NULL);CHKERRQ(ierr); 238 ierr = KSPSetNormType(mglevels[i]->smoothd,KSP_NORM_NONE);CHKERRQ(ierr); 239 ierr = KSPGetPC(mglevels[i]->smoothd,&ipc);CHKERRQ(ierr); 240 ierr = PCSetType(ipc,PCSOR);CHKERRQ(ierr); 241 ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, mg->default_smoothd);CHKERRQ(ierr); 242 243 sprintf(tprefix,"mg_levels_%d_",(int)i); 244 ierr = KSPAppendOptionsPrefix(mglevels[i]->smoothd,tprefix);CHKERRQ(ierr); 245 } else { 246 ierr = KSPAppendOptionsPrefix(mglevels[0]->smoothd,"mg_coarse_");CHKERRQ(ierr); 247 248 /* coarse solve is (redundant) LU by default; set shifttype NONZERO to avoid annoying zero-pivot in LU preconditioner */ 249 ierr = KSPSetType(mglevels[0]->smoothd,KSPPREONLY);CHKERRQ(ierr); 250 ierr = KSPGetPC(mglevels[0]->smoothd,&ipc);CHKERRQ(ierr); 251 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 252 if (size > 1) { 253 ierr = PCSetType(ipc,PCREDUNDANT);CHKERRQ(ierr); 254 } else { 255 ierr = PCSetType(ipc,PCLU);CHKERRQ(ierr); 256 } 257 ierr = PCFactorSetShiftType(ipc,MAT_SHIFT_INBLOCKS);CHKERRQ(ierr); 258 } 259 ierr = PetscLogObjectParent((PetscObject)pc,(PetscObject)mglevels[i]->smoothd);CHKERRQ(ierr); 260 261 mglevels[i]->smoothu = mglevels[i]->smoothd; 262 mg->rtol = 0.0; 263 mg->abstol = 0.0; 264 mg->dtol = 0.0; 265 mg->ttol = 0.0; 266 mg->cyclesperpcapply = 1; 267 } 268 mg->levels = mglevels; 269 ierr = PCMGSetType(pc,mgtype);CHKERRQ(ierr); 270 PetscFunctionReturn(0); 271 } 272 273 274 PetscErrorCode PCDestroy_MG(PC pc) 275 { 276 PetscErrorCode ierr; 277 PC_MG *mg = (PC_MG*)pc->data; 278 PC_MG_Levels **mglevels = mg->levels; 279 PetscInt i,n; 280 281 PetscFunctionBegin; 282 ierr = PCReset_MG(pc);CHKERRQ(ierr); 283 if (mglevels) { 284 n = mglevels[0]->levels; 285 for (i=0; i<n; i++) { 286 if (mglevels[i]->smoothd != mglevels[i]->smoothu) { 287 ierr = KSPDestroy(&mglevels[i]->smoothd);CHKERRQ(ierr); 288 } 289 ierr = KSPDestroy(&mglevels[i]->smoothu);CHKERRQ(ierr); 290 ierr = PetscFree(mglevels[i]);CHKERRQ(ierr); 291 } 292 ierr = PetscFree(mg->levels);CHKERRQ(ierr); 293 } 294 ierr = PetscFree(pc->data);CHKERRQ(ierr); 295 PetscFunctionReturn(0); 296 } 297 298 299 300 extern PetscErrorCode PCMGACycle_Private(PC,PC_MG_Levels**); 301 extern PetscErrorCode PCMGFCycle_Private(PC,PC_MG_Levels**); 302 extern PetscErrorCode PCMGKCycle_Private(PC,PC_MG_Levels**); 303 304 /* 305 PCApply_MG - Runs either an additive, multiplicative, Kaskadic 306 or full cycle of multigrid. 307 308 Note: 309 A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle(). 310 */ 311 static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x) 312 { 313 PC_MG *mg = (PC_MG*)pc->data; 314 PC_MG_Levels **mglevels = mg->levels; 315 PetscErrorCode ierr; 316 PetscInt levels = mglevels[0]->levels,i; 317 318 PetscFunctionBegin; 319 if (mg->stageApply) {ierr = PetscLogStagePush(mg->stageApply);CHKERRQ(ierr);} 320 /* When the DM is supplying the matrix then it will not exist until here */ 321 for (i=0; i<levels; i++) { 322 if (!mglevels[i]->A) { 323 ierr = KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);CHKERRQ(ierr); 324 ierr = PetscObjectReference((PetscObject)mglevels[i]->A);CHKERRQ(ierr); 325 } 326 } 327 328 mglevels[levels-1]->b = b; 329 mglevels[levels-1]->x = x; 330 if (mg->am == PC_MG_MULTIPLICATIVE) { 331 ierr = VecSet(x,0.0);CHKERRQ(ierr); 332 for (i=0; i<mg->cyclesperpcapply; i++) { 333 ierr = PCMGMCycle_Private(pc,mglevels+levels-1,NULL);CHKERRQ(ierr); 334 } 335 } else if (mg->am == PC_MG_ADDITIVE) { 336 ierr = PCMGACycle_Private(pc,mglevels);CHKERRQ(ierr); 337 } else if (mg->am == PC_MG_KASKADE) { 338 ierr = PCMGKCycle_Private(pc,mglevels);CHKERRQ(ierr); 339 } else { 340 ierr = PCMGFCycle_Private(pc,mglevels);CHKERRQ(ierr); 341 } 342 if (mg->stageApply) {ierr = PetscLogStagePop();CHKERRQ(ierr);} 343 PetscFunctionReturn(0); 344 } 345 346 347 PetscErrorCode PCSetFromOptions_MG(PetscOptionItems *PetscOptionsObject,PC pc) 348 { 349 PetscErrorCode ierr; 350 PetscInt m,levels = 1,cycles; 351 PetscBool flg; 352 PC_MG *mg = (PC_MG*)pc->data; 353 PC_MG_Levels **mglevels; 354 PCMGType mgtype; 355 PCMGCycleType mgctype; 356 PCMGGalerkinType gtype; 357 358 PetscFunctionBegin; 359 ierr = PetscOptionsHead(PetscOptionsObject,"Multigrid options");CHKERRQ(ierr); 360 if (!mg->levels) { 361 ierr = PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);CHKERRQ(ierr); 362 if (!flg && pc->dm) { 363 ierr = DMGetRefineLevel(pc->dm,&levels);CHKERRQ(ierr); 364 levels++; 365 mg->usedmfornumberoflevels = PETSC_TRUE; 366 } 367 ierr = PCMGSetLevels(pc,levels,NULL);CHKERRQ(ierr); 368 } 369 mglevels = mg->levels; 370 371 mgctype = (PCMGCycleType) mglevels[0]->cycles; 372 ierr = PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);CHKERRQ(ierr); 373 if (flg) { 374 ierr = PCMGSetCycleType(pc,mgctype);CHKERRQ(ierr); 375 } 376 gtype = mg->galerkin; 377 ierr = PetscOptionsEnum("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",PCMGGalerkinTypes,(PetscEnum)gtype,(PetscEnum*)>ype,&flg);CHKERRQ(ierr); 378 if (flg) { 379 ierr = PCMGSetGalerkin(pc,gtype);CHKERRQ(ierr); 380 } 381 ierr = PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",mg->default_smoothu,&m,&flg);CHKERRQ(ierr); 382 if (flg) { 383 ierr = PCMGSetNumberSmoothUp(pc,m);CHKERRQ(ierr); 384 } 385 ierr = PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",mg->default_smoothd,&m,&flg);CHKERRQ(ierr); 386 if (flg) { 387 ierr = PCMGSetNumberSmoothDown(pc,m);CHKERRQ(ierr); 388 } 389 mgtype = mg->am; 390 ierr = PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);CHKERRQ(ierr); 391 if (flg) { 392 ierr = PCMGSetType(pc,mgtype);CHKERRQ(ierr); 393 } 394 if (mg->am == PC_MG_MULTIPLICATIVE) { 395 ierr = PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGMultiplicativeSetCycles",mg->cyclesperpcapply,&cycles,&flg);CHKERRQ(ierr); 396 if (flg) { 397 ierr = PCMGMultiplicativeSetCycles(pc,cycles);CHKERRQ(ierr); 398 } 399 } 400 flg = PETSC_FALSE; 401 ierr = PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,NULL);CHKERRQ(ierr); 402 if (flg) { 403 PetscInt i; 404 char eventname[128]; 405 if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 406 levels = mglevels[0]->levels; 407 for (i=0; i<levels; i++) { 408 sprintf(eventname,"MGSetup Level %d",(int)i); 409 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);CHKERRQ(ierr); 410 sprintf(eventname,"MGSmooth Level %d",(int)i); 411 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);CHKERRQ(ierr); 412 if (i) { 413 sprintf(eventname,"MGResid Level %d",(int)i); 414 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);CHKERRQ(ierr); 415 sprintf(eventname,"MGInterp Level %d",(int)i); 416 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);CHKERRQ(ierr); 417 } 418 } 419 420 #if defined(PETSC_USE_LOG) 421 { 422 const char *sname = "MG Apply"; 423 PetscStageLog stageLog; 424 PetscInt st; 425 426 PetscFunctionBegin; 427 ierr = PetscLogGetStageLog(&stageLog);CHKERRQ(ierr); 428 for (st = 0; st < stageLog->numStages; ++st) { 429 PetscBool same; 430 431 ierr = PetscStrcmp(stageLog->stageInfo[st].name, sname, &same);CHKERRQ(ierr); 432 if (same) mg->stageApply = st; 433 } 434 if (!mg->stageApply) { 435 ierr = PetscLogStageRegister(sname, &mg->stageApply);CHKERRQ(ierr); 436 } 437 } 438 #endif 439 } 440 ierr = PetscOptionsTail();CHKERRQ(ierr); 441 PetscFunctionReturn(0); 442 } 443 444 const char *const PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0}; 445 const char *const PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",0}; 446 const char *const PCMGGalerkinTypes[] = {"both","pmat","mat","none","external","PCMGGalerkinType","PC_MG_GALERKIN",0}; 447 448 #include <petscdraw.h> 449 PetscErrorCode PCView_MG(PC pc,PetscViewer viewer) 450 { 451 PC_MG *mg = (PC_MG*)pc->data; 452 PC_MG_Levels **mglevels = mg->levels; 453 PetscErrorCode ierr; 454 PetscInt levels = mglevels ? mglevels[0]->levels : 0,i; 455 PetscBool iascii,isbinary,isdraw; 456 457 PetscFunctionBegin; 458 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 459 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 460 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 461 if (iascii) { 462 const char *cyclename = levels ? (mglevels[0]->cycles == PC_MG_CYCLE_V ? "v" : "w") : "unknown"; 463 ierr = PetscViewerASCIIPrintf(viewer," type is %s, levels=%D cycles=%s\n", PCMGTypes[mg->am],levels,cyclename);CHKERRQ(ierr); 464 if (mg->am == PC_MG_MULTIPLICATIVE) { 465 ierr = PetscViewerASCIIPrintf(viewer," Cycles per PCApply=%d\n",mg->cyclesperpcapply);CHKERRQ(ierr); 466 } 467 if (mg->galerkin == PC_MG_GALERKIN_BOTH) { 468 ierr = PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr); 469 } else if (mg->galerkin == PC_MG_GALERKIN_PMAT) { 470 ierr = PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices for pmat\n");CHKERRQ(ierr); 471 } else if (mg->galerkin == PC_MG_GALERKIN_MAT) { 472 ierr = PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices for mat\n");CHKERRQ(ierr); 473 } else if (mg->galerkin == PC_MG_GALERKIN_EXTERNAL) { 474 ierr = PetscViewerASCIIPrintf(viewer," Using externally compute Galerkin coarse grid matrices\n");CHKERRQ(ierr); 475 } else { 476 ierr = PetscViewerASCIIPrintf(viewer," Not using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr); 477 } 478 if (mg->view){ 479 ierr = (*mg->view)(pc,viewer);CHKERRQ(ierr); 480 } 481 for (i=0; i<levels; i++) { 482 if (!i) { 483 ierr = PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level -------------------------------\n",i);CHKERRQ(ierr); 484 } else { 485 ierr = PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr); 486 } 487 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 488 ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr); 489 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 490 if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) { 491 ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");CHKERRQ(ierr); 492 } else if (i) { 493 ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr); 494 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 495 ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr); 496 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 497 } 498 } 499 } else if (isbinary) { 500 for (i=levels-1; i>=0; i--) { 501 ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr); 502 if (i && mglevels[i]->smoothd != mglevels[i]->smoothu) { 503 ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr); 504 } 505 } 506 } else if (isdraw) { 507 PetscDraw draw; 508 PetscReal x,w,y,bottom,th; 509 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 510 ierr = PetscDrawGetCurrentPoint(draw,&x,&y);CHKERRQ(ierr); 511 ierr = PetscDrawStringGetSize(draw,NULL,&th);CHKERRQ(ierr); 512 bottom = y - th; 513 for (i=levels-1; i>=0; i--) { 514 if (!mglevels[i]->smoothu || (mglevels[i]->smoothu == mglevels[i]->smoothd)) { 515 ierr = PetscDrawPushCurrentPoint(draw,x,bottom);CHKERRQ(ierr); 516 ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr); 517 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 518 } else { 519 w = 0.5*PetscMin(1.0-x,x); 520 ierr = PetscDrawPushCurrentPoint(draw,x+w,bottom);CHKERRQ(ierr); 521 ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr); 522 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 523 ierr = PetscDrawPushCurrentPoint(draw,x-w,bottom);CHKERRQ(ierr); 524 ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr); 525 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 526 } 527 ierr = PetscDrawGetBoundingBox(draw,NULL,&bottom,NULL,NULL);CHKERRQ(ierr); 528 bottom -= th; 529 } 530 } 531 PetscFunctionReturn(0); 532 } 533 534 #include <petsc/private/dmimpl.h> 535 #include <petsc/private/kspimpl.h> 536 537 /* 538 Calls setup for the KSP on each level 539 */ 540 PetscErrorCode PCSetUp_MG(PC pc) 541 { 542 PC_MG *mg = (PC_MG*)pc->data; 543 PC_MG_Levels **mglevels = mg->levels; 544 PetscErrorCode ierr; 545 PetscInt i,n = mglevels[0]->levels; 546 PC cpc; 547 PetscBool dump = PETSC_FALSE,opsset,use_amat,missinginterpolate = PETSC_FALSE; 548 Mat dA,dB; 549 Vec tvec; 550 DM *dms; 551 PetscViewer viewer = 0; 552 PetscBool dAeqdB = PETSC_FALSE, needRestricts = PETSC_FALSE; 553 554 PetscFunctionBegin; 555 /* FIX: Move this to PCSetFromOptions_MG? */ 556 if (mg->usedmfornumberoflevels) { 557 PetscInt levels; 558 ierr = DMGetRefineLevel(pc->dm,&levels);CHKERRQ(ierr); 559 levels++; 560 if (levels > n) { /* the problem is now being solved on a finer grid */ 561 ierr = PCMGSetLevels(pc,levels,NULL);CHKERRQ(ierr); 562 n = levels; 563 ierr = PCSetFromOptions(pc);CHKERRQ(ierr); /* it is bad to call this here, but otherwise will never be called for the new hierarchy */ 564 mglevels = mg->levels; 565 } 566 } 567 ierr = KSPGetPC(mglevels[0]->smoothd,&cpc);CHKERRQ(ierr); 568 569 570 /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */ 571 /* so use those from global PC */ 572 /* Is this what we always want? What if user wants to keep old one? */ 573 ierr = KSPGetOperatorsSet(mglevels[n-1]->smoothd,NULL,&opsset);CHKERRQ(ierr); 574 if (opsset) { 575 Mat mmat; 576 ierr = KSPGetOperators(mglevels[n-1]->smoothd,NULL,&mmat);CHKERRQ(ierr); 577 if (mmat == pc->pmat) opsset = PETSC_FALSE; 578 } 579 580 if (!opsset) { 581 ierr = PCGetUseAmat(pc,&use_amat);CHKERRQ(ierr); 582 if(use_amat){ 583 ierr = PetscInfo(pc,"Using outer operators to define finest grid operator \n because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");CHKERRQ(ierr); 584 ierr = KSPSetOperators(mglevels[n-1]->smoothd,pc->mat,pc->pmat);CHKERRQ(ierr); 585 } 586 else { 587 ierr = PetscInfo(pc,"Using matrix (pmat) operators to define finest grid operator \n because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");CHKERRQ(ierr); 588 ierr = KSPSetOperators(mglevels[n-1]->smoothd,pc->pmat,pc->pmat);CHKERRQ(ierr); 589 } 590 } 591 592 for (i=n-1; i>0; i--) { 593 if (!(mglevels[i]->interpolate || mglevels[i]->restrct)) { 594 missinginterpolate = PETSC_TRUE; 595 continue; 596 } 597 } 598 599 ierr = KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB);CHKERRQ(ierr); 600 if (dA == dB) dAeqdB = PETSC_TRUE; 601 if ((mg->galerkin == PC_MG_GALERKIN_NONE) || (((mg->galerkin == PC_MG_GALERKIN_PMAT) || (mg->galerkin == PC_MG_GALERKIN_MAT)) && !dAeqdB)) { 602 needRestricts = PETSC_TRUE; /* user must compute either mat, pmat, or both so must restrict x to coarser levels */ 603 } 604 605 606 /* 607 Skipping if user has provided all interpolation/restriction needed (since DM might not be able to produce them (when coming from SNES/TS) 608 Skipping for galerkin==2 (externally managed hierarchy such as ML and GAMG). Cleaner logic here would be great. Wrap ML/GAMG as DMs? 609 */ 610 if (missinginterpolate && pc->dm && mg->galerkin != PC_MG_GALERKIN_EXTERNAL && !pc->setupcalled) { 611 /* set the mat type of coarse level operators to be AIJ. 612 It can be overwritten by -mat_type because KSPSetUp() reads command line options. 613 So we suggest to use -dm_mat_type for the fine level operator */ 614 ierr = DMSetMatType(pc->dm,MATAIJ);CHKERRQ(ierr); 615 /* construct the interpolation from the DMs */ 616 Mat p; 617 Vec rscale; 618 ierr = PetscMalloc1(n,&dms);CHKERRQ(ierr); 619 dms[n-1] = pc->dm; 620 /* Separately create them so we do not get DMKSP interference between levels */ 621 for (i=n-2; i>-1; i--) {ierr = DMCoarsen(dms[i+1],MPI_COMM_NULL,&dms[i]);CHKERRQ(ierr);} 622 for (i=n-2; i>-1; i--) { 623 DMKSP kdm; 624 PetscBool dmhasrestrict; 625 ierr = KSPSetDM(mglevels[i]->smoothd,dms[i]);CHKERRQ(ierr); 626 if (!needRestricts) {ierr = KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);CHKERRQ(ierr);} 627 ierr = DMGetDMKSPWrite(dms[i],&kdm);CHKERRQ(ierr); 628 /* Ugly hack so that the next KSPSetUp() will use the RHS that we set. A better fix is to change dmActive to take 629 * a bitwise OR of computing the matrix, RHS, and initial iterate. */ 630 kdm->ops->computerhs = NULL; 631 kdm->rhsctx = NULL; 632 if (!mglevels[i+1]->interpolate) { 633 ierr = DMCreateInterpolation(dms[i],dms[i+1],&p,&rscale);CHKERRQ(ierr); 634 ierr = PCMGSetInterpolation(pc,i+1,p);CHKERRQ(ierr); 635 if (rscale) {ierr = PCMGSetRScale(pc,i+1,rscale);CHKERRQ(ierr);} 636 ierr = VecDestroy(&rscale);CHKERRQ(ierr); 637 ierr = MatDestroy(&p);CHKERRQ(ierr); 638 } 639 ierr = DMHasCreateRestriction(dms[i],&dmhasrestrict);CHKERRQ(ierr); 640 if (dmhasrestrict && !mglevels[i+1]->restrct){ 641 ierr = DMCreateRestriction(dms[i],dms[i+1],&p);CHKERRQ(ierr); 642 ierr = PCMGSetRestriction(pc,i+1,p);CHKERRQ(ierr); 643 ierr = MatDestroy(&p);CHKERRQ(ierr); 644 } 645 } 646 647 for (i=n-2; i>-1; i--) {ierr = DMDestroy(&dms[i]);CHKERRQ(ierr);} 648 ierr = PetscFree(dms);CHKERRQ(ierr); 649 } 650 651 if (pc->dm && !pc->setupcalled) { 652 /* finest smoother also gets DM but it is not active, independent of whether galerkin==PC_MG_GALERKIN_EXTERNAL */ 653 ierr = KSPSetDM(mglevels[n-1]->smoothd,pc->dm);CHKERRQ(ierr); 654 ierr = KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);CHKERRQ(ierr); 655 } 656 657 if (mg->galerkin < PC_MG_GALERKIN_NONE) { 658 Mat A,B; 659 PetscBool doA = PETSC_FALSE,doB = PETSC_FALSE; 660 MatReuse reuse = MAT_INITIAL_MATRIX; 661 662 if ((mg->galerkin == PC_MG_GALERKIN_PMAT) || (mg->galerkin == PC_MG_GALERKIN_BOTH)) doB = PETSC_TRUE; 663 if ((mg->galerkin == PC_MG_GALERKIN_MAT) || ((mg->galerkin == PC_MG_GALERKIN_BOTH) && (dA != dB))) doA = PETSC_TRUE; 664 if (pc->setupcalled) reuse = MAT_REUSE_MATRIX; 665 for (i=n-2; i>-1; i--) { 666 if (!mglevels[i+1]->restrct && !mglevels[i+1]->interpolate) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must provide interpolation or restriction for each MG level except level 0"); 667 if (!mglevels[i+1]->interpolate) { 668 ierr = PCMGSetInterpolation(pc,i+1,mglevels[i+1]->restrct);CHKERRQ(ierr); 669 } 670 if (!mglevels[i+1]->restrct) { 671 ierr = PCMGSetRestriction(pc,i+1,mglevels[i+1]->interpolate);CHKERRQ(ierr); 672 } 673 if (reuse == MAT_REUSE_MATRIX) { 674 ierr = KSPGetOperators(mglevels[i]->smoothd,&A,&B);CHKERRQ(ierr); 675 } 676 if (doA) { 677 ierr = MatGalerkin(mglevels[i+1]->restrct,dA,mglevels[i+1]->interpolate,reuse,1.0,&A);CHKERRQ(ierr); 678 } 679 if (doB) { 680 ierr = MatGalerkin(mglevels[i+1]->restrct,dB,mglevels[i+1]->interpolate,reuse,1.0,&B);CHKERRQ(ierr); 681 } 682 /* the management of the PetscObjectReference() and PetscObjecDereference() below is rather delicate */ 683 if (!doA && dAeqdB) { 684 if (reuse == MAT_INITIAL_MATRIX) {ierr = PetscObjectReference((PetscObject)B);CHKERRQ(ierr);} 685 A = B; 686 } else if (!doA && reuse == MAT_INITIAL_MATRIX ) { 687 ierr = KSPGetOperators(mglevels[i]->smoothd,&A,NULL);CHKERRQ(ierr); 688 ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr); 689 } 690 if (!doB && dAeqdB) { 691 if (reuse == MAT_INITIAL_MATRIX) {ierr = PetscObjectReference((PetscObject)A);CHKERRQ(ierr);} 692 B = A; 693 } else if (!doB && reuse == MAT_INITIAL_MATRIX) { 694 ierr = KSPGetOperators(mglevels[i]->smoothd,NULL,&B);CHKERRQ(ierr); 695 ierr = PetscObjectReference((PetscObject)B);CHKERRQ(ierr); 696 } 697 if (reuse == MAT_INITIAL_MATRIX) { 698 ierr = KSPSetOperators(mglevels[i]->smoothd,A,B);CHKERRQ(ierr); 699 ierr = PetscObjectDereference((PetscObject)A);CHKERRQ(ierr); 700 ierr = PetscObjectDereference((PetscObject)B);CHKERRQ(ierr); 701 } 702 dA = A; 703 dB = B; 704 } 705 } 706 if (needRestricts && pc->dm && pc->dm->x) { 707 /* need to restrict Jacobian location to coarser meshes for evaluation */ 708 for (i=n-2; i>-1; i--) { 709 Mat R; 710 Vec rscale; 711 if (!mglevels[i]->smoothd->dm->x) { 712 Vec *vecs; 713 ierr = KSPCreateVecs(mglevels[i]->smoothd,1,&vecs,0,NULL);CHKERRQ(ierr); 714 mglevels[i]->smoothd->dm->x = vecs[0]; 715 ierr = PetscFree(vecs);CHKERRQ(ierr); 716 } 717 ierr = PCMGGetRestriction(pc,i+1,&R);CHKERRQ(ierr); 718 ierr = PCMGGetRScale(pc,i+1,&rscale);CHKERRQ(ierr); 719 ierr = MatRestrict(R,mglevels[i+1]->smoothd->dm->x,mglevels[i]->smoothd->dm->x);CHKERRQ(ierr); 720 ierr = VecPointwiseMult(mglevels[i]->smoothd->dm->x,mglevels[i]->smoothd->dm->x,rscale);CHKERRQ(ierr); 721 } 722 } 723 if (needRestricts && pc->dm) { 724 for (i=n-2; i>=0; i--) { 725 DM dmfine,dmcoarse; 726 Mat Restrict,Inject; 727 Vec rscale; 728 ierr = KSPGetDM(mglevels[i+1]->smoothd,&dmfine);CHKERRQ(ierr); 729 ierr = KSPGetDM(mglevels[i]->smoothd,&dmcoarse);CHKERRQ(ierr); 730 ierr = PCMGGetRestriction(pc,i+1,&Restrict);CHKERRQ(ierr); 731 ierr = PCMGGetRScale(pc,i+1,&rscale);CHKERRQ(ierr); 732 Inject = NULL; /* Callback should create it if it needs Injection */ 733 ierr = DMRestrict(dmfine,Restrict,rscale,Inject,dmcoarse);CHKERRQ(ierr); 734 } 735 } 736 737 if (!pc->setupcalled) { 738 for (i=0; i<n; i++) { 739 ierr = KSPSetFromOptions(mglevels[i]->smoothd);CHKERRQ(ierr); 740 } 741 for (i=1; i<n; i++) { 742 if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) { 743 ierr = KSPSetFromOptions(mglevels[i]->smoothu);CHKERRQ(ierr); 744 } 745 } 746 /* insure that if either interpolation or restriction is set the other other one is set */ 747 for (i=1; i<n; i++) { 748 ierr = PCMGGetInterpolation(pc,i,NULL);CHKERRQ(ierr); 749 ierr = PCMGGetRestriction(pc,i,NULL);CHKERRQ(ierr); 750 } 751 for (i=0; i<n-1; i++) { 752 if (!mglevels[i]->b) { 753 Vec *vec; 754 ierr = KSPCreateVecs(mglevels[i]->smoothd,1,&vec,0,NULL);CHKERRQ(ierr); 755 ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr); 756 ierr = VecDestroy(vec);CHKERRQ(ierr); 757 ierr = PetscFree(vec);CHKERRQ(ierr); 758 } 759 if (!mglevels[i]->r && i) { 760 ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr); 761 ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr); 762 ierr = VecDestroy(&tvec);CHKERRQ(ierr); 763 } 764 if (!mglevels[i]->x) { 765 ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr); 766 ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr); 767 ierr = VecDestroy(&tvec);CHKERRQ(ierr); 768 } 769 } 770 if (n != 1 && !mglevels[n-1]->r) { 771 /* PCMGSetR() on the finest level if user did not supply it */ 772 Vec *vec; 773 ierr = KSPCreateVecs(mglevels[n-1]->smoothd,1,&vec,0,NULL);CHKERRQ(ierr); 774 ierr = PCMGSetR(pc,n-1,*vec);CHKERRQ(ierr); 775 ierr = VecDestroy(vec);CHKERRQ(ierr); 776 ierr = PetscFree(vec);CHKERRQ(ierr); 777 } 778 } 779 780 if (pc->dm) { 781 /* need to tell all the coarser levels to rebuild the matrix using the DM for that level */ 782 for (i=0; i<n-1; i++) { 783 if (mglevels[i]->smoothd->setupstage != KSP_SETUP_NEW) mglevels[i]->smoothd->setupstage = KSP_SETUP_NEWMATRIX; 784 } 785 } 786 787 for (i=1; i<n; i++) { 788 if (mglevels[i]->smoothu == mglevels[i]->smoothd || mg->am == PC_MG_FULL || mg->am == PC_MG_KASKADE || mg->cyclesperpcapply > 1){ 789 /* if doing only down then initial guess is zero */ 790 ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr); 791 } 792 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 793 ierr = KSPSetUp(mglevels[i]->smoothd);CHKERRQ(ierr); 794 if (mglevels[i]->smoothd->reason == KSP_DIVERGED_PCSETUP_FAILED) { 795 pc->failedreason = PC_SUBPC_ERROR; 796 } 797 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 798 if (!mglevels[i]->residual) { 799 Mat mat; 800 ierr = KSPGetOperators(mglevels[i]->smoothd,&mat,NULL);CHKERRQ(ierr); 801 ierr = PCMGSetResidual(pc,i,PCMGResidualDefault,mat);CHKERRQ(ierr); 802 } 803 } 804 for (i=1; i<n; i++) { 805 if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) { 806 Mat downmat,downpmat; 807 808 /* check if operators have been set for up, if not use down operators to set them */ 809 ierr = KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,NULL);CHKERRQ(ierr); 810 if (!opsset) { 811 ierr = KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat);CHKERRQ(ierr); 812 ierr = KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat);CHKERRQ(ierr); 813 } 814 815 ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr); 816 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 817 ierr = KSPSetUp(mglevels[i]->smoothu);CHKERRQ(ierr); 818 if (mglevels[i]->smoothu->reason == KSP_DIVERGED_PCSETUP_FAILED) { 819 pc->failedreason = PC_SUBPC_ERROR; 820 } 821 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 822 } 823 } 824 825 if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 826 ierr = KSPSetUp(mglevels[0]->smoothd);CHKERRQ(ierr); 827 if (mglevels[0]->smoothd->reason == KSP_DIVERGED_PCSETUP_FAILED) { 828 pc->failedreason = PC_SUBPC_ERROR; 829 } 830 if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 831 832 /* 833 Dump the interpolation/restriction matrices plus the 834 Jacobian/stiffness on each level. This allows MATLAB users to 835 easily check if the Galerkin condition A_c = R A_f R^T is satisfied. 836 837 Only support one or the other at the same time. 838 */ 839 #if defined(PETSC_USE_SOCKET_VIEWER) 840 ierr = PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,NULL);CHKERRQ(ierr); 841 if (dump) viewer = PETSC_VIEWER_SOCKET_(PetscObjectComm((PetscObject)pc)); 842 dump = PETSC_FALSE; 843 #endif 844 ierr = PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,NULL);CHKERRQ(ierr); 845 if (dump) viewer = PETSC_VIEWER_BINARY_(PetscObjectComm((PetscObject)pc)); 846 847 if (viewer) { 848 for (i=1; i<n; i++) { 849 ierr = MatView(mglevels[i]->restrct,viewer);CHKERRQ(ierr); 850 } 851 for (i=0; i<n; i++) { 852 ierr = KSPGetPC(mglevels[i]->smoothd,&pc);CHKERRQ(ierr); 853 ierr = MatView(pc->mat,viewer);CHKERRQ(ierr); 854 } 855 } 856 PetscFunctionReturn(0); 857 } 858 859 /* -------------------------------------------------------------------------------------*/ 860 861 /*@ 862 PCMGGetLevels - Gets the number of levels to use with MG. 863 864 Not Collective 865 866 Input Parameter: 867 . pc - the preconditioner context 868 869 Output parameter: 870 . levels - the number of levels 871 872 Level: advanced 873 874 .keywords: MG, get, levels, multigrid 875 876 .seealso: PCMGSetLevels() 877 @*/ 878 PetscErrorCode PCMGGetLevels(PC pc,PetscInt *levels) 879 { 880 PC_MG *mg = (PC_MG*)pc->data; 881 882 PetscFunctionBegin; 883 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 884 PetscValidIntPointer(levels,2); 885 *levels = mg->nlevels; 886 PetscFunctionReturn(0); 887 } 888 889 /*@ 890 PCMGSetType - Determines the form of multigrid to use: 891 multiplicative, additive, full, or the Kaskade algorithm. 892 893 Logically Collective on PC 894 895 Input Parameters: 896 + pc - the preconditioner context 897 - form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE, 898 PC_MG_FULL, PC_MG_KASKADE 899 900 Options Database Key: 901 . -pc_mg_type <form> - Sets <form>, one of multiplicative, 902 additive, full, kaskade 903 904 Level: advanced 905 906 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid 907 908 .seealso: PCMGSetLevels() 909 @*/ 910 PetscErrorCode PCMGSetType(PC pc,PCMGType form) 911 { 912 PC_MG *mg = (PC_MG*)pc->data; 913 914 PetscFunctionBegin; 915 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 916 PetscValidLogicalCollectiveEnum(pc,form,2); 917 mg->am = form; 918 if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG; 919 else pc->ops->applyrichardson = NULL; 920 PetscFunctionReturn(0); 921 } 922 923 /*@ 924 PCMGGetType - Determines the form of multigrid to use: 925 multiplicative, additive, full, or the Kaskade algorithm. 926 927 Logically Collective on PC 928 929 Input Parameter: 930 . pc - the preconditioner context 931 932 Output Parameter: 933 . type - one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,PC_MG_FULL, PC_MG_KASKADE 934 935 936 Level: advanced 937 938 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid 939 940 .seealso: PCMGSetLevels() 941 @*/ 942 PetscErrorCode PCMGGetType(PC pc,PCMGType *type) 943 { 944 PC_MG *mg = (PC_MG*)pc->data; 945 946 PetscFunctionBegin; 947 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 948 *type = mg->am; 949 PetscFunctionReturn(0); 950 } 951 952 /*@ 953 PCMGSetCycleType - Sets the type cycles to use. Use PCMGSetCycleTypeOnLevel() for more 954 complicated cycling. 955 956 Logically Collective on PC 957 958 Input Parameters: 959 + pc - the multigrid context 960 - n - either PC_MG_CYCLE_V or PC_MG_CYCLE_W 961 962 Options Database Key: 963 . -pc_mg_cycle_type <v,w> - provide the cycle desired 964 965 Level: advanced 966 967 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid 968 969 .seealso: PCMGSetCycleTypeOnLevel() 970 @*/ 971 PetscErrorCode PCMGSetCycleType(PC pc,PCMGCycleType n) 972 { 973 PC_MG *mg = (PC_MG*)pc->data; 974 PC_MG_Levels **mglevels = mg->levels; 975 PetscInt i,levels; 976 977 PetscFunctionBegin; 978 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 979 if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 980 PetscValidLogicalCollectiveEnum(pc,n,2); 981 levels = mglevels[0]->levels; 982 983 for (i=0; i<levels; i++) mglevels[i]->cycles = n; 984 PetscFunctionReturn(0); 985 } 986 987 /*@ 988 PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step 989 of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used 990 991 Logically Collective on PC 992 993 Input Parameters: 994 + pc - the multigrid context 995 - n - number of cycles (default is 1) 996 997 Options Database Key: 998 . -pc_mg_multiplicative_cycles n 999 1000 Level: advanced 1001 1002 Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType() 1003 1004 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid 1005 1006 .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType() 1007 @*/ 1008 PetscErrorCode PCMGMultiplicativeSetCycles(PC pc,PetscInt n) 1009 { 1010 PC_MG *mg = (PC_MG*)pc->data; 1011 1012 PetscFunctionBegin; 1013 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1014 PetscValidLogicalCollectiveInt(pc,n,2); 1015 mg->cyclesperpcapply = n; 1016 PetscFunctionReturn(0); 1017 } 1018 1019 PetscErrorCode PCMGSetGalerkin_MG(PC pc,PCMGGalerkinType use) 1020 { 1021 PC_MG *mg = (PC_MG*)pc->data; 1022 1023 PetscFunctionBegin; 1024 mg->galerkin = use; 1025 PetscFunctionReturn(0); 1026 } 1027 1028 /*@ 1029 PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the 1030 finest grid via the Galerkin process: A_i-1 = r_i * A_i * p_i 1031 1032 Logically Collective on PC 1033 1034 Input Parameters: 1035 + pc - the multigrid context 1036 - use - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, or PC_MG_GALERKIN_NONE 1037 1038 Options Database Key: 1039 . -pc_mg_galerkin <both,pmat,mat,none> 1040 1041 Level: intermediate 1042 1043 Notes: Some codes that use PCMG such as PCGAMG use Galerkin internally while constructing the hierarchy and thus do not 1044 use the PCMG construction of the coarser grids. 1045 1046 .keywords: MG, set, Galerkin 1047 1048 .seealso: PCMGGetGalerkin(), PCMGGalerkinType 1049 1050 @*/ 1051 PetscErrorCode PCMGSetGalerkin(PC pc,PCMGGalerkinType use) 1052 { 1053 PetscErrorCode ierr; 1054 1055 PetscFunctionBegin; 1056 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1057 ierr = PetscTryMethod(pc,"PCMGSetGalerkin_C",(PC,PCMGGalerkinType),(pc,use));CHKERRQ(ierr); 1058 PetscFunctionReturn(0); 1059 } 1060 1061 /*@ 1062 PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e. 1063 A_i-1 = r_i * A_i * p_i 1064 1065 Not Collective 1066 1067 Input Parameter: 1068 . pc - the multigrid context 1069 1070 Output Parameter: 1071 . galerkin - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, PC_MG_GALERKIN_NONE, or PC_MG_GALERKIN_EXTERNAL 1072 1073 Level: intermediate 1074 1075 .keywords: MG, set, Galerkin 1076 1077 .seealso: PCMGSetGalerkin(), PCMGGalerkinType 1078 1079 @*/ 1080 PetscErrorCode PCMGGetGalerkin(PC pc,PCMGGalerkinType *galerkin) 1081 { 1082 PC_MG *mg = (PC_MG*)pc->data; 1083 1084 PetscFunctionBegin; 1085 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1086 *galerkin = mg->galerkin; 1087 PetscFunctionReturn(0); 1088 } 1089 1090 /*@ 1091 PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to 1092 use on all levels. Use PCMGGetSmootherDown() to set different 1093 pre-smoothing steps on different levels. 1094 1095 Logically Collective on PC 1096 1097 Input Parameters: 1098 + mg - the multigrid context 1099 - n - the number of smoothing steps 1100 1101 Options Database Key: 1102 . -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps 1103 1104 Level: advanced 1105 If the number of smoothing steps is changed in this call then the PCMGGetSmoothUp() will be called and now the 1106 up smoother will no longer share the same KSP object as the down smoother. Use PCMGSetNumberSmooth() to set the same 1107 number of smoothing steps for pre and post smoothing. 1108 1109 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid 1110 1111 .seealso: PCMGSetNumberSmoothUp(), PCMGSetNumberSmooth() 1112 @*/ 1113 PetscErrorCode PCMGSetNumberSmoothDown(PC pc,PetscInt n) 1114 { 1115 PC_MG *mg = (PC_MG*)pc->data; 1116 PC_MG_Levels **mglevels = mg->levels; 1117 PetscErrorCode ierr; 1118 PetscInt i,levels; 1119 1120 PetscFunctionBegin; 1121 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1122 if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 1123 PetscValidLogicalCollectiveInt(pc,n,2); 1124 levels = mglevels[0]->levels; 1125 1126 for (i=1; i<levels; i++) { 1127 PetscInt nc; 1128 ierr = KSPGetTolerances(mglevels[i]->smoothd,NULL,NULL,NULL,&nc);CHKERRQ(ierr); 1129 if (nc == n) continue; 1130 1131 /* make sure smoother up and down are different */ 1132 ierr = PCMGGetSmootherUp(pc,i,NULL);CHKERRQ(ierr); 1133 ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 1134 1135 mg->default_smoothd = n; 1136 } 1137 PetscFunctionReturn(0); 1138 } 1139 1140 /*@ 1141 PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use 1142 on all levels. Use PCMGGetSmootherUp() to set different numbers of 1143 post-smoothing steps on different levels. 1144 1145 Logically Collective on PC 1146 1147 Input Parameters: 1148 + mg - the multigrid context 1149 - n - the number of smoothing steps 1150 1151 Options Database Key: 1152 . -pc_mg_smoothup <n> - Sets number of post-smoothing steps 1153 1154 Level: advanced 1155 1156 Notes: this does not set a value on the coarsest grid, since we assume that 1157 there is no separate smooth up on the coarsest grid. 1158 1159 If the number of smoothing steps is changed in this call then the PCMGGetSmoothUp() will be called and now the 1160 up smoother will no longer share the same KSP object as the down smoother. Use PCMGSetNumberSmooth() to set the same 1161 number of smoothing steps for pre and post smoothing. 1162 1163 1164 .keywords: MG, smooth, up, post-smoothing, steps, multigrid 1165 1166 .seealso: PCMGSetNumberSmoothDown(), PCMGSetNumberSmooth() 1167 @*/ 1168 PetscErrorCode PCMGSetNumberSmoothUp(PC pc,PetscInt n) 1169 { 1170 PC_MG *mg = (PC_MG*)pc->data; 1171 PC_MG_Levels **mglevels = mg->levels; 1172 PetscErrorCode ierr; 1173 PetscInt i,levels; 1174 1175 PetscFunctionBegin; 1176 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1177 if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 1178 PetscValidLogicalCollectiveInt(pc,n,2); 1179 levels = mglevels[0]->levels; 1180 1181 for (i=1; i<levels; i++) { 1182 if (mglevels[i]->smoothu == mglevels[i]->smoothd) { 1183 PetscInt nc; 1184 ierr = KSPGetTolerances(mglevels[i]->smoothd,NULL,NULL,NULL,&nc);CHKERRQ(ierr); 1185 if (nc == n) continue; 1186 } 1187 1188 /* make sure smoother up and down are different */ 1189 ierr = PCMGGetSmootherUp(pc,i,NULL);CHKERRQ(ierr); 1190 ierr = KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 1191 1192 mg->default_smoothu = n; 1193 } 1194 PetscFunctionReturn(0); 1195 } 1196 1197 /*@ 1198 PCMGSetNumberSmooth - Sets the number of pre and post-smoothing steps to use 1199 on all levels. Use PCMGSetSmoothUp() and PCMGSetSmoothDown() set different numbers of 1200 pre ad post-smoothing steps 1201 1202 Logically Collective on PC 1203 1204 Input Parameters: 1205 + mg - the multigrid context 1206 - n - the number of smoothing steps 1207 1208 Options Database Key: 1209 + -mg_levels_ksp_max_it <n> - Sets number of pre and post-smoothing steps 1210 . -pc_mg_smooth_down <n> - Sets number of pre-smoothing steps (if setting different pre and post amounts) 1211 - -pc_mg_smooth_up <n> - Sets number of post-smoothing steps (if setting different pre and post amounts) 1212 1213 Level: advanced 1214 1215 Notes: this does not set a value on the coarsest grid, since we assume that 1216 there is no separate smooth up on the coarsest grid. 1217 1218 .keywords: MG, smooth, up, post-smoothing, steps, multigrid 1219 1220 .seealso: PCMGSetNumberSmoothDown(), PCMGSetNumberSmoothUp() 1221 @*/ 1222 PetscErrorCode PCMGSetNumberSmooth(PC pc,PetscInt n) 1223 { 1224 PC_MG *mg = (PC_MG*)pc->data; 1225 PC_MG_Levels **mglevels = mg->levels; 1226 PetscErrorCode ierr; 1227 PetscInt i,levels; 1228 1229 PetscFunctionBegin; 1230 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1231 if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 1232 PetscValidLogicalCollectiveInt(pc,n,2); 1233 levels = mglevels[0]->levels; 1234 1235 for (i=1; i<levels; i++) { 1236 ierr = KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 1237 ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 1238 mg->default_smoothu = n; 1239 mg->default_smoothd = n; 1240 } 1241 PetscFunctionReturn(0); 1242 } 1243 1244 /* ----------------------------------------------------------------------------------------*/ 1245 1246 /*MC 1247 PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional 1248 information about the coarser grid matrices and restriction/interpolation operators. 1249 1250 Options Database Keys: 1251 + -pc_mg_levels <nlevels> - number of levels including finest 1252 . -pc_mg_cycle_type <v,w> - 1253 . -pc_mg_smoothup <n> - number of smoothing steps after interpolation 1254 . -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator 1255 . -pc_mg_type <additive,multiplicative,full,kaskade> - multiplicative is the default 1256 . -pc_mg_log - log information about time spent on each level of the solver 1257 . -pc_mg_galerkin <both,pmat,mat,none> - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R' 1258 . -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1) 1259 . -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices 1260 to the Socket viewer for reading from MATLAB. 1261 - -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices 1262 to the binary output file called binaryoutput 1263 1264 Notes: If one uses a Krylov method such GMRES or CG as the smoother than one must use KSPFGMRES, KSPGCG, or KSPRICHARDSON as the outer Krylov method 1265 1266 When run with a single level the smoother options are used on that level NOT the coarse grid solver options 1267 1268 When run with KSPRICHARDSON the convergence test changes slightly if monitor is turned on. The iteration count may change slightly. This 1269 is because without monitoring the residual norm is computed WITHIN each multigrid cycle on the finest level after the pre-smoothing 1270 (because the residual has just been computed for the multigrid algorithm and is hence available for free) while with monitoring the 1271 residual is computed at the end of each cycle. 1272 1273 Level: intermediate 1274 1275 Concepts: multigrid/multilevel 1276 1277 .seealso: PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE 1278 PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(), 1279 PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(), 1280 PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(), 1281 PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR() 1282 M*/ 1283 1284 PETSC_EXTERN PetscErrorCode PCCreate_MG(PC pc) 1285 { 1286 PC_MG *mg; 1287 PetscErrorCode ierr; 1288 1289 PetscFunctionBegin; 1290 ierr = PetscNewLog(pc,&mg);CHKERRQ(ierr); 1291 pc->data = (void*)mg; 1292 mg->nlevels = -1; 1293 mg->am = PC_MG_MULTIPLICATIVE; 1294 mg->galerkin = PC_MG_GALERKIN_NONE; 1295 1296 pc->useAmat = PETSC_TRUE; 1297 1298 pc->ops->apply = PCApply_MG; 1299 pc->ops->setup = PCSetUp_MG; 1300 pc->ops->reset = PCReset_MG; 1301 pc->ops->destroy = PCDestroy_MG; 1302 pc->ops->setfromoptions = PCSetFromOptions_MG; 1303 pc->ops->view = PCView_MG; 1304 1305 ierr = PetscObjectComposeFunction((PetscObject)pc,"PCMGSetGalerkin_C",PCMGSetGalerkin_MG);CHKERRQ(ierr); 1306 PetscFunctionReturn(0); 1307 } 1308