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 #undef __FUNCT__ 9 #define __FUNCT__ "PCMGMCycle_Private" 10 PetscErrorCode PCMGMCycle_Private(PC pc,PC_MG_Levels **mglevelsin,PCRichardsonConvergedReason *reason) 11 { 12 PC_MG *mg = (PC_MG*)pc->data; 13 PC_MG_Levels *mgc,*mglevels = *mglevelsin; 14 PetscErrorCode ierr; 15 PetscInt cycles = (mglevels->level == 1) ? 1 : (PetscInt) mglevels->cycles; 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 if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 21 if (mglevels->level) { /* not the coarsest grid */ 22 if (mglevels->eventresidual) {ierr = PetscLogEventBegin(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);} 23 ierr = (*mglevels->residual)(mglevels->A,mglevels->b,mglevels->x,mglevels->r);CHKERRQ(ierr); 24 if (mglevels->eventresidual) {ierr = PetscLogEventEnd(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);} 25 26 /* if on finest level and have convergence criteria set */ 27 if (mglevels->level == mglevels->levels-1 && mg->ttol && reason) { 28 PetscReal rnorm; 29 ierr = VecNorm(mglevels->r,NORM_2,&rnorm);CHKERRQ(ierr); 30 if (rnorm <= mg->ttol) { 31 if (rnorm < mg->abstol) { 32 *reason = PCRICHARDSON_CONVERGED_ATOL; 33 ierr = PetscInfo2(pc,"Linear solver has converged. Residual norm %g is less than absolute tolerance %g\n",(double)rnorm,(double)mg->abstol);CHKERRQ(ierr); 34 } else { 35 *reason = PCRICHARDSON_CONVERGED_RTOL; 36 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); 37 } 38 PetscFunctionReturn(0); 39 } 40 } 41 42 mgc = *(mglevelsin - 1); 43 if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 44 ierr = MatRestrict(mglevels->restrct,mglevels->r,mgc->b);CHKERRQ(ierr); 45 if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 46 ierr = VecSet(mgc->x,0.0);CHKERRQ(ierr); 47 while (cycles--) { 48 ierr = PCMGMCycle_Private(pc,mglevelsin-1,reason);CHKERRQ(ierr); 49 } 50 if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 51 ierr = MatInterpolateAdd(mglevels->interpolate,mgc->x,mglevels->x,mglevels->x);CHKERRQ(ierr); 52 if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 53 if (mglevels->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 54 ierr = KSPSolve(mglevels->smoothu,mglevels->b,mglevels->x);CHKERRQ(ierr); /* post smooth */ 55 if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 56 } 57 PetscFunctionReturn(0); 58 } 59 60 #undef __FUNCT__ 61 #define __FUNCT__ "PCApplyRichardson_MG" 62 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) 63 { 64 PC_MG *mg = (PC_MG*)pc->data; 65 PC_MG_Levels **mglevels = mg->levels; 66 PetscErrorCode ierr; 67 PetscInt levels = mglevels[0]->levels,i; 68 69 PetscFunctionBegin; 70 /* When the DM is supplying the matrix then it will not exist until here */ 71 for (i=0; i<levels; i++) { 72 if (!mglevels[i]->A) { 73 ierr = KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);CHKERRQ(ierr); 74 ierr = PetscObjectReference((PetscObject)mglevels[i]->A);CHKERRQ(ierr); 75 } 76 } 77 mglevels[levels-1]->b = b; 78 mglevels[levels-1]->x = x; 79 80 mg->rtol = rtol; 81 mg->abstol = abstol; 82 mg->dtol = dtol; 83 if (rtol) { 84 /* compute initial residual norm for relative convergence test */ 85 PetscReal rnorm; 86 if (zeroguess) { 87 ierr = VecNorm(b,NORM_2,&rnorm);CHKERRQ(ierr); 88 } else { 89 ierr = (*mglevels[levels-1]->residual)(mglevels[levels-1]->A,b,x,w);CHKERRQ(ierr); 90 ierr = VecNorm(w,NORM_2,&rnorm);CHKERRQ(ierr); 91 } 92 mg->ttol = PetscMax(rtol*rnorm,abstol); 93 } else if (abstol) mg->ttol = abstol; 94 else mg->ttol = 0.0; 95 96 /* since smoother is applied to full system, not just residual we need to make sure that smoothers don't 97 stop prematurely due to small residual */ 98 for (i=1; i<levels; i++) { 99 ierr = KSPSetTolerances(mglevels[i]->smoothu,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr); 100 if (mglevels[i]->smoothu != mglevels[i]->smoothd) { 101 ierr = KSPSetTolerances(mglevels[i]->smoothd,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr); 102 } 103 } 104 105 *reason = (PCRichardsonConvergedReason)0; 106 for (i=0; i<its; i++) { 107 ierr = PCMGMCycle_Private(pc,mglevels+levels-1,reason);CHKERRQ(ierr); 108 if (*reason) break; 109 } 110 if (!*reason) *reason = PCRICHARDSON_CONVERGED_ITS; 111 *outits = i; 112 PetscFunctionReturn(0); 113 } 114 115 #undef __FUNCT__ 116 #define __FUNCT__ "PCReset_MG" 117 PetscErrorCode PCReset_MG(PC pc) 118 { 119 PC_MG *mg = (PC_MG*)pc->data; 120 PC_MG_Levels **mglevels = mg->levels; 121 PetscErrorCode ierr; 122 PetscInt i,n; 123 124 PetscFunctionBegin; 125 if (mglevels) { 126 n = mglevels[0]->levels; 127 for (i=0; i<n-1; i++) { 128 ierr = VecDestroy(&mglevels[i+1]->r);CHKERRQ(ierr); 129 ierr = VecDestroy(&mglevels[i]->b);CHKERRQ(ierr); 130 ierr = VecDestroy(&mglevels[i]->x);CHKERRQ(ierr); 131 ierr = MatDestroy(&mglevels[i+1]->restrct);CHKERRQ(ierr); 132 ierr = MatDestroy(&mglevels[i+1]->interpolate);CHKERRQ(ierr); 133 ierr = VecDestroy(&mglevels[i+1]->rscale);CHKERRQ(ierr); 134 } 135 136 for (i=0; i<n; i++) { 137 ierr = MatDestroy(&mglevels[i]->A);CHKERRQ(ierr); 138 if (mglevels[i]->smoothd != mglevels[i]->smoothu) { 139 ierr = KSPReset(mglevels[i]->smoothd);CHKERRQ(ierr); 140 } 141 ierr = KSPReset(mglevels[i]->smoothu);CHKERRQ(ierr); 142 } 143 } 144 PetscFunctionReturn(0); 145 } 146 147 #undef __FUNCT__ 148 #define __FUNCT__ "PCMGSetLevels" 149 /*@C 150 PCMGSetLevels - Sets the number of levels to use with MG. 151 Must be called before any other MG routine. 152 153 Logically Collective on PC 154 155 Input Parameters: 156 + pc - the preconditioner context 157 . levels - the number of levels 158 - comms - optional communicators for each level; this is to allow solving the coarser problems 159 on smaller sets of processors. Use NULL_OBJECT for default in Fortran 160 161 Level: intermediate 162 163 Notes: 164 If the number of levels is one then the multigrid uses the -mg_levels prefix 165 for setting the level options rather than the -mg_coarse prefix. 166 167 .keywords: MG, set, levels, multigrid 168 169 .seealso: PCMGSetType(), PCMGGetLevels() 170 @*/ 171 PetscErrorCode PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms) 172 { 173 PetscErrorCode ierr; 174 PC_MG *mg = (PC_MG*)pc->data; 175 MPI_Comm comm; 176 PC_MG_Levels **mglevels = mg->levels; 177 PetscInt i; 178 PetscMPIInt size; 179 const char *prefix; 180 PC ipc; 181 PetscInt n; 182 183 PetscFunctionBegin; 184 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 185 PetscValidLogicalCollectiveInt(pc,levels,2); 186 ierr = PetscObjectGetComm((PetscObject)pc,&comm);CHKERRQ(ierr); 187 if (mg->nlevels == levels) PetscFunctionReturn(0); 188 if (mglevels) { 189 /* changing the number of levels so free up the previous stuff */ 190 ierr = PCReset_MG(pc);CHKERRQ(ierr); 191 n = mglevels[0]->levels; 192 for (i=0; i<n; i++) { 193 if (mglevels[i]->smoothd != mglevels[i]->smoothu) { 194 ierr = KSPDestroy(&mglevels[i]->smoothd);CHKERRQ(ierr); 195 } 196 ierr = KSPDestroy(&mglevels[i]->smoothu);CHKERRQ(ierr); 197 ierr = PetscFree(mglevels[i]);CHKERRQ(ierr); 198 } 199 ierr = PetscFree(mg->levels);CHKERRQ(ierr); 200 } 201 202 mg->nlevels = levels; 203 204 ierr = PetscMalloc1(levels,&mglevels);CHKERRQ(ierr); 205 ierr = PetscLogObjectMemory((PetscObject)pc,levels*(sizeof(PC_MG*)));CHKERRQ(ierr); 206 207 ierr = PCGetOptionsPrefix(pc,&prefix);CHKERRQ(ierr); 208 209 mg->stageApply = 0; 210 for (i=0; i<levels; i++) { 211 ierr = PetscNewLog(pc,&mglevels[i]);CHKERRQ(ierr); 212 213 mglevels[i]->level = i; 214 mglevels[i]->levels = levels; 215 mglevels[i]->cycles = PC_MG_CYCLE_V; 216 mg->default_smoothu = 2; 217 mg->default_smoothd = 2; 218 mglevels[i]->eventsmoothsetup = 0; 219 mglevels[i]->eventsmoothsolve = 0; 220 mglevels[i]->eventresidual = 0; 221 mglevels[i]->eventinterprestrict = 0; 222 223 if (comms) comm = comms[i]; 224 ierr = KSPCreate(comm,&mglevels[i]->smoothd);CHKERRQ(ierr); 225 ierr = KSPSetErrorIfNotConverged(mglevels[i]->smoothd,pc->erroriffailure);CHKERRQ(ierr); 226 ierr = KSPSetType(mglevels[i]->smoothd,KSPCHEBYSHEV);CHKERRQ(ierr); 227 ierr = KSPSetConvergenceTest(mglevels[i]->smoothd,KSPConvergedSkip,NULL,NULL);CHKERRQ(ierr); 228 ierr = KSPSetNormType(mglevels[i]->smoothd,KSP_NORM_NONE);CHKERRQ(ierr); 229 ierr = KSPGetPC(mglevels[i]->smoothd,&ipc);CHKERRQ(ierr); 230 ierr = PCSetType(ipc,PCSOR);CHKERRQ(ierr); 231 ierr = PetscObjectIncrementTabLevel((PetscObject)mglevels[i]->smoothd,(PetscObject)pc,levels-i);CHKERRQ(ierr); 232 ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, i ? mg->default_smoothd : 1);CHKERRQ(ierr); 233 ierr = KSPSetOptionsPrefix(mglevels[i]->smoothd,prefix);CHKERRQ(ierr); 234 235 /* do special stuff for coarse grid */ 236 if (!i && levels > 1) { 237 ierr = KSPAppendOptionsPrefix(mglevels[0]->smoothd,"mg_coarse_");CHKERRQ(ierr); 238 239 /* coarse solve is (redundant) LU by default; set shifttype NONZERO to avoid annoying zero-pivot in LU preconditioner */ 240 ierr = KSPSetType(mglevels[0]->smoothd,KSPPREONLY);CHKERRQ(ierr); 241 ierr = KSPGetPC(mglevels[0]->smoothd,&ipc);CHKERRQ(ierr); 242 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 243 if (size > 1) { 244 KSP innerksp; 245 PC innerpc; 246 ierr = PCSetType(ipc,PCREDUNDANT);CHKERRQ(ierr); 247 ierr = PCRedundantGetKSP(ipc,&innerksp);CHKERRQ(ierr); 248 ierr = KSPGetPC(innerksp,&innerpc);CHKERRQ(ierr); 249 ierr = PCFactorSetShiftType(innerpc,MAT_SHIFT_INBLOCKS);CHKERRQ(ierr); 250 } else { 251 ierr = PCSetType(ipc,PCLU);CHKERRQ(ierr); 252 ierr = PCFactorSetShiftType(ipc,MAT_SHIFT_INBLOCKS);CHKERRQ(ierr); 253 } 254 } else { 255 char tprefix[128]; 256 sprintf(tprefix,"mg_levels_%d_",(int)i); 257 ierr = KSPAppendOptionsPrefix(mglevels[i]->smoothd,tprefix);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->am = PC_MG_MULTIPLICATIVE; 269 mg->levels = mglevels; 270 pc->ops->applyrichardson = PCApplyRichardson_MG; 271 PetscFunctionReturn(0); 272 } 273 274 275 #undef __FUNCT__ 276 #define __FUNCT__ "PCDestroy_MG" 277 PetscErrorCode PCDestroy_MG(PC pc) 278 { 279 PetscErrorCode ierr; 280 PC_MG *mg = (PC_MG*)pc->data; 281 PC_MG_Levels **mglevels = mg->levels; 282 PetscInt i,n; 283 284 PetscFunctionBegin; 285 ierr = PCReset_MG(pc);CHKERRQ(ierr); 286 if (mglevels) { 287 n = mglevels[0]->levels; 288 for (i=0; i<n; i++) { 289 if (mglevels[i]->smoothd != mglevels[i]->smoothu) { 290 ierr = KSPDestroy(&mglevels[i]->smoothd);CHKERRQ(ierr); 291 } 292 ierr = KSPDestroy(&mglevels[i]->smoothu);CHKERRQ(ierr); 293 ierr = PetscFree(mglevels[i]);CHKERRQ(ierr); 294 } 295 ierr = PetscFree(mg->levels);CHKERRQ(ierr); 296 } 297 ierr = PetscFree(pc->data);CHKERRQ(ierr); 298 PetscFunctionReturn(0); 299 } 300 301 302 303 extern PetscErrorCode PCMGACycle_Private(PC,PC_MG_Levels**); 304 extern PetscErrorCode PCMGFCycle_Private(PC,PC_MG_Levels**); 305 extern PetscErrorCode PCMGKCycle_Private(PC,PC_MG_Levels**); 306 307 /* 308 PCApply_MG - Runs either an additive, multiplicative, Kaskadic 309 or full cycle of multigrid. 310 311 Note: 312 A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle(). 313 */ 314 #undef __FUNCT__ 315 #define __FUNCT__ "PCApply_MG" 316 static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x) 317 { 318 PC_MG *mg = (PC_MG*)pc->data; 319 PC_MG_Levels **mglevels = mg->levels; 320 PetscErrorCode ierr; 321 PetscInt levels = mglevels[0]->levels,i; 322 323 PetscFunctionBegin; 324 if (mg->stageApply) {ierr = PetscLogStagePush(mg->stageApply);CHKERRQ(ierr);} 325 /* When the DM is supplying the matrix then it will not exist until here */ 326 for (i=0; i<levels; i++) { 327 if (!mglevels[i]->A) { 328 ierr = KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);CHKERRQ(ierr); 329 ierr = PetscObjectReference((PetscObject)mglevels[i]->A);CHKERRQ(ierr); 330 } 331 } 332 333 mglevels[levels-1]->b = b; 334 mglevels[levels-1]->x = x; 335 if (mg->am == PC_MG_MULTIPLICATIVE) { 336 ierr = VecSet(x,0.0);CHKERRQ(ierr); 337 for (i=0; i<mg->cyclesperpcapply; i++) { 338 ierr = PCMGMCycle_Private(pc,mglevels+levels-1,NULL);CHKERRQ(ierr); 339 } 340 } else if (mg->am == PC_MG_ADDITIVE) { 341 ierr = PCMGACycle_Private(pc,mglevels);CHKERRQ(ierr); 342 } else if (mg->am == PC_MG_KASKADE) { 343 ierr = PCMGKCycle_Private(pc,mglevels);CHKERRQ(ierr); 344 } else { 345 ierr = PCMGFCycle_Private(pc,mglevels);CHKERRQ(ierr); 346 } 347 if (mg->stageApply) {ierr = PetscLogStagePop();CHKERRQ(ierr);} 348 PetscFunctionReturn(0); 349 } 350 351 352 #undef __FUNCT__ 353 #define __FUNCT__ "PCSetFromOptions_MG" 354 PetscErrorCode PCSetFromOptions_MG(PetscOptions *PetscOptionsObject,PC pc) 355 { 356 PetscErrorCode ierr; 357 PetscInt m,levels = 1,cycles; 358 PetscBool flg,set; 359 PC_MG *mg = (PC_MG*)pc->data; 360 PC_MG_Levels **mglevels = mg->levels; 361 PCMGType mgtype; 362 PCMGCycleType mgctype; 363 364 PetscFunctionBegin; 365 ierr = PetscOptionsHead(PetscOptionsObject,"Multigrid options");CHKERRQ(ierr); 366 if (!mg->levels) { 367 ierr = PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);CHKERRQ(ierr); 368 if (!flg && pc->dm) { 369 ierr = DMGetRefineLevel(pc->dm,&levels);CHKERRQ(ierr); 370 levels++; 371 mg->usedmfornumberoflevels = PETSC_TRUE; 372 } 373 ierr = PCMGSetLevels(pc,levels,NULL);CHKERRQ(ierr); 374 } 375 mglevels = mg->levels; 376 377 mgctype = (PCMGCycleType) mglevels[0]->cycles; 378 ierr = PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);CHKERRQ(ierr); 379 if (flg) { 380 ierr = PCMGSetCycleType(pc,mgctype);CHKERRQ(ierr); 381 } 382 flg = PETSC_FALSE; 383 ierr = PetscOptionsBool("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",flg,&flg,&set);CHKERRQ(ierr); 384 if (set) { 385 ierr = PCMGSetGalerkin(pc,flg);CHKERRQ(ierr); 386 } 387 ierr = PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",mg->default_smoothu,&m,&flg);CHKERRQ(ierr); 388 if (flg) { 389 ierr = PCMGSetNumberSmoothUp(pc,m);CHKERRQ(ierr); 390 } 391 ierr = PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",mg->default_smoothd,&m,&flg);CHKERRQ(ierr); 392 if (flg) { 393 ierr = PCMGSetNumberSmoothDown(pc,m);CHKERRQ(ierr); 394 } 395 mgtype = mg->am; 396 ierr = PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);CHKERRQ(ierr); 397 if (flg) { 398 ierr = PCMGSetType(pc,mgtype);CHKERRQ(ierr); 399 } 400 if (mg->am == PC_MG_MULTIPLICATIVE) { 401 ierr = PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGSetLevels",mg->cyclesperpcapply,&cycles,&flg);CHKERRQ(ierr); 402 if (flg) { 403 ierr = PCMGMultiplicativeSetCycles(pc,cycles);CHKERRQ(ierr); 404 } 405 } 406 flg = PETSC_FALSE; 407 ierr = PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,NULL);CHKERRQ(ierr); 408 if (flg) { 409 PetscInt i; 410 char eventname[128]; 411 if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 412 levels = mglevels[0]->levels; 413 for (i=0; i<levels; i++) { 414 sprintf(eventname,"MGSetup Level %d",(int)i); 415 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);CHKERRQ(ierr); 416 sprintf(eventname,"MGSmooth Level %d",(int)i); 417 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);CHKERRQ(ierr); 418 if (i) { 419 sprintf(eventname,"MGResid Level %d",(int)i); 420 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);CHKERRQ(ierr); 421 sprintf(eventname,"MGInterp Level %d",(int)i); 422 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);CHKERRQ(ierr); 423 } 424 } 425 426 #if defined(PETSC_USE_LOG) 427 { 428 const char *sname = "MG Apply"; 429 PetscStageLog stageLog; 430 PetscInt st; 431 432 PetscFunctionBegin; 433 ierr = PetscLogGetStageLog(&stageLog);CHKERRQ(ierr); 434 for (st = 0; st < stageLog->numStages; ++st) { 435 PetscBool same; 436 437 ierr = PetscStrcmp(stageLog->stageInfo[st].name, sname, &same);CHKERRQ(ierr); 438 if (same) mg->stageApply = st; 439 } 440 if (!mg->stageApply) { 441 ierr = PetscLogStageRegister(sname, &mg->stageApply);CHKERRQ(ierr); 442 } 443 } 444 #endif 445 } 446 ierr = PetscOptionsTail();CHKERRQ(ierr); 447 PetscFunctionReturn(0); 448 } 449 450 const char *const PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0}; 451 const char *const PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",0}; 452 453 #include <petscdraw.h> 454 #undef __FUNCT__ 455 #define __FUNCT__ "PCView_MG" 456 PetscErrorCode PCView_MG(PC pc,PetscViewer viewer) 457 { 458 PC_MG *mg = (PC_MG*)pc->data; 459 PC_MG_Levels **mglevels = mg->levels; 460 PetscErrorCode ierr; 461 PetscInt levels = mglevels ? mglevels[0]->levels : 0,i; 462 PetscBool iascii,isbinary,isdraw; 463 464 PetscFunctionBegin; 465 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 466 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 467 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 468 if (iascii) { 469 const char *cyclename = levels ? (mglevels[0]->cycles == PC_MG_CYCLE_V ? "v" : "w") : "unknown"; 470 ierr = PetscViewerASCIIPrintf(viewer," MG: type is %s, levels=%D cycles=%s\n", PCMGTypes[mg->am],levels,cyclename);CHKERRQ(ierr); 471 if (mg->am == PC_MG_MULTIPLICATIVE) { 472 ierr = PetscViewerASCIIPrintf(viewer," Cycles per PCApply=%d\n",mg->cyclesperpcapply);CHKERRQ(ierr); 473 } 474 if (mg->galerkin) { 475 ierr = PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr); 476 } else { 477 ierr = PetscViewerASCIIPrintf(viewer," Not using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr); 478 } 479 if (mg->view){ 480 ierr = (*mg->view)(pc,viewer);CHKERRQ(ierr); 481 } 482 for (i=0; i<levels; i++) { 483 if (!i) { 484 ierr = PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level -------------------------------\n",i);CHKERRQ(ierr); 485 } else { 486 ierr = PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr); 487 } 488 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 489 ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr); 490 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 491 if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) { 492 ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");CHKERRQ(ierr); 493 } else if (i) { 494 ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr); 495 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 496 ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr); 497 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 498 } 499 } 500 } else if (isbinary) { 501 for (i=levels-1; i>=0; i--) { 502 ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr); 503 if (i && mglevels[i]->smoothd != mglevels[i]->smoothu) { 504 ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr); 505 } 506 } 507 } else if (isdraw) { 508 PetscDraw draw; 509 PetscReal x,w,y,bottom,th; 510 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 511 ierr = PetscDrawGetCurrentPoint(draw,&x,&y);CHKERRQ(ierr); 512 ierr = PetscDrawStringGetSize(draw,NULL,&th);CHKERRQ(ierr); 513 bottom = y - th; 514 for (i=levels-1; i>=0; i--) { 515 if (!mglevels[i]->smoothu || (mglevels[i]->smoothu == mglevels[i]->smoothd)) { 516 ierr = PetscDrawPushCurrentPoint(draw,x,bottom);CHKERRQ(ierr); 517 ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr); 518 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 519 } else { 520 w = 0.5*PetscMin(1.0-x,x); 521 ierr = PetscDrawPushCurrentPoint(draw,x+w,bottom);CHKERRQ(ierr); 522 ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr); 523 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 524 ierr = PetscDrawPushCurrentPoint(draw,x-w,bottom);CHKERRQ(ierr); 525 ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr); 526 ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr); 527 } 528 ierr = PetscDrawGetBoundingBox(draw,NULL,&bottom,NULL,NULL);CHKERRQ(ierr); 529 bottom -= th; 530 } 531 } 532 PetscFunctionReturn(0); 533 } 534 535 #include <petsc/private/dmimpl.h> 536 #include <petsc/private/kspimpl.h> 537 538 /* 539 Calls setup for the KSP on each level 540 */ 541 #undef __FUNCT__ 542 #define __FUNCT__ "PCSetUp_MG" 543 PetscErrorCode PCSetUp_MG(PC pc) 544 { 545 PC_MG *mg = (PC_MG*)pc->data; 546 PC_MG_Levels **mglevels = mg->levels; 547 PetscErrorCode ierr; 548 PetscInt i,n = mglevels[0]->levels; 549 PC cpc; 550 PetscBool preonly,lu,redundant,cholesky,svd,dump = PETSC_FALSE,opsset,use_amat,missinginterpolate = PETSC_FALSE,bjaclu; 551 Mat dA,dB; 552 Vec tvec; 553 DM *dms; 554 PetscViewer viewer = 0; 555 556 PetscFunctionBegin; 557 /* FIX: Move this to PCSetFromOptions_MG? */ 558 if (mg->usedmfornumberoflevels) { 559 PetscInt levels; 560 ierr = DMGetRefineLevel(pc->dm,&levels);CHKERRQ(ierr); 561 levels++; 562 if (levels > n) { /* the problem is now being solved on a finer grid */ 563 ierr = PCMGSetLevels(pc,levels,NULL);CHKERRQ(ierr); 564 n = levels; 565 ierr = PCSetFromOptions(pc);CHKERRQ(ierr); /* it is bad to call this here, but otherwise will never be called for the new hierarchy */ 566 mglevels = mg->levels; 567 } 568 } 569 ierr = KSPGetPC(mglevels[0]->smoothd,&cpc);CHKERRQ(ierr); 570 571 572 /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */ 573 /* so use those from global PC */ 574 /* Is this what we always want? What if user wants to keep old one? */ 575 ierr = KSPGetOperatorsSet(mglevels[n-1]->smoothd,NULL,&opsset);CHKERRQ(ierr); 576 if (opsset) { 577 Mat mmat; 578 ierr = KSPGetOperators(mglevels[n-1]->smoothd,NULL,&mmat);CHKERRQ(ierr); 579 if (mmat == pc->pmat) opsset = PETSC_FALSE; 580 } 581 582 if (!opsset) { 583 ierr = PCGetUseAmat(pc,&use_amat);CHKERRQ(ierr); 584 if(use_amat){ 585 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); 586 ierr = KSPSetOperators(mglevels[n-1]->smoothd,pc->mat,pc->pmat);CHKERRQ(ierr); 587 } 588 else { 589 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); 590 ierr = KSPSetOperators(mglevels[n-1]->smoothd,pc->pmat,pc->pmat);CHKERRQ(ierr); 591 } 592 } 593 594 for (i=n-1; i>0; i--) { 595 if (!(mglevels[i]->interpolate || mglevels[i]->restrct)) { 596 missinginterpolate = PETSC_TRUE; 597 continue; 598 } 599 } 600 /* 601 Skipping if user has provided all interpolation/restriction needed (since DM might not be able to produce them (when coming from SNES/TS) 602 Skipping for galerkin==2 (externally managed hierarchy such as ML and GAMG). Cleaner logic here would be great. Wrap ML/GAMG as DMs? 603 */ 604 if (missinginterpolate && pc->dm && mg->galerkin != 2 && !pc->setupcalled) { 605 /* construct the interpolation from the DMs */ 606 Mat p; 607 Vec rscale; 608 ierr = PetscMalloc1(n,&dms);CHKERRQ(ierr); 609 dms[n-1] = pc->dm; 610 /* Separately create them so we do not get DMKSP interference between levels */ 611 for (i=n-2; i>-1; i--) {ierr = DMCoarsen(dms[i+1],MPI_COMM_NULL,&dms[i]);CHKERRQ(ierr);} 612 for (i=n-2; i>-1; i--) { 613 DMKSP kdm; 614 ierr = KSPSetDM(mglevels[i]->smoothd,dms[i]);CHKERRQ(ierr); 615 if (mg->galerkin) {ierr = KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);CHKERRQ(ierr);} 616 ierr = DMGetDMKSPWrite(dms[i],&kdm);CHKERRQ(ierr); 617 /* Ugly hack so that the next KSPSetUp() will use the RHS that we set. A better fix is to change dmActive to take 618 * a bitwise OR of computing the matrix, RHS, and initial iterate. */ 619 kdm->ops->computerhs = NULL; 620 kdm->rhsctx = NULL; 621 if (!mglevels[i+1]->interpolate) { 622 ierr = DMCreateInterpolation(dms[i],dms[i+1],&p,&rscale);CHKERRQ(ierr); 623 ierr = PCMGSetInterpolation(pc,i+1,p);CHKERRQ(ierr); 624 if (rscale) {ierr = PCMGSetRScale(pc,i+1,rscale);CHKERRQ(ierr);} 625 ierr = VecDestroy(&rscale);CHKERRQ(ierr); 626 ierr = MatDestroy(&p);CHKERRQ(ierr); 627 } 628 } 629 630 for (i=n-2; i>-1; i--) {ierr = DMDestroy(&dms[i]);CHKERRQ(ierr);} 631 ierr = PetscFree(dms);CHKERRQ(ierr); 632 } 633 634 if (pc->dm && !pc->setupcalled) { 635 /* finest smoother also gets DM but it is not active, independent of whether galerkin==2 */ 636 ierr = KSPSetDM(mglevels[n-1]->smoothd,pc->dm);CHKERRQ(ierr); 637 ierr = KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);CHKERRQ(ierr); 638 } 639 640 if (mg->galerkin == 1) { 641 Mat B; 642 /* currently only handle case where mat and pmat are the same on coarser levels */ 643 ierr = KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB);CHKERRQ(ierr); 644 if (!pc->setupcalled) { 645 for (i=n-2; i>-1; i--) { 646 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"); 647 if (!mglevels[i+1]->interpolate) { 648 ierr = PCMGSetInterpolation(pc,i+1,mglevels[i+1]->restrct);CHKERRQ(ierr); 649 } 650 if (!mglevels[i+1]->restrct) { 651 ierr = PCMGSetRestriction(pc,i+1,mglevels[i+1]->interpolate);CHKERRQ(ierr); 652 } 653 if (mglevels[i+1]->interpolate == mglevels[i+1]->restrct) { 654 ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr); 655 } else { 656 ierr = MatMatMatMult(mglevels[i+1]->restrct,dB,mglevels[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr); 657 } 658 ierr = KSPSetOperators(mglevels[i]->smoothd,B,B);CHKERRQ(ierr); 659 if (i != n-2) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);} 660 dB = B; 661 } 662 if (n > 1) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);} 663 } else { 664 for (i=n-2; i>-1; i--) { 665 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"); 666 if (!mglevels[i+1]->interpolate) { 667 ierr = PCMGSetInterpolation(pc,i+1,mglevels[i+1]->restrct);CHKERRQ(ierr); 668 } 669 if (!mglevels[i+1]->restrct) { 670 ierr = PCMGSetRestriction(pc,i+1,mglevels[i+1]->interpolate);CHKERRQ(ierr); 671 } 672 ierr = KSPGetOperators(mglevels[i]->smoothd,NULL,&B);CHKERRQ(ierr); 673 if (mglevels[i+1]->interpolate == mglevels[i+1]->restrct) { 674 ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr); 675 } else { 676 ierr = MatMatMatMult(mglevels[i+1]->restrct,dB,mglevels[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr); 677 } 678 ierr = KSPSetOperators(mglevels[i]->smoothd,B,B);CHKERRQ(ierr); 679 dB = B; 680 } 681 } 682 } else if (!mg->galerkin && pc->dm && pc->dm->x) { 683 /* need to restrict Jacobian location to coarser meshes for evaluation */ 684 for (i=n-2; i>-1; i--) { 685 Mat R; 686 Vec rscale; 687 if (!mglevels[i]->smoothd->dm->x) { 688 Vec *vecs; 689 ierr = KSPCreateVecs(mglevels[i]->smoothd,1,&vecs,0,NULL);CHKERRQ(ierr); 690 691 mglevels[i]->smoothd->dm->x = vecs[0]; 692 693 ierr = PetscFree(vecs);CHKERRQ(ierr); 694 } 695 ierr = PCMGGetRestriction(pc,i+1,&R);CHKERRQ(ierr); 696 ierr = PCMGGetRScale(pc,i+1,&rscale);CHKERRQ(ierr); 697 ierr = MatRestrict(R,mglevels[i+1]->smoothd->dm->x,mglevels[i]->smoothd->dm->x);CHKERRQ(ierr); 698 ierr = VecPointwiseMult(mglevels[i]->smoothd->dm->x,mglevels[i]->smoothd->dm->x,rscale);CHKERRQ(ierr); 699 } 700 } 701 if (!mg->galerkin && pc->dm) { 702 for (i=n-2; i>=0; i--) { 703 DM dmfine,dmcoarse; 704 Mat Restrict,Inject; 705 Vec rscale; 706 ierr = KSPGetDM(mglevels[i+1]->smoothd,&dmfine);CHKERRQ(ierr); 707 ierr = KSPGetDM(mglevels[i]->smoothd,&dmcoarse);CHKERRQ(ierr); 708 ierr = PCMGGetRestriction(pc,i+1,&Restrict);CHKERRQ(ierr); 709 ierr = PCMGGetRScale(pc,i+1,&rscale);CHKERRQ(ierr); 710 Inject = NULL; /* Callback should create it if it needs Injection */ 711 ierr = DMRestrict(dmfine,Restrict,rscale,Inject,dmcoarse);CHKERRQ(ierr); 712 } 713 } 714 715 if (!pc->setupcalled) { 716 for (i=0; i<n; i++) { 717 ierr = KSPSetFromOptions(mglevels[i]->smoothd);CHKERRQ(ierr); 718 } 719 for (i=1; i<n; i++) { 720 if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) { 721 ierr = KSPSetFromOptions(mglevels[i]->smoothu);CHKERRQ(ierr); 722 } 723 } 724 for (i=1; i<n; i++) { 725 ierr = PCMGGetInterpolation(pc,i,&mglevels[i]->interpolate);CHKERRQ(ierr); 726 ierr = PCMGGetRestriction(pc,i,&mglevels[i]->restrct);CHKERRQ(ierr); 727 } 728 for (i=0; i<n-1; i++) { 729 if (!mglevels[i]->b) { 730 Vec *vec; 731 ierr = KSPCreateVecs(mglevels[i]->smoothd,1,&vec,0,NULL);CHKERRQ(ierr); 732 ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr); 733 ierr = VecDestroy(vec);CHKERRQ(ierr); 734 ierr = PetscFree(vec);CHKERRQ(ierr); 735 } 736 if (!mglevels[i]->r && i) { 737 ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr); 738 ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr); 739 ierr = VecDestroy(&tvec);CHKERRQ(ierr); 740 } 741 if (!mglevels[i]->x) { 742 ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr); 743 ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr); 744 ierr = VecDestroy(&tvec);CHKERRQ(ierr); 745 } 746 } 747 if (n != 1 && !mglevels[n-1]->r) { 748 /* PCMGSetR() on the finest level if user did not supply it */ 749 Vec *vec; 750 ierr = KSPCreateVecs(mglevels[n-1]->smoothd,1,&vec,0,NULL);CHKERRQ(ierr); 751 ierr = PCMGSetR(pc,n-1,*vec);CHKERRQ(ierr); 752 ierr = VecDestroy(vec);CHKERRQ(ierr); 753 ierr = PetscFree(vec);CHKERRQ(ierr); 754 } 755 } 756 757 if (pc->dm) { 758 /* need to tell all the coarser levels to rebuild the matrix using the DM for that level */ 759 for (i=0; i<n-1; i++) { 760 if (mglevels[i]->smoothd->setupstage != KSP_SETUP_NEW) mglevels[i]->smoothd->setupstage = KSP_SETUP_NEWMATRIX; 761 } 762 } 763 764 for (i=1; i<n; i++) { 765 if (mglevels[i]->smoothu == mglevels[i]->smoothd || mg->am == PC_MG_FULL || mg->am == PC_MG_KASKADE || mg->cyclesperpcapply > 1){ 766 /* if doing only down then initial guess is zero */ 767 ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr); 768 } 769 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 770 ierr = KSPSetUp(mglevels[i]->smoothd);CHKERRQ(ierr); 771 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 772 if (!mglevels[i]->residual) { 773 Mat mat; 774 ierr = KSPGetOperators(mglevels[i]->smoothd,NULL,&mat);CHKERRQ(ierr); 775 ierr = PCMGSetResidual(pc,i,PCMGResidualDefault,mat);CHKERRQ(ierr); 776 } 777 } 778 for (i=1; i<n; i++) { 779 if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) { 780 Mat downmat,downpmat; 781 782 /* check if operators have been set for up, if not use down operators to set them */ 783 ierr = KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,NULL);CHKERRQ(ierr); 784 if (!opsset) { 785 ierr = KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat);CHKERRQ(ierr); 786 ierr = KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat);CHKERRQ(ierr); 787 } 788 789 ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr); 790 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 791 ierr = KSPSetUp(mglevels[i]->smoothu);CHKERRQ(ierr); 792 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 793 } 794 } 795 796 /* 797 If coarse solver is not direct method then DO NOT USE preonly 798 */ 799 ierr = PetscObjectTypeCompare((PetscObject)mglevels[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr); 800 if (preonly) { 801 ierr = PetscObjectTypeCompare((PetscObject)cpc,PCBJACOBI,&bjaclu);CHKERRQ(ierr); 802 if (bjaclu) { 803 KSP *k2; 804 PetscInt ii,first; 805 ierr = PCBJacobiGetSubKSP(cpc,&ii,&first,&k2);CHKERRQ(ierr); 806 if (ii==1) { 807 PC pc2; 808 ierr = KSPGetPC(k2[0],&pc2);CHKERRQ(ierr); 809 ierr = PetscObjectTypeCompare((PetscObject)pc2,PCLU,&bjaclu);CHKERRQ(ierr); 810 } 811 else bjaclu = PETSC_FALSE; 812 } 813 ierr = PetscObjectTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr); 814 ierr = PetscObjectTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr); 815 ierr = PetscObjectTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr); 816 ierr = PetscObjectTypeCompare((PetscObject)cpc,PCSVD,&svd);CHKERRQ(ierr); 817 if (!lu && !redundant && !cholesky && !svd && !bjaclu) { 818 ierr = KSPSetType(mglevels[0]->smoothd,KSPGMRES);CHKERRQ(ierr); 819 } 820 } 821 822 if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 823 ierr = KSPSetUp(mglevels[0]->smoothd);CHKERRQ(ierr); 824 if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 825 826 /* 827 Dump the interpolation/restriction matrices plus the 828 Jacobian/stiffness on each level. This allows MATLAB users to 829 easily check if the Galerkin condition A_c = R A_f R^T is satisfied. 830 831 Only support one or the other at the same time. 832 */ 833 #if defined(PETSC_USE_SOCKET_VIEWER) 834 ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,NULL);CHKERRQ(ierr); 835 if (dump) viewer = PETSC_VIEWER_SOCKET_(PetscObjectComm((PetscObject)pc)); 836 dump = PETSC_FALSE; 837 #endif 838 ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,NULL);CHKERRQ(ierr); 839 if (dump) viewer = PETSC_VIEWER_BINARY_(PetscObjectComm((PetscObject)pc)); 840 841 if (viewer) { 842 for (i=1; i<n; i++) { 843 ierr = MatView(mglevels[i]->restrct,viewer);CHKERRQ(ierr); 844 } 845 for (i=0; i<n; i++) { 846 ierr = KSPGetPC(mglevels[i]->smoothd,&pc);CHKERRQ(ierr); 847 ierr = MatView(pc->mat,viewer);CHKERRQ(ierr); 848 } 849 } 850 PetscFunctionReturn(0); 851 } 852 853 /* -------------------------------------------------------------------------------------*/ 854 855 #undef __FUNCT__ 856 #define __FUNCT__ "PCMGGetLevels" 857 /*@ 858 PCMGGetLevels - Gets the number of levels to use with MG. 859 860 Not Collective 861 862 Input Parameter: 863 . pc - the preconditioner context 864 865 Output parameter: 866 . levels - the number of levels 867 868 Level: advanced 869 870 .keywords: MG, get, levels, multigrid 871 872 .seealso: PCMGSetLevels() 873 @*/ 874 PetscErrorCode PCMGGetLevels(PC pc,PetscInt *levels) 875 { 876 PC_MG *mg = (PC_MG*)pc->data; 877 878 PetscFunctionBegin; 879 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 880 PetscValidIntPointer(levels,2); 881 *levels = mg->nlevels; 882 PetscFunctionReturn(0); 883 } 884 885 #undef __FUNCT__ 886 #define __FUNCT__ "PCMGSetType" 887 /*@ 888 PCMGSetType - Determines the form of multigrid to use: 889 multiplicative, additive, full, or the Kaskade algorithm. 890 891 Logically Collective on PC 892 893 Input Parameters: 894 + pc - the preconditioner context 895 - form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE, 896 PC_MG_FULL, PC_MG_KASKADE 897 898 Options Database Key: 899 . -pc_mg_type <form> - Sets <form>, one of multiplicative, 900 additive, full, kaskade 901 902 Level: advanced 903 904 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid 905 906 .seealso: PCMGSetLevels() 907 @*/ 908 PetscErrorCode PCMGSetType(PC pc,PCMGType form) 909 { 910 PC_MG *mg = (PC_MG*)pc->data; 911 912 PetscFunctionBegin; 913 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 914 PetscValidLogicalCollectiveEnum(pc,form,2); 915 mg->am = form; 916 if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG; 917 else pc->ops->applyrichardson = NULL; 918 PetscFunctionReturn(0); 919 } 920 921 /*@ 922 PCMGGetType - Determines the form of multigrid to use: 923 multiplicative, additive, full, or the Kaskade algorithm. 924 925 Logically Collective on PC 926 927 Input Parameter: 928 . pc - the preconditioner context 929 930 Output Parameter: 931 . type - one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,PC_MG_FULL, PC_MG_KASKADE 932 933 934 Level: advanced 935 936 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid 937 938 .seealso: PCMGSetLevels() 939 @*/ 940 PetscErrorCode PCMGGetType(PC pc,PCMGType *type) 941 { 942 PC_MG *mg = (PC_MG*)pc->data; 943 944 PetscFunctionBegin; 945 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 946 *type = mg->am; 947 PetscFunctionReturn(0); 948 } 949 950 #undef __FUNCT__ 951 #define __FUNCT__ "PCMGSetCycleType" 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 - PC_MG_CYCLE_V or PC_MG_CYCLE_W 961 962 Options Database Key: 963 . -pc_mg_cycle_type <v,w> 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 PetscValidLogicalCollectiveInt(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 #undef __FUNCT__ 988 #define __FUNCT__ "PCMGMultiplicativeSetCycles" 989 /*@ 990 PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step 991 of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used 992 993 Logically Collective on PC 994 995 Input Parameters: 996 + pc - the multigrid context 997 - n - number of cycles (default is 1) 998 999 Options Database Key: 1000 . -pc_mg_multiplicative_cycles n 1001 1002 Level: advanced 1003 1004 Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType() 1005 1006 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid 1007 1008 .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType() 1009 @*/ 1010 PetscErrorCode PCMGMultiplicativeSetCycles(PC pc,PetscInt n) 1011 { 1012 PC_MG *mg = (PC_MG*)pc->data; 1013 1014 PetscFunctionBegin; 1015 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1016 PetscValidLogicalCollectiveInt(pc,n,2); 1017 mg->cyclesperpcapply = n; 1018 PetscFunctionReturn(0); 1019 } 1020 1021 #undef __FUNCT__ 1022 #define __FUNCT__ "PCMGSetGalerkin_MG" 1023 PetscErrorCode PCMGSetGalerkin_MG(PC pc,PetscBool use) 1024 { 1025 PC_MG *mg = (PC_MG*)pc->data; 1026 1027 PetscFunctionBegin; 1028 mg->galerkin = use ? 1 : 0; 1029 PetscFunctionReturn(0); 1030 } 1031 1032 #undef __FUNCT__ 1033 #define __FUNCT__ "PCMGSetGalerkin" 1034 /*@ 1035 PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the 1036 finest grid via the Galerkin process: A_i-1 = r_i * A_i * p_i 1037 1038 Logically Collective on PC 1039 1040 Input Parameters: 1041 + pc - the multigrid context 1042 - use - PETSC_TRUE to use the Galerkin process to compute coarse-level operators 1043 1044 Options Database Key: 1045 . -pc_mg_galerkin <true,false> 1046 1047 Level: intermediate 1048 1049 Notes: Some codes that use PCMG such as PCGAMG use Galerkin internally while constructing the hierarchy and thus do not 1050 use the PCMG construction of the coarser grids. 1051 1052 .keywords: MG, set, Galerkin 1053 1054 .seealso: PCMGGetGalerkin() 1055 1056 @*/ 1057 PetscErrorCode PCMGSetGalerkin(PC pc,PetscBool use) 1058 { 1059 PetscErrorCode ierr; 1060 1061 PetscFunctionBegin; 1062 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1063 ierr = PetscTryMethod(pc,"PCMGSetGalerkin_C",(PC,PetscBool),(pc,use));CHKERRQ(ierr); 1064 PetscFunctionReturn(0); 1065 } 1066 1067 #undef __FUNCT__ 1068 #define __FUNCT__ "PCMGGetGalerkin" 1069 /*@ 1070 PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e. 1071 A_i-1 = r_i * A_i * p_i 1072 1073 Not Collective 1074 1075 Input Parameter: 1076 . pc - the multigrid context 1077 1078 Output Parameter: 1079 . galerkin - PETSC_TRUE or PETSC_FALSE 1080 1081 Options Database Key: 1082 . -pc_mg_galerkin 1083 1084 Level: intermediate 1085 1086 .keywords: MG, set, Galerkin 1087 1088 .seealso: PCMGSetGalerkin() 1089 1090 @*/ 1091 PetscErrorCode PCMGGetGalerkin(PC pc,PetscBool *galerkin) 1092 { 1093 PC_MG *mg = (PC_MG*)pc->data; 1094 1095 PetscFunctionBegin; 1096 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1097 *galerkin = (PetscBool)mg->galerkin; 1098 PetscFunctionReturn(0); 1099 } 1100 1101 #undef __FUNCT__ 1102 #define __FUNCT__ "PCMGSetNumberSmoothDown" 1103 /*@ 1104 PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to 1105 use on all levels. Use PCMGGetSmootherDown() to set different 1106 pre-smoothing steps on different levels. 1107 1108 Logically Collective on PC 1109 1110 Input Parameters: 1111 + mg - the multigrid context 1112 - n - the number of smoothing steps 1113 1114 Options Database Key: 1115 . -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps 1116 1117 Level: advanced 1118 1119 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid 1120 1121 .seealso: PCMGSetNumberSmoothUp() 1122 @*/ 1123 PetscErrorCode PCMGSetNumberSmoothDown(PC pc,PetscInt n) 1124 { 1125 PC_MG *mg = (PC_MG*)pc->data; 1126 PC_MG_Levels **mglevels = mg->levels; 1127 PetscErrorCode ierr; 1128 PetscInt i,levels; 1129 1130 PetscFunctionBegin; 1131 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1132 if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 1133 PetscValidLogicalCollectiveInt(pc,n,2); 1134 levels = mglevels[0]->levels; 1135 1136 for (i=1; i<levels; i++) { 1137 /* make sure smoother up and down are different */ 1138 ierr = PCMGGetSmootherUp(pc,i,NULL);CHKERRQ(ierr); 1139 ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 1140 1141 mg->default_smoothd = n; 1142 } 1143 PetscFunctionReturn(0); 1144 } 1145 1146 #undef __FUNCT__ 1147 #define __FUNCT__ "PCMGSetNumberSmoothUp" 1148 /*@ 1149 PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use 1150 on all levels. Use PCMGGetSmootherUp() to set different numbers of 1151 post-smoothing steps on different levels. 1152 1153 Logically Collective on PC 1154 1155 Input Parameters: 1156 + mg - the multigrid context 1157 - n - the number of smoothing steps 1158 1159 Options Database Key: 1160 . -pc_mg_smoothup <n> - Sets number of post-smoothing steps 1161 1162 Level: advanced 1163 1164 Note: this does not set a value on the coarsest grid, since we assume that 1165 there is no separate smooth up on the coarsest grid. 1166 1167 .keywords: MG, smooth, up, post-smoothing, steps, multigrid 1168 1169 .seealso: PCMGSetNumberSmoothDown() 1170 @*/ 1171 PetscErrorCode PCMGSetNumberSmoothUp(PC pc,PetscInt n) 1172 { 1173 PC_MG *mg = (PC_MG*)pc->data; 1174 PC_MG_Levels **mglevels = mg->levels; 1175 PetscErrorCode ierr; 1176 PetscInt i,levels; 1177 1178 PetscFunctionBegin; 1179 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1180 if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 1181 PetscValidLogicalCollectiveInt(pc,n,2); 1182 levels = mglevels[0]->levels; 1183 1184 for (i=1; i<levels; i++) { 1185 /* make sure smoother up and down are different */ 1186 ierr = PCMGGetSmootherUp(pc,i,NULL);CHKERRQ(ierr); 1187 ierr = KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 1188 1189 mg->default_smoothu = n; 1190 } 1191 PetscFunctionReturn(0); 1192 } 1193 1194 /* ----------------------------------------------------------------------------------------*/ 1195 1196 /*MC 1197 PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional 1198 information about the coarser grid matrices and restriction/interpolation operators. 1199 1200 Options Database Keys: 1201 + -pc_mg_levels <nlevels> - number of levels including finest 1202 . -pc_mg_cycles <v,w> - 1203 . -pc_mg_smoothup <n> - number of smoothing steps after interpolation 1204 . -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator 1205 . -pc_mg_type <additive,multiplicative,full,kaskade> - multiplicative is the default 1206 . -pc_mg_log - log information about time spent on each level of the solver 1207 . -pc_mg_galerkin - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R' 1208 . -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1) 1209 . -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices 1210 to the Socket viewer for reading from MATLAB. 1211 - -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices 1212 to the binary output file called binaryoutput 1213 1214 Notes: By default this uses GMRES on the fine grid smoother so this should be used with KSPFGMRES or the smoother changed to not use GMRES 1215 1216 When run with a single level the smoother options are used on that level NOT the coarse grid solver options 1217 1218 Level: intermediate 1219 1220 Concepts: multigrid/multilevel 1221 1222 .seealso: PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE 1223 PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(), 1224 PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(), 1225 PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(), 1226 PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR() 1227 M*/ 1228 1229 #undef __FUNCT__ 1230 #define __FUNCT__ "PCCreate_MG" 1231 PETSC_EXTERN PetscErrorCode PCCreate_MG(PC pc) 1232 { 1233 PC_MG *mg; 1234 PetscErrorCode ierr; 1235 1236 PetscFunctionBegin; 1237 ierr = PetscNewLog(pc,&mg);CHKERRQ(ierr); 1238 pc->data = (void*)mg; 1239 mg->nlevels = -1; 1240 1241 pc->useAmat = PETSC_TRUE; 1242 1243 pc->ops->apply = PCApply_MG; 1244 pc->ops->setup = PCSetUp_MG; 1245 pc->ops->reset = PCReset_MG; 1246 pc->ops->destroy = PCDestroy_MG; 1247 pc->ops->setfromoptions = PCSetFromOptions_MG; 1248 pc->ops->view = PCView_MG; 1249 1250 ierr = PetscObjectComposeFunction((PetscObject)pc,"PCMGSetGalerkin_C",PCMGSetGalerkin_MG);CHKERRQ(ierr); 1251 PetscFunctionReturn(0); 1252 } 1253