1 2 /* 3 Defines the multigrid preconditioner interface. 4 */ 5 #include <../src/ksp/pc/impls/mg/mgimpl.h> /*I "petscpcmg.h" I*/ 6 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 19 if (mglevels->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 20 ierr = KSPSolve(mglevels->smoothd,mglevels->b,mglevels->x);CHKERRQ(ierr); /* pre-smooth */ 21 if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 22 if (mglevels->level) { /* not the coarsest grid */ 23 if (mglevels->eventresidual) {ierr = PetscLogEventBegin(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);} 24 ierr = (*mglevels->residual)(mglevels->A,mglevels->b,mglevels->x,mglevels->r);CHKERRQ(ierr); 25 if (mglevels->eventresidual) {ierr = PetscLogEventEnd(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);} 26 27 /* if on finest level and have convergence criteria set */ 28 if (mglevels->level == mglevels->levels-1 && mg->ttol && reason) { 29 PetscReal rnorm; 30 ierr = VecNorm(mglevels->r,NORM_2,&rnorm);CHKERRQ(ierr); 31 if (rnorm <= mg->ttol) { 32 if (rnorm < mg->abstol) { 33 *reason = PCRICHARDSON_CONVERGED_ATOL; 34 ierr = PetscInfo2(pc,"Linear solver has converged. Residual norm %G is less than absolute tolerance %G\n",rnorm,mg->abstol);CHKERRQ(ierr); 35 } else { 36 *reason = PCRICHARDSON_CONVERGED_RTOL; 37 ierr = PetscInfo2(pc,"Linear solver has converged. Residual norm %G is less than relative tolerance times initial residual norm %G\n",rnorm,mg->ttol);CHKERRQ(ierr); 38 } 39 PetscFunctionReturn(0); 40 } 41 } 42 43 mgc = *(mglevelsin - 1); 44 if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 45 ierr = MatRestrict(mglevels->restrct,mglevels->r,mgc->b);CHKERRQ(ierr); 46 if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 47 ierr = VecSet(mgc->x,0.0);CHKERRQ(ierr); 48 while (cycles--) { 49 ierr = PCMGMCycle_Private(pc,mglevelsin-1,reason);CHKERRQ(ierr); 50 } 51 if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 52 ierr = MatInterpolateAdd(mglevels->interpolate,mgc->x,mglevels->x,mglevels->x);CHKERRQ(ierr); 53 if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 54 if (mglevels->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 55 ierr = KSPSolve(mglevels->smoothu,mglevels->b,mglevels->x);CHKERRQ(ierr); /* post smooth */ 56 if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 57 } 58 PetscFunctionReturn(0); 59 } 60 61 #undef __FUNCT__ 62 #define __FUNCT__ "PCApplyRichardson_MG" 63 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) 64 { 65 PC_MG *mg = (PC_MG*)pc->data; 66 PC_MG_Levels **mglevels = mg->levels; 67 PetscErrorCode ierr; 68 PetscInt levels = mglevels[0]->levels,i; 69 70 PetscFunctionBegin; 71 mglevels[levels-1]->b = b; 72 mglevels[levels-1]->x = x; 73 74 mg->rtol = rtol; 75 mg->abstol = abstol; 76 mg->dtol = dtol; 77 if (rtol) { 78 /* compute initial residual norm for relative convergence test */ 79 PetscReal rnorm; 80 if (zeroguess) { 81 ierr = VecNorm(b,NORM_2,&rnorm);CHKERRQ(ierr); 82 } else { 83 ierr = (*mglevels[levels-1]->residual)(mglevels[levels-1]->A,b,x,w);CHKERRQ(ierr); 84 ierr = VecNorm(w,NORM_2,&rnorm);CHKERRQ(ierr); 85 } 86 mg->ttol = PetscMax(rtol*rnorm,abstol); 87 } else if (abstol) { 88 mg->ttol = abstol; 89 } else { 90 mg->ttol = 0.0; 91 } 92 93 /* since smoother is applied to full system, not just residual we need to make sure that smoothers don't 94 stop prematurely do to small residual */ 95 for (i=1; i<levels; i++) { 96 ierr = KSPSetTolerances(mglevels[i]->smoothu,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr); 97 if (mglevels[i]->smoothu != mglevels[i]->smoothd) { 98 ierr = KSPSetTolerances(mglevels[i]->smoothd,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr); 99 } 100 } 101 102 *reason = (PCRichardsonConvergedReason)0; 103 for (i=0; i<its; i++) { 104 ierr = PCMGMCycle_Private(pc,mglevels+levels-1,reason);CHKERRQ(ierr); 105 if (*reason) break; 106 } 107 if (!*reason) *reason = PCRICHARDSON_CONVERGED_ITS; 108 *outits = i; 109 PetscFunctionReturn(0); 110 } 111 112 #undef __FUNCT__ 113 #define __FUNCT__ "PCReset_MG" 114 PetscErrorCode PCReset_MG(PC pc) 115 { 116 PC_MG *mg = (PC_MG*)pc->data; 117 PC_MG_Levels **mglevels = mg->levels; 118 PetscErrorCode ierr; 119 PetscInt i,n; 120 121 PetscFunctionBegin; 122 if (mglevels) { 123 n = mglevels[0]->levels; 124 for (i=0; i<n-1; i++) { 125 ierr = VecDestroy(&mglevels[i+1]->r);CHKERRQ(ierr); 126 ierr = VecDestroy(&mglevels[i]->b);CHKERRQ(ierr); 127 ierr = VecDestroy(&mglevels[i]->x);CHKERRQ(ierr); 128 ierr = MatDestroy(&mglevels[i+1]->restrct);CHKERRQ(ierr); 129 ierr = MatDestroy(&mglevels[i+1]->interpolate);CHKERRQ(ierr); 130 ierr = VecDestroy(&mglevels[i+1]->rscale);CHKERRQ(ierr); 131 } 132 133 for (i=0; i<n; i++) { 134 ierr = MatDestroy(&mglevels[i]->A);CHKERRQ(ierr); 135 if (mglevels[i]->smoothd != mglevels[i]->smoothu) { 136 ierr = KSPReset(mglevels[i]->smoothd);CHKERRQ(ierr); 137 } 138 ierr = KSPReset(mglevels[i]->smoothu);CHKERRQ(ierr); 139 } 140 } 141 PetscFunctionReturn(0); 142 } 143 144 #undef __FUNCT__ 145 #define __FUNCT__ "PCMGSetLevels" 146 /*@C 147 PCMGSetLevels - Sets the number of levels to use with MG. 148 Must be called before any other MG routine. 149 150 Logically Collective on PC 151 152 Input Parameters: 153 + pc - the preconditioner context 154 . levels - the number of levels 155 - comms - optional communicators for each level; this is to allow solving the coarser problems 156 on smaller sets of processors. Use PETSC_NULL_OBJECT for default in Fortran 157 158 Level: intermediate 159 160 Notes: 161 If the number of levels is one then the multigrid uses the -mg_levels prefix 162 for setting the level options rather than the -mg_coarse prefix. 163 164 .keywords: MG, set, levels, multigrid 165 166 .seealso: PCMGSetType(), PCMGGetLevels() 167 @*/ 168 PetscErrorCode PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms) 169 { 170 PetscErrorCode ierr; 171 PC_MG *mg = (PC_MG*)pc->data; 172 MPI_Comm comm = ((PetscObject)pc)->comm; 173 PC_MG_Levels **mglevels = mg->levels; 174 PetscInt i; 175 PetscMPIInt size; 176 const char *prefix; 177 PC ipc; 178 PetscInt n; 179 180 PetscFunctionBegin; 181 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 182 PetscValidLogicalCollectiveInt(pc,levels,2); 183 if (mg->nlevels == levels) PetscFunctionReturn(0); 184 if (mglevels) { 185 /* changing the number of levels so free up the previous stuff */ 186 ierr = PCReset_MG(pc);CHKERRQ(ierr); 187 n = mglevels[0]->levels; 188 for (i=0; i<n; i++) { 189 if (mglevels[i]->smoothd != mglevels[i]->smoothu) { 190 ierr = KSPDestroy(&mglevels[i]->smoothd);CHKERRQ(ierr); 191 } 192 ierr = KSPDestroy(&mglevels[i]->smoothu);CHKERRQ(ierr); 193 ierr = PetscFree(mglevels[i]);CHKERRQ(ierr); 194 } 195 ierr = PetscFree(mg->levels);CHKERRQ(ierr); 196 } 197 198 mg->nlevels = levels; 199 200 ierr = PetscMalloc(levels*sizeof(PC_MG*),&mglevels);CHKERRQ(ierr); 201 ierr = PetscLogObjectMemory(pc,levels*(sizeof(PC_MG*)));CHKERRQ(ierr); 202 203 ierr = PCGetOptionsPrefix(pc,&prefix);CHKERRQ(ierr); 204 205 for (i=0; i<levels; i++) { 206 ierr = PetscNewLog(pc,PC_MG_Levels,&mglevels[i]);CHKERRQ(ierr); 207 mglevels[i]->level = i; 208 mglevels[i]->levels = levels; 209 mglevels[i]->cycles = PC_MG_CYCLE_V; 210 mg->default_smoothu = 1; 211 mg->default_smoothd = 1; 212 mglevels[i]->eventsmoothsetup = 0; 213 mglevels[i]->eventsmoothsolve = 0; 214 mglevels[i]->eventresidual = 0; 215 mglevels[i]->eventinterprestrict = 0; 216 217 if (comms) comm = comms[i]; 218 ierr = KSPCreate(comm,&mglevels[i]->smoothd);CHKERRQ(ierr); 219 ierr = PetscObjectIncrementTabLevel((PetscObject)mglevels[i]->smoothd,(PetscObject)pc,levels-i);CHKERRQ(ierr); 220 ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, mg->default_smoothd);CHKERRQ(ierr); 221 ierr = KSPSetOptionsPrefix(mglevels[i]->smoothd,prefix);CHKERRQ(ierr); 222 223 /* do special stuff for coarse grid */ 224 if (!i && levels > 1) { 225 ierr = KSPAppendOptionsPrefix(mglevels[0]->smoothd,"mg_coarse_");CHKERRQ(ierr); 226 227 /* coarse solve is (redundant) LU by default */ 228 ierr = KSPSetType(mglevels[0]->smoothd,KSPPREONLY);CHKERRQ(ierr); 229 ierr = KSPGetPC(mglevels[0]->smoothd,&ipc);CHKERRQ(ierr); 230 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 231 if (size > 1) { 232 ierr = PCSetType(ipc,PCREDUNDANT);CHKERRQ(ierr); 233 } else { 234 ierr = PCSetType(ipc,PCLU);CHKERRQ(ierr); 235 } 236 237 } else { 238 char tprefix[128]; 239 sprintf(tprefix,"mg_levels_%d_",(int)i); 240 ierr = KSPAppendOptionsPrefix(mglevels[i]->smoothd,tprefix);CHKERRQ(ierr); 241 } 242 ierr = PetscLogObjectParent(pc,mglevels[i]->smoothd);CHKERRQ(ierr); 243 mglevels[i]->smoothu = mglevels[i]->smoothd; 244 mg->rtol = 0.0; 245 mg->abstol = 0.0; 246 mg->dtol = 0.0; 247 mg->ttol = 0.0; 248 mg->cyclesperpcapply = 1; 249 } 250 mg->am = PC_MG_MULTIPLICATIVE; 251 mg->levels = mglevels; 252 pc->ops->applyrichardson = PCApplyRichardson_MG; 253 PetscFunctionReturn(0); 254 } 255 256 257 #undef __FUNCT__ 258 #define __FUNCT__ "PCDestroy_MG" 259 PetscErrorCode PCDestroy_MG(PC pc) 260 { 261 PetscErrorCode ierr; 262 PC_MG *mg = (PC_MG*)pc->data; 263 PC_MG_Levels **mglevels = mg->levels; 264 PetscInt i,n; 265 266 PetscFunctionBegin; 267 ierr = PCReset_MG(pc);CHKERRQ(ierr); 268 if (mglevels) { 269 n = mglevels[0]->levels; 270 for (i=0; i<n; i++) { 271 if (mglevels[i]->smoothd != mglevels[i]->smoothu) { 272 ierr = KSPDestroy(&mglevels[i]->smoothd);CHKERRQ(ierr); 273 } 274 ierr = KSPDestroy(&mglevels[i]->smoothu);CHKERRQ(ierr); 275 ierr = PetscFree(mglevels[i]);CHKERRQ(ierr); 276 } 277 ierr = PetscFree(mg->levels);CHKERRQ(ierr); 278 } 279 ierr = PetscFree(pc->data);CHKERRQ(ierr); 280 PetscFunctionReturn(0); 281 } 282 283 284 285 extern PetscErrorCode PCMGACycle_Private(PC,PC_MG_Levels**); 286 extern PetscErrorCode PCMGFCycle_Private(PC,PC_MG_Levels**); 287 extern PetscErrorCode PCMGKCycle_Private(PC,PC_MG_Levels**); 288 289 /* 290 PCApply_MG - Runs either an additive, multiplicative, Kaskadic 291 or full cycle of multigrid. 292 293 Note: 294 A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle(). 295 */ 296 #undef __FUNCT__ 297 #define __FUNCT__ "PCApply_MG" 298 static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x) 299 { 300 PC_MG *mg = (PC_MG*)pc->data; 301 PC_MG_Levels **mglevels = mg->levels; 302 PetscErrorCode ierr; 303 PetscInt levels = mglevels[0]->levels,i; 304 305 PetscFunctionBegin; 306 307 /* When the DM is supplying the matrix then it will not exist until here */ 308 for (i=0; i<levels; i++) { 309 if (!mglevels[i]->A) { 310 ierr = KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 311 ierr = PetscObjectReference((PetscObject)mglevels[i]->A);CHKERRQ(ierr); 312 } 313 } 314 315 mglevels[levels-1]->b = b; 316 mglevels[levels-1]->x = x; 317 if (mg->am == PC_MG_MULTIPLICATIVE) { 318 ierr = VecSet(x,0.0);CHKERRQ(ierr); 319 for (i=0; i<mg->cyclesperpcapply; i++) { 320 ierr = PCMGMCycle_Private(pc,mglevels+levels-1,PETSC_NULL);CHKERRQ(ierr); 321 } 322 } 323 else if (mg->am == PC_MG_ADDITIVE) { 324 ierr = PCMGACycle_Private(pc,mglevels);CHKERRQ(ierr); 325 } 326 else if (mg->am == PC_MG_KASKADE) { 327 ierr = PCMGKCycle_Private(pc,mglevels);CHKERRQ(ierr); 328 } 329 else { 330 ierr = PCMGFCycle_Private(pc,mglevels);CHKERRQ(ierr); 331 } 332 PetscFunctionReturn(0); 333 } 334 335 336 #undef __FUNCT__ 337 #define __FUNCT__ "PCSetFromOptions_MG" 338 PetscErrorCode PCSetFromOptions_MG(PC pc) 339 { 340 PetscErrorCode ierr; 341 PetscInt m,levels = 1,cycles; 342 PetscBool flg,set; 343 PC_MG *mg = (PC_MG*)pc->data; 344 PC_MG_Levels **mglevels = mg->levels; 345 PCMGType mgtype; 346 PCMGCycleType mgctype; 347 348 PetscFunctionBegin; 349 ierr = PetscOptionsHead("Multigrid options");CHKERRQ(ierr); 350 if (!mg->levels) { 351 ierr = PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);CHKERRQ(ierr); 352 if (!flg && pc->dm) { 353 ierr = DMGetRefineLevel(pc->dm,&levels);CHKERRQ(ierr); 354 levels++; 355 mg->usedmfornumberoflevels = PETSC_TRUE; 356 } 357 ierr = PCMGSetLevels(pc,levels,PETSC_NULL);CHKERRQ(ierr); 358 } 359 mglevels = mg->levels; 360 361 mgctype = (PCMGCycleType) mglevels[0]->cycles; 362 ierr = PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);CHKERRQ(ierr); 363 if (flg) { 364 ierr = PCMGSetCycleType(pc,mgctype);CHKERRQ(ierr); 365 }; 366 flg = PETSC_FALSE; 367 ierr = PetscOptionsBool("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",flg,&flg,&set);CHKERRQ(ierr); 368 if (set) { 369 ierr = PCMGSetGalerkin(pc,flg);CHKERRQ(ierr); 370 } 371 ierr = PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",1,&m,&flg);CHKERRQ(ierr); 372 if (flg) { 373 ierr = PCMGSetNumberSmoothUp(pc,m);CHKERRQ(ierr); 374 } 375 ierr = PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",1,&m,&flg);CHKERRQ(ierr); 376 if (flg) { 377 ierr = PCMGSetNumberSmoothDown(pc,m);CHKERRQ(ierr); 378 } 379 mgtype = mg->am; 380 ierr = PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);CHKERRQ(ierr); 381 if (flg) { 382 ierr = PCMGSetType(pc,mgtype);CHKERRQ(ierr); 383 } 384 if (mg->am == PC_MG_MULTIPLICATIVE) { 385 ierr = PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGSetLevels",mg->cyclesperpcapply,&cycles,&flg);CHKERRQ(ierr); 386 if (flg) { 387 ierr = PCMGMultiplicativeSetCycles(pc,cycles);CHKERRQ(ierr); 388 } 389 } 390 flg = PETSC_FALSE; 391 ierr = PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,PETSC_NULL);CHKERRQ(ierr); 392 if (flg) { 393 PetscInt i; 394 char eventname[128]; 395 if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 396 levels = mglevels[0]->levels; 397 for (i=0; i<levels; i++) { 398 sprintf(eventname,"MGSetup Level %d",(int)i); 399 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);CHKERRQ(ierr); 400 sprintf(eventname,"MGSmooth Level %d",(int)i); 401 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);CHKERRQ(ierr); 402 if (i) { 403 sprintf(eventname,"MGResid Level %d",(int)i); 404 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);CHKERRQ(ierr); 405 sprintf(eventname,"MGInterp Level %d",(int)i); 406 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);CHKERRQ(ierr); 407 } 408 } 409 } 410 ierr = PetscOptionsTail();CHKERRQ(ierr); 411 PetscFunctionReturn(0); 412 } 413 414 const char *PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0}; 415 const char *PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",0}; 416 417 #undef __FUNCT__ 418 #define __FUNCT__ "PCView_MG" 419 PetscErrorCode PCView_MG(PC pc,PetscViewer viewer) 420 { 421 PC_MG *mg = (PC_MG*)pc->data; 422 PC_MG_Levels **mglevels = mg->levels; 423 PetscErrorCode ierr; 424 PetscInt levels = mglevels[0]->levels,i; 425 PetscBool iascii; 426 427 PetscFunctionBegin; 428 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 429 if (iascii) { 430 ierr = PetscViewerASCIIPrintf(viewer," MG: type is %s, levels=%D cycles=%s\n", PCMGTypes[mg->am],levels,(mglevels[0]->cycles == PC_MG_CYCLE_V) ? "v" : "w");CHKERRQ(ierr); 431 if (mg->am == PC_MG_MULTIPLICATIVE) { 432 ierr = PetscViewerASCIIPrintf(viewer," Cycles per PCApply=%d\n",mg->cyclesperpcapply);CHKERRQ(ierr); 433 } 434 if (mg->galerkin) { 435 ierr = PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr); 436 } else { 437 ierr = PetscViewerASCIIPrintf(viewer," Not using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr); 438 } 439 for (i=0; i<levels; i++) { 440 if (!i) { 441 ierr = PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level -------------------------------\n",i);CHKERRQ(ierr); 442 } else { 443 ierr = PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr); 444 } 445 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 446 ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr); 447 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 448 if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) { 449 ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");CHKERRQ(ierr); 450 } else if (i){ 451 ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr); 452 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 453 ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr); 454 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 455 } 456 } 457 } else SETERRQ1(((PetscObject)pc)->comm,PETSC_ERR_SUP,"Viewer type %s not supported for PCMG",((PetscObject)viewer)->type_name); 458 PetscFunctionReturn(0); 459 } 460 461 #include <private/dmimpl.h> 462 #include <private/kspimpl.h> 463 464 /* 465 Calls setup for the KSP on each level 466 */ 467 #undef __FUNCT__ 468 #define __FUNCT__ "PCSetUp_MG" 469 PetscErrorCode PCSetUp_MG(PC pc) 470 { 471 PC_MG *mg = (PC_MG*)pc->data; 472 PC_MG_Levels **mglevels = mg->levels; 473 PetscErrorCode ierr; 474 PetscInt i,n = mglevels[0]->levels; 475 PC cpc,mpc; 476 PetscBool preonly,lu,redundant,cholesky,svd,dump = PETSC_FALSE,opsset; 477 Mat dA,dB; 478 MatStructure uflag; 479 Vec tvec; 480 DM *dms; 481 PetscViewer viewer = 0; 482 483 PetscFunctionBegin; 484 if (mg->usedmfornumberoflevels) { 485 PetscInt levels; 486 ierr = DMGetRefineLevel(pc->dm,&levels);CHKERRQ(ierr); 487 levels++; 488 if (levels > n) { /* the problem is now being solved on a finer grid */ 489 ierr = PCMGSetLevels(pc,levels,PETSC_NULL);CHKERRQ(ierr); 490 n = levels; 491 ierr = PCSetFromOptions(pc);CHKERRQ(ierr); /* it is bad to call this here, but otherwise will never be called for the new hierarchy */ 492 mglevels = mg->levels; 493 } 494 } 495 496 497 /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */ 498 /* so use those from global PC */ 499 /* Is this what we always want? What if user wants to keep old one? */ 500 ierr = KSPGetOperatorsSet(mglevels[n-1]->smoothd,PETSC_NULL,&opsset);CHKERRQ(ierr); 501 ierr = KSPGetPC(mglevels[0]->smoothd,&cpc);CHKERRQ(ierr); 502 ierr = KSPGetPC(mglevels[n-1]->smoothd,&mpc);CHKERRQ(ierr); 503 if (!opsset || ((cpc->setupcalled == 1) && (mpc->setupcalled == 2)) || ((mpc == cpc) && (mpc->setupcalled == 2))) { 504 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); 505 ierr = KSPSetOperators(mglevels[n-1]->smoothd,pc->mat,pc->pmat,pc->flag);CHKERRQ(ierr); 506 } 507 508 if (pc->dm && !pc->setupcalled) { 509 /* construct the interpolation from the DMs */ 510 Mat p; 511 Vec rscale; 512 ierr = PetscMalloc(n*sizeof(DM),&dms);CHKERRQ(ierr); 513 dms[n-1] = pc->dm; 514 for (i=n-2; i>-1; i--) { 515 ierr = DMCoarsen(dms[i+1],PETSC_NULL,&dms[i]);CHKERRQ(ierr); 516 ierr = KSPSetDM(mglevels[i]->smoothd,dms[i]);CHKERRQ(ierr); 517 if (mg->galerkin) {ierr = KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);CHKERRQ(ierr);} 518 ierr = DMSetFunction(dms[i],0); 519 ierr = DMSetInitialGuess(dms[i],0); 520 if (!mglevels[i+1]->interpolate) { 521 ierr = DMGetInterpolation(dms[i],dms[i+1],&p,&rscale);CHKERRQ(ierr); 522 ierr = PCMGSetInterpolation(pc,i+1,p);CHKERRQ(ierr); 523 if (rscale) {ierr = PCMGSetRScale(pc,i+1,rscale);CHKERRQ(ierr);} 524 ierr = VecDestroy(&rscale);CHKERRQ(ierr); 525 ierr = MatDestroy(&p);CHKERRQ(ierr); 526 } 527 } 528 529 for (i=n-2; i>-1; i--) { 530 ierr = DMDestroy(&dms[i]);CHKERRQ(ierr); 531 } 532 ierr = PetscFree(dms);CHKERRQ(ierr); 533 534 /* finest smoother also gets DM but it is not active */ 535 ierr = KSPSetDM(mglevels[n-1]->smoothd,pc->dm);CHKERRQ(ierr); 536 ierr = KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);CHKERRQ(ierr); 537 } 538 539 if (mg->galerkin == 1) { 540 Mat B; 541 /* currently only handle case where mat and pmat are the same on coarser levels */ 542 ierr = KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr); 543 if (!pc->setupcalled) { 544 for (i=n-2; i>-1; i--) { 545 ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr); 546 ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr); 547 if (i != n-2) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);} 548 dB = B; 549 } 550 if (n > 1) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);} 551 } else { 552 for (i=n-2; i>-1; i--) { 553 ierr = KSPGetOperators(mglevels[i]->smoothd,PETSC_NULL,&B,PETSC_NULL);CHKERRQ(ierr); 554 ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr); 555 ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr); 556 dB = B; 557 } 558 } 559 } else if (pc->dm && pc->dm->x) { 560 /* need to restrict Jacobian location to coarser meshes for evaluation */ 561 for (i=n-2;i>-1; i--) { 562 if (!mglevels[i]->smoothd->dm->x) { 563 Vec *vecs; 564 ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vecs,0,PETSC_NULL);CHKERRQ(ierr); 565 mglevels[i]->smoothd->dm->x = vecs[0]; 566 ierr = PetscFree(vecs);CHKERRQ(ierr); 567 } 568 ierr = MatRestrict(mglevels[i+1]->interpolate,mglevels[i+1]->smoothd->dm->x,mglevels[i]->smoothd->dm->x);CHKERRQ(ierr); 569 ierr = VecPointwiseMult(mglevels[i]->smoothd->dm->x,mglevels[i]->smoothd->dm->x,mglevels[i+1]->rscale);CHKERRQ(ierr); 570 } 571 } 572 573 if (!pc->setupcalled) { 574 for (i=0; i<n; i++) { 575 ierr = KSPSetFromOptions(mglevels[i]->smoothd);CHKERRQ(ierr); 576 } 577 for (i=1; i<n; i++) { 578 if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) { 579 ierr = KSPSetFromOptions(mglevels[i]->smoothu);CHKERRQ(ierr); 580 } 581 } 582 for (i=1; i<n; i++) { 583 if (mglevels[i]->restrct && !mglevels[i]->interpolate) { 584 ierr = PCMGSetInterpolation(pc,i,mglevels[i]->restrct);CHKERRQ(ierr); 585 } 586 if (!mglevels[i]->restrct && mglevels[i]->interpolate) { 587 ierr = PCMGSetRestriction(pc,i,mglevels[i]->interpolate);CHKERRQ(ierr); 588 } 589 #if defined(PETSC_USE_DEBUG) 590 if (!mglevels[i]->restrct || !mglevels[i]->interpolate) { 591 SETERRQ1(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Need to set restriction or interpolation on level %d",(int)i); 592 } 593 #endif 594 } 595 for (i=0; i<n-1; i++) { 596 if (!mglevels[i]->b) { 597 Vec *vec; 598 ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr); 599 ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr); 600 ierr = VecDestroy(vec);CHKERRQ(ierr); 601 ierr = PetscFree(vec);CHKERRQ(ierr); 602 } 603 if (!mglevels[i]->r && i) { 604 ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr); 605 ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr); 606 ierr = VecDestroy(&tvec);CHKERRQ(ierr); 607 } 608 if (!mglevels[i]->x) { 609 ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr); 610 ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr); 611 ierr = VecDestroy(&tvec);CHKERRQ(ierr); 612 } 613 } 614 if (n != 1 && !mglevels[n-1]->r) { 615 /* PCMGSetR() on the finest level if user did not supply it */ 616 Vec *vec; 617 ierr = KSPGetVecs(mglevels[n-1]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr); 618 ierr = PCMGSetR(pc,n-1,*vec);CHKERRQ(ierr); 619 ierr = VecDestroy(vec);CHKERRQ(ierr); 620 ierr = PetscFree(vec);CHKERRQ(ierr); 621 } 622 } 623 624 625 for (i=1; i<n; i++) { 626 if (mglevels[i]->smoothu == mglevels[i]->smoothd) { 627 /* if doing only down then initial guess is zero */ 628 ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr); 629 } 630 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 631 ierr = KSPSetUp(mglevels[i]->smoothd);CHKERRQ(ierr); 632 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 633 if (!mglevels[i]->residual) { 634 Mat mat; 635 ierr = KSPGetOperators(mglevels[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);CHKERRQ(ierr); 636 ierr = PCMGSetResidual(pc,i,PCMGDefaultResidual,mat);CHKERRQ(ierr); 637 } 638 } 639 for (i=1; i<n; i++) { 640 if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) { 641 Mat downmat,downpmat; 642 MatStructure matflag; 643 PetscBool opsset; 644 645 /* check if operators have been set for up, if not use down operators to set them */ 646 ierr = KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,PETSC_NULL);CHKERRQ(ierr); 647 if (!opsset) { 648 ierr = KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat,&matflag);CHKERRQ(ierr); 649 ierr = KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr); 650 } 651 652 ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr); 653 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 654 ierr = KSPSetUp(mglevels[i]->smoothu);CHKERRQ(ierr); 655 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 656 } 657 } 658 659 /* 660 If coarse solver is not direct method then DO NOT USE preonly 661 */ 662 ierr = PetscTypeCompare((PetscObject)mglevels[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr); 663 if (preonly) { 664 ierr = PetscTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr); 665 ierr = PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr); 666 ierr = PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr); 667 ierr = PetscTypeCompare((PetscObject)cpc,PCSVD,&svd);CHKERRQ(ierr); 668 if (!lu && !redundant && !cholesky && !svd) { 669 ierr = KSPSetType(mglevels[0]->smoothd,KSPGMRES);CHKERRQ(ierr); 670 } 671 } 672 673 if (!pc->setupcalled) { 674 ierr = KSPSetFromOptions(mglevels[0]->smoothd);CHKERRQ(ierr); 675 } 676 677 if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 678 ierr = KSPSetUp(mglevels[0]->smoothd);CHKERRQ(ierr); 679 if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 680 681 /* 682 Dump the interpolation/restriction matrices plus the 683 Jacobian/stiffness on each level. This allows MATLAB users to 684 easily check if the Galerkin condition A_c = R A_f R^T is satisfied. 685 686 Only support one or the other at the same time. 687 */ 688 #if defined(PETSC_USE_SOCKET_VIEWER) 689 ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,PETSC_NULL);CHKERRQ(ierr); 690 if (dump) { 691 viewer = PETSC_VIEWER_SOCKET_(((PetscObject)pc)->comm); 692 } 693 dump = PETSC_FALSE; 694 #endif 695 ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,PETSC_NULL);CHKERRQ(ierr); 696 if (dump) { 697 viewer = PETSC_VIEWER_BINARY_(((PetscObject)pc)->comm); 698 } 699 700 if (viewer) { 701 for (i=1; i<n; i++) { 702 ierr = MatView(mglevels[i]->restrct,viewer);CHKERRQ(ierr); 703 } 704 for (i=0; i<n; i++) { 705 ierr = KSPGetPC(mglevels[i]->smoothd,&pc);CHKERRQ(ierr); 706 ierr = MatView(pc->mat,viewer);CHKERRQ(ierr); 707 } 708 } 709 PetscFunctionReturn(0); 710 } 711 712 /* -------------------------------------------------------------------------------------*/ 713 714 #undef __FUNCT__ 715 #define __FUNCT__ "PCMGGetLevels" 716 /*@ 717 PCMGGetLevels - Gets the number of levels to use with MG. 718 719 Not Collective 720 721 Input Parameter: 722 . pc - the preconditioner context 723 724 Output parameter: 725 . levels - the number of levels 726 727 Level: advanced 728 729 .keywords: MG, get, levels, multigrid 730 731 .seealso: PCMGSetLevels() 732 @*/ 733 PetscErrorCode PCMGGetLevels(PC pc,PetscInt *levels) 734 { 735 PC_MG *mg = (PC_MG*)pc->data; 736 737 PetscFunctionBegin; 738 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 739 PetscValidIntPointer(levels,2); 740 *levels = mg->nlevels; 741 PetscFunctionReturn(0); 742 } 743 744 #undef __FUNCT__ 745 #define __FUNCT__ "PCMGSetType" 746 /*@ 747 PCMGSetType - Determines the form of multigrid to use: 748 multiplicative, additive, full, or the Kaskade algorithm. 749 750 Logically Collective on PC 751 752 Input Parameters: 753 + pc - the preconditioner context 754 - form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE, 755 PC_MG_FULL, PC_MG_KASKADE 756 757 Options Database Key: 758 . -pc_mg_type <form> - Sets <form>, one of multiplicative, 759 additive, full, kaskade 760 761 Level: advanced 762 763 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid 764 765 .seealso: PCMGSetLevels() 766 @*/ 767 PetscErrorCode PCMGSetType(PC pc,PCMGType form) 768 { 769 PC_MG *mg = (PC_MG*)pc->data; 770 771 PetscFunctionBegin; 772 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 773 PetscValidLogicalCollectiveEnum(pc,form,2); 774 mg->am = form; 775 if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG; 776 else pc->ops->applyrichardson = 0; 777 PetscFunctionReturn(0); 778 } 779 780 #undef __FUNCT__ 781 #define __FUNCT__ "PCMGSetCycleType" 782 /*@ 783 PCMGSetCycleType - Sets the type cycles to use. Use PCMGSetCycleTypeOnLevel() for more 784 complicated cycling. 785 786 Logically Collective on PC 787 788 Input Parameters: 789 + pc - the multigrid context 790 - PC_MG_CYCLE_V or PC_MG_CYCLE_W 791 792 Options Database Key: 793 $ -pc_mg_cycle_type v or w 794 795 Level: advanced 796 797 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid 798 799 .seealso: PCMGSetCycleTypeOnLevel() 800 @*/ 801 PetscErrorCode PCMGSetCycleType(PC pc,PCMGCycleType n) 802 { 803 PC_MG *mg = (PC_MG*)pc->data; 804 PC_MG_Levels **mglevels = mg->levels; 805 PetscInt i,levels; 806 807 PetscFunctionBegin; 808 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 809 if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 810 PetscValidLogicalCollectiveInt(pc,n,2); 811 levels = mglevels[0]->levels; 812 813 for (i=0; i<levels; i++) { 814 mglevels[i]->cycles = n; 815 } 816 PetscFunctionReturn(0); 817 } 818 819 #undef __FUNCT__ 820 #define __FUNCT__ "PCMGMultiplicativeSetCycles" 821 /*@ 822 PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step 823 of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used 824 825 Logically Collective on PC 826 827 Input Parameters: 828 + pc - the multigrid context 829 - n - number of cycles (default is 1) 830 831 Options Database Key: 832 $ -pc_mg_multiplicative_cycles n 833 834 Level: advanced 835 836 Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType() 837 838 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid 839 840 .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType() 841 @*/ 842 PetscErrorCode PCMGMultiplicativeSetCycles(PC pc,PetscInt n) 843 { 844 PC_MG *mg = (PC_MG*)pc->data; 845 PC_MG_Levels **mglevels = mg->levels; 846 PetscInt i,levels; 847 848 PetscFunctionBegin; 849 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 850 if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 851 PetscValidLogicalCollectiveInt(pc,n,2); 852 levels = mglevels[0]->levels; 853 854 for (i=0; i<levels; i++) { 855 mg->cyclesperpcapply = n; 856 } 857 PetscFunctionReturn(0); 858 } 859 860 #undef __FUNCT__ 861 #define __FUNCT__ "PCMGSetGalerkin" 862 /*@ 863 PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the 864 finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t 865 866 Logically Collective on PC 867 868 Input Parameters: 869 + pc - the multigrid context 870 - use - PETSC_TRUE to use the Galerkin process to compute coarse-level operators 871 872 Options Database Key: 873 $ -pc_mg_galerkin 874 875 Level: intermediate 876 877 .keywords: MG, set, Galerkin 878 879 .seealso: PCMGGetGalerkin() 880 881 @*/ 882 PetscErrorCode PCMGSetGalerkin(PC pc,PetscBool use) 883 { 884 PC_MG *mg = (PC_MG*)pc->data; 885 886 PetscFunctionBegin; 887 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 888 mg->galerkin = (PetscInt)use; 889 PetscFunctionReturn(0); 890 } 891 892 #undef __FUNCT__ 893 #define __FUNCT__ "PCMGGetGalerkin" 894 /*@ 895 PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e. 896 A_i-1 = r_i * A_i * r_i^t 897 898 Not Collective 899 900 Input Parameter: 901 . pc - the multigrid context 902 903 Output Parameter: 904 . gelerkin - PETSC_TRUE or PETSC_FALSE 905 906 Options Database Key: 907 $ -pc_mg_galerkin 908 909 Level: intermediate 910 911 .keywords: MG, set, Galerkin 912 913 .seealso: PCMGSetGalerkin() 914 915 @*/ 916 PetscErrorCode PCMGGetGalerkin(PC pc,PetscBool *galerkin) 917 { 918 PC_MG *mg = (PC_MG*)pc->data; 919 920 PetscFunctionBegin; 921 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 922 *galerkin = (PetscBool)mg->galerkin; 923 PetscFunctionReturn(0); 924 } 925 926 #undef __FUNCT__ 927 #define __FUNCT__ "PCMGSetNumberSmoothDown" 928 /*@ 929 PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to 930 use on all levels. Use PCMGGetSmootherDown() to set different 931 pre-smoothing steps on different levels. 932 933 Logically Collective on PC 934 935 Input Parameters: 936 + mg - the multigrid context 937 - n - the number of smoothing steps 938 939 Options Database Key: 940 . -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps 941 942 Level: advanced 943 944 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid 945 946 .seealso: PCMGSetNumberSmoothUp() 947 @*/ 948 PetscErrorCode PCMGSetNumberSmoothDown(PC pc,PetscInt n) 949 { 950 PC_MG *mg = (PC_MG*)pc->data; 951 PC_MG_Levels **mglevels = mg->levels; 952 PetscErrorCode ierr; 953 PetscInt i,levels; 954 955 PetscFunctionBegin; 956 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 957 if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 958 PetscValidLogicalCollectiveInt(pc,n,2); 959 levels = mglevels[0]->levels; 960 961 for (i=1; i<levels; i++) { 962 /* make sure smoother up and down are different */ 963 ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr); 964 ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 965 mg->default_smoothd = n; 966 } 967 PetscFunctionReturn(0); 968 } 969 970 #undef __FUNCT__ 971 #define __FUNCT__ "PCMGSetNumberSmoothUp" 972 /*@ 973 PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use 974 on all levels. Use PCMGGetSmootherUp() to set different numbers of 975 post-smoothing steps on different levels. 976 977 Logically Collective on PC 978 979 Input Parameters: 980 + mg - the multigrid context 981 - n - the number of smoothing steps 982 983 Options Database Key: 984 . -pc_mg_smoothup <n> - Sets number of post-smoothing steps 985 986 Level: advanced 987 988 Note: this does not set a value on the coarsest grid, since we assume that 989 there is no separate smooth up on the coarsest grid. 990 991 .keywords: MG, smooth, up, post-smoothing, steps, multigrid 992 993 .seealso: PCMGSetNumberSmoothDown() 994 @*/ 995 PetscErrorCode PCMGSetNumberSmoothUp(PC pc,PetscInt n) 996 { 997 PC_MG *mg = (PC_MG*)pc->data; 998 PC_MG_Levels **mglevels = mg->levels; 999 PetscErrorCode ierr; 1000 PetscInt i,levels; 1001 1002 PetscFunctionBegin; 1003 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1004 if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 1005 PetscValidLogicalCollectiveInt(pc,n,2); 1006 levels = mglevels[0]->levels; 1007 1008 for (i=1; i<levels; i++) { 1009 /* make sure smoother up and down are different */ 1010 ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr); 1011 ierr = KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 1012 mg->default_smoothu = n; 1013 } 1014 PetscFunctionReturn(0); 1015 } 1016 1017 /* ----------------------------------------------------------------------------------------*/ 1018 1019 /*MC 1020 PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional 1021 information about the coarser grid matrices and restriction/interpolation operators. 1022 1023 Options Database Keys: 1024 + -pc_mg_levels <nlevels> - number of levels including finest 1025 . -pc_mg_cycles v or w 1026 . -pc_mg_smoothup <n> - number of smoothing steps after interpolation 1027 . -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator 1028 . -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default 1029 . -pc_mg_log - log information about time spent on each level of the solver 1030 . -pc_mg_monitor - print information on the multigrid convergence 1031 . -pc_mg_galerkin - use Galerkin process to compute coarser operators 1032 - -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices 1033 to the Socket viewer for reading from MATLAB. 1034 1035 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 1036 1037 Level: intermediate 1038 1039 Concepts: multigrid/multilevel 1040 1041 .seealso: PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC 1042 PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(), 1043 PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(), 1044 PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(), 1045 PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR() 1046 M*/ 1047 1048 EXTERN_C_BEGIN 1049 #undef __FUNCT__ 1050 #define __FUNCT__ "PCCreate_MG" 1051 PetscErrorCode PCCreate_MG(PC pc) 1052 { 1053 PC_MG *mg; 1054 PetscErrorCode ierr; 1055 1056 PetscFunctionBegin; 1057 ierr = PetscNewLog(pc,PC_MG,&mg);CHKERRQ(ierr); 1058 pc->data = (void*)mg; 1059 mg->nlevels = -1; 1060 1061 pc->ops->apply = PCApply_MG; 1062 pc->ops->setup = PCSetUp_MG; 1063 pc->ops->reset = PCReset_MG; 1064 pc->ops->destroy = PCDestroy_MG; 1065 pc->ops->setfromoptions = PCSetFromOptions_MG; 1066 pc->ops->view = PCView_MG; 1067 PetscFunctionReturn(0); 1068 } 1069 EXTERN_C_END 1070