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 /* Skipping this for galerkin==2 (externally managed hierarchy such as ML and GAMG). Cleaner logic here would be great. */ 509 if (pc->dm && mg->galerkin != 2 && !pc->setupcalled) { 510 /* construct the interpolation from the DMs */ 511 Mat p; 512 Vec rscale; 513 ierr = PetscMalloc(n*sizeof(DM),&dms);CHKERRQ(ierr); 514 dms[n-1] = pc->dm; 515 for (i=n-2; i>-1; i--) { 516 KSPDM kdm; 517 ierr = DMCoarsen(dms[i+1],PETSC_NULL,&dms[i]);CHKERRQ(ierr); 518 ierr = KSPSetDM(mglevels[i]->smoothd,dms[i]);CHKERRQ(ierr); 519 if (mg->galerkin) {ierr = KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);CHKERRQ(ierr);} 520 ierr = DMKSPGetContextWrite(dms[i],&kdm);CHKERRQ(ierr); 521 /* Ugly hack so that the next KSPSetUp() will use the RHS that we set */ 522 kdm->computerhs = PETSC_NULL; 523 kdm->rhsctx = PETSC_NULL; 524 ierr = DMSetFunction(dms[i],0); 525 ierr = DMSetInitialGuess(dms[i],0); 526 if (!mglevels[i+1]->interpolate) { 527 ierr = DMCreateInterpolation(dms[i],dms[i+1],&p,&rscale);CHKERRQ(ierr); 528 ierr = PCMGSetInterpolation(pc,i+1,p);CHKERRQ(ierr); 529 if (rscale) {ierr = PCMGSetRScale(pc,i+1,rscale);CHKERRQ(ierr);} 530 ierr = VecDestroy(&rscale);CHKERRQ(ierr); 531 ierr = MatDestroy(&p);CHKERRQ(ierr); 532 } 533 } 534 535 for (i=n-2; i>-1; i--) { 536 ierr = DMDestroy(&dms[i]);CHKERRQ(ierr); 537 } 538 ierr = PetscFree(dms);CHKERRQ(ierr); 539 } 540 541 if (pc->dm && !pc->setupcalled) { 542 /* finest smoother also gets DM but it is not active, independent of whether galerkin==2 */ 543 ierr = KSPSetDM(mglevels[n-1]->smoothd,pc->dm);CHKERRQ(ierr); 544 ierr = KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);CHKERRQ(ierr); 545 } 546 547 if (mg->galerkin == 1) { 548 Mat B; 549 /* currently only handle case where mat and pmat are the same on coarser levels */ 550 ierr = KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr); 551 if (!pc->setupcalled) { 552 for (i=n-2; i>-1; i--) { 553 ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr); 554 ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr); 555 if (i != n-2) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);} 556 dB = B; 557 } 558 if (n > 1) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);} 559 } else { 560 for (i=n-2; i>-1; i--) { 561 ierr = KSPGetOperators(mglevels[i]->smoothd,PETSC_NULL,&B,PETSC_NULL);CHKERRQ(ierr); 562 ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr); 563 ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr); 564 dB = B; 565 } 566 } 567 } else if (!mg->galerkin && pc->dm && pc->dm->x) { 568 /* need to restrict Jacobian location to coarser meshes for evaluation */ 569 for (i=n-2;i>-1; i--) { 570 Mat R; 571 Vec rscale; 572 if (!mglevels[i]->smoothd->dm->x) { 573 Vec *vecs; 574 ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vecs,0,PETSC_NULL);CHKERRQ(ierr); 575 mglevels[i]->smoothd->dm->x = vecs[0]; 576 ierr = PetscFree(vecs);CHKERRQ(ierr); 577 } 578 ierr = PCMGGetRestriction(pc,i+1,&R);CHKERRQ(ierr); 579 ierr = PCMGGetRScale(pc,i+1,&rscale);CHKERRQ(ierr); 580 ierr = MatRestrict(R,mglevels[i+1]->smoothd->dm->x,mglevels[i]->smoothd->dm->x);CHKERRQ(ierr); 581 ierr = VecPointwiseMult(mglevels[i]->smoothd->dm->x,mglevels[i]->smoothd->dm->x,rscale);CHKERRQ(ierr); 582 } 583 } 584 if (!mg->galerkin) { 585 for (i=n-2;i>=0; i--) { 586 DM dmfine = mglevels[i+1]->smoothd->dm; 587 DM dmcoarse = mglevels[i]->smoothd->dm; 588 Mat Restrict,Inject; 589 Vec rscale; 590 ierr = PCMGGetRestriction(pc,i+1,&Restrict);CHKERRQ(ierr); 591 ierr = PCMGGetRScale(pc,i+1,&rscale);CHKERRQ(ierr); 592 Inject = PETSC_NULL; /* Callback should create it if it needs Injection */ 593 ierr = DMRestrict(dmfine,Restrict,rscale,Inject,dmcoarse);CHKERRQ(ierr); 594 } 595 } 596 597 if (!pc->setupcalled) { 598 for (i=0; i<n; i++) { 599 ierr = KSPSetFromOptions(mglevels[i]->smoothd);CHKERRQ(ierr); 600 } 601 for (i=1; i<n; i++) { 602 if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) { 603 ierr = KSPSetFromOptions(mglevels[i]->smoothu);CHKERRQ(ierr); 604 } 605 } 606 for (i=1; i<n; i++) { 607 ierr = PCMGGetInterpolation(pc,i,&mglevels[i]->interpolate);CHKERRQ(ierr); 608 ierr = PCMGGetRestriction(pc,i,&mglevels[i]->restrct);CHKERRQ(ierr); 609 } 610 for (i=0; i<n-1; i++) { 611 if (!mglevels[i]->b) { 612 Vec *vec; 613 ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr); 614 ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr); 615 ierr = VecDestroy(vec);CHKERRQ(ierr); 616 ierr = PetscFree(vec);CHKERRQ(ierr); 617 } 618 if (!mglevels[i]->r && i) { 619 ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr); 620 ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr); 621 ierr = VecDestroy(&tvec);CHKERRQ(ierr); 622 } 623 if (!mglevels[i]->x) { 624 ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr); 625 ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr); 626 ierr = VecDestroy(&tvec);CHKERRQ(ierr); 627 } 628 } 629 if (n != 1 && !mglevels[n-1]->r) { 630 /* PCMGSetR() on the finest level if user did not supply it */ 631 Vec *vec; 632 ierr = KSPGetVecs(mglevels[n-1]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr); 633 ierr = PCMGSetR(pc,n-1,*vec);CHKERRQ(ierr); 634 ierr = VecDestroy(vec);CHKERRQ(ierr); 635 ierr = PetscFree(vec);CHKERRQ(ierr); 636 } 637 } 638 639 640 for (i=1; i<n; i++) { 641 if (mglevels[i]->smoothu == mglevels[i]->smoothd) { 642 /* if doing only down then initial guess is zero */ 643 ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr); 644 } 645 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 646 ierr = KSPSetUp(mglevels[i]->smoothd);CHKERRQ(ierr); 647 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 648 if (!mglevels[i]->residual) { 649 Mat mat; 650 ierr = KSPGetOperators(mglevels[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);CHKERRQ(ierr); 651 ierr = PCMGSetResidual(pc,i,PCMGDefaultResidual,mat);CHKERRQ(ierr); 652 } 653 } 654 for (i=1; i<n; i++) { 655 if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) { 656 Mat downmat,downpmat; 657 MatStructure matflag; 658 PetscBool opsset; 659 660 /* check if operators have been set for up, if not use down operators to set them */ 661 ierr = KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,PETSC_NULL);CHKERRQ(ierr); 662 if (!opsset) { 663 ierr = KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat,&matflag);CHKERRQ(ierr); 664 ierr = KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr); 665 } 666 667 ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr); 668 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 669 ierr = KSPSetUp(mglevels[i]->smoothu);CHKERRQ(ierr); 670 if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 671 } 672 } 673 674 /* 675 If coarse solver is not direct method then DO NOT USE preonly 676 */ 677 ierr = PetscTypeCompare((PetscObject)mglevels[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr); 678 if (preonly) { 679 ierr = PetscTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr); 680 ierr = PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr); 681 ierr = PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr); 682 ierr = PetscTypeCompare((PetscObject)cpc,PCSVD,&svd);CHKERRQ(ierr); 683 if (!lu && !redundant && !cholesky && !svd) { 684 ierr = KSPSetType(mglevels[0]->smoothd,KSPGMRES);CHKERRQ(ierr); 685 } 686 } 687 688 if (!pc->setupcalled) { 689 ierr = KSPSetFromOptions(mglevels[0]->smoothd);CHKERRQ(ierr); 690 } 691 692 if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 693 ierr = KSPSetUp(mglevels[0]->smoothd);CHKERRQ(ierr); 694 if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 695 696 /* 697 Dump the interpolation/restriction matrices plus the 698 Jacobian/stiffness on each level. This allows MATLAB users to 699 easily check if the Galerkin condition A_c = R A_f R^T is satisfied. 700 701 Only support one or the other at the same time. 702 */ 703 #if defined(PETSC_USE_SOCKET_VIEWER) 704 ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,PETSC_NULL);CHKERRQ(ierr); 705 if (dump) { 706 viewer = PETSC_VIEWER_SOCKET_(((PetscObject)pc)->comm); 707 } 708 dump = PETSC_FALSE; 709 #endif 710 ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,PETSC_NULL);CHKERRQ(ierr); 711 if (dump) { 712 viewer = PETSC_VIEWER_BINARY_(((PetscObject)pc)->comm); 713 } 714 715 if (viewer) { 716 for (i=1; i<n; i++) { 717 ierr = MatView(mglevels[i]->restrct,viewer);CHKERRQ(ierr); 718 } 719 for (i=0; i<n; i++) { 720 ierr = KSPGetPC(mglevels[i]->smoothd,&pc);CHKERRQ(ierr); 721 ierr = MatView(pc->mat,viewer);CHKERRQ(ierr); 722 } 723 } 724 PetscFunctionReturn(0); 725 } 726 727 /* -------------------------------------------------------------------------------------*/ 728 729 #undef __FUNCT__ 730 #define __FUNCT__ "PCMGGetLevels" 731 /*@ 732 PCMGGetLevels - Gets the number of levels to use with MG. 733 734 Not Collective 735 736 Input Parameter: 737 . pc - the preconditioner context 738 739 Output parameter: 740 . levels - the number of levels 741 742 Level: advanced 743 744 .keywords: MG, get, levels, multigrid 745 746 .seealso: PCMGSetLevels() 747 @*/ 748 PetscErrorCode PCMGGetLevels(PC pc,PetscInt *levels) 749 { 750 PC_MG *mg = (PC_MG*)pc->data; 751 752 PetscFunctionBegin; 753 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 754 PetscValidIntPointer(levels,2); 755 *levels = mg->nlevels; 756 PetscFunctionReturn(0); 757 } 758 759 #undef __FUNCT__ 760 #define __FUNCT__ "PCMGSetType" 761 /*@ 762 PCMGSetType - Determines the form of multigrid to use: 763 multiplicative, additive, full, or the Kaskade algorithm. 764 765 Logically Collective on PC 766 767 Input Parameters: 768 + pc - the preconditioner context 769 - form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE, 770 PC_MG_FULL, PC_MG_KASKADE 771 772 Options Database Key: 773 . -pc_mg_type <form> - Sets <form>, one of multiplicative, 774 additive, full, kaskade 775 776 Level: advanced 777 778 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid 779 780 .seealso: PCMGSetLevels() 781 @*/ 782 PetscErrorCode PCMGSetType(PC pc,PCMGType form) 783 { 784 PC_MG *mg = (PC_MG*)pc->data; 785 786 PetscFunctionBegin; 787 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 788 PetscValidLogicalCollectiveEnum(pc,form,2); 789 mg->am = form; 790 if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG; 791 else pc->ops->applyrichardson = 0; 792 PetscFunctionReturn(0); 793 } 794 795 #undef __FUNCT__ 796 #define __FUNCT__ "PCMGSetCycleType" 797 /*@ 798 PCMGSetCycleType - Sets the type cycles to use. Use PCMGSetCycleTypeOnLevel() for more 799 complicated cycling. 800 801 Logically Collective on PC 802 803 Input Parameters: 804 + pc - the multigrid context 805 - PC_MG_CYCLE_V or PC_MG_CYCLE_W 806 807 Options Database Key: 808 $ -pc_mg_cycle_type v or w 809 810 Level: advanced 811 812 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid 813 814 .seealso: PCMGSetCycleTypeOnLevel() 815 @*/ 816 PetscErrorCode PCMGSetCycleType(PC pc,PCMGCycleType n) 817 { 818 PC_MG *mg = (PC_MG*)pc->data; 819 PC_MG_Levels **mglevels = mg->levels; 820 PetscInt i,levels; 821 822 PetscFunctionBegin; 823 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 824 if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 825 PetscValidLogicalCollectiveInt(pc,n,2); 826 levels = mglevels[0]->levels; 827 828 for (i=0; i<levels; i++) { 829 mglevels[i]->cycles = n; 830 } 831 PetscFunctionReturn(0); 832 } 833 834 #undef __FUNCT__ 835 #define __FUNCT__ "PCMGMultiplicativeSetCycles" 836 /*@ 837 PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step 838 of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used 839 840 Logically Collective on PC 841 842 Input Parameters: 843 + pc - the multigrid context 844 - n - number of cycles (default is 1) 845 846 Options Database Key: 847 $ -pc_mg_multiplicative_cycles n 848 849 Level: advanced 850 851 Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType() 852 853 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid 854 855 .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType() 856 @*/ 857 PetscErrorCode PCMGMultiplicativeSetCycles(PC pc,PetscInt n) 858 { 859 PC_MG *mg = (PC_MG*)pc->data; 860 PC_MG_Levels **mglevels = mg->levels; 861 PetscInt i,levels; 862 863 PetscFunctionBegin; 864 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 865 if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 866 PetscValidLogicalCollectiveInt(pc,n,2); 867 levels = mglevels[0]->levels; 868 869 for (i=0; i<levels; i++) { 870 mg->cyclesperpcapply = n; 871 } 872 PetscFunctionReturn(0); 873 } 874 875 #undef __FUNCT__ 876 #define __FUNCT__ "PCMGSetGalerkin" 877 /*@ 878 PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the 879 finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t 880 881 Logically Collective on PC 882 883 Input Parameters: 884 + pc - the multigrid context 885 - use - PETSC_TRUE to use the Galerkin process to compute coarse-level operators 886 887 Options Database Key: 888 $ -pc_mg_galerkin 889 890 Level: intermediate 891 892 .keywords: MG, set, Galerkin 893 894 .seealso: PCMGGetGalerkin() 895 896 @*/ 897 PetscErrorCode PCMGSetGalerkin(PC pc,PetscBool use) 898 { 899 PC_MG *mg = (PC_MG*)pc->data; 900 901 PetscFunctionBegin; 902 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 903 mg->galerkin = (PetscInt)use; 904 PetscFunctionReturn(0); 905 } 906 907 #undef __FUNCT__ 908 #define __FUNCT__ "PCMGGetGalerkin" 909 /*@ 910 PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e. 911 A_i-1 = r_i * A_i * r_i^t 912 913 Not Collective 914 915 Input Parameter: 916 . pc - the multigrid context 917 918 Output Parameter: 919 . gelerkin - PETSC_TRUE or PETSC_FALSE 920 921 Options Database Key: 922 $ -pc_mg_galerkin 923 924 Level: intermediate 925 926 .keywords: MG, set, Galerkin 927 928 .seealso: PCMGSetGalerkin() 929 930 @*/ 931 PetscErrorCode PCMGGetGalerkin(PC pc,PetscBool *galerkin) 932 { 933 PC_MG *mg = (PC_MG*)pc->data; 934 935 PetscFunctionBegin; 936 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 937 *galerkin = (PetscBool)mg->galerkin; 938 PetscFunctionReturn(0); 939 } 940 941 #undef __FUNCT__ 942 #define __FUNCT__ "PCMGSetNumberSmoothDown" 943 /*@ 944 PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to 945 use on all levels. Use PCMGGetSmootherDown() to set different 946 pre-smoothing steps on different levels. 947 948 Logically Collective on PC 949 950 Input Parameters: 951 + mg - the multigrid context 952 - n - the number of smoothing steps 953 954 Options Database Key: 955 . -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps 956 957 Level: advanced 958 959 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid 960 961 .seealso: PCMGSetNumberSmoothUp() 962 @*/ 963 PetscErrorCode PCMGSetNumberSmoothDown(PC pc,PetscInt n) 964 { 965 PC_MG *mg = (PC_MG*)pc->data; 966 PC_MG_Levels **mglevels = mg->levels; 967 PetscErrorCode ierr; 968 PetscInt i,levels; 969 970 PetscFunctionBegin; 971 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 972 if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 973 PetscValidLogicalCollectiveInt(pc,n,2); 974 levels = mglevels[0]->levels; 975 976 for (i=1; i<levels; i++) { 977 /* make sure smoother up and down are different */ 978 ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr); 979 ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 980 mg->default_smoothd = n; 981 } 982 PetscFunctionReturn(0); 983 } 984 985 #undef __FUNCT__ 986 #define __FUNCT__ "PCMGSetNumberSmoothUp" 987 /*@ 988 PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use 989 on all levels. Use PCMGGetSmootherUp() to set different numbers of 990 post-smoothing steps on different levels. 991 992 Logically Collective on PC 993 994 Input Parameters: 995 + mg - the multigrid context 996 - n - the number of smoothing steps 997 998 Options Database Key: 999 . -pc_mg_smoothup <n> - Sets number of post-smoothing steps 1000 1001 Level: advanced 1002 1003 Note: this does not set a value on the coarsest grid, since we assume that 1004 there is no separate smooth up on the coarsest grid. 1005 1006 .keywords: MG, smooth, up, post-smoothing, steps, multigrid 1007 1008 .seealso: PCMGSetNumberSmoothDown() 1009 @*/ 1010 PetscErrorCode PCMGSetNumberSmoothUp(PC pc,PetscInt n) 1011 { 1012 PC_MG *mg = (PC_MG*)pc->data; 1013 PC_MG_Levels **mglevels = mg->levels; 1014 PetscErrorCode ierr; 1015 PetscInt i,levels; 1016 1017 PetscFunctionBegin; 1018 PetscValidHeaderSpecific(pc,PC_CLASSID,1); 1019 if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 1020 PetscValidLogicalCollectiveInt(pc,n,2); 1021 levels = mglevels[0]->levels; 1022 1023 for (i=1; i<levels; i++) { 1024 /* make sure smoother up and down are different */ 1025 ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr); 1026 ierr = KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 1027 mg->default_smoothu = n; 1028 } 1029 PetscFunctionReturn(0); 1030 } 1031 1032 /* ----------------------------------------------------------------------------------------*/ 1033 1034 /*MC 1035 PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional 1036 information about the coarser grid matrices and restriction/interpolation operators. 1037 1038 Options Database Keys: 1039 + -pc_mg_levels <nlevels> - number of levels including finest 1040 . -pc_mg_cycles v or w 1041 . -pc_mg_smoothup <n> - number of smoothing steps after interpolation 1042 . -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator 1043 . -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default 1044 . -pc_mg_log - log information about time spent on each level of the solver 1045 . -pc_mg_monitor - print information on the multigrid convergence 1046 . -pc_mg_galerkin - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R' 1047 . -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1) 1048 . -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices 1049 to the Socket viewer for reading from MATLAB. 1050 - -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices 1051 to the binary output file called binaryoutput 1052 1053 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 1054 1055 When run with a single level the smoother options are used on that level NOT the coarse grid solver options 1056 1057 Level: intermediate 1058 1059 Concepts: multigrid/multilevel 1060 1061 .seealso: PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE 1062 PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(), 1063 PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(), 1064 PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(), 1065 PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR() 1066 M*/ 1067 1068 EXTERN_C_BEGIN 1069 #undef __FUNCT__ 1070 #define __FUNCT__ "PCCreate_MG" 1071 PetscErrorCode PCCreate_MG(PC pc) 1072 { 1073 PC_MG *mg; 1074 PetscErrorCode ierr; 1075 1076 PetscFunctionBegin; 1077 ierr = PetscNewLog(pc,PC_MG,&mg);CHKERRQ(ierr); 1078 pc->data = (void*)mg; 1079 mg->nlevels = -1; 1080 1081 pc->ops->apply = PCApply_MG; 1082 pc->ops->setup = PCSetUp_MG; 1083 pc->ops->reset = PCReset_MG; 1084 pc->ops->destroy = PCDestroy_MG; 1085 pc->ops->setfromoptions = PCSetFromOptions_MG; 1086 pc->ops->view = PCView_MG; 1087 PetscFunctionReturn(0); 1088 } 1089 EXTERN_C_END 1090