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