Actual source code: mg.c

petsc-3.10.4 2019-02-26
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  2: /*
  3:     Defines the multigrid preconditioner interface.
  4: */
  5:  #include <petsc/private/pcmgimpl.h>
  6:  #include <petscdm.h>
  7: PETSC_INTERN PetscErrorCode PCPreSolveChangeRHS(PC,PetscBool*);

  9: PetscErrorCode PCMGMCycle_Private(PC pc,PC_MG_Levels **mglevelsin,PCRichardsonConvergedReason *reason)
 10: {
 11:   PC_MG          *mg = (PC_MG*)pc->data;
 12:   PC_MG_Levels   *mgc,*mglevels = *mglevelsin;
 14:   PetscInt       cycles = (mglevels->level == 1) ? 1 : (PetscInt) mglevels->cycles;
 15:   PC             subpc;
 16:   PCFailedReason pcreason;

 19:   if (mglevels->eventsmoothsolve) {PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);}
 20:   KSPSolve(mglevels->smoothd,mglevels->b,mglevels->x);  /* pre-smooth */
 21:   KSPGetPC(mglevels->smoothd,&subpc);
 22:   PCGetSetUpFailedReason(subpc,&pcreason);
 23:   if (pcreason) {
 24:     pc->failedreason = PC_SUBPC_ERROR;
 25:   }
 26:   if (mglevels->eventsmoothsolve) {PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);}
 27:   if (mglevels->level) {  /* not the coarsest grid */
 28:     if (mglevels->eventresidual) {PetscLogEventBegin(mglevels->eventresidual,0,0,0,0);}
 29:     (*mglevels->residual)(mglevels->A,mglevels->b,mglevels->x,mglevels->r);
 30:     if (mglevels->eventresidual) {PetscLogEventEnd(mglevels->eventresidual,0,0,0,0);}

 32:     /* if on finest level and have convergence criteria set */
 33:     if (mglevels->level == mglevels->levels-1 && mg->ttol && reason) {
 34:       PetscReal rnorm;
 35:       VecNorm(mglevels->r,NORM_2,&rnorm);
 36:       if (rnorm <= mg->ttol) {
 37:         if (rnorm < mg->abstol) {
 38:           *reason = PCRICHARDSON_CONVERGED_ATOL;
 39:           PetscInfo2(pc,"Linear solver has converged. Residual norm %g is less than absolute tolerance %g\n",(double)rnorm,(double)mg->abstol);
 40:         } else {
 41:           *reason = PCRICHARDSON_CONVERGED_RTOL;
 42:           PetscInfo2(pc,"Linear solver has converged. Residual norm %g is less than relative tolerance times initial residual norm %g\n",(double)rnorm,(double)mg->ttol);
 43:         }
 44:         return(0);
 45:       }
 46:     }

 48:     mgc = *(mglevelsin - 1);
 49:     if (mglevels->eventinterprestrict) {PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);}
 50:     MatRestrict(mglevels->restrct,mglevels->r,mgc->b);
 51:     if (mglevels->eventinterprestrict) {PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);}
 52:     VecSet(mgc->x,0.0);
 53:     while (cycles--) {
 54:       PCMGMCycle_Private(pc,mglevelsin-1,reason);
 55:     }
 56:     if (mglevels->eventinterprestrict) {PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);}
 57:     MatInterpolateAdd(mglevels->interpolate,mgc->x,mglevels->x,mglevels->x);
 58:     if (mglevels->eventinterprestrict) {PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);}
 59:     if (mglevels->eventsmoothsolve) {PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);}
 60:     KSPSolve(mglevels->smoothu,mglevels->b,mglevels->x);    /* post smooth */
 61:     if (mglevels->eventsmoothsolve) {PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);}
 62:   }
 63:   return(0);
 64: }

 66: 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)
 67: {
 68:   PC_MG          *mg        = (PC_MG*)pc->data;
 69:   PC_MG_Levels   **mglevels = mg->levels;
 71:   PC             tpc;
 72:   PetscBool      changeu,changed;
 73:   PetscInt       levels = mglevels[0]->levels,i;

 76:   /* When the DM is supplying the matrix then it will not exist until here */
 77:   for (i=0; i<levels; i++) {
 78:     if (!mglevels[i]->A) {
 79:       KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);
 80:       PetscObjectReference((PetscObject)mglevels[i]->A);
 81:     }
 82:   }

 84:   KSPGetPC(mglevels[levels-1]->smoothd,&tpc);
 85:   PCPreSolveChangeRHS(tpc,&changed);
 86:   KSPGetPC(mglevels[levels-1]->smoothu,&tpc);
 87:   PCPreSolveChangeRHS(tpc,&changeu);
 88:   if (!changed && !changeu) {
 89:     VecDestroy(&mglevels[levels-1]->b);
 90:     mglevels[levels-1]->b = b;
 91:   } else { /* if the smoother changes the rhs during PreSolve, we cannot use the input vector */
 92:     if (!mglevels[levels-1]->b) {
 93:       Vec *vec;

 95:       KSPCreateVecs(mglevels[levels-1]->smoothd,1,&vec,0,NULL);
 96:       mglevels[levels-1]->b = *vec;
 97:       PetscFree(vec);
 98:     }
 99:     VecCopy(b,mglevels[levels-1]->b);
100:   }
101:   mglevels[levels-1]->x = x;

103:   mg->rtol   = rtol;
104:   mg->abstol = abstol;
105:   mg->dtol   = dtol;
106:   if (rtol) {
107:     /* compute initial residual norm for relative convergence test */
108:     PetscReal rnorm;
109:     if (zeroguess) {
110:       VecNorm(b,NORM_2,&rnorm);
111:     } else {
112:       (*mglevels[levels-1]->residual)(mglevels[levels-1]->A,b,x,w);
113:       VecNorm(w,NORM_2,&rnorm);
114:     }
115:     mg->ttol = PetscMax(rtol*rnorm,abstol);
116:   } else if (abstol) mg->ttol = abstol;
117:   else mg->ttol = 0.0;

119:   /* since smoother is applied to full system, not just residual we need to make sure that smoothers don't
120:      stop prematurely due to small residual */
121:   for (i=1; i<levels; i++) {
122:     KSPSetTolerances(mglevels[i]->smoothu,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);
123:     if (mglevels[i]->smoothu != mglevels[i]->smoothd) {
124:       /* For Richardson the initial guess is nonzero since it is solving in each cycle the original system not just applying as a preconditioner */
125:       KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);
126:       KSPSetTolerances(mglevels[i]->smoothd,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);
127:     }
128:   }

130:   *reason = (PCRichardsonConvergedReason)0;
131:   for (i=0; i<its; i++) {
132:     PCMGMCycle_Private(pc,mglevels+levels-1,reason);
133:     if (*reason) break;
134:   }
135:   if (!*reason) *reason = PCRICHARDSON_CONVERGED_ITS;
136:   *outits = i;
137:   if (!changed && !changeu) mglevels[levels-1]->b = NULL;
138:   return(0);
139: }

141: PetscErrorCode PCReset_MG(PC pc)
142: {
143:   PC_MG          *mg        = (PC_MG*)pc->data;
144:   PC_MG_Levels   **mglevels = mg->levels;
146:   PetscInt       i,n;

149:   if (mglevels) {
150:     n = mglevels[0]->levels;
151:     for (i=0; i<n-1; i++) {
152:       VecDestroy(&mglevels[i+1]->r);
153:       VecDestroy(&mglevels[i]->b);
154:       VecDestroy(&mglevels[i]->x);
155:       MatDestroy(&mglevels[i+1]->restrct);
156:       MatDestroy(&mglevels[i+1]->interpolate);
157:       MatDestroy(&mglevels[i+1]->inject);
158:       VecDestroy(&mglevels[i+1]->rscale);
159:     }
160:     /* this is not null only if the smoother on the finest level
161:        changes the rhs during PreSolve */
162:     VecDestroy(&mglevels[n-1]->b);

164:     for (i=0; i<n; i++) {
165:       MatDestroy(&mglevels[i]->A);
166:       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
167:         KSPReset(mglevels[i]->smoothd);
168:       }
169:       KSPReset(mglevels[i]->smoothu);
170:     }
171:   }
172:   return(0);
173: }

175: /*@C
176:    PCMGSetLevels - Sets the number of levels to use with MG.
177:    Must be called before any other MG routine.

179:    Logically Collective on PC

181:    Input Parameters:
182: +  pc - the preconditioner context
183: .  levels - the number of levels
184: -  comms - optional communicators for each level; this is to allow solving the coarser problems
185:            on smaller sets of processors.

187:    Level: intermediate

189:    Notes:
190:      If the number of levels is one then the multigrid uses the -mg_levels prefix
191:   for setting the level options rather than the -mg_coarse prefix.

193: .keywords: MG, set, levels, multigrid

195: .seealso: PCMGSetType(), PCMGGetLevels()
196: @*/
197: PetscErrorCode  PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
198: {
200:   PC_MG          *mg        = (PC_MG*)pc->data;
201:   MPI_Comm       comm;
202:   PC_MG_Levels   **mglevels = mg->levels;
203:   PCMGType       mgtype     = mg->am;
204:   PetscInt       mgctype    = (PetscInt) PC_MG_CYCLE_V;
205:   PetscInt       i;
206:   PetscMPIInt    size;
207:   const char     *prefix;
208:   PC             ipc;
209:   PetscInt       n;

214:   if (mg->nlevels == levels) return(0);
215:   PetscObjectGetComm((PetscObject)pc,&comm);
216:   if (mglevels) {
217:     mgctype = mglevels[0]->cycles;
218:     /* changing the number of levels so free up the previous stuff */
219:     PCReset_MG(pc);
220:     n    = mglevels[0]->levels;
221:     for (i=0; i<n; i++) {
222:       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
223:         KSPDestroy(&mglevels[i]->smoothd);
224:       }
225:       KSPDestroy(&mglevels[i]->smoothu);
226:       PetscFree(mglevels[i]);
227:     }
228:     PetscFree(mg->levels);
229:   }

231:   mg->nlevels = levels;

233:   PetscMalloc1(levels,&mglevels);
234:   PetscLogObjectMemory((PetscObject)pc,levels*(sizeof(PC_MG*)));

236:   PCGetOptionsPrefix(pc,&prefix);

238:   mg->stageApply = 0;
239:   for (i=0; i<levels; i++) {
240:     PetscNewLog(pc,&mglevels[i]);

242:     mglevels[i]->level               = i;
243:     mglevels[i]->levels              = levels;
244:     mglevels[i]->cycles              = mgctype;
245:     mg->default_smoothu              = 2;
246:     mg->default_smoothd              = 2;
247:     mglevels[i]->eventsmoothsetup    = 0;
248:     mglevels[i]->eventsmoothsolve    = 0;
249:     mglevels[i]->eventresidual       = 0;
250:     mglevels[i]->eventinterprestrict = 0;

252:     if (comms) comm = comms[i];
253:     KSPCreate(comm,&mglevels[i]->smoothd);
254:     KSPSetErrorIfNotConverged(mglevels[i]->smoothd,pc->erroriffailure);
255:     PetscObjectIncrementTabLevel((PetscObject)mglevels[i]->smoothd,(PetscObject)pc,levels-i);
256:     KSPSetOptionsPrefix(mglevels[i]->smoothd,prefix);
257:     PetscObjectComposedDataSetInt((PetscObject) mglevels[i]->smoothd, PetscMGLevelId, mglevels[i]->level);
258:     if (i || levels == 1) {
259:       char tprefix[128];

261:       KSPSetType(mglevels[i]->smoothd,KSPCHEBYSHEV);
262:       KSPSetConvergenceTest(mglevels[i]->smoothd,KSPConvergedSkip,NULL,NULL);
263:       KSPSetNormType(mglevels[i]->smoothd,KSP_NORM_NONE);
264:       KSPGetPC(mglevels[i]->smoothd,&ipc);
265:       PCSetType(ipc,PCSOR);
266:       KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, mg->default_smoothd);

268:       sprintf(tprefix,"mg_levels_%d_",(int)i);
269:       KSPAppendOptionsPrefix(mglevels[i]->smoothd,tprefix);
270:     } else {
271:       KSPAppendOptionsPrefix(mglevels[0]->smoothd,"mg_coarse_");

273:       /* coarse solve is (redundant) LU by default; set shifttype NONZERO to avoid annoying zero-pivot in LU preconditioner */
274:       KSPSetType(mglevels[0]->smoothd,KSPPREONLY);
275:       KSPGetPC(mglevels[0]->smoothd,&ipc);
276:       MPI_Comm_size(comm,&size);
277:       if (size > 1) {
278:         PCSetType(ipc,PCREDUNDANT);
279:       } else {
280:         PCSetType(ipc,PCLU);
281:       }
282:       PCFactorSetShiftType(ipc,MAT_SHIFT_INBLOCKS);
283:     }
284:     PetscLogObjectParent((PetscObject)pc,(PetscObject)mglevels[i]->smoothd);

286:     mglevels[i]->smoothu = mglevels[i]->smoothd;
287:     mg->rtol             = 0.0;
288:     mg->abstol           = 0.0;
289:     mg->dtol             = 0.0;
290:     mg->ttol             = 0.0;
291:     mg->cyclesperpcapply = 1;
292:   }
293:   mg->levels = mglevels;
294:   PCMGSetType(pc,mgtype);
295:   return(0);
296: }


299: PetscErrorCode PCDestroy_MG(PC pc)
300: {
302:   PC_MG          *mg        = (PC_MG*)pc->data;
303:   PC_MG_Levels   **mglevels = mg->levels;
304:   PetscInt       i,n;

307:   PCReset_MG(pc);
308:   if (mglevels) {
309:     n = mglevels[0]->levels;
310:     for (i=0; i<n; i++) {
311:       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
312:         KSPDestroy(&mglevels[i]->smoothd);
313:       }
314:       KSPDestroy(&mglevels[i]->smoothu);
315:       PetscFree(mglevels[i]);
316:     }
317:     PetscFree(mg->levels);
318:   }
319:   PetscFree(pc->data);
320:   return(0);
321: }



325: extern PetscErrorCode PCMGACycle_Private(PC,PC_MG_Levels**);
326: extern PetscErrorCode PCMGFCycle_Private(PC,PC_MG_Levels**);
327: extern PetscErrorCode PCMGKCycle_Private(PC,PC_MG_Levels**);

329: /*
330:    PCApply_MG - Runs either an additive, multiplicative, Kaskadic
331:              or full cycle of multigrid.

333:   Note:
334:   A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle().
335: */
336: static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
337: {
338:   PC_MG          *mg        = (PC_MG*)pc->data;
339:   PC_MG_Levels   **mglevels = mg->levels;
341:   PC             tpc;
342:   PetscInt       levels = mglevels[0]->levels,i;
343:   PetscBool      changeu,changed;

346:   if (mg->stageApply) {PetscLogStagePush(mg->stageApply);}
347:   /* When the DM is supplying the matrix then it will not exist until here */
348:   for (i=0; i<levels; i++) {
349:     if (!mglevels[i]->A) {
350:       KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);
351:       PetscObjectReference((PetscObject)mglevels[i]->A);
352:     }
353:   }

355:   KSPGetPC(mglevels[levels-1]->smoothd,&tpc);
356:   PCPreSolveChangeRHS(tpc,&changed);
357:   KSPGetPC(mglevels[levels-1]->smoothu,&tpc);
358:   PCPreSolveChangeRHS(tpc,&changeu);
359:   if (!changeu && !changed) {
360:     VecDestroy(&mglevels[levels-1]->b);
361:     mglevels[levels-1]->b = b;
362:   } else { /* if the smoother changes the rhs during PreSolve, we cannot use the input vector */
363:     if (!mglevels[levels-1]->b) {
364:       Vec *vec;

366:       KSPCreateVecs(mglevels[levels-1]->smoothd,1,&vec,0,NULL);
367:       mglevels[levels-1]->b = *vec;
368:       PetscFree(vec);
369:     }
370:     VecCopy(b,mglevels[levels-1]->b);
371:   }
372:   mglevels[levels-1]->x = x;

374:   if (mg->am == PC_MG_MULTIPLICATIVE) {
375:     VecSet(x,0.0);
376:     for (i=0; i<mg->cyclesperpcapply; i++) {
377:       PCMGMCycle_Private(pc,mglevels+levels-1,NULL);
378:     }
379:   } else if (mg->am == PC_MG_ADDITIVE) {
380:     PCMGACycle_Private(pc,mglevels);
381:   } else if (mg->am == PC_MG_KASKADE) {
382:     PCMGKCycle_Private(pc,mglevels);
383:   } else {
384:     PCMGFCycle_Private(pc,mglevels);
385:   }
386:   if (mg->stageApply) {PetscLogStagePop();}
387:   if (!changeu && !changed) mglevels[levels-1]->b = NULL;
388:   return(0);
389: }


392: PetscErrorCode PCSetFromOptions_MG(PetscOptionItems *PetscOptionsObject,PC pc)
393: {
394:   PetscErrorCode   ierr;
395:   PetscInt         levels,cycles;
396:   PetscBool        flg;
397:   PC_MG            *mg = (PC_MG*)pc->data;
398:   PC_MG_Levels     **mglevels;
399:   PCMGType         mgtype;
400:   PCMGCycleType    mgctype;
401:   PCMGGalerkinType gtype;

404:   levels = PetscMax(mg->nlevels,1);
405:   PetscOptionsHead(PetscOptionsObject,"Multigrid options");
406:   PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);
407:   if (!flg && !mg->levels && pc->dm) {
408:     DMGetRefineLevel(pc->dm,&levels);
409:     levels++;
410:     mg->usedmfornumberoflevels = PETSC_TRUE;
411:   }
412:   PCMGSetLevels(pc,levels,NULL);
413:   mglevels = mg->levels;

415:   mgctype = (PCMGCycleType) mglevels[0]->cycles;
416:   PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);
417:   if (flg) {
418:     PCMGSetCycleType(pc,mgctype);
419:   }
420:   gtype = mg->galerkin;
421:   PetscOptionsEnum("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",PCMGGalerkinTypes,(PetscEnum)gtype,(PetscEnum*)&gtype,&flg);
422:   if (flg) {
423:     PCMGSetGalerkin(pc,gtype);
424:   }
425:   flg = PETSC_FALSE;
426:   PetscOptionsBool("-pc_mg_distinct_smoothup","Create seperate smoothup KSP and append the prefix _up","PCMGSetDistinctSmoothUp",PETSC_FALSE,&flg,NULL);
427:   if (flg) {
428:     PCMGSetDistinctSmoothUp(pc);
429:   }
430:   mgtype = mg->am;
431:   PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);
432:   if (flg) {
433:     PCMGSetType(pc,mgtype);
434:   }
435:   if (mg->am == PC_MG_MULTIPLICATIVE) {
436:     PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGMultiplicativeSetCycles",mg->cyclesperpcapply,&cycles,&flg);
437:     if (flg) {
438:       PCMGMultiplicativeSetCycles(pc,cycles);
439:     }
440:   }
441:   flg  = PETSC_FALSE;
442:   PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,NULL);
443:   if (flg) {
444:     PetscInt i;
445:     char     eventname[128];

447:     levels = mglevels[0]->levels;
448:     for (i=0; i<levels; i++) {
449:       sprintf(eventname,"MGSetup Level %d",(int)i);
450:       PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);
451:       sprintf(eventname,"MGSmooth Level %d",(int)i);
452:       PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);
453:       if (i) {
454:         sprintf(eventname,"MGResid Level %d",(int)i);
455:         PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);
456:         sprintf(eventname,"MGInterp Level %d",(int)i);
457:         PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);
458:       }
459:     }

461: #if defined(PETSC_USE_LOG)
462:     {
463:       const char    *sname = "MG Apply";
464:       PetscStageLog stageLog;
465:       PetscInt      st;

467:       PetscLogGetStageLog(&stageLog);
468:       for (st = 0; st < stageLog->numStages; ++st) {
469:         PetscBool same;

471:         PetscStrcmp(stageLog->stageInfo[st].name, sname, &same);
472:         if (same) mg->stageApply = st;
473:       }
474:       if (!mg->stageApply) {
475:         PetscLogStageRegister(sname, &mg->stageApply);
476:       }
477:     }
478: #endif
479:   }
480:   PetscOptionsTail();
481:   return(0);
482: }

484: const char *const PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0};
485: const char *const PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",0};
486: const char *const PCMGGalerkinTypes[] = {"both","pmat","mat","none","external","PCMGGalerkinType","PC_MG_GALERKIN",0};

488:  #include <petscdraw.h>
489: PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
490: {
491:   PC_MG          *mg        = (PC_MG*)pc->data;
492:   PC_MG_Levels   **mglevels = mg->levels;
494:   PetscInt       levels = mglevels ? mglevels[0]->levels : 0,i;
495:   PetscBool      iascii,isbinary,isdraw;

498:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
499:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
500:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
501:   if (iascii) {
502:     const char *cyclename = levels ? (mglevels[0]->cycles == PC_MG_CYCLE_V ? "v" : "w") : "unknown";
503:     PetscViewerASCIIPrintf(viewer,"  type is %s, levels=%D cycles=%s\n", PCMGTypes[mg->am],levels,cyclename);
504:     if (mg->am == PC_MG_MULTIPLICATIVE) {
505:       PetscViewerASCIIPrintf(viewer,"    Cycles per PCApply=%d\n",mg->cyclesperpcapply);
506:     }
507:     if (mg->galerkin == PC_MG_GALERKIN_BOTH) {
508:       PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices\n");
509:     } else if (mg->galerkin == PC_MG_GALERKIN_PMAT) {
510:       PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices for pmat\n");
511:     } else if (mg->galerkin == PC_MG_GALERKIN_MAT) {
512:       PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices for mat\n");
513:     } else if (mg->galerkin == PC_MG_GALERKIN_EXTERNAL) {
514:       PetscViewerASCIIPrintf(viewer,"    Using externally compute Galerkin coarse grid matrices\n");
515:     } else {
516:       PetscViewerASCIIPrintf(viewer,"    Not using Galerkin computed coarse grid matrices\n");
517:     }
518:     if (mg->view){
519:       (*mg->view)(pc,viewer);
520:     }
521:     for (i=0; i<levels; i++) {
522:       if (!i) {
523:         PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level -------------------------------\n",i);
524:       } else {
525:         PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);
526:       }
527:       PetscViewerASCIIPushTab(viewer);
528:       KSPView(mglevels[i]->smoothd,viewer);
529:       PetscViewerASCIIPopTab(viewer);
530:       if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) {
531:         PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");
532:       } else if (i) {
533:         PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);
534:         PetscViewerASCIIPushTab(viewer);
535:         KSPView(mglevels[i]->smoothu,viewer);
536:         PetscViewerASCIIPopTab(viewer);
537:       }
538:     }
539:   } else if (isbinary) {
540:     for (i=levels-1; i>=0; i--) {
541:       KSPView(mglevels[i]->smoothd,viewer);
542:       if (i && mglevels[i]->smoothd != mglevels[i]->smoothu) {
543:         KSPView(mglevels[i]->smoothu,viewer);
544:       }
545:     }
546:   } else if (isdraw) {
547:     PetscDraw draw;
548:     PetscReal x,w,y,bottom,th;
549:     PetscViewerDrawGetDraw(viewer,0,&draw);
550:     PetscDrawGetCurrentPoint(draw,&x,&y);
551:     PetscDrawStringGetSize(draw,NULL,&th);
552:     bottom = y - th;
553:     for (i=levels-1; i>=0; i--) {
554:       if (!mglevels[i]->smoothu || (mglevels[i]->smoothu == mglevels[i]->smoothd)) {
555:         PetscDrawPushCurrentPoint(draw,x,bottom);
556:         KSPView(mglevels[i]->smoothd,viewer);
557:         PetscDrawPopCurrentPoint(draw);
558:       } else {
559:         w    = 0.5*PetscMin(1.0-x,x);
560:         PetscDrawPushCurrentPoint(draw,x+w,bottom);
561:         KSPView(mglevels[i]->smoothd,viewer);
562:         PetscDrawPopCurrentPoint(draw);
563:         PetscDrawPushCurrentPoint(draw,x-w,bottom);
564:         KSPView(mglevels[i]->smoothu,viewer);
565:         PetscDrawPopCurrentPoint(draw);
566:       }
567:       PetscDrawGetBoundingBox(draw,NULL,&bottom,NULL,NULL);
568:       bottom -= th;
569:     }
570:   }
571:   return(0);
572: }

574:  #include <petsc/private/dmimpl.h>
575:  #include <petsc/private/kspimpl.h>

577: /*
578:     Calls setup for the KSP on each level
579: */
580: PetscErrorCode PCSetUp_MG(PC pc)
581: {
582:   PC_MG          *mg        = (PC_MG*)pc->data;
583:   PC_MG_Levels   **mglevels = mg->levels;
585:   PetscInt       i,n;
586:   PC             cpc;
587:   PetscBool      dump = PETSC_FALSE,opsset,use_amat,missinginterpolate = PETSC_FALSE;
588:   Mat            dA,dB;
589:   Vec            tvec;
590:   DM             *dms;
591:   PetscViewer    viewer = 0;
592:   PetscBool      dAeqdB = PETSC_FALSE, needRestricts = PETSC_FALSE;

595:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels with PCMGSetLevels() before setting up");
596:   n = mglevels[0]->levels;
597:   /* FIX: Move this to PCSetFromOptions_MG? */
598:   if (mg->usedmfornumberoflevels) {
599:     PetscInt levels;
600:     DMGetRefineLevel(pc->dm,&levels);
601:     levels++;
602:     if (levels > n) { /* the problem is now being solved on a finer grid */
603:       PCMGSetLevels(pc,levels,NULL);
604:       n        = levels;
605:       PCSetFromOptions(pc); /* it is bad to call this here, but otherwise will never be called for the new hierarchy */
606:       mglevels =  mg->levels;
607:     }
608:   }
609:   KSPGetPC(mglevels[0]->smoothd,&cpc);


612:   /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */
613:   /* so use those from global PC */
614:   /* Is this what we always want? What if user wants to keep old one? */
615:   KSPGetOperatorsSet(mglevels[n-1]->smoothd,NULL,&opsset);
616:   if (opsset) {
617:     Mat mmat;
618:     KSPGetOperators(mglevels[n-1]->smoothd,NULL,&mmat);
619:     if (mmat == pc->pmat) opsset = PETSC_FALSE;
620:   }

622:   if (!opsset) {
623:     PCGetUseAmat(pc,&use_amat);
624:     if(use_amat){
625:       PetscInfo(pc,"Using outer operators to define finest grid operator \n  because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
626:       KSPSetOperators(mglevels[n-1]->smoothd,pc->mat,pc->pmat);
627:     }
628:     else {
629:       PetscInfo(pc,"Using matrix (pmat) operators to define finest grid operator \n  because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
630:       KSPSetOperators(mglevels[n-1]->smoothd,pc->pmat,pc->pmat);
631:     }
632:   }

634:   for (i=n-1; i>0; i--) {
635:     if (!(mglevels[i]->interpolate || mglevels[i]->restrct)) {
636:       missinginterpolate = PETSC_TRUE;
637:       continue;
638:     }
639:   }

641:   KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB);
642:   if (dA == dB) dAeqdB = PETSC_TRUE;
643:   if ((mg->galerkin == PC_MG_GALERKIN_NONE) || (((mg->galerkin == PC_MG_GALERKIN_PMAT) || (mg->galerkin == PC_MG_GALERKIN_MAT)) && !dAeqdB)) {
644:     needRestricts = PETSC_TRUE;  /* user must compute either mat, pmat, or both so must restrict x to coarser levels */
645:   }


648:   /*
649:    Skipping if user has provided all interpolation/restriction needed (since DM might not be able to produce them (when coming from SNES/TS)
650:    Skipping for galerkin==2 (externally managed hierarchy such as ML and GAMG). Cleaner logic here would be great. Wrap ML/GAMG as DMs?
651:   */
652:   if (missinginterpolate && pc->dm && mg->galerkin != PC_MG_GALERKIN_EXTERNAL && !pc->setupcalled) {
653:         /* construct the interpolation from the DMs */
654:     Mat p;
655:     Vec rscale;
656:     PetscMalloc1(n,&dms);
657:     dms[n-1] = pc->dm;
658:     /* Separately create them so we do not get DMKSP interference between levels */
659:     for (i=n-2; i>-1; i--) {DMCoarsen(dms[i+1],MPI_COMM_NULL,&dms[i]);}
660:         /*
661:            Force the mat type of coarse level operator to be AIJ because usually we want to use LU for coarse level.
662:            Notice that it can be overwritten by -mat_type because KSPSetUp() reads command line options.
663:            But it is safe to use -dm_mat_type.

665:            The mat type should not be hardcoded like this, we need to find a better way.
666:     DMSetMatType(dms[0],MATAIJ);
667:     */
668:     for (i=n-2; i>-1; i--) {
669:       DMKSP     kdm;
670:       PetscBool dmhasrestrict, dmhasinject;
671:       KSPSetDM(mglevels[i]->smoothd,dms[i]);
672:       if (!needRestricts) {KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);}
673:       DMGetDMKSPWrite(dms[i],&kdm);
674:       /* Ugly hack so that the next KSPSetUp() will use the RHS that we set. A better fix is to change dmActive to take
675:        * a bitwise OR of computing the matrix, RHS, and initial iterate. */
676:       kdm->ops->computerhs = NULL;
677:       kdm->rhsctx          = NULL;
678:       if (!mglevels[i+1]->interpolate) {
679:         DMCreateInterpolation(dms[i],dms[i+1],&p,&rscale);
680:         PCMGSetInterpolation(pc,i+1,p);
681:         if (rscale) {PCMGSetRScale(pc,i+1,rscale);}
682:         VecDestroy(&rscale);
683:         MatDestroy(&p);
684:       }
685:       DMHasCreateRestriction(dms[i],&dmhasrestrict);
686:       if (dmhasrestrict && !mglevels[i+1]->restrct){
687:         DMCreateRestriction(dms[i],dms[i+1],&p);
688:         PCMGSetRestriction(pc,i+1,p);
689:         MatDestroy(&p);
690:       }
691:       DMHasCreateInjection(dms[i],&dmhasinject);
692:       if (dmhasinject && !mglevels[i+1]->inject){
693:         DMCreateInjection(dms[i],dms[i+1],&p);
694:         PCMGSetInjection(pc,i+1,p);
695:         MatDestroy(&p);
696:       }
697:     }

699:     for (i=n-2; i>-1; i--) {DMDestroy(&dms[i]);}
700:     PetscFree(dms);
701:   }

703:   if (pc->dm && !pc->setupcalled) {
704:     /* finest smoother also gets DM but it is not active, independent of whether galerkin==PC_MG_GALERKIN_EXTERNAL */
705:     KSPSetDM(mglevels[n-1]->smoothd,pc->dm);
706:     KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);
707:   }

709:   if (mg->galerkin < PC_MG_GALERKIN_NONE) {
710:     Mat       A,B;
711:     PetscBool doA = PETSC_FALSE,doB = PETSC_FALSE;
712:     MatReuse  reuse = MAT_INITIAL_MATRIX;

714:     if ((mg->galerkin == PC_MG_GALERKIN_PMAT) || (mg->galerkin == PC_MG_GALERKIN_BOTH)) doB = PETSC_TRUE;
715:     if ((mg->galerkin == PC_MG_GALERKIN_MAT) || ((mg->galerkin == PC_MG_GALERKIN_BOTH) && (dA != dB))) doA = PETSC_TRUE;
716:     if (pc->setupcalled) reuse = MAT_REUSE_MATRIX;
717:     for (i=n-2; i>-1; i--) {
718:       if (!mglevels[i+1]->restrct && !mglevels[i+1]->interpolate) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must provide interpolation or restriction for each MG level except level 0");
719:       if (!mglevels[i+1]->interpolate) {
720:         PCMGSetInterpolation(pc,i+1,mglevels[i+1]->restrct);
721:       }
722:       if (!mglevels[i+1]->restrct) {
723:         PCMGSetRestriction(pc,i+1,mglevels[i+1]->interpolate);
724:       }
725:       if (reuse == MAT_REUSE_MATRIX) {
726:         KSPGetOperators(mglevels[i]->smoothd,&A,&B);
727:       }
728:       if (doA) {
729:         MatGalerkin(mglevels[i+1]->restrct,dA,mglevels[i+1]->interpolate,reuse,1.0,&A);
730:       }
731:       if (doB) {
732:         MatGalerkin(mglevels[i+1]->restrct,dB,mglevels[i+1]->interpolate,reuse,1.0,&B);
733:       }
734:       /* the management of the PetscObjectReference() and PetscObjecDereference() below is rather delicate */
735:       if (!doA && dAeqdB) {
736:         if (reuse == MAT_INITIAL_MATRIX) {PetscObjectReference((PetscObject)B);}
737:         A = B;
738:       } else if (!doA && reuse == MAT_INITIAL_MATRIX ) {
739:         KSPGetOperators(mglevels[i]->smoothd,&A,NULL);
740:         PetscObjectReference((PetscObject)A);
741:       }
742:       if (!doB && dAeqdB) {
743:         if (reuse == MAT_INITIAL_MATRIX) {PetscObjectReference((PetscObject)A);}
744:         B = A;
745:       } else if (!doB && reuse == MAT_INITIAL_MATRIX) {
746:         KSPGetOperators(mglevels[i]->smoothd,NULL,&B);
747:         PetscObjectReference((PetscObject)B);
748:       }
749:       if (reuse == MAT_INITIAL_MATRIX) {
750:         KSPSetOperators(mglevels[i]->smoothd,A,B);
751:         PetscObjectDereference((PetscObject)A);
752:         PetscObjectDereference((PetscObject)B);
753:       }
754:       dA = A;
755:       dB = B;
756:     }
757:   }
758:   if (needRestricts && pc->dm && pc->dm->x) {
759:     /* need to restrict Jacobian location to coarser meshes for evaluation */
760:     for (i=n-2; i>-1; i--) {
761:       Mat R;
762:       Vec rscale;
763:       if (!mglevels[i]->smoothd->dm->x) {
764:         Vec *vecs;
765:         KSPCreateVecs(mglevels[i]->smoothd,1,&vecs,0,NULL);
766:         mglevels[i]->smoothd->dm->x = vecs[0];
767:         PetscFree(vecs);
768:       }
769:       PCMGGetRestriction(pc,i+1,&R);
770:       PCMGGetRScale(pc,i+1,&rscale);
771:       MatRestrict(R,mglevels[i+1]->smoothd->dm->x,mglevels[i]->smoothd->dm->x);
772:       VecPointwiseMult(mglevels[i]->smoothd->dm->x,mglevels[i]->smoothd->dm->x,rscale);
773:     }
774:   }
775:   if (needRestricts && pc->dm) {
776:     for (i=n-2; i>=0; i--) {
777:       DM  dmfine,dmcoarse;
778:       Mat Restrict,Inject;
779:       Vec rscale;
780:       KSPGetDM(mglevels[i+1]->smoothd,&dmfine);
781:       KSPGetDM(mglevels[i]->smoothd,&dmcoarse);
782:       PCMGGetRestriction(pc,i+1,&Restrict);
783:       PCMGGetRScale(pc,i+1,&rscale);
784:       PCMGGetInjection(pc,i+1,&Inject);
785:       DMRestrict(dmfine,Restrict,rscale,Inject,dmcoarse);
786:     }
787:   }

789:   if (!pc->setupcalled) {
790:     for (i=0; i<n; i++) {
791:       KSPSetFromOptions(mglevels[i]->smoothd);
792:     }
793:     for (i=1; i<n; i++) {
794:       if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) {
795:         KSPSetFromOptions(mglevels[i]->smoothu);
796:       }
797:     }
798:     /* insure that if either interpolation or restriction is set the other other one is set */
799:     for (i=1; i<n; i++) {
800:       PCMGGetInterpolation(pc,i,NULL);
801:       PCMGGetRestriction(pc,i,NULL);
802:     }
803:     for (i=0; i<n-1; i++) {
804:       if (!mglevels[i]->b) {
805:         Vec *vec;
806:         KSPCreateVecs(mglevels[i]->smoothd,1,&vec,0,NULL);
807:         PCMGSetRhs(pc,i,*vec);
808:         VecDestroy(vec);
809:         PetscFree(vec);
810:       }
811:       if (!mglevels[i]->r && i) {
812:         VecDuplicate(mglevels[i]->b,&tvec);
813:         PCMGSetR(pc,i,tvec);
814:         VecDestroy(&tvec);
815:       }
816:       if (!mglevels[i]->x) {
817:         VecDuplicate(mglevels[i]->b,&tvec);
818:         PCMGSetX(pc,i,tvec);
819:         VecDestroy(&tvec);
820:       }
821:     }
822:     if (n != 1 && !mglevels[n-1]->r) {
823:       /* PCMGSetR() on the finest level if user did not supply it */
824:       Vec *vec;
825:       KSPCreateVecs(mglevels[n-1]->smoothd,1,&vec,0,NULL);
826:       PCMGSetR(pc,n-1,*vec);
827:       VecDestroy(vec);
828:       PetscFree(vec);
829:     }
830:   }

832:   if (pc->dm) {
833:     /* need to tell all the coarser levels to rebuild the matrix using the DM for that level */
834:     for (i=0; i<n-1; i++) {
835:       if (mglevels[i]->smoothd->setupstage != KSP_SETUP_NEW) mglevels[i]->smoothd->setupstage = KSP_SETUP_NEWMATRIX;
836:     }
837:   }

839:   for (i=1; i<n; i++) {
840:     if (mglevels[i]->smoothu == mglevels[i]->smoothd || mg->am == PC_MG_FULL || mg->am == PC_MG_KASKADE || mg->cyclesperpcapply > 1){
841:       /* if doing only down then initial guess is zero */
842:       KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);
843:     }
844:     if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
845:     KSPSetUp(mglevels[i]->smoothd);
846:     if (mglevels[i]->smoothd->reason == KSP_DIVERGED_PCSETUP_FAILED) {
847:       pc->failedreason = PC_SUBPC_ERROR;
848:     }
849:     if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
850:     if (!mglevels[i]->residual) {
851:       Mat mat;
852:       KSPGetOperators(mglevels[i]->smoothd,&mat,NULL);
853:       PCMGSetResidual(pc,i,PCMGResidualDefault,mat);
854:     }
855:   }
856:   for (i=1; i<n; i++) {
857:     if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) {
858:       Mat downmat,downpmat;

860:       /* check if operators have been set for up, if not use down operators to set them */
861:       KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,NULL);
862:       if (!opsset) {
863:         KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat);
864:         KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat);
865:       }

867:       KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);
868:       if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
869:       KSPSetUp(mglevels[i]->smoothu);
870:       if (mglevels[i]->smoothu->reason == KSP_DIVERGED_PCSETUP_FAILED) {
871:         pc->failedreason = PC_SUBPC_ERROR;
872:       }
873:       if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
874:     }
875:   }

877:   if (mglevels[0]->eventsmoothsetup) {PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);}
878:   KSPSetUp(mglevels[0]->smoothd);
879:   if (mglevels[0]->smoothd->reason == KSP_DIVERGED_PCSETUP_FAILED) {
880:     pc->failedreason = PC_SUBPC_ERROR;
881:   }
882:   if (mglevels[0]->eventsmoothsetup) {PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);}

884:   /*
885:      Dump the interpolation/restriction matrices plus the
886:    Jacobian/stiffness on each level. This allows MATLAB users to
887:    easily check if the Galerkin condition A_c = R A_f R^T is satisfied.

889:    Only support one or the other at the same time.
890:   */
891: #if defined(PETSC_USE_SOCKET_VIEWER)
892:   PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,NULL);
893:   if (dump) viewer = PETSC_VIEWER_SOCKET_(PetscObjectComm((PetscObject)pc));
894:   dump = PETSC_FALSE;
895: #endif
896:   PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,NULL);
897:   if (dump) viewer = PETSC_VIEWER_BINARY_(PetscObjectComm((PetscObject)pc));

899:   if (viewer) {
900:     for (i=1; i<n; i++) {
901:       MatView(mglevels[i]->restrct,viewer);
902:     }
903:     for (i=0; i<n; i++) {
904:       KSPGetPC(mglevels[i]->smoothd,&pc);
905:       MatView(pc->mat,viewer);
906:     }
907:   }
908:   return(0);
909: }

911: /* -------------------------------------------------------------------------------------*/

913: /*@
914:    PCMGGetLevels - Gets the number of levels to use with MG.

916:    Not Collective

918:    Input Parameter:
919: .  pc - the preconditioner context

921:    Output parameter:
922: .  levels - the number of levels

924:    Level: advanced

926: .keywords: MG, get, levels, multigrid

928: .seealso: PCMGSetLevels()
929: @*/
930: PetscErrorCode  PCMGGetLevels(PC pc,PetscInt *levels)
931: {
932:   PC_MG *mg = (PC_MG*)pc->data;

937:   *levels = mg->nlevels;
938:   return(0);
939: }

941: /*@
942:    PCMGSetType - Determines the form of multigrid to use:
943:    multiplicative, additive, full, or the Kaskade algorithm.

945:    Logically Collective on PC

947:    Input Parameters:
948: +  pc - the preconditioner context
949: -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
950:    PC_MG_FULL, PC_MG_KASKADE

952:    Options Database Key:
953: .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
954:    additive, full, kaskade

956:    Level: advanced

958: .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid

960: .seealso: PCMGSetLevels()
961: @*/
962: PetscErrorCode  PCMGSetType(PC pc,PCMGType form)
963: {
964:   PC_MG *mg = (PC_MG*)pc->data;

969:   mg->am = form;
970:   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
971:   else pc->ops->applyrichardson = NULL;
972:   return(0);
973: }

975: /*@
976:    PCMGGetType - Determines the form of multigrid to use:
977:    multiplicative, additive, full, or the Kaskade algorithm.

979:    Logically Collective on PC

981:    Input Parameter:
982: .  pc - the preconditioner context

984:    Output Parameter:
985: .  type - one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,PC_MG_FULL, PC_MG_KASKADE


988:    Level: advanced

990: .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid

992: .seealso: PCMGSetLevels()
993: @*/
994: PetscErrorCode  PCMGGetType(PC pc,PCMGType *type)
995: {
996:   PC_MG *mg = (PC_MG*)pc->data;

1000:   *type = mg->am;
1001:   return(0);
1002: }

1004: /*@
1005:    PCMGSetCycleType - Sets the type cycles to use.  Use PCMGSetCycleTypeOnLevel() for more
1006:    complicated cycling.

1008:    Logically Collective on PC

1010:    Input Parameters:
1011: +  pc - the multigrid context
1012: -  n - either PC_MG_CYCLE_V or PC_MG_CYCLE_W

1014:    Options Database Key:
1015: .  -pc_mg_cycle_type <v,w> - provide the cycle desired

1017:    Level: advanced

1019: .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid

1021: .seealso: PCMGSetCycleTypeOnLevel()
1022: @*/
1023: PetscErrorCode  PCMGSetCycleType(PC pc,PCMGCycleType n)
1024: {
1025:   PC_MG        *mg        = (PC_MG*)pc->data;
1026:   PC_MG_Levels **mglevels = mg->levels;
1027:   PetscInt     i,levels;

1032:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1033:   levels = mglevels[0]->levels;
1034:   for (i=0; i<levels; i++) mglevels[i]->cycles = n;
1035:   return(0);
1036: }

1038: /*@
1039:    PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step
1040:          of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used

1042:    Logically Collective on PC

1044:    Input Parameters:
1045: +  pc - the multigrid context
1046: -  n - number of cycles (default is 1)

1048:    Options Database Key:
1049: .  -pc_mg_multiplicative_cycles n

1051:    Level: advanced

1053:    Notes:
1054:     This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType()

1056: .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid

1058: .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
1059: @*/
1060: PetscErrorCode  PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
1061: {
1062:   PC_MG        *mg        = (PC_MG*)pc->data;

1067:   mg->cyclesperpcapply = n;
1068:   return(0);
1069: }

1071: PetscErrorCode PCMGSetGalerkin_MG(PC pc,PCMGGalerkinType use)
1072: {
1073:   PC_MG *mg = (PC_MG*)pc->data;

1076:   mg->galerkin = use;
1077:   return(0);
1078: }

1080: /*@
1081:    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
1082:       finest grid via the Galerkin process: A_i-1 = r_i * A_i * p_i

1084:    Logically Collective on PC

1086:    Input Parameters:
1087: +  pc - the multigrid context
1088: -  use - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, or PC_MG_GALERKIN_NONE

1090:    Options Database Key:
1091: .  -pc_mg_galerkin <both,pmat,mat,none>

1093:    Level: intermediate

1095:    Notes:
1096:     Some codes that use PCMG such as PCGAMG use Galerkin internally while constructing the hierarchy and thus do not
1097:      use the PCMG construction of the coarser grids.

1099: .keywords: MG, set, Galerkin

1101: .seealso: PCMGGetGalerkin(), PCMGGalerkinType

1103: @*/
1104: PetscErrorCode PCMGSetGalerkin(PC pc,PCMGGalerkinType use)
1105: {

1110:   PetscTryMethod(pc,"PCMGSetGalerkin_C",(PC,PCMGGalerkinType),(pc,use));
1111:   return(0);
1112: }

1114: /*@
1115:    PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
1116:       A_i-1 = r_i * A_i * p_i

1118:    Not Collective

1120:    Input Parameter:
1121: .  pc - the multigrid context

1123:    Output Parameter:
1124: .  galerkin - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, PC_MG_GALERKIN_NONE, or PC_MG_GALERKIN_EXTERNAL

1126:    Level: intermediate

1128: .keywords: MG, set, Galerkin

1130: .seealso: PCMGSetGalerkin(), PCMGGalerkinType

1132: @*/
1133: PetscErrorCode  PCMGGetGalerkin(PC pc,PCMGGalerkinType  *galerkin)
1134: {
1135:   PC_MG *mg = (PC_MG*)pc->data;

1139:   *galerkin = mg->galerkin;
1140:   return(0);
1141: }

1143: /*@
1144:    PCMGSetNumberSmooth - Sets the number of pre and post-smoothing steps to use
1145:    on all levels.  Use PCMGDistinctSmoothUp() to create separate up and down smoothers if you want different numbers of
1146:    pre- and post-smoothing steps.

1148:    Logically Collective on PC

1150:    Input Parameters:
1151: +  mg - the multigrid context
1152: -  n - the number of smoothing steps

1154:    Options Database Key:
1155: +  -mg_levels_ksp_max_it <n> - Sets number of pre and post-smoothing steps

1157:    Level: advanced

1159:    Notes:
1160:     this does not set a value on the coarsest grid, since we assume that
1161:     there is no separate smooth up on the coarsest grid.

1163: .keywords: MG, smooth, up, post-smoothing, steps, multigrid

1165: .seealso: PCMGSetDistinctSmoothUp()
1166: @*/
1167: PetscErrorCode  PCMGSetNumberSmooth(PC pc,PetscInt n)
1168: {
1169:   PC_MG          *mg        = (PC_MG*)pc->data;
1170:   PC_MG_Levels   **mglevels = mg->levels;
1172:   PetscInt       i,levels;

1177:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1178:   levels = mglevels[0]->levels;

1180:   for (i=1; i<levels; i++) {
1181:     KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1182:     KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1183:     mg->default_smoothu = n;
1184:     mg->default_smoothd = n;
1185:   }
1186:   return(0);
1187: }

1189: /*@
1190:    PCMGSetDistinctSmoothUp - sets the up (post) smoother to be a seperate KSP from the down (pre) smoother on all levels
1191:        and adds the suffix _up to the options name

1193:    Logically Collective on PC

1195:    Input Parameters:
1196: .  pc - the preconditioner context

1198:    Options Database Key:
1199: .  -pc_mg_distinct_smoothup

1201:    Level: advanced

1203:    Notes:
1204:     this does not set a value on the coarsest grid, since we assume that
1205:     there is no separate smooth up on the coarsest grid.

1207: .keywords: MG, smooth, up, post-smoothing, steps, multigrid

1209: .seealso: PCMGSetNumberSmooth()
1210: @*/
1211: PetscErrorCode  PCMGSetDistinctSmoothUp(PC pc)
1212: {
1213:   PC_MG          *mg        = (PC_MG*)pc->data;
1214:   PC_MG_Levels   **mglevels = mg->levels;
1216:   PetscInt       i,levels;
1217:   KSP            subksp;

1221:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1222:   levels = mglevels[0]->levels;

1224:   for (i=1; i<levels; i++) {
1225:     const char *prefix = NULL;
1226:     /* make sure smoother up and down are different */
1227:     PCMGGetSmootherUp(pc,i,&subksp);
1228:     KSPGetOptionsPrefix(mglevels[i]->smoothd,&prefix);
1229:     KSPSetOptionsPrefix(subksp,prefix);
1230:     KSPAppendOptionsPrefix(subksp,"up_");
1231:   }
1232:   return(0);
1233: }

1235: /* ----------------------------------------------------------------------------------------*/

1237: /*MC
1238:    PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional
1239:     information about the coarser grid matrices and restriction/interpolation operators.

1241:    Options Database Keys:
1242: +  -pc_mg_levels <nlevels> - number of levels including finest
1243: .  -pc_mg_cycle_type <v,w> - provide the cycle desired
1244: .  -pc_mg_type <additive,multiplicative,full,kaskade> - multiplicative is the default
1245: .  -pc_mg_log - log information about time spent on each level of the solver
1246: .  -pc_mg_distinct_smoothup - configure up (after interpolation) and down (before restriction) smoothers separately (with different options prefixes)
1247: .  -pc_mg_galerkin <both,pmat,mat,none> - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R'
1248: .  -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1)
1249: .  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
1250:                         to the Socket viewer for reading from MATLAB.
1251: -  -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices
1252:                         to the binary output file called binaryoutput

1254:    Notes:
1255:     If one uses a Krylov method such GMRES or CG as the smoother then one must use KSPFGMRES, KSPGCR, or KSPRICHARDSON as the outer Krylov method

1257:        When run with a single level the smoother options are used on that level NOT the coarse grid solver options

1259:        When run with KSPRICHARDSON the convergence test changes slightly if monitor is turned on. The iteration count may change slightly. This
1260:        is because without monitoring the residual norm is computed WITHIN each multigrid cycle on the finest level after the pre-smoothing
1261:        (because the residual has just been computed for the multigrid algorithm and is hence available for free) while with monitoring the
1262:        residual is computed at the end of each cycle.

1264:    Level: intermediate

1266:    Concepts: multigrid/multilevel

1268: .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE
1269:            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(),
1270:            PCMGSetDistinctSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
1271:            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
1272:            PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
1273: M*/

1275: PETSC_EXTERN PetscErrorCode PCCreate_MG(PC pc)
1276: {
1277:   PC_MG          *mg;

1281:   PetscNewLog(pc,&mg);
1282:   pc->data     = (void*)mg;
1283:   mg->nlevels  = -1;
1284:   mg->am       = PC_MG_MULTIPLICATIVE;
1285:   mg->galerkin = PC_MG_GALERKIN_NONE;

1287:   pc->useAmat = PETSC_TRUE;

1289:   pc->ops->apply          = PCApply_MG;
1290:   pc->ops->setup          = PCSetUp_MG;
1291:   pc->ops->reset          = PCReset_MG;
1292:   pc->ops->destroy        = PCDestroy_MG;
1293:   pc->ops->setfromoptions = PCSetFromOptions_MG;
1294:   pc->ops->view           = PCView_MG;

1296:   PetscObjectComposeFunction((PetscObject)pc,"PCMGSetGalerkin_C",PCMGSetGalerkin_MG);
1297:   return(0);
1298: }