Actual source code: mg.c

petsc-3.7.3 2016-07-24
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  2: /*
  3:     Defines the multigrid preconditioner interface.
  4: */
  5: #include <petsc/private/pcmgimpl.h>                    /*I "petscksp.h" I*/
  6: #include <petscdm.h>

 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;
 15:   PetscInt       cycles = (mglevels->level == 1) ? 1 : (PetscInt) mglevels->cycles;
 16:   PC             subpc;
 17:   PCFailedReason pcreason;

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

 33:     /* if on finest level and have convergence criteria set */
 34:     if (mglevels->level == mglevels->levels-1 && mg->ttol && reason) {
 35:       PetscReal rnorm;
 36:       VecNorm(mglevels->r,NORM_2,&rnorm);
 37:       if (rnorm <= mg->ttol) {
 38:         if (rnorm < mg->abstol) {
 39:           *reason = PCRICHARDSON_CONVERGED_ATOL;
 40:           PetscInfo2(pc,"Linear solver has converged. Residual norm %g is less than absolute tolerance %g\n",(double)rnorm,(double)mg->abstol);
 41:         } else {
 42:           *reason = PCRICHARDSON_CONVERGED_RTOL;
 43:           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);
 44:         }
 45:         return(0);
 46:       }
 47:     }

 49:     mgc = *(mglevelsin - 1);
 50:     if (mglevels->eventinterprestrict) {PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);}
 51:     MatRestrict(mglevels->restrct,mglevels->r,mgc->b);
 52:     if (mglevels->eventinterprestrict) {PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);}
 53:     VecSet(mgc->x,0.0);
 54:     while (cycles--) {
 55:       PCMGMCycle_Private(pc,mglevelsin-1,reason);
 56:     }
 57:     if (mglevels->eventinterprestrict) {PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);}
 58:     MatInterpolateAdd(mglevels->interpolate,mgc->x,mglevels->x,mglevels->x);
 59:     if (mglevels->eventinterprestrict) {PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);}
 60:     if (mglevels->eventsmoothsolve) {PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);}
 61:     KSPSolve(mglevels->smoothu,mglevels->b,mglevels->x);    /* post smooth */
 62:     if (mglevels->eventsmoothsolve) {PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);}
 63:   }
 64:   return(0);
 65: }

 69: 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)
 70: {
 71:   PC_MG          *mg        = (PC_MG*)pc->data;
 72:   PC_MG_Levels   **mglevels = mg->levels;
 74:   PetscInt       levels = mglevels[0]->levels,i;

 77:   /* When the DM is supplying the matrix then it will not exist until here */
 78:   for (i=0; i<levels; i++) {
 79:     if (!mglevels[i]->A) {
 80:       KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);
 81:       PetscObjectReference((PetscObject)mglevels[i]->A);
 82:     }
 83:   }
 84:   mglevels[levels-1]->b = b;
 85:   mglevels[levels-1]->x = x;

 87:   mg->rtol   = rtol;
 88:   mg->abstol = abstol;
 89:   mg->dtol   = dtol;
 90:   if (rtol) {
 91:     /* compute initial residual norm for relative convergence test */
 92:     PetscReal rnorm;
 93:     if (zeroguess) {
 94:       VecNorm(b,NORM_2,&rnorm);
 95:     } else {
 96:       (*mglevels[levels-1]->residual)(mglevels[levels-1]->A,b,x,w);
 97:       VecNorm(w,NORM_2,&rnorm);
 98:     }
 99:     mg->ttol = PetscMax(rtol*rnorm,abstol);
100:   } else if (abstol) mg->ttol = abstol;
101:   else mg->ttol = 0.0;

103:   /* since smoother is applied to full system, not just residual we need to make sure that smoothers don't
104:      stop prematurely due to small residual */
105:   for (i=1; i<levels; i++) {
106:     KSPSetTolerances(mglevels[i]->smoothu,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);
107:     if (mglevels[i]->smoothu != mglevels[i]->smoothd) {
108:       KSPSetTolerances(mglevels[i]->smoothd,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);
109:     }
110:   }

112:   *reason = (PCRichardsonConvergedReason)0;
113:   for (i=0; i<its; i++) {
114:     PCMGMCycle_Private(pc,mglevels+levels-1,reason);
115:     if (*reason) break;
116:   }
117:   if (!*reason) *reason = PCRICHARDSON_CONVERGED_ITS;
118:   *outits = i;
119:   return(0);
120: }

124: PetscErrorCode PCReset_MG(PC pc)
125: {
126:   PC_MG          *mg        = (PC_MG*)pc->data;
127:   PC_MG_Levels   **mglevels = mg->levels;
129:   PetscInt       i,n;

132:   if (mglevels) {
133:     n = mglevels[0]->levels;
134:     for (i=0; i<n-1; i++) {
135:       VecDestroy(&mglevels[i+1]->r);
136:       VecDestroy(&mglevels[i]->b);
137:       VecDestroy(&mglevels[i]->x);
138:       MatDestroy(&mglevels[i+1]->restrct);
139:       MatDestroy(&mglevels[i+1]->interpolate);
140:       VecDestroy(&mglevels[i+1]->rscale);
141:     }

143:     for (i=0; i<n; i++) {
144:       MatDestroy(&mglevels[i]->A);
145:       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
146:         KSPReset(mglevels[i]->smoothd);
147:       }
148:       KSPReset(mglevels[i]->smoothu);
149:     }
150:   }
151:   return(0);
152: }

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

160:    Logically Collective on PC

162:    Input Parameters:
163: +  pc - the preconditioner context
164: .  levels - the number of levels
165: -  comms - optional communicators for each level; this is to allow solving the coarser problems
166:            on smaller sets of processors. Use NULL_OBJECT for default in Fortran

168:    Level: intermediate

170:    Notes:
171:      If the number of levels is one then the multigrid uses the -mg_levels prefix
172:   for setting the level options rather than the -mg_coarse prefix.

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

176: .seealso: PCMGSetType(), PCMGGetLevels()
177: @*/
178: PetscErrorCode  PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
179: {
181:   PC_MG          *mg        = (PC_MG*)pc->data;
182:   MPI_Comm       comm;
183:   PC_MG_Levels   **mglevels = mg->levels;
184:   PCMGType       mgtype     = mg->am;
185:   PetscInt       mgctype    = (PetscInt) PC_MG_CYCLE_V;
186:   PetscInt       i;
187:   PetscMPIInt    size;
188:   const char     *prefix;
189:   PC             ipc;
190:   PetscInt       n;

195:   PetscObjectGetComm((PetscObject)pc,&comm);
196:   if (mg->nlevels == levels) return(0);
197:   if (mglevels) {
198:     mgctype = mglevels[0]->cycles;
199:     /* changing the number of levels so free up the previous stuff */
200:     PCReset_MG(pc);
201:     n    = mglevels[0]->levels;
202:     for (i=0; i<n; i++) {
203:       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
204:         KSPDestroy(&mglevels[i]->smoothd);
205:       }
206:       KSPDestroy(&mglevels[i]->smoothu);
207:       PetscFree(mglevels[i]);
208:     }
209:     PetscFree(mg->levels);
210:   }

212:   mg->nlevels = levels;

214:   PetscMalloc1(levels,&mglevels);
215:   PetscLogObjectMemory((PetscObject)pc,levels*(sizeof(PC_MG*)));

217:   PCGetOptionsPrefix(pc,&prefix);

219:   mg->stageApply = 0;
220:   for (i=0; i<levels; i++) {
221:     PetscNewLog(pc,&mglevels[i]);

223:     mglevels[i]->level               = i;
224:     mglevels[i]->levels              = levels;
225:     mglevels[i]->cycles              = mgctype;
226:     mg->default_smoothu              = 2;
227:     mg->default_smoothd              = 2;
228:     mglevels[i]->eventsmoothsetup    = 0;
229:     mglevels[i]->eventsmoothsolve    = 0;
230:     mglevels[i]->eventresidual       = 0;
231:     mglevels[i]->eventinterprestrict = 0;

233:     if (comms) comm = comms[i];
234:     KSPCreate(comm,&mglevels[i]->smoothd);
235:     KSPSetErrorIfNotConverged(mglevels[i]->smoothd,pc->erroriffailure);
236:     PetscObjectIncrementTabLevel((PetscObject)mglevels[i]->smoothd,(PetscObject)pc,levels-i);
237:     KSPSetOptionsPrefix(mglevels[i]->smoothd,prefix);
238:     PetscObjectComposedDataSetInt((PetscObject) mglevels[i]->smoothd, PetscMGLevelId, mglevels[i]->level);
239:     if (i || levels == 1) {
240:       char tprefix[128];

242:       KSPSetType(mglevels[i]->smoothd,KSPCHEBYSHEV);
243:       KSPSetConvergenceTest(mglevels[i]->smoothd,KSPConvergedSkip,NULL,NULL);
244:       KSPSetNormType(mglevels[i]->smoothd,KSP_NORM_NONE);
245:       KSPGetPC(mglevels[i]->smoothd,&ipc);
246:       PCSetType(ipc,PCSOR);
247:       KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, mg->default_smoothd);

249:       sprintf(tprefix,"mg_levels_%d_",(int)i);
250:       KSPAppendOptionsPrefix(mglevels[i]->smoothd,tprefix);
251:     } else {
252:       KSPAppendOptionsPrefix(mglevels[0]->smoothd,"mg_coarse_");

254:       /* coarse solve is (redundant) LU by default; set shifttype NONZERO to avoid annoying zero-pivot in LU preconditioner */
255:       KSPSetType(mglevels[0]->smoothd,KSPPREONLY);
256:       KSPGetPC(mglevels[0]->smoothd,&ipc);
257:       MPI_Comm_size(comm,&size);
258:       if (size > 1) {
259:         PCSetType(ipc,PCREDUNDANT);
260:       } else {
261:         PCSetType(ipc,PCLU);
262:       }
263:       PCFactorSetShiftType(ipc,MAT_SHIFT_INBLOCKS);
264:     }
265:     PetscLogObjectParent((PetscObject)pc,(PetscObject)mglevels[i]->smoothd);

267:     mglevels[i]->smoothu = mglevels[i]->smoothd;
268:     mg->rtol             = 0.0;
269:     mg->abstol           = 0.0;
270:     mg->dtol             = 0.0;
271:     mg->ttol             = 0.0;
272:     mg->cyclesperpcapply = 1;
273:   }
274:   mg->levels = mglevels;
275:   PCMGSetType(pc,mgtype);
276:   return(0);
277: }


282: PetscErrorCode PCDestroy_MG(PC pc)
283: {
285:   PC_MG          *mg        = (PC_MG*)pc->data;
286:   PC_MG_Levels   **mglevels = mg->levels;
287:   PetscInt       i,n;

290:   PCReset_MG(pc);
291:   if (mglevels) {
292:     n = mglevels[0]->levels;
293:     for (i=0; i<n; i++) {
294:       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
295:         KSPDestroy(&mglevels[i]->smoothd);
296:       }
297:       KSPDestroy(&mglevels[i]->smoothu);
298:       PetscFree(mglevels[i]);
299:     }
300:     PetscFree(mg->levels);
301:   }
302:   PetscFree(pc->data);
303:   return(0);
304: }



308: extern PetscErrorCode PCMGACycle_Private(PC,PC_MG_Levels**);
309: extern PetscErrorCode PCMGFCycle_Private(PC,PC_MG_Levels**);
310: extern PetscErrorCode PCMGKCycle_Private(PC,PC_MG_Levels**);

312: /*
313:    PCApply_MG - Runs either an additive, multiplicative, Kaskadic
314:              or full cycle of multigrid.

316:   Note:
317:   A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle().
318: */
321: static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
322: {
323:   PC_MG          *mg        = (PC_MG*)pc->data;
324:   PC_MG_Levels   **mglevels = mg->levels;
326:   PetscInt       levels = mglevels[0]->levels,i;

329:   if (mg->stageApply) {PetscLogStagePush(mg->stageApply);}
330:   /* When the DM is supplying the matrix then it will not exist until here */
331:   for (i=0; i<levels; i++) {
332:     if (!mglevels[i]->A) {
333:       KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);
334:       PetscObjectReference((PetscObject)mglevels[i]->A);
335:     }
336:   }

338:   mglevels[levels-1]->b = b;
339:   mglevels[levels-1]->x = x;
340:   if (mg->am == PC_MG_MULTIPLICATIVE) {
341:     VecSet(x,0.0);
342:     for (i=0; i<mg->cyclesperpcapply; i++) {
343:       PCMGMCycle_Private(pc,mglevels+levels-1,NULL);
344:     }
345:   } else if (mg->am == PC_MG_ADDITIVE) {
346:     PCMGACycle_Private(pc,mglevels);
347:   } else if (mg->am == PC_MG_KASKADE) {
348:     PCMGKCycle_Private(pc,mglevels);
349:   } else {
350:     PCMGFCycle_Private(pc,mglevels);
351:   }
352:   if (mg->stageApply) {PetscLogStagePop();}
353:   return(0);
354: }


359: PetscErrorCode PCSetFromOptions_MG(PetscOptionItems *PetscOptionsObject,PC pc)
360: {
362:   PetscInt       m,levels = 1,cycles;
363:   PetscBool      flg,set;
364:   PC_MG          *mg        = (PC_MG*)pc->data;
365:   PC_MG_Levels   **mglevels;
366:   PCMGType       mgtype;
367:   PCMGCycleType  mgctype;

370:   PetscOptionsHead(PetscOptionsObject,"Multigrid options");
371:   if (!mg->levels) {
372:     PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);
373:     if (!flg && pc->dm) {
374:       DMGetRefineLevel(pc->dm,&levels);
375:       levels++;
376:       mg->usedmfornumberoflevels = PETSC_TRUE;
377:     }
378:     PCMGSetLevels(pc,levels,NULL);
379:   }
380:   mglevels = mg->levels;

382:   mgctype = (PCMGCycleType) mglevels[0]->cycles;
383:   PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);
384:   if (flg) {
385:     PCMGSetCycleType(pc,mgctype);
386:   }
387:   flg  = PETSC_FALSE;
388:   PetscOptionsBool("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",flg,&flg,&set);
389:   if (set) {
390:     PCMGSetGalerkin(pc,flg);
391:   }
392:   PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",mg->default_smoothu,&m,&flg);
393:   if (flg) {
394:     PCMGSetNumberSmoothUp(pc,m);
395:   }
396:   PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",mg->default_smoothd,&m,&flg);
397:   if (flg) {
398:     PCMGSetNumberSmoothDown(pc,m);
399:   }
400:   mgtype = mg->am;
401:   PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);
402:   if (flg) {
403:     PCMGSetType(pc,mgtype);
404:   }
405:   if (mg->am == PC_MG_MULTIPLICATIVE) {
406:     PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGMultiplicativeSetCycles",mg->cyclesperpcapply,&cycles,&flg);
407:     if (flg) {
408:       PCMGMultiplicativeSetCycles(pc,cycles);
409:     }
410:   }
411:   flg  = PETSC_FALSE;
412:   PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,NULL);
413:   if (flg) {
414:     PetscInt i;
415:     char     eventname[128];
416:     if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
417:     levels = mglevels[0]->levels;
418:     for (i=0; i<levels; i++) {
419:       sprintf(eventname,"MGSetup Level %d",(int)i);
420:       PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);
421:       sprintf(eventname,"MGSmooth Level %d",(int)i);
422:       PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);
423:       if (i) {
424:         sprintf(eventname,"MGResid Level %d",(int)i);
425:         PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);
426:         sprintf(eventname,"MGInterp Level %d",(int)i);
427:         PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);
428:       }
429:     }

431: #if defined(PETSC_USE_LOG)
432:     {
433:       const char    *sname = "MG Apply";
434:       PetscStageLog stageLog;
435:       PetscInt      st;

438:       PetscLogGetStageLog(&stageLog);
439:       for (st = 0; st < stageLog->numStages; ++st) {
440:         PetscBool same;

442:         PetscStrcmp(stageLog->stageInfo[st].name, sname, &same);
443:         if (same) mg->stageApply = st;
444:       }
445:       if (!mg->stageApply) {
446:         PetscLogStageRegister(sname, &mg->stageApply);
447:       }
448:     }
449: #endif
450:   }
451:   PetscOptionsTail();
452:   return(0);
453: }

455: const char *const PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0};
456: const char *const PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",0};

458: #include <petscdraw.h>
461: PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
462: {
463:   PC_MG          *mg        = (PC_MG*)pc->data;
464:   PC_MG_Levels   **mglevels = mg->levels;
466:   PetscInt       levels = mglevels ? mglevels[0]->levels : 0,i;
467:   PetscBool      iascii,isbinary,isdraw;

470:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
471:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
472:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
473:   if (iascii) {
474:     const char *cyclename = levels ? (mglevels[0]->cycles == PC_MG_CYCLE_V ? "v" : "w") : "unknown";
475:     PetscViewerASCIIPrintf(viewer,"  MG: type is %s, levels=%D cycles=%s\n", PCMGTypes[mg->am],levels,cyclename);
476:     if (mg->am == PC_MG_MULTIPLICATIVE) {
477:       PetscViewerASCIIPrintf(viewer,"    Cycles per PCApply=%d\n",mg->cyclesperpcapply);
478:     }
479:     if (mg->galerkin) {
480:       PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices\n");
481:     } else {
482:       PetscViewerASCIIPrintf(viewer,"    Not using Galerkin computed coarse grid matrices\n");
483:     }
484:     if (mg->view){
485:       (*mg->view)(pc,viewer);
486:     }
487:     for (i=0; i<levels; i++) {
488:       if (!i) {
489:         PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level -------------------------------\n",i);
490:       } else {
491:         PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);
492:       }
493:       PetscViewerASCIIPushTab(viewer);
494:       KSPView(mglevels[i]->smoothd,viewer);
495:       PetscViewerASCIIPopTab(viewer);
496:       if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) {
497:         PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");
498:       } else if (i) {
499:         PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);
500:         PetscViewerASCIIPushTab(viewer);
501:         KSPView(mglevels[i]->smoothu,viewer);
502:         PetscViewerASCIIPopTab(viewer);
503:       }
504:     }
505:   } else if (isbinary) {
506:     for (i=levels-1; i>=0; i--) {
507:       KSPView(mglevels[i]->smoothd,viewer);
508:       if (i && mglevels[i]->smoothd != mglevels[i]->smoothu) {
509:         KSPView(mglevels[i]->smoothu,viewer);
510:       }
511:     }
512:   } else if (isdraw) {
513:     PetscDraw draw;
514:     PetscReal x,w,y,bottom,th;
515:     PetscViewerDrawGetDraw(viewer,0,&draw);
516:     PetscDrawGetCurrentPoint(draw,&x,&y);
517:     PetscDrawStringGetSize(draw,NULL,&th);
518:     bottom = y - th;
519:     for (i=levels-1; i>=0; i--) {
520:       if (!mglevels[i]->smoothu || (mglevels[i]->smoothu == mglevels[i]->smoothd)) {
521:         PetscDrawPushCurrentPoint(draw,x,bottom);
522:         KSPView(mglevels[i]->smoothd,viewer);
523:         PetscDrawPopCurrentPoint(draw);
524:       } else {
525:         w    = 0.5*PetscMin(1.0-x,x);
526:         PetscDrawPushCurrentPoint(draw,x+w,bottom);
527:         KSPView(mglevels[i]->smoothd,viewer);
528:         PetscDrawPopCurrentPoint(draw);
529:         PetscDrawPushCurrentPoint(draw,x-w,bottom);
530:         KSPView(mglevels[i]->smoothu,viewer);
531:         PetscDrawPopCurrentPoint(draw);
532:       }
533:       PetscDrawGetBoundingBox(draw,NULL,&bottom,NULL,NULL);
534:       bottom -= th;
535:     }
536:   }
537:   return(0);
538: }

540: #include <petsc/private/dmimpl.h>
541: #include <petsc/private/kspimpl.h>

543: /*
544:     Calls setup for the KSP on each level
545: */
548: PetscErrorCode PCSetUp_MG(PC pc)
549: {
550:   PC_MG          *mg        = (PC_MG*)pc->data;
551:   PC_MG_Levels   **mglevels = mg->levels;
553:   PetscInt       i,n = mglevels[0]->levels;
554:   PC             cpc;
555:   PetscBool      dump = PETSC_FALSE,opsset,use_amat,missinginterpolate = PETSC_FALSE;
556:   Mat            dA,dB;
557:   Vec            tvec;
558:   DM             *dms;
559:   PetscViewer    viewer = 0;

562:   /* FIX: Move this to PCSetFromOptions_MG? */
563:   if (mg->usedmfornumberoflevels) {
564:     PetscInt levels;
565:     DMGetRefineLevel(pc->dm,&levels);
566:     levels++;
567:     if (levels > n) { /* the problem is now being solved on a finer grid */
568:       PCMGSetLevels(pc,levels,NULL);
569:       n        = levels;
570:       PCSetFromOptions(pc); /* it is bad to call this here, but otherwise will never be called for the new hierarchy */
571:       mglevels =  mg->levels;
572:     }
573:   }
574:   KSPGetPC(mglevels[0]->smoothd,&cpc);


577:   /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */
578:   /* so use those from global PC */
579:   /* Is this what we always want? What if user wants to keep old one? */
580:   KSPGetOperatorsSet(mglevels[n-1]->smoothd,NULL,&opsset);
581:   if (opsset) {
582:     Mat mmat;
583:     KSPGetOperators(mglevels[n-1]->smoothd,NULL,&mmat);
584:     if (mmat == pc->pmat) opsset = PETSC_FALSE;
585:   }

587:   if (!opsset) {
588:     PCGetUseAmat(pc,&use_amat);
589:     if(use_amat){
590:       PetscInfo(pc,"Using outer operators to define finest grid operator \n  because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
591:       KSPSetOperators(mglevels[n-1]->smoothd,pc->mat,pc->pmat);
592:     }
593:     else {
594:       PetscInfo(pc,"Using matrix (pmat) operators to define finest grid operator \n  because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
595:       KSPSetOperators(mglevels[n-1]->smoothd,pc->pmat,pc->pmat);
596:     }
597:   }

599:   for (i=n-1; i>0; i--) {
600:     if (!(mglevels[i]->interpolate || mglevels[i]->restrct)) {
601:       missinginterpolate = PETSC_TRUE;
602:       continue;
603:     }
604:   }
605:   /*
606:    Skipping if user has provided all interpolation/restriction needed (since DM might not be able to produce them (when coming from SNES/TS)
607:    Skipping for galerkin==2 (externally managed hierarchy such as ML and GAMG). Cleaner logic here would be great. Wrap ML/GAMG as DMs?
608:   */
609:   if (missinginterpolate && pc->dm && mg->galerkin != 2 && !pc->setupcalled) {
610:     /* construct the interpolation from the DMs */
611:     Mat p;
612:     Vec rscale;
613:     PetscMalloc1(n,&dms);
614:     dms[n-1] = pc->dm;
615:     /* Separately create them so we do not get DMKSP interference between levels */
616:     for (i=n-2; i>-1; i--) {DMCoarsen(dms[i+1],MPI_COMM_NULL,&dms[i]);}
617:     for (i=n-2; i>-1; i--) {
618:       DMKSP     kdm;
619:       PetscBool dmhasrestrict;
620:       KSPSetDM(mglevels[i]->smoothd,dms[i]);
621:       if (mg->galerkin) {KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);}
622:       DMGetDMKSPWrite(dms[i],&kdm);
623:       /* Ugly hack so that the next KSPSetUp() will use the RHS that we set. A better fix is to change dmActive to take
624:        * a bitwise OR of computing the matrix, RHS, and initial iterate. */
625:       kdm->ops->computerhs = NULL;
626:       kdm->rhsctx          = NULL;
627:       if (!mglevels[i+1]->interpolate) {
628:         DMCreateInterpolation(dms[i],dms[i+1],&p,&rscale);
629:         PCMGSetInterpolation(pc,i+1,p);
630:         if (rscale) {PCMGSetRScale(pc,i+1,rscale);}
631:         VecDestroy(&rscale);
632:         MatDestroy(&p);
633:       }
634:       DMHasCreateRestriction(dms[i],&dmhasrestrict);
635:       if (dmhasrestrict && !mglevels[i+1]->restrct){
636:         DMCreateRestriction(dms[i],dms[i+1],&p);
637:         PCMGSetRestriction(pc,i+1,p);
638:         MatDestroy(&p);
639:       }
640:     }

642:     for (i=n-2; i>-1; i--) {DMDestroy(&dms[i]);}
643:     PetscFree(dms);
644:   }

646:   if (pc->dm && !pc->setupcalled) {
647:     /* finest smoother also gets DM but it is not active, independent of whether galerkin==2 */
648:     KSPSetDM(mglevels[n-1]->smoothd,pc->dm);
649:     KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);
650:   }

652:   if (mg->galerkin == 1) {
653:     Mat B;
654:     /* currently only handle case where mat and pmat are the same on coarser levels */
655:     KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB);
656:     if (!pc->setupcalled) {
657:       for (i=n-2; i>-1; i--) {
658:         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");
659:         if (!mglevels[i+1]->interpolate) {
660:           PCMGSetInterpolation(pc,i+1,mglevels[i+1]->restrct);
661:         }
662:         if (!mglevels[i+1]->restrct) {
663:           PCMGSetRestriction(pc,i+1,mglevels[i+1]->interpolate);
664:         }
665:         if (mglevels[i+1]->interpolate == mglevels[i+1]->restrct) {
666:           MatPtAP(dB,mglevels[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);
667:         } else {
668:           MatMatMatMult(mglevels[i+1]->restrct,dB,mglevels[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);
669:         }
670:         KSPSetOperators(mglevels[i]->smoothd,B,B);
671:         if (i != n-2) {PetscObjectDereference((PetscObject)dB);}
672:         dB = B;
673:       }
674:       if (n > 1) {PetscObjectDereference((PetscObject)dB);}
675:     } else {
676:       for (i=n-2; i>-1; i--) {
677:         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");
678:         if (!mglevels[i+1]->interpolate) {
679:           PCMGSetInterpolation(pc,i+1,mglevels[i+1]->restrct);
680:         }
681:         if (!mglevels[i+1]->restrct) {
682:           PCMGSetRestriction(pc,i+1,mglevels[i+1]->interpolate);
683:         }
684:         KSPGetOperators(mglevels[i]->smoothd,NULL,&B);
685:         if (mglevels[i+1]->interpolate == mglevels[i+1]->restrct) {
686:           MatPtAP(dB,mglevels[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);
687:         } else {
688:           MatMatMatMult(mglevels[i+1]->restrct,dB,mglevels[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);
689:         }
690:         KSPSetOperators(mglevels[i]->smoothd,B,B);
691:         dB   = B;
692:       }
693:     }
694:   } else if (!mg->galerkin && pc->dm && pc->dm->x) {
695:     /* need to restrict Jacobian location to coarser meshes for evaluation */
696:     for (i=n-2; i>-1; i--) {
697:       Mat R;
698:       Vec rscale;
699:       if (!mglevels[i]->smoothd->dm->x) {
700:         Vec *vecs;
701:         KSPCreateVecs(mglevels[i]->smoothd,1,&vecs,0,NULL);

703:         mglevels[i]->smoothd->dm->x = vecs[0];

705:         PetscFree(vecs);
706:       }
707:       PCMGGetRestriction(pc,i+1,&R);
708:       PCMGGetRScale(pc,i+1,&rscale);
709:       MatRestrict(R,mglevels[i+1]->smoothd->dm->x,mglevels[i]->smoothd->dm->x);
710:       VecPointwiseMult(mglevels[i]->smoothd->dm->x,mglevels[i]->smoothd->dm->x,rscale);
711:     }
712:   }
713:   if (!mg->galerkin && pc->dm) {
714:     for (i=n-2; i>=0; i--) {
715:       DM  dmfine,dmcoarse;
716:       Mat Restrict,Inject;
717:       Vec rscale;
718:       KSPGetDM(mglevels[i+1]->smoothd,&dmfine);
719:       KSPGetDM(mglevels[i]->smoothd,&dmcoarse);
720:       PCMGGetRestriction(pc,i+1,&Restrict);
721:       PCMGGetRScale(pc,i+1,&rscale);
722:       Inject = NULL;      /* Callback should create it if it needs Injection */
723:       DMRestrict(dmfine,Restrict,rscale,Inject,dmcoarse);
724:     }
725:   }

727:   if (!pc->setupcalled) {
728:     for (i=0; i<n; i++) {
729:       KSPSetFromOptions(mglevels[i]->smoothd);
730:     }
731:     for (i=1; i<n; i++) {
732:       if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) {
733:         KSPSetFromOptions(mglevels[i]->smoothu);
734:       }
735:     }
736:     /* insure that if either interpolation or restriction is set the other other one is set */
737:     for (i=1; i<n; i++) {
738:       PCMGGetInterpolation(pc,i,NULL);
739:       PCMGGetRestriction(pc,i,NULL);
740:     }
741:     for (i=0; i<n-1; i++) {
742:       if (!mglevels[i]->b) {
743:         Vec *vec;
744:         KSPCreateVecs(mglevels[i]->smoothd,1,&vec,0,NULL);
745:         PCMGSetRhs(pc,i,*vec);
746:         VecDestroy(vec);
747:         PetscFree(vec);
748:       }
749:       if (!mglevels[i]->r && i) {
750:         VecDuplicate(mglevels[i]->b,&tvec);
751:         PCMGSetR(pc,i,tvec);
752:         VecDestroy(&tvec);
753:       }
754:       if (!mglevels[i]->x) {
755:         VecDuplicate(mglevels[i]->b,&tvec);
756:         PCMGSetX(pc,i,tvec);
757:         VecDestroy(&tvec);
758:       }
759:     }
760:     if (n != 1 && !mglevels[n-1]->r) {
761:       /* PCMGSetR() on the finest level if user did not supply it */
762:       Vec *vec;
763:       KSPCreateVecs(mglevels[n-1]->smoothd,1,&vec,0,NULL);
764:       PCMGSetR(pc,n-1,*vec);
765:       VecDestroy(vec);
766:       PetscFree(vec);
767:     }
768:   }

770:   if (pc->dm) {
771:     /* need to tell all the coarser levels to rebuild the matrix using the DM for that level */
772:     for (i=0; i<n-1; i++) {
773:       if (mglevels[i]->smoothd->setupstage != KSP_SETUP_NEW) mglevels[i]->smoothd->setupstage = KSP_SETUP_NEWMATRIX;
774:     }
775:   }

777:   for (i=1; i<n; i++) {
778:     if (mglevels[i]->smoothu == mglevels[i]->smoothd || mg->am == PC_MG_FULL || mg->am == PC_MG_KASKADE || mg->cyclesperpcapply > 1){
779:       /* if doing only down then initial guess is zero */
780:       KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);
781:     }
782:     if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
783:     KSPSetUp(mglevels[i]->smoothd);
784:     if (mglevels[i]->smoothd->reason == KSP_DIVERGED_PCSETUP_FAILED) {
785:       pc->failedreason = PC_SUBPC_ERROR;
786:     }
787:     if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
788:     if (!mglevels[i]->residual) {
789:       Mat mat;
790:       KSPGetOperators(mglevels[i]->smoothd,NULL,&mat);
791:       PCMGSetResidual(pc,i,PCMGResidualDefault,mat);
792:     }
793:   }
794:   for (i=1; i<n; i++) {
795:     if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) {
796:       Mat          downmat,downpmat;

798:       /* check if operators have been set for up, if not use down operators to set them */
799:       KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,NULL);
800:       if (!opsset) {
801:         KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat);
802:         KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat);
803:       }

805:       KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);
806:       if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
807:       KSPSetUp(mglevels[i]->smoothu);
808:       if (mglevels[i]->smoothu->reason == KSP_DIVERGED_PCSETUP_FAILED) {
809:         pc->failedreason = PC_SUBPC_ERROR;
810:       }
811:       if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
812:     }
813:   }

815:   if (mglevels[0]->eventsmoothsetup) {PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);}
816:   KSPSetUp(mglevels[0]->smoothd);
817:   if (mglevels[0]->smoothd->reason == KSP_DIVERGED_PCSETUP_FAILED) {
818:     pc->failedreason = PC_SUBPC_ERROR;
819:   }
820:   if (mglevels[0]->eventsmoothsetup) {PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);}

822:   /*
823:      Dump the interpolation/restriction matrices plus the
824:    Jacobian/stiffness on each level. This allows MATLAB users to
825:    easily check if the Galerkin condition A_c = R A_f R^T is satisfied.

827:    Only support one or the other at the same time.
828:   */
829: #if defined(PETSC_USE_SOCKET_VIEWER)
830:   PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,NULL);
831:   if (dump) viewer = PETSC_VIEWER_SOCKET_(PetscObjectComm((PetscObject)pc));
832:   dump = PETSC_FALSE;
833: #endif
834:   PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,NULL);
835:   if (dump) viewer = PETSC_VIEWER_BINARY_(PetscObjectComm((PetscObject)pc));

837:   if (viewer) {
838:     for (i=1; i<n; i++) {
839:       MatView(mglevels[i]->restrct,viewer);
840:     }
841:     for (i=0; i<n; i++) {
842:       KSPGetPC(mglevels[i]->smoothd,&pc);
843:       MatView(pc->mat,viewer);
844:     }
845:   }
846:   return(0);
847: }

849: /* -------------------------------------------------------------------------------------*/

853: /*@
854:    PCMGGetLevels - Gets the number of levels to use with MG.

856:    Not Collective

858:    Input Parameter:
859: .  pc - the preconditioner context

861:    Output parameter:
862: .  levels - the number of levels

864:    Level: advanced

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

868: .seealso: PCMGSetLevels()
869: @*/
870: PetscErrorCode  PCMGGetLevels(PC pc,PetscInt *levels)
871: {
872:   PC_MG *mg = (PC_MG*)pc->data;

877:   *levels = mg->nlevels;
878:   return(0);
879: }

883: /*@
884:    PCMGSetType - Determines the form of multigrid to use:
885:    multiplicative, additive, full, or the Kaskade algorithm.

887:    Logically Collective on PC

889:    Input Parameters:
890: +  pc - the preconditioner context
891: -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
892:    PC_MG_FULL, PC_MG_KASKADE

894:    Options Database Key:
895: .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
896:    additive, full, kaskade

898:    Level: advanced

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

902: .seealso: PCMGSetLevels()
903: @*/
904: PetscErrorCode  PCMGSetType(PC pc,PCMGType form)
905: {
906:   PC_MG *mg = (PC_MG*)pc->data;

911:   mg->am = form;
912:   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
913:   else pc->ops->applyrichardson = NULL;
914:   return(0);
915: }

919: /*@
920:    PCMGGetType - Determines the form of multigrid to use:
921:    multiplicative, additive, full, or the Kaskade algorithm.

923:    Logically Collective on PC

925:    Input Parameter:
926: .  pc - the preconditioner context

928:    Output Parameter:
929: .  type - one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,PC_MG_FULL, PC_MG_KASKADE


932:    Level: advanced

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

936: .seealso: PCMGSetLevels()
937: @*/
938: PetscErrorCode  PCMGGetType(PC pc,PCMGType *type)
939: {
940:   PC_MG *mg = (PC_MG*)pc->data;

944:   *type = mg->am;
945:   return(0);
946: }

950: /*@
951:    PCMGSetCycleType - Sets the type cycles to use.  Use PCMGSetCycleTypeOnLevel() for more
952:    complicated cycling.

954:    Logically Collective on PC

956:    Input Parameters:
957: +  pc - the multigrid context
958: -  PC_MG_CYCLE_V or PC_MG_CYCLE_W

960:    Options Database Key:
961: .  -pc_mg_cycle_type <v,w>

963:    Level: advanced

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

967: .seealso: PCMGSetCycleTypeOnLevel()
968: @*/
969: PetscErrorCode  PCMGSetCycleType(PC pc,PCMGCycleType n)
970: {
971:   PC_MG        *mg        = (PC_MG*)pc->data;
972:   PC_MG_Levels **mglevels = mg->levels;
973:   PetscInt     i,levels;

977:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
979:   levels = mglevels[0]->levels;

981:   for (i=0; i<levels; i++) mglevels[i]->cycles = n;
982:   return(0);
983: }

987: /*@
988:    PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step
989:          of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used

991:    Logically Collective on PC

993:    Input Parameters:
994: +  pc - the multigrid context
995: -  n - number of cycles (default is 1)

997:    Options Database Key:
998: .  -pc_mg_multiplicative_cycles n

1000:    Level: advanced

1002:    Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType()

1004: .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid

1006: .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
1007: @*/
1008: PetscErrorCode  PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
1009: {
1010:   PC_MG        *mg        = (PC_MG*)pc->data;

1015:   mg->cyclesperpcapply = n;
1016:   return(0);
1017: }

1021: PetscErrorCode PCMGSetGalerkin_MG(PC pc,PetscBool use)
1022: {
1023:   PC_MG *mg = (PC_MG*)pc->data;

1026:   mg->galerkin = use ? 1 : 0;
1027:   return(0);
1028: }

1032: /*@
1033:    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
1034:       finest grid via the Galerkin process: A_i-1 = r_i * A_i * p_i

1036:    Logically Collective on PC

1038:    Input Parameters:
1039: +  pc - the multigrid context
1040: -  use - PETSC_TRUE to use the Galerkin process to compute coarse-level operators

1042:    Options Database Key:
1043: .  -pc_mg_galerkin <true,false>

1045:    Level: intermediate

1047:    Notes: Some codes that use PCMG such as PCGAMG use Galerkin internally while constructing the hierarchy and thus do not
1048:      use the PCMG construction of the coarser grids.

1050: .keywords: MG, set, Galerkin

1052: .seealso: PCMGGetGalerkin()

1054: @*/
1055: PetscErrorCode PCMGSetGalerkin(PC pc,PetscBool use)
1056: {

1061:   PetscTryMethod(pc,"PCMGSetGalerkin_C",(PC,PetscBool),(pc,use));
1062:   return(0);
1063: }

1067: /*@
1068:    PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
1069:       A_i-1 = r_i * A_i * p_i

1071:    Not Collective

1073:    Input Parameter:
1074: .  pc - the multigrid context

1076:    Output Parameter:
1077: .  galerkin - PETSC_TRUE or PETSC_FALSE

1079:    Options Database Key:
1080: .  -pc_mg_galerkin

1082:    Level: intermediate

1084: .keywords: MG, set, Galerkin

1086: .seealso: PCMGSetGalerkin()

1088: @*/
1089: PetscErrorCode  PCMGGetGalerkin(PC pc,PetscBool  *galerkin)
1090: {
1091:   PC_MG *mg = (PC_MG*)pc->data;

1095:   *galerkin = (PetscBool)mg->galerkin;
1096:   return(0);
1097: }

1101: /*@
1102:    PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to
1103:    use on all levels. Use PCMGGetSmootherDown() to set different
1104:    pre-smoothing steps on different levels.

1106:    Logically Collective on PC

1108:    Input Parameters:
1109: +  mg - the multigrid context
1110: -  n - the number of smoothing steps

1112:    Options Database Key:
1113: .  -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps

1115:    Level: advanced

1117: .keywords: MG, smooth, down, pre-smoothing, steps, multigrid

1119: .seealso: PCMGSetNumberSmoothUp()
1120: @*/
1121: PetscErrorCode  PCMGSetNumberSmoothDown(PC pc,PetscInt n)
1122: {
1123:   PC_MG          *mg        = (PC_MG*)pc->data;
1124:   PC_MG_Levels   **mglevels = mg->levels;
1126:   PetscInt       i,levels;

1130:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1132:   levels = mglevels[0]->levels;

1134:   for (i=1; i<levels; i++) {
1135:     /* make sure smoother up and down are different */
1136:     PCMGGetSmootherUp(pc,i,NULL);
1137:     KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);

1139:     mg->default_smoothd = n;
1140:   }
1141:   return(0);
1142: }

1146: /*@
1147:    PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use
1148:    on all levels. Use PCMGGetSmootherUp() to set different numbers of
1149:    post-smoothing steps on different levels.

1151:    Logically Collective on PC

1153:    Input Parameters:
1154: +  mg - the multigrid context
1155: -  n - the number of smoothing steps

1157:    Options Database Key:
1158: .  -pc_mg_smoothup <n> - Sets number of post-smoothing steps

1160:    Level: advanced

1162:    Note: this does not set a value on the coarsest grid, since we assume that
1163:     there is no separate smooth up on the coarsest grid.

1165: .keywords: MG, smooth, up, post-smoothing, steps, multigrid

1167: .seealso: PCMGSetNumberSmoothDown()
1168: @*/
1169: PetscErrorCode  PCMGSetNumberSmoothUp(PC pc,PetscInt n)
1170: {
1171:   PC_MG          *mg        = (PC_MG*)pc->data;
1172:   PC_MG_Levels   **mglevels = mg->levels;
1174:   PetscInt       i,levels;

1178:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1180:   levels = mglevels[0]->levels;

1182:   for (i=1; i<levels; i++) {
1183:     /* make sure smoother up and down are different */
1184:     PCMGGetSmootherUp(pc,i,NULL);
1185:     KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);

1187:     mg->default_smoothu = n;
1188:   }
1189:   return(0);
1190: }

1192: /* ----------------------------------------------------------------------------------------*/

1194: /*MC
1195:    PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional
1196:     information about the coarser grid matrices and restriction/interpolation operators.

1198:    Options Database Keys:
1199: +  -pc_mg_levels <nlevels> - number of levels including finest
1200: .  -pc_mg_cycle_type <v,w> - 
1201: .  -pc_mg_smoothup <n> - number of smoothing steps after interpolation
1202: .  -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator
1203: .  -pc_mg_type <additive,multiplicative,full,kaskade> - multiplicative is the default
1204: .  -pc_mg_log - log information about time spent on each level of the solver
1205: .  -pc_mg_galerkin - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R'
1206: .  -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1)
1207: .  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
1208:                         to the Socket viewer for reading from MATLAB.
1209: -  -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices
1210:                         to the binary output file called binaryoutput

1212:    Notes: If one uses a Krylov method such GMRES or CG as the smoother than one must use KSPFGMRES, KSPGCG, or KSPRICHARDSON as the outer Krylov method

1214:        When run with a single level the smoother options are used on that level NOT the coarse grid solver options

1216:    Level: intermediate

1218:    Concepts: multigrid/multilevel

1220: .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE
1221:            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(),
1222:            PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
1223:            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
1224:            PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
1225: M*/

1229: PETSC_EXTERN PetscErrorCode PCCreate_MG(PC pc)
1230: {
1231:   PC_MG          *mg;

1235:   PetscNewLog(pc,&mg);
1236:   pc->data    = (void*)mg;
1237:   mg->nlevels = -1;
1238:   mg->am      = PC_MG_MULTIPLICATIVE;

1240:   pc->useAmat = PETSC_TRUE;

1242:   pc->ops->apply          = PCApply_MG;
1243:   pc->ops->setup          = PCSetUp_MG;
1244:   pc->ops->reset          = PCReset_MG;
1245:   pc->ops->destroy        = PCDestroy_MG;
1246:   pc->ops->setfromoptions = PCSetFromOptions_MG;
1247:   pc->ops->view           = PCView_MG;

1249:   PetscObjectComposeFunction((PetscObject)pc,"PCMGSetGalerkin_C",PCMGSetGalerkin_MG);
1250:   return(0);
1251: }