Actual source code: mg.c
petsc-3.7.1 2016-05-15
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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: By default this uses GMRES on the fine grid smoother so this should be used with KSPFGMRES or the smoother changed to not use GMRES

    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: }