Actual source code: mg.c
petsc-3.10.5 2019-03-28
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      2: /*
      3:     Defines the multigrid preconditioner interface.
      4: */
      5:  #include <petsc/private/pcmgimpl.h>
      6:  #include <petscdm.h>
      7: PETSC_INTERN PetscErrorCode PCPreSolveChangeRHS(PC,PetscBool*);

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

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

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

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

     66: static PetscErrorCode PCApplyRichardson_MG(PC pc,Vec b,Vec x,Vec w,PetscReal rtol,PetscReal abstol, PetscReal dtol,PetscInt its,PetscBool zeroguess,PetscInt *outits,PCRichardsonConvergedReason *reason)
     67: {
     68:   PC_MG          *mg        = (PC_MG*)pc->data;
     69:   PC_MG_Levels   **mglevels = mg->levels;
     71:   PC             tpc;
     72:   PetscBool      changeu,changed;
     73:   PetscInt       levels = mglevels[0]->levels,i;

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

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

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

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

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

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

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

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

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

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

    179:    Logically Collective on PC

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

    187:    Level: intermediate

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

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

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

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

    231:   mg->nlevels = levels;

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

    236:   PCGetOptionsPrefix(pc,&prefix);

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    916:    Not Collective

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

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

    924:    Level: advanced

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

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

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

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

    945:    Logically Collective on PC

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

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

    956:    Level: advanced

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

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

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

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

    979:    Logically Collective on PC

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

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

    988:    Level: advanced

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

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

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

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

    1008:    Logically Collective on PC

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

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

    1017:    Level: advanced

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

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

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

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

    1042:    Logically Collective on PC

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

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

    1051:    Level: advanced

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

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

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

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

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

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

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

    1084:    Logically Collective on PC

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

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

    1093:    Level: intermediate

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

    1099: .keywords: MG, set, Galerkin

    1101: .seealso: PCMGGetGalerkin(), PCMGGalerkinType

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

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

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

    1118:    Not Collective

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

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

    1126:    Level: intermediate

    1128: .keywords: MG, set, Galerkin

    1130: .seealso: PCMGSetGalerkin(), PCMGGalerkinType

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

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

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

    1148:    Logically Collective on PC

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

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

    1157:    Level: advanced

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

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

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

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

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

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

    1193:    Logically Collective on PC

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

    1198:    Options Database Key:
    1199: .  -pc_mg_distinct_smoothup

    1201:    Level: advanced

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

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

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

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

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

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

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

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

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

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

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

    1264:    Level: intermediate

    1266:    Concepts: multigrid/multilevel

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

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

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

    1287:   pc->useAmat = PETSC_TRUE;

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

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