Actual source code: mg.c

  1: #define PETSCKSP_DLL

  3: /*
  4:     Defines the multigrid preconditioner interface.
  5: */
 6:  #include src/ksp/pc/impls/mg/mgimpl.h


 11: PetscErrorCode PCMGMCycle_Private(PC_MG **mglevels,PetscTruth *converged)
 12: {
 13:   PC_MG          *mg = *mglevels,*mgc;
 15:   PetscInt       cycles = (PetscInt) mg->cycles;

 18:   if (converged) *converged = PETSC_FALSE;

 21:   KSPSolve(mg->smoothd,mg->b,mg->x);  /* pre-smooth */
 23:   if (mg->level) {  /* not the coarsest grid */
 25:     (*mg->residual)(mg->A,mg->b,mg->x,mg->r);

 28:     /* if on finest level and have convergence criteria set */
 29:     if (mg->level == mg->levels-1 && mg->ttol) {
 30:       PetscReal rnorm;
 31:       VecNorm(mg->r,NORM_2,&rnorm);
 32:       if (rnorm <= mg->ttol) {
 33:         *converged = PETSC_TRUE;
 34:         if (rnorm < mg->abstol) {
 35:           PetscInfo2(0,"Linear solver has converged. Residual norm %G is less than absolute tolerance %G\n",rnorm,mg->abstol);
 36:         } else {
 37:           PetscInfo2(0,"Linear solver has converged. Residual norm %G is less than relative tolerance times initial residual norm %G\n",rnorm,mg->ttol);
 38:         }
 39:         return(0);
 40:       }
 41:     }

 43:     mgc = *(mglevels - 1);
 45:     MatRestrict(mg->restrct,mg->r,mgc->b);
 47:     VecSet(mgc->x,0.0);
 48:     while (cycles--) {
 49:       PCMGMCycle_Private(mglevels-1,converged);
 50:     }
 52:     MatInterpolateAdd(mg->interpolate,mgc->x,mg->x,mg->x);
 55:     KSPSolve(mg->smoothu,mg->b,mg->x);    /* post smooth */
 57:   }
 58:   return(0);
 59: }

 61: /*
 62:        PCMGCreate_Private - Creates a PC_MG structure for use with the
 63:                multigrid code. Level 0 is the coarsest. (But the 
 64:                finest level is stored first in the array).

 66: */
 69: static PetscErrorCode PCMGCreate_Private(MPI_Comm comm,PetscInt levels,PC pc,MPI_Comm *comms,PC_MG ***result)
 70: {
 71:   PC_MG          **mg;
 73:   PetscInt       i;
 74:   PetscMPIInt    size;
 75:   const char     *prefix;
 76:   PC             ipc;

 79:   PetscMalloc(levels*sizeof(PC_MG*),&mg);
 80:   PetscLogObjectMemory(pc,levels*(sizeof(PC_MG*)+sizeof(PC_MG)));

 82:   PCGetOptionsPrefix(pc,&prefix);

 84:   for (i=0; i<levels; i++) {
 85:     PetscNew(PC_MG,&mg[i]);
 86:     mg[i]->level           = i;
 87:     mg[i]->levels          = levels;
 88:     mg[i]->cycles          = PC_MG_CYCLE_V;
 89:     mg[i]->galerkin        = PETSC_FALSE;
 90:     mg[i]->galerkinused    = PETSC_FALSE;
 91:     mg[i]->default_smoothu = 1;
 92:     mg[i]->default_smoothd = 1;

 94:     if (comms) comm = comms[i];
 95:     KSPCreate(comm,&mg[i]->smoothd);
 96:     KSPSetTolerances(mg[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, mg[i]->default_smoothd);
 97:     KSPSetOptionsPrefix(mg[i]->smoothd,prefix);

 99:     /* do special stuff for coarse grid */
100:     if (!i && levels > 1) {
101:       KSPAppendOptionsPrefix(mg[0]->smoothd,"mg_coarse_");

103:       /* coarse solve is (redundant) LU by default */
104:       KSPSetType(mg[0]->smoothd,KSPPREONLY);
105:       KSPGetPC(mg[0]->smoothd,&ipc);
106:       MPI_Comm_size(comm,&size);
107:       if (size > 1) {
108:         PCSetType(ipc,PCREDUNDANT);
109:       } else {
110:         PCSetType(ipc,PCLU);
111:       }

113:     } else {
114:       char tprefix[128];
115:       sprintf(tprefix,"mg_levels_%d_",(int)i);
116:       KSPAppendOptionsPrefix(mg[i]->smoothd,tprefix);
117:     }
118:     PetscLogObjectParent(pc,mg[i]->smoothd);
119:     mg[i]->smoothu             = mg[i]->smoothd;
120:     mg[i]->rtol                = 0.0;
121:     mg[i]->abstol              = 0.0;
122:     mg[i]->dtol                = 0.0;
123:     mg[i]->ttol                = 0.0;
124:     mg[i]->eventsmoothsetup    = 0;
125:     mg[i]->eventsmoothsolve    = 0;
126:     mg[i]->eventresidual       = 0;
127:     mg[i]->eventinterprestrict = 0;
128:     mg[i]->cyclesperpcapply    = 1;
129:   }
130:   *result = mg;
131:   return(0);
132: }

136: static PetscErrorCode PCDestroy_MG(PC pc)
137: {
138:   PC_MG          **mg = (PC_MG**)pc->data;
140:   PetscInt       i,n = mg[0]->levels;

143:   for (i=0; i<n-1; i++) {
144:     if (mg[i+1]->r) {VecDestroy(mg[i+1]->r);}
145:     if (mg[i]->b) {VecDestroy(mg[i]->b);}
146:     if (mg[i]->x) {VecDestroy(mg[i]->x);}
147:     if (mg[i+1]->restrct) {MatDestroy(mg[i+1]->restrct);}
148:     if (mg[i+1]->interpolate) {MatDestroy(mg[i+1]->interpolate);}
149:   }

151:   for (i=0; i<n; i++) {
152:     if (mg[i]->smoothd != mg[i]->smoothu) {
153:       KSPDestroy(mg[i]->smoothd);
154:     }
155:     KSPDestroy(mg[i]->smoothu);
156:     PetscFree(mg[i]);
157:   }
158:   PetscFree(mg);
159:   return(0);
160: }



164: EXTERN PetscErrorCode PCMGACycle_Private(PC_MG**);
165: EXTERN PetscErrorCode PCMGFCycle_Private(PC_MG**);
166: EXTERN PetscErrorCode PCMGKCycle_Private(PC_MG**);

168: /*
169:    PCApply_MG - Runs either an additive, multiplicative, Kaskadic
170:              or full cycle of multigrid. 

172:   Note: 
173:   A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle(). 
174: */
177: static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
178: {
179:   PC_MG          **mg = (PC_MG**)pc->data;
181:   PetscInt       levels = mg[0]->levels,i;

184:   mg[levels-1]->b = b;
185:   mg[levels-1]->x = x;
186:   if (!mg[levels-1]->r && mg[0]->am != PC_MG_ADDITIVE && levels > 1) {
187:     Vec tvec;
188:     VecDuplicate(mg[levels-1]->b,&tvec);
189:     PCMGSetR(pc,levels-1,tvec);
190:     VecDestroy(tvec);
191:   }
192:   if (mg[0]->am == PC_MG_MULTIPLICATIVE) {
193:     VecSet(x,0.0);
194:     for (i=0; i<mg[0]->cyclesperpcapply; i++) {
195:       PCMGMCycle_Private(mg+levels-1,PETSC_NULL);
196:     }
197:   }
198:   else if (mg[0]->am == PC_MG_ADDITIVE) {
199:     PCMGACycle_Private(mg);
200:   }
201:   else if (mg[0]->am == PC_MG_KASKADE) {
202:     PCMGKCycle_Private(mg);
203:   }
204:   else {
205:     PCMGFCycle_Private(mg);
206:   }
207:   return(0);
208: }

212: static PetscErrorCode PCApplyRichardson_MG(PC pc,Vec b,Vec x,Vec w,PetscReal rtol,PetscReal abstol, PetscReal dtol,PetscInt its)
213: {
214:   PC_MG          **mg = (PC_MG**)pc->data;
216:   PetscInt       levels = mg[0]->levels;
217:   PetscTruth     converged = PETSC_FALSE;

220:   mg[levels-1]->b    = b;
221:   mg[levels-1]->x    = x;

223:   mg[levels-1]->rtol = rtol;
224:   mg[levels-1]->abstol = abstol;
225:   mg[levels-1]->dtol = dtol;
226:   if (rtol) {
227:     /* compute initial residual norm for relative convergence test */
228:     PetscReal rnorm;
229:     (*mg[levels-1]->residual)(mg[levels-1]->A,b,x,w);
230:     VecNorm(w,NORM_2,&rnorm);
231:     mg[levels-1]->ttol = PetscMax(rtol*rnorm,abstol);
232:   } else if (abstol) {
233:     mg[levels-1]->ttol = abstol;
234:   } else {
235:     mg[levels-1]->ttol = 0.0;
236:   }

238:   while (its-- && !converged) {
239:     PCMGMCycle_Private(mg+levels-1,&converged);
240:   }
241:   return(0);
242: }

246: PetscErrorCode PCSetFromOptions_MG(PC pc)
247: {
249:   PetscInt       m,levels = 1,cycles;
250:   PetscTruth     flg;
251:   PC_MG          **mg = (PC_MG**)pc->data;
252:   PCMGType       mgtype = PC_MG_ADDITIVE;
253:   PCMGCycleType  mgctype;

256:   PetscOptionsHead("Multigrid options");
257:     if (!pc->data) {
258:       PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);
259:       PCMGSetLevels(pc,levels,PETSC_NULL);
260:       mg = (PC_MG**)pc->data;
261:     }
262:     mgctype = (PCMGCycleType) mg[0]->cycles;
263:     PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);
264:     if (flg) {
265:       PCMGSetCycleType(pc,mgctype);
266:     };
267:     PetscOptionsName("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",&flg);
268:     if (flg) {
269:       PCMGSetGalerkin(pc);
270:     }
271:     PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",1,&m,&flg);
272:     if (flg) {
273:       PCMGSetNumberSmoothUp(pc,m);
274:     }
275:     PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",1,&m,&flg);
276:     if (flg) {
277:       PCMGSetNumberSmoothDown(pc,m);
278:     }
279:     PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);
280:     if (flg) {
281:       PCMGSetType(pc,mgtype);
282:     }
283:     if (mg[0]->am == PC_MG_MULTIPLICATIVE) {
284:       PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGSetLevels",mg[0]->cyclesperpcapply,&cycles,&flg);
285:       if (flg) {
286:         PCMGMultiplicativeSetCycles(pc,cycles);
287:       }
288:     }
289:     PetscOptionsName("-pc_mg_log","Log times for each multigrid level","None",&flg);
290:     if (flg) {
291:       PetscInt i;
292:       char     eventname[128];
293:       if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
294:       levels = mg[0]->levels;
295:       for (i=0; i<levels; i++) {
296:         sprintf(eventname,"MGSetup Level %d",(int)i);
298:         sprintf(eventname,"MGSmooth Level %d",(int)i);
300:         if (i) {
301:           sprintf(eventname,"MGResid Level %d",(int)i);
303:           sprintf(eventname,"MGInterp Level %d",(int)i);
305:         }
306:       }
307:     }
308:   PetscOptionsTail();
309:   return(0);
310: }

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

317: static PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
318: {
319:   PC_MG          **mg = (PC_MG**)pc->data;
321:   PetscInt       levels = mg[0]->levels,i;
322:   PetscTruth     iascii;

325:   PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
326:   if (iascii) {
327:     PetscViewerASCIIPrintf(viewer,"  MG: type is %s, levels=%D cycles=%s, pre-smooths=%D, post-smooths=%D\n",
328:                                   PCMGTypes[mg[0]->am],levels,(mg[0]->cycles == PC_MG_CYCLE_V) ? "v" : "w",
329:                                   mg[0]->default_smoothd,mg[0]->default_smoothu);
330:     if (mg[0]->galerkin) {
331:       PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices\n");
332:     }
333:     for (i=0; i<levels; i++) {
334:       if (!i) {
335:         PetscViewerASCIIPrintf(viewer,"Coarse gride solver -- level %D -------------------------------\n",i);
336:       } else {
337:         PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);
338:       }
339:       PetscViewerASCIIPushTab(viewer);
340:       KSPView(mg[i]->smoothd,viewer);
341:       PetscViewerASCIIPopTab(viewer);
342:       if (i && mg[i]->smoothd == mg[i]->smoothu) {
343:         PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");
344:       } else if (i){
345:         PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);
346:         PetscViewerASCIIPushTab(viewer);
347:         KSPView(mg[i]->smoothu,viewer);
348:         PetscViewerASCIIPopTab(viewer);
349:       }
350:     }
351:   } else {
352:     SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported for PCMG",((PetscObject)viewer)->type_name);
353:   }
354:   return(0);
355: }

357: /*
358:     Calls setup for the KSP on each level
359: */
362: static PetscErrorCode PCSetUp_MG(PC pc)
363: {
364:   PC_MG                   **mg = (PC_MG**)pc->data;
365:   PetscErrorCode          ierr;
366:   PetscInt                i,n = mg[0]->levels;
367:   PC                      cpc,mpc;
368:   PetscTruth              preonly,lu,redundant,cholesky,monitor = PETSC_FALSE,dump,opsset;
369:   PetscViewerASCIIMonitor ascii;
370:   PetscViewer             viewer = PETSC_NULL;
371:   MPI_Comm                comm;
372:   Mat                     dA,dB;
373:   MatStructure            uflag;
374:   Vec                     tvec;


378:   /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */
379:   /* so use those from global PC */
380:   /* Is this what we always want? What if user wants to keep old one? */
381:   KSPGetOperatorsSet(mg[n-1]->smoothd,PETSC_NULL,&opsset);
382:   KSPGetPC(mg[0]->smoothd,&cpc);
383:   KSPGetPC(mg[n-1]->smoothd,&mpc);
384:   if (!opsset || ((cpc->setupcalled == 1) && (mpc->setupcalled == 2))) {
385:     PetscInfo(pc,"Using outer operators to define finest grid operator \n  because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
386:     KSPSetOperators(mg[n-1]->smoothd,pc->mat,pc->pmat,pc->flag);
387:   }

389:   if (mg[0]->galerkin) {
390:     Mat B;
391:     mg[0]->galerkinused = PETSC_TRUE;
392:     /* currently only handle case where mat and pmat are the same on coarser levels */
393:     KSPGetOperators(mg[n-1]->smoothd,&dA,&dB,&uflag);
394:     if (!pc->setupcalled) {
395:       for (i=n-2; i>-1; i--) {
396:         MatPtAP(dB,mg[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);
397:         KSPSetOperators(mg[i]->smoothd,B,B,uflag);
398:         if (i != n-2) {PetscObjectDereference((PetscObject)dB);}
399:         dB   = B;
400:       }
401:       PetscObjectDereference((PetscObject)dB);
402:     } else {
403:       for (i=n-2; i>-1; i--) {
404:         KSPGetOperators(mg[i]->smoothd,PETSC_NULL,&B,PETSC_NULL);
405:         MatPtAP(dB,mg[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);
406:         KSPSetOperators(mg[i]->smoothd,B,B,uflag);
407:         dB   = B;
408:       }
409:     }
410:   }

412:   if (!pc->setupcalled) {
413:     PetscOptionsHasName(0,"-pc_mg_monitor",&monitor);
414: 
415:     for (i=0; i<n; i++) {
416:       if (monitor) {
417:         PetscObjectGetComm((PetscObject)mg[i]->smoothd,&comm);
418:         PetscViewerASCIIMonitorCreate(comm,"stdout",n-i,&ascii);
419:         KSPMonitorSet(mg[i]->smoothd,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);
420:       }
421:       KSPSetFromOptions(mg[i]->smoothd);
422:     }
423:     for (i=1; i<n; i++) {
424:       if (mg[i]->smoothu && (mg[i]->smoothu != mg[i]->smoothd)) {
425:         if (monitor) {
426:           PetscObjectGetComm((PetscObject)mg[i]->smoothu,&comm);
427:           PetscViewerASCIIMonitorCreate(comm,"stdout",n-i,&ascii);
428:           KSPMonitorSet(mg[i]->smoothu,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);
429:         }
430:         KSPSetFromOptions(mg[i]->smoothu);
431:       }
432:     }
433:     for (i=1; i<n; i++) {
434:       if (!mg[i]->residual) {
435:         Mat mat;
436:         KSPGetOperators(mg[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);
437:         PCMGSetResidual(pc,i,PCMGDefaultResidual,mat);
438:       }
439:       if (mg[i]->restrct && !mg[i]->interpolate) {
440:         PCMGSetInterpolation(pc,i,mg[i]->restrct);
441:       }
442:       if (!mg[i]->restrct && mg[i]->interpolate) {
443:         PCMGSetRestriction(pc,i,mg[i]->interpolate);
444:       }
445: #if defined(PETSC_USE_DEBUG)
446:       if (!mg[i]->restrct || !mg[i]->interpolate) {
447:         SETERRQ1(PETSC_ERR_ARG_WRONGSTATE,"Need to set restriction or interpolation on level %d",(int)i);
448:       }
449: #endif
450:     }
451:     for (i=0; i<n-1; i++) {
452:       if (!mg[i]->b) {
453:         Vec *vec;
454:         KSPGetVecs(mg[i]->smoothd,1,&vec,0,PETSC_NULL);
455:         PCMGSetRhs(pc,i,*vec);
456:         VecDestroy(*vec);
457:         PetscFree(vec);
458:       }
459:       if (!mg[i]->r && i) {
460:         VecDuplicate(mg[i]->b,&tvec);
461:         PCMGSetR(pc,i,tvec);
462:         VecDestroy(tvec);
463:       }
464:       if (!mg[i]->x) {
465:         VecDuplicate(mg[i]->b,&tvec);
466:         PCMGSetX(pc,i,tvec);
467:         VecDestroy(tvec);
468:       }
469:     }
470:   }


473:   for (i=1; i<n; i++) {
474:     if (mg[i]->smoothu == mg[i]->smoothd) {
475:       /* if doing only down then initial guess is zero */
476:       KSPSetInitialGuessNonzero(mg[i]->smoothd,PETSC_TRUE);
477:     }
479:     KSPSetUp(mg[i]->smoothd);
481:   }
482:   for (i=1; i<n; i++) {
483:     if (mg[i]->smoothu && mg[i]->smoothu != mg[i]->smoothd) {
484:       Mat          downmat,downpmat;
485:       MatStructure matflag;
486:       PetscTruth   opsset;

488:       /* check if operators have been set for up, if not use down operators to set them */
489:       KSPGetOperatorsSet(mg[i]->smoothu,&opsset,PETSC_NULL);
490:       if (!opsset) {
491:         KSPGetOperators(mg[i]->smoothd,&downmat,&downpmat,&matflag);
492:         KSPSetOperators(mg[i]->smoothu,downmat,downpmat,matflag);
493:       }

495:       KSPSetInitialGuessNonzero(mg[i]->smoothu,PETSC_TRUE);
497:       KSPSetUp(mg[i]->smoothu);
499:     }
500:   }

502:   /*
503:       If coarse solver is not direct method then DO NOT USE preonly 
504:   */
505:   PetscTypeCompare((PetscObject)mg[0]->smoothd,KSPPREONLY,&preonly);
506:   if (preonly) {
507:     PetscTypeCompare((PetscObject)cpc,PCLU,&lu);
508:     PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);
509:     PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);
510:     if (!lu && !redundant && !cholesky) {
511:       KSPSetType(mg[0]->smoothd,KSPGMRES);
512:     }
513:   }

515:   if (!pc->setupcalled) {
516:     if (monitor) {
517:       PetscObjectGetComm((PetscObject)mg[0]->smoothd,&comm);
518:       PetscViewerASCIIMonitorCreate(comm,"stdout",n,&ascii);
519:       KSPMonitorSet(mg[0]->smoothd,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);
520:     }
521:     KSPSetFromOptions(mg[0]->smoothd);
522:   }

525:   KSPSetUp(mg[0]->smoothd);

528:   /*
529:      Dump the interpolation/restriction matrices plus the 
530:    Jacobian/stiffness on each level. This allows Matlab users to 
531:    easily check if the Galerkin condition A_c = R A_f R^T is satisfied.

533:    Only support one or the other at the same time.
534:   */
535: #if defined(PETSC_USE_SOCKET_VIEWER)
536:   PetscOptionsHasName(pc->prefix,"-pc_mg_dump_matlab",&dump);
537:   if (dump) {
538:     viewer = PETSC_VIEWER_SOCKET_(pc->comm);
539:   }
540: #endif
541:   PetscOptionsHasName(pc->prefix,"-pc_mg_dump_binary",&dump);
542:   if (dump) {
543:     viewer = PETSC_VIEWER_BINARY_(pc->comm);
544:   }

546:   if (viewer) {
547:     for (i=1; i<n; i++) {
548:       MatView(mg[i]->restrct,viewer);
549:     }
550:     for (i=0; i<n; i++) {
551:       KSPGetPC(mg[i]->smoothd,&pc);
552:       MatView(pc->mat,viewer);
553:     }
554:   }
555:   return(0);
556: }

558: /* -------------------------------------------------------------------------------------*/

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

566:    Collective on PC

568:    Input Parameters:
569: +  pc - the preconditioner context
570: .  levels - the number of levels
571: -  comms - optional communicators for each level; this is to allow solving the coarser problems
572:            on smaller sets of processors. Use PETSC_NULL_OBJECT for default in Fortran

574:    Level: intermediate

576:    Notes:
577:      If the number of levels is one then the multigrid uses the -mg_levels prefix
578:   for setting the level options rather than the -mg_coarse prefix.

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

582: .seealso: PCMGSetType(), PCMGGetLevels()
583: @*/
584: PetscErrorCode  PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
585: {
587:   PC_MG          **mg=0;


592:   if (pc->data) {
593:     SETERRQ(PETSC_ERR_ORDER,"Number levels already set for MG\n\
594:     make sure that you call PCMGSetLevels() before KSPSetFromOptions()");
595:   }
596:   PCMGCreate_Private(pc->comm,levels,pc,comms,&mg);
597:   mg[0]->am                = PC_MG_MULTIPLICATIVE;
598:   pc->data                 = (void*)mg;
599:   pc->ops->applyrichardson = PCApplyRichardson_MG;
600:   return(0);
601: }

605: /*@
606:    PCMGGetLevels - Gets the number of levels to use with MG.

608:    Not Collective

610:    Input Parameter:
611: .  pc - the preconditioner context

613:    Output parameter:
614: .  levels - the number of levels

616:    Level: advanced

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

620: .seealso: PCMGSetLevels()
621: @*/
622: PetscErrorCode  PCMGGetLevels(PC pc,PetscInt *levels)
623: {
624:   PC_MG  **mg;


630:   mg      = (PC_MG**)pc->data;
631:   *levels = mg[0]->levels;
632:   return(0);
633: }

637: /*@
638:    PCMGSetType - Determines the form of multigrid to use:
639:    multiplicative, additive, full, or the Kaskade algorithm.

641:    Collective on PC

643:    Input Parameters:
644: +  pc - the preconditioner context
645: -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
646:    PC_MG_FULL, PC_MG_KASKADE

648:    Options Database Key:
649: .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
650:    additive, full, kaskade   

652:    Level: advanced

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

656: .seealso: PCMGSetLevels()
657: @*/
658: PetscErrorCode  PCMGSetType(PC pc,PCMGType form)
659: {
660:   PC_MG **mg;

664:   mg = (PC_MG**)pc->data;

666:   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
667:   mg[0]->am = form;
668:   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
669:   else pc->ops->applyrichardson = 0;
670:   return(0);
671: }

675: /*@
676:    PCMGSetCycleType - Sets the type cycles to use.  Use PCMGSetCycleTypeOnLevel() for more 
677:    complicated cycling.

679:    Collective on PC

681:    Input Parameters:
682: +  pc - the multigrid context 
683: -  PC_MG_CYCLE_V or PC_MG_CYCLE_W

685:    Options Database Key:
686: $  -pc_mg_cycle_type v or w

688:    Level: advanced

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

692: .seealso: PCMGSetCycleTypeOnLevel()
693: @*/
694: PetscErrorCode  PCMGSetCycleType(PC pc,PCMGCycleType n)
695: {
696:   PC_MG    **mg;
697:   PetscInt i,levels;

701:   mg     = (PC_MG**)pc->data;
702:   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
703:   levels = mg[0]->levels;

705:   for (i=0; i<levels; i++) {
706:     mg[i]->cycles  = n;
707:   }
708:   return(0);
709: }

713: /*@
714:    PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step 
715:          of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used

717:    Collective on PC

719:    Input Parameters:
720: +  pc - the multigrid context 
721: -  n - number of cycles (default is 1)

723:    Options Database Key:
724: $  -pc_mg_multiplicative_cycles n

726:    Level: advanced

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

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

732: .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
733: @*/
734: PetscErrorCode  PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
735: {
736:   PC_MG    **mg;
737:   PetscInt i,levels;

741:   mg     = (PC_MG**)pc->data;
742:   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
743:   levels = mg[0]->levels;

745:   for (i=0; i<levels; i++) {
746:     mg[i]->cyclesperpcapply  = n;
747:   }
748:   return(0);
749: }

753: /*@
754:    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
755:       finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t

757:    Collective on PC

759:    Input Parameters:
760: .  pc - the multigrid context 

762:    Options Database Key:
763: $  -pc_mg_galerkin

765:    Level: intermediate

767: .keywords: MG, set, Galerkin

769: .seealso: PCMGGetGalerkin()

771: @*/
772: PetscErrorCode  PCMGSetGalerkin(PC pc)
773: {
774:   PC_MG    **mg;
775:   PetscInt i,levels;

779:   mg     = (PC_MG**)pc->data;
780:   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
781:   levels = mg[0]->levels;

783:   for (i=0; i<levels; i++) {
784:     mg[i]->galerkin = PETSC_TRUE;
785:   }
786:   return(0);
787: }

791: /*@
792:    PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
793:       A_i-1 = r_i * A_i * r_i^t

795:    Not Collective

797:    Input Parameter:
798: .  pc - the multigrid context 

800:    Output Parameter:
801: .  gelerkin - PETSC_TRUE or PETSC_FALSE

803:    Options Database Key:
804: $  -pc_mg_galerkin

806:    Level: intermediate

808: .keywords: MG, set, Galerkin

810: .seealso: PCMGSetGalerkin()

812: @*/
813: PetscErrorCode  PCMGGetGalerkin(PC pc,PetscTruth *galerkin)
814: {
815:   PC_MG    **mg;

819:   mg     = (PC_MG**)pc->data;
820:   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
821:   *galerkin = mg[0]->galerkin;
822:   return(0);
823: }

827: /*@
828:    PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to
829:    use on all levels. Use PCMGGetSmootherDown() to set different 
830:    pre-smoothing steps on different levels.

832:    Collective on PC

834:    Input Parameters:
835: +  mg - the multigrid context 
836: -  n - the number of smoothing steps

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

841:    Level: advanced

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

845: .seealso: PCMGSetNumberSmoothUp()
846: @*/
847: PetscErrorCode  PCMGSetNumberSmoothDown(PC pc,PetscInt n)
848: {
849:   PC_MG          **mg;
851:   PetscInt       i,levels;

855:   mg     = (PC_MG**)pc->data;
856:   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
857:   levels = mg[0]->levels;

859:   for (i=1; i<levels; i++) {
860:     /* make sure smoother up and down are different */
861:     PCMGGetSmootherUp(pc,i,PETSC_NULL);
862:     KSPSetTolerances(mg[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
863:     mg[i]->default_smoothd = n;
864:   }
865:   return(0);
866: }

870: /*@
871:    PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use 
872:    on all levels. Use PCMGGetSmootherUp() to set different numbers of 
873:    post-smoothing steps on different levels.

875:    Collective on PC

877:    Input Parameters:
878: +  mg - the multigrid context 
879: -  n - the number of smoothing steps

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

884:    Level: advanced

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

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

891: .seealso: PCMGSetNumberSmoothDown()
892: @*/
893: PetscErrorCode  PCMGSetNumberSmoothUp(PC pc,PetscInt n)
894: {
895:   PC_MG          **mg;
897:   PetscInt       i,levels;

901:   mg     = (PC_MG**)pc->data;
902:   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
903:   levels = mg[0]->levels;

905:   for (i=1; i<levels; i++) {
906:     /* make sure smoother up and down are different */
907:     PCMGGetSmootherUp(pc,i,PETSC_NULL);
908:     KSPSetTolerances(mg[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
909:     mg[i]->default_smoothu = n;
910:   }
911:   return(0);
912: }

914: /* ----------------------------------------------------------------------------------------*/

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

920:    Options Database Keys:
921: +  -pc_mg_levels <nlevels> - number of levels including finest
922: .  -pc_mg_cycles v or w
923: .  -pc_mg_smoothup <n> - number of smoothing steps after interpolation
924: .  -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator
925: .  -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default
926: .  -pc_mg_log - log information about time spent on each level of the solver
927: .  -pc_mg_monitor - print information on the multigrid convergence
928: .  -pc_mg_galerkin - use Galerkin process to compute coarser operators
929: -  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
930:                         to the Socket viewer for reading from Matlab.

932:    Notes:

934:    Level: intermediate

936:    Concepts: multigrid/multilevel

938: .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, 
939:            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(),
940:            PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
941:            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
942:            PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()           
943: M*/

948: PetscErrorCode  PCCreate_MG(PC pc)
949: {
951:   pc->ops->apply          = PCApply_MG;
952:   pc->ops->setup          = PCSetUp_MG;
953:   pc->ops->destroy        = PCDestroy_MG;
954:   pc->ops->setfromoptions = PCSetFromOptions_MG;
955:   pc->ops->view           = PCView_MG;

957:   pc->data                = (void*)0;
958:   return(0);
959: }