Actual source code: mg.c

petsc-3.15.0 2021-03-30
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  2: /*
  3:     Defines the multigrid preconditioner interface.
  4: */
  5: #include <petsc/private/pcmgimpl.h>
  6: #include <petsc/private/kspimpl.h>
  7: #include <petscdm.h>
  8: PETSC_INTERN PetscErrorCode PCPreSolveChangeRHS(PC,PetscBool*);

 10: /*
 11:    Contains the list of registered coarse space construction routines
 12: */
 13: PetscFunctionList PCMGCoarseList = NULL;

 15: PetscErrorCode PCMGMCycle_Private(PC pc,PC_MG_Levels **mglevelsin,PetscBool transpose,PetscBool matapp,PCRichardsonConvergedReason *reason)
 16: {
 17:   PC_MG          *mg = (PC_MG*)pc->data;
 18:   PC_MG_Levels   *mgc,*mglevels = *mglevelsin;
 20:   PetscInt       cycles = (mglevels->level == 1) ? 1 : (PetscInt) mglevels->cycles;

 23:   if (mglevels->eventsmoothsolve) {PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);}
 24:   if (!transpose) {
 25:     if (matapp) {
 26:       KSPMatSolve(mglevels->smoothd,mglevels->B,mglevels->X);  /* pre-smooth */
 27:       KSPCheckSolve(mglevels->smoothd,pc,NULL);
 28:     } else {
 29:       KSPSolve(mglevels->smoothd,mglevels->b,mglevels->x);  /* pre-smooth */
 30:       KSPCheckSolve(mglevels->smoothd,pc,mglevels->x);
 31:     }
 32:   } else {
 33:     if (matapp) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_SUP,"Not supported");
 34:     KSPSolveTranspose(mglevels->smoothu,mglevels->b,mglevels->x); /* transpose of post-smooth */
 35:     KSPCheckSolve(mglevels->smoothu,pc,mglevels->x);
 36:   }
 37:   if (mglevels->eventsmoothsolve) {PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);}
 38:   if (mglevels->level) {  /* not the coarsest grid */
 39:     if (mglevels->eventresidual) {PetscLogEventBegin(mglevels->eventresidual,0,0,0,0);}
 40:     if (matapp && !mglevels->R) {
 41:       MatDuplicate(mglevels->B,MAT_DO_NOT_COPY_VALUES,&mglevels->R);
 42:     }
 43:     if (!transpose) {
 44:       if (matapp) { (*mglevels->matresidual)(mglevels->A,mglevels->B,mglevels->X,mglevels->R); }
 45:       else { (*mglevels->residual)(mglevels->A,mglevels->b,mglevels->x,mglevels->r); }
 46:     } else {
 47:       if (matapp) { (*mglevels->matresidualtranspose)(mglevels->A,mglevels->B,mglevels->X,mglevels->R); }
 48:       else { (*mglevels->residualtranspose)(mglevels->A,mglevels->b,mglevels->x,mglevels->r); }
 49:     }
 50:     if (mglevels->eventresidual) {PetscLogEventEnd(mglevels->eventresidual,0,0,0,0);}

 52:     /* if on finest level and have convergence criteria set */
 53:     if (mglevels->level == mglevels->levels-1 && mg->ttol && reason) {
 54:       PetscReal rnorm;
 55:       VecNorm(mglevels->r,NORM_2,&rnorm);
 56:       if (rnorm <= mg->ttol) {
 57:         if (rnorm < mg->abstol) {
 58:           *reason = PCRICHARDSON_CONVERGED_ATOL;
 59:           PetscInfo2(pc,"Linear solver has converged. Residual norm %g is less than absolute tolerance %g\n",(double)rnorm,(double)mg->abstol);
 60:         } else {
 61:           *reason = PCRICHARDSON_CONVERGED_RTOL;
 62:           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);
 63:         }
 64:         return(0);
 65:       }
 66:     }

 68:     mgc = *(mglevelsin - 1);
 69:     if (mglevels->eventinterprestrict) {PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);}
 70:     if (!transpose) {
 71:       if (matapp) { MatMatRestrict(mglevels->restrct,mglevels->R,&mgc->B); }
 72:       else { MatRestrict(mglevels->restrct,mglevels->r,mgc->b); }
 73:     } else {
 74:       if (matapp) { MatMatRestrict(mglevels->interpolate,mglevels->R,&mgc->B); }
 75:       else { MatRestrict(mglevels->interpolate,mglevels->r,mgc->b); }
 76:     }
 77:     if (mglevels->eventinterprestrict) {PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);}
 78:     if (matapp) {
 79:       if (!mgc->X) {
 80:         MatDuplicate(mgc->B,MAT_DO_NOT_COPY_VALUES,&mgc->X);
 81:       } else {
 82:         MatZeroEntries(mgc->X);
 83:       }
 84:     } else {
 85:       VecZeroEntries(mgc->x);
 86:     }
 87:     while (cycles--) {
 88:       PCMGMCycle_Private(pc,mglevelsin-1,transpose,matapp,reason);
 89:     }
 90:     if (mglevels->eventinterprestrict) {PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);}
 91:     if (!transpose) {
 92:       if (matapp) { MatMatInterpolateAdd(mglevels->interpolate,mgc->X,mglevels->X,&mglevels->X); }
 93:       else { MatInterpolateAdd(mglevels->interpolate,mgc->x,mglevels->x,mglevels->x); }
 94:     } else {
 95:       MatInterpolateAdd(mglevels->restrct,mgc->x,mglevels->x,mglevels->x);
 96:     }
 97:     if (mglevels->eventinterprestrict) {PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);}
 98:     if (mglevels->eventsmoothsolve) {PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);}
 99:     if (!transpose) {
100:       if (matapp) {
101:         KSPMatSolve(mglevels->smoothu,mglevels->B,mglevels->X);    /* post smooth */
102:         KSPCheckSolve(mglevels->smoothu,pc,NULL);
103:       } else {
104:         KSPSolve(mglevels->smoothu,mglevels->b,mglevels->x);    /* post smooth */
105:         KSPCheckSolve(mglevels->smoothu,pc,mglevels->x);
106:       }
107:     } else {
108:       if (matapp) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_SUP,"Not supported");
109:       KSPSolveTranspose(mglevels->smoothd,mglevels->b,mglevels->x);    /* post smooth */
110:       KSPCheckSolve(mglevels->smoothd,pc,mglevels->x);
111:     }
112:     if (mglevels->cr) {
113:       if (matapp) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_SUP,"Not supported");
114:       /* TODO Turn on copy and turn off noisy if we have an exact solution
115:       VecCopy(mglevels->x, mglevels->crx);
116:       VecCopy(mglevels->b, mglevels->crb); */
117:       KSPSetNoisy_Private(mglevels->crx);
118:       KSPSolve(mglevels->cr,mglevels->crb,mglevels->crx);    /* compatible relaxation */
119:       KSPCheckSolve(mglevels->cr,pc,mglevels->crx);
120:     }
121:     if (mglevels->eventsmoothsolve) {PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);}
122:   }
123:   return(0);
124: }

126: 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)
127: {
128:   PC_MG          *mg        = (PC_MG*)pc->data;
129:   PC_MG_Levels   **mglevels = mg->levels;
131:   PC             tpc;
132:   PetscBool      changeu,changed;
133:   PetscInt       levels = mglevels[0]->levels,i;

136:   /* When the DM is supplying the matrix then it will not exist until here */
137:   for (i=0; i<levels; i++) {
138:     if (!mglevels[i]->A) {
139:       KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);
140:       PetscObjectReference((PetscObject)mglevels[i]->A);
141:     }
142:   }

144:   KSPGetPC(mglevels[levels-1]->smoothd,&tpc);
145:   PCPreSolveChangeRHS(tpc,&changed);
146:   KSPGetPC(mglevels[levels-1]->smoothu,&tpc);
147:   PCPreSolveChangeRHS(tpc,&changeu);
148:   if (!changed && !changeu) {
149:     VecDestroy(&mglevels[levels-1]->b);
150:     mglevels[levels-1]->b = b;
151:   } else { /* if the smoother changes the rhs during PreSolve, we cannot use the input vector */
152:     if (!mglevels[levels-1]->b) {
153:       Vec *vec;

155:       KSPCreateVecs(mglevels[levels-1]->smoothd,1,&vec,0,NULL);
156:       mglevels[levels-1]->b = *vec;
157:       PetscFree(vec);
158:     }
159:     VecCopy(b,mglevels[levels-1]->b);
160:   }
161:   mglevels[levels-1]->x = x;

163:   mg->rtol   = rtol;
164:   mg->abstol = abstol;
165:   mg->dtol   = dtol;
166:   if (rtol) {
167:     /* compute initial residual norm for relative convergence test */
168:     PetscReal rnorm;
169:     if (zeroguess) {
170:       VecNorm(b,NORM_2,&rnorm);
171:     } else {
172:       (*mglevels[levels-1]->residual)(mglevels[levels-1]->A,b,x,w);
173:       VecNorm(w,NORM_2,&rnorm);
174:     }
175:     mg->ttol = PetscMax(rtol*rnorm,abstol);
176:   } else if (abstol) mg->ttol = abstol;
177:   else mg->ttol = 0.0;

179:   /* since smoother is applied to full system, not just residual we need to make sure that smoothers don't
180:      stop prematurely due to small residual */
181:   for (i=1; i<levels; i++) {
182:     KSPSetTolerances(mglevels[i]->smoothu,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);
183:     if (mglevels[i]->smoothu != mglevels[i]->smoothd) {
184:       /* For Richardson the initial guess is nonzero since it is solving in each cycle the original system not just applying as a preconditioner */
185:       KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);
186:       KSPSetTolerances(mglevels[i]->smoothd,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);
187:     }
188:   }

190:   *reason = (PCRichardsonConvergedReason)0;
191:   for (i=0; i<its; i++) {
192:     PCMGMCycle_Private(pc,mglevels+levels-1,PETSC_FALSE,PETSC_FALSE,reason);
193:     if (*reason) break;
194:   }
195:   if (!*reason) *reason = PCRICHARDSON_CONVERGED_ITS;
196:   *outits = i;
197:   if (!changed && !changeu) mglevels[levels-1]->b = NULL;
198:   return(0);
199: }

201: PetscErrorCode PCReset_MG(PC pc)
202: {
203:   PC_MG          *mg        = (PC_MG*)pc->data;
204:   PC_MG_Levels   **mglevels = mg->levels;
206:   PetscInt       i,c,n;

209:   if (mglevels) {
210:     n = mglevels[0]->levels;
211:     for (i=0; i<n-1; i++) {
212:       VecDestroy(&mglevels[i+1]->r);
213:       VecDestroy(&mglevels[i]->b);
214:       VecDestroy(&mglevels[i]->x);
215:       MatDestroy(&mglevels[i+1]->R);
216:       MatDestroy(&mglevels[i]->B);
217:       MatDestroy(&mglevels[i]->X);
218:       VecDestroy(&mglevels[i]->crx);
219:       VecDestroy(&mglevels[i]->crb);
220:       MatDestroy(&mglevels[i+1]->restrct);
221:       MatDestroy(&mglevels[i+1]->interpolate);
222:       MatDestroy(&mglevels[i+1]->inject);
223:       VecDestroy(&mglevels[i+1]->rscale);
224:     }
225:     VecDestroy(&mglevels[n-1]->crx);
226:     VecDestroy(&mglevels[n-1]->crb);
227:     /* this is not null only if the smoother on the finest level
228:        changes the rhs during PreSolve */
229:     VecDestroy(&mglevels[n-1]->b);
230:     MatDestroy(&mglevels[n-1]->B);

232:     for (i=0; i<n; i++) {
233:       if (mglevels[i]->coarseSpace) for (c = 0; c < mg->Nc; ++c) {VecDestroy(&mglevels[i]->coarseSpace[c]);}
234:       PetscFree(mglevels[i]->coarseSpace);
235:       mglevels[i]->coarseSpace = NULL;
236:       MatDestroy(&mglevels[i]->A);
237:       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
238:         KSPReset(mglevels[i]->smoothd);
239:       }
240:       KSPReset(mglevels[i]->smoothu);
241:       if (mglevels[i]->cr) {KSPReset(mglevels[i]->cr);}
242:     }
243:     mg->Nc = 0;
244:   }
245:   return(0);
246: }

248: /* Implementing CR

250: We only want to make corrections that ``do not change'' the coarse solution. What we mean by not changing is that if I prolong my coarse solution to the fine grid and then inject that fine solution back to the coarse grid, I get the same answer. Injection is what Brannick calls R. We want the complementary projector to Inj, which we will call S, after Brannick, so that Inj S = 0. Now the orthogonal projector onto the range of Inj^T is

252:   Inj^T (Inj Inj^T)^{-1} Inj

254: and if Inj is a VecScatter, as it is now in PETSc, we have

256:   Inj^T Inj

258: and

260:   S = I - Inj^T Inj

262: since

264:   Inj S = Inj - (Inj Inj^T) Inj = 0.

266: Brannick suggests

268:   A \to S^T A S  \qquad\mathrm{and}\qquad M \to S^T M S

270: but I do not think his :math:`S^T S = I` is correct. Our S is an orthogonal projector, so :math:`S^T S = S^2 = S`. We will use

272:   M^{-1} A \to S M^{-1} A S

274: In fact, since it is somewhat hard in PETSc to do the symmetric application, we will just apply S on the left.

276:   Check: || Inj P - I ||_F < tol
277:   Check: In general, Inj Inj^T = I
278: */

280: typedef struct {
281:   PC       mg;  /* The PCMG object */
282:   PetscInt l;   /* The multigrid level for this solver */
283:   Mat      Inj; /* The injection matrix */
284:   Mat      S;   /* I - Inj^T Inj */
285: } CRContext;

287: static PetscErrorCode CRSetup_Private(PC pc)
288: {
289:   CRContext     *ctx;
290:   Mat            It;

294:   PCShellGetContext(pc, (void **) &ctx);
295:   PCMGGetInjection(ctx->mg, ctx->l, &It);
296:   if (!It) SETERRQ(PetscObjectComm((PetscObject) pc), PETSC_ERR_ARG_WRONGSTATE, "CR requires that injection be defined for this PCMG");
297:   MatCreateTranspose(It, &ctx->Inj);
298:   MatCreateNormal(ctx->Inj, &ctx->S);
299:   MatScale(ctx->S, -1.0);
300:   MatShift(ctx->S,  1.0);
301:   return(0);
302: }

304: static PetscErrorCode CRApply_Private(PC pc, Vec x, Vec y)
305: {
306:   CRContext     *ctx;

310:   PCShellGetContext(pc, (void **) &ctx);
311:   MatMult(ctx->S, x, y);
312:   return(0);
313: }

315: static PetscErrorCode CRDestroy_Private(PC pc)
316: {
317:   CRContext     *ctx;

321:   PCShellGetContext(pc, (void **) &ctx);
322:   MatDestroy(&ctx->Inj);
323:   MatDestroy(&ctx->S);
324:   PetscFree(ctx);
325:   PCShellSetContext(pc, NULL);
326:   return(0);
327: }

329: static PetscErrorCode CreateCR_Private(PC pc, PetscInt l, PC *cr)
330: {
331:   CRContext     *ctx;

335:   PCCreate(PetscObjectComm((PetscObject) pc), cr);
336:   PetscObjectSetName((PetscObject) *cr, "S (complementary projector to injection)");
337:   PetscCalloc1(1, &ctx);
338:   ctx->mg = pc;
339:   ctx->l  = l;
340:   PCSetType(*cr, PCSHELL);
341:   PCShellSetContext(*cr, ctx);
342:   PCShellSetApply(*cr, CRApply_Private);
343:   PCShellSetSetUp(*cr, CRSetup_Private);
344:   PCShellSetDestroy(*cr, CRDestroy_Private);
345:   return(0);
346: }

348: PetscErrorCode PCMGSetLevels_MG(PC pc,PetscInt levels,MPI_Comm *comms)
349: {
351:   PC_MG          *mg        = (PC_MG*)pc->data;
352:   MPI_Comm       comm;
353:   PC_MG_Levels   **mglevels = mg->levels;
354:   PCMGType       mgtype     = mg->am;
355:   PetscInt       mgctype    = (PetscInt) PC_MG_CYCLE_V;
356:   PetscInt       i;
357:   PetscMPIInt    size;
358:   const char     *prefix;
359:   PC             ipc;
360:   PetscInt       n;

365:   if (mg->nlevels == levels) return(0);
366:   PetscObjectGetComm((PetscObject)pc,&comm);
367:   if (mglevels) {
368:     mgctype = mglevels[0]->cycles;
369:     /* changing the number of levels so free up the previous stuff */
370:     PCReset_MG(pc);
371:     n    = mglevels[0]->levels;
372:     for (i=0; i<n; i++) {
373:       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
374:         KSPDestroy(&mglevels[i]->smoothd);
375:       }
376:       KSPDestroy(&mglevels[i]->smoothu);
377:       KSPDestroy(&mglevels[i]->cr);
378:       PetscFree(mglevels[i]);
379:     }
380:     PetscFree(mg->levels);
381:   }

383:   mg->nlevels = levels;

385:   PetscMalloc1(levels,&mglevels);
386:   PetscLogObjectMemory((PetscObject)pc,levels*(sizeof(PC_MG*)));

388:   PCGetOptionsPrefix(pc,&prefix);

390:   mg->stageApply = 0;
391:   for (i=0; i<levels; i++) {
392:     PetscNewLog(pc,&mglevels[i]);

394:     mglevels[i]->level               = i;
395:     mglevels[i]->levels              = levels;
396:     mglevels[i]->cycles              = mgctype;
397:     mg->default_smoothu              = 2;
398:     mg->default_smoothd              = 2;
399:     mglevels[i]->eventsmoothsetup    = 0;
400:     mglevels[i]->eventsmoothsolve    = 0;
401:     mglevels[i]->eventresidual       = 0;
402:     mglevels[i]->eventinterprestrict = 0;

404:     if (comms) comm = comms[i];
405:     if (comm != MPI_COMM_NULL) {
406:       KSPCreate(comm,&mglevels[i]->smoothd);
407:       KSPSetErrorIfNotConverged(mglevels[i]->smoothd,pc->erroriffailure);
408:       PetscObjectIncrementTabLevel((PetscObject)mglevels[i]->smoothd,(PetscObject)pc,levels-i);
409:       KSPSetOptionsPrefix(mglevels[i]->smoothd,prefix);
410:       PetscObjectComposedDataSetInt((PetscObject) mglevels[i]->smoothd, PetscMGLevelId, mglevels[i]->level);
411:       if (i || levels == 1) {
412:         char tprefix[128];

414:         KSPSetType(mglevels[i]->smoothd,KSPCHEBYSHEV);
415:         KSPSetConvergenceTest(mglevels[i]->smoothd,KSPConvergedSkip,NULL,NULL);
416:         KSPSetNormType(mglevels[i]->smoothd,KSP_NORM_NONE);
417:         KSPGetPC(mglevels[i]->smoothd,&ipc);
418:         PCSetType(ipc,PCSOR);
419:         KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, mg->default_smoothd);

421:         PetscSNPrintf(tprefix,128,"mg_levels_%d_",(int)i);
422:         KSPAppendOptionsPrefix(mglevels[i]->smoothd,tprefix);
423:       } else {
424:         KSPAppendOptionsPrefix(mglevels[0]->smoothd,"mg_coarse_");

426:         /* coarse solve is (redundant) LU by default; set shifttype NONZERO to avoid annoying zero-pivot in LU preconditioner */
427:         KSPSetType(mglevels[0]->smoothd,KSPPREONLY);
428:         KSPGetPC(mglevels[0]->smoothd,&ipc);
429:         MPI_Comm_size(comm,&size);
430:         if (size > 1) {
431:           PCSetType(ipc,PCREDUNDANT);
432:         } else {
433:           PCSetType(ipc,PCLU);
434:         }
435:         PCFactorSetShiftType(ipc,MAT_SHIFT_INBLOCKS);
436:       }
437:       PetscLogObjectParent((PetscObject)pc,(PetscObject)mglevels[i]->smoothd);
438:     }
439:     mglevels[i]->smoothu = mglevels[i]->smoothd;
440:     mg->rtol             = 0.0;
441:     mg->abstol           = 0.0;
442:     mg->dtol             = 0.0;
443:     mg->ttol             = 0.0;
444:     mg->cyclesperpcapply = 1;
445:   }
446:   mg->levels = mglevels;
447:   PCMGSetType(pc,mgtype);
448:   return(0);
449: }

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

455:    Logically Collective on PC

457:    Input Parameters:
458: +  pc - the preconditioner context
459: .  levels - the number of levels
460: -  comms - optional communicators for each level; this is to allow solving the coarser problems
461:            on smaller sets of processes. For processes that are not included in the computation
462:            you must pass MPI_COMM_NULL.

464:    Level: intermediate

466:    Notes:
467:      If the number of levels is one then the multigrid uses the -mg_levels prefix
468:      for setting the level options rather than the -mg_coarse prefix.

470:      You can free the information in comms after this routine is called.

472:      The array of MPI communicators must contain MPI_COMM_NULL for those ranks that at each level
473:      are not participating in the coarser solve. For example, with 2 levels and 1 and 2 ranks on
474:      the two levels, rank 0 in the original communicator will pass in an array of 2 communicators
475:      of size 2 and 1, while rank 1 in the original communicator will pass in array of 2 communicators
476:      the first of size 2 and the second of value MPI_COMM_NULL since the rank 1 does not participate
477:      in the coarse grid solve.

479:      Since each coarser level may have a new MPI_Comm with fewer ranks than the previous, one
480:      must take special care in providing the restriction and interpolation operation. We recommend
481:      providing these as two step operations; first perform a standard restriction or interpolation on
482:      the full number of ranks for that level and then use an MPI call to copy the resulting vector
483:      array entries (after calls to VecGetArray()) to the smaller or larger number of ranks, not in both
484:      cases the MPI calls must be made on the larger of the two communicators. Traditional MPI send and
485:      recieves or MPI_AlltoAllv() could be used to do the reshuffling of the vector entries.


488: .seealso: PCMGSetType(), PCMGGetLevels()
489: @*/
490: PetscErrorCode PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
491: {

497:   PetscTryMethod(pc,"PCMGSetLevels_C",(PC,PetscInt,MPI_Comm*),(pc,levels,comms));
498:   return(0);
499: }


502: PetscErrorCode PCDestroy_MG(PC pc)
503: {
505:   PC_MG          *mg        = (PC_MG*)pc->data;
506:   PC_MG_Levels   **mglevels = mg->levels;
507:   PetscInt       i,n;

510:   PCReset_MG(pc);
511:   if (mglevels) {
512:     n = mglevels[0]->levels;
513:     for (i=0; i<n; i++) {
514:       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
515:         KSPDestroy(&mglevels[i]->smoothd);
516:       }
517:       KSPDestroy(&mglevels[i]->smoothu);
518:       KSPDestroy(&mglevels[i]->cr);
519:       PetscFree(mglevels[i]);
520:     }
521:     PetscFree(mg->levels);
522:   }
523:   PetscFree(pc->data);
524:   PetscObjectComposeFunction((PetscObject)pc,"PCGetInterpolations_C",NULL);
525:   PetscObjectComposeFunction((PetscObject)pc,"PCGetCoarseOperators_C",NULL);
526:   return(0);
527: }


530: /*
531:    PCApply_MG - Runs either an additive, multiplicative, Kaskadic
532:              or full cycle of multigrid.

534:   Note:
535:   A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle().
536: */
537: static PetscErrorCode PCApply_MG_Internal(PC pc,Vec b,Vec x,Mat B,Mat X,PetscBool transpose)
538: {
539:   PC_MG          *mg        = (PC_MG*)pc->data;
540:   PC_MG_Levels   **mglevels = mg->levels;
542:   PC             tpc;
543:   PetscInt       levels = mglevels[0]->levels,i;
544:   PetscBool      changeu,changed,matapp;

547:   matapp = (PetscBool)(B && X);
548:   if (mg->stageApply) {PetscLogStagePush(mg->stageApply);}
549:   /* When the DM is supplying the matrix then it will not exist until here */
550:   for (i=0; i<levels; i++) {
551:     if (!mglevels[i]->A) {
552:       KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);
553:       PetscObjectReference((PetscObject)mglevels[i]->A);
554:     }
555:   }

557:   KSPGetPC(mglevels[levels-1]->smoothd,&tpc);
558:   PCPreSolveChangeRHS(tpc,&changed);
559:   KSPGetPC(mglevels[levels-1]->smoothu,&tpc);
560:   PCPreSolveChangeRHS(tpc,&changeu);
561:   if (!changeu && !changed) {
562:     if (matapp) {
563:       MatDestroy(&mglevels[levels-1]->B);
564:       mglevels[levels-1]->B = B;
565:     } else {
566:       VecDestroy(&mglevels[levels-1]->b);
567:       mglevels[levels-1]->b = b;
568:     }
569:   } else { /* if the smoother changes the rhs during PreSolve, we cannot use the input vector */
570:     if (matapp) {
571:       if (mglevels[levels-1]->B) {
572:         PetscInt  N1,N2;
573:         PetscBool flg;

575:         MatGetSize(mglevels[levels-1]->B,NULL,&N1);
576:         MatGetSize(B,NULL,&N2);
577:         PetscObjectTypeCompare((PetscObject)mglevels[levels-1]->B,((PetscObject)B)->type_name,&flg);
578:         if (N1 != N2 || !flg) {
579:           MatDestroy(&mglevels[levels-1]->B);
580:         }
581:       }
582:       if (!mglevels[levels-1]->B) {
583:         MatDuplicate(B,MAT_COPY_VALUES,&mglevels[levels-1]->B);
584:       } else {
585:         MatCopy(B,mglevels[levels-1]->B,SAME_NONZERO_PATTERN);
586:       }
587:     } else {
588:       if (!mglevels[levels-1]->b) {
589:         Vec *vec;

591:         KSPCreateVecs(mglevels[levels-1]->smoothd,1,&vec,0,NULL);
592:         mglevels[levels-1]->b = *vec;
593:         PetscFree(vec);
594:       }
595:       VecCopy(b,mglevels[levels-1]->b);
596:     }
597:   }
598:   if (matapp) { mglevels[levels-1]->X = X; }
599:   else { mglevels[levels-1]->x = x; }

601:   /* If coarser Xs are present, it means we have already block applied the PC at least once
602:      Reset operators if sizes/type do no match */
603:   if (matapp && levels > 1 && mglevels[levels-2]->X) {
604:     PetscInt  Xc,Bc;
605:     PetscBool flg;

607:     MatGetSize(mglevels[levels-2]->X,NULL,&Xc);
608:     MatGetSize(mglevels[levels-1]->B,NULL,&Bc);
609:     PetscObjectTypeCompare((PetscObject)mglevels[levels-2]->X,((PetscObject)mglevels[levels-1]->X)->type_name,&flg);
610:     if (Xc != Bc || !flg) {
611:       MatDestroy(&mglevels[levels-1]->R);
612:       for (i=0;i<levels-1;i++) {
613:         MatDestroy(&mglevels[i]->R);
614:         MatDestroy(&mglevels[i]->B);
615:         MatDestroy(&mglevels[i]->X);
616:       }
617:     }
618:   }

620:   if (mg->am == PC_MG_MULTIPLICATIVE) {
621:     if (matapp) { MatZeroEntries(X); }
622:     else { VecZeroEntries(x); }
623:     for (i=0; i<mg->cyclesperpcapply; i++) {
624:       PCMGMCycle_Private(pc,mglevels+levels-1,transpose,matapp,NULL);
625:     }
626:   } else if (mg->am == PC_MG_ADDITIVE) {
627:     PCMGACycle_Private(pc,mglevels,transpose,matapp);
628:   } else if (mg->am == PC_MG_KASKADE) {
629:     PCMGKCycle_Private(pc,mglevels,transpose,matapp);
630:   } else {
631:     PCMGFCycle_Private(pc,mglevels,transpose,matapp);
632:   }
633:   if (mg->stageApply) {PetscLogStagePop();}
634:   if (!changeu && !changed) {
635:     if (matapp) { mglevels[levels-1]->B = NULL; }
636:     else { mglevels[levels-1]->b = NULL; }
637:   }
638:   return(0);
639: }

641: static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
642: {

646:   PCApply_MG_Internal(pc,b,x,NULL,NULL,PETSC_FALSE);
647:   return(0);
648: }

650: static PetscErrorCode PCApplyTranspose_MG(PC pc,Vec b,Vec x)
651: {

655:   PCApply_MG_Internal(pc,b,x,NULL,NULL,PETSC_TRUE);
656:   return(0);
657: }

659: static PetscErrorCode PCMatApply_MG(PC pc,Mat b,Mat x)
660: {

664:   PCApply_MG_Internal(pc,NULL,NULL,b,x,PETSC_FALSE);
665:   return(0);
666: }

668: PetscErrorCode PCSetFromOptions_MG(PetscOptionItems *PetscOptionsObject,PC pc)
669: {
670:   PetscErrorCode   ierr;
671:   PetscInt         levels,cycles;
672:   PetscBool        flg, flg2;
673:   PC_MG            *mg = (PC_MG*)pc->data;
674:   PC_MG_Levels     **mglevels;
675:   PCMGType         mgtype;
676:   PCMGCycleType    mgctype;
677:   PCMGGalerkinType gtype;

680:   levels = PetscMax(mg->nlevels,1);
681:   PetscOptionsHead(PetscOptionsObject,"Multigrid options");
682:   PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);
683:   if (!flg && !mg->levels && pc->dm) {
684:     DMGetRefineLevel(pc->dm,&levels);
685:     levels++;
686:     mg->usedmfornumberoflevels = PETSC_TRUE;
687:   }
688:   PCMGSetLevels(pc,levels,NULL);
689:   mglevels = mg->levels;

691:   mgctype = (PCMGCycleType) mglevels[0]->cycles;
692:   PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);
693:   if (flg) {
694:     PCMGSetCycleType(pc,mgctype);
695:   }
696:   gtype = mg->galerkin;
697:   PetscOptionsEnum("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",PCMGGalerkinTypes,(PetscEnum)gtype,(PetscEnum*)&gtype,&flg);
698:   if (flg) {
699:     PCMGSetGalerkin(pc,gtype);
700:   }
701:   flg2 = PETSC_FALSE;
702:   PetscOptionsBool("-pc_mg_adapt_interp","Adapt interpolation using some coarse space","PCMGSetAdaptInterpolation",PETSC_FALSE,&flg2,&flg);
703:   if (flg) {PCMGSetAdaptInterpolation(pc, flg2);}
704:   PetscOptionsInt("-pc_mg_adapt_interp_n","Size of the coarse space for adaptive interpolation","PCMGSetCoarseSpace",mg->Nc,&mg->Nc,&flg);
705:   PetscOptionsEnum("-pc_mg_adapt_interp_coarse_space","Type of coarse space: polynomial, harmonic, eigenvector, generalized_eigenvector","PCMGSetAdaptCoarseSpaceType",PCMGCoarseSpaceTypes,(PetscEnum)mg->coarseSpaceType,(PetscEnum*)&mg->coarseSpaceType,&flg);
706:   PetscOptionsBool("-pc_mg_mesp_monitor","Monitor the multilevel eigensolver","PCMGSetAdaptInterpolation",PETSC_FALSE,&mg->mespMonitor,&flg);
707:   flg2 = PETSC_FALSE;
708:   PetscOptionsBool("-pc_mg_adapt_cr","Monitor coarse space quality using Compatible Relaxation (CR)","PCMGSetAdaptCR",PETSC_FALSE,&flg2,&flg);
709:   if (flg) {PCMGSetAdaptCR(pc, flg2);}
710:   flg = PETSC_FALSE;
711:   PetscOptionsBool("-pc_mg_distinct_smoothup","Create separate smoothup KSP and append the prefix _up","PCMGSetDistinctSmoothUp",PETSC_FALSE,&flg,NULL);
712:   if (flg) {
713:     PCMGSetDistinctSmoothUp(pc);
714:   }
715:   mgtype = mg->am;
716:   PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);
717:   if (flg) {
718:     PCMGSetType(pc,mgtype);
719:   }
720:   if (mg->am == PC_MG_MULTIPLICATIVE) {
721:     PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGMultiplicativeSetCycles",mg->cyclesperpcapply,&cycles,&flg);
722:     if (flg) {
723:       PCMGMultiplicativeSetCycles(pc,cycles);
724:     }
725:   }
726:   flg  = PETSC_FALSE;
727:   PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,NULL);
728:   if (flg) {
729:     PetscInt i;
730:     char     eventname[128];

732:     levels = mglevels[0]->levels;
733:     for (i=0; i<levels; i++) {
734:       sprintf(eventname,"MGSetup Level %d",(int)i);
735:       PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);
736:       sprintf(eventname,"MGSmooth Level %d",(int)i);
737:       PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);
738:       if (i) {
739:         sprintf(eventname,"MGResid Level %d",(int)i);
740:         PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);
741:         sprintf(eventname,"MGInterp Level %d",(int)i);
742:         PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);
743:       }
744:     }

746: #if defined(PETSC_USE_LOG)
747:     {
748:       const char    *sname = "MG Apply";
749:       PetscStageLog stageLog;
750:       PetscInt      st;

752:       PetscLogGetStageLog(&stageLog);
753:       for (st = 0; st < stageLog->numStages; ++st) {
754:         PetscBool same;

756:         PetscStrcmp(stageLog->stageInfo[st].name, sname, &same);
757:         if (same) mg->stageApply = st;
758:       }
759:       if (!mg->stageApply) {
760:         PetscLogStageRegister(sname, &mg->stageApply);
761:       }
762:     }
763: #endif
764:   }
765:   PetscOptionsTail();
766:   /* Check option consistency */
767:   PCMGGetGalerkin(pc, &gtype);
768:   PCMGGetAdaptInterpolation(pc, &flg);
769:   if (flg && (gtype >= PC_MG_GALERKIN_NONE)) SETERRQ(PetscObjectComm((PetscObject) pc), PETSC_ERR_ARG_INCOMP, "Must use Galerkin coarse operators when adapting the interpolator");
770:   return(0);
771: }

773: const char *const PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",NULL};
774: const char *const PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",NULL};
775: const char *const PCMGGalerkinTypes[] = {"both","pmat","mat","none","external","PCMGGalerkinType","PC_MG_GALERKIN",NULL};
776: const char *const PCMGCoarseSpaceTypes[] = {"polynomial","harmonic","eigenvector","generalized_eigenvector","PCMGCoarseSpaceType","PCMG_POLYNOMIAL",NULL};

778: #include <petscdraw.h>
779: PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
780: {
781:   PC_MG          *mg        = (PC_MG*)pc->data;
782:   PC_MG_Levels   **mglevels = mg->levels;
784:   PetscInt       levels = mglevels ? mglevels[0]->levels : 0,i;
785:   PetscBool      iascii,isbinary,isdraw;

788:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
789:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
790:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
791:   if (iascii) {
792:     const char *cyclename = levels ? (mglevels[0]->cycles == PC_MG_CYCLE_V ? "v" : "w") : "unknown";
793:     PetscViewerASCIIPrintf(viewer,"  type is %s, levels=%D cycles=%s\n", PCMGTypes[mg->am],levels,cyclename);
794:     if (mg->am == PC_MG_MULTIPLICATIVE) {
795:       PetscViewerASCIIPrintf(viewer,"    Cycles per PCApply=%d\n",mg->cyclesperpcapply);
796:     }
797:     if (mg->galerkin == PC_MG_GALERKIN_BOTH) {
798:       PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices\n");
799:     } else if (mg->galerkin == PC_MG_GALERKIN_PMAT) {
800:       PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices for pmat\n");
801:     } else if (mg->galerkin == PC_MG_GALERKIN_MAT) {
802:       PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices for mat\n");
803:     } else if (mg->galerkin == PC_MG_GALERKIN_EXTERNAL) {
804:       PetscViewerASCIIPrintf(viewer,"    Using externally compute Galerkin coarse grid matrices\n");
805:     } else {
806:       PetscViewerASCIIPrintf(viewer,"    Not using Galerkin computed coarse grid matrices\n");
807:     }
808:     if (mg->view){
809:       (*mg->view)(pc,viewer);
810:     }
811:     for (i=0; i<levels; i++) {
812:       if (!i) {
813:         PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level -------------------------------\n",i);
814:       } else {
815:         PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);
816:       }
817:       PetscViewerASCIIPushTab(viewer);
818:       KSPView(mglevels[i]->smoothd,viewer);
819:       PetscViewerASCIIPopTab(viewer);
820:       if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) {
821:         PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");
822:       } else if (i) {
823:         PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);
824:         PetscViewerASCIIPushTab(viewer);
825:         KSPView(mglevels[i]->smoothu,viewer);
826:         PetscViewerASCIIPopTab(viewer);
827:       }
828:       if (i && mglevels[i]->cr) {
829:         PetscViewerASCIIPrintf(viewer,"CR solver on level %D -------------------------------\n",i);
830:         PetscViewerASCIIPushTab(viewer);
831:         KSPView(mglevels[i]->cr,viewer);
832:         PetscViewerASCIIPopTab(viewer);
833:       }
834:     }
835:   } else if (isbinary) {
836:     for (i=levels-1; i>=0; i--) {
837:       KSPView(mglevels[i]->smoothd,viewer);
838:       if (i && mglevels[i]->smoothd != mglevels[i]->smoothu) {
839:         KSPView(mglevels[i]->smoothu,viewer);
840:       }
841:     }
842:   } else if (isdraw) {
843:     PetscDraw draw;
844:     PetscReal x,w,y,bottom,th;
845:     PetscViewerDrawGetDraw(viewer,0,&draw);
846:     PetscDrawGetCurrentPoint(draw,&x,&y);
847:     PetscDrawStringGetSize(draw,NULL,&th);
848:     bottom = y - th;
849:     for (i=levels-1; i>=0; i--) {
850:       if (!mglevels[i]->smoothu || (mglevels[i]->smoothu == mglevels[i]->smoothd)) {
851:         PetscDrawPushCurrentPoint(draw,x,bottom);
852:         KSPView(mglevels[i]->smoothd,viewer);
853:         PetscDrawPopCurrentPoint(draw);
854:       } else {
855:         w    = 0.5*PetscMin(1.0-x,x);
856:         PetscDrawPushCurrentPoint(draw,x+w,bottom);
857:         KSPView(mglevels[i]->smoothd,viewer);
858:         PetscDrawPopCurrentPoint(draw);
859:         PetscDrawPushCurrentPoint(draw,x-w,bottom);
860:         KSPView(mglevels[i]->smoothu,viewer);
861:         PetscDrawPopCurrentPoint(draw);
862:       }
863:       PetscDrawGetBoundingBox(draw,NULL,&bottom,NULL,NULL);
864:       bottom -= th;
865:     }
866:   }
867:   return(0);
868: }

870: #include <petsc/private/kspimpl.h>

872: /*
873:     Calls setup for the KSP on each level
874: */
875: PetscErrorCode PCSetUp_MG(PC pc)
876: {
877:   PC_MG          *mg        = (PC_MG*)pc->data;
878:   PC_MG_Levels   **mglevels = mg->levels;
880:   PetscInt       i,n;
881:   PC             cpc;
882:   PetscBool      dump = PETSC_FALSE,opsset,use_amat,missinginterpolate = PETSC_FALSE;
883:   Mat            dA,dB;
884:   Vec            tvec;
885:   DM             *dms;
886:   PetscViewer    viewer = NULL;
887:   PetscBool      dAeqdB = PETSC_FALSE, needRestricts = PETSC_FALSE, doCR = PETSC_FALSE;

890:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels with PCMGSetLevels() before setting up");
891:   n = mglevels[0]->levels;
892:   /* FIX: Move this to PCSetFromOptions_MG? */
893:   if (mg->usedmfornumberoflevels) {
894:     PetscInt levels;
895:     DMGetRefineLevel(pc->dm,&levels);
896:     levels++;
897:     if (levels > n) { /* the problem is now being solved on a finer grid */
898:       PCMGSetLevels(pc,levels,NULL);
899:       n        = levels;
900:       PCSetFromOptions(pc); /* it is bad to call this here, but otherwise will never be called for the new hierarchy */
901:       mglevels = mg->levels;
902:     }
903:   }
904:   KSPGetPC(mglevels[0]->smoothd,&cpc);


907:   /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */
908:   /* so use those from global PC */
909:   /* Is this what we always want? What if user wants to keep old one? */
910:   KSPGetOperatorsSet(mglevels[n-1]->smoothd,NULL,&opsset);
911:   if (opsset) {
912:     Mat mmat;
913:     KSPGetOperators(mglevels[n-1]->smoothd,NULL,&mmat);
914:     if (mmat == pc->pmat) opsset = PETSC_FALSE;
915:   }

917:   /* Create CR solvers */
918:   PCMGGetAdaptCR(pc, &doCR);
919:   if (doCR) {
920:     const char *prefix;

922:     PCGetOptionsPrefix(pc, &prefix);
923:     for (i = 1; i < n; ++i) {
924:       PC   ipc, cr;
925:       char crprefix[128];

927:       KSPCreate(PetscObjectComm((PetscObject) pc), &mglevels[i]->cr);
928:       KSPSetErrorIfNotConverged(mglevels[i]->cr, PETSC_FALSE);
929:       PetscObjectIncrementTabLevel((PetscObject) mglevels[i]->cr, (PetscObject) pc, n-i);
930:       KSPSetOptionsPrefix(mglevels[i]->cr, prefix);
931:       PetscObjectComposedDataSetInt((PetscObject) mglevels[i]->cr, PetscMGLevelId, mglevels[i]->level);
932:       KSPSetType(mglevels[i]->cr, KSPCHEBYSHEV);
933:       KSPSetConvergenceTest(mglevels[i]->cr, KSPConvergedSkip, NULL, NULL);
934:       KSPSetNormType(mglevels[i]->cr, KSP_NORM_PRECONDITIONED);
935:       KSPGetPC(mglevels[i]->cr, &ipc);

937:       PCSetType(ipc, PCCOMPOSITE);
938:       PCCompositeSetType(ipc, PC_COMPOSITE_MULTIPLICATIVE);
939:       PCCompositeAddPCType(ipc, PCSOR);
940:       CreateCR_Private(pc, i, &cr);
941:       PCCompositeAddPC(ipc, cr);
942:       PCDestroy(&cr);

944:       KSPSetTolerances(mglevels[i]->cr, PETSC_DEFAULT, PETSC_DEFAULT, PETSC_DEFAULT, mg->default_smoothd);
945:       KSPSetInitialGuessNonzero(mglevels[i]->cr, PETSC_TRUE);
946:       PetscSNPrintf(crprefix, 128, "mg_levels_%d_cr_", (int) i);
947:       KSPAppendOptionsPrefix(mglevels[i]->cr, crprefix);
948:       PetscLogObjectParent((PetscObject) pc, (PetscObject) mglevels[i]->cr);
949:     }
950:   }

952:   if (!opsset) {
953:     PCGetUseAmat(pc,&use_amat);
954:     if (use_amat) {
955:       PetscInfo(pc,"Using outer operators to define finest grid operator \n  because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
956:       KSPSetOperators(mglevels[n-1]->smoothd,pc->mat,pc->pmat);
957:     } else {
958:       PetscInfo(pc,"Using matrix (pmat) operators to define finest grid operator \n  because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
959:       KSPSetOperators(mglevels[n-1]->smoothd,pc->pmat,pc->pmat);
960:     }
961:   }

963:   for (i=n-1; i>0; i--) {
964:     if (!(mglevels[i]->interpolate || mglevels[i]->restrct)) {
965:       missinginterpolate = PETSC_TRUE;
966:       continue;
967:     }
968:   }

970:   KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB);
971:   if (dA == dB) dAeqdB = PETSC_TRUE;
972:   if ((mg->galerkin == PC_MG_GALERKIN_NONE) || (((mg->galerkin == PC_MG_GALERKIN_PMAT) || (mg->galerkin == PC_MG_GALERKIN_MAT)) && !dAeqdB)) {
973:     needRestricts = PETSC_TRUE;  /* user must compute either mat, pmat, or both so must restrict x to coarser levels */
974:   }


977:   /*
978:    Skipping if user has provided all interpolation/restriction needed (since DM might not be able to produce them (when coming from SNES/TS)
979:    Skipping for galerkin==2 (externally managed hierarchy such as ML and GAMG). Cleaner logic here would be great. Wrap ML/GAMG as DMs?
980:   */
981:   if (missinginterpolate && pc->dm && mg->galerkin != PC_MG_GALERKIN_EXTERNAL && !pc->setupcalled) {
982:         /* construct the interpolation from the DMs */
983:     Mat p;
984:     Vec rscale;
985:     PetscMalloc1(n,&dms);
986:     dms[n-1] = pc->dm;
987:     /* Separately create them so we do not get DMKSP interference between levels */
988:     for (i=n-2; i>-1; i--) {DMCoarsen(dms[i+1],MPI_COMM_NULL,&dms[i]);}
989:         /*
990:            Force the mat type of coarse level operator to be AIJ because usually we want to use LU for coarse level.
991:            Notice that it can be overwritten by -mat_type because KSPSetUp() reads command line options.
992:            But it is safe to use -dm_mat_type.

994:            The mat type should not be hardcoded like this, we need to find a better way.
995:     DMSetMatType(dms[0],MATAIJ);
996:     */
997:     for (i=n-2; i>-1; i--) {
998:       DMKSP     kdm;
999:       PetscBool dmhasrestrict, dmhasinject;
1000:       KSPSetDM(mglevels[i]->smoothd,dms[i]);
1001:       if (!needRestricts) {KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);}
1002:       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
1003:         KSPSetDM(mglevels[i]->smoothu,dms[i]);
1004:         if (!needRestricts) {KSPSetDMActive(mglevels[i]->smoothu,PETSC_FALSE);}
1005:       }
1006:       if (mglevels[i]->cr) {
1007:         KSPSetDM(mglevels[i]->cr,dms[i]);
1008:         if (!needRestricts) {KSPSetDMActive(mglevels[i]->cr,PETSC_FALSE);}
1009:       }
1010:       DMGetDMKSPWrite(dms[i],&kdm);
1011:       /* Ugly hack so that the next KSPSetUp() will use the RHS that we set. A better fix is to change dmActive to take
1012:        * a bitwise OR of computing the matrix, RHS, and initial iterate. */
1013:       kdm->ops->computerhs = NULL;
1014:       kdm->rhsctx          = NULL;
1015:       if (!mglevels[i+1]->interpolate) {
1016:         DMCreateInterpolation(dms[i],dms[i+1],&p,&rscale);
1017:         PCMGSetInterpolation(pc,i+1,p);
1018:         if (rscale) {PCMGSetRScale(pc,i+1,rscale);}
1019:         VecDestroy(&rscale);
1020:         MatDestroy(&p);
1021:       }
1022:       DMHasCreateRestriction(dms[i],&dmhasrestrict);
1023:       if (dmhasrestrict && !mglevels[i+1]->restrct){
1024:         DMCreateRestriction(dms[i],dms[i+1],&p);
1025:         PCMGSetRestriction(pc,i+1,p);
1026:         MatDestroy(&p);
1027:       }
1028:       DMHasCreateInjection(dms[i],&dmhasinject);
1029:       if (dmhasinject && !mglevels[i+1]->inject){
1030:         DMCreateInjection(dms[i],dms[i+1],&p);
1031:         PCMGSetInjection(pc,i+1,p);
1032:         MatDestroy(&p);
1033:       }
1034:     }

1036:     for (i=n-2; i>-1; i--) {DMDestroy(&dms[i]);}
1037:     PetscFree(dms);
1038:   }

1040:   if (pc->dm && !pc->setupcalled) {
1041:     /* finest smoother also gets DM but it is not active, independent of whether galerkin==PC_MG_GALERKIN_EXTERNAL */
1042:     KSPSetDM(mglevels[n-1]->smoothd,pc->dm);
1043:     KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);
1044:     if (mglevels[n-1]->smoothd != mglevels[n-1]->smoothu) {
1045:       KSPSetDM(mglevels[n-1]->smoothu,pc->dm);
1046:       KSPSetDMActive(mglevels[n-1]->smoothu,PETSC_FALSE);
1047:     }
1048:     if (mglevels[n-1]->cr) {
1049:       KSPSetDM(mglevels[n-1]->cr,pc->dm);
1050:       KSPSetDMActive(mglevels[n-1]->cr,PETSC_FALSE);
1051:     }
1052:   }

1054:   if (mg->galerkin < PC_MG_GALERKIN_NONE) {
1055:     Mat       A,B;
1056:     PetscBool doA = PETSC_FALSE,doB = PETSC_FALSE;
1057:     MatReuse  reuse = MAT_INITIAL_MATRIX;

1059:     if ((mg->galerkin == PC_MG_GALERKIN_PMAT) || (mg->galerkin == PC_MG_GALERKIN_BOTH)) doB = PETSC_TRUE;
1060:     if ((mg->galerkin == PC_MG_GALERKIN_MAT) || ((mg->galerkin == PC_MG_GALERKIN_BOTH) && (dA != dB))) doA = PETSC_TRUE;
1061:     if (pc->setupcalled) reuse = MAT_REUSE_MATRIX;
1062:     for (i=n-2; i>-1; i--) {
1063:       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");
1064:       if (!mglevels[i+1]->interpolate) {
1065:         PCMGSetInterpolation(pc,i+1,mglevels[i+1]->restrct);
1066:       }
1067:       if (!mglevels[i+1]->restrct) {
1068:         PCMGSetRestriction(pc,i+1,mglevels[i+1]->interpolate);
1069:       }
1070:       if (reuse == MAT_REUSE_MATRIX) {
1071:         KSPGetOperators(mglevels[i]->smoothd,&A,&B);
1072:       }
1073:       if (doA) {
1074:         MatGalerkin(mglevels[i+1]->restrct,dA,mglevels[i+1]->interpolate,reuse,1.0,&A);
1075:       }
1076:       if (doB) {
1077:         MatGalerkin(mglevels[i+1]->restrct,dB,mglevels[i+1]->interpolate,reuse,1.0,&B);
1078:       }
1079:       /* the management of the PetscObjectReference() and PetscObjecDereference() below is rather delicate */
1080:       if (!doA && dAeqdB) {
1081:         if (reuse == MAT_INITIAL_MATRIX) {PetscObjectReference((PetscObject)B);}
1082:         A = B;
1083:       } else if (!doA && reuse == MAT_INITIAL_MATRIX) {
1084:         KSPGetOperators(mglevels[i]->smoothd,&A,NULL);
1085:         PetscObjectReference((PetscObject)A);
1086:       }
1087:       if (!doB && dAeqdB) {
1088:         if (reuse == MAT_INITIAL_MATRIX) {PetscObjectReference((PetscObject)A);}
1089:         B = A;
1090:       } else if (!doB && reuse == MAT_INITIAL_MATRIX) {
1091:         KSPGetOperators(mglevels[i]->smoothd,NULL,&B);
1092:         PetscObjectReference((PetscObject)B);
1093:       }
1094:       if (reuse == MAT_INITIAL_MATRIX) {
1095:         KSPSetOperators(mglevels[i]->smoothd,A,B);
1096:         PetscObjectDereference((PetscObject)A);
1097:         PetscObjectDereference((PetscObject)B);
1098:       }
1099:       dA = A;
1100:       dB = B;
1101:     }
1102:   }


1105:   /* Adapt interpolation matrices */
1106:   if (mg->adaptInterpolation) {
1107:     mg->Nc = mg->Nc < 0 ? 6 : mg->Nc; /* Default to 6 modes */
1108:     for (i = 0; i < n; ++i) {
1109:       PCMGComputeCoarseSpace_Internal(pc, i, mg->coarseSpaceType, mg->Nc, !i ? NULL : mglevels[i-1]->coarseSpace, &mglevels[i]->coarseSpace);
1110:       if (i) {PCMGAdaptInterpolator_Internal(pc, i, mglevels[i-1]->smoothu, mglevels[i]->smoothu, mg->Nc, mglevels[i-1]->coarseSpace, mglevels[i]->coarseSpace);}
1111:     }
1112:     for (i = n-2; i > -1; --i) {
1113:       PCMGRecomputeLevelOperators_Internal(pc, i);
1114:     }
1115:   }

1117:   if (needRestricts && pc->dm) {
1118:     for (i=n-2; i>=0; i--) {
1119:       DM  dmfine,dmcoarse;
1120:       Mat Restrict,Inject;
1121:       Vec rscale;
1122:       KSPGetDM(mglevels[i+1]->smoothd,&dmfine);
1123:       KSPGetDM(mglevels[i]->smoothd,&dmcoarse);
1124:       PCMGGetRestriction(pc,i+1,&Restrict);
1125:       PCMGGetRScale(pc,i+1,&rscale);
1126:       PCMGGetInjection(pc,i+1,&Inject);
1127:       DMRestrict(dmfine,Restrict,rscale,Inject,dmcoarse);
1128:     }
1129:   }

1131:   if (!pc->setupcalled) {
1132:     for (i=0; i<n; i++) {
1133:       KSPSetFromOptions(mglevels[i]->smoothd);
1134:     }
1135:     for (i=1; i<n; i++) {
1136:       if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) {
1137:         KSPSetFromOptions(mglevels[i]->smoothu);
1138:       }
1139:       if (mglevels[i]->cr) {
1140:         KSPSetFromOptions(mglevels[i]->cr);
1141:       }
1142:     }
1143:     /* insure that if either interpolation or restriction is set the other other one is set */
1144:     for (i=1; i<n; i++) {
1145:       PCMGGetInterpolation(pc,i,NULL);
1146:       PCMGGetRestriction(pc,i,NULL);
1147:     }
1148:     for (i=0; i<n-1; i++) {
1149:       if (!mglevels[i]->b) {
1150:         Vec *vec;
1151:         KSPCreateVecs(mglevels[i]->smoothd,1,&vec,0,NULL);
1152:         PCMGSetRhs(pc,i,*vec);
1153:         VecDestroy(vec);
1154:         PetscFree(vec);
1155:       }
1156:       if (!mglevels[i]->r && i) {
1157:         VecDuplicate(mglevels[i]->b,&tvec);
1158:         PCMGSetR(pc,i,tvec);
1159:         VecDestroy(&tvec);
1160:       }
1161:       if (!mglevels[i]->x) {
1162:         VecDuplicate(mglevels[i]->b,&tvec);
1163:         PCMGSetX(pc,i,tvec);
1164:         VecDestroy(&tvec);
1165:       }
1166:       if (doCR) {
1167:         VecDuplicate(mglevels[i]->b,&mglevels[i]->crx);
1168:         VecDuplicate(mglevels[i]->b,&mglevels[i]->crb);
1169:         VecZeroEntries(mglevels[i]->crb);
1170:       }
1171:     }
1172:     if (n != 1 && !mglevels[n-1]->r) {
1173:       /* PCMGSetR() on the finest level if user did not supply it */
1174:       Vec *vec;
1175:       KSPCreateVecs(mglevels[n-1]->smoothd,1,&vec,0,NULL);
1176:       PCMGSetR(pc,n-1,*vec);
1177:       VecDestroy(vec);
1178:       PetscFree(vec);
1179:     }
1180:     if (doCR) {
1181:       VecDuplicate(mglevels[n-1]->r, &mglevels[n-1]->crx);
1182:       VecDuplicate(mglevels[n-1]->r, &mglevels[n-1]->crb);
1183:       VecZeroEntries(mglevels[n-1]->crb);
1184:     }
1185:   }

1187:   if (pc->dm) {
1188:     /* need to tell all the coarser levels to rebuild the matrix using the DM for that level */
1189:     for (i=0; i<n-1; i++) {
1190:       if (mglevels[i]->smoothd->setupstage != KSP_SETUP_NEW) mglevels[i]->smoothd->setupstage = KSP_SETUP_NEWMATRIX;
1191:     }
1192:   }

1194:   for (i=1; i<n; i++) {
1195:     if (mglevels[i]->smoothu == mglevels[i]->smoothd || mg->am == PC_MG_FULL || mg->am == PC_MG_KASKADE || mg->cyclesperpcapply > 1){
1196:       /* if doing only down then initial guess is zero */
1197:       KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);
1198:     }
1199:     if (mglevels[i]->cr) {KSPSetInitialGuessNonzero(mglevels[i]->cr,PETSC_TRUE);}
1200:     if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1201:     KSPSetUp(mglevels[i]->smoothd);
1202:     if (mglevels[i]->smoothd->reason == KSP_DIVERGED_PC_FAILED) {
1203:       pc->failedreason = PC_SUBPC_ERROR;
1204:     }
1205:     if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1206:     if (!mglevels[i]->residual) {
1207:       Mat mat;
1208:       KSPGetOperators(mglevels[i]->smoothd,&mat,NULL);
1209:       PCMGSetResidual(pc,i,PCMGResidualDefault,mat);
1210:     }
1211:     if (!mglevels[i]->residualtranspose) {
1212:       Mat mat;
1213:       KSPGetOperators(mglevels[i]->smoothd,&mat,NULL);
1214:       PCMGSetResidualTranspose(pc,i,PCMGResidualTransposeDefault,mat);
1215:     }
1216:   }
1217:   for (i=1; i<n; i++) {
1218:     if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) {
1219:       Mat downmat,downpmat;

1221:       /* check if operators have been set for up, if not use down operators to set them */
1222:       KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,NULL);
1223:       if (!opsset) {
1224:         KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat);
1225:         KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat);
1226:       }

1228:       KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);
1229:       if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1230:       KSPSetUp(mglevels[i]->smoothu);
1231:       if (mglevels[i]->smoothu->reason == KSP_DIVERGED_PC_FAILED) {
1232:         pc->failedreason = PC_SUBPC_ERROR;
1233:       }
1234:       if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1235:     }
1236:     if (mglevels[i]->cr) {
1237:       Mat downmat,downpmat;

1239:       /* check if operators have been set for up, if not use down operators to set them */
1240:       KSPGetOperatorsSet(mglevels[i]->cr,&opsset,NULL);
1241:       if (!opsset) {
1242:         KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat);
1243:         KSPSetOperators(mglevels[i]->cr,downmat,downpmat);
1244:       }

1246:       KSPSetInitialGuessNonzero(mglevels[i]->cr,PETSC_TRUE);
1247:       if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1248:       KSPSetUp(mglevels[i]->cr);
1249:       if (mglevels[i]->cr->reason == KSP_DIVERGED_PC_FAILED) {
1250:         pc->failedreason = PC_SUBPC_ERROR;
1251:       }
1252:       if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1253:     }
1254:   }

1256:   if (mglevels[0]->eventsmoothsetup) {PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);}
1257:   KSPSetUp(mglevels[0]->smoothd);
1258:   if (mglevels[0]->smoothd->reason == KSP_DIVERGED_PC_FAILED) {
1259:     pc->failedreason = PC_SUBPC_ERROR;
1260:   }
1261:   if (mglevels[0]->eventsmoothsetup) {PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);}

1263:   /*
1264:      Dump the interpolation/restriction matrices plus the
1265:    Jacobian/stiffness on each level. This allows MATLAB users to
1266:    easily check if the Galerkin condition A_c = R A_f R^T is satisfied.

1268:    Only support one or the other at the same time.
1269:   */
1270: #if defined(PETSC_USE_SOCKET_VIEWER)
1271:   PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,NULL);
1272:   if (dump) viewer = PETSC_VIEWER_SOCKET_(PetscObjectComm((PetscObject)pc));
1273:   dump = PETSC_FALSE;
1274: #endif
1275:   PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,NULL);
1276:   if (dump) viewer = PETSC_VIEWER_BINARY_(PetscObjectComm((PetscObject)pc));

1278:   if (viewer) {
1279:     for (i=1; i<n; i++) {
1280:       MatView(mglevels[i]->restrct,viewer);
1281:     }
1282:     for (i=0; i<n; i++) {
1283:       KSPGetPC(mglevels[i]->smoothd,&pc);
1284:       MatView(pc->mat,viewer);
1285:     }
1286:   }
1287:   return(0);
1288: }

1290: /* -------------------------------------------------------------------------------------*/

1292: PetscErrorCode PCMGGetLevels_MG(PC pc, PetscInt *levels)
1293: {
1294:   PC_MG *mg = (PC_MG *) pc->data;

1297:   *levels = mg->nlevels;
1298:   return(0);
1299: }

1301: /*@
1302:    PCMGGetLevels - Gets the number of levels to use with MG.

1304:    Not Collective

1306:    Input Parameter:
1307: .  pc - the preconditioner context

1309:    Output parameter:
1310: .  levels - the number of levels

1312:    Level: advanced

1314: .seealso: PCMGSetLevels()
1315: @*/
1316: PetscErrorCode PCMGGetLevels(PC pc,PetscInt *levels)
1317: {

1323:   *levels = 0;
1324:   PetscTryMethod(pc,"PCMGGetLevels_C",(PC,PetscInt*),(pc,levels));
1325:   return(0);
1326: }

1328: /*@
1329:    PCMGSetType - Determines the form of multigrid to use:
1330:    multiplicative, additive, full, or the Kaskade algorithm.

1332:    Logically Collective on PC

1334:    Input Parameters:
1335: +  pc - the preconditioner context
1336: -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
1337:    PC_MG_FULL, PC_MG_KASKADE

1339:    Options Database Key:
1340: .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
1341:    additive, full, kaskade

1343:    Level: advanced

1345: .seealso: PCMGSetLevels()
1346: @*/
1347: PetscErrorCode  PCMGSetType(PC pc,PCMGType form)
1348: {
1349:   PC_MG *mg = (PC_MG*)pc->data;

1354:   mg->am = form;
1355:   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
1356:   else pc->ops->applyrichardson = NULL;
1357:   return(0);
1358: }

1360: /*@
1361:    PCMGGetType - Determines the form of multigrid to use:
1362:    multiplicative, additive, full, or the Kaskade algorithm.

1364:    Logically Collective on PC

1366:    Input Parameter:
1367: .  pc - the preconditioner context

1369:    Output Parameter:
1370: .  type - one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,PC_MG_FULL, PC_MG_KASKADE


1373:    Level: advanced

1375: .seealso: PCMGSetLevels()
1376: @*/
1377: PetscErrorCode  PCMGGetType(PC pc,PCMGType *type)
1378: {
1379:   PC_MG *mg = (PC_MG*)pc->data;

1383:   *type = mg->am;
1384:   return(0);
1385: }

1387: /*@
1388:    PCMGSetCycleType - Sets the type cycles to use.  Use PCMGSetCycleTypeOnLevel() for more
1389:    complicated cycling.

1391:    Logically Collective on PC

1393:    Input Parameters:
1394: +  pc - the multigrid context
1395: -  n - either PC_MG_CYCLE_V or PC_MG_CYCLE_W

1397:    Options Database Key:
1398: .  -pc_mg_cycle_type <v,w> - provide the cycle desired

1400:    Level: advanced

1402: .seealso: PCMGSetCycleTypeOnLevel()
1403: @*/
1404: PetscErrorCode  PCMGSetCycleType(PC pc,PCMGCycleType n)
1405: {
1406:   PC_MG        *mg        = (PC_MG*)pc->data;
1407:   PC_MG_Levels **mglevels = mg->levels;
1408:   PetscInt     i,levels;

1413:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1414:   levels = mglevels[0]->levels;
1415:   for (i=0; i<levels; i++) mglevels[i]->cycles = n;
1416:   return(0);
1417: }

1419: /*@
1420:    PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step
1421:          of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used

1423:    Logically Collective on PC

1425:    Input Parameters:
1426: +  pc - the multigrid context
1427: -  n - number of cycles (default is 1)

1429:    Options Database Key:
1430: .  -pc_mg_multiplicative_cycles n

1432:    Level: advanced

1434:    Notes:
1435:     This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType()

1437: .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
1438: @*/
1439: PetscErrorCode  PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
1440: {
1441:   PC_MG        *mg        = (PC_MG*)pc->data;

1446:   mg->cyclesperpcapply = n;
1447:   return(0);
1448: }

1450: PetscErrorCode PCMGSetGalerkin_MG(PC pc,PCMGGalerkinType use)
1451: {
1452:   PC_MG *mg = (PC_MG*)pc->data;

1455:   mg->galerkin = use;
1456:   return(0);
1457: }

1459: /*@
1460:    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
1461:       finest grid via the Galerkin process: A_i-1 = r_i * A_i * p_i

1463:    Logically Collective on PC

1465:    Input Parameters:
1466: +  pc - the multigrid context
1467: -  use - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, or PC_MG_GALERKIN_NONE

1469:    Options Database Key:
1470: .  -pc_mg_galerkin <both,pmat,mat,none>

1472:    Level: intermediate

1474:    Notes:
1475:     Some codes that use PCMG such as PCGAMG use Galerkin internally while constructing the hierarchy and thus do not
1476:      use the PCMG construction of the coarser grids.

1478: .seealso: PCMGGetGalerkin(), PCMGGalerkinType

1480: @*/
1481: PetscErrorCode PCMGSetGalerkin(PC pc,PCMGGalerkinType use)
1482: {

1487:   PetscTryMethod(pc,"PCMGSetGalerkin_C",(PC,PCMGGalerkinType),(pc,use));
1488:   return(0);
1489: }

1491: /*@
1492:    PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
1493:       A_i-1 = r_i * A_i * p_i

1495:    Not Collective

1497:    Input Parameter:
1498: .  pc - the multigrid context

1500:    Output Parameter:
1501: .  galerkin - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, PC_MG_GALERKIN_NONE, or PC_MG_GALERKIN_EXTERNAL

1503:    Level: intermediate

1505: .seealso: PCMGSetGalerkin(), PCMGGalerkinType

1507: @*/
1508: PetscErrorCode  PCMGGetGalerkin(PC pc,PCMGGalerkinType  *galerkin)
1509: {
1510:   PC_MG *mg = (PC_MG*)pc->data;

1514:   *galerkin = mg->galerkin;
1515:   return(0);
1516: }

1518: PetscErrorCode PCMGSetAdaptInterpolation_MG(PC pc, PetscBool adapt)
1519: {
1520:   PC_MG *mg = (PC_MG *) pc->data;

1523:   mg->adaptInterpolation = adapt;
1524:   return(0);
1525: }

1527: PetscErrorCode PCMGGetAdaptInterpolation_MG(PC pc, PetscBool *adapt)
1528: {
1529:   PC_MG *mg = (PC_MG *) pc->data;

1532:   *adapt = mg->adaptInterpolation;
1533:   return(0);
1534: }

1536: PetscErrorCode PCMGSetAdaptCR_MG(PC pc, PetscBool cr)
1537: {
1538:   PC_MG *mg = (PC_MG *) pc->data;

1541:   mg->compatibleRelaxation = cr;
1542:   return(0);
1543: }

1545: PetscErrorCode PCMGGetAdaptCR_MG(PC pc, PetscBool *cr)
1546: {
1547:   PC_MG *mg = (PC_MG *) pc->data;

1550:   *cr = mg->compatibleRelaxation;
1551:   return(0);
1552: }

1554: /*@
1555:   PCMGSetAdaptInterpolation - Adapt the interpolator based upon a vector space which should be accurately captured by the next coarser mesh, and thus accurately interpolated.

1557:   Logically Collective on PC

1559:   Input Parameters:
1560: + pc    - the multigrid context
1561: - adapt - flag for adaptation of the interpolator

1563:   Options Database Keys:
1564: + -pc_mg_adapt_interp                     - Turn on adaptation
1565: . -pc_mg_adapt_interp_n <int>             - The number of modes to use, should be divisible by dimension
1566: - -pc_mg_adapt_interp_coarse_space <type> - The type of coarse space: polynomial, harmonic, eigenvector, generalized_eigenvector

1568:   Level: intermediate

1570: .keywords: MG, set, Galerkin
1571: .seealso: PCMGGetAdaptInterpolation(), PCMGSetGalerkin()
1572: @*/
1573: PetscErrorCode PCMGSetAdaptInterpolation(PC pc, PetscBool adapt)
1574: {

1579:   PetscTryMethod(pc,"PCMGSetAdaptInterpolation_C",(PC,PetscBool),(pc,adapt));
1580:   return(0);
1581: }

1583: /*@
1584:   PCMGGetAdaptInterpolation - Get the flag to adapt the interpolator based upon a vector space which should be accurately captured by the next coarser mesh, and thus accurately interpolated.

1586:   Not collective

1588:   Input Parameter:
1589: . pc    - the multigrid context

1591:   Output Parameter:
1592: . adapt - flag for adaptation of the interpolator

1594:   Level: intermediate

1596: .keywords: MG, set, Galerkin
1597: .seealso: PCMGSetAdaptInterpolation(), PCMGSetGalerkin()
1598: @*/
1599: PetscErrorCode PCMGGetAdaptInterpolation(PC pc, PetscBool *adapt)
1600: {

1606:   PetscUseMethod(pc,"PCMGGetAdaptInterpolation_C",(PC,PetscBool*),(pc,adapt));
1607:   return(0);
1608: }

1610: /*@
1611:   PCMGSetAdaptCR - Monitor the coarse space quality using an auxiliary solve with compatible relaxation.

1613:   Logically Collective on PC

1615:   Input Parameters:
1616: + pc - the multigrid context
1617: - cr - flag for compatible relaxation

1619:   Options Database Keys:
1620: . -pc_mg_adapt_cr - Turn on compatible relaxation

1622:   Level: intermediate

1624: .keywords: MG, set, Galerkin
1625: .seealso: PCMGGetAdaptCR(), PCMGSetAdaptInterpolation(), PCMGSetGalerkin()
1626: @*/
1627: PetscErrorCode PCMGSetAdaptCR(PC pc, PetscBool cr)
1628: {

1633:   PetscTryMethod(pc,"PCMGSetAdaptCR_C",(PC,PetscBool),(pc,cr));
1634:   return(0);
1635: }

1637: /*@
1638:   PCMGGetAdaptCR - Get the flag to monitor coarse space quality using an auxiliary solve with compatible relaxation.

1640:   Not collective

1642:   Input Parameter:
1643: . pc    - the multigrid context

1645:   Output Parameter:
1646: . cr - flag for compatible relaxaion

1648:   Level: intermediate

1650: .keywords: MG, set, Galerkin
1651: .seealso: PCMGSetAdaptCR(), PCMGGetAdaptInterpolation(), PCMGSetGalerkin()
1652: @*/
1653: PetscErrorCode PCMGGetAdaptCR(PC pc, PetscBool *cr)
1654: {

1660:   PetscUseMethod(pc,"PCMGGetAdaptCR_C",(PC,PetscBool*),(pc,cr));
1661:   return(0);
1662: }

1664: /*@
1665:    PCMGSetNumberSmooth - Sets the number of pre and post-smoothing steps to use
1666:    on all levels.  Use PCMGDistinctSmoothUp() to create separate up and down smoothers if you want different numbers of
1667:    pre- and post-smoothing steps.

1669:    Logically Collective on PC

1671:    Input Parameters:
1672: +  mg - the multigrid context
1673: -  n - the number of smoothing steps

1675:    Options Database Key:
1676: .  -mg_levels_ksp_max_it <n> - Sets number of pre and post-smoothing steps

1678:    Level: advanced

1680:    Notes:
1681:     this does not set a value on the coarsest grid, since we assume that
1682:     there is no separate smooth up on the coarsest grid.

1684: .seealso: PCMGSetDistinctSmoothUp()
1685: @*/
1686: PetscErrorCode  PCMGSetNumberSmooth(PC pc,PetscInt n)
1687: {
1688:   PC_MG          *mg        = (PC_MG*)pc->data;
1689:   PC_MG_Levels   **mglevels = mg->levels;
1691:   PetscInt       i,levels;

1696:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1697:   levels = mglevels[0]->levels;

1699:   for (i=1; i<levels; i++) {
1700:     KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1701:     KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1702:     mg->default_smoothu = n;
1703:     mg->default_smoothd = n;
1704:   }
1705:   return(0);
1706: }

1708: /*@
1709:    PCMGSetDistinctSmoothUp - sets the up (post) smoother to be a separate KSP from the down (pre) smoother on all levels
1710:        and adds the suffix _up to the options name

1712:    Logically Collective on PC

1714:    Input Parameters:
1715: .  pc - the preconditioner context

1717:    Options Database Key:
1718: .  -pc_mg_distinct_smoothup

1720:    Level: advanced

1722:    Notes:
1723:     this does not set a value on the coarsest grid, since we assume that
1724:     there is no separate smooth up on the coarsest grid.

1726: .seealso: PCMGSetNumberSmooth()
1727: @*/
1728: PetscErrorCode  PCMGSetDistinctSmoothUp(PC pc)
1729: {
1730:   PC_MG          *mg        = (PC_MG*)pc->data;
1731:   PC_MG_Levels   **mglevels = mg->levels;
1733:   PetscInt       i,levels;
1734:   KSP            subksp;

1738:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1739:   levels = mglevels[0]->levels;

1741:   for (i=1; i<levels; i++) {
1742:     const char *prefix = NULL;
1743:     /* make sure smoother up and down are different */
1744:     PCMGGetSmootherUp(pc,i,&subksp);
1745:     KSPGetOptionsPrefix(mglevels[i]->smoothd,&prefix);
1746:     KSPSetOptionsPrefix(subksp,prefix);
1747:     KSPAppendOptionsPrefix(subksp,"up_");
1748:   }
1749:   return(0);
1750: }

1752: /* No new matrices are created, and the coarse operator matrices are the references to the original ones */
1753: PetscErrorCode  PCGetInterpolations_MG(PC pc,PetscInt *num_levels,Mat *interpolations[])
1754: {
1755:   PC_MG          *mg        = (PC_MG*)pc->data;
1756:   PC_MG_Levels   **mglevels = mg->levels;
1757:   Mat            *mat;
1758:   PetscInt       l;

1762:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1763:   PetscMalloc1(mg->nlevels,&mat);
1764:   for (l=1; l< mg->nlevels; l++) {
1765:     mat[l-1] = mglevels[l]->interpolate;
1766:     PetscObjectReference((PetscObject)mat[l-1]);
1767:   }
1768:   *num_levels = mg->nlevels;
1769:   *interpolations = mat;
1770:   return(0);
1771: }

1773: /* No new matrices are created, and the coarse operator matrices are the references to the original ones */
1774: PetscErrorCode  PCGetCoarseOperators_MG(PC pc,PetscInt *num_levels,Mat *coarseOperators[])
1775: {
1776:   PC_MG          *mg        = (PC_MG*)pc->data;
1777:   PC_MG_Levels   **mglevels = mg->levels;
1778:   PetscInt       l;
1779:   Mat            *mat;

1783:   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1784:   PetscMalloc1(mg->nlevels,&mat);
1785:   for (l=0; l<mg->nlevels-1; l++) {
1786:     KSPGetOperators(mglevels[l]->smoothd,NULL,&(mat[l]));
1787:     PetscObjectReference((PetscObject)mat[l]);
1788:   }
1789:   *num_levels = mg->nlevels;
1790:   *coarseOperators = mat;
1791:   return(0);
1792: }

1794: /*@C
1795:   PCMGRegisterCoarseSpaceConstructor -  Adds a method to the PCMG package for coarse space construction.

1797:   Not collective

1799:   Input Parameters:
1800: + name     - name of the constructor
1801: - function - constructor routine

1803:   Notes:
1804:   Calling sequence for the routine:
1805: $ my_csp(PC pc, PetscInt l, DM dm, KSP smooth, PetscInt Nc, const Vec initGuess[], Vec **coarseSp)
1806: $   pc        - The PC object
1807: $   l         - The multigrid level, 0 is the coarse level
1808: $   dm        - The DM for this level
1809: $   smooth    - The level smoother
1810: $   Nc        - The size of the coarse space
1811: $   initGuess - Basis for an initial guess for the space
1812: $   coarseSp  - A basis for the computed coarse space

1814:   Level: advanced

1816: .seealso: PCMGGetCoarseSpaceConstructor(), PCRegister()
1817: @*/
1818: PetscErrorCode PCMGRegisterCoarseSpaceConstructor(const char name[], PetscErrorCode (*function)(PC, PetscInt, DM, KSP, PetscInt, const Vec[], Vec **))
1819: {

1823:   PCInitializePackage();
1824:   PetscFunctionListAdd(&PCMGCoarseList,name,function);
1825:   return(0);
1826: }

1828: /*@C
1829:   PCMGGetCoarseSpaceConstructor -  Returns the given coarse space construction method.

1831:   Not collective

1833:   Input Parameter:
1834: . name     - name of the constructor

1836:   Output Parameter:
1837: . function - constructor routine

1839:   Notes:
1840:   Calling sequence for the routine:
1841: $ my_csp(PC pc, PetscInt l, DM dm, KSP smooth, PetscInt Nc, const Vec initGuess[], Vec **coarseSp)
1842: $   pc        - The PC object
1843: $   l         - The multigrid level, 0 is the coarse level
1844: $   dm        - The DM for this level
1845: $   smooth    - The level smoother
1846: $   Nc        - The size of the coarse space
1847: $   initGuess - Basis for an initial guess for the space
1848: $   coarseSp  - A basis for the computed coarse space

1850:   Level: advanced

1852: .seealso: PCMGRegisterCoarseSpaceConstructor(), PCRegister()
1853: @*/
1854: PetscErrorCode PCMGGetCoarseSpaceConstructor(const char name[], PetscErrorCode (**function)(PC, PetscInt, DM, KSP, PetscInt, const Vec[], Vec **))
1855: {

1859:   PetscFunctionListFind(PCMGCoarseList,name,function);
1860:   return(0);
1861: }

1863: /* ----------------------------------------------------------------------------------------*/

1865: /*MC
1866:    PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional
1867:     information about the coarser grid matrices and restriction/interpolation operators.

1869:    Options Database Keys:
1870: +  -pc_mg_levels <nlevels> - number of levels including finest
1871: .  -pc_mg_cycle_type <v,w> - provide the cycle desired
1872: .  -pc_mg_type <additive,multiplicative,full,kaskade> - multiplicative is the default
1873: .  -pc_mg_log - log information about time spent on each level of the solver
1874: .  -pc_mg_distinct_smoothup - configure up (after interpolation) and down (before restriction) smoothers separately (with different options prefixes)
1875: .  -pc_mg_galerkin <both,pmat,mat,none> - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R'
1876: .  -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1)
1877: .  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
1878:                         to the Socket viewer for reading from MATLAB.
1879: -  -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices
1880:                         to the binary output file called binaryoutput

1882:    Notes:
1883:     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

1885:        When run with a single level the smoother options are used on that level NOT the coarse grid solver options

1887:        When run with KSPRICHARDSON the convergence test changes slightly if monitor is turned on. The iteration count may change slightly. This
1888:        is because without monitoring the residual norm is computed WITHIN each multigrid cycle on the finest level after the pre-smoothing
1889:        (because the residual has just been computed for the multigrid algorithm and is hence available for free) while with monitoring the
1890:        residual is computed at the end of each cycle.

1892:    Level: intermediate

1894: .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE
1895:            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(),
1896:            PCMGSetDistinctSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
1897:            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
1898:            PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
1899: M*/

1901: PETSC_EXTERN PetscErrorCode PCCreate_MG(PC pc)
1902: {
1903:   PC_MG          *mg;

1907:   PetscNewLog(pc,&mg);
1908:   pc->data     = (void*)mg;
1909:   mg->nlevels  = -1;
1910:   mg->am       = PC_MG_MULTIPLICATIVE;
1911:   mg->galerkin = PC_MG_GALERKIN_NONE;
1912:   mg->adaptInterpolation = PETSC_FALSE;
1913:   mg->Nc                 = -1;
1914:   mg->eigenvalue         = -1;

1916:   pc->useAmat = PETSC_TRUE;

1918:   pc->ops->apply          = PCApply_MG;
1919:   pc->ops->applytranspose = PCApplyTranspose_MG;
1920:   pc->ops->matapply       = PCMatApply_MG;
1921:   pc->ops->setup          = PCSetUp_MG;
1922:   pc->ops->reset          = PCReset_MG;
1923:   pc->ops->destroy        = PCDestroy_MG;
1924:   pc->ops->setfromoptions = PCSetFromOptions_MG;
1925:   pc->ops->view           = PCView_MG;

1927:   PetscObjectComposedDataRegister(&mg->eigenvalue);
1928:   PetscObjectComposeFunction((PetscObject)pc,"PCMGSetGalerkin_C",PCMGSetGalerkin_MG);
1929:   PetscObjectComposeFunction((PetscObject)pc,"PCMGGetLevels_C",PCMGGetLevels_MG);
1930:   PetscObjectComposeFunction((PetscObject)pc,"PCMGSetLevels_C",PCMGSetLevels_MG);
1931:   PetscObjectComposeFunction((PetscObject)pc,"PCGetInterpolations_C",PCGetInterpolations_MG);
1932:   PetscObjectComposeFunction((PetscObject)pc,"PCGetCoarseOperators_C",PCGetCoarseOperators_MG);
1933:   PetscObjectComposeFunction((PetscObject)pc,"PCMGSetAdaptInterpolation_C",PCMGSetAdaptInterpolation_MG);
1934:   PetscObjectComposeFunction((PetscObject)pc,"PCMGGetAdaptInterpolation_C",PCMGGetAdaptInterpolation_MG);
1935:   PetscObjectComposeFunction((PetscObject)pc,"PCMGSetAdaptCR_C",PCMGSetAdaptCR_MG);
1936:   PetscObjectComposeFunction((PetscObject)pc,"PCMGGetAdaptCR_C",PCMGGetAdaptCR_MG);
1937:   return(0);
1938: }