Actual source code: mg.c
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, &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, &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, &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. Use comms = NULL to specify that all processes
463: should participate in each level of problem.
465: Level: intermediate
467: Notes:
468: If the number of levels is one then the multigrid uses the -mg_levels prefix
469: for setting the level options rather than the -mg_coarse prefix.
471: You can free the information in comms after this routine is called.
473: The array of MPI communicators must contain MPI_COMM_NULL for those ranks that at each level
474: are not participating in the coarser solve. For example, with 2 levels and 1 and 2 ranks on
475: the two levels, rank 0 in the original communicator will pass in an array of 2 communicators
476: of size 2 and 1, while rank 1 in the original communicator will pass in array of 2 communicators
477: the first of size 2 and the second of value MPI_COMM_NULL since the rank 1 does not participate
478: in the coarse grid solve.
480: Since each coarser level may have a new MPI_Comm with fewer ranks than the previous, one
481: must take special care in providing the restriction and interpolation operation. We recommend
482: providing these as two step operations; first perform a standard restriction or interpolation on
483: the full number of ranks for that level and then use an MPI call to copy the resulting vector
484: array entries (after calls to VecGetArray()) to the smaller or larger number of ranks, note in both
485: cases the MPI calls must be made on the larger of the two communicators. Traditional MPI send and
486: recieves or MPI_AlltoAllv() could be used to do the reshuffling of the vector entries.
488: Fortran Notes:
489: Use comms = PETSC_NULL_MPI_COMM as the equivalent of NULL in the C interface. Note PETSC_NULL_MPI_COMM
490: is not MPI_COMM_NULL. It is more like PETSC_NULL_INTEGER, PETSC_NULL_REAL etc.
492: .seealso: PCMGSetType(), PCMGGetLevels()
493: @*/
494: PetscErrorCode PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
495: {
501: PetscTryMethod(pc,"PCMGSetLevels_C",(PC,PetscInt,MPI_Comm*),(pc,levels,comms));
502: return(0);
503: }
505: PetscErrorCode PCDestroy_MG(PC pc)
506: {
508: PC_MG *mg = (PC_MG*)pc->data;
509: PC_MG_Levels **mglevels = mg->levels;
510: PetscInt i,n;
513: PCReset_MG(pc);
514: if (mglevels) {
515: n = mglevels[0]->levels;
516: for (i=0; i<n; i++) {
517: if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
518: KSPDestroy(&mglevels[i]->smoothd);
519: }
520: KSPDestroy(&mglevels[i]->smoothu);
521: KSPDestroy(&mglevels[i]->cr);
522: PetscFree(mglevels[i]);
523: }
524: PetscFree(mg->levels);
525: }
526: PetscFree(pc->data);
527: PetscObjectComposeFunction((PetscObject)pc,"PCGetInterpolations_C",NULL);
528: PetscObjectComposeFunction((PetscObject)pc,"PCGetCoarseOperators_C",NULL);
529: return(0);
530: }
532: /*
533: PCApply_MG - Runs either an additive, multiplicative, Kaskadic
534: or full cycle of multigrid.
536: Note:
537: A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle().
538: */
539: static PetscErrorCode PCApply_MG_Internal(PC pc,Vec b,Vec x,Mat B,Mat X,PetscBool transpose)
540: {
541: PC_MG *mg = (PC_MG*)pc->data;
542: PC_MG_Levels **mglevels = mg->levels;
544: PC tpc;
545: PetscInt levels = mglevels[0]->levels,i;
546: PetscBool changeu,changed,matapp;
549: matapp = (PetscBool)(B && X);
550: if (mg->stageApply) {PetscLogStagePush(mg->stageApply);}
551: /* When the DM is supplying the matrix then it will not exist until here */
552: for (i=0; i<levels; i++) {
553: if (!mglevels[i]->A) {
554: KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);
555: PetscObjectReference((PetscObject)mglevels[i]->A);
556: }
557: }
559: KSPGetPC(mglevels[levels-1]->smoothd,&tpc);
560: PCPreSolveChangeRHS(tpc,&changed);
561: KSPGetPC(mglevels[levels-1]->smoothu,&tpc);
562: PCPreSolveChangeRHS(tpc,&changeu);
563: if (!changeu && !changed) {
564: if (matapp) {
565: MatDestroy(&mglevels[levels-1]->B);
566: mglevels[levels-1]->B = B;
567: } else {
568: VecDestroy(&mglevels[levels-1]->b);
569: mglevels[levels-1]->b = b;
570: }
571: } else { /* if the smoother changes the rhs during PreSolve, we cannot use the input vector */
572: if (matapp) {
573: if (mglevels[levels-1]->B) {
574: PetscInt N1,N2;
575: PetscBool flg;
577: MatGetSize(mglevels[levels-1]->B,NULL,&N1);
578: MatGetSize(B,NULL,&N2);
579: PetscObjectTypeCompare((PetscObject)mglevels[levels-1]->B,((PetscObject)B)->type_name,&flg);
580: if (N1 != N2 || !flg) {
581: MatDestroy(&mglevels[levels-1]->B);
582: }
583: }
584: if (!mglevels[levels-1]->B) {
585: MatDuplicate(B,MAT_COPY_VALUES,&mglevels[levels-1]->B);
586: } else {
587: MatCopy(B,mglevels[levels-1]->B,SAME_NONZERO_PATTERN);
588: }
589: } else {
590: if (!mglevels[levels-1]->b) {
591: Vec *vec;
593: KSPCreateVecs(mglevels[levels-1]->smoothd,1,&vec,0,NULL);
594: mglevels[levels-1]->b = *vec;
595: PetscFree(vec);
596: }
597: VecCopy(b,mglevels[levels-1]->b);
598: }
599: }
600: if (matapp) { mglevels[levels-1]->X = X; }
601: else { mglevels[levels-1]->x = x; }
603: /* If coarser Xs are present, it means we have already block applied the PC at least once
604: Reset operators if sizes/type do no match */
605: if (matapp && levels > 1 && mglevels[levels-2]->X) {
606: PetscInt Xc,Bc;
607: PetscBool flg;
609: MatGetSize(mglevels[levels-2]->X,NULL,&Xc);
610: MatGetSize(mglevels[levels-1]->B,NULL,&Bc);
611: PetscObjectTypeCompare((PetscObject)mglevels[levels-2]->X,((PetscObject)mglevels[levels-1]->X)->type_name,&flg);
612: if (Xc != Bc || !flg) {
613: MatDestroy(&mglevels[levels-1]->R);
614: for (i=0;i<levels-1;i++) {
615: MatDestroy(&mglevels[i]->R);
616: MatDestroy(&mglevels[i]->B);
617: MatDestroy(&mglevels[i]->X);
618: }
619: }
620: }
622: if (mg->am == PC_MG_MULTIPLICATIVE) {
623: if (matapp) { MatZeroEntries(X); }
624: else { VecZeroEntries(x); }
625: for (i=0; i<mg->cyclesperpcapply; i++) {
626: PCMGMCycle_Private(pc,mglevels+levels-1,transpose,matapp,NULL);
627: }
628: } else if (mg->am == PC_MG_ADDITIVE) {
629: PCMGACycle_Private(pc,mglevels,transpose,matapp);
630: } else if (mg->am == PC_MG_KASKADE) {
631: PCMGKCycle_Private(pc,mglevels,transpose,matapp);
632: } else {
633: PCMGFCycle_Private(pc,mglevels,transpose,matapp);
634: }
635: if (mg->stageApply) {PetscLogStagePop();}
636: if (!changeu && !changed) {
637: if (matapp) { mglevels[levels-1]->B = NULL; }
638: else { mglevels[levels-1]->b = NULL; }
639: }
640: return(0);
641: }
643: static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
644: {
648: PCApply_MG_Internal(pc,b,x,NULL,NULL,PETSC_FALSE);
649: return(0);
650: }
652: static PetscErrorCode PCApplyTranspose_MG(PC pc,Vec b,Vec x)
653: {
657: PCApply_MG_Internal(pc,b,x,NULL,NULL,PETSC_TRUE);
658: return(0);
659: }
661: static PetscErrorCode PCMatApply_MG(PC pc,Mat b,Mat x)
662: {
666: PCApply_MG_Internal(pc,NULL,NULL,b,x,PETSC_FALSE);
667: return(0);
668: }
670: PetscErrorCode PCSetFromOptions_MG(PetscOptionItems *PetscOptionsObject,PC pc)
671: {
672: PetscErrorCode ierr;
673: PetscInt levels,cycles;
674: PetscBool flg, flg2;
675: PC_MG *mg = (PC_MG*)pc->data;
676: PC_MG_Levels **mglevels;
677: PCMGType mgtype;
678: PCMGCycleType mgctype;
679: PCMGGalerkinType gtype;
682: levels = PetscMax(mg->nlevels,1);
683: PetscOptionsHead(PetscOptionsObject,"Multigrid options");
684: PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);
685: if (!flg && !mg->levels && pc->dm) {
686: DMGetRefineLevel(pc->dm,&levels);
687: levels++;
688: mg->usedmfornumberoflevels = PETSC_TRUE;
689: }
690: PCMGSetLevels(pc,levels,NULL);
691: mglevels = mg->levels;
693: mgctype = (PCMGCycleType) mglevels[0]->cycles;
694: PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);
695: if (flg) {
696: PCMGSetCycleType(pc,mgctype);
697: }
698: gtype = mg->galerkin;
699: PetscOptionsEnum("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",PCMGGalerkinTypes,(PetscEnum)gtype,(PetscEnum*)>ype,&flg);
700: if (flg) {
701: PCMGSetGalerkin(pc,gtype);
702: }
703: flg2 = PETSC_FALSE;
704: PetscOptionsBool("-pc_mg_adapt_interp","Adapt interpolation using some coarse space","PCMGSetAdaptInterpolation",PETSC_FALSE,&flg2,&flg);
705: if (flg) {PCMGSetAdaptInterpolation(pc, flg2);}
706: PetscOptionsInt("-pc_mg_adapt_interp_n","Size of the coarse space for adaptive interpolation","PCMGSetCoarseSpace",mg->Nc,&mg->Nc,&flg);
707: 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);
708: PetscOptionsBool("-pc_mg_mesp_monitor","Monitor the multilevel eigensolver","PCMGSetAdaptInterpolation",PETSC_FALSE,&mg->mespMonitor,&flg);
709: flg2 = PETSC_FALSE;
710: PetscOptionsBool("-pc_mg_adapt_cr","Monitor coarse space quality using Compatible Relaxation (CR)","PCMGSetAdaptCR",PETSC_FALSE,&flg2,&flg);
711: if (flg) {PCMGSetAdaptCR(pc, flg2);}
712: flg = PETSC_FALSE;
713: PetscOptionsBool("-pc_mg_distinct_smoothup","Create separate smoothup KSP and append the prefix _up","PCMGSetDistinctSmoothUp",PETSC_FALSE,&flg,NULL);
714: if (flg) {
715: PCMGSetDistinctSmoothUp(pc);
716: }
717: mgtype = mg->am;
718: PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);
719: if (flg) {
720: PCMGSetType(pc,mgtype);
721: }
722: if (mg->am == PC_MG_MULTIPLICATIVE) {
723: PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGMultiplicativeSetCycles",mg->cyclesperpcapply,&cycles,&flg);
724: if (flg) {
725: PCMGMultiplicativeSetCycles(pc,cycles);
726: }
727: }
728: flg = PETSC_FALSE;
729: PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,NULL);
730: if (flg) {
731: PetscInt i;
732: char eventname[128];
734: levels = mglevels[0]->levels;
735: for (i=0; i<levels; i++) {
736: sprintf(eventname,"MGSetup Level %d",(int)i);
737: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);
738: sprintf(eventname,"MGSmooth Level %d",(int)i);
739: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);
740: if (i) {
741: sprintf(eventname,"MGResid Level %d",(int)i);
742: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);
743: sprintf(eventname,"MGInterp Level %d",(int)i);
744: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);
745: }
746: }
748: #if defined(PETSC_USE_LOG)
749: {
750: const char *sname = "MG Apply";
751: PetscStageLog stageLog;
752: PetscInt st;
754: PetscLogGetStageLog(&stageLog);
755: for (st = 0; st < stageLog->numStages; ++st) {
756: PetscBool same;
758: PetscStrcmp(stageLog->stageInfo[st].name, sname, &same);
759: if (same) mg->stageApply = st;
760: }
761: if (!mg->stageApply) {
762: PetscLogStageRegister(sname, &mg->stageApply);
763: }
764: }
765: #endif
766: }
767: PetscOptionsTail();
768: /* Check option consistency */
769: PCMGGetGalerkin(pc, >ype);
770: PCMGGetAdaptInterpolation(pc, &flg);
771: if (flg && (gtype >= PC_MG_GALERKIN_NONE)) SETERRQ(PetscObjectComm((PetscObject) pc), PETSC_ERR_ARG_INCOMP, "Must use Galerkin coarse operators when adapting the interpolator");
772: return(0);
773: }
775: const char *const PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",NULL};
776: const char *const PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",NULL};
777: const char *const PCMGGalerkinTypes[] = {"both","pmat","mat","none","external","PCMGGalerkinType","PC_MG_GALERKIN",NULL};
778: const char *const PCMGCoarseSpaceTypes[] = {"polynomial","harmonic","eigenvector","generalized_eigenvector","PCMGCoarseSpaceType","PCMG_POLYNOMIAL",NULL};
780: #include <petscdraw.h>
781: PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
782: {
783: PC_MG *mg = (PC_MG*)pc->data;
784: PC_MG_Levels **mglevels = mg->levels;
786: PetscInt levels = mglevels ? mglevels[0]->levels : 0,i;
787: PetscBool iascii,isbinary,isdraw;
790: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
791: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
792: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
793: if (iascii) {
794: const char *cyclename = levels ? (mglevels[0]->cycles == PC_MG_CYCLE_V ? "v" : "w") : "unknown";
795: PetscViewerASCIIPrintf(viewer," type is %s, levels=%D cycles=%s\n", PCMGTypes[mg->am],levels,cyclename);
796: if (mg->am == PC_MG_MULTIPLICATIVE) {
797: PetscViewerASCIIPrintf(viewer," Cycles per PCApply=%d\n",mg->cyclesperpcapply);
798: }
799: if (mg->galerkin == PC_MG_GALERKIN_BOTH) {
800: PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices\n");
801: } else if (mg->galerkin == PC_MG_GALERKIN_PMAT) {
802: PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices for pmat\n");
803: } else if (mg->galerkin == PC_MG_GALERKIN_MAT) {
804: PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices for mat\n");
805: } else if (mg->galerkin == PC_MG_GALERKIN_EXTERNAL) {
806: PetscViewerASCIIPrintf(viewer," Using externally compute Galerkin coarse grid matrices\n");
807: } else {
808: PetscViewerASCIIPrintf(viewer," Not using Galerkin computed coarse grid matrices\n");
809: }
810: if (mg->view) {
811: (*mg->view)(pc,viewer);
812: }
813: for (i=0; i<levels; i++) {
814: if (!i) {
815: PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level -------------------------------\n",i);
816: } else {
817: PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);
818: }
819: PetscViewerASCIIPushTab(viewer);
820: KSPView(mglevels[i]->smoothd,viewer);
821: PetscViewerASCIIPopTab(viewer);
822: if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) {
823: PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");
824: } else if (i) {
825: PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);
826: PetscViewerASCIIPushTab(viewer);
827: KSPView(mglevels[i]->smoothu,viewer);
828: PetscViewerASCIIPopTab(viewer);
829: }
830: if (i && mglevels[i]->cr) {
831: PetscViewerASCIIPrintf(viewer,"CR solver on level %D -------------------------------\n",i);
832: PetscViewerASCIIPushTab(viewer);
833: KSPView(mglevels[i]->cr,viewer);
834: PetscViewerASCIIPopTab(viewer);
835: }
836: }
837: } else if (isbinary) {
838: for (i=levels-1; i>=0; i--) {
839: KSPView(mglevels[i]->smoothd,viewer);
840: if (i && mglevels[i]->smoothd != mglevels[i]->smoothu) {
841: KSPView(mglevels[i]->smoothu,viewer);
842: }
843: }
844: } else if (isdraw) {
845: PetscDraw draw;
846: PetscReal x,w,y,bottom,th;
847: PetscViewerDrawGetDraw(viewer,0,&draw);
848: PetscDrawGetCurrentPoint(draw,&x,&y);
849: PetscDrawStringGetSize(draw,NULL,&th);
850: bottom = y - th;
851: for (i=levels-1; i>=0; i--) {
852: if (!mglevels[i]->smoothu || (mglevels[i]->smoothu == mglevels[i]->smoothd)) {
853: PetscDrawPushCurrentPoint(draw,x,bottom);
854: KSPView(mglevels[i]->smoothd,viewer);
855: PetscDrawPopCurrentPoint(draw);
856: } else {
857: w = 0.5*PetscMin(1.0-x,x);
858: PetscDrawPushCurrentPoint(draw,x+w,bottom);
859: KSPView(mglevels[i]->smoothd,viewer);
860: PetscDrawPopCurrentPoint(draw);
861: PetscDrawPushCurrentPoint(draw,x-w,bottom);
862: KSPView(mglevels[i]->smoothu,viewer);
863: PetscDrawPopCurrentPoint(draw);
864: }
865: PetscDrawGetBoundingBox(draw,NULL,&bottom,NULL,NULL);
866: bottom -= th;
867: }
868: }
869: return(0);
870: }
872: #include <petsc/private/kspimpl.h>
874: /*
875: Calls setup for the KSP on each level
876: */
877: PetscErrorCode PCSetUp_MG(PC pc)
878: {
879: PC_MG *mg = (PC_MG*)pc->data;
880: PC_MG_Levels **mglevels = mg->levels;
882: PetscInt i,n;
883: PC cpc;
884: PetscBool dump = PETSC_FALSE,opsset,use_amat,missinginterpolate = PETSC_FALSE;
885: Mat dA,dB;
886: Vec tvec;
887: DM *dms;
888: PetscViewer viewer = NULL;
889: PetscBool dAeqdB = PETSC_FALSE, needRestricts = PETSC_FALSE, doCR = PETSC_FALSE;
892: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels with PCMGSetLevels() before setting up");
893: n = mglevels[0]->levels;
894: /* FIX: Move this to PCSetFromOptions_MG? */
895: if (mg->usedmfornumberoflevels) {
896: PetscInt levels;
897: DMGetRefineLevel(pc->dm,&levels);
898: levels++;
899: if (levels > n) { /* the problem is now being solved on a finer grid */
900: PCMGSetLevels(pc,levels,NULL);
901: n = levels;
902: PCSetFromOptions(pc); /* it is bad to call this here, but otherwise will never be called for the new hierarchy */
903: mglevels = mg->levels;
904: }
905: }
906: KSPGetPC(mglevels[0]->smoothd,&cpc);
908: /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */
909: /* so use those from global PC */
910: /* Is this what we always want? What if user wants to keep old one? */
911: KSPGetOperatorsSet(mglevels[n-1]->smoothd,NULL,&opsset);
912: if (opsset) {
913: Mat mmat;
914: KSPGetOperators(mglevels[n-1]->smoothd,NULL,&mmat);
915: if (mmat == pc->pmat) opsset = PETSC_FALSE;
916: }
918: /* Create CR solvers */
919: PCMGGetAdaptCR(pc, &doCR);
920: if (doCR) {
921: const char *prefix;
923: PCGetOptionsPrefix(pc, &prefix);
924: for (i = 1; i < n; ++i) {
925: PC ipc, cr;
926: char crprefix[128];
928: KSPCreate(PetscObjectComm((PetscObject) pc), &mglevels[i]->cr);
929: KSPSetErrorIfNotConverged(mglevels[i]->cr, PETSC_FALSE);
930: PetscObjectIncrementTabLevel((PetscObject) mglevels[i]->cr, (PetscObject) pc, n-i);
931: KSPSetOptionsPrefix(mglevels[i]->cr, prefix);
932: PetscObjectComposedDataSetInt((PetscObject) mglevels[i]->cr, PetscMGLevelId, mglevels[i]->level);
933: KSPSetType(mglevels[i]->cr, KSPCHEBYSHEV);
934: KSPSetConvergenceTest(mglevels[i]->cr, KSPConvergedSkip, NULL, NULL);
935: KSPSetNormType(mglevels[i]->cr, KSP_NORM_PRECONDITIONED);
936: KSPGetPC(mglevels[i]->cr, &ipc);
938: PCSetType(ipc, PCCOMPOSITE);
939: PCCompositeSetType(ipc, PC_COMPOSITE_MULTIPLICATIVE);
940: PCCompositeAddPCType(ipc, PCSOR);
941: CreateCR_Private(pc, i, &cr);
942: PCCompositeAddPC(ipc, cr);
943: PCDestroy(&cr);
945: KSPSetTolerances(mglevels[i]->cr, PETSC_DEFAULT, PETSC_DEFAULT, PETSC_DEFAULT, mg->default_smoothd);
946: KSPSetInitialGuessNonzero(mglevels[i]->cr, PETSC_TRUE);
947: PetscSNPrintf(crprefix, 128, "mg_levels_%d_cr_", (int) i);
948: KSPAppendOptionsPrefix(mglevels[i]->cr, crprefix);
949: PetscLogObjectParent((PetscObject) pc, (PetscObject) mglevels[i]->cr);
950: }
951: }
953: if (!opsset) {
954: PCGetUseAmat(pc,&use_amat);
955: if (use_amat) {
956: PetscInfo(pc,"Using outer operators to define finest grid operator \n because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
957: KSPSetOperators(mglevels[n-1]->smoothd,pc->mat,pc->pmat);
958: } else {
959: PetscInfo(pc,"Using matrix (pmat) operators to define finest grid operator \n because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
960: KSPSetOperators(mglevels[n-1]->smoothd,pc->pmat,pc->pmat);
961: }
962: }
964: for (i=n-1; i>0; i--) {
965: if (!(mglevels[i]->interpolate || mglevels[i]->restrct)) {
966: missinginterpolate = PETSC_TRUE;
967: continue;
968: }
969: }
971: KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB);
972: if (dA == dB) dAeqdB = PETSC_TRUE;
973: if ((mg->galerkin == PC_MG_GALERKIN_NONE) || (((mg->galerkin == PC_MG_GALERKIN_PMAT) || (mg->galerkin == PC_MG_GALERKIN_MAT)) && !dAeqdB)) {
974: needRestricts = PETSC_TRUE; /* user must compute either mat, pmat, or both so must restrict x to coarser levels */
975: }
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: }
1104: /* Adapt interpolation matrices */
1105: if (mg->adaptInterpolation) {
1106: mg->Nc = mg->Nc < 0 ? 6 : mg->Nc; /* Default to 6 modes */
1107: for (i = 0; i < n; ++i) {
1108: PCMGComputeCoarseSpace_Internal(pc, i, mg->coarseSpaceType, mg->Nc, !i ? NULL : mglevels[i-1]->coarseSpace, &mglevels[i]->coarseSpace);
1109: if (i) {PCMGAdaptInterpolator_Internal(pc, i, mglevels[i-1]->smoothu, mglevels[i]->smoothu, mg->Nc, mglevels[i-1]->coarseSpace, mglevels[i]->coarseSpace);}
1110: }
1111: for (i = n-2; i > -1; --i) {
1112: PCMGRecomputeLevelOperators_Internal(pc, i);
1113: }
1114: }
1116: if (needRestricts && pc->dm) {
1117: for (i=n-2; i>=0; i--) {
1118: DM dmfine,dmcoarse;
1119: Mat Restrict,Inject;
1120: Vec rscale;
1121: KSPGetDM(mglevels[i+1]->smoothd,&dmfine);
1122: KSPGetDM(mglevels[i]->smoothd,&dmcoarse);
1123: PCMGGetRestriction(pc,i+1,&Restrict);
1124: PCMGGetRScale(pc,i+1,&rscale);
1125: PCMGGetInjection(pc,i+1,&Inject);
1126: DMRestrict(dmfine,Restrict,rscale,Inject,dmcoarse);
1127: }
1128: }
1130: if (!pc->setupcalled) {
1131: for (i=0; i<n; i++) {
1132: KSPSetFromOptions(mglevels[i]->smoothd);
1133: }
1134: for (i=1; i<n; i++) {
1135: if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) {
1136: KSPSetFromOptions(mglevels[i]->smoothu);
1137: }
1138: if (mglevels[i]->cr) {
1139: KSPSetFromOptions(mglevels[i]->cr);
1140: }
1141: }
1142: /* insure that if either interpolation or restriction is set the other other one is set */
1143: for (i=1; i<n; i++) {
1144: PCMGGetInterpolation(pc,i,NULL);
1145: PCMGGetRestriction(pc,i,NULL);
1146: }
1147: for (i=0; i<n-1; i++) {
1148: if (!mglevels[i]->b) {
1149: Vec *vec;
1150: KSPCreateVecs(mglevels[i]->smoothd,1,&vec,0,NULL);
1151: PCMGSetRhs(pc,i,*vec);
1152: VecDestroy(vec);
1153: PetscFree(vec);
1154: }
1155: if (!mglevels[i]->r && i) {
1156: VecDuplicate(mglevels[i]->b,&tvec);
1157: PCMGSetR(pc,i,tvec);
1158: VecDestroy(&tvec);
1159: }
1160: if (!mglevels[i]->x) {
1161: VecDuplicate(mglevels[i]->b,&tvec);
1162: PCMGSetX(pc,i,tvec);
1163: VecDestroy(&tvec);
1164: }
1165: if (doCR) {
1166: VecDuplicate(mglevels[i]->b,&mglevels[i]->crx);
1167: VecDuplicate(mglevels[i]->b,&mglevels[i]->crb);
1168: VecZeroEntries(mglevels[i]->crb);
1169: }
1170: }
1171: if (n != 1 && !mglevels[n-1]->r) {
1172: /* PCMGSetR() on the finest level if user did not supply it */
1173: Vec *vec;
1174: KSPCreateVecs(mglevels[n-1]->smoothd,1,&vec,0,NULL);
1175: PCMGSetR(pc,n-1,*vec);
1176: VecDestroy(vec);
1177: PetscFree(vec);
1178: }
1179: if (doCR) {
1180: VecDuplicate(mglevels[n-1]->r, &mglevels[n-1]->crx);
1181: VecDuplicate(mglevels[n-1]->r, &mglevels[n-1]->crb);
1182: VecZeroEntries(mglevels[n-1]->crb);
1183: }
1184: }
1186: if (pc->dm) {
1187: /* need to tell all the coarser levels to rebuild the matrix using the DM for that level */
1188: for (i=0; i<n-1; i++) {
1189: if (mglevels[i]->smoothd->setupstage != KSP_SETUP_NEW) mglevels[i]->smoothd->setupstage = KSP_SETUP_NEWMATRIX;
1190: }
1191: }
1193: for (i=1; i<n; i++) {
1194: if (mglevels[i]->smoothu == mglevels[i]->smoothd || mg->am == PC_MG_FULL || mg->am == PC_MG_KASKADE || mg->cyclesperpcapply > 1) {
1195: /* if doing only down then initial guess is zero */
1196: KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);
1197: }
1198: if (mglevels[i]->cr) {KSPSetInitialGuessNonzero(mglevels[i]->cr,PETSC_TRUE);}
1199: if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1200: KSPSetUp(mglevels[i]->smoothd);
1201: if (mglevels[i]->smoothd->reason == KSP_DIVERGED_PC_FAILED) {
1202: pc->failedreason = PC_SUBPC_ERROR;
1203: }
1204: if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1205: if (!mglevels[i]->residual) {
1206: Mat mat;
1207: KSPGetOperators(mglevels[i]->smoothd,&mat,NULL);
1208: PCMGSetResidual(pc,i,PCMGResidualDefault,mat);
1209: }
1210: if (!mglevels[i]->residualtranspose) {
1211: Mat mat;
1212: KSPGetOperators(mglevels[i]->smoothd,&mat,NULL);
1213: PCMGSetResidualTranspose(pc,i,PCMGResidualTransposeDefault,mat);
1214: }
1215: }
1216: for (i=1; i<n; i++) {
1217: if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) {
1218: Mat downmat,downpmat;
1220: /* check if operators have been set for up, if not use down operators to set them */
1221: KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,NULL);
1222: if (!opsset) {
1223: KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat);
1224: KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat);
1225: }
1227: KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);
1228: if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1229: KSPSetUp(mglevels[i]->smoothu);
1230: if (mglevels[i]->smoothu->reason == KSP_DIVERGED_PC_FAILED) {
1231: pc->failedreason = PC_SUBPC_ERROR;
1232: }
1233: if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1234: }
1235: if (mglevels[i]->cr) {
1236: Mat downmat,downpmat;
1238: /* check if operators have been set for up, if not use down operators to set them */
1239: KSPGetOperatorsSet(mglevels[i]->cr,&opsset,NULL);
1240: if (!opsset) {
1241: KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat);
1242: KSPSetOperators(mglevels[i]->cr,downmat,downpmat);
1243: }
1245: KSPSetInitialGuessNonzero(mglevels[i]->cr,PETSC_TRUE);
1246: if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1247: KSPSetUp(mglevels[i]->cr);
1248: if (mglevels[i]->cr->reason == KSP_DIVERGED_PC_FAILED) {
1249: pc->failedreason = PC_SUBPC_ERROR;
1250: }
1251: if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1252: }
1253: }
1255: if (mglevels[0]->eventsmoothsetup) {PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);}
1256: KSPSetUp(mglevels[0]->smoothd);
1257: if (mglevels[0]->smoothd->reason == KSP_DIVERGED_PC_FAILED) {
1258: pc->failedreason = PC_SUBPC_ERROR;
1259: }
1260: if (mglevels[0]->eventsmoothsetup) {PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);}
1262: /*
1263: Dump the interpolation/restriction matrices plus the
1264: Jacobian/stiffness on each level. This allows MATLAB users to
1265: easily check if the Galerkin condition A_c = R A_f R^T is satisfied.
1267: Only support one or the other at the same time.
1268: */
1269: #if defined(PETSC_USE_SOCKET_VIEWER)
1270: PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,NULL);
1271: if (dump) viewer = PETSC_VIEWER_SOCKET_(PetscObjectComm((PetscObject)pc));
1272: dump = PETSC_FALSE;
1273: #endif
1274: PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,NULL);
1275: if (dump) viewer = PETSC_VIEWER_BINARY_(PetscObjectComm((PetscObject)pc));
1277: if (viewer) {
1278: for (i=1; i<n; i++) {
1279: MatView(mglevels[i]->restrct,viewer);
1280: }
1281: for (i=0; i<n; i++) {
1282: KSPGetPC(mglevels[i]->smoothd,&pc);
1283: MatView(pc->mat,viewer);
1284: }
1285: }
1286: return(0);
1287: }
1289: /* -------------------------------------------------------------------------------------*/
1291: PetscErrorCode PCMGGetLevels_MG(PC pc, PetscInt *levels)
1292: {
1293: PC_MG *mg = (PC_MG *) pc->data;
1296: *levels = mg->nlevels;
1297: return(0);
1298: }
1300: /*@
1301: PCMGGetLevels - Gets the number of levels to use with MG.
1303: Not Collective
1305: Input Parameter:
1306: . pc - the preconditioner context
1308: Output parameter:
1309: . levels - the number of levels
1311: Level: advanced
1313: .seealso: PCMGSetLevels()
1314: @*/
1315: PetscErrorCode PCMGGetLevels(PC pc,PetscInt *levels)
1316: {
1322: *levels = 0;
1323: PetscTryMethod(pc,"PCMGGetLevels_C",(PC,PetscInt*),(pc,levels));
1324: return(0);
1325: }
1327: /*@
1328: PCMGSetType - Determines the form of multigrid to use:
1329: multiplicative, additive, full, or the Kaskade algorithm.
1331: Logically Collective on PC
1333: Input Parameters:
1334: + pc - the preconditioner context
1335: - form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
1336: PC_MG_FULL, PC_MG_KASKADE
1338: Options Database Key:
1339: . -pc_mg_type <form> - Sets <form>, one of multiplicative,
1340: additive, full, kaskade
1342: Level: advanced
1344: .seealso: PCMGSetLevels()
1345: @*/
1346: PetscErrorCode PCMGSetType(PC pc,PCMGType form)
1347: {
1348: PC_MG *mg = (PC_MG*)pc->data;
1353: mg->am = form;
1354: if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
1355: else pc->ops->applyrichardson = NULL;
1356: return(0);
1357: }
1359: /*@
1360: PCMGGetType - Determines the form of multigrid to use:
1361: multiplicative, additive, full, or the Kaskade algorithm.
1363: Logically Collective on PC
1365: Input Parameter:
1366: . pc - the preconditioner context
1368: Output Parameter:
1369: . type - one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,PC_MG_FULL, PC_MG_KASKADE
1371: Level: advanced
1373: .seealso: PCMGSetLevels()
1374: @*/
1375: PetscErrorCode PCMGGetType(PC pc,PCMGType *type)
1376: {
1377: PC_MG *mg = (PC_MG*)pc->data;
1381: *type = mg->am;
1382: return(0);
1383: }
1385: /*@
1386: PCMGSetCycleType - Sets the type cycles to use. Use PCMGSetCycleTypeOnLevel() for more
1387: complicated cycling.
1389: Logically Collective on PC
1391: Input Parameters:
1392: + pc - the multigrid context
1393: - n - either PC_MG_CYCLE_V or PC_MG_CYCLE_W
1395: Options Database Key:
1396: . -pc_mg_cycle_type <v,w> - provide the cycle desired
1398: Level: advanced
1400: .seealso: PCMGSetCycleTypeOnLevel()
1401: @*/
1402: PetscErrorCode PCMGSetCycleType(PC pc,PCMGCycleType n)
1403: {
1404: PC_MG *mg = (PC_MG*)pc->data;
1405: PC_MG_Levels **mglevels = mg->levels;
1406: PetscInt i,levels;
1411: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1412: levels = mglevels[0]->levels;
1413: for (i=0; i<levels; i++) mglevels[i]->cycles = n;
1414: return(0);
1415: }
1417: /*@
1418: PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step
1419: of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used
1421: Logically Collective on PC
1423: Input Parameters:
1424: + pc - the multigrid context
1425: - n - number of cycles (default is 1)
1427: Options Database Key:
1428: . -pc_mg_multiplicative_cycles n
1430: Level: advanced
1432: Notes:
1433: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType()
1435: .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
1436: @*/
1437: PetscErrorCode PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
1438: {
1439: PC_MG *mg = (PC_MG*)pc->data;
1444: mg->cyclesperpcapply = n;
1445: return(0);
1446: }
1448: PetscErrorCode PCMGSetGalerkin_MG(PC pc,PCMGGalerkinType use)
1449: {
1450: PC_MG *mg = (PC_MG*)pc->data;
1453: mg->galerkin = use;
1454: return(0);
1455: }
1457: /*@
1458: PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
1459: finest grid via the Galerkin process: A_i-1 = r_i * A_i * p_i
1461: Logically Collective on PC
1463: Input Parameters:
1464: + pc - the multigrid context
1465: - use - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, or PC_MG_GALERKIN_NONE
1467: Options Database Key:
1468: . -pc_mg_galerkin <both,pmat,mat,none>
1470: Level: intermediate
1472: Notes:
1473: Some codes that use PCMG such as PCGAMG use Galerkin internally while constructing the hierarchy and thus do not
1474: use the PCMG construction of the coarser grids.
1476: .seealso: PCMGGetGalerkin(), PCMGGalerkinType
1478: @*/
1479: PetscErrorCode PCMGSetGalerkin(PC pc,PCMGGalerkinType use)
1480: {
1485: PetscTryMethod(pc,"PCMGSetGalerkin_C",(PC,PCMGGalerkinType),(pc,use));
1486: return(0);
1487: }
1489: /*@
1490: PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
1491: A_i-1 = r_i * A_i * p_i
1493: Not Collective
1495: Input Parameter:
1496: . pc - the multigrid context
1498: Output Parameter:
1499: . galerkin - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, PC_MG_GALERKIN_NONE, or PC_MG_GALERKIN_EXTERNAL
1501: Level: intermediate
1503: .seealso: PCMGSetGalerkin(), PCMGGalerkinType
1505: @*/
1506: PetscErrorCode PCMGGetGalerkin(PC pc,PCMGGalerkinType *galerkin)
1507: {
1508: PC_MG *mg = (PC_MG*)pc->data;
1512: *galerkin = mg->galerkin;
1513: return(0);
1514: }
1516: PetscErrorCode PCMGSetAdaptInterpolation_MG(PC pc, PetscBool adapt)
1517: {
1518: PC_MG *mg = (PC_MG *) pc->data;
1521: mg->adaptInterpolation = adapt;
1522: return(0);
1523: }
1525: PetscErrorCode PCMGGetAdaptInterpolation_MG(PC pc, PetscBool *adapt)
1526: {
1527: PC_MG *mg = (PC_MG *) pc->data;
1530: *adapt = mg->adaptInterpolation;
1531: return(0);
1532: }
1534: PetscErrorCode PCMGSetAdaptCR_MG(PC pc, PetscBool cr)
1535: {
1536: PC_MG *mg = (PC_MG *) pc->data;
1539: mg->compatibleRelaxation = cr;
1540: return(0);
1541: }
1543: PetscErrorCode PCMGGetAdaptCR_MG(PC pc, PetscBool *cr)
1544: {
1545: PC_MG *mg = (PC_MG *) pc->data;
1548: *cr = mg->compatibleRelaxation;
1549: return(0);
1550: }
1552: /*@
1553: PCMGSetAdaptInterpolation - Adapt the interpolator based upon a vector space which should be accurately captured by the next coarser mesh, and thus accurately interpolated.
1555: Logically Collective on PC
1557: Input Parameters:
1558: + pc - the multigrid context
1559: - adapt - flag for adaptation of the interpolator
1561: Options Database Keys:
1562: + -pc_mg_adapt_interp - Turn on adaptation
1563: . -pc_mg_adapt_interp_n <int> - The number of modes to use, should be divisible by dimension
1564: - -pc_mg_adapt_interp_coarse_space <type> - The type of coarse space: polynomial, harmonic, eigenvector, generalized_eigenvector
1566: Level: intermediate
1568: .keywords: MG, set, Galerkin
1569: .seealso: PCMGGetAdaptInterpolation(), PCMGSetGalerkin()
1570: @*/
1571: PetscErrorCode PCMGSetAdaptInterpolation(PC pc, PetscBool adapt)
1572: {
1577: PetscTryMethod(pc,"PCMGSetAdaptInterpolation_C",(PC,PetscBool),(pc,adapt));
1578: return(0);
1579: }
1581: /*@
1582: 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.
1584: Not collective
1586: Input Parameter:
1587: . pc - the multigrid context
1589: Output Parameter:
1590: . adapt - flag for adaptation of the interpolator
1592: Level: intermediate
1594: .keywords: MG, set, Galerkin
1595: .seealso: PCMGSetAdaptInterpolation(), PCMGSetGalerkin()
1596: @*/
1597: PetscErrorCode PCMGGetAdaptInterpolation(PC pc, PetscBool *adapt)
1598: {
1604: PetscUseMethod(pc,"PCMGGetAdaptInterpolation_C",(PC,PetscBool*),(pc,adapt));
1605: return(0);
1606: }
1608: /*@
1609: PCMGSetAdaptCR - Monitor the coarse space quality using an auxiliary solve with compatible relaxation.
1611: Logically Collective on PC
1613: Input Parameters:
1614: + pc - the multigrid context
1615: - cr - flag for compatible relaxation
1617: Options Database Keys:
1618: . -pc_mg_adapt_cr - Turn on compatible relaxation
1620: Level: intermediate
1622: .keywords: MG, set, Galerkin
1623: .seealso: PCMGGetAdaptCR(), PCMGSetAdaptInterpolation(), PCMGSetGalerkin()
1624: @*/
1625: PetscErrorCode PCMGSetAdaptCR(PC pc, PetscBool cr)
1626: {
1631: PetscTryMethod(pc,"PCMGSetAdaptCR_C",(PC,PetscBool),(pc,cr));
1632: return(0);
1633: }
1635: /*@
1636: PCMGGetAdaptCR - Get the flag to monitor coarse space quality using an auxiliary solve with compatible relaxation.
1638: Not collective
1640: Input Parameter:
1641: . pc - the multigrid context
1643: Output Parameter:
1644: . cr - flag for compatible relaxaion
1646: Level: intermediate
1648: .keywords: MG, set, Galerkin
1649: .seealso: PCMGSetAdaptCR(), PCMGGetAdaptInterpolation(), PCMGSetGalerkin()
1650: @*/
1651: PetscErrorCode PCMGGetAdaptCR(PC pc, PetscBool *cr)
1652: {
1658: PetscUseMethod(pc,"PCMGGetAdaptCR_C",(PC,PetscBool*),(pc,cr));
1659: return(0);
1660: }
1662: /*@
1663: PCMGSetNumberSmooth - Sets the number of pre and post-smoothing steps to use
1664: on all levels. Use PCMGDistinctSmoothUp() to create separate up and down smoothers if you want different numbers of
1665: pre- and post-smoothing steps.
1667: Logically Collective on PC
1669: Input Parameters:
1670: + mg - the multigrid context
1671: - n - the number of smoothing steps
1673: Options Database Key:
1674: . -mg_levels_ksp_max_it <n> - Sets number of pre and post-smoothing steps
1676: Level: advanced
1678: Notes:
1679: this does not set a value on the coarsest grid, since we assume that
1680: there is no separate smooth up on the coarsest grid.
1682: .seealso: PCMGSetDistinctSmoothUp()
1683: @*/
1684: PetscErrorCode PCMGSetNumberSmooth(PC pc,PetscInt n)
1685: {
1686: PC_MG *mg = (PC_MG*)pc->data;
1687: PC_MG_Levels **mglevels = mg->levels;
1689: PetscInt i,levels;
1694: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1695: levels = mglevels[0]->levels;
1697: for (i=1; i<levels; i++) {
1698: KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1699: KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1700: mg->default_smoothu = n;
1701: mg->default_smoothd = n;
1702: }
1703: return(0);
1704: }
1706: /*@
1707: PCMGSetDistinctSmoothUp - sets the up (post) smoother to be a separate KSP from the down (pre) smoother on all levels
1708: and adds the suffix _up to the options name
1710: Logically Collective on PC
1712: Input Parameters:
1713: . pc - the preconditioner context
1715: Options Database Key:
1716: . -pc_mg_distinct_smoothup
1718: Level: advanced
1720: Notes:
1721: this does not set a value on the coarsest grid, since we assume that
1722: there is no separate smooth up on the coarsest grid.
1724: .seealso: PCMGSetNumberSmooth()
1725: @*/
1726: PetscErrorCode PCMGSetDistinctSmoothUp(PC pc)
1727: {
1728: PC_MG *mg = (PC_MG*)pc->data;
1729: PC_MG_Levels **mglevels = mg->levels;
1731: PetscInt i,levels;
1732: KSP subksp;
1736: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1737: levels = mglevels[0]->levels;
1739: for (i=1; i<levels; i++) {
1740: const char *prefix = NULL;
1741: /* make sure smoother up and down are different */
1742: PCMGGetSmootherUp(pc,i,&subksp);
1743: KSPGetOptionsPrefix(mglevels[i]->smoothd,&prefix);
1744: KSPSetOptionsPrefix(subksp,prefix);
1745: KSPAppendOptionsPrefix(subksp,"up_");
1746: }
1747: return(0);
1748: }
1750: /* No new matrices are created, and the coarse operator matrices are the references to the original ones */
1751: PetscErrorCode PCGetInterpolations_MG(PC pc,PetscInt *num_levels,Mat *interpolations[])
1752: {
1753: PC_MG *mg = (PC_MG*)pc->data;
1754: PC_MG_Levels **mglevels = mg->levels;
1755: Mat *mat;
1756: PetscInt l;
1760: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1761: PetscMalloc1(mg->nlevels,&mat);
1762: for (l=1; l< mg->nlevels; l++) {
1763: mat[l-1] = mglevels[l]->interpolate;
1764: PetscObjectReference((PetscObject)mat[l-1]);
1765: }
1766: *num_levels = mg->nlevels;
1767: *interpolations = mat;
1768: return(0);
1769: }
1771: /* No new matrices are created, and the coarse operator matrices are the references to the original ones */
1772: PetscErrorCode PCGetCoarseOperators_MG(PC pc,PetscInt *num_levels,Mat *coarseOperators[])
1773: {
1774: PC_MG *mg = (PC_MG*)pc->data;
1775: PC_MG_Levels **mglevels = mg->levels;
1776: PetscInt l;
1777: Mat *mat;
1781: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1782: PetscMalloc1(mg->nlevels,&mat);
1783: for (l=0; l<mg->nlevels-1; l++) {
1784: KSPGetOperators(mglevels[l]->smoothd,NULL,&(mat[l]));
1785: PetscObjectReference((PetscObject)mat[l]);
1786: }
1787: *num_levels = mg->nlevels;
1788: *coarseOperators = mat;
1789: return(0);
1790: }
1792: /*@C
1793: PCMGRegisterCoarseSpaceConstructor - Adds a method to the PCMG package for coarse space construction.
1795: Not collective
1797: Input Parameters:
1798: + name - name of the constructor
1799: - function - constructor routine
1801: Notes:
1802: Calling sequence for the routine:
1803: $ my_csp(PC pc, PetscInt l, DM dm, KSP smooth, PetscInt Nc, const Vec initGuess[], Vec **coarseSp)
1804: $ pc - The PC object
1805: $ l - The multigrid level, 0 is the coarse level
1806: $ dm - The DM for this level
1807: $ smooth - The level smoother
1808: $ Nc - The size of the coarse space
1809: $ initGuess - Basis for an initial guess for the space
1810: $ coarseSp - A basis for the computed coarse space
1812: Level: advanced
1814: .seealso: PCMGGetCoarseSpaceConstructor(), PCRegister()
1815: @*/
1816: PetscErrorCode PCMGRegisterCoarseSpaceConstructor(const char name[], PetscErrorCode (*function)(PC, PetscInt, DM, KSP, PetscInt, const Vec[], Vec **))
1817: {
1821: PCInitializePackage();
1822: PetscFunctionListAdd(&PCMGCoarseList,name,function);
1823: return(0);
1824: }
1826: /*@C
1827: PCMGGetCoarseSpaceConstructor - Returns the given coarse space construction method.
1829: Not collective
1831: Input Parameter:
1832: . name - name of the constructor
1834: Output Parameter:
1835: . function - constructor routine
1837: Notes:
1838: Calling sequence for the routine:
1839: $ my_csp(PC pc, PetscInt l, DM dm, KSP smooth, PetscInt Nc, const Vec initGuess[], Vec **coarseSp)
1840: $ pc - The PC object
1841: $ l - The multigrid level, 0 is the coarse level
1842: $ dm - The DM for this level
1843: $ smooth - The level smoother
1844: $ Nc - The size of the coarse space
1845: $ initGuess - Basis for an initial guess for the space
1846: $ coarseSp - A basis for the computed coarse space
1848: Level: advanced
1850: .seealso: PCMGRegisterCoarseSpaceConstructor(), PCRegister()
1851: @*/
1852: PetscErrorCode PCMGGetCoarseSpaceConstructor(const char name[], PetscErrorCode (**function)(PC, PetscInt, DM, KSP, PetscInt, const Vec[], Vec **))
1853: {
1857: PetscFunctionListFind(PCMGCoarseList,name,function);
1858: return(0);
1859: }
1861: /* ----------------------------------------------------------------------------------------*/
1863: /*MC
1864: PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional
1865: information about the coarser grid matrices and restriction/interpolation operators.
1867: Options Database Keys:
1868: + -pc_mg_levels <nlevels> - number of levels including finest
1869: . -pc_mg_cycle_type <v,w> - provide the cycle desired
1870: . -pc_mg_type <additive,multiplicative,full,kaskade> - multiplicative is the default
1871: . -pc_mg_log - log information about time spent on each level of the solver
1872: . -pc_mg_distinct_smoothup - configure up (after interpolation) and down (before restriction) smoothers separately (with different options prefixes)
1873: . -pc_mg_galerkin <both,pmat,mat,none> - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R'
1874: . -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1)
1875: . -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
1876: to the Socket viewer for reading from MATLAB.
1877: - -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices
1878: to the binary output file called binaryoutput
1880: Notes:
1881: 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
1883: When run with a single level the smoother options are used on that level NOT the coarse grid solver options
1885: When run with KSPRICHARDSON the convergence test changes slightly if monitor is turned on. The iteration count may change slightly. This
1886: is because without monitoring the residual norm is computed WITHIN each multigrid cycle on the finest level after the pre-smoothing
1887: (because the residual has just been computed for the multigrid algorithm and is hence available for free) while with monitoring the
1888: residual is computed at the end of each cycle.
1890: Level: intermediate
1892: .seealso: PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE
1893: PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(),
1894: PCMGSetDistinctSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
1895: PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
1896: PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
1897: M*/
1899: PETSC_EXTERN PetscErrorCode PCCreate_MG(PC pc)
1900: {
1901: PC_MG *mg;
1905: PetscNewLog(pc,&mg);
1906: pc->data = mg;
1907: mg->nlevels = -1;
1908: mg->am = PC_MG_MULTIPLICATIVE;
1909: mg->galerkin = PC_MG_GALERKIN_NONE;
1910: mg->adaptInterpolation = PETSC_FALSE;
1911: mg->Nc = -1;
1912: mg->eigenvalue = -1;
1914: pc->useAmat = PETSC_TRUE;
1916: pc->ops->apply = PCApply_MG;
1917: pc->ops->applytranspose = PCApplyTranspose_MG;
1918: pc->ops->matapply = PCMatApply_MG;
1919: pc->ops->setup = PCSetUp_MG;
1920: pc->ops->reset = PCReset_MG;
1921: pc->ops->destroy = PCDestroy_MG;
1922: pc->ops->setfromoptions = PCSetFromOptions_MG;
1923: pc->ops->view = PCView_MG;
1925: PetscObjectComposedDataRegister(&mg->eigenvalue);
1926: PetscObjectComposeFunction((PetscObject)pc,"PCMGSetGalerkin_C",PCMGSetGalerkin_MG);
1927: PetscObjectComposeFunction((PetscObject)pc,"PCMGGetLevels_C",PCMGGetLevels_MG);
1928: PetscObjectComposeFunction((PetscObject)pc,"PCMGSetLevels_C",PCMGSetLevels_MG);
1929: PetscObjectComposeFunction((PetscObject)pc,"PCGetInterpolations_C",PCGetInterpolations_MG);
1930: PetscObjectComposeFunction((PetscObject)pc,"PCGetCoarseOperators_C",PCGetCoarseOperators_MG);
1931: PetscObjectComposeFunction((PetscObject)pc,"PCMGSetAdaptInterpolation_C",PCMGSetAdaptInterpolation_MG);
1932: PetscObjectComposeFunction((PetscObject)pc,"PCMGGetAdaptInterpolation_C",PCMGGetAdaptInterpolation_MG);
1933: PetscObjectComposeFunction((PetscObject)pc,"PCMGSetAdaptCR_C",PCMGSetAdaptCR_MG);
1934: PetscObjectComposeFunction((PetscObject)pc,"PCMGGetAdaptCR_C",PCMGGetAdaptCR_MG);
1935: return(0);
1936: }