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, (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. 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: }
506: PetscErrorCode PCDestroy_MG(PC pc)
507: {
509: PC_MG *mg = (PC_MG*)pc->data;
510: PC_MG_Levels **mglevels = mg->levels;
511: PetscInt i,n;
514: PCReset_MG(pc);
515: if (mglevels) {
516: n = mglevels[0]->levels;
517: for (i=0; i<n; i++) {
518: if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
519: KSPDestroy(&mglevels[i]->smoothd);
520: }
521: KSPDestroy(&mglevels[i]->smoothu);
522: KSPDestroy(&mglevels[i]->cr);
523: PetscFree(mglevels[i]);
524: }
525: PetscFree(mg->levels);
526: }
527: PetscFree(pc->data);
528: PetscObjectComposeFunction((PetscObject)pc,"PCGetInterpolations_C",NULL);
529: PetscObjectComposeFunction((PetscObject)pc,"PCGetCoarseOperators_C",NULL);
530: return(0);
531: }
534: /*
535: PCApply_MG - Runs either an additive, multiplicative, Kaskadic
536: or full cycle of multigrid.
538: Note:
539: A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle().
540: */
541: static PetscErrorCode PCApply_MG_Internal(PC pc,Vec b,Vec x,Mat B,Mat X,PetscBool transpose)
542: {
543: PC_MG *mg = (PC_MG*)pc->data;
544: PC_MG_Levels **mglevels = mg->levels;
546: PC tpc;
547: PetscInt levels = mglevels[0]->levels,i;
548: PetscBool changeu,changed,matapp;
551: matapp = (PetscBool)(B && X);
552: if (mg->stageApply) {PetscLogStagePush(mg->stageApply);}
553: /* When the DM is supplying the matrix then it will not exist until here */
554: for (i=0; i<levels; i++) {
555: if (!mglevels[i]->A) {
556: KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);
557: PetscObjectReference((PetscObject)mglevels[i]->A);
558: }
559: }
561: KSPGetPC(mglevels[levels-1]->smoothd,&tpc);
562: PCPreSolveChangeRHS(tpc,&changed);
563: KSPGetPC(mglevels[levels-1]->smoothu,&tpc);
564: PCPreSolveChangeRHS(tpc,&changeu);
565: if (!changeu && !changed) {
566: if (matapp) {
567: MatDestroy(&mglevels[levels-1]->B);
568: mglevels[levels-1]->B = B;
569: } else {
570: VecDestroy(&mglevels[levels-1]->b);
571: mglevels[levels-1]->b = b;
572: }
573: } else { /* if the smoother changes the rhs during PreSolve, we cannot use the input vector */
574: if (matapp) {
575: if (mglevels[levels-1]->B) {
576: PetscInt N1,N2;
577: PetscBool flg;
579: MatGetSize(mglevels[levels-1]->B,NULL,&N1);
580: MatGetSize(B,NULL,&N2);
581: PetscObjectTypeCompare((PetscObject)mglevels[levels-1]->B,((PetscObject)B)->type_name,&flg);
582: if (N1 != N2 || !flg) {
583: MatDestroy(&mglevels[levels-1]->B);
584: }
585: }
586: if (!mglevels[levels-1]->B) {
587: MatDuplicate(B,MAT_COPY_VALUES,&mglevels[levels-1]->B);
588: } else {
589: MatCopy(B,mglevels[levels-1]->B,SAME_NONZERO_PATTERN);
590: }
591: } else {
592: if (!mglevels[levels-1]->b) {
593: Vec *vec;
595: KSPCreateVecs(mglevels[levels-1]->smoothd,1,&vec,0,NULL);
596: mglevels[levels-1]->b = *vec;
597: PetscFree(vec);
598: }
599: VecCopy(b,mglevels[levels-1]->b);
600: }
601: }
602: if (matapp) { mglevels[levels-1]->X = X; }
603: else { mglevels[levels-1]->x = x; }
605: /* If coarser Xs are present, it means we have already block applied the PC at least once
606: Reset operators if sizes/type do no match */
607: if (matapp && levels > 1 && mglevels[levels-2]->X) {
608: PetscInt Xc,Bc;
609: PetscBool flg;
611: MatGetSize(mglevels[levels-2]->X,NULL,&Xc);
612: MatGetSize(mglevels[levels-1]->B,NULL,&Bc);
613: PetscObjectTypeCompare((PetscObject)mglevels[levels-2]->X,((PetscObject)mglevels[levels-1]->X)->type_name,&flg);
614: if (Xc != Bc || !flg) {
615: MatDestroy(&mglevels[levels-1]->R);
616: for (i=0;i<levels-1;i++) {
617: MatDestroy(&mglevels[i]->R);
618: MatDestroy(&mglevels[i]->B);
619: MatDestroy(&mglevels[i]->X);
620: }
621: }
622: }
624: if (mg->am == PC_MG_MULTIPLICATIVE) {
625: if (matapp) { MatZeroEntries(X); }
626: else { VecZeroEntries(x); }
627: for (i=0; i<mg->cyclesperpcapply; i++) {
628: PCMGMCycle_Private(pc,mglevels+levels-1,transpose,matapp,NULL);
629: }
630: } else if (mg->am == PC_MG_ADDITIVE) {
631: PCMGACycle_Private(pc,mglevels,transpose,matapp);
632: } else if (mg->am == PC_MG_KASKADE) {
633: PCMGKCycle_Private(pc,mglevels,transpose,matapp);
634: } else {
635: PCMGFCycle_Private(pc,mglevels,transpose,matapp);
636: }
637: if (mg->stageApply) {PetscLogStagePop();}
638: if (!changeu && !changed) {
639: if (matapp) { mglevels[levels-1]->B = NULL; }
640: else { mglevels[levels-1]->b = NULL; }
641: }
642: return(0);
643: }
645: static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
646: {
650: PCApply_MG_Internal(pc,b,x,NULL,NULL,PETSC_FALSE);
651: return(0);
652: }
654: static PetscErrorCode PCApplyTranspose_MG(PC pc,Vec b,Vec x)
655: {
659: PCApply_MG_Internal(pc,b,x,NULL,NULL,PETSC_TRUE);
660: return(0);
661: }
663: static PetscErrorCode PCMatApply_MG(PC pc,Mat b,Mat x)
664: {
668: PCApply_MG_Internal(pc,NULL,NULL,b,x,PETSC_FALSE);
669: return(0);
670: }
672: PetscErrorCode PCSetFromOptions_MG(PetscOptionItems *PetscOptionsObject,PC pc)
673: {
674: PetscErrorCode ierr;
675: PetscInt levels,cycles;
676: PetscBool flg, flg2;
677: PC_MG *mg = (PC_MG*)pc->data;
678: PC_MG_Levels **mglevels;
679: PCMGType mgtype;
680: PCMGCycleType mgctype;
681: PCMGGalerkinType gtype;
684: levels = PetscMax(mg->nlevels,1);
685: PetscOptionsHead(PetscOptionsObject,"Multigrid options");
686: PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);
687: if (!flg && !mg->levels && pc->dm) {
688: DMGetRefineLevel(pc->dm,&levels);
689: levels++;
690: mg->usedmfornumberoflevels = PETSC_TRUE;
691: }
692: PCMGSetLevels(pc,levels,NULL);
693: mglevels = mg->levels;
695: mgctype = (PCMGCycleType) mglevels[0]->cycles;
696: PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);
697: if (flg) {
698: PCMGSetCycleType(pc,mgctype);
699: }
700: gtype = mg->galerkin;
701: PetscOptionsEnum("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",PCMGGalerkinTypes,(PetscEnum)gtype,(PetscEnum*)>ype,&flg);
702: if (flg) {
703: PCMGSetGalerkin(pc,gtype);
704: }
705: flg2 = PETSC_FALSE;
706: PetscOptionsBool("-pc_mg_adapt_interp","Adapt interpolation using some coarse space","PCMGSetAdaptInterpolation",PETSC_FALSE,&flg2,&flg);
707: if (flg) {PCMGSetAdaptInterpolation(pc, flg2);}
708: PetscOptionsInt("-pc_mg_adapt_interp_n","Size of the coarse space for adaptive interpolation","PCMGSetCoarseSpace",mg->Nc,&mg->Nc,&flg);
709: 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);
710: PetscOptionsBool("-pc_mg_mesp_monitor","Monitor the multilevel eigensolver","PCMGSetAdaptInterpolation",PETSC_FALSE,&mg->mespMonitor,&flg);
711: flg2 = PETSC_FALSE;
712: PetscOptionsBool("-pc_mg_adapt_cr","Monitor coarse space quality using Compatible Relaxation (CR)","PCMGSetAdaptCR",PETSC_FALSE,&flg2,&flg);
713: if (flg) {PCMGSetAdaptCR(pc, flg2);}
714: flg = PETSC_FALSE;
715: PetscOptionsBool("-pc_mg_distinct_smoothup","Create separate smoothup KSP and append the prefix _up","PCMGSetDistinctSmoothUp",PETSC_FALSE,&flg,NULL);
716: if (flg) {
717: PCMGSetDistinctSmoothUp(pc);
718: }
719: mgtype = mg->am;
720: PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);
721: if (flg) {
722: PCMGSetType(pc,mgtype);
723: }
724: if (mg->am == PC_MG_MULTIPLICATIVE) {
725: PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGMultiplicativeSetCycles",mg->cyclesperpcapply,&cycles,&flg);
726: if (flg) {
727: PCMGMultiplicativeSetCycles(pc,cycles);
728: }
729: }
730: flg = PETSC_FALSE;
731: PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,NULL);
732: if (flg) {
733: PetscInt i;
734: char eventname[128];
736: levels = mglevels[0]->levels;
737: for (i=0; i<levels; i++) {
738: sprintf(eventname,"MGSetup Level %d",(int)i);
739: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);
740: sprintf(eventname,"MGSmooth Level %d",(int)i);
741: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);
742: if (i) {
743: sprintf(eventname,"MGResid Level %d",(int)i);
744: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);
745: sprintf(eventname,"MGInterp Level %d",(int)i);
746: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);
747: }
748: }
750: #if defined(PETSC_USE_LOG)
751: {
752: const char *sname = "MG Apply";
753: PetscStageLog stageLog;
754: PetscInt st;
756: PetscLogGetStageLog(&stageLog);
757: for (st = 0; st < stageLog->numStages; ++st) {
758: PetscBool same;
760: PetscStrcmp(stageLog->stageInfo[st].name, sname, &same);
761: if (same) mg->stageApply = st;
762: }
763: if (!mg->stageApply) {
764: PetscLogStageRegister(sname, &mg->stageApply);
765: }
766: }
767: #endif
768: }
769: PetscOptionsTail();
770: /* Check option consistency */
771: PCMGGetGalerkin(pc, >ype);
772: PCMGGetAdaptInterpolation(pc, &flg);
773: if (flg && (gtype >= PC_MG_GALERKIN_NONE)) SETERRQ(PetscObjectComm((PetscObject) pc), PETSC_ERR_ARG_INCOMP, "Must use Galerkin coarse operators when adapting the interpolator");
774: return(0);
775: }
777: const char *const PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",NULL};
778: const char *const PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",NULL};
779: const char *const PCMGGalerkinTypes[] = {"both","pmat","mat","none","external","PCMGGalerkinType","PC_MG_GALERKIN",NULL};
780: const char *const PCMGCoarseSpaceTypes[] = {"polynomial","harmonic","eigenvector","generalized_eigenvector","PCMGCoarseSpaceType","PCMG_POLYNOMIAL",NULL};
782: #include <petscdraw.h>
783: PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
784: {
785: PC_MG *mg = (PC_MG*)pc->data;
786: PC_MG_Levels **mglevels = mg->levels;
788: PetscInt levels = mglevels ? mglevels[0]->levels : 0,i;
789: PetscBool iascii,isbinary,isdraw;
792: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
793: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
794: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
795: if (iascii) {
796: const char *cyclename = levels ? (mglevels[0]->cycles == PC_MG_CYCLE_V ? "v" : "w") : "unknown";
797: PetscViewerASCIIPrintf(viewer," type is %s, levels=%D cycles=%s\n", PCMGTypes[mg->am],levels,cyclename);
798: if (mg->am == PC_MG_MULTIPLICATIVE) {
799: PetscViewerASCIIPrintf(viewer," Cycles per PCApply=%d\n",mg->cyclesperpcapply);
800: }
801: if (mg->galerkin == PC_MG_GALERKIN_BOTH) {
802: PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices\n");
803: } else if (mg->galerkin == PC_MG_GALERKIN_PMAT) {
804: PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices for pmat\n");
805: } else if (mg->galerkin == PC_MG_GALERKIN_MAT) {
806: PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices for mat\n");
807: } else if (mg->galerkin == PC_MG_GALERKIN_EXTERNAL) {
808: PetscViewerASCIIPrintf(viewer," Using externally compute Galerkin coarse grid matrices\n");
809: } else {
810: PetscViewerASCIIPrintf(viewer," Not using Galerkin computed coarse grid matrices\n");
811: }
812: if (mg->view){
813: (*mg->view)(pc,viewer);
814: }
815: for (i=0; i<levels; i++) {
816: if (!i) {
817: PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level -------------------------------\n",i);
818: } else {
819: PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);
820: }
821: PetscViewerASCIIPushTab(viewer);
822: KSPView(mglevels[i]->smoothd,viewer);
823: PetscViewerASCIIPopTab(viewer);
824: if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) {
825: PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");
826: } else if (i) {
827: PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);
828: PetscViewerASCIIPushTab(viewer);
829: KSPView(mglevels[i]->smoothu,viewer);
830: PetscViewerASCIIPopTab(viewer);
831: }
832: if (i && mglevels[i]->cr) {
833: PetscViewerASCIIPrintf(viewer,"CR solver on level %D -------------------------------\n",i);
834: PetscViewerASCIIPushTab(viewer);
835: KSPView(mglevels[i]->cr,viewer);
836: PetscViewerASCIIPopTab(viewer);
837: }
838: }
839: } else if (isbinary) {
840: for (i=levels-1; i>=0; i--) {
841: KSPView(mglevels[i]->smoothd,viewer);
842: if (i && mglevels[i]->smoothd != mglevels[i]->smoothu) {
843: KSPView(mglevels[i]->smoothu,viewer);
844: }
845: }
846: } else if (isdraw) {
847: PetscDraw draw;
848: PetscReal x,w,y,bottom,th;
849: PetscViewerDrawGetDraw(viewer,0,&draw);
850: PetscDrawGetCurrentPoint(draw,&x,&y);
851: PetscDrawStringGetSize(draw,NULL,&th);
852: bottom = y - th;
853: for (i=levels-1; i>=0; i--) {
854: if (!mglevels[i]->smoothu || (mglevels[i]->smoothu == mglevels[i]->smoothd)) {
855: PetscDrawPushCurrentPoint(draw,x,bottom);
856: KSPView(mglevels[i]->smoothd,viewer);
857: PetscDrawPopCurrentPoint(draw);
858: } else {
859: w = 0.5*PetscMin(1.0-x,x);
860: PetscDrawPushCurrentPoint(draw,x+w,bottom);
861: KSPView(mglevels[i]->smoothd,viewer);
862: PetscDrawPopCurrentPoint(draw);
863: PetscDrawPushCurrentPoint(draw,x-w,bottom);
864: KSPView(mglevels[i]->smoothu,viewer);
865: PetscDrawPopCurrentPoint(draw);
866: }
867: PetscDrawGetBoundingBox(draw,NULL,&bottom,NULL,NULL);
868: bottom -= th;
869: }
870: }
871: return(0);
872: }
874: #include <petsc/private/kspimpl.h>
876: /*
877: Calls setup for the KSP on each level
878: */
879: PetscErrorCode PCSetUp_MG(PC pc)
880: {
881: PC_MG *mg = (PC_MG*)pc->data;
882: PC_MG_Levels **mglevels = mg->levels;
884: PetscInt i,n;
885: PC cpc;
886: PetscBool dump = PETSC_FALSE,opsset,use_amat,missinginterpolate = PETSC_FALSE;
887: Mat dA,dB;
888: Vec tvec;
889: DM *dms;
890: PetscViewer viewer = NULL;
891: PetscBool dAeqdB = PETSC_FALSE, needRestricts = PETSC_FALSE, doCR = PETSC_FALSE;
894: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels with PCMGSetLevels() before setting up");
895: n = mglevels[0]->levels;
896: /* FIX: Move this to PCSetFromOptions_MG? */
897: if (mg->usedmfornumberoflevels) {
898: PetscInt levels;
899: DMGetRefineLevel(pc->dm,&levels);
900: levels++;
901: if (levels > n) { /* the problem is now being solved on a finer grid */
902: PCMGSetLevels(pc,levels,NULL);
903: n = levels;
904: PCSetFromOptions(pc); /* it is bad to call this here, but otherwise will never be called for the new hierarchy */
905: mglevels = mg->levels;
906: }
907: }
908: KSPGetPC(mglevels[0]->smoothd,&cpc);
911: /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */
912: /* so use those from global PC */
913: /* Is this what we always want? What if user wants to keep old one? */
914: KSPGetOperatorsSet(mglevels[n-1]->smoothd,NULL,&opsset);
915: if (opsset) {
916: Mat mmat;
917: KSPGetOperators(mglevels[n-1]->smoothd,NULL,&mmat);
918: if (mmat == pc->pmat) opsset = PETSC_FALSE;
919: }
921: /* Create CR solvers */
922: PCMGGetAdaptCR(pc, &doCR);
923: if (doCR) {
924: const char *prefix;
926: PCGetOptionsPrefix(pc, &prefix);
927: for (i = 1; i < n; ++i) {
928: PC ipc, cr;
929: char crprefix[128];
931: KSPCreate(PetscObjectComm((PetscObject) pc), &mglevels[i]->cr);
932: KSPSetErrorIfNotConverged(mglevels[i]->cr, PETSC_FALSE);
933: PetscObjectIncrementTabLevel((PetscObject) mglevels[i]->cr, (PetscObject) pc, n-i);
934: KSPSetOptionsPrefix(mglevels[i]->cr, prefix);
935: PetscObjectComposedDataSetInt((PetscObject) mglevels[i]->cr, PetscMGLevelId, mglevels[i]->level);
936: KSPSetType(mglevels[i]->cr, KSPCHEBYSHEV);
937: KSPSetConvergenceTest(mglevels[i]->cr, KSPConvergedSkip, NULL, NULL);
938: KSPSetNormType(mglevels[i]->cr, KSP_NORM_PRECONDITIONED);
939: KSPGetPC(mglevels[i]->cr, &ipc);
941: PCSetType(ipc, PCCOMPOSITE);
942: PCCompositeSetType(ipc, PC_COMPOSITE_MULTIPLICATIVE);
943: PCCompositeAddPCType(ipc, PCSOR);
944: CreateCR_Private(pc, i, &cr);
945: PCCompositeAddPC(ipc, cr);
946: PCDestroy(&cr);
948: KSPSetTolerances(mglevels[i]->cr, PETSC_DEFAULT, PETSC_DEFAULT, PETSC_DEFAULT, mg->default_smoothd);
949: KSPSetInitialGuessNonzero(mglevels[i]->cr, PETSC_TRUE);
950: PetscSNPrintf(crprefix, 128, "mg_levels_%d_cr_", (int) i);
951: KSPAppendOptionsPrefix(mglevels[i]->cr, crprefix);
952: PetscLogObjectParent((PetscObject) pc, (PetscObject) mglevels[i]->cr);
953: }
954: }
956: if (!opsset) {
957: PCGetUseAmat(pc,&use_amat);
958: if (use_amat) {
959: PetscInfo(pc,"Using outer 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->mat,pc->pmat);
961: } else {
962: PetscInfo(pc,"Using matrix (pmat) operators to define finest grid operator \n because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
963: KSPSetOperators(mglevels[n-1]->smoothd,pc->pmat,pc->pmat);
964: }
965: }
967: for (i=n-1; i>0; i--) {
968: if (!(mglevels[i]->interpolate || mglevels[i]->restrct)) {
969: missinginterpolate = PETSC_TRUE;
970: continue;
971: }
972: }
974: KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB);
975: if (dA == dB) dAeqdB = PETSC_TRUE;
976: if ((mg->galerkin == PC_MG_GALERKIN_NONE) || (((mg->galerkin == PC_MG_GALERKIN_PMAT) || (mg->galerkin == PC_MG_GALERKIN_MAT)) && !dAeqdB)) {
977: needRestricts = PETSC_TRUE; /* user must compute either mat, pmat, or both so must restrict x to coarser levels */
978: }
981: /*
982: Skipping if user has provided all interpolation/restriction needed (since DM might not be able to produce them (when coming from SNES/TS)
983: Skipping for galerkin==2 (externally managed hierarchy such as ML and GAMG). Cleaner logic here would be great. Wrap ML/GAMG as DMs?
984: */
985: if (missinginterpolate && pc->dm && mg->galerkin != PC_MG_GALERKIN_EXTERNAL && !pc->setupcalled) {
986: /* construct the interpolation from the DMs */
987: Mat p;
988: Vec rscale;
989: PetscMalloc1(n,&dms);
990: dms[n-1] = pc->dm;
991: /* Separately create them so we do not get DMKSP interference between levels */
992: for (i=n-2; i>-1; i--) {DMCoarsen(dms[i+1],MPI_COMM_NULL,&dms[i]);}
993: /*
994: Force the mat type of coarse level operator to be AIJ because usually we want to use LU for coarse level.
995: Notice that it can be overwritten by -mat_type because KSPSetUp() reads command line options.
996: But it is safe to use -dm_mat_type.
998: The mat type should not be hardcoded like this, we need to find a better way.
999: DMSetMatType(dms[0],MATAIJ);
1000: */
1001: for (i=n-2; i>-1; i--) {
1002: DMKSP kdm;
1003: PetscBool dmhasrestrict, dmhasinject;
1004: KSPSetDM(mglevels[i]->smoothd,dms[i]);
1005: if (!needRestricts) {KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);}
1006: if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
1007: KSPSetDM(mglevels[i]->smoothu,dms[i]);
1008: if (!needRestricts) {KSPSetDMActive(mglevels[i]->smoothu,PETSC_FALSE);}
1009: }
1010: if (mglevels[i]->cr) {
1011: KSPSetDM(mglevels[i]->cr,dms[i]);
1012: if (!needRestricts) {KSPSetDMActive(mglevels[i]->cr,PETSC_FALSE);}
1013: }
1014: DMGetDMKSPWrite(dms[i],&kdm);
1015: /* Ugly hack so that the next KSPSetUp() will use the RHS that we set. A better fix is to change dmActive to take
1016: * a bitwise OR of computing the matrix, RHS, and initial iterate. */
1017: kdm->ops->computerhs = NULL;
1018: kdm->rhsctx = NULL;
1019: if (!mglevels[i+1]->interpolate) {
1020: DMCreateInterpolation(dms[i],dms[i+1],&p,&rscale);
1021: PCMGSetInterpolation(pc,i+1,p);
1022: if (rscale) {PCMGSetRScale(pc,i+1,rscale);}
1023: VecDestroy(&rscale);
1024: MatDestroy(&p);
1025: }
1026: DMHasCreateRestriction(dms[i],&dmhasrestrict);
1027: if (dmhasrestrict && !mglevels[i+1]->restrct){
1028: DMCreateRestriction(dms[i],dms[i+1],&p);
1029: PCMGSetRestriction(pc,i+1,p);
1030: MatDestroy(&p);
1031: }
1032: DMHasCreateInjection(dms[i],&dmhasinject);
1033: if (dmhasinject && !mglevels[i+1]->inject){
1034: DMCreateInjection(dms[i],dms[i+1],&p);
1035: PCMGSetInjection(pc,i+1,p);
1036: MatDestroy(&p);
1037: }
1038: }
1040: for (i=n-2; i>-1; i--) {DMDestroy(&dms[i]);}
1041: PetscFree(dms);
1042: }
1044: if (pc->dm && !pc->setupcalled) {
1045: /* finest smoother also gets DM but it is not active, independent of whether galerkin==PC_MG_GALERKIN_EXTERNAL */
1046: KSPSetDM(mglevels[n-1]->smoothd,pc->dm);
1047: KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);
1048: if (mglevels[n-1]->smoothd != mglevels[n-1]->smoothu) {
1049: KSPSetDM(mglevels[n-1]->smoothu,pc->dm);
1050: KSPSetDMActive(mglevels[n-1]->smoothu,PETSC_FALSE);
1051: }
1052: if (mglevels[n-1]->cr) {
1053: KSPSetDM(mglevels[n-1]->cr,pc->dm);
1054: KSPSetDMActive(mglevels[n-1]->cr,PETSC_FALSE);
1055: }
1056: }
1058: if (mg->galerkin < PC_MG_GALERKIN_NONE) {
1059: Mat A,B;
1060: PetscBool doA = PETSC_FALSE,doB = PETSC_FALSE;
1061: MatReuse reuse = MAT_INITIAL_MATRIX;
1063: if ((mg->galerkin == PC_MG_GALERKIN_PMAT) || (mg->galerkin == PC_MG_GALERKIN_BOTH)) doB = PETSC_TRUE;
1064: if ((mg->galerkin == PC_MG_GALERKIN_MAT) || ((mg->galerkin == PC_MG_GALERKIN_BOTH) && (dA != dB))) doA = PETSC_TRUE;
1065: if (pc->setupcalled) reuse = MAT_REUSE_MATRIX;
1066: for (i=n-2; i>-1; i--) {
1067: 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");
1068: if (!mglevels[i+1]->interpolate) {
1069: PCMGSetInterpolation(pc,i+1,mglevels[i+1]->restrct);
1070: }
1071: if (!mglevels[i+1]->restrct) {
1072: PCMGSetRestriction(pc,i+1,mglevels[i+1]->interpolate);
1073: }
1074: if (reuse == MAT_REUSE_MATRIX) {
1075: KSPGetOperators(mglevels[i]->smoothd,&A,&B);
1076: }
1077: if (doA) {
1078: MatGalerkin(mglevels[i+1]->restrct,dA,mglevels[i+1]->interpolate,reuse,1.0,&A);
1079: }
1080: if (doB) {
1081: MatGalerkin(mglevels[i+1]->restrct,dB,mglevels[i+1]->interpolate,reuse,1.0,&B);
1082: }
1083: /* the management of the PetscObjectReference() and PetscObjecDereference() below is rather delicate */
1084: if (!doA && dAeqdB) {
1085: if (reuse == MAT_INITIAL_MATRIX) {PetscObjectReference((PetscObject)B);}
1086: A = B;
1087: } else if (!doA && reuse == MAT_INITIAL_MATRIX) {
1088: KSPGetOperators(mglevels[i]->smoothd,&A,NULL);
1089: PetscObjectReference((PetscObject)A);
1090: }
1091: if (!doB && dAeqdB) {
1092: if (reuse == MAT_INITIAL_MATRIX) {PetscObjectReference((PetscObject)A);}
1093: B = A;
1094: } else if (!doB && reuse == MAT_INITIAL_MATRIX) {
1095: KSPGetOperators(mglevels[i]->smoothd,NULL,&B);
1096: PetscObjectReference((PetscObject)B);
1097: }
1098: if (reuse == MAT_INITIAL_MATRIX) {
1099: KSPSetOperators(mglevels[i]->smoothd,A,B);
1100: PetscObjectDereference((PetscObject)A);
1101: PetscObjectDereference((PetscObject)B);
1102: }
1103: dA = A;
1104: dB = B;
1105: }
1106: }
1109: /* Adapt interpolation matrices */
1110: if (mg->adaptInterpolation) {
1111: mg->Nc = mg->Nc < 0 ? 6 : mg->Nc; /* Default to 6 modes */
1112: for (i = 0; i < n; ++i) {
1113: PCMGComputeCoarseSpace_Internal(pc, i, mg->coarseSpaceType, mg->Nc, !i ? NULL : mglevels[i-1]->coarseSpace, &mglevels[i]->coarseSpace);
1114: if (i) {PCMGAdaptInterpolator_Internal(pc, i, mglevels[i-1]->smoothu, mglevels[i]->smoothu, mg->Nc, mglevels[i-1]->coarseSpace, mglevels[i]->coarseSpace);}
1115: }
1116: for (i = n-2; i > -1; --i) {
1117: PCMGRecomputeLevelOperators_Internal(pc, i);
1118: }
1119: }
1121: if (needRestricts && pc->dm) {
1122: for (i=n-2; i>=0; i--) {
1123: DM dmfine,dmcoarse;
1124: Mat Restrict,Inject;
1125: Vec rscale;
1126: KSPGetDM(mglevels[i+1]->smoothd,&dmfine);
1127: KSPGetDM(mglevels[i]->smoothd,&dmcoarse);
1128: PCMGGetRestriction(pc,i+1,&Restrict);
1129: PCMGGetRScale(pc,i+1,&rscale);
1130: PCMGGetInjection(pc,i+1,&Inject);
1131: DMRestrict(dmfine,Restrict,rscale,Inject,dmcoarse);
1132: }
1133: }
1135: if (!pc->setupcalled) {
1136: for (i=0; i<n; i++) {
1137: KSPSetFromOptions(mglevels[i]->smoothd);
1138: }
1139: for (i=1; i<n; i++) {
1140: if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) {
1141: KSPSetFromOptions(mglevels[i]->smoothu);
1142: }
1143: if (mglevels[i]->cr) {
1144: KSPSetFromOptions(mglevels[i]->cr);
1145: }
1146: }
1147: /* insure that if either interpolation or restriction is set the other other one is set */
1148: for (i=1; i<n; i++) {
1149: PCMGGetInterpolation(pc,i,NULL);
1150: PCMGGetRestriction(pc,i,NULL);
1151: }
1152: for (i=0; i<n-1; i++) {
1153: if (!mglevels[i]->b) {
1154: Vec *vec;
1155: KSPCreateVecs(mglevels[i]->smoothd,1,&vec,0,NULL);
1156: PCMGSetRhs(pc,i,*vec);
1157: VecDestroy(vec);
1158: PetscFree(vec);
1159: }
1160: if (!mglevels[i]->r && i) {
1161: VecDuplicate(mglevels[i]->b,&tvec);
1162: PCMGSetR(pc,i,tvec);
1163: VecDestroy(&tvec);
1164: }
1165: if (!mglevels[i]->x) {
1166: VecDuplicate(mglevels[i]->b,&tvec);
1167: PCMGSetX(pc,i,tvec);
1168: VecDestroy(&tvec);
1169: }
1170: if (doCR) {
1171: VecDuplicate(mglevels[i]->b,&mglevels[i]->crx);
1172: VecDuplicate(mglevels[i]->b,&mglevels[i]->crb);
1173: VecZeroEntries(mglevels[i]->crb);
1174: }
1175: }
1176: if (n != 1 && !mglevels[n-1]->r) {
1177: /* PCMGSetR() on the finest level if user did not supply it */
1178: Vec *vec;
1179: KSPCreateVecs(mglevels[n-1]->smoothd,1,&vec,0,NULL);
1180: PCMGSetR(pc,n-1,*vec);
1181: VecDestroy(vec);
1182: PetscFree(vec);
1183: }
1184: if (doCR) {
1185: VecDuplicate(mglevels[n-1]->r, &mglevels[n-1]->crx);
1186: VecDuplicate(mglevels[n-1]->r, &mglevels[n-1]->crb);
1187: VecZeroEntries(mglevels[n-1]->crb);
1188: }
1189: }
1191: if (pc->dm) {
1192: /* need to tell all the coarser levels to rebuild the matrix using the DM for that level */
1193: for (i=0; i<n-1; i++) {
1194: if (mglevels[i]->smoothd->setupstage != KSP_SETUP_NEW) mglevels[i]->smoothd->setupstage = KSP_SETUP_NEWMATRIX;
1195: }
1196: }
1198: for (i=1; i<n; i++) {
1199: if (mglevels[i]->smoothu == mglevels[i]->smoothd || mg->am == PC_MG_FULL || mg->am == PC_MG_KASKADE || mg->cyclesperpcapply > 1){
1200: /* if doing only down then initial guess is zero */
1201: KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);
1202: }
1203: if (mglevels[i]->cr) {KSPSetInitialGuessNonzero(mglevels[i]->cr,PETSC_TRUE);}
1204: if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1205: KSPSetUp(mglevels[i]->smoothd);
1206: if (mglevels[i]->smoothd->reason == KSP_DIVERGED_PC_FAILED) {
1207: pc->failedreason = PC_SUBPC_ERROR;
1208: }
1209: if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1210: if (!mglevels[i]->residual) {
1211: Mat mat;
1212: KSPGetOperators(mglevels[i]->smoothd,&mat,NULL);
1213: PCMGSetResidual(pc,i,PCMGResidualDefault,mat);
1214: }
1215: if (!mglevels[i]->residualtranspose) {
1216: Mat mat;
1217: KSPGetOperators(mglevels[i]->smoothd,&mat,NULL);
1218: PCMGSetResidualTranspose(pc,i,PCMGResidualTransposeDefault,mat);
1219: }
1220: }
1221: for (i=1; i<n; i++) {
1222: if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) {
1223: Mat downmat,downpmat;
1225: /* check if operators have been set for up, if not use down operators to set them */
1226: KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,NULL);
1227: if (!opsset) {
1228: KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat);
1229: KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat);
1230: }
1232: KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);
1233: if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1234: KSPSetUp(mglevels[i]->smoothu);
1235: if (mglevels[i]->smoothu->reason == KSP_DIVERGED_PC_FAILED) {
1236: pc->failedreason = PC_SUBPC_ERROR;
1237: }
1238: if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1239: }
1240: if (mglevels[i]->cr) {
1241: Mat downmat,downpmat;
1243: /* check if operators have been set for up, if not use down operators to set them */
1244: KSPGetOperatorsSet(mglevels[i]->cr,&opsset,NULL);
1245: if (!opsset) {
1246: KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat);
1247: KSPSetOperators(mglevels[i]->cr,downmat,downpmat);
1248: }
1250: KSPSetInitialGuessNonzero(mglevels[i]->cr,PETSC_TRUE);
1251: if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1252: KSPSetUp(mglevels[i]->cr);
1253: if (mglevels[i]->cr->reason == KSP_DIVERGED_PC_FAILED) {
1254: pc->failedreason = PC_SUBPC_ERROR;
1255: }
1256: if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
1257: }
1258: }
1260: if (mglevels[0]->eventsmoothsetup) {PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);}
1261: KSPSetUp(mglevels[0]->smoothd);
1262: if (mglevels[0]->smoothd->reason == KSP_DIVERGED_PC_FAILED) {
1263: pc->failedreason = PC_SUBPC_ERROR;
1264: }
1265: if (mglevels[0]->eventsmoothsetup) {PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);}
1267: /*
1268: Dump the interpolation/restriction matrices plus the
1269: Jacobian/stiffness on each level. This allows MATLAB users to
1270: easily check if the Galerkin condition A_c = R A_f R^T is satisfied.
1272: Only support one or the other at the same time.
1273: */
1274: #if defined(PETSC_USE_SOCKET_VIEWER)
1275: PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,NULL);
1276: if (dump) viewer = PETSC_VIEWER_SOCKET_(PetscObjectComm((PetscObject)pc));
1277: dump = PETSC_FALSE;
1278: #endif
1279: PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,NULL);
1280: if (dump) viewer = PETSC_VIEWER_BINARY_(PetscObjectComm((PetscObject)pc));
1282: if (viewer) {
1283: for (i=1; i<n; i++) {
1284: MatView(mglevels[i]->restrct,viewer);
1285: }
1286: for (i=0; i<n; i++) {
1287: KSPGetPC(mglevels[i]->smoothd,&pc);
1288: MatView(pc->mat,viewer);
1289: }
1290: }
1291: return(0);
1292: }
1294: /* -------------------------------------------------------------------------------------*/
1296: PetscErrorCode PCMGGetLevels_MG(PC pc, PetscInt *levels)
1297: {
1298: PC_MG *mg = (PC_MG *) pc->data;
1301: *levels = mg->nlevels;
1302: return(0);
1303: }
1305: /*@
1306: PCMGGetLevels - Gets the number of levels to use with MG.
1308: Not Collective
1310: Input Parameter:
1311: . pc - the preconditioner context
1313: Output parameter:
1314: . levels - the number of levels
1316: Level: advanced
1318: .seealso: PCMGSetLevels()
1319: @*/
1320: PetscErrorCode PCMGGetLevels(PC pc,PetscInt *levels)
1321: {
1327: *levels = 0;
1328: PetscTryMethod(pc,"PCMGGetLevels_C",(PC,PetscInt*),(pc,levels));
1329: return(0);
1330: }
1332: /*@
1333: PCMGSetType - Determines the form of multigrid to use:
1334: multiplicative, additive, full, or the Kaskade algorithm.
1336: Logically Collective on PC
1338: Input Parameters:
1339: + pc - the preconditioner context
1340: - form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
1341: PC_MG_FULL, PC_MG_KASKADE
1343: Options Database Key:
1344: . -pc_mg_type <form> - Sets <form>, one of multiplicative,
1345: additive, full, kaskade
1347: Level: advanced
1349: .seealso: PCMGSetLevels()
1350: @*/
1351: PetscErrorCode PCMGSetType(PC pc,PCMGType form)
1352: {
1353: PC_MG *mg = (PC_MG*)pc->data;
1358: mg->am = form;
1359: if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
1360: else pc->ops->applyrichardson = NULL;
1361: return(0);
1362: }
1364: /*@
1365: PCMGGetType - Determines the form of multigrid to use:
1366: multiplicative, additive, full, or the Kaskade algorithm.
1368: Logically Collective on PC
1370: Input Parameter:
1371: . pc - the preconditioner context
1373: Output Parameter:
1374: . type - one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,PC_MG_FULL, PC_MG_KASKADE
1377: Level: advanced
1379: .seealso: PCMGSetLevels()
1380: @*/
1381: PetscErrorCode PCMGGetType(PC pc,PCMGType *type)
1382: {
1383: PC_MG *mg = (PC_MG*)pc->data;
1387: *type = mg->am;
1388: return(0);
1389: }
1391: /*@
1392: PCMGSetCycleType - Sets the type cycles to use. Use PCMGSetCycleTypeOnLevel() for more
1393: complicated cycling.
1395: Logically Collective on PC
1397: Input Parameters:
1398: + pc - the multigrid context
1399: - n - either PC_MG_CYCLE_V or PC_MG_CYCLE_W
1401: Options Database Key:
1402: . -pc_mg_cycle_type <v,w> - provide the cycle desired
1404: Level: advanced
1406: .seealso: PCMGSetCycleTypeOnLevel()
1407: @*/
1408: PetscErrorCode PCMGSetCycleType(PC pc,PCMGCycleType n)
1409: {
1410: PC_MG *mg = (PC_MG*)pc->data;
1411: PC_MG_Levels **mglevels = mg->levels;
1412: PetscInt i,levels;
1417: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1418: levels = mglevels[0]->levels;
1419: for (i=0; i<levels; i++) mglevels[i]->cycles = n;
1420: return(0);
1421: }
1423: /*@
1424: PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step
1425: of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used
1427: Logically Collective on PC
1429: Input Parameters:
1430: + pc - the multigrid context
1431: - n - number of cycles (default is 1)
1433: Options Database Key:
1434: . -pc_mg_multiplicative_cycles n
1436: Level: advanced
1438: Notes:
1439: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType()
1441: .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
1442: @*/
1443: PetscErrorCode PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
1444: {
1445: PC_MG *mg = (PC_MG*)pc->data;
1450: mg->cyclesperpcapply = n;
1451: return(0);
1452: }
1454: PetscErrorCode PCMGSetGalerkin_MG(PC pc,PCMGGalerkinType use)
1455: {
1456: PC_MG *mg = (PC_MG*)pc->data;
1459: mg->galerkin = use;
1460: return(0);
1461: }
1463: /*@
1464: PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
1465: finest grid via the Galerkin process: A_i-1 = r_i * A_i * p_i
1467: Logically Collective on PC
1469: Input Parameters:
1470: + pc - the multigrid context
1471: - use - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, or PC_MG_GALERKIN_NONE
1473: Options Database Key:
1474: . -pc_mg_galerkin <both,pmat,mat,none>
1476: Level: intermediate
1478: Notes:
1479: Some codes that use PCMG such as PCGAMG use Galerkin internally while constructing the hierarchy and thus do not
1480: use the PCMG construction of the coarser grids.
1482: .seealso: PCMGGetGalerkin(), PCMGGalerkinType
1484: @*/
1485: PetscErrorCode PCMGSetGalerkin(PC pc,PCMGGalerkinType use)
1486: {
1491: PetscTryMethod(pc,"PCMGSetGalerkin_C",(PC,PCMGGalerkinType),(pc,use));
1492: return(0);
1493: }
1495: /*@
1496: PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
1497: A_i-1 = r_i * A_i * p_i
1499: Not Collective
1501: Input Parameter:
1502: . pc - the multigrid context
1504: Output Parameter:
1505: . galerkin - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, PC_MG_GALERKIN_NONE, or PC_MG_GALERKIN_EXTERNAL
1507: Level: intermediate
1509: .seealso: PCMGSetGalerkin(), PCMGGalerkinType
1511: @*/
1512: PetscErrorCode PCMGGetGalerkin(PC pc,PCMGGalerkinType *galerkin)
1513: {
1514: PC_MG *mg = (PC_MG*)pc->data;
1518: *galerkin = mg->galerkin;
1519: return(0);
1520: }
1522: PetscErrorCode PCMGSetAdaptInterpolation_MG(PC pc, PetscBool adapt)
1523: {
1524: PC_MG *mg = (PC_MG *) pc->data;
1527: mg->adaptInterpolation = adapt;
1528: return(0);
1529: }
1531: PetscErrorCode PCMGGetAdaptInterpolation_MG(PC pc, PetscBool *adapt)
1532: {
1533: PC_MG *mg = (PC_MG *) pc->data;
1536: *adapt = mg->adaptInterpolation;
1537: return(0);
1538: }
1540: PetscErrorCode PCMGSetAdaptCR_MG(PC pc, PetscBool cr)
1541: {
1542: PC_MG *mg = (PC_MG *) pc->data;
1545: mg->compatibleRelaxation = cr;
1546: return(0);
1547: }
1549: PetscErrorCode PCMGGetAdaptCR_MG(PC pc, PetscBool *cr)
1550: {
1551: PC_MG *mg = (PC_MG *) pc->data;
1554: *cr = mg->compatibleRelaxation;
1555: return(0);
1556: }
1558: /*@
1559: PCMGSetAdaptInterpolation - Adapt the interpolator based upon a vector space which should be accurately captured by the next coarser mesh, and thus accurately interpolated.
1561: Logically Collective on PC
1563: Input Parameters:
1564: + pc - the multigrid context
1565: - adapt - flag for adaptation of the interpolator
1567: Options Database Keys:
1568: + -pc_mg_adapt_interp - Turn on adaptation
1569: . -pc_mg_adapt_interp_n <int> - The number of modes to use, should be divisible by dimension
1570: - -pc_mg_adapt_interp_coarse_space <type> - The type of coarse space: polynomial, harmonic, eigenvector, generalized_eigenvector
1572: Level: intermediate
1574: .keywords: MG, set, Galerkin
1575: .seealso: PCMGGetAdaptInterpolation(), PCMGSetGalerkin()
1576: @*/
1577: PetscErrorCode PCMGSetAdaptInterpolation(PC pc, PetscBool adapt)
1578: {
1583: PetscTryMethod(pc,"PCMGSetAdaptInterpolation_C",(PC,PetscBool),(pc,adapt));
1584: return(0);
1585: }
1587: /*@
1588: 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.
1590: Not collective
1592: Input Parameter:
1593: . pc - the multigrid context
1595: Output Parameter:
1596: . adapt - flag for adaptation of the interpolator
1598: Level: intermediate
1600: .keywords: MG, set, Galerkin
1601: .seealso: PCMGSetAdaptInterpolation(), PCMGSetGalerkin()
1602: @*/
1603: PetscErrorCode PCMGGetAdaptInterpolation(PC pc, PetscBool *adapt)
1604: {
1610: PetscUseMethod(pc,"PCMGGetAdaptInterpolation_C",(PC,PetscBool*),(pc,adapt));
1611: return(0);
1612: }
1614: /*@
1615: PCMGSetAdaptCR - Monitor the coarse space quality using an auxiliary solve with compatible relaxation.
1617: Logically Collective on PC
1619: Input Parameters:
1620: + pc - the multigrid context
1621: - cr - flag for compatible relaxation
1623: Options Database Keys:
1624: . -pc_mg_adapt_cr - Turn on compatible relaxation
1626: Level: intermediate
1628: .keywords: MG, set, Galerkin
1629: .seealso: PCMGGetAdaptCR(), PCMGSetAdaptInterpolation(), PCMGSetGalerkin()
1630: @*/
1631: PetscErrorCode PCMGSetAdaptCR(PC pc, PetscBool cr)
1632: {
1637: PetscTryMethod(pc,"PCMGSetAdaptCR_C",(PC,PetscBool),(pc,cr));
1638: return(0);
1639: }
1641: /*@
1642: PCMGGetAdaptCR - Get the flag to monitor coarse space quality using an auxiliary solve with compatible relaxation.
1644: Not collective
1646: Input Parameter:
1647: . pc - the multigrid context
1649: Output Parameter:
1650: . cr - flag for compatible relaxaion
1652: Level: intermediate
1654: .keywords: MG, set, Galerkin
1655: .seealso: PCMGSetAdaptCR(), PCMGGetAdaptInterpolation(), PCMGSetGalerkin()
1656: @*/
1657: PetscErrorCode PCMGGetAdaptCR(PC pc, PetscBool *cr)
1658: {
1664: PetscUseMethod(pc,"PCMGGetAdaptCR_C",(PC,PetscBool*),(pc,cr));
1665: return(0);
1666: }
1668: /*@
1669: PCMGSetNumberSmooth - Sets the number of pre and post-smoothing steps to use
1670: on all levels. Use PCMGDistinctSmoothUp() to create separate up and down smoothers if you want different numbers of
1671: pre- and post-smoothing steps.
1673: Logically Collective on PC
1675: Input Parameters:
1676: + mg - the multigrid context
1677: - n - the number of smoothing steps
1679: Options Database Key:
1680: . -mg_levels_ksp_max_it <n> - Sets number of pre and post-smoothing steps
1682: Level: advanced
1684: Notes:
1685: this does not set a value on the coarsest grid, since we assume that
1686: there is no separate smooth up on the coarsest grid.
1688: .seealso: PCMGSetDistinctSmoothUp()
1689: @*/
1690: PetscErrorCode PCMGSetNumberSmooth(PC pc,PetscInt n)
1691: {
1692: PC_MG *mg = (PC_MG*)pc->data;
1693: PC_MG_Levels **mglevels = mg->levels;
1695: PetscInt i,levels;
1700: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1701: levels = mglevels[0]->levels;
1703: for (i=1; i<levels; i++) {
1704: KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1705: KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1706: mg->default_smoothu = n;
1707: mg->default_smoothd = n;
1708: }
1709: return(0);
1710: }
1712: /*@
1713: PCMGSetDistinctSmoothUp - sets the up (post) smoother to be a separate KSP from the down (pre) smoother on all levels
1714: and adds the suffix _up to the options name
1716: Logically Collective on PC
1718: Input Parameters:
1719: . pc - the preconditioner context
1721: Options Database Key:
1722: . -pc_mg_distinct_smoothup
1724: Level: advanced
1726: Notes:
1727: this does not set a value on the coarsest grid, since we assume that
1728: there is no separate smooth up on the coarsest grid.
1730: .seealso: PCMGSetNumberSmooth()
1731: @*/
1732: PetscErrorCode PCMGSetDistinctSmoothUp(PC pc)
1733: {
1734: PC_MG *mg = (PC_MG*)pc->data;
1735: PC_MG_Levels **mglevels = mg->levels;
1737: PetscInt i,levels;
1738: KSP subksp;
1742: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1743: levels = mglevels[0]->levels;
1745: for (i=1; i<levels; i++) {
1746: const char *prefix = NULL;
1747: /* make sure smoother up and down are different */
1748: PCMGGetSmootherUp(pc,i,&subksp);
1749: KSPGetOptionsPrefix(mglevels[i]->smoothd,&prefix);
1750: KSPSetOptionsPrefix(subksp,prefix);
1751: KSPAppendOptionsPrefix(subksp,"up_");
1752: }
1753: return(0);
1754: }
1756: /* No new matrices are created, and the coarse operator matrices are the references to the original ones */
1757: PetscErrorCode PCGetInterpolations_MG(PC pc,PetscInt *num_levels,Mat *interpolations[])
1758: {
1759: PC_MG *mg = (PC_MG*)pc->data;
1760: PC_MG_Levels **mglevels = mg->levels;
1761: Mat *mat;
1762: PetscInt l;
1766: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1767: PetscMalloc1(mg->nlevels,&mat);
1768: for (l=1; l< mg->nlevels; l++) {
1769: mat[l-1] = mglevels[l]->interpolate;
1770: PetscObjectReference((PetscObject)mat[l-1]);
1771: }
1772: *num_levels = mg->nlevels;
1773: *interpolations = mat;
1774: return(0);
1775: }
1777: /* No new matrices are created, and the coarse operator matrices are the references to the original ones */
1778: PetscErrorCode PCGetCoarseOperators_MG(PC pc,PetscInt *num_levels,Mat *coarseOperators[])
1779: {
1780: PC_MG *mg = (PC_MG*)pc->data;
1781: PC_MG_Levels **mglevels = mg->levels;
1782: PetscInt l;
1783: Mat *mat;
1787: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1788: PetscMalloc1(mg->nlevels,&mat);
1789: for (l=0; l<mg->nlevels-1; l++) {
1790: KSPGetOperators(mglevels[l]->smoothd,NULL,&(mat[l]));
1791: PetscObjectReference((PetscObject)mat[l]);
1792: }
1793: *num_levels = mg->nlevels;
1794: *coarseOperators = mat;
1795: return(0);
1796: }
1798: /*@C
1799: PCMGRegisterCoarseSpaceConstructor - Adds a method to the PCMG package for coarse space construction.
1801: Not collective
1803: Input Parameters:
1804: + name - name of the constructor
1805: - function - constructor routine
1807: Notes:
1808: Calling sequence for the routine:
1809: $ my_csp(PC pc, PetscInt l, DM dm, KSP smooth, PetscInt Nc, const Vec initGuess[], Vec **coarseSp)
1810: $ pc - The PC object
1811: $ l - The multigrid level, 0 is the coarse level
1812: $ dm - The DM for this level
1813: $ smooth - The level smoother
1814: $ Nc - The size of the coarse space
1815: $ initGuess - Basis for an initial guess for the space
1816: $ coarseSp - A basis for the computed coarse space
1818: Level: advanced
1820: .seealso: PCMGGetCoarseSpaceConstructor(), PCRegister()
1821: @*/
1822: PetscErrorCode PCMGRegisterCoarseSpaceConstructor(const char name[], PetscErrorCode (*function)(PC, PetscInt, DM, KSP, PetscInt, const Vec[], Vec **))
1823: {
1827: PCInitializePackage();
1828: PetscFunctionListAdd(&PCMGCoarseList,name,function);
1829: return(0);
1830: }
1832: /*@C
1833: PCMGGetCoarseSpaceConstructor - Returns the given coarse space construction method.
1835: Not collective
1837: Input Parameter:
1838: . name - name of the constructor
1840: Output Parameter:
1841: . function - constructor routine
1843: Notes:
1844: Calling sequence for the routine:
1845: $ my_csp(PC pc, PetscInt l, DM dm, KSP smooth, PetscInt Nc, const Vec initGuess[], Vec **coarseSp)
1846: $ pc - The PC object
1847: $ l - The multigrid level, 0 is the coarse level
1848: $ dm - The DM for this level
1849: $ smooth - The level smoother
1850: $ Nc - The size of the coarse space
1851: $ initGuess - Basis for an initial guess for the space
1852: $ coarseSp - A basis for the computed coarse space
1854: Level: advanced
1856: .seealso: PCMGRegisterCoarseSpaceConstructor(), PCRegister()
1857: @*/
1858: PetscErrorCode PCMGGetCoarseSpaceConstructor(const char name[], PetscErrorCode (**function)(PC, PetscInt, DM, KSP, PetscInt, const Vec[], Vec **))
1859: {
1863: PetscFunctionListFind(PCMGCoarseList,name,function);
1864: return(0);
1865: }
1867: /* ----------------------------------------------------------------------------------------*/
1869: /*MC
1870: PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional
1871: information about the coarser grid matrices and restriction/interpolation operators.
1873: Options Database Keys:
1874: + -pc_mg_levels <nlevels> - number of levels including finest
1875: . -pc_mg_cycle_type <v,w> - provide the cycle desired
1876: . -pc_mg_type <additive,multiplicative,full,kaskade> - multiplicative is the default
1877: . -pc_mg_log - log information about time spent on each level of the solver
1878: . -pc_mg_distinct_smoothup - configure up (after interpolation) and down (before restriction) smoothers separately (with different options prefixes)
1879: . -pc_mg_galerkin <both,pmat,mat,none> - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R'
1880: . -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1)
1881: . -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
1882: to the Socket viewer for reading from MATLAB.
1883: - -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices
1884: to the binary output file called binaryoutput
1886: Notes:
1887: 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
1889: When run with a single level the smoother options are used on that level NOT the coarse grid solver options
1891: When run with KSPRICHARDSON the convergence test changes slightly if monitor is turned on. The iteration count may change slightly. This
1892: is because without monitoring the residual norm is computed WITHIN each multigrid cycle on the finest level after the pre-smoothing
1893: (because the residual has just been computed for the multigrid algorithm and is hence available for free) while with monitoring the
1894: residual is computed at the end of each cycle.
1896: Level: intermediate
1898: .seealso: PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE
1899: PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(),
1900: PCMGSetDistinctSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
1901: PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
1902: PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
1903: M*/
1905: PETSC_EXTERN PetscErrorCode PCCreate_MG(PC pc)
1906: {
1907: PC_MG *mg;
1911: PetscNewLog(pc,&mg);
1912: pc->data = (void*)mg;
1913: mg->nlevels = -1;
1914: mg->am = PC_MG_MULTIPLICATIVE;
1915: mg->galerkin = PC_MG_GALERKIN_NONE;
1916: mg->adaptInterpolation = PETSC_FALSE;
1917: mg->Nc = -1;
1918: mg->eigenvalue = -1;
1920: pc->useAmat = PETSC_TRUE;
1922: pc->ops->apply = PCApply_MG;
1923: pc->ops->applytranspose = PCApplyTranspose_MG;
1924: pc->ops->matapply = PCMatApply_MG;
1925: pc->ops->setup = PCSetUp_MG;
1926: pc->ops->reset = PCReset_MG;
1927: pc->ops->destroy = PCDestroy_MG;
1928: pc->ops->setfromoptions = PCSetFromOptions_MG;
1929: pc->ops->view = PCView_MG;
1931: PetscObjectComposedDataRegister(&mg->eigenvalue);
1932: PetscObjectComposeFunction((PetscObject)pc,"PCMGSetGalerkin_C",PCMGSetGalerkin_MG);
1933: PetscObjectComposeFunction((PetscObject)pc,"PCMGGetLevels_C",PCMGGetLevels_MG);
1934: PetscObjectComposeFunction((PetscObject)pc,"PCMGSetLevels_C",PCMGSetLevels_MG);
1935: PetscObjectComposeFunction((PetscObject)pc,"PCGetInterpolations_C",PCGetInterpolations_MG);
1936: PetscObjectComposeFunction((PetscObject)pc,"PCGetCoarseOperators_C",PCGetCoarseOperators_MG);
1937: PetscObjectComposeFunction((PetscObject)pc,"PCMGSetAdaptInterpolation_C",PCMGSetAdaptInterpolation_MG);
1938: PetscObjectComposeFunction((PetscObject)pc,"PCMGGetAdaptInterpolation_C",PCMGGetAdaptInterpolation_MG);
1939: PetscObjectComposeFunction((PetscObject)pc,"PCMGSetAdaptCR_C",PCMGSetAdaptCR_MG);
1940: PetscObjectComposeFunction((PetscObject)pc,"PCMGGetAdaptCR_C",PCMGGetAdaptCR_MG);
1941: return(0);
1942: }