Actual source code: mg.c
petsc-3.8.4 2018-03-24
2: /*
3: Defines the multigrid preconditioner interface.
4: */
5: #include <petsc/private/pcmgimpl.h>
6: #include <petscdm.h>
8: PetscErrorCode PCMGMCycle_Private(PC pc,PC_MG_Levels **mglevelsin,PCRichardsonConvergedReason *reason)
9: {
10: PC_MG *mg = (PC_MG*)pc->data;
11: PC_MG_Levels *mgc,*mglevels = *mglevelsin;
13: PetscInt cycles = (mglevels->level == 1) ? 1 : (PetscInt) mglevels->cycles;
14: PC subpc;
15: PCFailedReason pcreason;
18: if (mglevels->eventsmoothsolve) {PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);}
19: KSPSolve(mglevels->smoothd,mglevels->b,mglevels->x); /* pre-smooth */
20: KSPGetPC(mglevels->smoothd,&subpc);
21: PCGetSetUpFailedReason(subpc,&pcreason);
22: if (pcreason) {
23: pc->failedreason = PC_SUBPC_ERROR;
24: }
25: if (mglevels->eventsmoothsolve) {PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);}
26: if (mglevels->level) { /* not the coarsest grid */
27: if (mglevels->eventresidual) {PetscLogEventBegin(mglevels->eventresidual,0,0,0,0);}
28: (*mglevels->residual)(mglevels->A,mglevels->b,mglevels->x,mglevels->r);
29: if (mglevels->eventresidual) {PetscLogEventEnd(mglevels->eventresidual,0,0,0,0);}
31: /* if on finest level and have convergence criteria set */
32: if (mglevels->level == mglevels->levels-1 && mg->ttol && reason) {
33: PetscReal rnorm;
34: VecNorm(mglevels->r,NORM_2,&rnorm);
35: if (rnorm <= mg->ttol) {
36: if (rnorm < mg->abstol) {
37: *reason = PCRICHARDSON_CONVERGED_ATOL;
38: PetscInfo2(pc,"Linear solver has converged. Residual norm %g is less than absolute tolerance %g\n",(double)rnorm,(double)mg->abstol);
39: } else {
40: *reason = PCRICHARDSON_CONVERGED_RTOL;
41: 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);
42: }
43: return(0);
44: }
45: }
47: mgc = *(mglevelsin - 1);
48: if (mglevels->eventinterprestrict) {PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);}
49: MatRestrict(mglevels->restrct,mglevels->r,mgc->b);
50: if (mglevels->eventinterprestrict) {PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);}
51: VecSet(mgc->x,0.0);
52: while (cycles--) {
53: PCMGMCycle_Private(pc,mglevelsin-1,reason);
54: }
55: if (mglevels->eventinterprestrict) {PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);}
56: MatInterpolateAdd(mglevels->interpolate,mgc->x,mglevels->x,mglevels->x);
57: if (mglevels->eventinterprestrict) {PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);}
58: if (mglevels->eventsmoothsolve) {PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);}
59: KSPSolve(mglevels->smoothu,mglevels->b,mglevels->x); /* post smooth */
60: if (mglevels->eventsmoothsolve) {PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);}
61: }
62: return(0);
63: }
65: 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)
66: {
67: PC_MG *mg = (PC_MG*)pc->data;
68: PC_MG_Levels **mglevels = mg->levels;
70: PetscInt levels = mglevels[0]->levels,i;
73: /* When the DM is supplying the matrix then it will not exist until here */
74: for (i=0; i<levels; i++) {
75: if (!mglevels[i]->A) {
76: KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);
77: PetscObjectReference((PetscObject)mglevels[i]->A);
78: }
79: }
80: mglevels[levels-1]->b = b;
81: mglevels[levels-1]->x = x;
83: mg->rtol = rtol;
84: mg->abstol = abstol;
85: mg->dtol = dtol;
86: if (rtol) {
87: /* compute initial residual norm for relative convergence test */
88: PetscReal rnorm;
89: if (zeroguess) {
90: VecNorm(b,NORM_2,&rnorm);
91: } else {
92: (*mglevels[levels-1]->residual)(mglevels[levels-1]->A,b,x,w);
93: VecNorm(w,NORM_2,&rnorm);
94: }
95: mg->ttol = PetscMax(rtol*rnorm,abstol);
96: } else if (abstol) mg->ttol = abstol;
97: else mg->ttol = 0.0;
99: /* since smoother is applied to full system, not just residual we need to make sure that smoothers don't
100: stop prematurely due to small residual */
101: for (i=1; i<levels; i++) {
102: KSPSetTolerances(mglevels[i]->smoothu,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);
103: if (mglevels[i]->smoothu != mglevels[i]->smoothd) {
104: /* For Richardson the initial guess is nonzero since it is solving in each cycle the original system not just applying as a preconditioner */
105: KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);
106: KSPSetTolerances(mglevels[i]->smoothd,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);
107: }
108: }
110: *reason = (PCRichardsonConvergedReason)0;
111: for (i=0; i<its; i++) {
112: PCMGMCycle_Private(pc,mglevels+levels-1,reason);
113: if (*reason) break;
114: }
115: if (!*reason) *reason = PCRICHARDSON_CONVERGED_ITS;
116: *outits = i;
117: return(0);
118: }
120: PetscErrorCode PCReset_MG(PC pc)
121: {
122: PC_MG *mg = (PC_MG*)pc->data;
123: PC_MG_Levels **mglevels = mg->levels;
125: PetscInt i,n;
128: if (mglevels) {
129: n = mglevels[0]->levels;
130: for (i=0; i<n-1; i++) {
131: VecDestroy(&mglevels[i+1]->r);
132: VecDestroy(&mglevels[i]->b);
133: VecDestroy(&mglevels[i]->x);
134: MatDestroy(&mglevels[i+1]->restrct);
135: MatDestroy(&mglevels[i+1]->interpolate);
136: VecDestroy(&mglevels[i+1]->rscale);
137: }
139: for (i=0; i<n; i++) {
140: MatDestroy(&mglevels[i]->A);
141: if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
142: KSPReset(mglevels[i]->smoothd);
143: }
144: KSPReset(mglevels[i]->smoothu);
145: }
146: }
147: return(0);
148: }
150: /*@C
151: PCMGSetLevels - Sets the number of levels to use with MG.
152: Must be called before any other MG routine.
154: Logically Collective on PC
156: Input Parameters:
157: + pc - the preconditioner context
158: . levels - the number of levels
159: - comms - optional communicators for each level; this is to allow solving the coarser problems
160: on smaller sets of processors.
162: Level: intermediate
164: Notes:
165: If the number of levels is one then the multigrid uses the -mg_levels prefix
166: for setting the level options rather than the -mg_coarse prefix.
168: .keywords: MG, set, levels, multigrid
170: .seealso: PCMGSetType(), PCMGGetLevels()
171: @*/
172: PetscErrorCode PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
173: {
175: PC_MG *mg = (PC_MG*)pc->data;
176: MPI_Comm comm;
177: PC_MG_Levels **mglevels = mg->levels;
178: PCMGType mgtype = mg->am;
179: PetscInt mgctype = (PetscInt) PC_MG_CYCLE_V;
180: PetscInt i;
181: PetscMPIInt size;
182: const char *prefix;
183: PC ipc;
184: PetscInt n;
189: if (mg->nlevels == levels) return(0);
190: PetscObjectGetComm((PetscObject)pc,&comm);
191: if (mglevels) {
192: mgctype = mglevels[0]->cycles;
193: /* changing the number of levels so free up the previous stuff */
194: PCReset_MG(pc);
195: n = mglevels[0]->levels;
196: for (i=0; i<n; i++) {
197: if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
198: KSPDestroy(&mglevels[i]->smoothd);
199: }
200: KSPDestroy(&mglevels[i]->smoothu);
201: PetscFree(mglevels[i]);
202: }
203: PetscFree(mg->levels);
204: }
206: mg->nlevels = levels;
208: PetscMalloc1(levels,&mglevels);
209: PetscLogObjectMemory((PetscObject)pc,levels*(sizeof(PC_MG*)));
211: PCGetOptionsPrefix(pc,&prefix);
213: mg->stageApply = 0;
214: for (i=0; i<levels; i++) {
215: PetscNewLog(pc,&mglevels[i]);
217: mglevels[i]->level = i;
218: mglevels[i]->levels = levels;
219: mglevels[i]->cycles = mgctype;
220: mg->default_smoothu = 2;
221: mg->default_smoothd = 2;
222: mglevels[i]->eventsmoothsetup = 0;
223: mglevels[i]->eventsmoothsolve = 0;
224: mglevels[i]->eventresidual = 0;
225: mglevels[i]->eventinterprestrict = 0;
227: if (comms) comm = comms[i];
228: KSPCreate(comm,&mglevels[i]->smoothd);
229: KSPSetErrorIfNotConverged(mglevels[i]->smoothd,pc->erroriffailure);
230: PetscObjectIncrementTabLevel((PetscObject)mglevels[i]->smoothd,(PetscObject)pc,levels-i);
231: KSPSetOptionsPrefix(mglevels[i]->smoothd,prefix);
232: PetscObjectComposedDataSetInt((PetscObject) mglevels[i]->smoothd, PetscMGLevelId, mglevels[i]->level);
233: if (i || levels == 1) {
234: char tprefix[128];
236: KSPSetType(mglevels[i]->smoothd,KSPCHEBYSHEV);
237: KSPSetConvergenceTest(mglevels[i]->smoothd,KSPConvergedSkip,NULL,NULL);
238: KSPSetNormType(mglevels[i]->smoothd,KSP_NORM_NONE);
239: KSPGetPC(mglevels[i]->smoothd,&ipc);
240: PCSetType(ipc,PCSOR);
241: KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, mg->default_smoothd);
243: sprintf(tprefix,"mg_levels_%d_",(int)i);
244: KSPAppendOptionsPrefix(mglevels[i]->smoothd,tprefix);
245: } else {
246: KSPAppendOptionsPrefix(mglevels[0]->smoothd,"mg_coarse_");
248: /* coarse solve is (redundant) LU by default; set shifttype NONZERO to avoid annoying zero-pivot in LU preconditioner */
249: KSPSetType(mglevels[0]->smoothd,KSPPREONLY);
250: KSPGetPC(mglevels[0]->smoothd,&ipc);
251: MPI_Comm_size(comm,&size);
252: if (size > 1) {
253: PCSetType(ipc,PCREDUNDANT);
254: } else {
255: PCSetType(ipc,PCLU);
256: }
257: PCFactorSetShiftType(ipc,MAT_SHIFT_INBLOCKS);
258: }
259: PetscLogObjectParent((PetscObject)pc,(PetscObject)mglevels[i]->smoothd);
261: mglevels[i]->smoothu = mglevels[i]->smoothd;
262: mg->rtol = 0.0;
263: mg->abstol = 0.0;
264: mg->dtol = 0.0;
265: mg->ttol = 0.0;
266: mg->cyclesperpcapply = 1;
267: }
268: mg->levels = mglevels;
269: PCMGSetType(pc,mgtype);
270: return(0);
271: }
274: PetscErrorCode PCDestroy_MG(PC pc)
275: {
277: PC_MG *mg = (PC_MG*)pc->data;
278: PC_MG_Levels **mglevels = mg->levels;
279: PetscInt i,n;
282: PCReset_MG(pc);
283: if (mglevels) {
284: n = mglevels[0]->levels;
285: for (i=0; i<n; i++) {
286: if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
287: KSPDestroy(&mglevels[i]->smoothd);
288: }
289: KSPDestroy(&mglevels[i]->smoothu);
290: PetscFree(mglevels[i]);
291: }
292: PetscFree(mg->levels);
293: }
294: PetscFree(pc->data);
295: return(0);
296: }
300: extern PetscErrorCode PCMGACycle_Private(PC,PC_MG_Levels**);
301: extern PetscErrorCode PCMGFCycle_Private(PC,PC_MG_Levels**);
302: extern PetscErrorCode PCMGKCycle_Private(PC,PC_MG_Levels**);
304: /*
305: PCApply_MG - Runs either an additive, multiplicative, Kaskadic
306: or full cycle of multigrid.
308: Note:
309: A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle().
310: */
311: static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
312: {
313: PC_MG *mg = (PC_MG*)pc->data;
314: PC_MG_Levels **mglevels = mg->levels;
316: PetscInt levels = mglevels[0]->levels,i;
319: if (mg->stageApply) {PetscLogStagePush(mg->stageApply);}
320: /* When the DM is supplying the matrix then it will not exist until here */
321: for (i=0; i<levels; i++) {
322: if (!mglevels[i]->A) {
323: KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL);
324: PetscObjectReference((PetscObject)mglevels[i]->A);
325: }
326: }
328: mglevels[levels-1]->b = b;
329: mglevels[levels-1]->x = x;
330: if (mg->am == PC_MG_MULTIPLICATIVE) {
331: VecSet(x,0.0);
332: for (i=0; i<mg->cyclesperpcapply; i++) {
333: PCMGMCycle_Private(pc,mglevels+levels-1,NULL);
334: }
335: } else if (mg->am == PC_MG_ADDITIVE) {
336: PCMGACycle_Private(pc,mglevels);
337: } else if (mg->am == PC_MG_KASKADE) {
338: PCMGKCycle_Private(pc,mglevels);
339: } else {
340: PCMGFCycle_Private(pc,mglevels);
341: }
342: if (mg->stageApply) {PetscLogStagePop();}
343: return(0);
344: }
347: PetscErrorCode PCSetFromOptions_MG(PetscOptionItems *PetscOptionsObject,PC pc)
348: {
349: PetscErrorCode ierr;
350: PetscInt m,levels,cycles;
351: PetscBool flg;
352: PC_MG *mg = (PC_MG*)pc->data;
353: PC_MG_Levels **mglevels;
354: PCMGType mgtype;
355: PCMGCycleType mgctype;
356: PCMGGalerkinType gtype;
359: levels = PetscMax(mg->nlevels,1);
360: PetscOptionsHead(PetscOptionsObject,"Multigrid options");
361: PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);
362: if (!flg && !mg->levels && pc->dm) {
363: DMGetRefineLevel(pc->dm,&levels);
364: levels++;
365: mg->usedmfornumberoflevels = PETSC_TRUE;
366: }
367: PCMGSetLevels(pc,levels,NULL);
368: mglevels = mg->levels;
370: mgctype = (PCMGCycleType) mglevels[0]->cycles;
371: PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);
372: if (flg) {
373: PCMGSetCycleType(pc,mgctype);
374: }
375: gtype = mg->galerkin;
376: PetscOptionsEnum("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",PCMGGalerkinTypes,(PetscEnum)gtype,(PetscEnum*)>ype,&flg);
377: if (flg) {
378: PCMGSetGalerkin(pc,gtype);
379: }
380: PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",mg->default_smoothu,&m,&flg);
381: if (flg) {
382: PCMGSetNumberSmoothUp(pc,m);
383: }
384: PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",mg->default_smoothd,&m,&flg);
385: if (flg) {
386: PCMGSetNumberSmoothDown(pc,m);
387: }
388: mgtype = mg->am;
389: PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);
390: if (flg) {
391: PCMGSetType(pc,mgtype);
392: }
393: if (mg->am == PC_MG_MULTIPLICATIVE) {
394: PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGMultiplicativeSetCycles",mg->cyclesperpcapply,&cycles,&flg);
395: if (flg) {
396: PCMGMultiplicativeSetCycles(pc,cycles);
397: }
398: }
399: flg = PETSC_FALSE;
400: PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,NULL);
401: if (flg) {
402: PetscInt i;
403: char eventname[128];
405: levels = mglevels[0]->levels;
406: for (i=0; i<levels; i++) {
407: sprintf(eventname,"MGSetup Level %d",(int)i);
408: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);
409: sprintf(eventname,"MGSmooth Level %d",(int)i);
410: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);
411: if (i) {
412: sprintf(eventname,"MGResid Level %d",(int)i);
413: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);
414: sprintf(eventname,"MGInterp Level %d",(int)i);
415: PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);
416: }
417: }
419: #if defined(PETSC_USE_LOG)
420: {
421: const char *sname = "MG Apply";
422: PetscStageLog stageLog;
423: PetscInt st;
426: PetscLogGetStageLog(&stageLog);
427: for (st = 0; st < stageLog->numStages; ++st) {
428: PetscBool same;
430: PetscStrcmp(stageLog->stageInfo[st].name, sname, &same);
431: if (same) mg->stageApply = st;
432: }
433: if (!mg->stageApply) {
434: PetscLogStageRegister(sname, &mg->stageApply);
435: }
436: }
437: #endif
438: }
439: PetscOptionsTail();
440: return(0);
441: }
443: const char *const PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0};
444: const char *const PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",0};
445: const char *const PCMGGalerkinTypes[] = {"both","pmat","mat","none","external","PCMGGalerkinType","PC_MG_GALERKIN",0};
447: #include <petscdraw.h>
448: PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
449: {
450: PC_MG *mg = (PC_MG*)pc->data;
451: PC_MG_Levels **mglevels = mg->levels;
453: PetscInt levels = mglevels ? mglevels[0]->levels : 0,i;
454: PetscBool iascii,isbinary,isdraw;
457: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
458: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
459: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
460: if (iascii) {
461: const char *cyclename = levels ? (mglevels[0]->cycles == PC_MG_CYCLE_V ? "v" : "w") : "unknown";
462: PetscViewerASCIIPrintf(viewer," type is %s, levels=%D cycles=%s\n", PCMGTypes[mg->am],levels,cyclename);
463: if (mg->am == PC_MG_MULTIPLICATIVE) {
464: PetscViewerASCIIPrintf(viewer," Cycles per PCApply=%d\n",mg->cyclesperpcapply);
465: }
466: if (mg->galerkin == PC_MG_GALERKIN_BOTH) {
467: PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices\n");
468: } else if (mg->galerkin == PC_MG_GALERKIN_PMAT) {
469: PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices for pmat\n");
470: } else if (mg->galerkin == PC_MG_GALERKIN_MAT) {
471: PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices for mat\n");
472: } else if (mg->galerkin == PC_MG_GALERKIN_EXTERNAL) {
473: PetscViewerASCIIPrintf(viewer," Using externally compute Galerkin coarse grid matrices\n");
474: } else {
475: PetscViewerASCIIPrintf(viewer," Not using Galerkin computed coarse grid matrices\n");
476: }
477: if (mg->view){
478: (*mg->view)(pc,viewer);
479: }
480: for (i=0; i<levels; i++) {
481: if (!i) {
482: PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level -------------------------------\n",i);
483: } else {
484: PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);
485: }
486: PetscViewerASCIIPushTab(viewer);
487: KSPView(mglevels[i]->smoothd,viewer);
488: PetscViewerASCIIPopTab(viewer);
489: if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) {
490: PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");
491: } else if (i) {
492: PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);
493: PetscViewerASCIIPushTab(viewer);
494: KSPView(mglevels[i]->smoothu,viewer);
495: PetscViewerASCIIPopTab(viewer);
496: }
497: }
498: } else if (isbinary) {
499: for (i=levels-1; i>=0; i--) {
500: KSPView(mglevels[i]->smoothd,viewer);
501: if (i && mglevels[i]->smoothd != mglevels[i]->smoothu) {
502: KSPView(mglevels[i]->smoothu,viewer);
503: }
504: }
505: } else if (isdraw) {
506: PetscDraw draw;
507: PetscReal x,w,y,bottom,th;
508: PetscViewerDrawGetDraw(viewer,0,&draw);
509: PetscDrawGetCurrentPoint(draw,&x,&y);
510: PetscDrawStringGetSize(draw,NULL,&th);
511: bottom = y - th;
512: for (i=levels-1; i>=0; i--) {
513: if (!mglevels[i]->smoothu || (mglevels[i]->smoothu == mglevels[i]->smoothd)) {
514: PetscDrawPushCurrentPoint(draw,x,bottom);
515: KSPView(mglevels[i]->smoothd,viewer);
516: PetscDrawPopCurrentPoint(draw);
517: } else {
518: w = 0.5*PetscMin(1.0-x,x);
519: PetscDrawPushCurrentPoint(draw,x+w,bottom);
520: KSPView(mglevels[i]->smoothd,viewer);
521: PetscDrawPopCurrentPoint(draw);
522: PetscDrawPushCurrentPoint(draw,x-w,bottom);
523: KSPView(mglevels[i]->smoothu,viewer);
524: PetscDrawPopCurrentPoint(draw);
525: }
526: PetscDrawGetBoundingBox(draw,NULL,&bottom,NULL,NULL);
527: bottom -= th;
528: }
529: }
530: return(0);
531: }
533: #include <petsc/private/dmimpl.h>
534: #include <petsc/private/kspimpl.h>
536: /*
537: Calls setup for the KSP on each level
538: */
539: PetscErrorCode PCSetUp_MG(PC pc)
540: {
541: PC_MG *mg = (PC_MG*)pc->data;
542: PC_MG_Levels **mglevels = mg->levels;
544: PetscInt i,n;
545: PC cpc;
546: PetscBool dump = PETSC_FALSE,opsset,use_amat,missinginterpolate = PETSC_FALSE;
547: Mat dA,dB;
548: Vec tvec;
549: DM *dms;
550: PetscViewer viewer = 0;
551: PetscBool dAeqdB = PETSC_FALSE, needRestricts = PETSC_FALSE;
554: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels with PCMGSetLevels() before setting up");
555: n = mglevels[0]->levels;
556: /* FIX: Move this to PCSetFromOptions_MG? */
557: if (mg->usedmfornumberoflevels) {
558: PetscInt levels;
559: DMGetRefineLevel(pc->dm,&levels);
560: levels++;
561: if (levels > n) { /* the problem is now being solved on a finer grid */
562: PCMGSetLevels(pc,levels,NULL);
563: n = levels;
564: PCSetFromOptions(pc); /* it is bad to call this here, but otherwise will never be called for the new hierarchy */
565: mglevels = mg->levels;
566: }
567: }
568: KSPGetPC(mglevels[0]->smoothd,&cpc);
571: /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */
572: /* so use those from global PC */
573: /* Is this what we always want? What if user wants to keep old one? */
574: KSPGetOperatorsSet(mglevels[n-1]->smoothd,NULL,&opsset);
575: if (opsset) {
576: Mat mmat;
577: KSPGetOperators(mglevels[n-1]->smoothd,NULL,&mmat);
578: if (mmat == pc->pmat) opsset = PETSC_FALSE;
579: }
581: if (!opsset) {
582: PCGetUseAmat(pc,&use_amat);
583: if(use_amat){
584: PetscInfo(pc,"Using outer operators to define finest grid operator \n because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
585: KSPSetOperators(mglevels[n-1]->smoothd,pc->mat,pc->pmat);
586: }
587: else {
588: PetscInfo(pc,"Using matrix (pmat) operators to define finest grid operator \n because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");
589: KSPSetOperators(mglevels[n-1]->smoothd,pc->pmat,pc->pmat);
590: }
591: }
593: for (i=n-1; i>0; i--) {
594: if (!(mglevels[i]->interpolate || mglevels[i]->restrct)) {
595: missinginterpolate = PETSC_TRUE;
596: continue;
597: }
598: }
600: KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB);
601: if (dA == dB) dAeqdB = PETSC_TRUE;
602: if ((mg->galerkin == PC_MG_GALERKIN_NONE) || (((mg->galerkin == PC_MG_GALERKIN_PMAT) || (mg->galerkin == PC_MG_GALERKIN_MAT)) && !dAeqdB)) {
603: needRestricts = PETSC_TRUE; /* user must compute either mat, pmat, or both so must restrict x to coarser levels */
604: }
607: /*
608: Skipping if user has provided all interpolation/restriction needed (since DM might not be able to produce them (when coming from SNES/TS)
609: Skipping for galerkin==2 (externally managed hierarchy such as ML and GAMG). Cleaner logic here would be great. Wrap ML/GAMG as DMs?
610: */
611: if (missinginterpolate && pc->dm && mg->galerkin != PC_MG_GALERKIN_EXTERNAL && !pc->setupcalled) {
612: /* construct the interpolation from the DMs */
613: Mat p;
614: Vec rscale;
615: PetscMalloc1(n,&dms);
616: dms[n-1] = pc->dm;
617: /* Separately create them so we do not get DMKSP interference between levels */
618: for (i=n-2; i>-1; i--) {DMCoarsen(dms[i+1],MPI_COMM_NULL,&dms[i]);}
619: for (i=n-2; i>-1; i--) {
620: DMKSP kdm;
621: PetscBool dmhasrestrict;
622: KSPSetDM(mglevels[i]->smoothd,dms[i]);
623: if (!needRestricts) {KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);}
624: DMGetDMKSPWrite(dms[i],&kdm);
625: /* Ugly hack so that the next KSPSetUp() will use the RHS that we set. A better fix is to change dmActive to take
626: * a bitwise OR of computing the matrix, RHS, and initial iterate. */
627: kdm->ops->computerhs = NULL;
628: kdm->rhsctx = NULL;
629: if (!mglevels[i+1]->interpolate) {
630: DMCreateInterpolation(dms[i],dms[i+1],&p,&rscale);
631: PCMGSetInterpolation(pc,i+1,p);
632: if (rscale) {PCMGSetRScale(pc,i+1,rscale);}
633: VecDestroy(&rscale);
634: MatDestroy(&p);
635: }
636: DMHasCreateRestriction(dms[i],&dmhasrestrict);
637: if (dmhasrestrict && !mglevels[i+1]->restrct){
638: DMCreateRestriction(dms[i],dms[i+1],&p);
639: PCMGSetRestriction(pc,i+1,p);
640: MatDestroy(&p);
641: }
642: }
644: for (i=n-2; i>-1; i--) {DMDestroy(&dms[i]);}
645: PetscFree(dms);
646: }
648: if (pc->dm && !pc->setupcalled) {
649: /* finest smoother also gets DM but it is not active, independent of whether galerkin==PC_MG_GALERKIN_EXTERNAL */
650: KSPSetDM(mglevels[n-1]->smoothd,pc->dm);
651: KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);
652: }
654: if (mg->galerkin < PC_MG_GALERKIN_NONE) {
655: Mat A,B;
656: PetscBool doA = PETSC_FALSE,doB = PETSC_FALSE;
657: MatReuse reuse = MAT_INITIAL_MATRIX;
659: if ((mg->galerkin == PC_MG_GALERKIN_PMAT) || (mg->galerkin == PC_MG_GALERKIN_BOTH)) doB = PETSC_TRUE;
660: if ((mg->galerkin == PC_MG_GALERKIN_MAT) || ((mg->galerkin == PC_MG_GALERKIN_BOTH) && (dA != dB))) doA = PETSC_TRUE;
661: if (pc->setupcalled) reuse = MAT_REUSE_MATRIX;
662: for (i=n-2; i>-1; i--) {
663: 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");
664: if (!mglevels[i+1]->interpolate) {
665: PCMGSetInterpolation(pc,i+1,mglevels[i+1]->restrct);
666: }
667: if (!mglevels[i+1]->restrct) {
668: PCMGSetRestriction(pc,i+1,mglevels[i+1]->interpolate);
669: }
670: if (reuse == MAT_REUSE_MATRIX) {
671: KSPGetOperators(mglevels[i]->smoothd,&A,&B);
672: }
673: if (doA) {
674: MatGalerkin(mglevels[i+1]->restrct,dA,mglevels[i+1]->interpolate,reuse,1.0,&A);
675: }
676: if (doB) {
677: MatGalerkin(mglevels[i+1]->restrct,dB,mglevels[i+1]->interpolate,reuse,1.0,&B);
678: }
679: /* the management of the PetscObjectReference() and PetscObjecDereference() below is rather delicate */
680: if (!doA && dAeqdB) {
681: if (reuse == MAT_INITIAL_MATRIX) {PetscObjectReference((PetscObject)B);}
682: A = B;
683: } else if (!doA && reuse == MAT_INITIAL_MATRIX ) {
684: KSPGetOperators(mglevels[i]->smoothd,&A,NULL);
685: PetscObjectReference((PetscObject)A);
686: }
687: if (!doB && dAeqdB) {
688: if (reuse == MAT_INITIAL_MATRIX) {PetscObjectReference((PetscObject)A);}
689: B = A;
690: } else if (!doB && reuse == MAT_INITIAL_MATRIX) {
691: KSPGetOperators(mglevels[i]->smoothd,NULL,&B);
692: PetscObjectReference((PetscObject)B);
693: }
694: if (reuse == MAT_INITIAL_MATRIX) {
695: KSPSetOperators(mglevels[i]->smoothd,A,B);
696: PetscObjectDereference((PetscObject)A);
697: PetscObjectDereference((PetscObject)B);
698: }
699: dA = A;
700: dB = B;
701: }
702: }
703: if (needRestricts && pc->dm && pc->dm->x) {
704: /* need to restrict Jacobian location to coarser meshes for evaluation */
705: for (i=n-2; i>-1; i--) {
706: Mat R;
707: Vec rscale;
708: if (!mglevels[i]->smoothd->dm->x) {
709: Vec *vecs;
710: KSPCreateVecs(mglevels[i]->smoothd,1,&vecs,0,NULL);
711: mglevels[i]->smoothd->dm->x = vecs[0];
712: PetscFree(vecs);
713: }
714: PCMGGetRestriction(pc,i+1,&R);
715: PCMGGetRScale(pc,i+1,&rscale);
716: MatRestrict(R,mglevels[i+1]->smoothd->dm->x,mglevels[i]->smoothd->dm->x);
717: VecPointwiseMult(mglevels[i]->smoothd->dm->x,mglevels[i]->smoothd->dm->x,rscale);
718: }
719: }
720: if (needRestricts && pc->dm) {
721: for (i=n-2; i>=0; i--) {
722: DM dmfine,dmcoarse;
723: Mat Restrict,Inject;
724: Vec rscale;
725: KSPGetDM(mglevels[i+1]->smoothd,&dmfine);
726: KSPGetDM(mglevels[i]->smoothd,&dmcoarse);
727: PCMGGetRestriction(pc,i+1,&Restrict);
728: PCMGGetRScale(pc,i+1,&rscale);
729: Inject = NULL; /* Callback should create it if it needs Injection */
730: DMRestrict(dmfine,Restrict,rscale,Inject,dmcoarse);
731: }
732: }
734: if (!pc->setupcalled) {
735: for (i=0; i<n; i++) {
736: KSPSetFromOptions(mglevels[i]->smoothd);
737: }
738: for (i=1; i<n; i++) {
739: if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) {
740: KSPSetFromOptions(mglevels[i]->smoothu);
741: }
742: }
743: /* insure that if either interpolation or restriction is set the other other one is set */
744: for (i=1; i<n; i++) {
745: PCMGGetInterpolation(pc,i,NULL);
746: PCMGGetRestriction(pc,i,NULL);
747: }
748: for (i=0; i<n-1; i++) {
749: if (!mglevels[i]->b) {
750: Vec *vec;
751: KSPCreateVecs(mglevels[i]->smoothd,1,&vec,0,NULL);
752: PCMGSetRhs(pc,i,*vec);
753: VecDestroy(vec);
754: PetscFree(vec);
755: }
756: if (!mglevels[i]->r && i) {
757: VecDuplicate(mglevels[i]->b,&tvec);
758: PCMGSetR(pc,i,tvec);
759: VecDestroy(&tvec);
760: }
761: if (!mglevels[i]->x) {
762: VecDuplicate(mglevels[i]->b,&tvec);
763: PCMGSetX(pc,i,tvec);
764: VecDestroy(&tvec);
765: }
766: }
767: if (n != 1 && !mglevels[n-1]->r) {
768: /* PCMGSetR() on the finest level if user did not supply it */
769: Vec *vec;
770: KSPCreateVecs(mglevels[n-1]->smoothd,1,&vec,0,NULL);
771: PCMGSetR(pc,n-1,*vec);
772: VecDestroy(vec);
773: PetscFree(vec);
774: }
775: }
777: if (pc->dm) {
778: /* need to tell all the coarser levels to rebuild the matrix using the DM for that level */
779: for (i=0; i<n-1; i++) {
780: if (mglevels[i]->smoothd->setupstage != KSP_SETUP_NEW) mglevels[i]->smoothd->setupstage = KSP_SETUP_NEWMATRIX;
781: }
782: }
784: for (i=1; i<n; i++) {
785: if (mglevels[i]->smoothu == mglevels[i]->smoothd || mg->am == PC_MG_FULL || mg->am == PC_MG_KASKADE || mg->cyclesperpcapply > 1){
786: /* if doing only down then initial guess is zero */
787: KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);
788: }
789: if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
790: KSPSetUp(mglevels[i]->smoothd);
791: if (mglevels[i]->smoothd->reason == KSP_DIVERGED_PCSETUP_FAILED) {
792: pc->failedreason = PC_SUBPC_ERROR;
793: }
794: if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
795: if (!mglevels[i]->residual) {
796: Mat mat;
797: KSPGetOperators(mglevels[i]->smoothd,&mat,NULL);
798: PCMGSetResidual(pc,i,PCMGResidualDefault,mat);
799: }
800: }
801: for (i=1; i<n; i++) {
802: if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) {
803: Mat downmat,downpmat;
805: /* check if operators have been set for up, if not use down operators to set them */
806: KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,NULL);
807: if (!opsset) {
808: KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat);
809: KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat);
810: }
812: KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);
813: if (mglevels[i]->eventsmoothsetup) {PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);}
814: KSPSetUp(mglevels[i]->smoothu);
815: if (mglevels[i]->smoothu->reason == KSP_DIVERGED_PCSETUP_FAILED) {
816: pc->failedreason = PC_SUBPC_ERROR;
817: }
818: if (mglevels[i]->eventsmoothsetup) {PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);}
819: }
820: }
822: if (mglevels[0]->eventsmoothsetup) {PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);}
823: KSPSetUp(mglevels[0]->smoothd);
824: if (mglevels[0]->smoothd->reason == KSP_DIVERGED_PCSETUP_FAILED) {
825: pc->failedreason = PC_SUBPC_ERROR;
826: }
827: if (mglevels[0]->eventsmoothsetup) {PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);}
829: /*
830: Dump the interpolation/restriction matrices plus the
831: Jacobian/stiffness on each level. This allows MATLAB users to
832: easily check if the Galerkin condition A_c = R A_f R^T is satisfied.
834: Only support one or the other at the same time.
835: */
836: #if defined(PETSC_USE_SOCKET_VIEWER)
837: PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,NULL);
838: if (dump) viewer = PETSC_VIEWER_SOCKET_(PetscObjectComm((PetscObject)pc));
839: dump = PETSC_FALSE;
840: #endif
841: PetscOptionsGetBool(((PetscObject)pc)->options,((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,NULL);
842: if (dump) viewer = PETSC_VIEWER_BINARY_(PetscObjectComm((PetscObject)pc));
844: if (viewer) {
845: for (i=1; i<n; i++) {
846: MatView(mglevels[i]->restrct,viewer);
847: }
848: for (i=0; i<n; i++) {
849: KSPGetPC(mglevels[i]->smoothd,&pc);
850: MatView(pc->mat,viewer);
851: }
852: }
853: return(0);
854: }
856: /* -------------------------------------------------------------------------------------*/
858: /*@
859: PCMGGetLevels - Gets the number of levels to use with MG.
861: Not Collective
863: Input Parameter:
864: . pc - the preconditioner context
866: Output parameter:
867: . levels - the number of levels
869: Level: advanced
871: .keywords: MG, get, levels, multigrid
873: .seealso: PCMGSetLevels()
874: @*/
875: PetscErrorCode PCMGGetLevels(PC pc,PetscInt *levels)
876: {
877: PC_MG *mg = (PC_MG*)pc->data;
882: *levels = mg->nlevels;
883: return(0);
884: }
886: /*@
887: PCMGSetType - Determines the form of multigrid to use:
888: multiplicative, additive, full, or the Kaskade algorithm.
890: Logically Collective on PC
892: Input Parameters:
893: + pc - the preconditioner context
894: - form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
895: PC_MG_FULL, PC_MG_KASKADE
897: Options Database Key:
898: . -pc_mg_type <form> - Sets <form>, one of multiplicative,
899: additive, full, kaskade
901: Level: advanced
903: .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid
905: .seealso: PCMGSetLevels()
906: @*/
907: PetscErrorCode PCMGSetType(PC pc,PCMGType form)
908: {
909: PC_MG *mg = (PC_MG*)pc->data;
914: mg->am = form;
915: if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
916: else pc->ops->applyrichardson = NULL;
917: return(0);
918: }
920: /*@
921: PCMGGetType - Determines the form of multigrid to use:
922: multiplicative, additive, full, or the Kaskade algorithm.
924: Logically Collective on PC
926: Input Parameter:
927: . pc - the preconditioner context
929: Output Parameter:
930: . type - one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,PC_MG_FULL, PC_MG_KASKADE
933: Level: advanced
935: .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid
937: .seealso: PCMGSetLevels()
938: @*/
939: PetscErrorCode PCMGGetType(PC pc,PCMGType *type)
940: {
941: PC_MG *mg = (PC_MG*)pc->data;
945: *type = mg->am;
946: return(0);
947: }
949: /*@
950: PCMGSetCycleType - Sets the type cycles to use. Use PCMGSetCycleTypeOnLevel() for more
951: complicated cycling.
953: Logically Collective on PC
955: Input Parameters:
956: + pc - the multigrid context
957: - n - either PC_MG_CYCLE_V or PC_MG_CYCLE_W
959: Options Database Key:
960: . -pc_mg_cycle_type <v,w> - provide the cycle desired
962: Level: advanced
964: .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
966: .seealso: PCMGSetCycleTypeOnLevel()
967: @*/
968: PetscErrorCode PCMGSetCycleType(PC pc,PCMGCycleType n)
969: {
970: PC_MG *mg = (PC_MG*)pc->data;
971: PC_MG_Levels **mglevels = mg->levels;
972: PetscInt i,levels;
977: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
978: levels = mglevels[0]->levels;
979: for (i=0; i<levels; i++) mglevels[i]->cycles = n;
980: return(0);
981: }
983: /*@
984: PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step
985: of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used
987: Logically Collective on PC
989: Input Parameters:
990: + pc - the multigrid context
991: - n - number of cycles (default is 1)
993: Options Database Key:
994: . -pc_mg_multiplicative_cycles n
996: Level: advanced
998: Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType()
1000: .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
1002: .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
1003: @*/
1004: PetscErrorCode PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
1005: {
1006: PC_MG *mg = (PC_MG*)pc->data;
1011: mg->cyclesperpcapply = n;
1012: return(0);
1013: }
1015: PetscErrorCode PCMGSetGalerkin_MG(PC pc,PCMGGalerkinType use)
1016: {
1017: PC_MG *mg = (PC_MG*)pc->data;
1020: mg->galerkin = use;
1021: return(0);
1022: }
1024: /*@
1025: PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
1026: finest grid via the Galerkin process: A_i-1 = r_i * A_i * p_i
1028: Logically Collective on PC
1030: Input Parameters:
1031: + pc - the multigrid context
1032: - use - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, or PC_MG_GALERKIN_NONE
1034: Options Database Key:
1035: . -pc_mg_galerkin <both,pmat,mat,none>
1037: Level: intermediate
1039: Notes: Some codes that use PCMG such as PCGAMG use Galerkin internally while constructing the hierarchy and thus do not
1040: use the PCMG construction of the coarser grids.
1042: .keywords: MG, set, Galerkin
1044: .seealso: PCMGGetGalerkin(), PCMGGalerkinType
1046: @*/
1047: PetscErrorCode PCMGSetGalerkin(PC pc,PCMGGalerkinType use)
1048: {
1053: PetscTryMethod(pc,"PCMGSetGalerkin_C",(PC,PCMGGalerkinType),(pc,use));
1054: return(0);
1055: }
1057: /*@
1058: PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
1059: A_i-1 = r_i * A_i * p_i
1061: Not Collective
1063: Input Parameter:
1064: . pc - the multigrid context
1066: Output Parameter:
1067: . galerkin - one of PC_MG_GALERKIN_BOTH,PC_MG_GALERKIN_PMAT,PC_MG_GALERKIN_MAT, PC_MG_GALERKIN_NONE, or PC_MG_GALERKIN_EXTERNAL
1069: Level: intermediate
1071: .keywords: MG, set, Galerkin
1073: .seealso: PCMGSetGalerkin(), PCMGGalerkinType
1075: @*/
1076: PetscErrorCode PCMGGetGalerkin(PC pc,PCMGGalerkinType *galerkin)
1077: {
1078: PC_MG *mg = (PC_MG*)pc->data;
1082: *galerkin = mg->galerkin;
1083: return(0);
1084: }
1086: /*@
1087: PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to
1088: use on all levels. Use PCMGGetSmootherDown() to set different
1089: pre-smoothing steps on different levels.
1091: Logically Collective on PC
1093: Input Parameters:
1094: + mg - the multigrid context
1095: - n - the number of smoothing steps
1097: Options Database Key:
1098: . -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps
1100: Level: advanced
1101: If the number of smoothing steps is changed in this call then the PCMGGetSmoothUp() will be called and now the
1102: up smoother will no longer share the same KSP object as the down smoother. Use PCMGSetNumberSmooth() to set the same
1103: number of smoothing steps for pre and post smoothing.
1105: .keywords: MG, smooth, down, pre-smoothing, steps, multigrid
1107: .seealso: PCMGSetNumberSmoothUp(), PCMGSetNumberSmooth()
1108: @*/
1109: PetscErrorCode PCMGSetNumberSmoothDown(PC pc,PetscInt n)
1110: {
1111: PC_MG *mg = (PC_MG*)pc->data;
1112: PC_MG_Levels **mglevels = mg->levels;
1114: PetscInt i,levels;
1119: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1120: levels = mglevels[0]->levels;
1121: for (i=1; i<levels; i++) {
1122: PetscInt nc;
1123: KSPGetTolerances(mglevels[i]->smoothd,NULL,NULL,NULL,&nc);
1124: if (nc == n) continue;
1126: /* make sure smoother up and down are different */
1127: PCMGGetSmootherUp(pc,i,NULL);
1128: KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1130: mg->default_smoothd = n;
1131: }
1132: return(0);
1133: }
1135: /*@
1136: PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use
1137: on all levels. Use PCMGGetSmootherUp() to set different numbers of
1138: post-smoothing steps on different levels.
1140: Logically Collective on PC
1142: Input Parameters:
1143: + mg - the multigrid context
1144: - n - the number of smoothing steps
1146: Options Database Key:
1147: . -pc_mg_smoothup <n> - Sets number of post-smoothing steps
1149: Level: advanced
1151: Notes: this does not set a value on the coarsest grid, since we assume that
1152: there is no separate smooth up on the coarsest grid.
1154: If the number of smoothing steps is changed in this call then the PCMGGetSmoothUp() will be called and now the
1155: up smoother will no longer share the same KSP object as the down smoother. Use PCMGSetNumberSmooth() to set the same
1156: number of smoothing steps for pre and post smoothing.
1159: .keywords: MG, smooth, up, post-smoothing, steps, multigrid
1161: .seealso: PCMGSetNumberSmoothDown(), PCMGSetNumberSmooth()
1162: @*/
1163: PetscErrorCode PCMGSetNumberSmoothUp(PC pc,PetscInt n)
1164: {
1165: PC_MG *mg = (PC_MG*)pc->data;
1166: PC_MG_Levels **mglevels = mg->levels;
1168: PetscInt i,levels;
1173: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1174: levels = mglevels[0]->levels;
1176: for (i=1; i<levels; i++) {
1177: if (mglevels[i]->smoothu == mglevels[i]->smoothd) {
1178: PetscInt nc;
1179: KSPGetTolerances(mglevels[i]->smoothd,NULL,NULL,NULL,&nc);
1180: if (nc == n) continue;
1181: }
1183: /* make sure smoother up and down are different */
1184: PCMGGetSmootherUp(pc,i,NULL);
1185: KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1187: mg->default_smoothu = n;
1188: }
1189: return(0);
1190: }
1192: /*@
1193: PCMGSetNumberSmooth - Sets the number of pre and post-smoothing steps to use
1194: on all levels. Use PCMGSetSmoothUp() and PCMGSetSmoothDown() set different numbers of
1195: pre ad post-smoothing steps
1197: Logically Collective on PC
1199: Input Parameters:
1200: + mg - the multigrid context
1201: - n - the number of smoothing steps
1203: Options Database Key:
1204: + -mg_levels_ksp_max_it <n> - Sets number of pre and post-smoothing steps
1205: . -pc_mg_smooth_down <n> - Sets number of pre-smoothing steps (if setting different pre and post amounts)
1206: - -pc_mg_smooth_up <n> - Sets number of post-smoothing steps (if setting different pre and post amounts)
1208: Level: advanced
1210: Notes: this does not set a value on the coarsest grid, since we assume that
1211: there is no separate smooth up on the coarsest grid.
1213: .keywords: MG, smooth, up, post-smoothing, steps, multigrid
1215: .seealso: PCMGSetNumberSmoothDown(), PCMGSetNumberSmoothUp()
1216: @*/
1217: PetscErrorCode PCMGSetNumberSmooth(PC pc,PetscInt n)
1218: {
1219: PC_MG *mg = (PC_MG*)pc->data;
1220: PC_MG_Levels **mglevels = mg->levels;
1222: PetscInt i,levels;
1227: if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ORDER,"Must set MG levels with PCMGSetLevels() before calling");
1228: levels = mglevels[0]->levels;
1230: for (i=1; i<levels; i++) {
1231: KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1232: KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);
1233: mg->default_smoothu = n;
1234: mg->default_smoothd = n;
1235: }
1236: return(0);
1237: }
1239: /* ----------------------------------------------------------------------------------------*/
1241: /*MC
1242: PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional
1243: information about the coarser grid matrices and restriction/interpolation operators.
1245: Options Database Keys:
1246: + -pc_mg_levels <nlevels> - number of levels including finest
1247: . -pc_mg_cycle_type <v,w> -
1248: . -pc_mg_smoothup <n> - number of smoothing steps after interpolation
1249: . -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator
1250: . -pc_mg_type <additive,multiplicative,full,kaskade> - multiplicative is the default
1251: . -pc_mg_log - log information about time spent on each level of the solver
1252: . -pc_mg_galerkin <both,pmat,mat,none> - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R'
1253: . -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1)
1254: . -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
1255: to the Socket viewer for reading from MATLAB.
1256: - -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices
1257: to the binary output file called binaryoutput
1259: Notes: If one uses a Krylov method such GMRES or CG as the smoother than one must use KSPFGMRES, KSPGCG, or KSPRICHARDSON as the outer Krylov method
1261: When run with a single level the smoother options are used on that level NOT the coarse grid solver options
1263: When run with KSPRICHARDSON the convergence test changes slightly if monitor is turned on. The iteration count may change slightly. This
1264: is because without monitoring the residual norm is computed WITHIN each multigrid cycle on the finest level after the pre-smoothing
1265: (because the residual has just been computed for the multigrid algorithm and is hence available for free) while with monitoring the
1266: residual is computed at the end of each cycle.
1268: Level: intermediate
1270: Concepts: multigrid/multilevel
1272: .seealso: PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE
1273: PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(),
1274: PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
1275: PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
1276: PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
1277: M*/
1279: PETSC_EXTERN PetscErrorCode PCCreate_MG(PC pc)
1280: {
1281: PC_MG *mg;
1285: PetscNewLog(pc,&mg);
1286: pc->data = (void*)mg;
1287: mg->nlevels = -1;
1288: mg->am = PC_MG_MULTIPLICATIVE;
1289: mg->galerkin = PC_MG_GALERKIN_NONE;
1291: pc->useAmat = PETSC_TRUE;
1293: pc->ops->apply = PCApply_MG;
1294: pc->ops->setup = PCSetUp_MG;
1295: pc->ops->reset = PCReset_MG;
1296: pc->ops->destroy = PCDestroy_MG;
1297: pc->ops->setfromoptions = PCSetFromOptions_MG;
1298: pc->ops->view = PCView_MG;
1300: PetscObjectComposeFunction((PetscObject)pc,"PCMGSetGalerkin_C",PCMGSetGalerkin_MG);
1301: return(0);
1302: }