xref: /petsc/src/ksp/pc/impls/mg/mg.c (revision 71b23a656256eec4ec090f1e6a6d9bbd8836ce31)
1 
2 /*
3     Defines the multigrid preconditioner interface.
4 */
5 #include <../src/ksp/pc/impls/mg/mgimpl.h>                    /*I "petscksp.h" I*/
6 #include <petscdm.h>
7 
8 #undef __FUNCT__
9 #define __FUNCT__ "PCMGMCycle_Private"
10 PetscErrorCode PCMGMCycle_Private(PC pc,PC_MG_Levels **mglevelsin,PCRichardsonConvergedReason *reason)
11 {
12   PC_MG          *mg = (PC_MG*)pc->data;
13   PC_MG_Levels   *mgc,*mglevels = *mglevelsin;
14   PetscErrorCode ierr;
15   PetscInt       cycles = (mglevels->level == 1) ? 1 : (PetscInt) mglevels->cycles;
16 
17   PetscFunctionBegin;
18   if (mglevels->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
19   ierr = KSPSolve(mglevels->smoothd,mglevels->b,mglevels->x);CHKERRQ(ierr);  /* pre-smooth */
20   if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
21   if (mglevels->level) {  /* not the coarsest grid */
22     if (mglevels->eventresidual) {ierr = PetscLogEventBegin(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);}
23     ierr = (*mglevels->residual)(mglevels->A,mglevels->b,mglevels->x,mglevels->r);CHKERRQ(ierr);
24     if (mglevels->eventresidual) {ierr = PetscLogEventEnd(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);}
25 
26     /* if on finest level and have convergence criteria set */
27     if (mglevels->level == mglevels->levels-1 && mg->ttol && reason) {
28       PetscReal rnorm;
29       ierr = VecNorm(mglevels->r,NORM_2,&rnorm);CHKERRQ(ierr);
30       if (rnorm <= mg->ttol) {
31         if (rnorm < mg->abstol) {
32           *reason = PCRICHARDSON_CONVERGED_ATOL;
33           ierr    = PetscInfo2(pc,"Linear solver has converged. Residual norm %G is less than absolute tolerance %G\n",rnorm,mg->abstol);CHKERRQ(ierr);
34         } else {
35           *reason = PCRICHARDSON_CONVERGED_RTOL;
36           ierr    = PetscInfo2(pc,"Linear solver has converged. Residual norm %G is less than relative tolerance times initial residual norm %G\n",rnorm,mg->ttol);CHKERRQ(ierr);
37         }
38         PetscFunctionReturn(0);
39       }
40     }
41 
42     mgc = *(mglevelsin - 1);
43     if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
44     ierr = MatRestrict(mglevels->restrct,mglevels->r,mgc->b);CHKERRQ(ierr);
45     if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
46     ierr = VecSet(mgc->x,0.0);CHKERRQ(ierr);
47     while (cycles--) {
48       ierr = PCMGMCycle_Private(pc,mglevelsin-1,reason);CHKERRQ(ierr);
49     }
50     if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
51     ierr = MatInterpolateAdd(mglevels->interpolate,mgc->x,mglevels->x,mglevels->x);CHKERRQ(ierr);
52     if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
53     if (mglevels->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
54     ierr = KSPSolve(mglevels->smoothu,mglevels->b,mglevels->x);CHKERRQ(ierr);    /* post smooth */
55     if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
56   }
57   PetscFunctionReturn(0);
58 }
59 
60 #undef __FUNCT__
61 #define __FUNCT__ "PCApplyRichardson_MG"
62 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)
63 {
64   PC_MG          *mg        = (PC_MG*)pc->data;
65   PC_MG_Levels   **mglevels = mg->levels;
66   PetscErrorCode ierr;
67   PetscInt       levels = mglevels[0]->levels,i;
68 
69   PetscFunctionBegin;
70   mglevels[levels-1]->b = b;
71   mglevels[levels-1]->x = x;
72 
73   mg->rtol   = rtol;
74   mg->abstol = abstol;
75   mg->dtol   = dtol;
76   if (rtol) {
77     /* compute initial residual norm for relative convergence test */
78     PetscReal rnorm;
79     if (zeroguess) {
80       ierr = VecNorm(b,NORM_2,&rnorm);CHKERRQ(ierr);
81     } else {
82       ierr = (*mglevels[levels-1]->residual)(mglevels[levels-1]->A,b,x,w);CHKERRQ(ierr);
83       ierr = VecNorm(w,NORM_2,&rnorm);CHKERRQ(ierr);
84     }
85     mg->ttol = PetscMax(rtol*rnorm,abstol);
86   } else if (abstol) mg->ttol = abstol;
87   else mg->ttol = 0.0;
88 
89   /* since smoother is applied to full system, not just residual we need to make sure that smoothers don't
90      stop prematurely due to small residual */
91   for (i=1; i<levels; i++) {
92     ierr = KSPSetTolerances(mglevels[i]->smoothu,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr);
93     if (mglevels[i]->smoothu != mglevels[i]->smoothd) {
94       ierr = KSPSetTolerances(mglevels[i]->smoothd,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr);
95     }
96   }
97 
98   *reason = (PCRichardsonConvergedReason)0;
99   for (i=0; i<its; i++) {
100     ierr = PCMGMCycle_Private(pc,mglevels+levels-1,reason);CHKERRQ(ierr);
101     if (*reason) break;
102   }
103   if (!*reason) *reason = PCRICHARDSON_CONVERGED_ITS;
104   *outits = i;
105   PetscFunctionReturn(0);
106 }
107 
108 #undef __FUNCT__
109 #define __FUNCT__ "PCReset_MG"
110 PetscErrorCode PCReset_MG(PC pc)
111 {
112   PC_MG          *mg        = (PC_MG*)pc->data;
113   PC_MG_Levels   **mglevels = mg->levels;
114   PetscErrorCode ierr;
115   PetscInt       i,n;
116 
117   PetscFunctionBegin;
118   if (mglevels) {
119     n = mglevels[0]->levels;
120     for (i=0; i<n-1; i++) {
121       ierr = VecDestroy(&mglevels[i+1]->r);CHKERRQ(ierr);
122       ierr = VecDestroy(&mglevels[i]->b);CHKERRQ(ierr);
123       ierr = VecDestroy(&mglevels[i]->x);CHKERRQ(ierr);
124       ierr = MatDestroy(&mglevels[i+1]->restrct);CHKERRQ(ierr);
125       ierr = MatDestroy(&mglevels[i+1]->interpolate);CHKERRQ(ierr);
126       ierr = VecDestroy(&mglevels[i+1]->rscale);CHKERRQ(ierr);
127     }
128 
129     for (i=0; i<n; i++) {
130       ierr = MatDestroy(&mglevels[i]->A);CHKERRQ(ierr);
131       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
132         ierr = KSPReset(mglevels[i]->smoothd);CHKERRQ(ierr);
133       }
134       ierr = KSPReset(mglevels[i]->smoothu);CHKERRQ(ierr);
135     }
136   }
137   PetscFunctionReturn(0);
138 }
139 
140 #undef __FUNCT__
141 #define __FUNCT__ "PCMGSetLevels"
142 /*@C
143    PCMGSetLevels - Sets the number of levels to use with MG.
144    Must be called before any other MG routine.
145 
146    Logically Collective on PC
147 
148    Input Parameters:
149 +  pc - the preconditioner context
150 .  levels - the number of levels
151 -  comms - optional communicators for each level; this is to allow solving the coarser problems
152            on smaller sets of processors. Use NULL_OBJECT for default in Fortran
153 
154    Level: intermediate
155 
156    Notes:
157      If the number of levels is one then the multigrid uses the -mg_levels prefix
158   for setting the level options rather than the -mg_coarse prefix.
159 
160 .keywords: MG, set, levels, multigrid
161 
162 .seealso: PCMGSetType(), PCMGGetLevels()
163 @*/
164 PetscErrorCode  PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
165 {
166   PetscErrorCode ierr;
167   PC_MG          *mg        = (PC_MG*)pc->data;
168   MPI_Comm       comm;
169   PC_MG_Levels   **mglevels = mg->levels;
170   PetscInt       i;
171   PetscMPIInt    size;
172   const char     *prefix;
173   PC             ipc;
174   PetscInt       n;
175 
176   PetscFunctionBegin;
177   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
178   PetscValidLogicalCollectiveInt(pc,levels,2);
179   ierr = PetscObjectGetComm((PetscObject)pc,&comm);CHKERRQ(ierr);
180   if (mg->nlevels == levels) PetscFunctionReturn(0);
181   if (mglevels) {
182     /* changing the number of levels so free up the previous stuff */
183     ierr = PCReset_MG(pc);CHKERRQ(ierr);
184     n    = mglevels[0]->levels;
185     for (i=0; i<n; i++) {
186       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
187         ierr = KSPDestroy(&mglevels[i]->smoothd);CHKERRQ(ierr);
188       }
189       ierr = KSPDestroy(&mglevels[i]->smoothu);CHKERRQ(ierr);
190       ierr = PetscFree(mglevels[i]);CHKERRQ(ierr);
191     }
192     ierr = PetscFree(mg->levels);CHKERRQ(ierr);
193   }
194 
195   mg->nlevels = levels;
196 
197   ierr = PetscMalloc(levels*sizeof(PC_MG*),&mglevels);CHKERRQ(ierr);
198   ierr = PetscLogObjectMemory(pc,levels*(sizeof(PC_MG*)));CHKERRQ(ierr);
199 
200   ierr = PCGetOptionsPrefix(pc,&prefix);CHKERRQ(ierr);
201 
202   mg->stageApply = 0;
203   for (i=0; i<levels; i++) {
204     ierr = PetscNewLog(pc,PC_MG_Levels,&mglevels[i]);CHKERRQ(ierr);
205 
206     mglevels[i]->level               = i;
207     mglevels[i]->levels              = levels;
208     mglevels[i]->cycles              = PC_MG_CYCLE_V;
209     mg->default_smoothu              = 2;
210     mg->default_smoothd              = 2;
211     mglevels[i]->eventsmoothsetup    = 0;
212     mglevels[i]->eventsmoothsolve    = 0;
213     mglevels[i]->eventresidual       = 0;
214     mglevels[i]->eventinterprestrict = 0;
215 
216     if (comms) comm = comms[i];
217     ierr = KSPCreate(comm,&mglevels[i]->smoothd);CHKERRQ(ierr);
218     ierr = KSPSetType(mglevels[i]->smoothd,KSPCHEBYSHEV);CHKERRQ(ierr);
219     ierr = KSPSetConvergenceTest(mglevels[i]->smoothd,KSPSkipConverged,NULL,NULL);CHKERRQ(ierr);
220     ierr = KSPSetNormType(mglevels[i]->smoothd,KSP_NORM_NONE);CHKERRQ(ierr);
221     ierr = KSPGetPC(mglevels[i]->smoothd,&ipc);CHKERRQ(ierr);
222     ierr = PCSetType(ipc,PCSOR);CHKERRQ(ierr);
223     ierr = PetscObjectIncrementTabLevel((PetscObject)mglevels[i]->smoothd,(PetscObject)pc,levels-i);CHKERRQ(ierr);
224     ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, i ? mg->default_smoothd : 1);CHKERRQ(ierr);
225     ierr = KSPSetOptionsPrefix(mglevels[i]->smoothd,prefix);CHKERRQ(ierr);
226 
227     /* do special stuff for coarse grid */
228     if (!i && levels > 1) {
229       ierr = KSPAppendOptionsPrefix(mglevels[0]->smoothd,"mg_coarse_");CHKERRQ(ierr);
230 
231       /* coarse solve is (redundant) LU by default; set shifttype NONZERO to avoid annoying zero-pivot in LU preconditioner */
232       ierr = KSPSetType(mglevels[0]->smoothd,KSPPREONLY);CHKERRQ(ierr);
233       ierr = KSPGetPC(mglevels[0]->smoothd,&ipc);CHKERRQ(ierr);
234       ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
235       if (size > 1) {
236         KSP innerksp;
237         PC  innerpc;
238         ierr = PCSetType(ipc,PCREDUNDANT);CHKERRQ(ierr);
239         ierr = PCRedundantGetKSP(ipc,&innerksp);CHKERRQ(ierr);
240         ierr = KSPGetPC(innerksp,&innerpc);CHKERRQ(ierr);
241         ierr = PCFactorSetShiftType(innerpc,MAT_SHIFT_INBLOCKS);CHKERRQ(ierr);
242       } else {
243         ierr = PCSetType(ipc,PCLU);CHKERRQ(ierr);
244         ierr = PCFactorSetShiftType(ipc,MAT_SHIFT_INBLOCKS);CHKERRQ(ierr);
245       }
246     } else {
247       char tprefix[128];
248       sprintf(tprefix,"mg_levels_%d_",(int)i);
249       ierr = KSPAppendOptionsPrefix(mglevels[i]->smoothd,tprefix);CHKERRQ(ierr);
250     }
251     ierr = PetscLogObjectParent(pc,mglevels[i]->smoothd);CHKERRQ(ierr);
252 
253     mglevels[i]->smoothu = mglevels[i]->smoothd;
254     mg->rtol             = 0.0;
255     mg->abstol           = 0.0;
256     mg->dtol             = 0.0;
257     mg->ttol             = 0.0;
258     mg->cyclesperpcapply = 1;
259   }
260   mg->am                   = PC_MG_MULTIPLICATIVE;
261   mg->levels               = mglevels;
262   pc->ops->applyrichardson = PCApplyRichardson_MG;
263   PetscFunctionReturn(0);
264 }
265 
266 
267 #undef __FUNCT__
268 #define __FUNCT__ "PCDestroy_MG"
269 PetscErrorCode PCDestroy_MG(PC pc)
270 {
271   PetscErrorCode ierr;
272   PC_MG          *mg        = (PC_MG*)pc->data;
273   PC_MG_Levels   **mglevels = mg->levels;
274   PetscInt       i,n;
275 
276   PetscFunctionBegin;
277   ierr = PCReset_MG(pc);CHKERRQ(ierr);
278   if (mglevels) {
279     n = mglevels[0]->levels;
280     for (i=0; i<n; i++) {
281       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
282         ierr = KSPDestroy(&mglevels[i]->smoothd);CHKERRQ(ierr);
283       }
284       ierr = KSPDestroy(&mglevels[i]->smoothu);CHKERRQ(ierr);
285       ierr = PetscFree(mglevels[i]);CHKERRQ(ierr);
286     }
287     ierr = PetscFree(mg->levels);CHKERRQ(ierr);
288   }
289   ierr = PetscFree(pc->data);CHKERRQ(ierr);
290   PetscFunctionReturn(0);
291 }
292 
293 
294 
295 extern PetscErrorCode PCMGACycle_Private(PC,PC_MG_Levels**);
296 extern PetscErrorCode PCMGFCycle_Private(PC,PC_MG_Levels**);
297 extern PetscErrorCode PCMGKCycle_Private(PC,PC_MG_Levels**);
298 
299 /*
300    PCApply_MG - Runs either an additive, multiplicative, Kaskadic
301              or full cycle of multigrid.
302 
303   Note:
304   A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle().
305 */
306 #undef __FUNCT__
307 #define __FUNCT__ "PCApply_MG"
308 static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
309 {
310   PC_MG          *mg        = (PC_MG*)pc->data;
311   PC_MG_Levels   **mglevels = mg->levels;
312   PetscErrorCode ierr;
313   PetscInt       levels = mglevels[0]->levels,i;
314 
315   PetscFunctionBegin;
316   if (mg->stageApply) {ierr = PetscLogStagePush(mg->stageApply);CHKERRQ(ierr);}
317   /* When the DM is supplying the matrix then it will not exist until here */
318   for (i=0; i<levels; i++) {
319     if (!mglevels[i]->A) {
320       ierr = KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,NULL,NULL);CHKERRQ(ierr);
321       ierr = PetscObjectReference((PetscObject)mglevels[i]->A);CHKERRQ(ierr);
322     }
323   }
324 
325   mglevels[levels-1]->b = b;
326   mglevels[levels-1]->x = x;
327   if (mg->am == PC_MG_MULTIPLICATIVE) {
328     ierr = VecSet(x,0.0);CHKERRQ(ierr);
329     for (i=0; i<mg->cyclesperpcapply; i++) {
330       ierr = PCMGMCycle_Private(pc,mglevels+levels-1,NULL);CHKERRQ(ierr);
331     }
332   } else if (mg->am == PC_MG_ADDITIVE) {
333     ierr = PCMGACycle_Private(pc,mglevels);CHKERRQ(ierr);
334   } else if (mg->am == PC_MG_KASKADE) {
335     ierr = PCMGKCycle_Private(pc,mglevels);CHKERRQ(ierr);
336   } else {
337     ierr = PCMGFCycle_Private(pc,mglevels);CHKERRQ(ierr);
338   }
339   if (mg->stageApply) {ierr = PetscLogStagePop();CHKERRQ(ierr);}
340   PetscFunctionReturn(0);
341 }
342 
343 
344 #undef __FUNCT__
345 #define __FUNCT__ "PCSetFromOptions_MG"
346 PetscErrorCode PCSetFromOptions_MG(PC pc)
347 {
348   PetscErrorCode ierr;
349   PetscInt       m,levels = 1,cycles;
350   PetscBool      flg,set;
351   PC_MG          *mg        = (PC_MG*)pc->data;
352   PC_MG_Levels   **mglevels = mg->levels;
353   PCMGType       mgtype;
354   PCMGCycleType  mgctype;
355 
356   PetscFunctionBegin;
357   ierr = PetscOptionsHead("Multigrid options");CHKERRQ(ierr);
358   if (!mg->levels) {
359     ierr = PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);CHKERRQ(ierr);
360     if (!flg && pc->dm) {
361       ierr = DMGetRefineLevel(pc->dm,&levels);CHKERRQ(ierr);
362       levels++;
363       mg->usedmfornumberoflevels = PETSC_TRUE;
364     }
365     ierr = PCMGSetLevels(pc,levels,NULL);CHKERRQ(ierr);
366   }
367   mglevels = mg->levels;
368 
369   mgctype = (PCMGCycleType) mglevels[0]->cycles;
370   ierr    = PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);CHKERRQ(ierr);
371   if (flg) {
372     ierr = PCMGSetCycleType(pc,mgctype);CHKERRQ(ierr);
373   }
374   flg  = PETSC_FALSE;
375   ierr = PetscOptionsBool("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",flg,&flg,&set);CHKERRQ(ierr);
376   if (set) {
377     ierr = PCMGSetGalerkin(pc,flg);CHKERRQ(ierr);
378   }
379   ierr = PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",1,&m,&flg);CHKERRQ(ierr);
380   if (flg) {
381     ierr = PCMGSetNumberSmoothUp(pc,m);CHKERRQ(ierr);
382   }
383   ierr = PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",1,&m,&flg);CHKERRQ(ierr);
384   if (flg) {
385     ierr = PCMGSetNumberSmoothDown(pc,m);CHKERRQ(ierr);
386   }
387   mgtype = mg->am;
388   ierr   = PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);CHKERRQ(ierr);
389   if (flg) {
390     ierr = PCMGSetType(pc,mgtype);CHKERRQ(ierr);
391   }
392   if (mg->am == PC_MG_MULTIPLICATIVE) {
393     ierr = PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGSetLevels",mg->cyclesperpcapply,&cycles,&flg);CHKERRQ(ierr);
394     if (flg) {
395       ierr = PCMGMultiplicativeSetCycles(pc,cycles);CHKERRQ(ierr);
396     }
397   }
398   flg  = PETSC_FALSE;
399   ierr = PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,NULL);CHKERRQ(ierr);
400   if (flg) {
401     PetscInt i;
402     char     eventname[128];
403     if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
404     levels = mglevels[0]->levels;
405     for (i=0; i<levels; i++) {
406       sprintf(eventname,"MGSetup Level %d",(int)i);
407       ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);CHKERRQ(ierr);
408       sprintf(eventname,"MGSmooth Level %d",(int)i);
409       ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);CHKERRQ(ierr);
410       if (i) {
411         sprintf(eventname,"MGResid Level %d",(int)i);
412         ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);CHKERRQ(ierr);
413         sprintf(eventname,"MGInterp Level %d",(int)i);
414         ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);CHKERRQ(ierr);
415       }
416     }
417 
418 #if defined(PETSC_USE_LOG)
419     {
420       const char    *sname = "MG Apply";
421       PetscStageLog stageLog;
422       PetscInt      st;
423 
424       PetscFunctionBegin;
425       ierr = PetscLogGetStageLog(&stageLog);CHKERRQ(ierr);
426       for (st = 0; st < stageLog->numStages; ++st) {
427         PetscBool same;
428 
429         ierr = PetscStrcmp(stageLog->stageInfo[st].name, sname, &same);CHKERRQ(ierr);
430         if (same) mg->stageApply = st;
431       }
432       if (!mg->stageApply) {
433         ierr = PetscLogStageRegister(sname, &mg->stageApply);CHKERRQ(ierr);
434       }
435     }
436 #endif
437   }
438   ierr = PetscOptionsTail();CHKERRQ(ierr);
439   PetscFunctionReturn(0);
440 }
441 
442 const char *const PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0};
443 const char *const PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",0};
444 
445 #include <petscdraw.h>
446 #undef __FUNCT__
447 #define __FUNCT__ "PCView_MG"
448 PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
449 {
450   PC_MG          *mg        = (PC_MG*)pc->data;
451   PC_MG_Levels   **mglevels = mg->levels;
452   PetscErrorCode ierr;
453   PetscInt       levels = mglevels[0]->levels,i;
454   PetscBool      iascii,isbinary,isdraw;
455 
456   PetscFunctionBegin;
457   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
458   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr);
459   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr);
460   if (iascii) {
461     ierr = PetscViewerASCIIPrintf(viewer,"  MG: type is %s, levels=%D cycles=%s\n", PCMGTypes[mg->am],levels,(mglevels[0]->cycles == PC_MG_CYCLE_V) ? "v" : "w");CHKERRQ(ierr);
462     if (mg->am == PC_MG_MULTIPLICATIVE) {
463       ierr = PetscViewerASCIIPrintf(viewer,"    Cycles per PCApply=%d\n",mg->cyclesperpcapply);CHKERRQ(ierr);
464     }
465     if (mg->galerkin) {
466       ierr = PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr);
467     } else {
468       ierr = PetscViewerASCIIPrintf(viewer,"    Not using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr);
469     }
470     for (i=0; i<levels; i++) {
471       if (!i) {
472         ierr = PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level -------------------------------\n",i);CHKERRQ(ierr);
473       } else {
474         ierr = PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr);
475       }
476       ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
477       ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr);
478       ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
479       if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) {
480         ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");CHKERRQ(ierr);
481       } else if (i) {
482         ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr);
483         ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
484         ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr);
485         ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
486       }
487     }
488   } else if (isbinary) {
489     for (i=levels-1; i>=0; i--) {
490       ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr);
491       if (i && mglevels[i]->smoothd != mglevels[i]->smoothu) {
492         ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr);
493       }
494     }
495   } else if (isdraw) {
496     PetscDraw draw;
497     PetscReal x,w,y,bottom,th;
498     ierr   = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr);
499     ierr   = PetscDrawGetCurrentPoint(draw,&x,&y);CHKERRQ(ierr);
500     ierr   = PetscDrawStringGetSize(draw,NULL,&th);CHKERRQ(ierr);
501     bottom = y - th;
502     for (i=levels-1; i>=0; i--) {
503       if (!mglevels[i]->smoothu || (mglevels[i]->smoothu == mglevels[i]->smoothd)) {
504         ierr = PetscDrawPushCurrentPoint(draw,x,bottom);CHKERRQ(ierr);
505         ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr);
506         ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr);
507       } else {
508         w    = 0.5*PetscMin(1.0-x,x);
509         ierr = PetscDrawPushCurrentPoint(draw,x+w,bottom);CHKERRQ(ierr);
510         ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr);
511         ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr);
512         ierr = PetscDrawPushCurrentPoint(draw,x-w,bottom);CHKERRQ(ierr);
513         ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr);
514         ierr = PetscDrawPopCurrentPoint(draw);CHKERRQ(ierr);
515       }
516       ierr    = PetscDrawGetBoundingBox(draw,NULL,&bottom,NULL,NULL);CHKERRQ(ierr);
517       bottom -= th;
518     }
519   }
520   PetscFunctionReturn(0);
521 }
522 
523 #include <petsc-private/dmimpl.h>
524 #include <petsc-private/kspimpl.h>
525 
526 /*
527     Calls setup for the KSP on each level
528 */
529 #undef __FUNCT__
530 #define __FUNCT__ "PCSetUp_MG"
531 PetscErrorCode PCSetUp_MG(PC pc)
532 {
533   PC_MG          *mg        = (PC_MG*)pc->data;
534   PC_MG_Levels   **mglevels = mg->levels;
535   PetscErrorCode ierr;
536   PetscInt       i,n = mglevels[0]->levels;
537   PC             cpc;
538   PetscBool      preonly,lu,redundant,cholesky,svd,dump = PETSC_FALSE,opsset,use_amat;
539   Mat            dA,dB;
540   MatStructure   uflag;
541   Vec            tvec;
542   DM             *dms;
543   PetscViewer    viewer = 0;
544 
545   PetscFunctionBegin;
546   /* FIX: Move this to PCSetFromOptions_MG? */
547   if (mg->usedmfornumberoflevels) {
548     PetscInt levels;
549     ierr = DMGetRefineLevel(pc->dm,&levels);CHKERRQ(ierr);
550     levels++;
551     if (levels > n) { /* the problem is now being solved on a finer grid */
552       ierr     = PCMGSetLevels(pc,levels,NULL);CHKERRQ(ierr);
553       n        = levels;
554       ierr     = PCSetFromOptions(pc);CHKERRQ(ierr); /* it is bad to call this here, but otherwise will never be called for the new hierarchy */
555       mglevels =  mg->levels;
556     }
557   }
558   ierr = KSPGetPC(mglevels[0]->smoothd,&cpc);CHKERRQ(ierr);
559 
560 
561   /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */
562   /* so use those from global PC */
563   /* Is this what we always want? What if user wants to keep old one? */
564   ierr = KSPGetOperatorsSet(mglevels[n-1]->smoothd,NULL,&opsset);CHKERRQ(ierr);
565   if (opsset) {
566     Mat mmat;
567     ierr = KSPGetOperators(mglevels[n-1]->smoothd,NULL,&mmat,NULL);CHKERRQ(ierr);
568     if (mmat == pc->pmat) opsset = PETSC_FALSE;
569   }
570   ierr = PCGetUseAmat(pc,&use_amat);CHKERRQ(ierr);
571   if (!opsset && use_amat) {
572     ierr = PetscInfo(pc,"Using outer operators to define finest grid operator \n  because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");CHKERRQ(ierr);
573     ierr = KSPSetOperators(mglevels[n-1]->smoothd,pc->mat,pc->pmat,pc->flag);CHKERRQ(ierr);
574   }
575 
576   /* Skipping this for galerkin==2 (externally managed hierarchy such as ML and GAMG). Cleaner logic here would be great. Wrap ML/GAMG as DMs? */
577   if (pc->dm && mg->galerkin != 2 && !pc->setupcalled) {
578     /* construct the interpolation from the DMs */
579     Mat p;
580     Vec rscale;
581     ierr     = PetscMalloc(n*sizeof(DM),&dms);CHKERRQ(ierr);
582     dms[n-1] = pc->dm;
583     for (i=n-2; i>-1; i--) {
584       DMKSP kdm;
585       ierr = DMCoarsen(dms[i+1],MPI_COMM_NULL,&dms[i]);CHKERRQ(ierr);
586       ierr = KSPSetDM(mglevels[i]->smoothd,dms[i]);CHKERRQ(ierr);
587       if (mg->galerkin) {ierr = KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);CHKERRQ(ierr);}
588       ierr = DMGetDMKSPWrite(dms[i],&kdm);CHKERRQ(ierr);
589       /* Ugly hack so that the next KSPSetUp() will use the RHS that we set. A better fix is to change dmActive to take
590        * a bitwise OR of computing the matrix, RHS, and initial iterate. */
591       kdm->ops->computerhs = NULL;
592       kdm->rhsctx          = NULL;
593       if (!mglevels[i+1]->interpolate) {
594         ierr = DMCreateInterpolation(dms[i],dms[i+1],&p,&rscale);CHKERRQ(ierr);
595         ierr = PCMGSetInterpolation(pc,i+1,p);CHKERRQ(ierr);
596         if (rscale) {ierr = PCMGSetRScale(pc,i+1,rscale);CHKERRQ(ierr);}
597         ierr = VecDestroy(&rscale);CHKERRQ(ierr);
598         ierr = MatDestroy(&p);CHKERRQ(ierr);
599       }
600     }
601 
602     for (i=n-2; i>-1; i--) {
603       ierr = DMDestroy(&dms[i]);CHKERRQ(ierr);
604     }
605     ierr = PetscFree(dms);CHKERRQ(ierr);
606   }
607 
608   if (pc->dm && !pc->setupcalled) {
609     /* finest smoother also gets DM but it is not active, independent of whether galerkin==2 */
610     ierr = KSPSetDM(mglevels[n-1]->smoothd,pc->dm);CHKERRQ(ierr);
611     ierr = KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);CHKERRQ(ierr);
612   }
613 
614   if (mg->galerkin == 1) {
615     Mat B;
616     /* currently only handle case where mat and pmat are the same on coarser levels */
617     ierr = KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr);
618     if (!pc->setupcalled) {
619       for (i=n-2; i>-1; i--) {
620         ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr);
621         ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
622         if (i != n-2) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);}
623         dB = B;
624       }
625       if (n > 1) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);}
626     } else {
627       for (i=n-2; i>-1; i--) {
628         ierr = KSPGetOperators(mglevels[i]->smoothd,NULL,&B,NULL);CHKERRQ(ierr);
629         ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr);
630         ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
631         dB   = B;
632       }
633     }
634   } else if (!mg->galerkin && pc->dm && pc->dm->x) {
635     /* need to restrict Jacobian location to coarser meshes for evaluation */
636     for (i=n-2; i>-1; i--) {
637       Mat R;
638       Vec rscale;
639       if (!mglevels[i]->smoothd->dm->x) {
640         Vec *vecs;
641         ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vecs,0,NULL);CHKERRQ(ierr);
642 
643         mglevels[i]->smoothd->dm->x = vecs[0];
644 
645         ierr = PetscFree(vecs);CHKERRQ(ierr);
646       }
647       ierr = PCMGGetRestriction(pc,i+1,&R);CHKERRQ(ierr);
648       ierr = PCMGGetRScale(pc,i+1,&rscale);CHKERRQ(ierr);
649       ierr = MatRestrict(R,mglevels[i+1]->smoothd->dm->x,mglevels[i]->smoothd->dm->x);CHKERRQ(ierr);
650       ierr = VecPointwiseMult(mglevels[i]->smoothd->dm->x,mglevels[i]->smoothd->dm->x,rscale);CHKERRQ(ierr);
651     }
652   }
653   if (!mg->galerkin && pc->dm) {
654     for (i=n-2; i>=0; i--) {
655       DM  dmfine,dmcoarse;
656       Mat Restrict,Inject;
657       Vec rscale;
658       ierr   = KSPGetDM(mglevels[i+1]->smoothd,&dmfine);CHKERRQ(ierr);
659       ierr   = KSPGetDM(mglevels[i]->smoothd,&dmcoarse);CHKERRQ(ierr);
660       ierr   = PCMGGetRestriction(pc,i+1,&Restrict);CHKERRQ(ierr);
661       ierr   = PCMGGetRScale(pc,i+1,&rscale);CHKERRQ(ierr);
662       Inject = NULL;      /* Callback should create it if it needs Injection */
663       ierr   = DMRestrict(dmfine,Restrict,rscale,Inject,dmcoarse);CHKERRQ(ierr);
664     }
665   }
666 
667   if (!pc->setupcalled) {
668     for (i=0; i<n; i++) {
669       ierr = KSPSetFromOptions(mglevels[i]->smoothd);CHKERRQ(ierr);
670     }
671     for (i=1; i<n; i++) {
672       if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) {
673         ierr = KSPSetFromOptions(mglevels[i]->smoothu);CHKERRQ(ierr);
674       }
675     }
676     for (i=1; i<n; i++) {
677       ierr = PCMGGetInterpolation(pc,i,&mglevels[i]->interpolate);CHKERRQ(ierr);
678       ierr = PCMGGetRestriction(pc,i,&mglevels[i]->restrct);CHKERRQ(ierr);
679     }
680     for (i=0; i<n-1; i++) {
681       if (!mglevels[i]->b) {
682         Vec *vec;
683         ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vec,0,NULL);CHKERRQ(ierr);
684         ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr);
685         ierr = VecDestroy(vec);CHKERRQ(ierr);
686         ierr = PetscFree(vec);CHKERRQ(ierr);
687       }
688       if (!mglevels[i]->r && i) {
689         ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr);
690         ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr);
691         ierr = VecDestroy(&tvec);CHKERRQ(ierr);
692       }
693       if (!mglevels[i]->x) {
694         ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr);
695         ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr);
696         ierr = VecDestroy(&tvec);CHKERRQ(ierr);
697       }
698     }
699     if (n != 1 && !mglevels[n-1]->r) {
700       /* PCMGSetR() on the finest level if user did not supply it */
701       Vec *vec;
702       ierr = KSPGetVecs(mglevels[n-1]->smoothd,1,&vec,0,NULL);CHKERRQ(ierr);
703       ierr = PCMGSetR(pc,n-1,*vec);CHKERRQ(ierr);
704       ierr = VecDestroy(vec);CHKERRQ(ierr);
705       ierr = PetscFree(vec);CHKERRQ(ierr);
706     }
707   }
708 
709   if (pc->dm) {
710     /* need to tell all the coarser levels to rebuild the matrix using the DM for that level */
711     for (i=0; i<n-1; i++) {
712       if (mglevels[i]->smoothd->setupstage != KSP_SETUP_NEW) mglevels[i]->smoothd->setupstage = KSP_SETUP_NEWMATRIX;
713     }
714   }
715 
716   for (i=1; i<n; i++) {
717     if (mglevels[i]->smoothu == mglevels[i]->smoothd) {
718       /* if doing only down then initial guess is zero */
719       ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr);
720     }
721     if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
722     ierr = KSPSetUp(mglevels[i]->smoothd);CHKERRQ(ierr);
723     if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
724     if (!mglevels[i]->residual) {
725       Mat mat;
726       ierr = KSPGetOperators(mglevels[i]->smoothd,NULL,&mat,NULL);CHKERRQ(ierr);
727       ierr = PCMGSetResidual(pc,i,PCMGResidual_Default,mat);CHKERRQ(ierr);
728     }
729   }
730   for (i=1; i<n; i++) {
731     if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) {
732       Mat          downmat,downpmat;
733       MatStructure matflag;
734 
735       /* check if operators have been set for up, if not use down operators to set them */
736       ierr = KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,NULL);CHKERRQ(ierr);
737       if (!opsset) {
738         ierr = KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat,&matflag);CHKERRQ(ierr);
739         ierr = KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr);
740       }
741 
742       ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr);
743       if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
744       ierr = KSPSetUp(mglevels[i]->smoothu);CHKERRQ(ierr);
745       if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
746     }
747   }
748 
749   /*
750       If coarse solver is not direct method then DO NOT USE preonly
751   */
752   ierr = PetscObjectTypeCompare((PetscObject)mglevels[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr);
753   if (preonly) {
754     ierr = PetscObjectTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr);
755     ierr = PetscObjectTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr);
756     ierr = PetscObjectTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr);
757     ierr = PetscObjectTypeCompare((PetscObject)cpc,PCSVD,&svd);CHKERRQ(ierr);
758     if (!lu && !redundant && !cholesky && !svd) {
759       ierr = KSPSetType(mglevels[0]->smoothd,KSPGMRES);CHKERRQ(ierr);
760     }
761   }
762 
763   if (!pc->setupcalled) {
764     ierr = KSPSetFromOptions(mglevels[0]->smoothd);CHKERRQ(ierr);
765   }
766 
767   if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
768   ierr = KSPSetUp(mglevels[0]->smoothd);CHKERRQ(ierr);
769   if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
770 
771   /*
772      Dump the interpolation/restriction matrices plus the
773    Jacobian/stiffness on each level. This allows MATLAB users to
774    easily check if the Galerkin condition A_c = R A_f R^T is satisfied.
775 
776    Only support one or the other at the same time.
777   */
778 #if defined(PETSC_USE_SOCKET_VIEWER)
779   ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,NULL);CHKERRQ(ierr);
780   if (dump) viewer = PETSC_VIEWER_SOCKET_(PetscObjectComm((PetscObject)pc));
781   dump = PETSC_FALSE;
782 #endif
783   ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,NULL);CHKERRQ(ierr);
784   if (dump) viewer = PETSC_VIEWER_BINARY_(PetscObjectComm((PetscObject)pc));
785 
786   if (viewer) {
787     for (i=1; i<n; i++) {
788       ierr = MatView(mglevels[i]->restrct,viewer);CHKERRQ(ierr);
789     }
790     for (i=0; i<n; i++) {
791       ierr = KSPGetPC(mglevels[i]->smoothd,&pc);CHKERRQ(ierr);
792       ierr = MatView(pc->mat,viewer);CHKERRQ(ierr);
793     }
794   }
795   PetscFunctionReturn(0);
796 }
797 
798 /* -------------------------------------------------------------------------------------*/
799 
800 #undef __FUNCT__
801 #define __FUNCT__ "PCMGGetLevels"
802 /*@
803    PCMGGetLevels - Gets the number of levels to use with MG.
804 
805    Not Collective
806 
807    Input Parameter:
808 .  pc - the preconditioner context
809 
810    Output parameter:
811 .  levels - the number of levels
812 
813    Level: advanced
814 
815 .keywords: MG, get, levels, multigrid
816 
817 .seealso: PCMGSetLevels()
818 @*/
819 PetscErrorCode  PCMGGetLevels(PC pc,PetscInt *levels)
820 {
821   PC_MG *mg = (PC_MG*)pc->data;
822 
823   PetscFunctionBegin;
824   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
825   PetscValidIntPointer(levels,2);
826   *levels = mg->nlevels;
827   PetscFunctionReturn(0);
828 }
829 
830 #undef __FUNCT__
831 #define __FUNCT__ "PCMGSetType"
832 /*@
833    PCMGSetType - Determines the form of multigrid to use:
834    multiplicative, additive, full, or the Kaskade algorithm.
835 
836    Logically Collective on PC
837 
838    Input Parameters:
839 +  pc - the preconditioner context
840 -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
841    PC_MG_FULL, PC_MG_KASKADE
842 
843    Options Database Key:
844 .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
845    additive, full, kaskade
846 
847    Level: advanced
848 
849 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid
850 
851 .seealso: PCMGSetLevels()
852 @*/
853 PetscErrorCode  PCMGSetType(PC pc,PCMGType form)
854 {
855   PC_MG *mg = (PC_MG*)pc->data;
856 
857   PetscFunctionBegin;
858   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
859   PetscValidLogicalCollectiveEnum(pc,form,2);
860   mg->am = form;
861   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
862   else pc->ops->applyrichardson = 0;
863   PetscFunctionReturn(0);
864 }
865 
866 #undef __FUNCT__
867 #define __FUNCT__ "PCMGSetCycleType"
868 /*@
869    PCMGSetCycleType - Sets the type cycles to use.  Use PCMGSetCycleTypeOnLevel() for more
870    complicated cycling.
871 
872    Logically Collective on PC
873 
874    Input Parameters:
875 +  pc - the multigrid context
876 -  PC_MG_CYCLE_V or PC_MG_CYCLE_W
877 
878    Options Database Key:
879 $  -pc_mg_cycle_type v or w
880 
881    Level: advanced
882 
883 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
884 
885 .seealso: PCMGSetCycleTypeOnLevel()
886 @*/
887 PetscErrorCode  PCMGSetCycleType(PC pc,PCMGCycleType n)
888 {
889   PC_MG        *mg        = (PC_MG*)pc->data;
890   PC_MG_Levels **mglevels = mg->levels;
891   PetscInt     i,levels;
892 
893   PetscFunctionBegin;
894   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
895   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
896   PetscValidLogicalCollectiveInt(pc,n,2);
897   levels = mglevels[0]->levels;
898 
899   for (i=0; i<levels; i++) mglevels[i]->cycles = n;
900   PetscFunctionReturn(0);
901 }
902 
903 #undef __FUNCT__
904 #define __FUNCT__ "PCMGMultiplicativeSetCycles"
905 /*@
906    PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step
907          of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used
908 
909    Logically Collective on PC
910 
911    Input Parameters:
912 +  pc - the multigrid context
913 -  n - number of cycles (default is 1)
914 
915    Options Database Key:
916 $  -pc_mg_multiplicative_cycles n
917 
918    Level: advanced
919 
920    Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType()
921 
922 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
923 
924 .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
925 @*/
926 PetscErrorCode  PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
927 {
928   PC_MG        *mg        = (PC_MG*)pc->data;
929   PC_MG_Levels **mglevels = mg->levels;
930   PetscInt     i,levels;
931 
932   PetscFunctionBegin;
933   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
934   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
935   PetscValidLogicalCollectiveInt(pc,n,2);
936   levels = mglevels[0]->levels;
937 
938   for (i=0; i<levels; i++) mg->cyclesperpcapply = n;
939   PetscFunctionReturn(0);
940 }
941 
942 #undef __FUNCT__
943 #define __FUNCT__ "PCMGSetGalerkin"
944 /*@
945    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
946       finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t
947 
948    Logically Collective on PC
949 
950    Input Parameters:
951 +  pc - the multigrid context
952 -  use - PETSC_TRUE to use the Galerkin process to compute coarse-level operators
953 
954    Options Database Key:
955 $  -pc_mg_galerkin
956 
957    Level: intermediate
958 
959 .keywords: MG, set, Galerkin
960 
961 .seealso: PCMGGetGalerkin()
962 
963 @*/
964 PetscErrorCode PCMGSetGalerkin(PC pc,PetscBool use)
965 {
966   PC_MG *mg = (PC_MG*)pc->data;
967 
968   PetscFunctionBegin;
969   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
970   mg->galerkin = use ? 1 : 0;
971   PetscFunctionReturn(0);
972 }
973 
974 #undef __FUNCT__
975 #define __FUNCT__ "PCMGGetGalerkin"
976 /*@
977    PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
978       A_i-1 = r_i * A_i * r_i^t
979 
980    Not Collective
981 
982    Input Parameter:
983 .  pc - the multigrid context
984 
985    Output Parameter:
986 .  gelerkin - PETSC_TRUE or PETSC_FALSE
987 
988    Options Database Key:
989 $  -pc_mg_galerkin
990 
991    Level: intermediate
992 
993 .keywords: MG, set, Galerkin
994 
995 .seealso: PCMGSetGalerkin()
996 
997 @*/
998 PetscErrorCode  PCMGGetGalerkin(PC pc,PetscBool  *galerkin)
999 {
1000   PC_MG *mg = (PC_MG*)pc->data;
1001 
1002   PetscFunctionBegin;
1003   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
1004   *galerkin = (PetscBool)mg->galerkin;
1005   PetscFunctionReturn(0);
1006 }
1007 
1008 #undef __FUNCT__
1009 #define __FUNCT__ "PCMGSetNumberSmoothDown"
1010 /*@
1011    PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to
1012    use on all levels. Use PCMGGetSmootherDown() to set different
1013    pre-smoothing steps on different levels.
1014 
1015    Logically Collective on PC
1016 
1017    Input Parameters:
1018 +  mg - the multigrid context
1019 -  n - the number of smoothing steps
1020 
1021    Options Database Key:
1022 .  -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps
1023 
1024    Level: advanced
1025 
1026 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid
1027 
1028 .seealso: PCMGSetNumberSmoothUp()
1029 @*/
1030 PetscErrorCode  PCMGSetNumberSmoothDown(PC pc,PetscInt n)
1031 {
1032   PC_MG          *mg        = (PC_MG*)pc->data;
1033   PC_MG_Levels   **mglevels = mg->levels;
1034   PetscErrorCode ierr;
1035   PetscInt       i,levels;
1036 
1037   PetscFunctionBegin;
1038   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
1039   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1040   PetscValidLogicalCollectiveInt(pc,n,2);
1041   levels = mglevels[0]->levels;
1042 
1043   for (i=1; i<levels; i++) {
1044     /* make sure smoother up and down are different */
1045     ierr = PCMGGetSmootherUp(pc,i,NULL);CHKERRQ(ierr);
1046     ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
1047 
1048     mg->default_smoothd = n;
1049   }
1050   PetscFunctionReturn(0);
1051 }
1052 
1053 #undef __FUNCT__
1054 #define __FUNCT__ "PCMGSetNumberSmoothUp"
1055 /*@
1056    PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use
1057    on all levels. Use PCMGGetSmootherUp() to set different numbers of
1058    post-smoothing steps on different levels.
1059 
1060    Logically Collective on PC
1061 
1062    Input Parameters:
1063 +  mg - the multigrid context
1064 -  n - the number of smoothing steps
1065 
1066    Options Database Key:
1067 .  -pc_mg_smoothup <n> - Sets number of post-smoothing steps
1068 
1069    Level: advanced
1070 
1071    Note: this does not set a value on the coarsest grid, since we assume that
1072     there is no separate smooth up on the coarsest grid.
1073 
1074 .keywords: MG, smooth, up, post-smoothing, steps, multigrid
1075 
1076 .seealso: PCMGSetNumberSmoothDown()
1077 @*/
1078 PetscErrorCode  PCMGSetNumberSmoothUp(PC pc,PetscInt n)
1079 {
1080   PC_MG          *mg        = (PC_MG*)pc->data;
1081   PC_MG_Levels   **mglevels = mg->levels;
1082   PetscErrorCode ierr;
1083   PetscInt       i,levels;
1084 
1085   PetscFunctionBegin;
1086   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
1087   if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1088   PetscValidLogicalCollectiveInt(pc,n,2);
1089   levels = mglevels[0]->levels;
1090 
1091   for (i=1; i<levels; i++) {
1092     /* make sure smoother up and down are different */
1093     ierr = PCMGGetSmootherUp(pc,i,NULL);CHKERRQ(ierr);
1094     ierr = KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
1095 
1096     mg->default_smoothu = n;
1097   }
1098   PetscFunctionReturn(0);
1099 }
1100 
1101 /* ----------------------------------------------------------------------------------------*/
1102 
1103 /*MC
1104    PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional
1105     information about the coarser grid matrices and restriction/interpolation operators.
1106 
1107    Options Database Keys:
1108 +  -pc_mg_levels <nlevels> - number of levels including finest
1109 .  -pc_mg_cycles v or w
1110 .  -pc_mg_smoothup <n> - number of smoothing steps after interpolation
1111 .  -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator
1112 .  -pc_mg_type <additive,multiplicative,full,kaskade> - multiplicative is the default
1113 .  -pc_mg_log - log information about time spent on each level of the solver
1114 .  -pc_mg_monitor - print information on the multigrid convergence
1115 .  -pc_mg_galerkin - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R'
1116 .  -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1)
1117 .  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
1118                         to the Socket viewer for reading from MATLAB.
1119 -  -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices
1120                         to the binary output file called binaryoutput
1121 
1122    Notes: By default this uses GMRES on the fine grid smoother so this should be used with KSPFGMRES or the smoother changed to not use GMRES
1123 
1124        When run with a single level the smoother options are used on that level NOT the coarse grid solver options
1125 
1126    Level: intermediate
1127 
1128    Concepts: multigrid/multilevel
1129 
1130 .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE
1131            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(),
1132            PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
1133            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
1134            PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
1135 M*/
1136 
1137 #undef __FUNCT__
1138 #define __FUNCT__ "PCCreate_MG"
1139 PETSC_EXTERN PetscErrorCode PCCreate_MG(PC pc)
1140 {
1141   PC_MG          *mg;
1142   PetscErrorCode ierr;
1143 
1144   PetscFunctionBegin;
1145   ierr        = PetscNewLog(pc,PC_MG,&mg);CHKERRQ(ierr);
1146   pc->data    = (void*)mg;
1147   mg->nlevels = -1;
1148 
1149   pc->ops->apply          = PCApply_MG;
1150   pc->ops->setup          = PCSetUp_MG;
1151   pc->ops->reset          = PCReset_MG;
1152   pc->ops->destroy        = PCDestroy_MG;
1153   pc->ops->setfromoptions = PCSetFromOptions_MG;
1154   pc->ops->view           = PCView_MG;
1155   PetscFunctionReturn(0);
1156 }
1157