xref: /petsc/src/ksp/pc/impls/mg/mg.c (revision c88c5224601c4a9900c397283ffbc1685ca8c72c)
1 
2 /*
3     Defines the multigrid preconditioner interface.
4 */
5 #include <../src/ksp/pc/impls/mg/mgimpl.h>                    /*I "petscpcmg.h" I*/
6 
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 
19   if (mglevels->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
20   ierr = KSPSolve(mglevels->smoothd,mglevels->b,mglevels->x);CHKERRQ(ierr);  /* pre-smooth */
21   if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
22   if (mglevels->level) {  /* not the coarsest grid */
23     if (mglevels->eventresidual) {ierr = PetscLogEventBegin(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);}
24     ierr = (*mglevels->residual)(mglevels->A,mglevels->b,mglevels->x,mglevels->r);CHKERRQ(ierr);
25     if (mglevels->eventresidual) {ierr = PetscLogEventEnd(mglevels->eventresidual,0,0,0,0);CHKERRQ(ierr);}
26 
27     /* if on finest level and have convergence criteria set */
28     if (mglevels->level == mglevels->levels-1 && mg->ttol && reason) {
29       PetscReal rnorm;
30       ierr = VecNorm(mglevels->r,NORM_2,&rnorm);CHKERRQ(ierr);
31       if (rnorm <= mg->ttol) {
32         if (rnorm < mg->abstol) {
33           *reason = PCRICHARDSON_CONVERGED_ATOL;
34           ierr = PetscInfo2(pc,"Linear solver has converged. Residual norm %G is less than absolute tolerance %G\n",rnorm,mg->abstol);CHKERRQ(ierr);
35         } else {
36           *reason = PCRICHARDSON_CONVERGED_RTOL;
37           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);
38         }
39         PetscFunctionReturn(0);
40       }
41     }
42 
43     mgc = *(mglevelsin - 1);
44     if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
45     ierr = MatRestrict(mglevels->restrct,mglevels->r,mgc->b);CHKERRQ(ierr);
46     if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
47     ierr = VecSet(mgc->x,0.0);CHKERRQ(ierr);
48     while (cycles--) {
49       ierr = PCMGMCycle_Private(pc,mglevelsin-1,reason);CHKERRQ(ierr);
50     }
51     if (mglevels->eventinterprestrict) {ierr = PetscLogEventBegin(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
52     ierr = MatInterpolateAdd(mglevels->interpolate,mgc->x,mglevels->x,mglevels->x);CHKERRQ(ierr);
53     if (mglevels->eventinterprestrict) {ierr = PetscLogEventEnd(mglevels->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
54     if (mglevels->eventsmoothsolve) {ierr = PetscLogEventBegin(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
55     ierr = KSPSolve(mglevels->smoothu,mglevels->b,mglevels->x);CHKERRQ(ierr);    /* post smooth */
56     if (mglevels->eventsmoothsolve) {ierr = PetscLogEventEnd(mglevels->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
57   }
58   PetscFunctionReturn(0);
59 }
60 
61 #undef __FUNCT__
62 #define __FUNCT__ "PCApplyRichardson_MG"
63 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)
64 {
65   PC_MG          *mg = (PC_MG*)pc->data;
66   PC_MG_Levels   **mglevels = mg->levels;
67   PetscErrorCode ierr;
68   PetscInt       levels = mglevels[0]->levels,i;
69 
70   PetscFunctionBegin;
71   mglevels[levels-1]->b    = b;
72   mglevels[levels-1]->x    = x;
73 
74   mg->rtol = rtol;
75   mg->abstol = abstol;
76   mg->dtol = dtol;
77   if (rtol) {
78     /* compute initial residual norm for relative convergence test */
79     PetscReal rnorm;
80     if (zeroguess) {
81       ierr               = VecNorm(b,NORM_2,&rnorm);CHKERRQ(ierr);
82     } else {
83       ierr               = (*mglevels[levels-1]->residual)(mglevels[levels-1]->A,b,x,w);CHKERRQ(ierr);
84       ierr               = VecNorm(w,NORM_2,&rnorm);CHKERRQ(ierr);
85     }
86     mg->ttol = PetscMax(rtol*rnorm,abstol);
87   } else if (abstol) {
88     mg->ttol = abstol;
89   } else {
90     mg->ttol = 0.0;
91   }
92 
93   /* since smoother is applied to full system, not just residual we need to make sure that smoothers don't
94      stop prematurely do to small residual */
95   for (i=1; i<levels; i++) {
96     ierr = KSPSetTolerances(mglevels[i]->smoothu,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr);
97     if (mglevels[i]->smoothu != mglevels[i]->smoothd) {
98       ierr = KSPSetTolerances(mglevels[i]->smoothd,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr);
99     }
100   }
101 
102   *reason = (PCRichardsonConvergedReason)0;
103   for (i=0; i<its; i++) {
104     ierr = PCMGMCycle_Private(pc,mglevels+levels-1,reason);CHKERRQ(ierr);
105     if (*reason) break;
106   }
107   if (!*reason) *reason = PCRICHARDSON_CONVERGED_ITS;
108   *outits = i;
109   PetscFunctionReturn(0);
110 }
111 
112 #undef __FUNCT__
113 #define __FUNCT__ "PCReset_MG"
114 PetscErrorCode PCReset_MG(PC pc)
115 {
116   PC_MG          *mg = (PC_MG*)pc->data;
117   PC_MG_Levels   **mglevels = mg->levels;
118   PetscErrorCode ierr;
119   PetscInt       i,n;
120 
121   PetscFunctionBegin;
122   if (mglevels) {
123     n = mglevels[0]->levels;
124     for (i=0; i<n-1; i++) {
125       ierr = VecDestroy(&mglevels[i+1]->r);CHKERRQ(ierr);
126       ierr = VecDestroy(&mglevels[i]->b);CHKERRQ(ierr);
127       ierr = VecDestroy(&mglevels[i]->x);CHKERRQ(ierr);
128       ierr = MatDestroy(&mglevels[i+1]->restrct);CHKERRQ(ierr);
129       ierr = MatDestroy(&mglevels[i+1]->interpolate);CHKERRQ(ierr);
130       ierr = VecDestroy(&mglevels[i+1]->rscale);CHKERRQ(ierr);
131     }
132 
133     for (i=0; i<n; i++) {
134       ierr = MatDestroy(&mglevels[i]->A);CHKERRQ(ierr);
135       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
136 	ierr = KSPReset(mglevels[i]->smoothd);CHKERRQ(ierr);
137       }
138       ierr = KSPReset(mglevels[i]->smoothu);CHKERRQ(ierr);
139     }
140   }
141   PetscFunctionReturn(0);
142 }
143 
144 #undef __FUNCT__
145 #define __FUNCT__ "PCMGSetLevels"
146 /*@C
147    PCMGSetLevels - Sets the number of levels to use with MG.
148    Must be called before any other MG routine.
149 
150    Logically Collective on PC
151 
152    Input Parameters:
153 +  pc - the preconditioner context
154 .  levels - the number of levels
155 -  comms - optional communicators for each level; this is to allow solving the coarser problems
156            on smaller sets of processors. Use PETSC_NULL_OBJECT for default in Fortran
157 
158    Level: intermediate
159 
160    Notes:
161      If the number of levels is one then the multigrid uses the -mg_levels prefix
162   for setting the level options rather than the -mg_coarse prefix.
163 
164 .keywords: MG, set, levels, multigrid
165 
166 .seealso: PCMGSetType(), PCMGGetLevels()
167 @*/
168 PetscErrorCode  PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
169 {
170   PetscErrorCode ierr;
171   PC_MG          *mg = (PC_MG*)pc->data;
172   MPI_Comm       comm = ((PetscObject)pc)->comm;
173   PC_MG_Levels   **mglevels = mg->levels;
174   PetscInt       i;
175   PetscMPIInt    size;
176   const char     *prefix;
177   PC             ipc;
178   PetscInt       n;
179 
180   PetscFunctionBegin;
181   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
182   PetscValidLogicalCollectiveInt(pc,levels,2);
183   if (mg->nlevels == levels) PetscFunctionReturn(0);
184   if (mglevels) {
185     /* changing the number of levels so free up the previous stuff */
186     ierr = PCReset_MG(pc);CHKERRQ(ierr);
187     n = mglevels[0]->levels;
188     for (i=0; i<n; i++) {
189       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
190 	ierr = KSPDestroy(&mglevels[i]->smoothd);CHKERRQ(ierr);
191       }
192       ierr = KSPDestroy(&mglevels[i]->smoothu);CHKERRQ(ierr);
193       ierr = PetscFree(mglevels[i]);CHKERRQ(ierr);
194     }
195     ierr = PetscFree(mg->levels);CHKERRQ(ierr);
196   }
197 
198   mg->nlevels      = levels;
199 
200   ierr = PetscMalloc(levels*sizeof(PC_MG*),&mglevels);CHKERRQ(ierr);
201   ierr = PetscLogObjectMemory(pc,levels*(sizeof(PC_MG*)));CHKERRQ(ierr);
202 
203   ierr = PCGetOptionsPrefix(pc,&prefix);CHKERRQ(ierr);
204 
205   for (i=0; i<levels; i++) {
206     ierr = PetscNewLog(pc,PC_MG_Levels,&mglevels[i]);CHKERRQ(ierr);
207     mglevels[i]->level           = i;
208     mglevels[i]->levels          = levels;
209     mglevels[i]->cycles          = PC_MG_CYCLE_V;
210     mg->default_smoothu = 1;
211     mg->default_smoothd = 1;
212     mglevels[i]->eventsmoothsetup    = 0;
213     mglevels[i]->eventsmoothsolve    = 0;
214     mglevels[i]->eventresidual       = 0;
215     mglevels[i]->eventinterprestrict = 0;
216 
217     if (comms) comm = comms[i];
218     ierr = KSPCreate(comm,&mglevels[i]->smoothd);CHKERRQ(ierr);
219     ierr = PetscObjectIncrementTabLevel((PetscObject)mglevels[i]->smoothd,(PetscObject)pc,levels-i);CHKERRQ(ierr);
220     ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, mg->default_smoothd);CHKERRQ(ierr);
221     ierr = KSPSetOptionsPrefix(mglevels[i]->smoothd,prefix);CHKERRQ(ierr);
222 
223     /* do special stuff for coarse grid */
224     if (!i && levels > 1) {
225       ierr = KSPAppendOptionsPrefix(mglevels[0]->smoothd,"mg_coarse_");CHKERRQ(ierr);
226 
227       /* coarse solve is (redundant) LU by default */
228       ierr = KSPSetType(mglevels[0]->smoothd,KSPPREONLY);CHKERRQ(ierr);
229       ierr = KSPGetPC(mglevels[0]->smoothd,&ipc);CHKERRQ(ierr);
230       ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
231       if (size > 1) {
232         ierr = PCSetType(ipc,PCREDUNDANT);CHKERRQ(ierr);
233       } else {
234         ierr = PCSetType(ipc,PCLU);CHKERRQ(ierr);
235       }
236 
237     } else {
238       char tprefix[128];
239       sprintf(tprefix,"mg_levels_%d_",(int)i);
240       ierr = KSPAppendOptionsPrefix(mglevels[i]->smoothd,tprefix);CHKERRQ(ierr);
241     }
242     ierr = PetscLogObjectParent(pc,mglevels[i]->smoothd);CHKERRQ(ierr);
243     mglevels[i]->smoothu    = mglevels[i]->smoothd;
244     mg->rtol                = 0.0;
245     mg->abstol              = 0.0;
246     mg->dtol                = 0.0;
247     mg->ttol                = 0.0;
248     mg->cyclesperpcapply    = 1;
249   }
250   mg->am          = PC_MG_MULTIPLICATIVE;
251   mg->levels      = mglevels;
252   pc->ops->applyrichardson = PCApplyRichardson_MG;
253   PetscFunctionReturn(0);
254 }
255 
256 
257 #undef __FUNCT__
258 #define __FUNCT__ "PCDestroy_MG"
259 PetscErrorCode PCDestroy_MG(PC pc)
260 {
261   PetscErrorCode ierr;
262   PC_MG          *mg = (PC_MG*)pc->data;
263   PC_MG_Levels   **mglevels = mg->levels;
264   PetscInt       i,n;
265 
266   PetscFunctionBegin;
267   ierr = PCReset_MG(pc);CHKERRQ(ierr);
268   if (mglevels) {
269     n = mglevels[0]->levels;
270     for (i=0; i<n; i++) {
271       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
272 	ierr = KSPDestroy(&mglevels[i]->smoothd);CHKERRQ(ierr);
273       }
274       ierr = KSPDestroy(&mglevels[i]->smoothu);CHKERRQ(ierr);
275       ierr = PetscFree(mglevels[i]);CHKERRQ(ierr);
276     }
277     ierr = PetscFree(mg->levels);CHKERRQ(ierr);
278   }
279   ierr = PetscFree(pc->data);CHKERRQ(ierr);
280   PetscFunctionReturn(0);
281 }
282 
283 
284 
285 extern PetscErrorCode PCMGACycle_Private(PC,PC_MG_Levels**);
286 extern PetscErrorCode PCMGFCycle_Private(PC,PC_MG_Levels**);
287 extern PetscErrorCode PCMGKCycle_Private(PC,PC_MG_Levels**);
288 
289 /*
290    PCApply_MG - Runs either an additive, multiplicative, Kaskadic
291              or full cycle of multigrid.
292 
293   Note:
294   A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle().
295 */
296 #undef __FUNCT__
297 #define __FUNCT__ "PCApply_MG"
298 static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
299 {
300   PC_MG          *mg = (PC_MG*)pc->data;
301   PC_MG_Levels   **mglevels = mg->levels;
302   PetscErrorCode ierr;
303   PetscInt       levels = mglevels[0]->levels,i;
304 
305   PetscFunctionBegin;
306 
307   /* When the DM is supplying the matrix then it will not exist until here */
308   for (i=0; i<levels; i++) {
309     if (!mglevels[i]->A) {
310       ierr = KSPGetOperators(mglevels[i]->smoothu,&mglevels[i]->A,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr);
311       ierr = PetscObjectReference((PetscObject)mglevels[i]->A);CHKERRQ(ierr);
312     }
313   }
314 
315   mglevels[levels-1]->b = b;
316   mglevels[levels-1]->x = x;
317   if (mg->am == PC_MG_MULTIPLICATIVE) {
318     ierr = VecSet(x,0.0);CHKERRQ(ierr);
319     for (i=0; i<mg->cyclesperpcapply; i++) {
320       ierr = PCMGMCycle_Private(pc,mglevels+levels-1,PETSC_NULL);CHKERRQ(ierr);
321     }
322   }
323   else if (mg->am == PC_MG_ADDITIVE) {
324     ierr = PCMGACycle_Private(pc,mglevels);CHKERRQ(ierr);
325   }
326   else if (mg->am == PC_MG_KASKADE) {
327     ierr = PCMGKCycle_Private(pc,mglevels);CHKERRQ(ierr);
328   }
329   else {
330     ierr = PCMGFCycle_Private(pc,mglevels);CHKERRQ(ierr);
331   }
332   PetscFunctionReturn(0);
333 }
334 
335 
336 #undef __FUNCT__
337 #define __FUNCT__ "PCSetFromOptions_MG"
338 PetscErrorCode PCSetFromOptions_MG(PC pc)
339 {
340   PetscErrorCode ierr;
341   PetscInt       m,levels = 1,cycles;
342   PetscBool      flg,set;
343   PC_MG          *mg = (PC_MG*)pc->data;
344   PC_MG_Levels   **mglevels = mg->levels;
345   PCMGType       mgtype;
346   PCMGCycleType  mgctype;
347 
348   PetscFunctionBegin;
349   ierr = PetscOptionsHead("Multigrid options");CHKERRQ(ierr);
350     if (!mg->levels) {
351       ierr = PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);CHKERRQ(ierr);
352       if (!flg && pc->dm) {
353         ierr = DMGetRefineLevel(pc->dm,&levels);CHKERRQ(ierr);
354         levels++;
355         mg->usedmfornumberoflevels = PETSC_TRUE;
356       }
357       ierr = PCMGSetLevels(pc,levels,PETSC_NULL);CHKERRQ(ierr);
358     }
359     mglevels = mg->levels;
360 
361     mgctype = (PCMGCycleType) mglevels[0]->cycles;
362     ierr = PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);CHKERRQ(ierr);
363     if (flg) {
364       ierr = PCMGSetCycleType(pc,mgctype);CHKERRQ(ierr);
365     };
366     flg  = PETSC_FALSE;
367     ierr = PetscOptionsBool("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",flg,&flg,&set);CHKERRQ(ierr);
368     if (set) {
369       ierr = PCMGSetGalerkin(pc,flg);CHKERRQ(ierr);
370     }
371     ierr = PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",1,&m,&flg);CHKERRQ(ierr);
372     if (flg) {
373       ierr = PCMGSetNumberSmoothUp(pc,m);CHKERRQ(ierr);
374     }
375     ierr = PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",1,&m,&flg);CHKERRQ(ierr);
376     if (flg) {
377       ierr = PCMGSetNumberSmoothDown(pc,m);CHKERRQ(ierr);
378     }
379     mgtype = mg->am;
380     ierr = PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);CHKERRQ(ierr);
381     if (flg) {
382       ierr = PCMGSetType(pc,mgtype);CHKERRQ(ierr);
383     }
384     if (mg->am == PC_MG_MULTIPLICATIVE) {
385       ierr = PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGSetLevels",mg->cyclesperpcapply,&cycles,&flg);CHKERRQ(ierr);
386       if (flg) {
387 	ierr = PCMGMultiplicativeSetCycles(pc,cycles);CHKERRQ(ierr);
388       }
389     }
390     flg  = PETSC_FALSE;
391     ierr = PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,PETSC_NULL);CHKERRQ(ierr);
392     if (flg) {
393       PetscInt i;
394       char     eventname[128];
395       if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
396       levels = mglevels[0]->levels;
397       for (i=0; i<levels; i++) {
398         sprintf(eventname,"MGSetup Level %d",(int)i);
399         ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);CHKERRQ(ierr);
400         sprintf(eventname,"MGSmooth Level %d",(int)i);
401         ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);CHKERRQ(ierr);
402         if (i) {
403           sprintf(eventname,"MGResid Level %d",(int)i);
404           ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);CHKERRQ(ierr);
405           sprintf(eventname,"MGInterp Level %d",(int)i);
406           ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);CHKERRQ(ierr);
407         }
408       }
409     }
410   ierr = PetscOptionsTail();CHKERRQ(ierr);
411   PetscFunctionReturn(0);
412 }
413 
414 const char *PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0};
415 const char *PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",0};
416 
417 #undef __FUNCT__
418 #define __FUNCT__ "PCView_MG"
419 PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
420 {
421   PC_MG          *mg = (PC_MG*)pc->data;
422   PC_MG_Levels   **mglevels = mg->levels;
423   PetscErrorCode ierr;
424   PetscInt       levels = mglevels[0]->levels,i;
425   PetscBool      iascii;
426 
427   PetscFunctionBegin;
428   ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
429   if (iascii) {
430     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);
431     if (mg->am == PC_MG_MULTIPLICATIVE) {
432       ierr = PetscViewerASCIIPrintf(viewer,"    Cycles per PCApply=%d\n",mg->cyclesperpcapply);CHKERRQ(ierr);
433     }
434     if (mg->galerkin) {
435       ierr = PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr);
436     } else {
437       ierr = PetscViewerASCIIPrintf(viewer,"    Not using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr);
438     }
439     for (i=0; i<levels; i++) {
440       if (!i) {
441         ierr = PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level -------------------------------\n",i);CHKERRQ(ierr);
442       } else {
443         ierr = PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr);
444       }
445       ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
446       ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr);
447       ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
448       if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) {
449         ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");CHKERRQ(ierr);
450       } else if (i){
451         ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr);
452         ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
453         ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr);
454         ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
455       }
456     }
457   } else SETERRQ1(((PetscObject)pc)->comm,PETSC_ERR_SUP,"Viewer type %s not supported for PCMG",((PetscObject)viewer)->type_name);
458   PetscFunctionReturn(0);
459 }
460 
461 #include <private/dmimpl.h>
462 #include <private/kspimpl.h>
463 
464 /*
465     Calls setup for the KSP on each level
466 */
467 #undef __FUNCT__
468 #define __FUNCT__ "PCSetUp_MG"
469 PetscErrorCode PCSetUp_MG(PC pc)
470 {
471   PC_MG                   *mg = (PC_MG*)pc->data;
472   PC_MG_Levels            **mglevels = mg->levels;
473   PetscErrorCode          ierr;
474   PetscInt                i,n = mglevels[0]->levels;
475   PC                      cpc,mpc;
476   PetscBool               preonly,lu,redundant,cholesky,svd,dump = PETSC_FALSE,opsset;
477   Mat                     dA,dB;
478   MatStructure            uflag;
479   Vec                     tvec;
480   DM                      *dms;
481   PetscViewer             viewer = 0;
482 
483   PetscFunctionBegin;
484   if (mg->usedmfornumberoflevels) {
485     PetscInt levels;
486     ierr = DMGetRefineLevel(pc->dm,&levels);CHKERRQ(ierr);
487     levels++;
488     if (levels > n) { /* the problem is now being solved on a finer grid */
489       ierr = PCMGSetLevels(pc,levels,PETSC_NULL);CHKERRQ(ierr);
490       n    = levels;
491       ierr = PCSetFromOptions(pc);CHKERRQ(ierr);  /* it is bad to call this here, but otherwise will never be called for the new hierarchy */
492       mglevels =  mg->levels;
493     }
494   }
495 
496 
497   /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */
498   /* so use those from global PC */
499   /* Is this what we always want? What if user wants to keep old one? */
500   ierr = KSPGetOperatorsSet(mglevels[n-1]->smoothd,PETSC_NULL,&opsset);CHKERRQ(ierr);
501   ierr = KSPGetPC(mglevels[0]->smoothd,&cpc);CHKERRQ(ierr);
502   ierr = KSPGetPC(mglevels[n-1]->smoothd,&mpc);CHKERRQ(ierr);
503   if (!opsset || ((cpc->setupcalled == 1) && (mpc->setupcalled == 2)) || ((mpc == cpc) && (mpc->setupcalled == 2))) {
504     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);
505     ierr = KSPSetOperators(mglevels[n-1]->smoothd,pc->mat,pc->pmat,pc->flag);CHKERRQ(ierr);
506   }
507 
508   if (pc->dm && !pc->setupcalled) {
509     /* construct the interpolation from the DMs */
510     Mat p;
511     Vec rscale;
512     ierr = PetscMalloc(n*sizeof(DM),&dms);CHKERRQ(ierr);
513     dms[n-1] = pc->dm;
514     for (i=n-2; i>-1; i--) {
515       ierr = DMCoarsen(dms[i+1],PETSC_NULL,&dms[i]);CHKERRQ(ierr);
516       ierr = KSPSetDM(mglevels[i]->smoothd,dms[i]);CHKERRQ(ierr);
517       if (mg->galerkin) {ierr = KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);CHKERRQ(ierr);}
518       ierr = DMSetFunction(dms[i],0);
519       ierr = DMSetInitialGuess(dms[i],0);
520       if (!mglevels[i+1]->interpolate) {
521 	ierr = DMCreateInterpolation(dms[i],dms[i+1],&p,&rscale);CHKERRQ(ierr);
522 	ierr = PCMGSetInterpolation(pc,i+1,p);CHKERRQ(ierr);
523 	if (rscale) {ierr = PCMGSetRScale(pc,i+1,rscale);CHKERRQ(ierr);}
524         ierr = VecDestroy(&rscale);CHKERRQ(ierr);
525         ierr = MatDestroy(&p);CHKERRQ(ierr);
526       }
527     }
528 
529     for (i=n-2; i>-1; i--) {
530       ierr = DMDestroy(&dms[i]);CHKERRQ(ierr);
531     }
532     ierr = PetscFree(dms);CHKERRQ(ierr);
533 
534     /* finest smoother also gets DM but it is not active */
535     ierr = KSPSetDM(mglevels[n-1]->smoothd,pc->dm);CHKERRQ(ierr);
536     ierr = KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);CHKERRQ(ierr);
537   }
538 
539   if (mg->galerkin == 1) {
540     Mat B;
541     /* currently only handle case where mat and pmat are the same on coarser levels */
542     ierr = KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr);
543     if (!pc->setupcalled) {
544       for (i=n-2; i>-1; i--) {
545         ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr);
546         ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
547 	if (i != n-2) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);}
548         dB   = B;
549       }
550       if (n > 1) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);}
551     } else {
552       for (i=n-2; i>-1; i--) {
553         ierr = KSPGetOperators(mglevels[i]->smoothd,PETSC_NULL,&B,PETSC_NULL);CHKERRQ(ierr);
554         ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr);
555         ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
556         dB   = B;
557       }
558     }
559   } else if (pc->dm && pc->dm->x) {
560     /* need to restrict Jacobian location to coarser meshes for evaluation */
561     for (i=n-2;i>-1; i--) {
562       Mat R;
563       Vec rscale;
564       if (!mglevels[i]->smoothd->dm->x) {
565         Vec *vecs;
566         ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vecs,0,PETSC_NULL);CHKERRQ(ierr);
567         mglevels[i]->smoothd->dm->x = vecs[0];
568         ierr = PetscFree(vecs);CHKERRQ(ierr);
569       }
570       ierr = PCMGGetRestriction(pc,i+1,&R);CHKERRQ(ierr);
571       ierr = PCMGGetRScale(pc,i+1,&rscale);CHKERRQ(ierr);
572       ierr = MatRestrict(R,mglevels[i+1]->smoothd->dm->x,mglevels[i]->smoothd->dm->x);CHKERRQ(ierr);
573       ierr = VecPointwiseMult(mglevels[i]->smoothd->dm->x,mglevels[i]->smoothd->dm->x,rscale);CHKERRQ(ierr);
574     }
575   }
576 
577   if (!pc->setupcalled) {
578     for (i=0; i<n; i++) {
579       ierr = KSPSetFromOptions(mglevels[i]->smoothd);CHKERRQ(ierr);
580     }
581     for (i=1; i<n; i++) {
582       if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) {
583         ierr = KSPSetFromOptions(mglevels[i]->smoothu);CHKERRQ(ierr);
584       }
585     }
586     for (i=1; i<n; i++) {
587       ierr = PCMGGetInterpolation(pc,i,&mglevels[i]->interpolate);CHKERRQ(ierr);
588       ierr = PCMGGetRestriction(pc,i,&mglevels[i]->restrct);CHKERRQ(ierr);
589     }
590     for (i=0; i<n-1; i++) {
591       if (!mglevels[i]->b) {
592         Vec *vec;
593         ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr);
594         ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr);
595         ierr = VecDestroy(vec);CHKERRQ(ierr);
596         ierr = PetscFree(vec);CHKERRQ(ierr);
597       }
598       if (!mglevels[i]->r && i) {
599         ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr);
600         ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr);
601         ierr = VecDestroy(&tvec);CHKERRQ(ierr);
602       }
603       if (!mglevels[i]->x) {
604         ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr);
605         ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr);
606         ierr = VecDestroy(&tvec);CHKERRQ(ierr);
607       }
608     }
609     if (n != 1 && !mglevels[n-1]->r) {
610       /* PCMGSetR() on the finest level if user did not supply it */
611       Vec *vec;
612       ierr = KSPGetVecs(mglevels[n-1]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr);
613       ierr = PCMGSetR(pc,n-1,*vec);CHKERRQ(ierr);
614       ierr = VecDestroy(vec);CHKERRQ(ierr);
615       ierr = PetscFree(vec);CHKERRQ(ierr);
616     }
617   }
618 
619 
620   for (i=1; i<n; i++) {
621     if (mglevels[i]->smoothu == mglevels[i]->smoothd) {
622       /* if doing only down then initial guess is zero */
623       ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr);
624     }
625     if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
626     ierr = KSPSetUp(mglevels[i]->smoothd);CHKERRQ(ierr);
627     if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
628     if (!mglevels[i]->residual) {
629       Mat mat;
630       ierr = KSPGetOperators(mglevels[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);CHKERRQ(ierr);
631       ierr = PCMGSetResidual(pc,i,PCMGDefaultResidual,mat);CHKERRQ(ierr);
632     }
633   }
634   for (i=1; i<n; i++) {
635     if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) {
636       Mat          downmat,downpmat;
637       MatStructure matflag;
638       PetscBool    opsset;
639 
640       /* check if operators have been set for up, if not use down operators to set them */
641       ierr = KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,PETSC_NULL);CHKERRQ(ierr);
642       if (!opsset) {
643         ierr = KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat,&matflag);CHKERRQ(ierr);
644         ierr = KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr);
645       }
646 
647       ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr);
648       if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
649       ierr = KSPSetUp(mglevels[i]->smoothu);CHKERRQ(ierr);
650       if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
651     }
652   }
653 
654   /*
655       If coarse solver is not direct method then DO NOT USE preonly
656   */
657   ierr = PetscTypeCompare((PetscObject)mglevels[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr);
658   if (preonly) {
659     ierr = PetscTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr);
660     ierr = PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr);
661     ierr = PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr);
662     ierr = PetscTypeCompare((PetscObject)cpc,PCSVD,&svd);CHKERRQ(ierr);
663     if (!lu && !redundant && !cholesky && !svd) {
664       ierr = KSPSetType(mglevels[0]->smoothd,KSPGMRES);CHKERRQ(ierr);
665     }
666   }
667 
668   if (!pc->setupcalled) {
669     ierr = KSPSetFromOptions(mglevels[0]->smoothd);CHKERRQ(ierr);
670   }
671 
672   if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
673   ierr = KSPSetUp(mglevels[0]->smoothd);CHKERRQ(ierr);
674   if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
675 
676   /*
677      Dump the interpolation/restriction matrices plus the
678    Jacobian/stiffness on each level. This allows MATLAB users to
679    easily check if the Galerkin condition A_c = R A_f R^T is satisfied.
680 
681    Only support one or the other at the same time.
682   */
683 #if defined(PETSC_USE_SOCKET_VIEWER)
684   ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,PETSC_NULL);CHKERRQ(ierr);
685   if (dump) {
686     viewer = PETSC_VIEWER_SOCKET_(((PetscObject)pc)->comm);
687   }
688   dump = PETSC_FALSE;
689 #endif
690   ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,PETSC_NULL);CHKERRQ(ierr);
691   if (dump) {
692     viewer = PETSC_VIEWER_BINARY_(((PetscObject)pc)->comm);
693   }
694 
695   if (viewer) {
696     for (i=1; i<n; i++) {
697       ierr = MatView(mglevels[i]->restrct,viewer);CHKERRQ(ierr);
698     }
699     for (i=0; i<n; i++) {
700       ierr = KSPGetPC(mglevels[i]->smoothd,&pc);CHKERRQ(ierr);
701       ierr = MatView(pc->mat,viewer);CHKERRQ(ierr);
702     }
703   }
704   PetscFunctionReturn(0);
705 }
706 
707 /* -------------------------------------------------------------------------------------*/
708 
709 #undef __FUNCT__
710 #define __FUNCT__ "PCMGGetLevels"
711 /*@
712    PCMGGetLevels - Gets the number of levels to use with MG.
713 
714    Not Collective
715 
716    Input Parameter:
717 .  pc - the preconditioner context
718 
719    Output parameter:
720 .  levels - the number of levels
721 
722    Level: advanced
723 
724 .keywords: MG, get, levels, multigrid
725 
726 .seealso: PCMGSetLevels()
727 @*/
728 PetscErrorCode  PCMGGetLevels(PC pc,PetscInt *levels)
729 {
730   PC_MG *mg = (PC_MG*)pc->data;
731 
732   PetscFunctionBegin;
733   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
734   PetscValidIntPointer(levels,2);
735   *levels = mg->nlevels;
736   PetscFunctionReturn(0);
737 }
738 
739 #undef __FUNCT__
740 #define __FUNCT__ "PCMGSetType"
741 /*@
742    PCMGSetType - Determines the form of multigrid to use:
743    multiplicative, additive, full, or the Kaskade algorithm.
744 
745    Logically Collective on PC
746 
747    Input Parameters:
748 +  pc - the preconditioner context
749 -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
750    PC_MG_FULL, PC_MG_KASKADE
751 
752    Options Database Key:
753 .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
754    additive, full, kaskade
755 
756    Level: advanced
757 
758 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid
759 
760 .seealso: PCMGSetLevels()
761 @*/
762 PetscErrorCode  PCMGSetType(PC pc,PCMGType form)
763 {
764   PC_MG                   *mg = (PC_MG*)pc->data;
765 
766   PetscFunctionBegin;
767   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
768   PetscValidLogicalCollectiveEnum(pc,form,2);
769   mg->am = form;
770   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
771   else pc->ops->applyrichardson = 0;
772   PetscFunctionReturn(0);
773 }
774 
775 #undef __FUNCT__
776 #define __FUNCT__ "PCMGSetCycleType"
777 /*@
778    PCMGSetCycleType - Sets the type cycles to use.  Use PCMGSetCycleTypeOnLevel() for more
779    complicated cycling.
780 
781    Logically Collective on PC
782 
783    Input Parameters:
784 +  pc - the multigrid context
785 -  PC_MG_CYCLE_V or PC_MG_CYCLE_W
786 
787    Options Database Key:
788 $  -pc_mg_cycle_type v or w
789 
790    Level: advanced
791 
792 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
793 
794 .seealso: PCMGSetCycleTypeOnLevel()
795 @*/
796 PetscErrorCode  PCMGSetCycleType(PC pc,PCMGCycleType n)
797 {
798   PC_MG        *mg = (PC_MG*)pc->data;
799   PC_MG_Levels **mglevels = mg->levels;
800   PetscInt     i,levels;
801 
802   PetscFunctionBegin;
803   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
804   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
805   PetscValidLogicalCollectiveInt(pc,n,2);
806   levels = mglevels[0]->levels;
807 
808   for (i=0; i<levels; i++) {
809     mglevels[i]->cycles  = n;
810   }
811   PetscFunctionReturn(0);
812 }
813 
814 #undef __FUNCT__
815 #define __FUNCT__ "PCMGMultiplicativeSetCycles"
816 /*@
817    PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step
818          of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used
819 
820    Logically Collective on PC
821 
822    Input Parameters:
823 +  pc - the multigrid context
824 -  n - number of cycles (default is 1)
825 
826    Options Database Key:
827 $  -pc_mg_multiplicative_cycles n
828 
829    Level: advanced
830 
831    Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType()
832 
833 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
834 
835 .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
836 @*/
837 PetscErrorCode  PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
838 {
839   PC_MG        *mg = (PC_MG*)pc->data;
840   PC_MG_Levels **mglevels = mg->levels;
841   PetscInt     i,levels;
842 
843   PetscFunctionBegin;
844   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
845   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
846   PetscValidLogicalCollectiveInt(pc,n,2);
847   levels = mglevels[0]->levels;
848 
849   for (i=0; i<levels; i++) {
850     mg->cyclesperpcapply  = n;
851   }
852   PetscFunctionReturn(0);
853 }
854 
855 #undef __FUNCT__
856 #define __FUNCT__ "PCMGSetGalerkin"
857 /*@
858    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
859       finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t
860 
861    Logically Collective on PC
862 
863    Input Parameters:
864 +  pc - the multigrid context
865 -  use - PETSC_TRUE to use the Galerkin process to compute coarse-level operators
866 
867    Options Database Key:
868 $  -pc_mg_galerkin
869 
870    Level: intermediate
871 
872 .keywords: MG, set, Galerkin
873 
874 .seealso: PCMGGetGalerkin()
875 
876 @*/
877 PetscErrorCode PCMGSetGalerkin(PC pc,PetscBool use)
878 {
879   PC_MG        *mg = (PC_MG*)pc->data;
880 
881   PetscFunctionBegin;
882   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
883   mg->galerkin = (PetscInt)use;
884   PetscFunctionReturn(0);
885 }
886 
887 #undef __FUNCT__
888 #define __FUNCT__ "PCMGGetGalerkin"
889 /*@
890    PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
891       A_i-1 = r_i * A_i * r_i^t
892 
893    Not Collective
894 
895    Input Parameter:
896 .  pc - the multigrid context
897 
898    Output Parameter:
899 .  gelerkin - PETSC_TRUE or PETSC_FALSE
900 
901    Options Database Key:
902 $  -pc_mg_galerkin
903 
904    Level: intermediate
905 
906 .keywords: MG, set, Galerkin
907 
908 .seealso: PCMGSetGalerkin()
909 
910 @*/
911 PetscErrorCode  PCMGGetGalerkin(PC pc,PetscBool  *galerkin)
912 {
913   PC_MG        *mg = (PC_MG*)pc->data;
914 
915   PetscFunctionBegin;
916   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
917   *galerkin = (PetscBool)mg->galerkin;
918   PetscFunctionReturn(0);
919 }
920 
921 #undef __FUNCT__
922 #define __FUNCT__ "PCMGSetNumberSmoothDown"
923 /*@
924    PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to
925    use on all levels. Use PCMGGetSmootherDown() to set different
926    pre-smoothing steps on different levels.
927 
928    Logically Collective on PC
929 
930    Input Parameters:
931 +  mg - the multigrid context
932 -  n - the number of smoothing steps
933 
934    Options Database Key:
935 .  -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps
936 
937    Level: advanced
938 
939 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid
940 
941 .seealso: PCMGSetNumberSmoothUp()
942 @*/
943 PetscErrorCode  PCMGSetNumberSmoothDown(PC pc,PetscInt n)
944 {
945   PC_MG          *mg = (PC_MG*)pc->data;
946   PC_MG_Levels   **mglevels = mg->levels;
947   PetscErrorCode ierr;
948   PetscInt       i,levels;
949 
950   PetscFunctionBegin;
951   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
952   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
953   PetscValidLogicalCollectiveInt(pc,n,2);
954   levels = mglevels[0]->levels;
955 
956   for (i=1; i<levels; i++) {
957     /* make sure smoother up and down are different */
958     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
959     ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
960     mg->default_smoothd = n;
961   }
962   PetscFunctionReturn(0);
963 }
964 
965 #undef __FUNCT__
966 #define __FUNCT__ "PCMGSetNumberSmoothUp"
967 /*@
968    PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use
969    on all levels. Use PCMGGetSmootherUp() to set different numbers of
970    post-smoothing steps on different levels.
971 
972    Logically Collective on PC
973 
974    Input Parameters:
975 +  mg - the multigrid context
976 -  n - the number of smoothing steps
977 
978    Options Database Key:
979 .  -pc_mg_smoothup <n> - Sets number of post-smoothing steps
980 
981    Level: advanced
982 
983    Note: this does not set a value on the coarsest grid, since we assume that
984     there is no separate smooth up on the coarsest grid.
985 
986 .keywords: MG, smooth, up, post-smoothing, steps, multigrid
987 
988 .seealso: PCMGSetNumberSmoothDown()
989 @*/
990 PetscErrorCode  PCMGSetNumberSmoothUp(PC pc,PetscInt n)
991 {
992   PC_MG          *mg = (PC_MG*)pc->data;
993   PC_MG_Levels   **mglevels = mg->levels;
994   PetscErrorCode ierr;
995   PetscInt       i,levels;
996 
997   PetscFunctionBegin;
998   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
999   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1000   PetscValidLogicalCollectiveInt(pc,n,2);
1001   levels = mglevels[0]->levels;
1002 
1003   for (i=1; i<levels; i++) {
1004     /* make sure smoother up and down are different */
1005     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
1006     ierr = KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
1007     mg->default_smoothu = n;
1008   }
1009   PetscFunctionReturn(0);
1010 }
1011 
1012 /* ----------------------------------------------------------------------------------------*/
1013 
1014 /*MC
1015    PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional
1016     information about the coarser grid matrices and restriction/interpolation operators.
1017 
1018    Options Database Keys:
1019 +  -pc_mg_levels <nlevels> - number of levels including finest
1020 .  -pc_mg_cycles v or w
1021 .  -pc_mg_smoothup <n> - number of smoothing steps after interpolation
1022 .  -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator
1023 .  -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default
1024 .  -pc_mg_log - log information about time spent on each level of the solver
1025 .  -pc_mg_monitor - print information on the multigrid convergence
1026 .  -pc_mg_galerkin - use Galerkin process to compute coarser operators
1027 -  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
1028                         to the Socket viewer for reading from MATLAB.
1029 
1030    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
1031 
1032    Level: intermediate
1033 
1034    Concepts: multigrid/multilevel
1035 
1036 .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC
1037            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(),
1038            PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
1039            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
1040            PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
1041 M*/
1042 
1043 EXTERN_C_BEGIN
1044 #undef __FUNCT__
1045 #define __FUNCT__ "PCCreate_MG"
1046 PetscErrorCode  PCCreate_MG(PC pc)
1047 {
1048   PC_MG          *mg;
1049   PetscErrorCode ierr;
1050 
1051   PetscFunctionBegin;
1052   ierr        = PetscNewLog(pc,PC_MG,&mg);CHKERRQ(ierr);
1053   pc->data    = (void*)mg;
1054   mg->nlevels = -1;
1055 
1056   pc->ops->apply          = PCApply_MG;
1057   pc->ops->setup          = PCSetUp_MG;
1058   pc->ops->reset          = PCReset_MG;
1059   pc->ops->destroy        = PCDestroy_MG;
1060   pc->ops->setfromoptions = PCSetFromOptions_MG;
1061   pc->ops->view           = PCView_MG;
1062   PetscFunctionReturn(0);
1063 }
1064 EXTERN_C_END
1065