xref: /petsc/src/ksp/pc/impls/mg/mg.c (revision caa4e7f26594b8daaf440f4757330959cfc6cef4)
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   /* Skipping this for galerkin==2 (externally managed hierarchy such as ML and GAMG). Cleaner logic here would be great. */
509   if (pc->dm && mg->galerkin != 2 && !pc->setupcalled) {
510     /* construct the interpolation from the DMs */
511     Mat p;
512     Vec rscale;
513     ierr = PetscMalloc(n*sizeof(DM),&dms);CHKERRQ(ierr);
514     dms[n-1] = pc->dm;
515     for (i=n-2; i>-1; i--) {
516       KSPDM kdm;
517       ierr = DMCoarsen(dms[i+1],PETSC_NULL,&dms[i]);CHKERRQ(ierr);
518       ierr = KSPSetDM(mglevels[i]->smoothd,dms[i]);CHKERRQ(ierr);
519       if (mg->galerkin) {ierr = KSPSetDMActive(mglevels[i]->smoothd,PETSC_FALSE);CHKERRQ(ierr);}
520       ierr = DMKSPGetContextWrite(dms[i],&kdm);CHKERRQ(ierr);
521       /* Ugly hack so that the next KSPSetUp() will use the RHS that we set */
522       kdm->computerhs = PETSC_NULL;
523       kdm->rhsctx = PETSC_NULL;
524       ierr = DMSetFunction(dms[i],0);
525       ierr = DMSetInitialGuess(dms[i],0);
526       if (!mglevels[i+1]->interpolate) {
527 	ierr = DMCreateInterpolation(dms[i],dms[i+1],&p,&rscale);CHKERRQ(ierr);
528 	ierr = PCMGSetInterpolation(pc,i+1,p);CHKERRQ(ierr);
529 	if (rscale) {ierr = PCMGSetRScale(pc,i+1,rscale);CHKERRQ(ierr);}
530         ierr = VecDestroy(&rscale);CHKERRQ(ierr);
531         ierr = MatDestroy(&p);CHKERRQ(ierr);
532       }
533     }
534 
535     for (i=n-2; i>-1; i--) {
536       ierr = DMDestroy(&dms[i]);CHKERRQ(ierr);
537     }
538     ierr = PetscFree(dms);CHKERRQ(ierr);
539   }
540 
541   if (pc->dm && !pc->setupcalled) {
542     /* finest smoother also gets DM but it is not active, independent of whether galerkin==2 */
543     ierr = KSPSetDM(mglevels[n-1]->smoothd,pc->dm);CHKERRQ(ierr);
544     ierr = KSPSetDMActive(mglevels[n-1]->smoothd,PETSC_FALSE);CHKERRQ(ierr);
545   }
546 
547   if (mg->galerkin == 1) {
548     Mat B;
549     /* currently only handle case where mat and pmat are the same on coarser levels */
550     ierr = KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr);
551     if (!pc->setupcalled) {
552       for (i=n-2; i>-1; i--) {
553         ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr);
554         ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
555 	if (i != n-2) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);}
556         dB   = B;
557       }
558       if (n > 1) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);}
559     } else {
560       for (i=n-2; i>-1; i--) {
561         ierr = KSPGetOperators(mglevels[i]->smoothd,PETSC_NULL,&B,PETSC_NULL);CHKERRQ(ierr);
562         ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr);
563         ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
564         dB   = B;
565       }
566     }
567   } else if (!mg->galerkin && pc->dm && pc->dm->x) {
568     /* need to restrict Jacobian location to coarser meshes for evaluation */
569     for (i=n-2;i>-1; i--) {
570       Mat R;
571       Vec rscale;
572       if (!mglevels[i]->smoothd->dm->x) {
573         Vec *vecs;
574         ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vecs,0,PETSC_NULL);CHKERRQ(ierr);
575         mglevels[i]->smoothd->dm->x = vecs[0];
576         ierr = PetscFree(vecs);CHKERRQ(ierr);
577       }
578       ierr = PCMGGetRestriction(pc,i+1,&R);CHKERRQ(ierr);
579       ierr = PCMGGetRScale(pc,i+1,&rscale);CHKERRQ(ierr);
580       ierr = MatRestrict(R,mglevels[i+1]->smoothd->dm->x,mglevels[i]->smoothd->dm->x);CHKERRQ(ierr);
581       ierr = VecPointwiseMult(mglevels[i]->smoothd->dm->x,mglevels[i]->smoothd->dm->x,rscale);CHKERRQ(ierr);
582     }
583   }
584   if (!mg->galerkin) {
585     for (i=n-2;i>=0; i--) {
586       DM dmfine = mglevels[i+1]->smoothd->dm;
587       DM dmcoarse = mglevels[i]->smoothd->dm;
588       Mat Restrict,Inject;
589       Vec rscale;
590       ierr = PCMGGetRestriction(pc,i+1,&Restrict);CHKERRQ(ierr);
591       ierr = PCMGGetRScale(pc,i+1,&rscale);CHKERRQ(ierr);
592       Inject = PETSC_NULL;      /* Callback should create it if it needs Injection */
593       ierr = DMRestrict(dmfine,Restrict,rscale,Inject,dmcoarse);CHKERRQ(ierr);
594     }
595   }
596 
597   if (!pc->setupcalled) {
598     for (i=0; i<n; i++) {
599       ierr = KSPSetFromOptions(mglevels[i]->smoothd);CHKERRQ(ierr);
600     }
601     for (i=1; i<n; i++) {
602       if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) {
603         ierr = KSPSetFromOptions(mglevels[i]->smoothu);CHKERRQ(ierr);
604       }
605     }
606     for (i=1; i<n; i++) {
607       ierr = PCMGGetInterpolation(pc,i,&mglevels[i]->interpolate);CHKERRQ(ierr);
608       ierr = PCMGGetRestriction(pc,i,&mglevels[i]->restrct);CHKERRQ(ierr);
609     }
610     for (i=0; i<n-1; i++) {
611       if (!mglevels[i]->b) {
612         Vec *vec;
613         ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr);
614         ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr);
615         ierr = VecDestroy(vec);CHKERRQ(ierr);
616         ierr = PetscFree(vec);CHKERRQ(ierr);
617       }
618       if (!mglevels[i]->r && i) {
619         ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr);
620         ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr);
621         ierr = VecDestroy(&tvec);CHKERRQ(ierr);
622       }
623       if (!mglevels[i]->x) {
624         ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr);
625         ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr);
626         ierr = VecDestroy(&tvec);CHKERRQ(ierr);
627       }
628     }
629     if (n != 1 && !mglevels[n-1]->r) {
630       /* PCMGSetR() on the finest level if user did not supply it */
631       Vec *vec;
632       ierr = KSPGetVecs(mglevels[n-1]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr);
633       ierr = PCMGSetR(pc,n-1,*vec);CHKERRQ(ierr);
634       ierr = VecDestroy(vec);CHKERRQ(ierr);
635       ierr = PetscFree(vec);CHKERRQ(ierr);
636     }
637   }
638 
639 
640   for (i=1; i<n; i++) {
641     if (mglevels[i]->smoothu == mglevels[i]->smoothd) {
642       /* if doing only down then initial guess is zero */
643       ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr);
644     }
645     if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
646     ierr = KSPSetUp(mglevels[i]->smoothd);CHKERRQ(ierr);
647     if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
648     if (!mglevels[i]->residual) {
649       Mat mat;
650       ierr = KSPGetOperators(mglevels[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);CHKERRQ(ierr);
651       ierr = PCMGSetResidual(pc,i,PCMGDefaultResidual,mat);CHKERRQ(ierr);
652     }
653   }
654   for (i=1; i<n; i++) {
655     if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) {
656       Mat          downmat,downpmat;
657       MatStructure matflag;
658       PetscBool    opsset;
659 
660       /* check if operators have been set for up, if not use down operators to set them */
661       ierr = KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,PETSC_NULL);CHKERRQ(ierr);
662       if (!opsset) {
663         ierr = KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat,&matflag);CHKERRQ(ierr);
664         ierr = KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr);
665       }
666 
667       ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr);
668       if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
669       ierr = KSPSetUp(mglevels[i]->smoothu);CHKERRQ(ierr);
670       if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
671     }
672   }
673 
674   /*
675       If coarse solver is not direct method then DO NOT USE preonly
676   */
677   ierr = PetscTypeCompare((PetscObject)mglevels[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr);
678   if (preonly) {
679     ierr = PetscTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr);
680     ierr = PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr);
681     ierr = PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr);
682     ierr = PetscTypeCompare((PetscObject)cpc,PCSVD,&svd);CHKERRQ(ierr);
683     if (!lu && !redundant && !cholesky && !svd) {
684       ierr = KSPSetType(mglevels[0]->smoothd,KSPGMRES);CHKERRQ(ierr);
685     }
686   }
687 
688   if (!pc->setupcalled) {
689     ierr = KSPSetFromOptions(mglevels[0]->smoothd);CHKERRQ(ierr);
690   }
691 
692   if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
693   ierr = KSPSetUp(mglevels[0]->smoothd);CHKERRQ(ierr);
694   if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
695 
696   /*
697      Dump the interpolation/restriction matrices plus the
698    Jacobian/stiffness on each level. This allows MATLAB users to
699    easily check if the Galerkin condition A_c = R A_f R^T is satisfied.
700 
701    Only support one or the other at the same time.
702   */
703 #if defined(PETSC_USE_SOCKET_VIEWER)
704   ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,PETSC_NULL);CHKERRQ(ierr);
705   if (dump) {
706     viewer = PETSC_VIEWER_SOCKET_(((PetscObject)pc)->comm);
707   }
708   dump = PETSC_FALSE;
709 #endif
710   ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,PETSC_NULL);CHKERRQ(ierr);
711   if (dump) {
712     viewer = PETSC_VIEWER_BINARY_(((PetscObject)pc)->comm);
713   }
714 
715   if (viewer) {
716     for (i=1; i<n; i++) {
717       ierr = MatView(mglevels[i]->restrct,viewer);CHKERRQ(ierr);
718     }
719     for (i=0; i<n; i++) {
720       ierr = KSPGetPC(mglevels[i]->smoothd,&pc);CHKERRQ(ierr);
721       ierr = MatView(pc->mat,viewer);CHKERRQ(ierr);
722     }
723   }
724   PetscFunctionReturn(0);
725 }
726 
727 /* -------------------------------------------------------------------------------------*/
728 
729 #undef __FUNCT__
730 #define __FUNCT__ "PCMGGetLevels"
731 /*@
732    PCMGGetLevels - Gets the number of levels to use with MG.
733 
734    Not Collective
735 
736    Input Parameter:
737 .  pc - the preconditioner context
738 
739    Output parameter:
740 .  levels - the number of levels
741 
742    Level: advanced
743 
744 .keywords: MG, get, levels, multigrid
745 
746 .seealso: PCMGSetLevels()
747 @*/
748 PetscErrorCode  PCMGGetLevels(PC pc,PetscInt *levels)
749 {
750   PC_MG *mg = (PC_MG*)pc->data;
751 
752   PetscFunctionBegin;
753   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
754   PetscValidIntPointer(levels,2);
755   *levels = mg->nlevels;
756   PetscFunctionReturn(0);
757 }
758 
759 #undef __FUNCT__
760 #define __FUNCT__ "PCMGSetType"
761 /*@
762    PCMGSetType - Determines the form of multigrid to use:
763    multiplicative, additive, full, or the Kaskade algorithm.
764 
765    Logically Collective on PC
766 
767    Input Parameters:
768 +  pc - the preconditioner context
769 -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
770    PC_MG_FULL, PC_MG_KASKADE
771 
772    Options Database Key:
773 .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
774    additive, full, kaskade
775 
776    Level: advanced
777 
778 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid
779 
780 .seealso: PCMGSetLevels()
781 @*/
782 PetscErrorCode  PCMGSetType(PC pc,PCMGType form)
783 {
784   PC_MG                   *mg = (PC_MG*)pc->data;
785 
786   PetscFunctionBegin;
787   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
788   PetscValidLogicalCollectiveEnum(pc,form,2);
789   mg->am = form;
790   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
791   else pc->ops->applyrichardson = 0;
792   PetscFunctionReturn(0);
793 }
794 
795 #undef __FUNCT__
796 #define __FUNCT__ "PCMGSetCycleType"
797 /*@
798    PCMGSetCycleType - Sets the type cycles to use.  Use PCMGSetCycleTypeOnLevel() for more
799    complicated cycling.
800 
801    Logically Collective on PC
802 
803    Input Parameters:
804 +  pc - the multigrid context
805 -  PC_MG_CYCLE_V or PC_MG_CYCLE_W
806 
807    Options Database Key:
808 $  -pc_mg_cycle_type v or w
809 
810    Level: advanced
811 
812 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
813 
814 .seealso: PCMGSetCycleTypeOnLevel()
815 @*/
816 PetscErrorCode  PCMGSetCycleType(PC pc,PCMGCycleType n)
817 {
818   PC_MG        *mg = (PC_MG*)pc->data;
819   PC_MG_Levels **mglevels = mg->levels;
820   PetscInt     i,levels;
821 
822   PetscFunctionBegin;
823   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
824   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
825   PetscValidLogicalCollectiveInt(pc,n,2);
826   levels = mglevels[0]->levels;
827 
828   for (i=0; i<levels; i++) {
829     mglevels[i]->cycles  = n;
830   }
831   PetscFunctionReturn(0);
832 }
833 
834 #undef __FUNCT__
835 #define __FUNCT__ "PCMGMultiplicativeSetCycles"
836 /*@
837    PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step
838          of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used
839 
840    Logically Collective on PC
841 
842    Input Parameters:
843 +  pc - the multigrid context
844 -  n - number of cycles (default is 1)
845 
846    Options Database Key:
847 $  -pc_mg_multiplicative_cycles n
848 
849    Level: advanced
850 
851    Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType()
852 
853 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
854 
855 .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
856 @*/
857 PetscErrorCode  PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
858 {
859   PC_MG        *mg = (PC_MG*)pc->data;
860   PC_MG_Levels **mglevels = mg->levels;
861   PetscInt     i,levels;
862 
863   PetscFunctionBegin;
864   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
865   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
866   PetscValidLogicalCollectiveInt(pc,n,2);
867   levels = mglevels[0]->levels;
868 
869   for (i=0; i<levels; i++) {
870     mg->cyclesperpcapply  = n;
871   }
872   PetscFunctionReturn(0);
873 }
874 
875 #undef __FUNCT__
876 #define __FUNCT__ "PCMGSetGalerkin"
877 /*@
878    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
879       finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t
880 
881    Logically Collective on PC
882 
883    Input Parameters:
884 +  pc - the multigrid context
885 -  use - PETSC_TRUE to use the Galerkin process to compute coarse-level operators
886 
887    Options Database Key:
888 $  -pc_mg_galerkin
889 
890    Level: intermediate
891 
892 .keywords: MG, set, Galerkin
893 
894 .seealso: PCMGGetGalerkin()
895 
896 @*/
897 PetscErrorCode PCMGSetGalerkin(PC pc,PetscBool use)
898 {
899   PC_MG        *mg = (PC_MG*)pc->data;
900 
901   PetscFunctionBegin;
902   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
903   mg->galerkin = (PetscInt)use;
904   PetscFunctionReturn(0);
905 }
906 
907 #undef __FUNCT__
908 #define __FUNCT__ "PCMGGetGalerkin"
909 /*@
910    PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
911       A_i-1 = r_i * A_i * r_i^t
912 
913    Not Collective
914 
915    Input Parameter:
916 .  pc - the multigrid context
917 
918    Output Parameter:
919 .  gelerkin - PETSC_TRUE or PETSC_FALSE
920 
921    Options Database Key:
922 $  -pc_mg_galerkin
923 
924    Level: intermediate
925 
926 .keywords: MG, set, Galerkin
927 
928 .seealso: PCMGSetGalerkin()
929 
930 @*/
931 PetscErrorCode  PCMGGetGalerkin(PC pc,PetscBool  *galerkin)
932 {
933   PC_MG        *mg = (PC_MG*)pc->data;
934 
935   PetscFunctionBegin;
936   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
937   *galerkin = (PetscBool)mg->galerkin;
938   PetscFunctionReturn(0);
939 }
940 
941 #undef __FUNCT__
942 #define __FUNCT__ "PCMGSetNumberSmoothDown"
943 /*@
944    PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to
945    use on all levels. Use PCMGGetSmootherDown() to set different
946    pre-smoothing steps on different levels.
947 
948    Logically Collective on PC
949 
950    Input Parameters:
951 +  mg - the multigrid context
952 -  n - the number of smoothing steps
953 
954    Options Database Key:
955 .  -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps
956 
957    Level: advanced
958 
959 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid
960 
961 .seealso: PCMGSetNumberSmoothUp()
962 @*/
963 PetscErrorCode  PCMGSetNumberSmoothDown(PC pc,PetscInt n)
964 {
965   PC_MG          *mg = (PC_MG*)pc->data;
966   PC_MG_Levels   **mglevels = mg->levels;
967   PetscErrorCode ierr;
968   PetscInt       i,levels;
969 
970   PetscFunctionBegin;
971   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
972   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
973   PetscValidLogicalCollectiveInt(pc,n,2);
974   levels = mglevels[0]->levels;
975 
976   for (i=1; i<levels; i++) {
977     /* make sure smoother up and down are different */
978     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
979     ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
980     mg->default_smoothd = n;
981   }
982   PetscFunctionReturn(0);
983 }
984 
985 #undef __FUNCT__
986 #define __FUNCT__ "PCMGSetNumberSmoothUp"
987 /*@
988    PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use
989    on all levels. Use PCMGGetSmootherUp() to set different numbers of
990    post-smoothing steps on different levels.
991 
992    Logically Collective on PC
993 
994    Input Parameters:
995 +  mg - the multigrid context
996 -  n - the number of smoothing steps
997 
998    Options Database Key:
999 .  -pc_mg_smoothup <n> - Sets number of post-smoothing steps
1000 
1001    Level: advanced
1002 
1003    Note: this does not set a value on the coarsest grid, since we assume that
1004     there is no separate smooth up on the coarsest grid.
1005 
1006 .keywords: MG, smooth, up, post-smoothing, steps, multigrid
1007 
1008 .seealso: PCMGSetNumberSmoothDown()
1009 @*/
1010 PetscErrorCode  PCMGSetNumberSmoothUp(PC pc,PetscInt n)
1011 {
1012   PC_MG          *mg = (PC_MG*)pc->data;
1013   PC_MG_Levels   **mglevels = mg->levels;
1014   PetscErrorCode ierr;
1015   PetscInt       i,levels;
1016 
1017   PetscFunctionBegin;
1018   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
1019   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1020   PetscValidLogicalCollectiveInt(pc,n,2);
1021   levels = mglevels[0]->levels;
1022 
1023   for (i=1; i<levels; i++) {
1024     /* make sure smoother up and down are different */
1025     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
1026     ierr = KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
1027     mg->default_smoothu = n;
1028   }
1029   PetscFunctionReturn(0);
1030 }
1031 
1032 /* ----------------------------------------------------------------------------------------*/
1033 
1034 /*MC
1035    PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional
1036     information about the coarser grid matrices and restriction/interpolation operators.
1037 
1038    Options Database Keys:
1039 +  -pc_mg_levels <nlevels> - number of levels including finest
1040 .  -pc_mg_cycles v or w
1041 .  -pc_mg_smoothup <n> - number of smoothing steps after interpolation
1042 .  -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator
1043 .  -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default
1044 .  -pc_mg_log - log information about time spent on each level of the solver
1045 .  -pc_mg_monitor - print information on the multigrid convergence
1046 .  -pc_mg_galerkin - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R'
1047 .  -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1)
1048 .  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
1049                         to the Socket viewer for reading from MATLAB.
1050 -  -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices
1051                         to the binary output file called binaryoutput
1052 
1053    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
1054 
1055        When run with a single level the smoother options are used on that level NOT the coarse grid solver options
1056 
1057    Level: intermediate
1058 
1059    Concepts: multigrid/multilevel
1060 
1061 .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE
1062            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(),
1063            PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
1064            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
1065            PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
1066 M*/
1067 
1068 EXTERN_C_BEGIN
1069 #undef __FUNCT__
1070 #define __FUNCT__ "PCCreate_MG"
1071 PetscErrorCode  PCCreate_MG(PC pc)
1072 {
1073   PC_MG          *mg;
1074   PetscErrorCode ierr;
1075 
1076   PetscFunctionBegin;
1077   ierr        = PetscNewLog(pc,PC_MG,&mg);CHKERRQ(ierr);
1078   pc->data    = (void*)mg;
1079   mg->nlevels = -1;
1080 
1081   pc->ops->apply          = PCApply_MG;
1082   pc->ops->setup          = PCSetUp_MG;
1083   pc->ops->reset          = PCReset_MG;
1084   pc->ops->destroy        = PCDestroy_MG;
1085   pc->ops->setfromoptions = PCSetFromOptions_MG;
1086   pc->ops->view           = PCView_MG;
1087   PetscFunctionReturn(0);
1088 }
1089 EXTERN_C_END
1090