xref: /petsc/src/ksp/pc/impls/mg/mg.c (revision ae9be28942d2d3eca8476af0b23adcfdc0f3733e)
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 
585   if (!pc->setupcalled) {
586     for (i=0; i<n; i++) {
587       ierr = KSPSetFromOptions(mglevels[i]->smoothd);CHKERRQ(ierr);
588     }
589     for (i=1; i<n; i++) {
590       if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) {
591         ierr = KSPSetFromOptions(mglevels[i]->smoothu);CHKERRQ(ierr);
592       }
593     }
594     for (i=1; i<n; i++) {
595       ierr = PCMGGetInterpolation(pc,i,&mglevels[i]->interpolate);CHKERRQ(ierr);
596       ierr = PCMGGetRestriction(pc,i,&mglevels[i]->restrct);CHKERRQ(ierr);
597     }
598     for (i=0; i<n-1; i++) {
599       if (!mglevels[i]->b) {
600         Vec *vec;
601         ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr);
602         ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr);
603         ierr = VecDestroy(vec);CHKERRQ(ierr);
604         ierr = PetscFree(vec);CHKERRQ(ierr);
605       }
606       if (!mglevels[i]->r && i) {
607         ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr);
608         ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr);
609         ierr = VecDestroy(&tvec);CHKERRQ(ierr);
610       }
611       if (!mglevels[i]->x) {
612         ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr);
613         ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr);
614         ierr = VecDestroy(&tvec);CHKERRQ(ierr);
615       }
616     }
617     if (n != 1 && !mglevels[n-1]->r) {
618       /* PCMGSetR() on the finest level if user did not supply it */
619       Vec *vec;
620       ierr = KSPGetVecs(mglevels[n-1]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr);
621       ierr = PCMGSetR(pc,n-1,*vec);CHKERRQ(ierr);
622       ierr = VecDestroy(vec);CHKERRQ(ierr);
623       ierr = PetscFree(vec);CHKERRQ(ierr);
624     }
625   }
626 
627 
628   for (i=1; i<n; i++) {
629     if (mglevels[i]->smoothu == mglevels[i]->smoothd) {
630       /* if doing only down then initial guess is zero */
631       ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr);
632     }
633     if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
634     ierr = KSPSetUp(mglevels[i]->smoothd);CHKERRQ(ierr);
635     if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
636     if (!mglevels[i]->residual) {
637       Mat mat;
638       ierr = KSPGetOperators(mglevels[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);CHKERRQ(ierr);
639       ierr = PCMGSetResidual(pc,i,PCMGDefaultResidual,mat);CHKERRQ(ierr);
640     }
641   }
642   for (i=1; i<n; i++) {
643     if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) {
644       Mat          downmat,downpmat;
645       MatStructure matflag;
646       PetscBool    opsset;
647 
648       /* check if operators have been set for up, if not use down operators to set them */
649       ierr = KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,PETSC_NULL);CHKERRQ(ierr);
650       if (!opsset) {
651         ierr = KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat,&matflag);CHKERRQ(ierr);
652         ierr = KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr);
653       }
654 
655       ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr);
656       if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
657       ierr = KSPSetUp(mglevels[i]->smoothu);CHKERRQ(ierr);
658       if (mglevels[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
659     }
660   }
661 
662   /*
663       If coarse solver is not direct method then DO NOT USE preonly
664   */
665   ierr = PetscTypeCompare((PetscObject)mglevels[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr);
666   if (preonly) {
667     ierr = PetscTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr);
668     ierr = PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr);
669     ierr = PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr);
670     ierr = PetscTypeCompare((PetscObject)cpc,PCSVD,&svd);CHKERRQ(ierr);
671     if (!lu && !redundant && !cholesky && !svd) {
672       ierr = KSPSetType(mglevels[0]->smoothd,KSPGMRES);CHKERRQ(ierr);
673     }
674   }
675 
676   if (!pc->setupcalled) {
677     ierr = KSPSetFromOptions(mglevels[0]->smoothd);CHKERRQ(ierr);
678   }
679 
680   if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventBegin(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
681   ierr = KSPSetUp(mglevels[0]->smoothd);CHKERRQ(ierr);
682   if (mglevels[0]->eventsmoothsetup) {ierr = PetscLogEventEnd(mglevels[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
683 
684   /*
685      Dump the interpolation/restriction matrices plus the
686    Jacobian/stiffness on each level. This allows MATLAB users to
687    easily check if the Galerkin condition A_c = R A_f R^T is satisfied.
688 
689    Only support one or the other at the same time.
690   */
691 #if defined(PETSC_USE_SOCKET_VIEWER)
692   ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,PETSC_NULL);CHKERRQ(ierr);
693   if (dump) {
694     viewer = PETSC_VIEWER_SOCKET_(((PetscObject)pc)->comm);
695   }
696   dump = PETSC_FALSE;
697 #endif
698   ierr = PetscOptionsGetBool(((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,PETSC_NULL);CHKERRQ(ierr);
699   if (dump) {
700     viewer = PETSC_VIEWER_BINARY_(((PetscObject)pc)->comm);
701   }
702 
703   if (viewer) {
704     for (i=1; i<n; i++) {
705       ierr = MatView(mglevels[i]->restrct,viewer);CHKERRQ(ierr);
706     }
707     for (i=0; i<n; i++) {
708       ierr = KSPGetPC(mglevels[i]->smoothd,&pc);CHKERRQ(ierr);
709       ierr = MatView(pc->mat,viewer);CHKERRQ(ierr);
710     }
711   }
712   PetscFunctionReturn(0);
713 }
714 
715 /* -------------------------------------------------------------------------------------*/
716 
717 #undef __FUNCT__
718 #define __FUNCT__ "PCMGGetLevels"
719 /*@
720    PCMGGetLevels - Gets the number of levels to use with MG.
721 
722    Not Collective
723 
724    Input Parameter:
725 .  pc - the preconditioner context
726 
727    Output parameter:
728 .  levels - the number of levels
729 
730    Level: advanced
731 
732 .keywords: MG, get, levels, multigrid
733 
734 .seealso: PCMGSetLevels()
735 @*/
736 PetscErrorCode  PCMGGetLevels(PC pc,PetscInt *levels)
737 {
738   PC_MG *mg = (PC_MG*)pc->data;
739 
740   PetscFunctionBegin;
741   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
742   PetscValidIntPointer(levels,2);
743   *levels = mg->nlevels;
744   PetscFunctionReturn(0);
745 }
746 
747 #undef __FUNCT__
748 #define __FUNCT__ "PCMGSetType"
749 /*@
750    PCMGSetType - Determines the form of multigrid to use:
751    multiplicative, additive, full, or the Kaskade algorithm.
752 
753    Logically Collective on PC
754 
755    Input Parameters:
756 +  pc - the preconditioner context
757 -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
758    PC_MG_FULL, PC_MG_KASKADE
759 
760    Options Database Key:
761 .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
762    additive, full, kaskade
763 
764    Level: advanced
765 
766 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid
767 
768 .seealso: PCMGSetLevels()
769 @*/
770 PetscErrorCode  PCMGSetType(PC pc,PCMGType form)
771 {
772   PC_MG                   *mg = (PC_MG*)pc->data;
773 
774   PetscFunctionBegin;
775   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
776   PetscValidLogicalCollectiveEnum(pc,form,2);
777   mg->am = form;
778   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
779   else pc->ops->applyrichardson = 0;
780   PetscFunctionReturn(0);
781 }
782 
783 #undef __FUNCT__
784 #define __FUNCT__ "PCMGSetCycleType"
785 /*@
786    PCMGSetCycleType - Sets the type cycles to use.  Use PCMGSetCycleTypeOnLevel() for more
787    complicated cycling.
788 
789    Logically Collective on PC
790 
791    Input Parameters:
792 +  pc - the multigrid context
793 -  PC_MG_CYCLE_V or PC_MG_CYCLE_W
794 
795    Options Database Key:
796 $  -pc_mg_cycle_type v or w
797 
798    Level: advanced
799 
800 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
801 
802 .seealso: PCMGSetCycleTypeOnLevel()
803 @*/
804 PetscErrorCode  PCMGSetCycleType(PC pc,PCMGCycleType n)
805 {
806   PC_MG        *mg = (PC_MG*)pc->data;
807   PC_MG_Levels **mglevels = mg->levels;
808   PetscInt     i,levels;
809 
810   PetscFunctionBegin;
811   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
812   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
813   PetscValidLogicalCollectiveInt(pc,n,2);
814   levels = mglevels[0]->levels;
815 
816   for (i=0; i<levels; i++) {
817     mglevels[i]->cycles  = n;
818   }
819   PetscFunctionReturn(0);
820 }
821 
822 #undef __FUNCT__
823 #define __FUNCT__ "PCMGMultiplicativeSetCycles"
824 /*@
825    PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step
826          of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used
827 
828    Logically Collective on PC
829 
830    Input Parameters:
831 +  pc - the multigrid context
832 -  n - number of cycles (default is 1)
833 
834    Options Database Key:
835 $  -pc_mg_multiplicative_cycles n
836 
837    Level: advanced
838 
839    Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType()
840 
841 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
842 
843 .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
844 @*/
845 PetscErrorCode  PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
846 {
847   PC_MG        *mg = (PC_MG*)pc->data;
848   PC_MG_Levels **mglevels = mg->levels;
849   PetscInt     i,levels;
850 
851   PetscFunctionBegin;
852   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
853   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
854   PetscValidLogicalCollectiveInt(pc,n,2);
855   levels = mglevels[0]->levels;
856 
857   for (i=0; i<levels; i++) {
858     mg->cyclesperpcapply  = n;
859   }
860   PetscFunctionReturn(0);
861 }
862 
863 #undef __FUNCT__
864 #define __FUNCT__ "PCMGSetGalerkin"
865 /*@
866    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
867       finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t
868 
869    Logically Collective on PC
870 
871    Input Parameters:
872 +  pc - the multigrid context
873 -  use - PETSC_TRUE to use the Galerkin process to compute coarse-level operators
874 
875    Options Database Key:
876 $  -pc_mg_galerkin
877 
878    Level: intermediate
879 
880 .keywords: MG, set, Galerkin
881 
882 .seealso: PCMGGetGalerkin()
883 
884 @*/
885 PetscErrorCode PCMGSetGalerkin(PC pc,PetscBool use)
886 {
887   PC_MG        *mg = (PC_MG*)pc->data;
888 
889   PetscFunctionBegin;
890   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
891   mg->galerkin = (PetscInt)use;
892   PetscFunctionReturn(0);
893 }
894 
895 #undef __FUNCT__
896 #define __FUNCT__ "PCMGGetGalerkin"
897 /*@
898    PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
899       A_i-1 = r_i * A_i * r_i^t
900 
901    Not Collective
902 
903    Input Parameter:
904 .  pc - the multigrid context
905 
906    Output Parameter:
907 .  gelerkin - PETSC_TRUE or PETSC_FALSE
908 
909    Options Database Key:
910 $  -pc_mg_galerkin
911 
912    Level: intermediate
913 
914 .keywords: MG, set, Galerkin
915 
916 .seealso: PCMGSetGalerkin()
917 
918 @*/
919 PetscErrorCode  PCMGGetGalerkin(PC pc,PetscBool  *galerkin)
920 {
921   PC_MG        *mg = (PC_MG*)pc->data;
922 
923   PetscFunctionBegin;
924   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
925   *galerkin = (PetscBool)mg->galerkin;
926   PetscFunctionReturn(0);
927 }
928 
929 #undef __FUNCT__
930 #define __FUNCT__ "PCMGSetNumberSmoothDown"
931 /*@
932    PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to
933    use on all levels. Use PCMGGetSmootherDown() to set different
934    pre-smoothing steps on different levels.
935 
936    Logically Collective on PC
937 
938    Input Parameters:
939 +  mg - the multigrid context
940 -  n - the number of smoothing steps
941 
942    Options Database Key:
943 .  -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps
944 
945    Level: advanced
946 
947 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid
948 
949 .seealso: PCMGSetNumberSmoothUp()
950 @*/
951 PetscErrorCode  PCMGSetNumberSmoothDown(PC pc,PetscInt n)
952 {
953   PC_MG          *mg = (PC_MG*)pc->data;
954   PC_MG_Levels   **mglevels = mg->levels;
955   PetscErrorCode ierr;
956   PetscInt       i,levels;
957 
958   PetscFunctionBegin;
959   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
960   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
961   PetscValidLogicalCollectiveInt(pc,n,2);
962   levels = mglevels[0]->levels;
963 
964   for (i=1; i<levels; i++) {
965     /* make sure smoother up and down are different */
966     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
967     ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
968     mg->default_smoothd = n;
969   }
970   PetscFunctionReturn(0);
971 }
972 
973 #undef __FUNCT__
974 #define __FUNCT__ "PCMGSetNumberSmoothUp"
975 /*@
976    PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use
977    on all levels. Use PCMGGetSmootherUp() to set different numbers of
978    post-smoothing steps on different levels.
979 
980    Logically Collective on PC
981 
982    Input Parameters:
983 +  mg - the multigrid context
984 -  n - the number of smoothing steps
985 
986    Options Database Key:
987 .  -pc_mg_smoothup <n> - Sets number of post-smoothing steps
988 
989    Level: advanced
990 
991    Note: this does not set a value on the coarsest grid, since we assume that
992     there is no separate smooth up on the coarsest grid.
993 
994 .keywords: MG, smooth, up, post-smoothing, steps, multigrid
995 
996 .seealso: PCMGSetNumberSmoothDown()
997 @*/
998 PetscErrorCode  PCMGSetNumberSmoothUp(PC pc,PetscInt n)
999 {
1000   PC_MG          *mg = (PC_MG*)pc->data;
1001   PC_MG_Levels   **mglevels = mg->levels;
1002   PetscErrorCode ierr;
1003   PetscInt       i,levels;
1004 
1005   PetscFunctionBegin;
1006   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
1007   if (!mglevels) SETERRQ(((PetscObject)pc)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
1008   PetscValidLogicalCollectiveInt(pc,n,2);
1009   levels = mglevels[0]->levels;
1010 
1011   for (i=1; i<levels; i++) {
1012     /* make sure smoother up and down are different */
1013     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
1014     ierr = KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
1015     mg->default_smoothu = n;
1016   }
1017   PetscFunctionReturn(0);
1018 }
1019 
1020 /* ----------------------------------------------------------------------------------------*/
1021 
1022 /*MC
1023    PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional
1024     information about the coarser grid matrices and restriction/interpolation operators.
1025 
1026    Options Database Keys:
1027 +  -pc_mg_levels <nlevels> - number of levels including finest
1028 .  -pc_mg_cycles v or w
1029 .  -pc_mg_smoothup <n> - number of smoothing steps after interpolation
1030 .  -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator
1031 .  -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default
1032 .  -pc_mg_log - log information about time spent on each level of the solver
1033 .  -pc_mg_monitor - print information on the multigrid convergence
1034 .  -pc_mg_galerkin - use Galerkin process to compute coarser operators, i.e. Acoarse = R A R'
1035 .  -pc_mg_multiplicative_cycles - number of cycles to use as the preconditioner (defaults to 1)
1036 .  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
1037                         to the Socket viewer for reading from MATLAB.
1038 -  -pc_mg_dump_binary - dumps the matrices for each level and the restriction/interpolation matrices
1039                         to the binary output file called binaryoutput
1040 
1041    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
1042 
1043        When run with a single level the smoother options are used on that level NOT the coarse grid solver options
1044 
1045    Level: intermediate
1046 
1047    Concepts: multigrid/multilevel
1048 
1049 .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, PCEXOTIC, PCGAMG, PCML, PCHYPRE
1050            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(),
1051            PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
1052            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
1053            PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
1054 M*/
1055 
1056 EXTERN_C_BEGIN
1057 #undef __FUNCT__
1058 #define __FUNCT__ "PCCreate_MG"
1059 PetscErrorCode  PCCreate_MG(PC pc)
1060 {
1061   PC_MG          *mg;
1062   PetscErrorCode ierr;
1063 
1064   PetscFunctionBegin;
1065   ierr        = PetscNewLog(pc,PC_MG,&mg);CHKERRQ(ierr);
1066   pc->data    = (void*)mg;
1067   mg->nlevels = -1;
1068 
1069   pc->ops->apply          = PCApply_MG;
1070   pc->ops->setup          = PCSetUp_MG;
1071   pc->ops->reset          = PCReset_MG;
1072   pc->ops->destroy        = PCDestroy_MG;
1073   pc->ops->setfromoptions = PCSetFromOptions_MG;
1074   pc->ops->view           = PCView_MG;
1075   PetscFunctionReturn(0);
1076 }
1077 EXTERN_C_END
1078