xref: /petsc/src/ksp/pc/impls/mg/mg.c (revision f22f69f01ec1ca0bb29797ff3752b65f1e1c47db)
1 #define PETSCKSP_DLL
2 
3 /*
4     Defines the multigrid preconditioner interface.
5 */
6 #include "../src/ksp/pc/impls/mg/mgimpl.h"                    /*I "petscmg.h" I*/
7 
8 
9 #undef __FUNCT__
10 #define __FUNCT__ "PCMGMCycle_Private"
11 PetscErrorCode PCMGMCycle_Private(PC pc,PC_MG_Levels **mglevelsin,PCRichardsonConvergedReason *reason)
12 {
13   PC_MG          *mg = (PC_MG*)pc->data;
14   PC_MG_Levels   *mgc,*mglevels = *mglevelsin;
15   PetscErrorCode ierr;
16   PetscInt       cycles = (mglevels->level == 1) ? 1 : (PetscInt) mglevels->cycles;
17 
18   PetscFunctionBegin;
19 
20   if (mg->eventsmoothsolve) {ierr = PetscLogEventBegin(mg->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
21   ierr = KSPSolve(mglevels->smoothd,mglevels->b,mglevels->x);CHKERRQ(ierr);  /* pre-smooth */
22   if (mg->eventsmoothsolve) {ierr = PetscLogEventEnd(mg->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
23   if (mglevels->level) {  /* not the coarsest grid */
24     if (mg->eventresidual) {ierr = PetscLogEventBegin(mg->eventresidual,0,0,0,0);CHKERRQ(ierr);}
25     ierr = (*mglevels->residual)(mglevels->A,mglevels->b,mglevels->x,mglevels->r);CHKERRQ(ierr);
26     if (mg->eventresidual) {ierr = PetscLogEventEnd(mg->eventresidual,0,0,0,0);CHKERRQ(ierr);}
27 
28     /* if on finest level and have convergence criteria set */
29     if (mglevels->level == mglevels->levels-1 && mg->ttol && reason) {
30       PetscReal rnorm;
31       ierr = VecNorm(mglevels->r,NORM_2,&rnorm);CHKERRQ(ierr);
32       if (rnorm <= mg->ttol) {
33         if (rnorm < mg->abstol) {
34           *reason = PCRICHARDSON_CONVERGED_ATOL;
35           ierr = PetscInfo2(pc,"Linear solver has converged. Residual norm %G is less than absolute tolerance %G\n",rnorm,mg->abstol);CHKERRQ(ierr);
36         } else {
37           *reason = PCRICHARDSON_CONVERGED_RTOL;
38           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);
39         }
40         PetscFunctionReturn(0);
41       }
42     }
43 
44     mgc = *(mglevelsin - 1);
45     if (mg->eventinterprestrict) {ierr = PetscLogEventBegin(mg->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
46     ierr = MatRestrict(mglevels->restrct,mglevels->r,mgc->b);CHKERRQ(ierr);
47     if (mg->eventinterprestrict) {ierr = PetscLogEventEnd(mg->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
48     ierr = VecSet(mgc->x,0.0);CHKERRQ(ierr);
49     while (cycles--) {
50       ierr = PCMGMCycle_Private(pc,mglevelsin-1,reason);CHKERRQ(ierr);
51     }
52     if (mg->eventinterprestrict) {ierr = PetscLogEventBegin(mg->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
53     ierr = MatInterpolateAdd(mglevels->interpolate,mgc->x,mglevels->x,mglevels->x);CHKERRQ(ierr);
54     if (mg->eventinterprestrict) {ierr = PetscLogEventEnd(mg->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);}
55     if (mg->eventsmoothsolve) {ierr = PetscLogEventBegin(mg->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
56     ierr = KSPSolve(mglevels->smoothu,mglevels->b,mglevels->x);CHKERRQ(ierr);    /* post smooth */
57     if (mg->eventsmoothsolve) {ierr = PetscLogEventEnd(mg->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);}
58   }
59   PetscFunctionReturn(0);
60 }
61 
62 #undef __FUNCT__
63 #define __FUNCT__ "PCApplyRichardson_MG"
64 static PetscErrorCode PCApplyRichardson_MG(PC pc,Vec b,Vec x,Vec w,PetscReal rtol,PetscReal abstol, PetscReal dtol,PetscInt its,PetscTruth zeroguess,PetscInt *outits,PCRichardsonConvergedReason *reason)
65 {
66   PC_MG          *mg = (PC_MG*)pc->data;
67   PC_MG_Levels   **mglevels = mg->levels;
68   PetscErrorCode ierr;
69   PetscInt       levels = mglevels[0]->levels,i;
70 
71   PetscFunctionBegin;
72   mglevels[levels-1]->b    = b;
73   mglevels[levels-1]->x    = x;
74 
75   mg->rtol = rtol;
76   mg->abstol = abstol;
77   mg->dtol = dtol;
78   if (rtol) {
79     /* compute initial residual norm for relative convergence test */
80     PetscReal rnorm;
81     if (zeroguess) {
82       ierr               = VecNorm(b,NORM_2,&rnorm);CHKERRQ(ierr);
83     } else {
84       ierr               = (*mglevels[levels-1]->residual)(mglevels[levels-1]->A,b,x,w);CHKERRQ(ierr);
85       ierr               = VecNorm(w,NORM_2,&rnorm);CHKERRQ(ierr);
86     }
87     mg->ttol = PetscMax(rtol*rnorm,abstol);
88   } else if (abstol) {
89     mg->ttol = abstol;
90   } else {
91     mg->ttol = 0.0;
92   }
93 
94   /* since smoother is applied to full system, not just residual we need to make sure that smoothers don't
95      stop prematurely do to small residual */
96   for (i=1; i<levels; i++) {
97     ierr = KSPSetTolerances(mglevels[i]->smoothu,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr);
98     if (mglevels[i]->smoothu != mglevels[i]->smoothd) {
99       ierr = KSPSetTolerances(mglevels[i]->smoothd,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr);
100     }
101   }
102 
103   *reason = (PCRichardsonConvergedReason)0;
104   for (i=0; i<its; i++) {
105     ierr = PCMGMCycle_Private(pc,mglevels+levels-1,reason);CHKERRQ(ierr);
106     if (*reason) break;
107   }
108   if (!*reason) *reason = PCRICHARDSON_CONVERGED_ITS;
109   *outits = i;
110   PetscFunctionReturn(0);
111 }
112 
113 #undef __FUNCT__
114 #define __FUNCT__ "PCMGSetLevels"
115 /*@C
116    PCMGSetLevels - Sets the number of levels to use with MG.
117    Must be called before any other MG routine.
118 
119    Collective on PC
120 
121    Input Parameters:
122 +  pc - the preconditioner context
123 .  levels - the number of levels
124 -  comms - optional communicators for each level; this is to allow solving the coarser problems
125            on smaller sets of processors. Use PETSC_NULL_OBJECT for default in Fortran
126 
127    Level: intermediate
128 
129    Notes:
130      If the number of levels is one then the multigrid uses the -mg_levels prefix
131   for setting the level options rather than the -mg_coarse prefix.
132 
133 .keywords: MG, set, levels, multigrid
134 
135 .seealso: PCMGSetType(), PCMGGetLevels()
136 @*/
137 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
138 {
139   PetscErrorCode ierr;
140   PC_MG          *mg = (PC_MG*)pc->data;
141   MPI_Comm       comm = ((PetscObject)pc)->comm;
142   PC_MG_Levels   **mglevels;
143   PetscInt       i;
144   PetscMPIInt    size;
145   const char     *prefix;
146   PC             ipc;
147 
148   PetscFunctionBegin;
149   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
150   if (mg->nlevels > -1) {
151     SETERRQ(PETSC_ERR_ORDER,"Number levels already set for MG\n  make sure that you call PCMGSetLevels() before KSPSetFromOptions()");
152   }
153   if (mg->levels) SETERRQ(PETSC_ERR_PLIB,"Internal error in PETSc, this array should not yet exist");
154 
155   mg->nlevels      = levels;
156   mg->galerkin     = PETSC_FALSE;
157   mg->galerkinused = PETSC_FALSE;
158 
159   ierr = PetscMalloc(levels*sizeof(PC_MG*),&mglevels);CHKERRQ(ierr);
160   ierr = PetscLogObjectMemory(pc,levels*(sizeof(PC_MG*)));CHKERRQ(ierr);
161 
162   ierr = PCGetOptionsPrefix(pc,&prefix);CHKERRQ(ierr);
163 
164   for (i=0; i<levels; i++) {
165     ierr = PetscNewLog(pc,PC_MG_Levels,&mglevels[i]);CHKERRQ(ierr);
166     mglevels[i]->level           = i;
167     mglevels[i]->levels          = levels;
168     mglevels[i]->cycles          = PC_MG_CYCLE_V;
169     mg->default_smoothu = 1;
170     mg->default_smoothd = 1;
171 
172     if (comms) comm = comms[i];
173     ierr = KSPCreate(comm,&mglevels[i]->smoothd);CHKERRQ(ierr);
174     ierr = PetscObjectIncrementTabLevel((PetscObject)mglevels[i]->smoothd,(PetscObject)pc,levels-i);CHKERRQ(ierr);
175     ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, mg->default_smoothd);CHKERRQ(ierr);
176     ierr = KSPSetOptionsPrefix(mglevels[i]->smoothd,prefix);CHKERRQ(ierr);
177 
178     /* do special stuff for coarse grid */
179     if (!i && levels > 1) {
180       ierr = KSPAppendOptionsPrefix(mglevels[0]->smoothd,"mg_coarse_");CHKERRQ(ierr);
181 
182       /* coarse solve is (redundant) LU by default */
183       ierr = KSPSetType(mglevels[0]->smoothd,KSPPREONLY);CHKERRQ(ierr);
184       ierr = KSPGetPC(mglevels[0]->smoothd,&ipc);CHKERRQ(ierr);
185       ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
186       if (size > 1) {
187         ierr = PCSetType(ipc,PCREDUNDANT);CHKERRQ(ierr);
188       } else {
189         ierr = PCSetType(ipc,PCLU);CHKERRQ(ierr);
190       }
191 
192     } else {
193       char tprefix[128];
194       sprintf(tprefix,"mg_levels_%d_",(int)i);
195       ierr = KSPAppendOptionsPrefix(mglevels[i]->smoothd,tprefix);CHKERRQ(ierr);
196     }
197     ierr = PetscLogObjectParent(pc,mglevels[i]->smoothd);CHKERRQ(ierr);
198     mglevels[i]->smoothu    = mglevels[i]->smoothd;
199     mg->rtol                = 0.0;
200     mg->abstol              = 0.0;
201     mg->dtol                = 0.0;
202     mg->ttol                = 0.0;
203     mg->eventsmoothsetup    = 0;
204     mg->eventsmoothsolve    = 0;
205     mg->eventresidual       = 0;
206     mg->eventinterprestrict = 0;
207     mg->cyclesperpcapply    = 1;
208   }
209   mg->am          = PC_MG_MULTIPLICATIVE;
210   mg->levels      = mglevels;
211   pc->ops->applyrichardson = PCApplyRichardson_MG;
212   PetscFunctionReturn(0);
213 }
214 
215 #undef __FUNCT__
216 #define __FUNCT__ "PCDestroy_MG_Private"
217 PetscErrorCode PCDestroy_MG_Private(PC pc)
218 {
219   PC_MG          *mg = (PC_MG*)pc->data;
220   PC_MG_Levels   **mglevels = mg->levels;
221   PetscErrorCode ierr;
222   PetscInt       i,n;
223 
224   PetscFunctionBegin;
225   if (mglevels) {
226     n = mglevels[0]->levels;
227     for (i=0; i<n-1; i++) {
228       if (mglevels[i+1]->r) {ierr = VecDestroy(mglevels[i+1]->r);CHKERRQ(ierr);}
229       if (mglevels[i]->b) {ierr = VecDestroy(mglevels[i]->b);CHKERRQ(ierr);}
230       if (mglevels[i]->x) {ierr = VecDestroy(mglevels[i]->x);CHKERRQ(ierr);}
231       if (mglevels[i+1]->restrct) {ierr = MatDestroy(mglevels[i+1]->restrct);CHKERRQ(ierr);}
232       if (mglevels[i+1]->interpolate) {ierr = MatDestroy(mglevels[i+1]->interpolate);CHKERRQ(ierr);}
233     }
234 
235     for (i=0; i<n; i++) {
236       if (mglevels[i]->smoothd != mglevels[i]->smoothu) {
237 	ierr = KSPDestroy(mglevels[i]->smoothd);CHKERRQ(ierr);
238       }
239       ierr = KSPDestroy(mglevels[i]->smoothu);CHKERRQ(ierr);
240       ierr = PetscFree(mglevels[i]);CHKERRQ(ierr);
241     }
242     ierr = PetscFree(mglevels);CHKERRQ(ierr);
243   }
244   mg->nlevels = -1;
245   mg->levels  = PETSC_NULL;
246   PetscFunctionReturn(0);
247 }
248 
249 #undef __FUNCT__
250 #define __FUNCT__ "PCDestroy_MG"
251 PetscErrorCode PCDestroy_MG(PC pc)
252 {
253   PC_MG          *mg = (PC_MG*)pc->data;
254   PetscErrorCode ierr;
255 
256   PetscFunctionBegin;
257   ierr = PCDestroy_MG_Private(pc);CHKERRQ(ierr);
258   ierr = PetscFree(mg);CHKERRQ(ierr);
259   PetscFunctionReturn(0);
260 }
261 
262 
263 
264 EXTERN PetscErrorCode PCMGACycle_Private(PC,PC_MG_Levels**);
265 EXTERN PetscErrorCode PCMGFCycle_Private(PC,PC_MG_Levels**);
266 EXTERN PetscErrorCode PCMGKCycle_Private(PC,PC_MG_Levels**);
267 
268 /*
269    PCApply_MG - Runs either an additive, multiplicative, Kaskadic
270              or full cycle of multigrid.
271 
272   Note:
273   A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle().
274 */
275 #undef __FUNCT__
276 #define __FUNCT__ "PCApply_MG"
277 static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
278 {
279   PC_MG          *mg = (PC_MG*)pc->data;
280   PC_MG_Levels   **mglevels = mg->levels;
281   PetscErrorCode ierr;
282   PetscInt       levels = mglevels[0]->levels,i;
283 
284   PetscFunctionBegin;
285   mglevels[levels-1]->b = b;
286   mglevels[levels-1]->x = x;
287   if (mg->am == PC_MG_MULTIPLICATIVE) {
288     ierr = VecSet(x,0.0);CHKERRQ(ierr);
289     for (i=0; i<mg->cyclesperpcapply; i++) {
290       ierr = PCMGMCycle_Private(pc,mglevels+levels-1,PETSC_NULL);CHKERRQ(ierr);
291     }
292   }
293   else if (mg->am == PC_MG_ADDITIVE) {
294     ierr = PCMGACycle_Private(pc,mglevels);CHKERRQ(ierr);
295   }
296   else if (mg->am == PC_MG_KASKADE) {
297     ierr = PCMGKCycle_Private(pc,mglevels);CHKERRQ(ierr);
298   }
299   else {
300     ierr = PCMGFCycle_Private(pc,mglevels);CHKERRQ(ierr);
301   }
302   PetscFunctionReturn(0);
303 }
304 
305 
306 #undef __FUNCT__
307 #define __FUNCT__ "PCSetFromOptions_MG"
308 PetscErrorCode PCSetFromOptions_MG(PC pc)
309 {
310   PetscErrorCode ierr;
311   PetscInt       m,levels = 1,cycles;
312   PetscTruth     flg;
313   PC_MG          *mg = (PC_MG*)pc->data;
314   PC_MG_Levels   **mglevels = mg->levels;
315   PCMGType       mgtype;
316   PCMGCycleType  mgctype;
317 
318   PetscFunctionBegin;
319   ierr = PetscOptionsHead("Multigrid options");CHKERRQ(ierr);
320     if (!mglevels) {
321       ierr = PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);CHKERRQ(ierr);
322       ierr = PCMGSetLevels(pc,levels,PETSC_NULL);CHKERRQ(ierr);
323       mglevels = mg->levels;
324     }
325     mgctype = (PCMGCycleType) mglevels[0]->cycles;
326     ierr = PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);CHKERRQ(ierr);
327     if (flg) {
328       ierr = PCMGSetCycleType(pc,mgctype);CHKERRQ(ierr);
329     };
330     flg  = PETSC_FALSE;
331     ierr = PetscOptionsTruth("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",flg,&flg,PETSC_NULL);CHKERRQ(ierr);
332     if (flg) {
333       ierr = PCMGSetGalerkin(pc);CHKERRQ(ierr);
334     }
335     ierr = PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",1,&m,&flg);CHKERRQ(ierr);
336     if (flg) {
337       ierr = PCMGSetNumberSmoothUp(pc,m);CHKERRQ(ierr);
338     }
339     ierr = PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",1,&m,&flg);CHKERRQ(ierr);
340     if (flg) {
341       ierr = PCMGSetNumberSmoothDown(pc,m);CHKERRQ(ierr);
342     }
343     mgtype = mg->am;
344     ierr = PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);CHKERRQ(ierr);
345     if (flg) {
346       ierr = PCMGSetType(pc,mgtype);CHKERRQ(ierr);
347     }
348     if (mg->am == PC_MG_MULTIPLICATIVE) {
349       ierr = PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGSetLevels",mg->cyclesperpcapply,&cycles,&flg);CHKERRQ(ierr);
350       if (flg) {
351 	ierr = PCMGMultiplicativeSetCycles(pc,cycles);CHKERRQ(ierr);
352       }
353     }
354     flg  = PETSC_FALSE;
355     ierr = PetscOptionsTruth("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,PETSC_NULL);CHKERRQ(ierr);
356     if (flg) {
357       PetscInt i;
358       char     eventname[128];
359       if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
360       levels = mglevels[0]->levels;
361       for (i=0; i<levels; i++) {
362         sprintf(eventname,"MGSetup Level %d",(int)i);
363         ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mg->eventsmoothsetup);CHKERRQ(ierr);
364         sprintf(eventname,"MGSmooth Level %d",(int)i);
365         ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mg->eventsmoothsolve);CHKERRQ(ierr);
366         if (i) {
367           sprintf(eventname,"MGResid Level %d",(int)i);
368           ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mg->eventresidual);CHKERRQ(ierr);
369           sprintf(eventname,"MGInterp Level %d",(int)i);
370           ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mg->eventinterprestrict);CHKERRQ(ierr);
371         }
372       }
373     }
374   ierr = PetscOptionsTail();CHKERRQ(ierr);
375   PetscFunctionReturn(0);
376 }
377 
378 const char *PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0};
379 const char *PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",0};
380 
381 #undef __FUNCT__
382 #define __FUNCT__ "PCView_MG"
383 PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
384 {
385   PC_MG          *mg = (PC_MG*)pc->data;
386   PC_MG_Levels   **mglevels = mg->levels;
387   PetscErrorCode ierr;
388   PetscInt       levels = mglevels[0]->levels,i;
389   PetscTruth     iascii;
390 
391   PetscFunctionBegin;
392   ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr);
393   if (iascii) {
394     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);
395     if (mg->am == PC_MG_MULTIPLICATIVE) {
396       ierr = PetscViewerASCIIPrintf(viewer,"    Cycles per PCApply=%d\n",mg->cyclesperpcapply);CHKERRQ(ierr);
397     }
398     if (mg->galerkin) {
399       ierr = PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr);
400     }
401     for (i=0; i<levels; i++) {
402       if (!i) {
403         ierr = PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level %D presmooths=%D postsmooths=%D -----\n",i,mg->default_smoothd,mg->default_smoothu);CHKERRQ(ierr);
404       } else {
405         ierr = PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D smooths=%D --------------------\n",i,mg->default_smoothd);CHKERRQ(ierr);
406       }
407       ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
408       ierr = KSPView(mglevels[i]->smoothd,viewer);CHKERRQ(ierr);
409       ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
410       if (i && mglevels[i]->smoothd == mglevels[i]->smoothu) {
411         ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");CHKERRQ(ierr);
412       } else if (i){
413         ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D smooths=%D --------------------\n",i,mg->default_smoothu);CHKERRQ(ierr);
414         ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
415         ierr = KSPView(mglevels[i]->smoothu,viewer);CHKERRQ(ierr);
416         ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
417       }
418     }
419   } else {
420     SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported for PCMG",((PetscObject)viewer)->type_name);
421   }
422   PetscFunctionReturn(0);
423 }
424 
425 /*
426     Calls setup for the KSP on each level
427 */
428 #undef __FUNCT__
429 #define __FUNCT__ "PCSetUp_MG"
430 PetscErrorCode PCSetUp_MG(PC pc)
431 {
432   PC_MG                   *mg = (PC_MG*)pc->data;
433   PC_MG_Levels            **mglevels = mg->levels;
434   PetscErrorCode          ierr;
435   PetscInt                i,n = mglevels[0]->levels;
436   PC                      cpc,mpc;
437   PetscTruth              preonly,lu,redundant,cholesky,monitor = PETSC_FALSE,dump = PETSC_FALSE,opsset;
438   PetscViewerASCIIMonitor ascii;
439   PetscViewer             viewer = PETSC_NULL;
440   MPI_Comm                comm;
441   Mat                     dA,dB;
442   MatStructure            uflag;
443   Vec                     tvec;
444   DM                      *dms;
445 
446   PetscFunctionBegin;
447 
448   /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */
449   /* so use those from global PC */
450   /* Is this what we always want? What if user wants to keep old one? */
451   ierr = KSPGetOperatorsSet(mglevels[n-1]->smoothd,PETSC_NULL,&opsset);CHKERRQ(ierr);
452   ierr = KSPGetPC(mglevels[0]->smoothd,&cpc);CHKERRQ(ierr);
453   ierr = KSPGetPC(mglevels[n-1]->smoothd,&mpc);CHKERRQ(ierr);
454   if (!opsset || ((cpc->setupcalled == 1) && (mpc->setupcalled == 2)) || ((mpc == cpc) && (mpc->setupcalled == 2))) {
455     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);
456     ierr = KSPSetOperators(mglevels[n-1]->smoothd,pc->mat,pc->pmat,pc->flag);CHKERRQ(ierr);
457   }
458 
459   if (pc->dm && !pc->setupcalled) {
460     /* construct the interpolation from the DMs */
461     Mat p;
462     ierr = PetscMalloc(n*sizeof(DM),&dms);CHKERRQ(ierr);
463     dms[n-1] = pc->dm;
464     for (i=n-2; i>-1; i--) {
465       ierr = DMCoarsen(dms[i+1],PETSC_NULL,&dms[i]);CHKERRQ(ierr);
466       ierr = DMSetFunction(dms[i],0);
467       ierr = DMSetInitialGuess(dms[i],0);
468       ierr = DMGetInterpolation(dms[i],dms[i+1],&p,PETSC_NULL);CHKERRQ(ierr);
469       ierr = PCMGSetInterpolation(pc,i+1,p);CHKERRQ(ierr);
470       ierr = MatDestroy(p);CHKERRQ(ierr);
471     }
472 
473     if (!mg->galerkin) {
474       /* each coarse level gets its DM */
475       for (i=n-2; i>-1; i--) {
476         ierr = KSPSetDM(mglevels[i]->smoothd,dms[i]);CHKERRQ(ierr);
477       }
478     }
479 
480     for (i=n-2; i>-1; i--) {
481       ierr = DMDestroy(dms[i]);CHKERRQ(ierr);
482     }
483     ierr = PetscFree(dms);CHKERRQ(ierr);
484   }
485 
486   if (mg->galerkin) {
487     Mat B;
488     mg->galerkinused = PETSC_TRUE;
489     /* currently only handle case where mat and pmat are the same on coarser levels */
490     ierr = KSPGetOperators(mglevels[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr);
491     if (!pc->setupcalled) {
492       for (i=n-2; i>-1; i--) {
493         ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr);
494         ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
495 	if (i != n-2) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);}
496         dB   = B;
497       }
498       ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);
499     } else {
500       for (i=n-2; i>-1; i--) {
501         ierr = KSPGetOperators(mglevels[i]->smoothd,PETSC_NULL,&B,PETSC_NULL);CHKERRQ(ierr);
502         ierr = MatPtAP(dB,mglevels[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr);
503         ierr = KSPSetOperators(mglevels[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
504         dB   = B;
505       }
506     }
507   }
508 
509   if (!pc->setupcalled) {
510     ierr = PetscOptionsGetTruth(0,"-pc_mg_monitor",&monitor,PETSC_NULL);CHKERRQ(ierr);
511 
512     for (i=0; i<n; i++) {
513       if (monitor) {
514         ierr = PetscObjectGetComm((PetscObject)mglevels[i]->smoothd,&comm);CHKERRQ(ierr);
515         ierr = PetscViewerASCIIMonitorCreate(comm,"stdout",n-i,&ascii);CHKERRQ(ierr);
516         ierr = KSPMonitorSet(mglevels[i]->smoothd,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);CHKERRQ(ierr);
517       }
518       ierr = KSPSetFromOptions(mglevels[i]->smoothd);CHKERRQ(ierr);
519     }
520     for (i=1; i<n; i++) {
521       if (mglevels[i]->smoothu && (mglevels[i]->smoothu != mglevels[i]->smoothd)) {
522         if (monitor) {
523           ierr = PetscObjectGetComm((PetscObject)mglevels[i]->smoothu,&comm);CHKERRQ(ierr);
524           ierr = PetscViewerASCIIMonitorCreate(comm,"stdout",n-i,&ascii);CHKERRQ(ierr);
525           ierr = KSPMonitorSet(mglevels[i]->smoothu,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);CHKERRQ(ierr);
526         }
527         ierr = KSPSetFromOptions(mglevels[i]->smoothu);CHKERRQ(ierr);
528       }
529     }
530     for (i=1; i<n; i++) {
531       if (!mglevels[i]->residual) {
532         Mat mat;
533         ierr = KSPGetOperators(mglevels[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);CHKERRQ(ierr);
534         ierr = PCMGSetResidual(pc,i,PCMGDefaultResidual,mat);CHKERRQ(ierr);
535       }
536       if (mglevels[i]->restrct && !mglevels[i]->interpolate) {
537         ierr = PCMGSetInterpolation(pc,i,mglevels[i]->restrct);CHKERRQ(ierr);
538       }
539       if (!mglevels[i]->restrct && mglevels[i]->interpolate) {
540         ierr = PCMGSetRestriction(pc,i,mglevels[i]->interpolate);CHKERRQ(ierr);
541       }
542 #if defined(PETSC_USE_DEBUG)
543       if (!mglevels[i]->restrct || !mglevels[i]->interpolate) {
544         SETERRQ1(PETSC_ERR_ARG_WRONGSTATE,"Need to set restriction or interpolation on level %d",(int)i);
545       }
546 #endif
547     }
548     for (i=0; i<n-1; i++) {
549       if (!mglevels[i]->b) {
550         Vec *vec;
551         ierr = KSPGetVecs(mglevels[i]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr);
552         ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr);
553         ierr = VecDestroy(*vec);CHKERRQ(ierr);
554         ierr = PetscFree(vec);CHKERRQ(ierr);
555       }
556       if (!mglevels[i]->r && i) {
557         ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr);
558         ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr);
559         ierr = VecDestroy(tvec);CHKERRQ(ierr);
560       }
561       if (!mglevels[i]->x) {
562         ierr = VecDuplicate(mglevels[i]->b,&tvec);CHKERRQ(ierr);
563         ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr);
564         ierr = VecDestroy(tvec);CHKERRQ(ierr);
565       }
566     }
567     if (n != 1 && !mglevels[n-1]->r) {
568       /* PCMGSetR() on the finest level if user did not supply it */
569       Vec *vec;
570       ierr = KSPGetVecs(mglevels[n-1]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr);
571       ierr = PCMGSetR(pc,n-1,*vec);CHKERRQ(ierr);
572       ierr = VecDestroy(*vec);CHKERRQ(ierr);
573       ierr = PetscFree(vec);CHKERRQ(ierr);
574     }
575   }
576 
577 
578   for (i=1; i<n; i++) {
579     if (mglevels[i]->smoothu == mglevels[i]->smoothd) {
580       /* if doing only down then initial guess is zero */
581       ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr);
582     }
583     if (mg->eventsmoothsetup) {ierr = PetscLogEventBegin(mg->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
584     ierr = KSPSetUp(mglevels[i]->smoothd);CHKERRQ(ierr);
585     if (mg->eventsmoothsetup) {ierr = PetscLogEventEnd(mg->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
586   }
587   for (i=1; i<n; i++) {
588     if (mglevels[i]->smoothu && mglevels[i]->smoothu != mglevels[i]->smoothd) {
589       Mat          downmat,downpmat;
590       MatStructure matflag;
591       PetscTruth   opsset;
592 
593       /* check if operators have been set for up, if not use down operators to set them */
594       ierr = KSPGetOperatorsSet(mglevels[i]->smoothu,&opsset,PETSC_NULL);CHKERRQ(ierr);
595       if (!opsset) {
596         ierr = KSPGetOperators(mglevels[i]->smoothd,&downmat,&downpmat,&matflag);CHKERRQ(ierr);
597         ierr = KSPSetOperators(mglevels[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr);
598       }
599 
600       ierr = KSPSetInitialGuessNonzero(mglevels[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr);
601       if (mg->eventsmoothsetup) {ierr = PetscLogEventBegin(mg->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
602       ierr = KSPSetUp(mglevels[i]->smoothu);CHKERRQ(ierr);
603       if (mg->eventsmoothsetup) {ierr = PetscLogEventEnd(mg->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
604     }
605   }
606 
607   /*
608       If coarse solver is not direct method then DO NOT USE preonly
609   */
610   ierr = PetscTypeCompare((PetscObject)mglevels[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr);
611   if (preonly) {
612     ierr = PetscTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr);
613     ierr = PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr);
614     ierr = PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr);
615     if (!lu && !redundant && !cholesky) {
616       ierr = KSPSetType(mglevels[0]->smoothd,KSPGMRES);CHKERRQ(ierr);
617     }
618   }
619 
620   if (!pc->setupcalled) {
621     if (monitor) {
622       ierr = PetscObjectGetComm((PetscObject)mglevels[0]->smoothd,&comm);CHKERRQ(ierr);
623       ierr = PetscViewerASCIIMonitorCreate(comm,"stdout",n,&ascii);CHKERRQ(ierr);
624       ierr = KSPMonitorSet(mglevels[0]->smoothd,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);CHKERRQ(ierr);
625     }
626     ierr = KSPSetFromOptions(mglevels[0]->smoothd);CHKERRQ(ierr);
627   }
628 
629   if (mg->eventsmoothsetup) {ierr = PetscLogEventBegin(mg->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
630   ierr = KSPSetUp(mglevels[0]->smoothd);CHKERRQ(ierr);
631   if (mg->eventsmoothsetup) {ierr = PetscLogEventEnd(mg->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);}
632 
633   /*
634      Dump the interpolation/restriction matrices plus the
635    Jacobian/stiffness on each level. This allows Matlab users to
636    easily check if the Galerkin condition A_c = R A_f R^T is satisfied.
637 
638    Only support one or the other at the same time.
639   */
640 #if defined(PETSC_USE_SOCKET_VIEWER)
641   ierr = PetscOptionsGetTruth(((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,PETSC_NULL);CHKERRQ(ierr);
642   if (dump) {
643     viewer = PETSC_VIEWER_SOCKET_(((PetscObject)pc)->comm);
644   }
645   dump = PETSC_FALSE;
646 #endif
647   ierr = PetscOptionsGetTruth(((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,PETSC_NULL);CHKERRQ(ierr);
648   if (dump) {
649     viewer = PETSC_VIEWER_BINARY_(((PetscObject)pc)->comm);
650   }
651 
652   if (viewer) {
653     for (i=1; i<n; i++) {
654       ierr = MatView(mglevels[i]->restrct,viewer);CHKERRQ(ierr);
655     }
656     for (i=0; i<n; i++) {
657       ierr = KSPGetPC(mglevels[i]->smoothd,&pc);CHKERRQ(ierr);
658       ierr = MatView(pc->mat,viewer);CHKERRQ(ierr);
659     }
660   }
661   PetscFunctionReturn(0);
662 }
663 
664 /* -------------------------------------------------------------------------------------*/
665 
666 #undef __FUNCT__
667 #define __FUNCT__ "PCMGGetLevels"
668 /*@
669    PCMGGetLevels - Gets the number of levels to use with MG.
670 
671    Not Collective
672 
673    Input Parameter:
674 .  pc - the preconditioner context
675 
676    Output parameter:
677 .  levels - the number of levels
678 
679    Level: advanced
680 
681 .keywords: MG, get, levels, multigrid
682 
683 .seealso: PCMGSetLevels()
684 @*/
685 PetscErrorCode PETSCKSP_DLLEXPORT PCMGGetLevels(PC pc,PetscInt *levels)
686 {
687   PC_MG *mg = (PC_MG*)pc->data;
688 
689   PetscFunctionBegin;
690   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
691   PetscValidIntPointer(levels,2);
692   *levels = mg->nlevels;
693   PetscFunctionReturn(0);
694 }
695 
696 #undef __FUNCT__
697 #define __FUNCT__ "PCMGSetType"
698 /*@
699    PCMGSetType - Determines the form of multigrid to use:
700    multiplicative, additive, full, or the Kaskade algorithm.
701 
702    Collective on PC
703 
704    Input Parameters:
705 +  pc - the preconditioner context
706 -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
707    PC_MG_FULL, PC_MG_KASKADE
708 
709    Options Database Key:
710 .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
711    additive, full, kaskade
712 
713    Level: advanced
714 
715 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid
716 
717 .seealso: PCMGSetLevels()
718 @*/
719 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetType(PC pc,PCMGType form)
720 {
721   PC_MG                   *mg = (PC_MG*)pc->data;
722 
723   PetscFunctionBegin;
724   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
725   mg->am = form;
726   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
727   else pc->ops->applyrichardson = 0;
728   PetscFunctionReturn(0);
729 }
730 
731 #undef __FUNCT__
732 #define __FUNCT__ "PCMGSetCycleType"
733 /*@
734    PCMGSetCycleType - Sets the type cycles to use.  Use PCMGSetCycleTypeOnLevel() for more
735    complicated cycling.
736 
737    Collective on PC
738 
739    Input Parameters:
740 +  pc - the multigrid context
741 -  PC_MG_CYCLE_V or PC_MG_CYCLE_W
742 
743    Options Database Key:
744 $  -pc_mg_cycle_type v or w
745 
746    Level: advanced
747 
748 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
749 
750 .seealso: PCMGSetCycleTypeOnLevel()
751 @*/
752 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetCycleType(PC pc,PCMGCycleType n)
753 {
754   PC_MG        *mg = (PC_MG*)pc->data;
755   PC_MG_Levels **mglevels = mg->levels;
756   PetscInt     i,levels;
757 
758   PetscFunctionBegin;
759   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
760   if (!mglevels) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
761   levels = mglevels[0]->levels;
762 
763   for (i=0; i<levels; i++) {
764     mglevels[i]->cycles  = n;
765   }
766   PetscFunctionReturn(0);
767 }
768 
769 #undef __FUNCT__
770 #define __FUNCT__ "PCMGMultiplicativeSetCycles"
771 /*@
772    PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step
773          of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used
774 
775    Collective on PC
776 
777    Input Parameters:
778 +  pc - the multigrid context
779 -  n - number of cycles (default is 1)
780 
781    Options Database Key:
782 $  -pc_mg_multiplicative_cycles n
783 
784    Level: advanced
785 
786    Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType()
787 
788 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
789 
790 .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType()
791 @*/
792 PetscErrorCode PETSCKSP_DLLEXPORT PCMGMultiplicativeSetCycles(PC pc,PetscInt n)
793 {
794   PC_MG        *mg = (PC_MG*)pc->data;
795   PC_MG_Levels **mglevels = mg->levels;
796   PetscInt     i,levels;
797 
798   PetscFunctionBegin;
799   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
800   if (!mglevels) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
801   levels = mglevels[0]->levels;
802 
803   for (i=0; i<levels; i++) {
804     mg->cyclesperpcapply  = n;
805   }
806   PetscFunctionReturn(0);
807 }
808 
809 #undef __FUNCT__
810 #define __FUNCT__ "PCMGSetGalerkin"
811 /*@
812    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
813       finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t
814 
815    Collective on PC
816 
817    Input Parameters:
818 .  pc - the multigrid context
819 
820    Options Database Key:
821 $  -pc_mg_galerkin
822 
823    Level: intermediate
824 
825 .keywords: MG, set, Galerkin
826 
827 .seealso: PCMGGetGalerkin()
828 
829 @*/
830 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetGalerkin(PC pc)
831 {
832   PC_MG        *mg = (PC_MG*)pc->data;
833 
834   PetscFunctionBegin;
835   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
836   mg->galerkin = PETSC_TRUE;
837   PetscFunctionReturn(0);
838 }
839 
840 #undef __FUNCT__
841 #define __FUNCT__ "PCMGGetGalerkin"
842 /*@
843    PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
844       A_i-1 = r_i * A_i * r_i^t
845 
846    Not Collective
847 
848    Input Parameter:
849 .  pc - the multigrid context
850 
851    Output Parameter:
852 .  gelerkin - PETSC_TRUE or PETSC_FALSE
853 
854    Options Database Key:
855 $  -pc_mg_galerkin
856 
857    Level: intermediate
858 
859 .keywords: MG, set, Galerkin
860 
861 .seealso: PCMGSetGalerkin()
862 
863 @*/
864 PetscErrorCode PETSCKSP_DLLEXPORT PCMGGetGalerkin(PC pc,PetscTruth *galerkin)
865 {
866   PC_MG        *mg = (PC_MG*)pc->data;
867 
868   PetscFunctionBegin;
869   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
870   *galerkin = mg->galerkin;
871   PetscFunctionReturn(0);
872 }
873 
874 #undef __FUNCT__
875 #define __FUNCT__ "PCMGSetNumberSmoothDown"
876 /*@
877    PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to
878    use on all levels. Use PCMGGetSmootherDown() to set different
879    pre-smoothing steps on different levels.
880 
881    Collective on PC
882 
883    Input Parameters:
884 +  mg - the multigrid context
885 -  n - the number of smoothing steps
886 
887    Options Database Key:
888 .  -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps
889 
890    Level: advanced
891 
892 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid
893 
894 .seealso: PCMGSetNumberSmoothUp()
895 @*/
896 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothDown(PC pc,PetscInt n)
897 {
898   PC_MG          *mg = (PC_MG*)pc->data;
899   PC_MG_Levels   **mglevels = mg->levels;
900   PetscErrorCode ierr;
901   PetscInt       i,levels;
902 
903   PetscFunctionBegin;
904   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
905   if (!mglevels) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
906   levels = mglevels[0]->levels;
907 
908   for (i=1; i<levels; i++) {
909     /* make sure smoother up and down are different */
910     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
911     ierr = KSPSetTolerances(mglevels[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
912     mg->default_smoothd = n;
913   }
914   PetscFunctionReturn(0);
915 }
916 
917 #undef __FUNCT__
918 #define __FUNCT__ "PCMGSetNumberSmoothUp"
919 /*@
920    PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use
921    on all levels. Use PCMGGetSmootherUp() to set different numbers of
922    post-smoothing steps on different levels.
923 
924    Collective on PC
925 
926    Input Parameters:
927 +  mg - the multigrid context
928 -  n - the number of smoothing steps
929 
930    Options Database Key:
931 .  -pc_mg_smoothup <n> - Sets number of post-smoothing steps
932 
933    Level: advanced
934 
935    Note: this does not set a value on the coarsest grid, since we assume that
936     there is no separate smooth up on the coarsest grid.
937 
938 .keywords: MG, smooth, up, post-smoothing, steps, multigrid
939 
940 .seealso: PCMGSetNumberSmoothDown()
941 @*/
942 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothUp(PC pc,PetscInt n)
943 {
944   PC_MG          *mg = (PC_MG*)pc->data;
945   PC_MG_Levels   **mglevels = mg->levels;
946   PetscErrorCode ierr;
947   PetscInt       i,levels;
948 
949   PetscFunctionBegin;
950   PetscValidHeaderSpecific(pc,PC_CLASSID,1);
951   if (!mglevels) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
952   levels = mglevels[0]->levels;
953 
954   for (i=1; i<levels; i++) {
955     /* make sure smoother up and down are different */
956     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
957     ierr = KSPSetTolerances(mglevels[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
958     mg->default_smoothu = n;
959   }
960   PetscFunctionReturn(0);
961 }
962 
963 /* ----------------------------------------------------------------------------------------*/
964 
965 /*MC
966    PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional
967     information about the coarser grid matrices and restriction/interpolation operators.
968 
969    Options Database Keys:
970 +  -pc_mg_levels <nlevels> - number of levels including finest
971 .  -pc_mg_cycles v or w
972 .  -pc_mg_smoothup <n> - number of smoothing steps after interpolation
973 .  -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator
974 .  -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default
975 .  -pc_mg_log - log information about time spent on each level of the solver
976 .  -pc_mg_monitor - print information on the multigrid convergence
977 .  -pc_mg_galerkin - use Galerkin process to compute coarser operators
978 -  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
979                         to the Socket viewer for reading from Matlab.
980 
981    Notes:
982 
983    Level: intermediate
984 
985    Concepts: multigrid/multilevel
986 
987 .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType,
988            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(),
989            PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
990            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
991            PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
992 M*/
993 
994 EXTERN_C_BEGIN
995 #undef __FUNCT__
996 #define __FUNCT__ "PCCreate_MG"
997 PetscErrorCode PETSCKSP_DLLEXPORT PCCreate_MG(PC pc)
998 {
999   PC_MG          *mg;
1000   PetscErrorCode ierr;
1001 
1002   PetscFunctionBegin;
1003   ierr        = PetscNewLog(pc,PC_MG,&mg);CHKERRQ(ierr);
1004   pc->data    = (void*)mg;
1005   mg->nlevels = -1;
1006 
1007   pc->ops->apply          = PCApply_MG;
1008   pc->ops->setup          = PCSetUp_MG;
1009   pc->ops->destroy        = PCDestroy_MG;
1010   pc->ops->setfromoptions = PCSetFromOptions_MG;
1011   pc->ops->view           = PCView_MG;
1012   PetscFunctionReturn(0);
1013 }
1014 EXTERN_C_END
1015