xref: /petsc/src/ksp/pc/impls/mg/mg.c (revision e2df7a95c5ea77c899beea10ff9effd6061e7c8f)
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_MG **mglevels,PetscTruth *converged)
12 {
13   PC_MG          *mg = *mglevels,*mgc;
14   PetscErrorCode ierr;
15   PetscInt       cycles = mg->cycles;
16 
17   PetscFunctionBegin;
18   if (converged) *converged = PETSC_FALSE;
19 
20   if (mg->eventsolve) {ierr = PetscLogEventBegin(mg->eventsolve,0,0,0,0);CHKERRQ(ierr);}
21   ierr = KSPSolve(mg->smoothd,mg->b,mg->x);CHKERRQ(ierr);
22   if (mg->eventsolve) {ierr = PetscLogEventEnd(mg->eventsolve,0,0,0,0);CHKERRQ(ierr);}
23   if (mg->level) {  /* not the coarsest grid */
24     ierr = (*mg->residual)(mg->A,mg->b,mg->x,mg->r);CHKERRQ(ierr);
25 
26     /* if on finest level and have convergence criteria set */
27     if (mg->level == mg->levels-1 && mg->ttol) {
28       PetscReal rnorm;
29       ierr = VecNorm(mg->r,NORM_2,&rnorm);CHKERRQ(ierr);
30       if (rnorm <= mg->ttol) {
31         *converged = PETSC_TRUE;
32         if (rnorm < mg->abstol) {
33           ierr = PetscLogInfo((0,"PCMGMCycle_Private:Linear solver has converged. Residual norm %g is less than absolute tolerance %g\n",rnorm,mg->abstol));CHKERRQ(ierr);
34         } else {
35           ierr = PetscLogInfo((0,"PCMGMCycle_Private:Linear solver has converged. Residual norm %g is less than relative tolerance times initial residual norm %g\n",rnorm,mg->ttol));CHKERRQ(ierr);
36         }
37         PetscFunctionReturn(0);
38       }
39     }
40 
41     mgc = *(mglevels - 1);
42     ierr = MatRestrict(mg->restrct,mg->r,mgc->b);CHKERRQ(ierr);
43     ierr = VecSet(mgc->x,0.0);CHKERRQ(ierr);
44     while (cycles--) {
45       ierr = PCMGMCycle_Private(mglevels-1,converged);CHKERRQ(ierr);
46     }
47     ierr = MatInterpolateAdd(mg->interpolate,mgc->x,mg->x,mg->x);CHKERRQ(ierr);
48     if (mg->eventsolve) {ierr = PetscLogEventBegin(mg->eventsolve,0,0,0,0);CHKERRQ(ierr);}
49     ierr = KSPSolve(mg->smoothu,mg->b,mg->x);CHKERRQ(ierr);
50     if (mg->eventsolve) {ierr = PetscLogEventEnd(mg->eventsolve,0,0,0,0);CHKERRQ(ierr);}
51   }
52   PetscFunctionReturn(0);
53 }
54 
55 /*
56        PCMGCreate_Private - Creates a PC_MG structure for use with the
57                multigrid code. Level 0 is the coarsest. (But the
58                finest level is stored first in the array).
59 
60 */
61 #undef __FUNCT__
62 #define __FUNCT__ "PCMGCreate_Private"
63 static PetscErrorCode PCMGCreate_Private(MPI_Comm comm,PetscInt levels,PC pc,MPI_Comm *comms,PC_MG ***result)
64 {
65   PC_MG          **mg;
66   PetscErrorCode ierr;
67   PetscInt       i;
68   PetscMPIInt    size;
69   const char     *prefix;
70   PC             ipc;
71 
72   PetscFunctionBegin;
73   ierr = PetscMalloc(levels*sizeof(PC_MG*),&mg);CHKERRQ(ierr);
74   ierr = PetscLogObjectMemory(pc,levels*(sizeof(PC_MG*)+sizeof(PC_MG)));CHKERRQ(ierr);
75 
76   ierr = PCGetOptionsPrefix(pc,&prefix);CHKERRQ(ierr);
77 
78   for (i=0; i<levels; i++) {
79     ierr = PetscNew(PC_MG,&mg[i]);CHKERRQ(ierr);
80     mg[i]->level           = i;
81     mg[i]->levels          = levels;
82     mg[i]->cycles          = 1;
83     mg[i]->galerkin        = PETSC_FALSE;
84     mg[i]->galerkinused    = PETSC_FALSE;
85     mg[i]->default_smoothu = 1;
86     mg[i]->default_smoothd = 1;
87 
88     if (comms) comm = comms[i];
89     ierr = KSPCreate(comm,&mg[i]->smoothd);CHKERRQ(ierr);
90     ierr = KSPSetTolerances(mg[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, mg[i]->default_smoothd);CHKERRQ(ierr);
91     ierr = KSPSetOptionsPrefix(mg[i]->smoothd,prefix);CHKERRQ(ierr);
92 
93     /* do special stuff for coarse grid */
94     if (!i && levels > 1) {
95       ierr = KSPAppendOptionsPrefix(mg[0]->smoothd,"mg_coarse_");CHKERRQ(ierr);
96 
97       /* coarse solve is (redundant) LU by default */
98       ierr = KSPSetType(mg[0]->smoothd,KSPPREONLY);CHKERRQ(ierr);
99       ierr = KSPGetPC(mg[0]->smoothd,&ipc);CHKERRQ(ierr);
100       ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
101       if (size > 1) {
102         ierr = PCSetType(ipc,PCREDUNDANT);CHKERRQ(ierr);
103         ierr = PCRedundantGetPC(ipc,&ipc);CHKERRQ(ierr);
104       }
105       ierr = PCSetType(ipc,PCLU);CHKERRQ(ierr);
106 
107     } else {
108       char tprefix[128];
109       sprintf(tprefix,"mg_levels_%d_",(int)i);
110       ierr = KSPAppendOptionsPrefix(mg[i]->smoothd,tprefix);CHKERRQ(ierr);
111     }
112     ierr = PetscLogObjectParent(pc,mg[i]->smoothd);CHKERRQ(ierr);
113     mg[i]->smoothu         = mg[i]->smoothd;
114     mg[i]->rtol = 0.0;
115     mg[i]->abstol = 0.0;
116     mg[i]->dtol = 0.0;
117     mg[i]->ttol = 0.0;
118     mg[i]->eventsetup = 0;
119     mg[i]->eventsolve = 0;
120   }
121   *result = mg;
122   PetscFunctionReturn(0);
123 }
124 
125 #undef __FUNCT__
126 #define __FUNCT__ "PCDestroy_MG"
127 static PetscErrorCode PCDestroy_MG(PC pc)
128 {
129   PC_MG          **mg = (PC_MG**)pc->data;
130   PetscErrorCode ierr;
131   PetscInt       i,n = mg[0]->levels;
132 
133   PetscFunctionBegin;
134   if (mg[0]->galerkinused) {
135     Mat B;
136     for (i=0; i<n-1; i++) {
137       ierr = KSPGetOperators(mg[i]->smoothd,0,&B,0);CHKERRQ(ierr);
138       ierr = MatDestroy(B);CHKERRQ(ierr);
139     }
140   }
141 
142   for (i=0; i<n-1; i++) {
143     if (mg[i+1]->r) {ierr = VecDestroy(mg[i+1]->r);CHKERRQ(ierr);}
144     if (mg[i]->b) {ierr = VecDestroy(mg[i]->b);CHKERRQ(ierr);}
145     if (mg[i]->x) {ierr = VecDestroy(mg[i]->x);CHKERRQ(ierr);}
146     if (mg[i+1]->restrct) {ierr = MatDestroy(mg[i+1]->restrct);CHKERRQ(ierr);}
147     if (mg[i+1]->interpolate) {ierr = MatDestroy(mg[i+1]->interpolate);CHKERRQ(ierr);}
148   }
149 
150   for (i=0; i<n; i++) {
151     if (mg[i]->smoothd != mg[i]->smoothu) {
152       ierr = KSPDestroy(mg[i]->smoothd);CHKERRQ(ierr);
153     }
154     ierr = KSPDestroy(mg[i]->smoothu);CHKERRQ(ierr);
155     ierr = PetscFree(mg[i]);CHKERRQ(ierr);
156   }
157   ierr = PetscFree(mg);CHKERRQ(ierr);
158   PetscFunctionReturn(0);
159 }
160 
161 
162 
163 EXTERN PetscErrorCode PCMGACycle_Private(PC_MG**);
164 EXTERN PetscErrorCode PCMGFCycle_Private(PC_MG**);
165 EXTERN PetscErrorCode PCMGKCycle_Private(PC_MG**);
166 
167 /*
168    PCApply_MG - Runs either an additive, multiplicative, Kaskadic
169              or full cycle of multigrid.
170 
171   Note:
172   A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle().
173 */
174 #undef __FUNCT__
175 #define __FUNCT__ "PCApply_MG"
176 static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
177 {
178   PC_MG          **mg = (PC_MG**)pc->data;
179   PetscErrorCode ierr;
180   PetscInt       levels = mg[0]->levels;
181 
182   PetscFunctionBegin;
183   mg[levels-1]->b = b;
184   mg[levels-1]->x = x;
185   if (!mg[levels-1]->r && mg[0]->am == PC_MG_ADDITIVE) {
186     Vec tvec;
187     ierr = VecDuplicate(mg[levels-1]->b,&tvec);CHKERRQ(ierr);
188     ierr = PCMGSetR(pc,levels-1,tvec);CHKERRQ(ierr);
189     ierr = VecDestroy(tvec);CHKERRQ(ierr);
190   }
191   if (mg[0]->am == PC_MG_MULTIPLICATIVE) {
192     ierr = VecSet(x,0.0);CHKERRQ(ierr);
193     ierr = PCMGMCycle_Private(mg+levels-1,PETSC_NULL);CHKERRQ(ierr);
194   }
195   else if (mg[0]->am == PC_MG_ADDITIVE) {
196     ierr = PCMGACycle_Private(mg);CHKERRQ(ierr);
197   }
198   else if (mg[0]->am == PC_MG_KASKADE) {
199     ierr = PCMGKCycle_Private(mg);CHKERRQ(ierr);
200   }
201   else {
202     ierr = PCMGFCycle_Private(mg);CHKERRQ(ierr);
203   }
204   PetscFunctionReturn(0);
205 }
206 
207 #undef __FUNCT__
208 #define __FUNCT__ "PCApplyRichardson_MG"
209 static PetscErrorCode PCApplyRichardson_MG(PC pc,Vec b,Vec x,Vec w,PetscReal rtol,PetscReal abstol, PetscReal dtol,PetscInt its)
210 {
211   PC_MG          **mg = (PC_MG**)pc->data;
212   PetscErrorCode ierr;
213   PetscInt       levels = mg[0]->levels;
214   PetscTruth     converged = PETSC_FALSE;
215 
216   PetscFunctionBegin;
217   mg[levels-1]->b    = b;
218   mg[levels-1]->x    = x;
219 
220   mg[levels-1]->rtol = rtol;
221   mg[levels-1]->abstol = abstol;
222   mg[levels-1]->dtol = dtol;
223   if (rtol) {
224     /* compute initial residual norm for relative convergence test */
225     PetscReal rnorm;
226     ierr               = (*mg[levels-1]->residual)(mg[levels-1]->A,b,x,w);CHKERRQ(ierr);
227     ierr               = VecNorm(w,NORM_2,&rnorm);CHKERRQ(ierr);
228     mg[levels-1]->ttol = PetscMax(rtol*rnorm,abstol);
229   } else if (abstol) {
230     mg[levels-1]->ttol = abstol;
231   } else {
232     mg[levels-1]->ttol = 0.0;
233   }
234 
235   while (its-- && !converged) {
236     ierr = PCMGMCycle_Private(mg+levels-1,&converged);CHKERRQ(ierr);
237   }
238   PetscFunctionReturn(0);
239 }
240 
241 #undef __FUNCT__
242 #define __FUNCT__ "PCSetFromOptions_MG"
243 PetscErrorCode PCSetFromOptions_MG(PC pc)
244 {
245   PetscErrorCode ierr;
246   PetscInt       m,levels = 1;
247   PetscTruth     flg;
248   PC_MG          **mg = (PC_MG**)pc->data;
249   PCMGType       mgtype = mg[0]->am;;
250 
251   PetscFunctionBegin;
252 
253   ierr = PetscOptionsHead("Multigrid options");CHKERRQ(ierr);
254     if (!pc->data) {
255       ierr = PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);CHKERRQ(ierr);
256       ierr = PCMGSetLevels(pc,levels,PETSC_NULL);CHKERRQ(ierr);
257     }
258     ierr = PetscOptionsInt("-pc_mg_cycles","1 for V cycle, 2 for W-cycle","PCMGSetCycles",1,&m,&flg);CHKERRQ(ierr);
259     if (flg) {
260       ierr = PCMGSetCycles(pc,m);CHKERRQ(ierr);
261     }
262     ierr = PetscOptionsName("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",&flg);CHKERRQ(ierr);
263     if (flg) {
264       ierr = PCMGSetGalerkin(pc);CHKERRQ(ierr);
265     }
266     ierr = PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",1,&m,&flg);CHKERRQ(ierr);
267     if (flg) {
268       ierr = PCMGSetNumberSmoothUp(pc,m);CHKERRQ(ierr);
269     }
270     ierr = PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",1,&m,&flg);CHKERRQ(ierr);
271     if (flg) {
272       ierr = PCMGSetNumberSmoothDown(pc,m);CHKERRQ(ierr);
273     }
274     ierr = PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);CHKERRQ(ierr);
275     if (flg) {ierr = PCMGSetType(pc,mgtype);CHKERRQ(ierr);}
276     ierr = PetscOptionsName("-pc_mg_log","Log times for each multigrid level","None",&flg);CHKERRQ(ierr);
277     if (flg) {
278       PetscInt i;
279       char     eventname[128];
280       if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
281       levels = mg[0]->levels;
282       for (i=0; i<levels; i++) {
283         sprintf(eventname,"MSetup Level %d",(int)i);
284         ierr = PetscLogEventRegister(&mg[i]->eventsetup,eventname,pc->cookie);CHKERRQ(ierr);
285         sprintf(eventname,"MGSolve Level %d to 0",(int)i);
286         ierr = PetscLogEventRegister(&mg[i]->eventsolve,eventname,pc->cookie);CHKERRQ(ierr);
287       }
288     }
289   ierr = PetscOptionsTail();CHKERRQ(ierr);
290   PetscFunctionReturn(0);
291 }
292 
293 const char *PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0};
294 
295 #undef __FUNCT__
296 #define __FUNCT__ "PCView_MG"
297 static PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
298 {
299   PC_MG          **mg = (PC_MG**)pc->data;
300   PetscErrorCode ierr;
301   PetscInt       levels = mg[0]->levels,i;
302   PetscTruth     iascii;
303 
304   PetscFunctionBegin;
305   ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr);
306   if (iascii) {
307     ierr = PetscViewerASCIIPrintf(viewer,"  MG: type is %s, levels=%D cycles=%D, pre-smooths=%D, post-smooths=%D\n",
308                       PCMGTypes[mg[0]->am],levels,mg[0]->cycles,mg[0]->default_smoothd,mg[0]->default_smoothu);CHKERRQ(ierr);
309     if (mg[0]->galerkin) {
310       ierr = PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr);
311     }
312     for (i=0; i<levels; i++) {
313       if (!i) {
314         ierr = PetscViewerASCIIPrintf(viewer,"Coarse gride solver -- level %D -------------------------------\n",i);CHKERRQ(ierr);
315       } else {
316         ierr = PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr);
317       }
318       ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
319       ierr = KSPView(mg[i]->smoothd,viewer);CHKERRQ(ierr);
320       ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
321       if (i && mg[i]->smoothd == mg[i]->smoothu) {
322         ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");CHKERRQ(ierr);
323       } else if (i){
324         ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr);
325         ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
326         ierr = KSPView(mg[i]->smoothu,viewer);CHKERRQ(ierr);
327         ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
328       }
329     }
330   } else {
331     SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported for PCMG",((PetscObject)viewer)->type_name);
332   }
333   PetscFunctionReturn(0);
334 }
335 
336 /*
337     Calls setup for the KSP on each level
338 */
339 #undef __FUNCT__
340 #define __FUNCT__ "PCSetUp_MG"
341 static PetscErrorCode PCSetUp_MG(PC pc)
342 {
343   PC_MG          **mg = (PC_MG**)pc->data;
344   PetscErrorCode ierr;
345   PetscInt       i,n = mg[0]->levels;
346   PC             cpc;
347   PetscTruth     preonly,lu,redundant,cholesky,monitor = PETSC_FALSE,dump;
348   PetscViewer    ascii;
349   MPI_Comm       comm;
350   Mat            dA,dB;
351   MatStructure   uflag;
352   Vec            tvec;
353 
354   PetscFunctionBegin;
355   if (!pc->setupcalled) {
356     ierr = PetscOptionsHasName(0,"-pc_mg_monitor",&monitor);CHKERRQ(ierr);
357 
358     for (i=0; i<n; i++) {
359       if (monitor) {
360         ierr = PetscObjectGetComm((PetscObject)mg[i]->smoothd,&comm);CHKERRQ(ierr);
361         ierr = PetscViewerASCIIOpen(comm,"stdout",&ascii);CHKERRQ(ierr);
362         ierr = PetscViewerASCIISetTab(ascii,n-i);CHKERRQ(ierr);
363         ierr = KSPSetMonitor(mg[i]->smoothd,KSPDefaultMonitor,ascii,(PetscErrorCode(*)(void*))PetscViewerDestroy);CHKERRQ(ierr);
364       }
365       ierr = KSPSetFromOptions(mg[i]->smoothd);CHKERRQ(ierr);
366     }
367     for (i=1; i<n; i++) {
368       if (mg[i]->smoothu && mg[i]->smoothu != mg[i]->smoothd) {
369         if (monitor) {
370           ierr = PetscObjectGetComm((PetscObject)mg[i]->smoothu,&comm);CHKERRQ(ierr);
371           ierr = PetscViewerASCIIOpen(comm,"stdout",&ascii);CHKERRQ(ierr);
372           ierr = PetscViewerASCIISetTab(ascii,n-i);CHKERRQ(ierr);
373           ierr = KSPSetMonitor(mg[i]->smoothu,KSPDefaultMonitor,ascii,(PetscErrorCode(*)(void*))PetscViewerDestroy);CHKERRQ(ierr);
374         }
375         ierr = KSPSetFromOptions(mg[i]->smoothu);CHKERRQ(ierr);
376       }
377     }
378     for (i=1; i<n; i++) {
379       if (mg[i]->restrct && !mg[i]->interpolate) {
380         ierr = PCMGSetInterpolate(pc,i,mg[i]->restrct);CHKERRQ(ierr);
381       }
382       if (!mg[i]->restrct && mg[i]->interpolate) {
383         ierr = PCMGSetRestriction(pc,i,mg[i]->interpolate);CHKERRQ(ierr);
384       }
385 #if defined(PETSC_USE_DEBUG)
386       if (!mg[i]->restrct || !mg[i]->interpolate) {
387         SETERRQ1(PETSC_ERR_ARG_WRONGSTATE,"Need to set restriction or interpolation on level %d",(int)i);
388       }
389 #endif
390     }
391     for (i=0; i<n-1; i++) {
392       if (!mg[i]->r && i) {
393         ierr = VecDuplicate(mg[i]->b,&tvec);CHKERRQ(ierr);
394         ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr);
395         ierr = VecDestroy(tvec);CHKERRQ(ierr);
396       }
397       if (!mg[i]->x) {
398         ierr = VecDuplicate(mg[i]->b,&tvec);CHKERRQ(ierr);
399         ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr);
400         ierr = VecDestroy(tvec);CHKERRQ(ierr);
401       }
402     }
403   }
404 
405   /* If user did not provide fine grid operators, use those from PC */
406   /* BUG BUG BUG This will work ONLY the first time called: hence if the user changes
407      the PC matrices between solves PCMG will continue to use first set provided */
408   ierr = KSPGetOperators(mg[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr);
409   if (!dA  && !dB) {
410     ierr = PetscLogInfo((pc,"PCSetUp_MG: Using outer operators to define finest grid operator \n  because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n"));
411     ierr = KSPSetOperators(mg[n-1]->smoothd,pc->mat,pc->pmat,uflag);CHKERRQ(ierr);
412   }
413 
414   if (mg[0]->galerkin) {
415     Mat B;
416     mg[0]->galerkinused = PETSC_TRUE;
417     /* currently only handle case where mat and pmat are the same on coarser levels */
418     ierr = KSPGetOperators(mg[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr);
419     if (!pc->setupcalled) {
420       for (i=n-2; i>-1; i--) {
421         ierr = MatPtAP(dB,mg[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr);
422         ierr = KSPSetOperators(mg[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
423         dB   = B;
424       }
425     } else {
426       for (i=n-2; i>-1; i--) {
427         ierr = KSPGetOperators(mg[i]->smoothd,0,&B,0);CHKERRQ(ierr);
428         ierr = MatPtAP(dB,mg[i]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr);
429         ierr = KSPSetOperators(mg[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
430         dB   = B;
431       }
432     }
433   }
434 
435   for (i=1; i<n; i++) {
436     if (mg[i]->smoothu == mg[i]->smoothd) {
437       /* if doing only down then initial guess is zero */
438       ierr = KSPSetInitialGuessNonzero(mg[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr);
439     }
440     if (mg[i]->eventsetup) {ierr = PetscLogEventBegin(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
441     ierr = KSPSetUp(mg[i]->smoothd);CHKERRQ(ierr);
442     if (mg[i]->eventsetup) {ierr = PetscLogEventEnd(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
443   }
444   for (i=1; i<n; i++) {
445     if (mg[i]->smoothu && mg[i]->smoothu != mg[i]->smoothd) {
446       PC           uppc,downpc;
447       Mat          downmat,downpmat,upmat,uppmat;
448       MatStructure matflag;
449 
450       /* check if operators have been set for up, if not use down operators to set them */
451       ierr = KSPGetPC(mg[i]->smoothu,&uppc);CHKERRQ(ierr);
452       ierr = PCGetOperators(uppc,&upmat,&uppmat,PETSC_NULL);CHKERRQ(ierr);
453       if (!upmat) {
454         ierr = KSPGetPC(mg[i]->smoothd,&downpc);CHKERRQ(ierr);
455         ierr = PCGetOperators(downpc,&downmat,&downpmat,&matflag);CHKERRQ(ierr);
456         ierr = KSPSetOperators(mg[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr);
457       }
458 
459       ierr = KSPSetInitialGuessNonzero(mg[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr);
460       if (mg[i]->eventsetup) {ierr = PetscLogEventBegin(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
461       ierr = KSPSetUp(mg[i]->smoothu);CHKERRQ(ierr);
462       if (mg[i]->eventsetup) {ierr = PetscLogEventEnd(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
463     }
464   }
465 
466   /*
467       If coarse solver is not direct method then DO NOT USE preonly
468   */
469   ierr = PetscTypeCompare((PetscObject)mg[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr);
470   if (preonly) {
471     ierr = KSPGetPC(mg[0]->smoothd,&cpc);CHKERRQ(ierr);
472     ierr = PetscTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr);
473     ierr = PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr);
474     ierr = PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr);
475     if (!lu && !redundant && !cholesky) {
476       ierr = KSPSetType(mg[0]->smoothd,KSPGMRES);CHKERRQ(ierr);
477     }
478   }
479 
480   if (!pc->setupcalled) {
481     if (monitor) {
482       ierr = PetscObjectGetComm((PetscObject)mg[0]->smoothd,&comm);CHKERRQ(ierr);
483       ierr = PetscViewerASCIIOpen(comm,"stdout",&ascii);CHKERRQ(ierr);
484       ierr = PetscViewerASCIISetTab(ascii,n);CHKERRQ(ierr);
485       ierr = KSPSetMonitor(mg[0]->smoothd,KSPDefaultMonitor,ascii,(PetscErrorCode(*)(void*))PetscViewerDestroy);CHKERRQ(ierr);
486     }
487     ierr = KSPSetFromOptions(mg[0]->smoothd);CHKERRQ(ierr);
488   }
489 
490   if (mg[0]->eventsetup) {ierr = PetscLogEventBegin(mg[0]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
491   ierr = KSPSetUp(mg[0]->smoothd);CHKERRQ(ierr);
492   if (mg[0]->eventsetup) {ierr = PetscLogEventEnd(mg[0]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
493 
494 #if defined(PETSC_USE_SOCKET_VIEWER)
495   /*
496      Dump the interpolation/restriction matrices to matlab plus the
497    Jacobian/stiffness on each level. This allows Matlab users to
498    easily check if the Galerkin condition A_c = R A_f R^T is satisfied */
499   ierr = PetscOptionsHasName(pc->prefix,"-pc_mg_dump_matlab",&dump);CHKERRQ(ierr);
500   if (dump) {
501     for (i=1; i<n; i++) {
502       ierr = MatView(mg[i]->restrct,PETSC_VIEWER_SOCKET_(pc->comm));CHKERRQ(ierr);
503     }
504     for (i=0; i<n; i++) {
505       ierr = KSPGetPC(mg[i]->smoothd,&pc);CHKERRQ(ierr);
506       ierr = MatView(pc->mat,PETSC_VIEWER_SOCKET_(pc->comm));CHKERRQ(ierr);
507     }
508   }
509 #endif
510 
511   ierr = PetscOptionsHasName(pc->prefix,"-pc_mg_dump_binary",&dump);CHKERRQ(ierr);
512   if (dump) {
513     for (i=1; i<n; i++) {
514       ierr = MatView(mg[i]->restrct,PETSC_VIEWER_BINARY_(pc->comm));CHKERRQ(ierr);
515     }
516     for (i=0; i<n; i++) {
517       ierr = KSPGetPC(mg[i]->smoothd,&pc);CHKERRQ(ierr);
518       ierr = MatView(pc->mat,PETSC_VIEWER_BINARY_(pc->comm));CHKERRQ(ierr);
519     }
520   }
521   PetscFunctionReturn(0);
522 }
523 
524 /* -------------------------------------------------------------------------------------*/
525 
526 #undef __FUNCT__
527 #define __FUNCT__ "PCMGSetLevels"
528 /*@C
529    PCMGSetLevels - Sets the number of levels to use with MG.
530    Must be called before any other MG routine.
531 
532    Collective on PC
533 
534    Input Parameters:
535 +  pc - the preconditioner context
536 .  levels - the number of levels
537 -  comms - optional communicators for each level; this is to allow solving the coarser problems
538            on smaller sets of processors. Use PETSC_NULL_OBJECT for default in Fortran
539 
540    Level: intermediate
541 
542    Notes:
543      If the number of levels is one then the multigrid uses the -mg_levels prefix
544   for setting the level options rather than the -mg_coarse prefix.
545 
546 .keywords: MG, set, levels, multigrid
547 
548 .seealso: PCMGSetType(), PCMGGetLevels()
549 @*/
550 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
551 {
552   PetscErrorCode ierr;
553   PC_MG          **mg;
554 
555   PetscFunctionBegin;
556   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
557 
558   if (pc->data) {
559     SETERRQ(PETSC_ERR_ORDER,"Number levels already set for MG\n\
560     make sure that you call PCMGSetLevels() before KSPSetFromOptions()");
561   }
562   ierr                     = PCMGCreate_Private(pc->comm,levels,pc,comms,&mg);CHKERRQ(ierr);
563   mg[0]->am                = PC_MG_MULTIPLICATIVE;
564   pc->data                 = (void*)mg;
565   pc->ops->applyrichardson = PCApplyRichardson_MG;
566   PetscFunctionReturn(0);
567 }
568 
569 #undef __FUNCT__
570 #define __FUNCT__ "PCMGGetLevels"
571 /*@
572    PCMGGetLevels - Gets the number of levels to use with MG.
573 
574    Not Collective
575 
576    Input Parameter:
577 .  pc - the preconditioner context
578 
579    Output parameter:
580 .  levels - the number of levels
581 
582    Level: advanced
583 
584 .keywords: MG, get, levels, multigrid
585 
586 .seealso: PCMGSetLevels()
587 @*/
588 PetscErrorCode PETSCKSP_DLLEXPORT PCMGGetLevels(PC pc,PetscInt *levels)
589 {
590   PC_MG  **mg;
591 
592   PetscFunctionBegin;
593   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
594   PetscValidIntPointer(levels,2);
595 
596   mg      = (PC_MG**)pc->data;
597   *levels = mg[0]->levels;
598   PetscFunctionReturn(0);
599 }
600 
601 #undef __FUNCT__
602 #define __FUNCT__ "PCMGSetType"
603 /*@
604    PCMGSetType - Determines the form of multigrid to use:
605    multiplicative, additive, full, or the Kaskade algorithm.
606 
607    Collective on PC
608 
609    Input Parameters:
610 +  pc - the preconditioner context
611 -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
612    PC_MG_FULL, PC_MG_KASKADE
613 
614    Options Database Key:
615 .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
616    additive, full, kaskade
617 
618    Level: advanced
619 
620 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid
621 
622 .seealso: PCMGSetLevels()
623 @*/
624 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetType(PC pc,PCMGType form)
625 {
626   PC_MG **mg;
627 
628   PetscFunctionBegin;
629   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
630   mg = (PC_MG**)pc->data;
631 
632   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
633   mg[0]->am = form;
634   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
635   else pc->ops->applyrichardson = 0;
636   PetscFunctionReturn(0);
637 }
638 
639 #undef __FUNCT__
640 #define __FUNCT__ "PCMGSetCycles"
641 /*@
642    PCMGSetCycles - Sets the type cycles to use.  Use PCMGSetCyclesOnLevel() for more
643    complicated cycling.
644 
645    Collective on PC
646 
647    Input Parameters:
648 +  pc - the multigrid context
649 -  n - the number of cycles
650 
651    Options Database Key:
652 $  -pc_mg_cycles n - 1 denotes a V-cycle; 2 denotes a W-cycle.
653 
654    Level: advanced
655 
656 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
657 
658 .seealso: PCMGSetCyclesOnLevel()
659 @*/
660 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetCycles(PC pc,PetscInt n)
661 {
662   PC_MG    **mg;
663   PetscInt i,levels;
664 
665   PetscFunctionBegin;
666   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
667   mg     = (PC_MG**)pc->data;
668   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
669   levels = mg[0]->levels;
670 
671   for (i=0; i<levels; i++) {
672     mg[i]->cycles  = n;
673   }
674   PetscFunctionReturn(0);
675 }
676 
677 #undef __FUNCT__
678 #define __FUNCT__ "PCMGSetGalerkin"
679 /*@
680    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
681       finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t
682 
683    Collective on PC
684 
685    Input Parameters:
686 +  pc - the multigrid context
687 -  n - the number of cycles
688 
689    Options Database Key:
690 $  -pc_mg_galerkin
691 
692    Level: intermediate
693 
694 .keywords: MG, set, Galerkin
695 
696 @*/
697 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetGalerkin(PC pc)
698 {
699   PC_MG    **mg;
700   PetscInt i,levels;
701 
702   PetscFunctionBegin;
703   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
704   mg     = (PC_MG**)pc->data;
705   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
706   levels = mg[0]->levels;
707 
708   for (i=0; i<levels; i++) {
709     mg[i]->galerkin = PETSC_TRUE;
710   }
711   PetscFunctionReturn(0);
712 }
713 
714 #undef __FUNCT__
715 #define __FUNCT__ "PCMGSetNumberSmoothDown"
716 /*@
717    PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to
718    use on all levels. Use PCMGGetSmootherDown() to set different
719    pre-smoothing steps on different levels.
720 
721    Collective on PC
722 
723    Input Parameters:
724 +  mg - the multigrid context
725 -  n - the number of smoothing steps
726 
727    Options Database Key:
728 .  -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps
729 
730    Level: advanced
731 
732 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid
733 
734 .seealso: PCMGSetNumberSmoothUp()
735 @*/
736 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothDown(PC pc,PetscInt n)
737 {
738   PC_MG          **mg;
739   PetscErrorCode ierr;
740   PetscInt       i,levels;
741 
742   PetscFunctionBegin;
743   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
744   mg     = (PC_MG**)pc->data;
745   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
746   levels = mg[0]->levels;
747 
748   for (i=1; i<levels; i++) {
749     /* make sure smoother up and down are different */
750     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
751     ierr = KSPSetTolerances(mg[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
752     mg[i]->default_smoothd = n;
753   }
754   PetscFunctionReturn(0);
755 }
756 
757 #undef __FUNCT__
758 #define __FUNCT__ "PCMGSetNumberSmoothUp"
759 /*@
760    PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use
761    on all levels. Use PCMGGetSmootherUp() to set different numbers of
762    post-smoothing steps on different levels.
763 
764    Collective on PC
765 
766    Input Parameters:
767 +  mg - the multigrid context
768 -  n - the number of smoothing steps
769 
770    Options Database Key:
771 .  -pc_mg_smoothup <n> - Sets number of post-smoothing steps
772 
773    Level: advanced
774 
775    Note: this does not set a value on the coarsest grid, since we assume that
776     there is no seperate smooth up on the coarsest grid.
777 
778 .keywords: MG, smooth, up, post-smoothing, steps, multigrid
779 
780 .seealso: PCMGSetNumberSmoothDown()
781 @*/
782 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothUp(PC pc,PetscInt n)
783 {
784   PC_MG          **mg;
785   PetscErrorCode ierr;
786   PetscInt       i,levels;
787 
788   PetscFunctionBegin;
789   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
790   mg     = (PC_MG**)pc->data;
791   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
792   levels = mg[0]->levels;
793 
794   for (i=1; i<levels; i++) {
795     /* make sure smoother up and down are different */
796     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
797     ierr = KSPSetTolerances(mg[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
798     mg[i]->default_smoothu = n;
799   }
800   PetscFunctionReturn(0);
801 }
802 
803 /* ----------------------------------------------------------------------------------------*/
804 
805 /*MC
806    PCMG - Use geometric multigrid preconditioning. This preconditioner requires you provide additional
807     information about the coarser grid matrices and restriction/interpolation operators.
808 
809    Options Database Keys:
810 +  -pc_mg_levels <nlevels> - number of levels including finest
811 .  -pc_mg_cycles 1 or 2 - for V or W-cycle
812 .  -pc_mg_smoothup <n> - number of smoothing steps after interpolation
813 .  -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator
814 .  -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default
815 .  -pc_mg_log - log information about time spent on each level of the solver
816 .  -pc_mg_monitor - print information on the multigrid convergence
817 .  -pc_mg_galerkin - use Galerkin process to compute coarser operators
818 -  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
819                         to the Socket viewer for reading from Matlab.
820 
821    Notes:
822 
823    Level: intermediate
824 
825    Concepts: multigrid
826 
827 .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType,
828            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycles(), PCMGSetNumberSmoothDown(),
829            PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
830            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
831            PCMGSetCyclesOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
832 M*/
833 
834 EXTERN_C_BEGIN
835 #undef __FUNCT__
836 #define __FUNCT__ "PCCreate_MG"
837 PetscErrorCode PETSCKSP_DLLEXPORT PCCreate_MG(PC pc)
838 {
839   PetscFunctionBegin;
840   pc->ops->apply          = PCApply_MG;
841   pc->ops->setup          = PCSetUp_MG;
842   pc->ops->destroy        = PCDestroy_MG;
843   pc->ops->setfromoptions = PCSetFromOptions_MG;
844   pc->ops->view           = PCView_MG;
845 
846   pc->data                = (void*)0;
847   PetscFunctionReturn(0);
848 }
849 EXTERN_C_END
850