xref: /petsc/src/ksp/pc/impls/mg/mg.c (revision 09f3b4e5628a00a1eaf17d80982cfbcc515cc9c1)
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 = PetscVerboseInfo((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 = PetscVerboseInfo((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 && levels > 1) {
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]->residual) {
380         Mat mat;
381         ierr = KSPGetOperators(mg[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);CHKERRQ(ierr);
382         ierr = PCMGSetResidual(pc,i,PCMGDefaultResidual,mat);CHKERRQ(ierr);
383       }
384       if (mg[i]->restrct && !mg[i]->interpolate) {
385         ierr = PCMGSetInterpolate(pc,i,mg[i]->restrct);CHKERRQ(ierr);
386       }
387       if (!mg[i]->restrct && mg[i]->interpolate) {
388         ierr = PCMGSetRestriction(pc,i,mg[i]->interpolate);CHKERRQ(ierr);
389       }
390 #if defined(PETSC_USE_DEBUG)
391       if (!mg[i]->restrct || !mg[i]->interpolate) {
392         SETERRQ1(PETSC_ERR_ARG_WRONGSTATE,"Need to set restriction or interpolation on level %d",(int)i);
393       }
394 #endif
395     }
396     for (i=0; i<n-1; i++) {
397       if (!mg[i]->b) {
398         Mat mat;
399         Vec vec;
400         ierr = KSPGetOperators(mg[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);CHKERRQ(ierr);
401         ierr = MatGetVecs(mat,&vec,PETSC_NULL);CHKERRQ(ierr);
402         ierr = PCMGSetRhs(pc,i,vec);CHKERRQ(ierr);
403       }
404       if (!mg[i]->r && i) {
405         ierr = VecDuplicate(mg[i]->b,&tvec);CHKERRQ(ierr);
406         ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr);
407         ierr = VecDestroy(tvec);CHKERRQ(ierr);
408       }
409       if (!mg[i]->x) {
410         ierr = VecDuplicate(mg[i]->b,&tvec);CHKERRQ(ierr);
411         ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr);
412         ierr = VecDestroy(tvec);CHKERRQ(ierr);
413       }
414     }
415   }
416 
417   /* If user did not provide fine grid operators, use those from PC */
418   /* BUG BUG BUG This will work ONLY the first time called: hence if the user changes
419      the PC matrices between solves PCMG will continue to use first set provided */
420   ierr = KSPGetOperators(mg[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr);
421   if (!dA  && !dB) {
422     ierr = PetscVerboseInfo((pc,"PCSetUp_MG: Using outer operators to define finest grid operator \n  because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n"));
423     ierr = KSPSetOperators(mg[n-1]->smoothd,pc->mat,pc->pmat,uflag);CHKERRQ(ierr);
424   }
425 
426   if (mg[0]->galerkin) {
427     Mat B;
428     mg[0]->galerkinused = PETSC_TRUE;
429     /* currently only handle case where mat and pmat are the same on coarser levels */
430     ierr = KSPGetOperators(mg[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr);
431     if (!pc->setupcalled) {
432       for (i=n-2; i>-1; i--) {
433         ierr = MatPtAP(dB,mg[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr);
434         ierr = KSPSetOperators(mg[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
435         dB   = B;
436       }
437     } else {
438       for (i=n-2; i>-1; i--) {
439         ierr = KSPGetOperators(mg[i]->smoothd,0,&B,0);CHKERRQ(ierr);
440         ierr = MatPtAP(dB,mg[i]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr);
441         ierr = KSPSetOperators(mg[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
442         dB   = B;
443       }
444     }
445   }
446 
447   for (i=1; i<n; i++) {
448     if (mg[i]->smoothu == mg[i]->smoothd) {
449       /* if doing only down then initial guess is zero */
450       ierr = KSPSetInitialGuessNonzero(mg[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr);
451     }
452     if (mg[i]->eventsetup) {ierr = PetscLogEventBegin(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
453     ierr = KSPSetUp(mg[i]->smoothd);CHKERRQ(ierr);
454     if (mg[i]->eventsetup) {ierr = PetscLogEventEnd(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
455   }
456   for (i=1; i<n; i++) {
457     if (mg[i]->smoothu && mg[i]->smoothu != mg[i]->smoothd) {
458       PC           uppc,downpc;
459       Mat          downmat,downpmat,upmat,uppmat;
460       MatStructure matflag;
461 
462       /* check if operators have been set for up, if not use down operators to set them */
463       ierr = KSPGetPC(mg[i]->smoothu,&uppc);CHKERRQ(ierr);
464       ierr = PCGetOperators(uppc,&upmat,&uppmat,PETSC_NULL);CHKERRQ(ierr);
465       if (!upmat) {
466         ierr = KSPGetPC(mg[i]->smoothd,&downpc);CHKERRQ(ierr);
467         ierr = PCGetOperators(downpc,&downmat,&downpmat,&matflag);CHKERRQ(ierr);
468         ierr = KSPSetOperators(mg[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr);
469       }
470 
471       ierr = KSPSetInitialGuessNonzero(mg[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr);
472       if (mg[i]->eventsetup) {ierr = PetscLogEventBegin(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
473       ierr = KSPSetUp(mg[i]->smoothu);CHKERRQ(ierr);
474       if (mg[i]->eventsetup) {ierr = PetscLogEventEnd(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
475     }
476   }
477 
478   /*
479       If coarse solver is not direct method then DO NOT USE preonly
480   */
481   ierr = PetscTypeCompare((PetscObject)mg[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr);
482   if (preonly) {
483     ierr = KSPGetPC(mg[0]->smoothd,&cpc);CHKERRQ(ierr);
484     ierr = PetscTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr);
485     ierr = PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr);
486     ierr = PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr);
487     if (!lu && !redundant && !cholesky) {
488       ierr = KSPSetType(mg[0]->smoothd,KSPGMRES);CHKERRQ(ierr);
489     }
490   }
491 
492   if (!pc->setupcalled) {
493     if (monitor) {
494       ierr = PetscObjectGetComm((PetscObject)mg[0]->smoothd,&comm);CHKERRQ(ierr);
495       ierr = PetscViewerASCIIOpen(comm,"stdout",&ascii);CHKERRQ(ierr);
496       ierr = PetscViewerASCIISetTab(ascii,n);CHKERRQ(ierr);
497       ierr = KSPSetMonitor(mg[0]->smoothd,KSPDefaultMonitor,ascii,(PetscErrorCode(*)(void*))PetscViewerDestroy);CHKERRQ(ierr);
498     }
499     ierr = KSPSetFromOptions(mg[0]->smoothd);CHKERRQ(ierr);
500   }
501 
502   if (mg[0]->eventsetup) {ierr = PetscLogEventBegin(mg[0]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
503   ierr = KSPSetUp(mg[0]->smoothd);CHKERRQ(ierr);
504   if (mg[0]->eventsetup) {ierr = PetscLogEventEnd(mg[0]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
505 
506 #if defined(PETSC_USE_SOCKET_VIEWER)
507   /*
508      Dump the interpolation/restriction matrices to matlab plus the
509    Jacobian/stiffness on each level. This allows Matlab users to
510    easily check if the Galerkin condition A_c = R A_f R^T is satisfied */
511   ierr = PetscOptionsHasName(pc->prefix,"-pc_mg_dump_matlab",&dump);CHKERRQ(ierr);
512   if (dump) {
513     for (i=1; i<n; i++) {
514       ierr = MatView(mg[i]->restrct,PETSC_VIEWER_SOCKET_(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_SOCKET_(pc->comm));CHKERRQ(ierr);
519     }
520   }
521 #endif
522 
523   ierr = PetscOptionsHasName(pc->prefix,"-pc_mg_dump_binary",&dump);CHKERRQ(ierr);
524   if (dump) {
525     for (i=1; i<n; i++) {
526       ierr = MatView(mg[i]->restrct,PETSC_VIEWER_BINARY_(pc->comm));CHKERRQ(ierr);
527     }
528     for (i=0; i<n; i++) {
529       ierr = KSPGetPC(mg[i]->smoothd,&pc);CHKERRQ(ierr);
530       ierr = MatView(pc->mat,PETSC_VIEWER_BINARY_(pc->comm));CHKERRQ(ierr);
531     }
532   }
533   PetscFunctionReturn(0);
534 }
535 
536 /* -------------------------------------------------------------------------------------*/
537 
538 #undef __FUNCT__
539 #define __FUNCT__ "PCMGSetLevels"
540 /*@C
541    PCMGSetLevels - Sets the number of levels to use with MG.
542    Must be called before any other MG routine.
543 
544    Collective on PC
545 
546    Input Parameters:
547 +  pc - the preconditioner context
548 .  levels - the number of levels
549 -  comms - optional communicators for each level; this is to allow solving the coarser problems
550            on smaller sets of processors. Use PETSC_NULL_OBJECT for default in Fortran
551 
552    Level: intermediate
553 
554    Notes:
555      If the number of levels is one then the multigrid uses the -mg_levels prefix
556   for setting the level options rather than the -mg_coarse prefix.
557 
558 .keywords: MG, set, levels, multigrid
559 
560 .seealso: PCMGSetType(), PCMGGetLevels()
561 @*/
562 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
563 {
564   PetscErrorCode ierr;
565   PC_MG          **mg;
566 
567   PetscFunctionBegin;
568   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
569 
570   if (pc->data) {
571     SETERRQ(PETSC_ERR_ORDER,"Number levels already set for MG\n\
572     make sure that you call PCMGSetLevels() before KSPSetFromOptions()");
573   }
574   ierr                     = PCMGCreate_Private(pc->comm,levels,pc,comms,&mg);CHKERRQ(ierr);
575   mg[0]->am                = PC_MG_MULTIPLICATIVE;
576   pc->data                 = (void*)mg;
577   pc->ops->applyrichardson = PCApplyRichardson_MG;
578   PetscFunctionReturn(0);
579 }
580 
581 #undef __FUNCT__
582 #define __FUNCT__ "PCMGGetLevels"
583 /*@
584    PCMGGetLevels - Gets the number of levels to use with MG.
585 
586    Not Collective
587 
588    Input Parameter:
589 .  pc - the preconditioner context
590 
591    Output parameter:
592 .  levels - the number of levels
593 
594    Level: advanced
595 
596 .keywords: MG, get, levels, multigrid
597 
598 .seealso: PCMGSetLevels()
599 @*/
600 PetscErrorCode PETSCKSP_DLLEXPORT PCMGGetLevels(PC pc,PetscInt *levels)
601 {
602   PC_MG  **mg;
603 
604   PetscFunctionBegin;
605   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
606   PetscValidIntPointer(levels,2);
607 
608   mg      = (PC_MG**)pc->data;
609   *levels = mg[0]->levels;
610   PetscFunctionReturn(0);
611 }
612 
613 #undef __FUNCT__
614 #define __FUNCT__ "PCMGSetType"
615 /*@
616    PCMGSetType - Determines the form of multigrid to use:
617    multiplicative, additive, full, or the Kaskade algorithm.
618 
619    Collective on PC
620 
621    Input Parameters:
622 +  pc - the preconditioner context
623 -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
624    PC_MG_FULL, PC_MG_KASKADE
625 
626    Options Database Key:
627 .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
628    additive, full, kaskade
629 
630    Level: advanced
631 
632 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid
633 
634 .seealso: PCMGSetLevels()
635 @*/
636 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetType(PC pc,PCMGType form)
637 {
638   PC_MG **mg;
639 
640   PetscFunctionBegin;
641   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
642   mg = (PC_MG**)pc->data;
643 
644   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
645   mg[0]->am = form;
646   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
647   else pc->ops->applyrichardson = 0;
648   PetscFunctionReturn(0);
649 }
650 
651 #undef __FUNCT__
652 #define __FUNCT__ "PCMGSetCycles"
653 /*@
654    PCMGSetCycles - Sets the type cycles to use.  Use PCMGSetCyclesOnLevel() for more
655    complicated cycling.
656 
657    Collective on PC
658 
659    Input Parameters:
660 +  pc - the multigrid context
661 -  n - the number of cycles
662 
663    Options Database Key:
664 $  -pc_mg_cycles n - 1 denotes a V-cycle; 2 denotes a W-cycle.
665 
666    Level: advanced
667 
668 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
669 
670 .seealso: PCMGSetCyclesOnLevel()
671 @*/
672 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetCycles(PC pc,PetscInt n)
673 {
674   PC_MG    **mg;
675   PetscInt i,levels;
676 
677   PetscFunctionBegin;
678   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
679   mg     = (PC_MG**)pc->data;
680   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
681   levels = mg[0]->levels;
682 
683   for (i=0; i<levels; i++) {
684     mg[i]->cycles  = n;
685   }
686   PetscFunctionReturn(0);
687 }
688 
689 #undef __FUNCT__
690 #define __FUNCT__ "PCMGSetGalerkin"
691 /*@
692    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
693       finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t
694 
695    Collective on PC
696 
697    Input Parameters:
698 +  pc - the multigrid context
699 -  n - the number of cycles
700 
701    Options Database Key:
702 $  -pc_mg_galerkin
703 
704    Level: intermediate
705 
706 .keywords: MG, set, Galerkin
707 
708 @*/
709 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetGalerkin(PC pc)
710 {
711   PC_MG    **mg;
712   PetscInt i,levels;
713 
714   PetscFunctionBegin;
715   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
716   mg     = (PC_MG**)pc->data;
717   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
718   levels = mg[0]->levels;
719 
720   for (i=0; i<levels; i++) {
721     mg[i]->galerkin = PETSC_TRUE;
722   }
723   PetscFunctionReturn(0);
724 }
725 
726 #undef __FUNCT__
727 #define __FUNCT__ "PCMGSetNumberSmoothDown"
728 /*@
729    PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to
730    use on all levels. Use PCMGGetSmootherDown() to set different
731    pre-smoothing steps on different levels.
732 
733    Collective on PC
734 
735    Input Parameters:
736 +  mg - the multigrid context
737 -  n - the number of smoothing steps
738 
739    Options Database Key:
740 .  -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps
741 
742    Level: advanced
743 
744 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid
745 
746 .seealso: PCMGSetNumberSmoothUp()
747 @*/
748 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothDown(PC pc,PetscInt n)
749 {
750   PC_MG          **mg;
751   PetscErrorCode ierr;
752   PetscInt       i,levels;
753 
754   PetscFunctionBegin;
755   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
756   mg     = (PC_MG**)pc->data;
757   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
758   levels = mg[0]->levels;
759 
760   for (i=1; i<levels; i++) {
761     /* make sure smoother up and down are different */
762     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
763     ierr = KSPSetTolerances(mg[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
764     mg[i]->default_smoothd = n;
765   }
766   PetscFunctionReturn(0);
767 }
768 
769 #undef __FUNCT__
770 #define __FUNCT__ "PCMGSetNumberSmoothUp"
771 /*@
772    PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use
773    on all levels. Use PCMGGetSmootherUp() to set different numbers of
774    post-smoothing steps on different levels.
775 
776    Collective on PC
777 
778    Input Parameters:
779 +  mg - the multigrid context
780 -  n - the number of smoothing steps
781 
782    Options Database Key:
783 .  -pc_mg_smoothup <n> - Sets number of post-smoothing steps
784 
785    Level: advanced
786 
787    Note: this does not set a value on the coarsest grid, since we assume that
788     there is no separate smooth up on the coarsest grid.
789 
790 .keywords: MG, smooth, up, post-smoothing, steps, multigrid
791 
792 .seealso: PCMGSetNumberSmoothDown()
793 @*/
794 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothUp(PC pc,PetscInt n)
795 {
796   PC_MG          **mg;
797   PetscErrorCode ierr;
798   PetscInt       i,levels;
799 
800   PetscFunctionBegin;
801   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
802   mg     = (PC_MG**)pc->data;
803   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
804   levels = mg[0]->levels;
805 
806   for (i=1; i<levels; i++) {
807     /* make sure smoother up and down are different */
808     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
809     ierr = KSPSetTolerances(mg[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
810     mg[i]->default_smoothu = n;
811   }
812   PetscFunctionReturn(0);
813 }
814 
815 /* ----------------------------------------------------------------------------------------*/
816 
817 /*MC
818    PCMG - Use geometric multigrid preconditioning. This preconditioner requires you provide additional
819     information about the coarser grid matrices and restriction/interpolation operators.
820 
821    Options Database Keys:
822 +  -pc_mg_levels <nlevels> - number of levels including finest
823 .  -pc_mg_cycles 1 or 2 - for V or W-cycle
824 .  -pc_mg_smoothup <n> - number of smoothing steps after interpolation
825 .  -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator
826 .  -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default
827 .  -pc_mg_log - log information about time spent on each level of the solver
828 .  -pc_mg_monitor - print information on the multigrid convergence
829 .  -pc_mg_galerkin - use Galerkin process to compute coarser operators
830 -  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
831                         to the Socket viewer for reading from Matlab.
832 
833    Notes:
834 
835    Level: intermediate
836 
837    Concepts: multigrid
838 
839 .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType,
840            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycles(), PCMGSetNumberSmoothDown(),
841            PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
842            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
843            PCMGSetCyclesOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
844 M*/
845 
846 EXTERN_C_BEGIN
847 #undef __FUNCT__
848 #define __FUNCT__ "PCCreate_MG"
849 PetscErrorCode PETSCKSP_DLLEXPORT PCCreate_MG(PC pc)
850 {
851   PetscFunctionBegin;
852   pc->ops->apply          = PCApply_MG;
853   pc->ops->setup          = PCSetUp_MG;
854   pc->ops->destroy        = PCDestroy_MG;
855   pc->ops->setfromoptions = PCSetFromOptions_MG;
856   pc->ops->view           = PCView_MG;
857 
858   pc->data                = (void*)0;
859   PetscFunctionReturn(0);
860 }
861 EXTERN_C_END
862