xref: /petsc/src/ksp/pc/impls/mg/mg.c (revision 906ed7cc33fecbafab01746eec64dcdcc8a4842f)
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 = PetscInfo2(0,"Linear solver has converged. Residual norm %G is less than absolute tolerance %G\n",rnorm,mg->abstol);CHKERRQ(ierr);
34         } else {
35           ierr = PetscInfo2(0,"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   for (i=0; i<n-1; i++) {
135     if (mg[i+1]->r) {ierr = VecDestroy(mg[i+1]->r);CHKERRQ(ierr);}
136     if (mg[i]->b) {ierr = VecDestroy(mg[i]->b);CHKERRQ(ierr);}
137     if (mg[i]->x) {ierr = VecDestroy(mg[i]->x);CHKERRQ(ierr);}
138     if (mg[i+1]->restrct) {ierr = MatDestroy(mg[i+1]->restrct);CHKERRQ(ierr);}
139     if (mg[i+1]->interpolate) {ierr = MatDestroy(mg[i+1]->interpolate);CHKERRQ(ierr);}
140   }
141 
142   for (i=0; i<n; i++) {
143     if (mg[i]->smoothd != mg[i]->smoothu) {
144       ierr = KSPDestroy(mg[i]->smoothd);CHKERRQ(ierr);
145     }
146     ierr = KSPDestroy(mg[i]->smoothu);CHKERRQ(ierr);
147     ierr = PetscFree(mg[i]);CHKERRQ(ierr);
148   }
149   ierr = PetscFree(mg);CHKERRQ(ierr);
150   PetscFunctionReturn(0);
151 }
152 
153 
154 
155 EXTERN PetscErrorCode PCMGACycle_Private(PC_MG**);
156 EXTERN PetscErrorCode PCMGFCycle_Private(PC_MG**);
157 EXTERN PetscErrorCode PCMGKCycle_Private(PC_MG**);
158 
159 /*
160    PCApply_MG - Runs either an additive, multiplicative, Kaskadic
161              or full cycle of multigrid.
162 
163   Note:
164   A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle().
165 */
166 #undef __FUNCT__
167 #define __FUNCT__ "PCApply_MG"
168 static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x)
169 {
170   PC_MG          **mg = (PC_MG**)pc->data;
171   PetscErrorCode ierr;
172   PetscInt       levels = mg[0]->levels;
173 
174   PetscFunctionBegin;
175   mg[levels-1]->b = b;
176   mg[levels-1]->x = x;
177   if (!mg[levels-1]->r && mg[0]->am != PC_MG_ADDITIVE && levels > 1) {
178     Vec tvec;
179     ierr = VecDuplicate(mg[levels-1]->b,&tvec);CHKERRQ(ierr);
180     ierr = PCMGSetR(pc,levels-1,tvec);CHKERRQ(ierr);
181     ierr = VecDestroy(tvec);CHKERRQ(ierr);
182   }
183   if (mg[0]->am == PC_MG_MULTIPLICATIVE) {
184     ierr = VecSet(x,0.0);CHKERRQ(ierr);
185     ierr = PCMGMCycle_Private(mg+levels-1,PETSC_NULL);CHKERRQ(ierr);
186   }
187   else if (mg[0]->am == PC_MG_ADDITIVE) {
188     ierr = PCMGACycle_Private(mg);CHKERRQ(ierr);
189   }
190   else if (mg[0]->am == PC_MG_KASKADE) {
191     ierr = PCMGKCycle_Private(mg);CHKERRQ(ierr);
192   }
193   else {
194     ierr = PCMGFCycle_Private(mg);CHKERRQ(ierr);
195   }
196   PetscFunctionReturn(0);
197 }
198 
199 #undef __FUNCT__
200 #define __FUNCT__ "PCApplyRichardson_MG"
201 static PetscErrorCode PCApplyRichardson_MG(PC pc,Vec b,Vec x,Vec w,PetscReal rtol,PetscReal abstol, PetscReal dtol,PetscInt its)
202 {
203   PC_MG          **mg = (PC_MG**)pc->data;
204   PetscErrorCode ierr;
205   PetscInt       levels = mg[0]->levels;
206   PetscTruth     converged = PETSC_FALSE;
207 
208   PetscFunctionBegin;
209   mg[levels-1]->b    = b;
210   mg[levels-1]->x    = x;
211 
212   mg[levels-1]->rtol = rtol;
213   mg[levels-1]->abstol = abstol;
214   mg[levels-1]->dtol = dtol;
215   if (rtol) {
216     /* compute initial residual norm for relative convergence test */
217     PetscReal rnorm;
218     ierr               = (*mg[levels-1]->residual)(mg[levels-1]->A,b,x,w);CHKERRQ(ierr);
219     ierr               = VecNorm(w,NORM_2,&rnorm);CHKERRQ(ierr);
220     mg[levels-1]->ttol = PetscMax(rtol*rnorm,abstol);
221   } else if (abstol) {
222     mg[levels-1]->ttol = abstol;
223   } else {
224     mg[levels-1]->ttol = 0.0;
225   }
226 
227   while (its-- && !converged) {
228     ierr = PCMGMCycle_Private(mg+levels-1,&converged);CHKERRQ(ierr);
229   }
230   PetscFunctionReturn(0);
231 }
232 
233 #undef __FUNCT__
234 #define __FUNCT__ "PCSetFromOptions_MG"
235 PetscErrorCode PCSetFromOptions_MG(PC pc)
236 {
237   PetscErrorCode ierr;
238   PetscInt       m,levels = 1;
239   PetscTruth     flg;
240   PC_MG          **mg = (PC_MG**)pc->data;
241   PCMGType       mgtype;
242 
243   PetscFunctionBegin;
244 
245   ierr = PetscOptionsHead("Multigrid options");CHKERRQ(ierr);
246     if (!pc->data) {
247       ierr = PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);CHKERRQ(ierr);
248       ierr = PCMGSetLevels(pc,levels,PETSC_NULL);CHKERRQ(ierr);
249       mg = (PC_MG**)pc->data;
250     }
251     mgtype = mg[0]->am;
252     ierr = PetscOptionsInt("-pc_mg_cycles","1 for V cycle, 2 for W-cycle","PCMGSetCycles",1,&m,&flg);CHKERRQ(ierr);
253     if (flg) {
254       ierr = PCMGSetCycles(pc,m);CHKERRQ(ierr);
255     }
256     ierr = PetscOptionsName("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",&flg);CHKERRQ(ierr);
257     if (flg) {
258       ierr = PCMGSetGalerkin(pc);CHKERRQ(ierr);
259     }
260     ierr = PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",1,&m,&flg);CHKERRQ(ierr);
261     if (flg) {
262       ierr = PCMGSetNumberSmoothUp(pc,m);CHKERRQ(ierr);
263     }
264     ierr = PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",1,&m,&flg);CHKERRQ(ierr);
265     if (flg) {
266       ierr = PCMGSetNumberSmoothDown(pc,m);CHKERRQ(ierr);
267     }
268     ierr = PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);CHKERRQ(ierr);
269     if (flg) {ierr = PCMGSetType(pc,mgtype);CHKERRQ(ierr);}
270     ierr = PetscOptionsName("-pc_mg_log","Log times for each multigrid level","None",&flg);CHKERRQ(ierr);
271     if (flg) {
272       PetscInt i;
273       char     eventname[128];
274       if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
275       levels = mg[0]->levels;
276       for (i=0; i<levels; i++) {
277         sprintf(eventname,"MSetup Level %d",(int)i);
278         ierr = PetscLogEventRegister(&mg[i]->eventsetup,eventname,pc->cookie);CHKERRQ(ierr);
279         sprintf(eventname,"MGSolve Level %d to 0",(int)i);
280         ierr = PetscLogEventRegister(&mg[i]->eventsolve,eventname,pc->cookie);CHKERRQ(ierr);
281       }
282     }
283   ierr = PetscOptionsTail();CHKERRQ(ierr);
284   PetscFunctionReturn(0);
285 }
286 
287 const char *PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0};
288 
289 #undef __FUNCT__
290 #define __FUNCT__ "PCView_MG"
291 static PetscErrorCode PCView_MG(PC pc,PetscViewer viewer)
292 {
293   PC_MG          **mg = (PC_MG**)pc->data;
294   PetscErrorCode ierr;
295   PetscInt       levels = mg[0]->levels,i;
296   PetscTruth     iascii;
297 
298   PetscFunctionBegin;
299   ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr);
300   if (iascii) {
301     ierr = PetscViewerASCIIPrintf(viewer,"  MG: type is %s, levels=%D cycles=%D, pre-smooths=%D, post-smooths=%D\n",
302                       PCMGTypes[mg[0]->am],levels,mg[0]->cycles,mg[0]->default_smoothd,mg[0]->default_smoothu);CHKERRQ(ierr);
303     if (mg[0]->galerkin) {
304       ierr = PetscViewerASCIIPrintf(viewer,"    Using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr);
305     }
306     for (i=0; i<levels; i++) {
307       if (!i) {
308         ierr = PetscViewerASCIIPrintf(viewer,"Coarse gride solver -- level %D -------------------------------\n",i);CHKERRQ(ierr);
309       } else {
310         ierr = PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr);
311       }
312       ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
313       ierr = KSPView(mg[i]->smoothd,viewer);CHKERRQ(ierr);
314       ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
315       if (i && mg[i]->smoothd == mg[i]->smoothu) {
316         ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");CHKERRQ(ierr);
317       } else if (i){
318         ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D -------------------------------\n",i);CHKERRQ(ierr);
319         ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
320         ierr = KSPView(mg[i]->smoothu,viewer);CHKERRQ(ierr);
321         ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
322       }
323     }
324   } else {
325     SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported for PCMG",((PetscObject)viewer)->type_name);
326   }
327   PetscFunctionReturn(0);
328 }
329 
330 /*
331     Calls setup for the KSP on each level
332 */
333 #undef __FUNCT__
334 #define __FUNCT__ "PCSetUp_MG"
335 static PetscErrorCode PCSetUp_MG(PC pc)
336 {
337   PC_MG          **mg = (PC_MG**)pc->data;
338   PetscErrorCode ierr;
339   PetscInt       i,n = mg[0]->levels;
340   PC             cpc;
341   PetscTruth     preonly,lu,redundant,cholesky,monitor = PETSC_FALSE,dump,opsset;
342   PetscViewer    ascii;
343   MPI_Comm       comm;
344   Mat            dA,dB;
345   MatStructure   uflag;
346   Vec            tvec;
347 
348   PetscFunctionBegin;
349 
350   /* If user did not provide fine grid operators, use those from PC */
351   /* BUG BUG BUG This will work ONLY the first time called: hence if the user changes
352      the PC matrices between solves PCMG will continue to use first set provided */
353   ierr = KSPGetOperatorsSet(mg[n-1]->smoothd,PETSC_NULL,&opsset);CHKERRQ(ierr);
354   if (!opsset) {
355     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);
356     ierr = KSPSetOperators(mg[n-1]->smoothd,pc->mat,pc->pmat,uflag);CHKERRQ(ierr);
357   }
358 
359   if (mg[0]->galerkin) {
360     Mat B;
361     mg[0]->galerkinused = PETSC_TRUE;
362     /* currently only handle case where mat and pmat are the same on coarser levels */
363     ierr = KSPGetOperators(mg[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr);
364     if (!pc->setupcalled) {
365       for (i=n-2; i>-1; i--) {
366         ierr = MatPtAP(dB,mg[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr);
367         ierr = KSPSetOperators(mg[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
368 	if (i != n-2) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);}
369         dB   = B;
370       }
371       ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);
372     } else {
373       for (i=n-2; i>-1; i--) {
374         ierr = KSPGetOperators(mg[i]->smoothd,PETSC_NULL,&B,PETSC_NULL);CHKERRQ(ierr);
375         ierr = MatPtAP(dB,mg[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr);
376         ierr = KSPSetOperators(mg[i]->smoothd,B,B,uflag);CHKERRQ(ierr);
377         dB   = B;
378       }
379     }
380   }
381 
382   if (!pc->setupcalled) {
383     ierr = PetscOptionsHasName(0,"-pc_mg_monitor",&monitor);CHKERRQ(ierr);
384 
385     for (i=0; i<n; i++) {
386       if (monitor) {
387         ierr = PetscObjectGetComm((PetscObject)mg[i]->smoothd,&comm);CHKERRQ(ierr);
388         ierr = PetscViewerASCIIOpen(comm,"stdout",&ascii);CHKERRQ(ierr);
389         ierr = PetscViewerASCIISetTab(ascii,n-i);CHKERRQ(ierr);
390         ierr = KSPSetMonitor(mg[i]->smoothd,KSPDefaultMonitor,ascii,(PetscErrorCode(*)(void*))PetscViewerDestroy);CHKERRQ(ierr);
391       }
392       ierr = KSPSetFromOptions(mg[i]->smoothd);CHKERRQ(ierr);
393     }
394     for (i=1; i<n; i++) {
395       if (mg[i]->smoothu && (mg[i]->smoothu != mg[i]->smoothd)) {
396         if (monitor) {
397           ierr = PetscObjectGetComm((PetscObject)mg[i]->smoothu,&comm);CHKERRQ(ierr);
398           ierr = PetscViewerASCIIOpen(comm,"stdout",&ascii);CHKERRQ(ierr);
399           ierr = PetscViewerASCIISetTab(ascii,n-i);CHKERRQ(ierr);
400           ierr = KSPSetMonitor(mg[i]->smoothu,KSPDefaultMonitor,ascii,(PetscErrorCode(*)(void*))PetscViewerDestroy);CHKERRQ(ierr);
401         }
402         ierr = KSPSetFromOptions(mg[i]->smoothu);CHKERRQ(ierr);
403       }
404     }
405     for (i=1; i<n; i++) {
406       if (!mg[i]->residual) {
407         Mat mat;
408         ierr = KSPGetOperators(mg[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);CHKERRQ(ierr);
409         ierr = PCMGSetResidual(pc,i,PCMGDefaultResidual,mat);CHKERRQ(ierr);
410       }
411       if (mg[i]->restrct && !mg[i]->interpolate) {
412         ierr = PCMGSetInterpolate(pc,i,mg[i]->restrct);CHKERRQ(ierr);
413       }
414       if (!mg[i]->restrct && mg[i]->interpolate) {
415         ierr = PCMGSetRestriction(pc,i,mg[i]->interpolate);CHKERRQ(ierr);
416       }
417 #if defined(PETSC_USE_DEBUG)
418       if (!mg[i]->restrct || !mg[i]->interpolate) {
419         SETERRQ1(PETSC_ERR_ARG_WRONGSTATE,"Need to set restriction or interpolation on level %d",(int)i);
420       }
421 #endif
422     }
423     for (i=0; i<n-1; i++) {
424       if (!mg[i]->b) {
425         Vec *vec;
426         ierr = KSPGetVecs(mg[i]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr);
427         ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr);
428         ierr = PetscFree(vec);CHKERRQ(ierr);
429       }
430       if (!mg[i]->r && i) {
431         ierr = VecDuplicate(mg[i]->b,&tvec);CHKERRQ(ierr);
432         ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr);
433         ierr = VecDestroy(tvec);CHKERRQ(ierr);
434       }
435       if (!mg[i]->x) {
436         ierr = VecDuplicate(mg[i]->b,&tvec);CHKERRQ(ierr);
437         ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr);
438         ierr = VecDestroy(tvec);CHKERRQ(ierr);
439       }
440     }
441   }
442 
443 
444   for (i=1; i<n; i++) {
445     if (mg[i]->smoothu == mg[i]->smoothd) {
446       /* if doing only down then initial guess is zero */
447       ierr = KSPSetInitialGuessNonzero(mg[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr);
448     }
449     if (mg[i]->eventsetup) {ierr = PetscLogEventBegin(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
450     ierr = KSPSetUp(mg[i]->smoothd);CHKERRQ(ierr);
451     if (mg[i]->eventsetup) {ierr = PetscLogEventEnd(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
452   }
453   for (i=1; i<n; i++) {
454     if (mg[i]->smoothu && mg[i]->smoothu != mg[i]->smoothd) {
455       Mat          downmat,downpmat;
456       MatStructure matflag;
457       PetscTruth   opsset;
458 
459       /* check if operators have been set for up, if not use down operators to set them */
460       ierr = KSPGetOperatorsSet(mg[i]->smoothu,&opsset,PETSC_NULL);CHKERRQ(ierr);
461       if (!opsset) {
462         ierr = KSPGetOperators(mg[i]->smoothd,&downmat,&downpmat,&matflag);CHKERRQ(ierr);
463         ierr = KSPSetOperators(mg[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr);
464       }
465 
466       ierr = KSPSetInitialGuessNonzero(mg[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr);
467       if (mg[i]->eventsetup) {ierr = PetscLogEventBegin(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
468       ierr = KSPSetUp(mg[i]->smoothu);CHKERRQ(ierr);
469       if (mg[i]->eventsetup) {ierr = PetscLogEventEnd(mg[i]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
470     }
471   }
472 
473   /*
474       If coarse solver is not direct method then DO NOT USE preonly
475   */
476   ierr = PetscTypeCompare((PetscObject)mg[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr);
477   if (preonly) {
478     ierr = KSPGetPC(mg[0]->smoothd,&cpc);CHKERRQ(ierr);
479     ierr = PetscTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr);
480     ierr = PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr);
481     ierr = PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr);
482     if (!lu && !redundant && !cholesky) {
483       ierr = KSPSetType(mg[0]->smoothd,KSPGMRES);CHKERRQ(ierr);
484     }
485   }
486 
487   if (!pc->setupcalled) {
488     if (monitor) {
489       ierr = PetscObjectGetComm((PetscObject)mg[0]->smoothd,&comm);CHKERRQ(ierr);
490       ierr = PetscViewerASCIIOpen(comm,"stdout",&ascii);CHKERRQ(ierr);
491       ierr = PetscViewerASCIISetTab(ascii,n);CHKERRQ(ierr);
492       ierr = KSPSetMonitor(mg[0]->smoothd,KSPDefaultMonitor,ascii,(PetscErrorCode(*)(void*))PetscViewerDestroy);CHKERRQ(ierr);
493     }
494     ierr = KSPSetFromOptions(mg[0]->smoothd);CHKERRQ(ierr);
495   }
496 
497   if (mg[0]->eventsetup) {ierr = PetscLogEventBegin(mg[0]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
498   ierr = KSPSetUp(mg[0]->smoothd);CHKERRQ(ierr);
499   if (mg[0]->eventsetup) {ierr = PetscLogEventEnd(mg[0]->eventsetup,0,0,0,0);CHKERRQ(ierr);}
500 
501 #if defined(PETSC_USE_SOCKET_VIEWER)
502   /*
503      Dump the interpolation/restriction matrices to matlab plus the
504    Jacobian/stiffness on each level. This allows Matlab users to
505    easily check if the Galerkin condition A_c = R A_f R^T is satisfied */
506   ierr = PetscOptionsHasName(pc->prefix,"-pc_mg_dump_matlab",&dump);CHKERRQ(ierr);
507   if (dump) {
508     for (i=1; i<n; i++) {
509       ierr = MatView(mg[i]->restrct,PETSC_VIEWER_SOCKET_(pc->comm));CHKERRQ(ierr);
510     }
511     for (i=0; i<n; i++) {
512       ierr = KSPGetPC(mg[i]->smoothd,&pc);CHKERRQ(ierr);
513       ierr = MatView(pc->mat,PETSC_VIEWER_SOCKET_(pc->comm));CHKERRQ(ierr);
514     }
515   }
516 #endif
517 
518   ierr = PetscOptionsHasName(pc->prefix,"-pc_mg_dump_binary",&dump);CHKERRQ(ierr);
519   if (dump) {
520     for (i=1; i<n; i++) {
521       ierr = MatView(mg[i]->restrct,PETSC_VIEWER_BINARY_(pc->comm));CHKERRQ(ierr);
522     }
523     for (i=0; i<n; i++) {
524       ierr = KSPGetPC(mg[i]->smoothd,&pc);CHKERRQ(ierr);
525       ierr = MatView(pc->mat,PETSC_VIEWER_BINARY_(pc->comm));CHKERRQ(ierr);
526     }
527   }
528   PetscFunctionReturn(0);
529 }
530 
531 /* -------------------------------------------------------------------------------------*/
532 
533 #undef __FUNCT__
534 #define __FUNCT__ "PCMGSetLevels"
535 /*@C
536    PCMGSetLevels - Sets the number of levels to use with MG.
537    Must be called before any other MG routine.
538 
539    Collective on PC
540 
541    Input Parameters:
542 +  pc - the preconditioner context
543 .  levels - the number of levels
544 -  comms - optional communicators for each level; this is to allow solving the coarser problems
545            on smaller sets of processors. Use PETSC_NULL_OBJECT for default in Fortran
546 
547    Level: intermediate
548 
549    Notes:
550      If the number of levels is one then the multigrid uses the -mg_levels prefix
551   for setting the level options rather than the -mg_coarse prefix.
552 
553 .keywords: MG, set, levels, multigrid
554 
555 .seealso: PCMGSetType(), PCMGGetLevels()
556 @*/
557 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms)
558 {
559   PetscErrorCode ierr;
560   PC_MG          **mg=0;
561 
562   PetscFunctionBegin;
563   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
564 
565   if (pc->data) {
566     SETERRQ(PETSC_ERR_ORDER,"Number levels already set for MG\n\
567     make sure that you call PCMGSetLevels() before KSPSetFromOptions()");
568   }
569   ierr                     = PCMGCreate_Private(pc->comm,levels,pc,comms,&mg);CHKERRQ(ierr);
570   mg[0]->am                = PC_MG_MULTIPLICATIVE;
571   pc->data                 = (void*)mg;
572   pc->ops->applyrichardson = PCApplyRichardson_MG;
573   PetscFunctionReturn(0);
574 }
575 
576 #undef __FUNCT__
577 #define __FUNCT__ "PCMGGetLevels"
578 /*@
579    PCMGGetLevels - Gets the number of levels to use with MG.
580 
581    Not Collective
582 
583    Input Parameter:
584 .  pc - the preconditioner context
585 
586    Output parameter:
587 .  levels - the number of levels
588 
589    Level: advanced
590 
591 .keywords: MG, get, levels, multigrid
592 
593 .seealso: PCMGSetLevels()
594 @*/
595 PetscErrorCode PETSCKSP_DLLEXPORT PCMGGetLevels(PC pc,PetscInt *levels)
596 {
597   PC_MG  **mg;
598 
599   PetscFunctionBegin;
600   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
601   PetscValidIntPointer(levels,2);
602 
603   mg      = (PC_MG**)pc->data;
604   *levels = mg[0]->levels;
605   PetscFunctionReturn(0);
606 }
607 
608 #undef __FUNCT__
609 #define __FUNCT__ "PCMGSetType"
610 /*@
611    PCMGSetType - Determines the form of multigrid to use:
612    multiplicative, additive, full, or the Kaskade algorithm.
613 
614    Collective on PC
615 
616    Input Parameters:
617 +  pc - the preconditioner context
618 -  form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE,
619    PC_MG_FULL, PC_MG_KASKADE
620 
621    Options Database Key:
622 .  -pc_mg_type <form> - Sets <form>, one of multiplicative,
623    additive, full, kaskade
624 
625    Level: advanced
626 
627 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid
628 
629 .seealso: PCMGSetLevels()
630 @*/
631 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetType(PC pc,PCMGType form)
632 {
633   PC_MG **mg;
634 
635   PetscFunctionBegin;
636   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
637   mg = (PC_MG**)pc->data;
638 
639   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
640   mg[0]->am = form;
641   if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG;
642   else pc->ops->applyrichardson = 0;
643   PetscFunctionReturn(0);
644 }
645 
646 #undef __FUNCT__
647 #define __FUNCT__ "PCMGSetCycles"
648 /*@
649    PCMGSetCycles - Sets the type cycles to use.  Use PCMGSetCyclesOnLevel() for more
650    complicated cycling.
651 
652    Collective on PC
653 
654    Input Parameters:
655 +  pc - the multigrid context
656 -  n - the number of cycles
657 
658    Options Database Key:
659 $  -pc_mg_cycles n - 1 denotes a V-cycle; 2 denotes a W-cycle.
660 
661    Level: advanced
662 
663 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid
664 
665 .seealso: PCMGSetCyclesOnLevel()
666 @*/
667 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetCycles(PC pc,PetscInt n)
668 {
669   PC_MG    **mg;
670   PetscInt i,levels;
671 
672   PetscFunctionBegin;
673   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
674   mg     = (PC_MG**)pc->data;
675   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
676   levels = mg[0]->levels;
677 
678   for (i=0; i<levels; i++) {
679     mg[i]->cycles  = n;
680   }
681   PetscFunctionReturn(0);
682 }
683 
684 #undef __FUNCT__
685 #define __FUNCT__ "PCMGSetGalerkin"
686 /*@
687    PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the
688       finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t
689 
690    Collective on PC
691 
692    Input Parameters:
693 .  pc - the multigrid context
694 
695    Options Database Key:
696 $  -pc_mg_galerkin
697 
698    Level: intermediate
699 
700 .keywords: MG, set, Galerkin
701 
702 .seealso: PCMGGetGalerkin()
703 
704 @*/
705 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetGalerkin(PC pc)
706 {
707   PC_MG    **mg;
708   PetscInt i,levels;
709 
710   PetscFunctionBegin;
711   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
712   mg     = (PC_MG**)pc->data;
713   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
714   levels = mg[0]->levels;
715 
716   for (i=0; i<levels; i++) {
717     mg[i]->galerkin = PETSC_TRUE;
718   }
719   PetscFunctionReturn(0);
720 }
721 
722 #undef __FUNCT__
723 #define __FUNCT__ "PCMGGetGalerkin"
724 /*@
725    PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e.
726       A_i-1 = r_i * A_i * r_i^t
727 
728    Not Collective
729 
730    Input Parameter:
731 .  pc - the multigrid context
732 
733    Output Parameter:
734 .  gelerkin - PETSC_TRUE or PETSC_FALSE
735 
736    Options Database Key:
737 $  -pc_mg_galerkin
738 
739    Level: intermediate
740 
741 .keywords: MG, set, Galerkin
742 
743 .seealso: PCMGSetGalerkin()
744 
745 @*/
746 PetscErrorCode PETSCKSP_DLLEXPORT PCMGGetGalerkin(PC pc,PetscTruth *galerkin)
747 {
748   PC_MG    **mg;
749 
750   PetscFunctionBegin;
751   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
752   mg     = (PC_MG**)pc->data;
753   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
754   *galerkin = mg[0]->galerkin;
755   PetscFunctionReturn(0);
756 }
757 
758 #undef __FUNCT__
759 #define __FUNCT__ "PCMGSetNumberSmoothDown"
760 /*@
761    PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to
762    use on all levels. Use PCMGGetSmootherDown() to set different
763    pre-smoothing steps on different levels.
764 
765    Collective on PC
766 
767    Input Parameters:
768 +  mg - the multigrid context
769 -  n - the number of smoothing steps
770 
771    Options Database Key:
772 .  -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps
773 
774    Level: advanced
775 
776 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid
777 
778 .seealso: PCMGSetNumberSmoothUp()
779 @*/
780 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothDown(PC pc,PetscInt n)
781 {
782   PC_MG          **mg;
783   PetscErrorCode ierr;
784   PetscInt       i,levels;
785 
786   PetscFunctionBegin;
787   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
788   mg     = (PC_MG**)pc->data;
789   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
790   levels = mg[0]->levels;
791 
792   for (i=1; i<levels; i++) {
793     /* make sure smoother up and down are different */
794     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
795     ierr = KSPSetTolerances(mg[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
796     mg[i]->default_smoothd = n;
797   }
798   PetscFunctionReturn(0);
799 }
800 
801 #undef __FUNCT__
802 #define __FUNCT__ "PCMGSetNumberSmoothUp"
803 /*@
804    PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use
805    on all levels. Use PCMGGetSmootherUp() to set different numbers of
806    post-smoothing steps on different levels.
807 
808    Collective on PC
809 
810    Input Parameters:
811 +  mg - the multigrid context
812 -  n - the number of smoothing steps
813 
814    Options Database Key:
815 .  -pc_mg_smoothup <n> - Sets number of post-smoothing steps
816 
817    Level: advanced
818 
819    Note: this does not set a value on the coarsest grid, since we assume that
820     there is no separate smooth up on the coarsest grid.
821 
822 .keywords: MG, smooth, up, post-smoothing, steps, multigrid
823 
824 .seealso: PCMGSetNumberSmoothDown()
825 @*/
826 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothUp(PC pc,PetscInt n)
827 {
828   PC_MG          **mg;
829   PetscErrorCode ierr;
830   PetscInt       i,levels;
831 
832   PetscFunctionBegin;
833   PetscValidHeaderSpecific(pc,PC_COOKIE,1);
834   mg     = (PC_MG**)pc->data;
835   if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
836   levels = mg[0]->levels;
837 
838   for (i=1; i<levels; i++) {
839     /* make sure smoother up and down are different */
840     ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr);
841     ierr = KSPSetTolerances(mg[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr);
842     mg[i]->default_smoothu = n;
843   }
844   PetscFunctionReturn(0);
845 }
846 
847 /* ----------------------------------------------------------------------------------------*/
848 
849 /*MC
850    PCMG - Use geometric multigrid preconditioning. This preconditioner requires you provide additional
851     information about the coarser grid matrices and restriction/interpolation operators.
852 
853    Options Database Keys:
854 +  -pc_mg_levels <nlevels> - number of levels including finest
855 .  -pc_mg_cycles 1 or 2 - for V or W-cycle
856 .  -pc_mg_smoothup <n> - number of smoothing steps after interpolation
857 .  -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator
858 .  -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default
859 .  -pc_mg_log - log information about time spent on each level of the solver
860 .  -pc_mg_monitor - print information on the multigrid convergence
861 .  -pc_mg_galerkin - use Galerkin process to compute coarser operators
862 -  -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices
863                         to the Socket viewer for reading from Matlab.
864 
865    Notes:
866 
867    Level: intermediate
868 
869    Concepts: multigrid
870 
871 .seealso:  PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType,
872            PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycles(), PCMGSetNumberSmoothDown(),
873            PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(),
874            PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(),
875            PCMGSetCyclesOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR()
876 M*/
877 
878 EXTERN_C_BEGIN
879 #undef __FUNCT__
880 #define __FUNCT__ "PCCreate_MG"
881 PetscErrorCode PETSCKSP_DLLEXPORT PCCreate_MG(PC pc)
882 {
883   PetscFunctionBegin;
884   pc->ops->apply          = PCApply_MG;
885   pc->ops->setup          = PCSetUp_MG;
886   pc->ops->destroy        = PCDestroy_MG;
887   pc->ops->setfromoptions = PCSetFromOptions_MG;
888   pc->ops->view           = PCView_MG;
889 
890   pc->data                = (void*)0;
891   PetscFunctionReturn(0);
892 }
893 EXTERN_C_END
894