Actual source code: gamg.c

petsc-3.11.3 2019-06-26
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  1: /*
  2:  GAMG geometric-algebric multigrid PC - Mark Adams 2011
  3:  */
  4:  #include <petsc/private/matimpl.h>
  5:  #include <../src/ksp/pc/impls/gamg/gamg.h>
  6: #include <../src/ksp/pc/impls/bjacobi/bjacobi.h> /* Hack to access same_local_solves */

  8: #if defined PETSC_GAMG_USE_LOG
  9: PetscLogEvent petsc_gamg_setup_events[NUM_SET];
 10: #endif

 12: #if defined PETSC_USE_LOG
 13: PetscLogEvent PC_GAMGGraph_AGG;
 14: PetscLogEvent PC_GAMGGraph_GEO;
 15: PetscLogEvent PC_GAMGCoarsen_AGG;
 16: PetscLogEvent PC_GAMGCoarsen_GEO;
 17: PetscLogEvent PC_GAMGProlongator_AGG;
 18: PetscLogEvent PC_GAMGProlongator_GEO;
 19: PetscLogEvent PC_GAMGOptProlongator_AGG;
 20: #endif

 22: /* #define GAMG_STAGES */
 23: #if (defined PETSC_GAMG_USE_LOG && defined GAMG_STAGES)
 24: static PetscLogStage gamg_stages[PETSC_GAMG_MAXLEVELS];
 25: #endif

 27: static PetscFunctionList GAMGList = 0;
 28: static PetscBool PCGAMGPackageInitialized;

 30: /* ----------------------------------------------------------------------------- */
 31: PetscErrorCode PCReset_GAMG(PC pc)
 32: {
 34:   PC_MG          *mg      = (PC_MG*)pc->data;
 35:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;

 38:   PetscFree(pc_gamg->data);
 39:   pc_gamg->data_sz = 0;
 40:   PetscFree(pc_gamg->orig_data);
 41:   return(0);
 42: }

 44: /* -------------------------------------------------------------------------- */
 45: /*
 46:    PCGAMGCreateLevel_GAMG: create coarse op with RAP.  repartition and/or reduce number
 47:      of active processors.

 49:    Input Parameter:
 50:    . pc - parameters + side effect: coarse data in 'pc_gamg->data' and
 51:           'pc_gamg->data_sz' are changed via repartitioning/reduction.
 52:    . Amat_fine - matrix on this fine (k) level
 53:    . cr_bs - coarse block size
 54:    In/Output Parameter:
 55:    . a_P_inout - prolongation operator to the next level (k-->k-1)
 56:    . a_nactive_proc - number of active procs
 57:    Output Parameter:
 58:    . a_Amat_crs - coarse matrix that is created (k-1)
 59: */

 61: static PetscErrorCode PCGAMGCreateLevel_GAMG(PC pc,Mat Amat_fine,PetscInt cr_bs,Mat *a_P_inout,Mat *a_Amat_crs,PetscMPIInt *a_nactive_proc,IS * Pcolumnperm, PetscBool is_last)
 62: {
 63:   PetscErrorCode  ierr;
 64:   PC_MG           *mg         = (PC_MG*)pc->data;
 65:   PC_GAMG         *pc_gamg    = (PC_GAMG*)mg->innerctx;
 66:   Mat             Cmat,Pold=*a_P_inout;
 67:   MPI_Comm        comm;
 68:   PetscMPIInt     rank,size,new_size,nactive=*a_nactive_proc;
 69:   PetscInt        ncrs_eq,ncrs,f_bs;

 72:   PetscObjectGetComm((PetscObject)Amat_fine,&comm);
 73:   MPI_Comm_rank(comm, &rank);
 74:   MPI_Comm_size(comm, &size);
 75:   MatGetBlockSize(Amat_fine, &f_bs);
 76:   MatPtAP(Amat_fine, Pold, MAT_INITIAL_MATRIX, 2.0, &Cmat);

 78:   /* set 'ncrs' (nodes), 'ncrs_eq' (equations)*/
 79:   MatGetLocalSize(Cmat, &ncrs_eq, NULL);
 80:   if (pc_gamg->data_cell_rows>0) {
 81:     ncrs = pc_gamg->data_sz/pc_gamg->data_cell_cols/pc_gamg->data_cell_rows;
 82:   } else {
 83:     PetscInt  bs;
 84:     MatGetBlockSize(Cmat, &bs);
 85:     ncrs = ncrs_eq/bs;
 86:   }

 88:   /* get number of PEs to make active 'new_size', reduce, can be any integer 1-P */
 89:   if (is_last && !pc_gamg->use_parallel_coarse_grid_solver) new_size = 1;
 90:   else {
 91:     PetscInt ncrs_eq_glob;
 92:     MatGetSize(Cmat, &ncrs_eq_glob, NULL);
 93:     new_size = (PetscMPIInt)((float)ncrs_eq_glob/(float)pc_gamg->min_eq_proc + 0.5); /* hardwire min. number of eq/proc */
 94:     if (!new_size) new_size = 1; /* not likely, posible? */
 95:     else if (new_size >= nactive) new_size = nactive; /* no change, rare */
 96:   }

 98:   if (Pcolumnperm) *Pcolumnperm = NULL;

100:   if (!pc_gamg->repart && new_size==nactive) {
101:     *a_Amat_crs = Cmat; /* output - no repartitioning or reduction - could bail here */
102:     /* we know that the grid structure can be reused in MatPtAP */
103:   } else {
104:     /* we know that the grid structure can NOT be reused in MatPtAP */
105:     PetscInt       *counts,*newproc_idx,ii,jj,kk,strideNew,*tidx,ncrs_new,ncrs_eq_new,nloc_old;
106:     IS             is_eq_newproc,is_eq_num,is_eq_num_prim,new_eq_indices;

108:     nloc_old = ncrs_eq/cr_bs;
109:     if (ncrs_eq % cr_bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"ncrs_eq %D not divisible by cr_bs %D",ncrs_eq,cr_bs);
110: #if defined PETSC_GAMG_USE_LOG
111:     PetscLogEventBegin(petsc_gamg_setup_events[SET12],0,0,0,0);
112: #endif
113:     /* make 'is_eq_newproc' */
114:     PetscMalloc1(size, &counts);
115:     if (pc_gamg->repart) {
116:       /* Repartition Cmat_{k} and move colums of P^{k}_{k-1} and coordinates of primal part accordingly */
117:       Mat adj;

119:      PetscInfo3(pc,"Repartition: size (active): %D --> %D, %D local equations\n",*a_nactive_proc,new_size,ncrs_eq);

121:       /* get 'adj' */
122:       if (cr_bs == 1) {
123:         MatConvert(Cmat, MATMPIADJ, MAT_INITIAL_MATRIX, &adj);
124:       } else {
125:         /* make a scalar matrix to partition (no Stokes here) */
126:         Mat               tMat;
127:         PetscInt          Istart_crs,Iend_crs,ncols,jj,Ii;
128:         const PetscScalar *vals;
129:         const PetscInt    *idx;
130:         PetscInt          *d_nnz, *o_nnz, M, N;
131:         static PetscInt   llev = 0;
132:         MatType           mtype;

134:         PetscMalloc2(ncrs, &d_nnz,ncrs, &o_nnz);
135:         MatGetOwnershipRange(Cmat, &Istart_crs, &Iend_crs);
136:         MatGetSize(Cmat, &M, &N);
137:         for (Ii = Istart_crs, jj = 0; Ii < Iend_crs; Ii += cr_bs, jj++) {
138:           MatGetRow(Cmat,Ii,&ncols,0,0);
139:           d_nnz[jj] = ncols/cr_bs;
140:           o_nnz[jj] = ncols/cr_bs;
141:           MatRestoreRow(Cmat,Ii,&ncols,0,0);
142:           if (d_nnz[jj] > ncrs) d_nnz[jj] = ncrs;
143:           if (o_nnz[jj] > (M/cr_bs-ncrs)) o_nnz[jj] = M/cr_bs-ncrs;
144:         }

146:         MatGetType(Amat_fine,&mtype);
147:         MatCreate(comm, &tMat);
148:         MatSetSizes(tMat, ncrs, ncrs,PETSC_DETERMINE, PETSC_DETERMINE);
149:         MatSetType(tMat,mtype);
150:         MatSeqAIJSetPreallocation(tMat,0,d_nnz);
151:         MatMPIAIJSetPreallocation(tMat,0,d_nnz,0,o_nnz);
152:         PetscFree2(d_nnz,o_nnz);

154:         for (ii = Istart_crs; ii < Iend_crs; ii++) {
155:           PetscInt dest_row = ii/cr_bs;
156:           MatGetRow(Cmat,ii,&ncols,&idx,&vals);
157:           for (jj = 0; jj < ncols; jj++) {
158:             PetscInt    dest_col = idx[jj]/cr_bs;
159:             PetscScalar v        = 1.0;
160:             MatSetValues(tMat,1,&dest_row,1,&dest_col,&v,ADD_VALUES);
161:           }
162:           MatRestoreRow(Cmat,ii,&ncols,&idx,&vals);
163:         }
164:         MatAssemblyBegin(tMat,MAT_FINAL_ASSEMBLY);
165:         MatAssemblyEnd(tMat,MAT_FINAL_ASSEMBLY);

167:         if (llev++ == -1) {
168:           PetscViewer viewer; char fname[32];
169:           PetscSNPrintf(fname,sizeof(fname),"part_mat_%D.mat",llev);
170:           PetscViewerBinaryOpen(comm,fname,FILE_MODE_WRITE,&viewer);
171:           MatView(tMat, viewer);
172:           PetscViewerDestroy(&viewer);
173:         }
174:         MatConvert(tMat, MATMPIADJ, MAT_INITIAL_MATRIX, &adj);
175:         MatDestroy(&tMat);
176:       } /* create 'adj' */

178:       { /* partition: get newproc_idx */
179:         char            prefix[256];
180:         const char      *pcpre;
181:         const PetscInt  *is_idx;
182:         MatPartitioning mpart;
183:         IS              proc_is;
184:         PetscInt        targetPE;

186:         MatPartitioningCreate(comm, &mpart);
187:         MatPartitioningSetAdjacency(mpart, adj);
188:         PCGetOptionsPrefix(pc, &pcpre);
189:         PetscSNPrintf(prefix,sizeof(prefix),"%spc_gamg_",pcpre ? pcpre : "");
190:         PetscObjectSetOptionsPrefix((PetscObject)mpart,prefix);
191:         MatPartitioningSetFromOptions(mpart);
192:         MatPartitioningSetNParts(mpart, new_size);
193:         MatPartitioningApply(mpart, &proc_is);
194:         MatPartitioningDestroy(&mpart);

196:         /* collect IS info */
197:         PetscMalloc1(ncrs_eq, &newproc_idx);
198:         ISGetIndices(proc_is, &is_idx);
199:         targetPE = 1; /* bring to "front" of machine */
200:         /*targetPE = size/new_size;*/ /* spread partitioning across machine */
201:         for (kk = jj = 0 ; kk < nloc_old ; kk++) {
202:           for (ii = 0 ; ii < cr_bs ; ii++, jj++) {
203:             newproc_idx[jj] = is_idx[kk] * targetPE; /* distribution */
204:           }
205:         }
206:         ISRestoreIndices(proc_is, &is_idx);
207:         ISDestroy(&proc_is);
208:       }
209:       MatDestroy(&adj);

211:       ISCreateGeneral(comm, ncrs_eq, newproc_idx, PETSC_COPY_VALUES, &is_eq_newproc);
212:       PetscFree(newproc_idx);
213:     } else { /* simple aggreagtion of parts -- 'is_eq_newproc' */
214:       PetscInt rfactor,targetPE;

216:       /* find factor */
217:       if (new_size == 1) rfactor = size; /* easy */
218:       else {
219:         PetscReal best_fact = 0.;
220:         jj = -1;
221:         for (kk = 1 ; kk <= size ; kk++) {
222:           if (!(size%kk)) { /* a candidate */
223:             PetscReal nactpe = (PetscReal)size/(PetscReal)kk, fact = nactpe/(PetscReal)new_size;
224:             if (fact > 1.0) fact = 1./fact; /* keep fact < 1 */
225:             if (fact > best_fact) {
226:               best_fact = fact; jj = kk;
227:             }
228:           }
229:         }
230:         if (jj != -1) rfactor = jj;
231:         else rfactor = 1; /* does this happen .. a prime */
232:       }
233:       new_size = size/rfactor;

235:       if (new_size==nactive) {
236:         *a_Amat_crs = Cmat; /* output - no repartitioning or reduction, bail out because nested here */
237:         PetscFree(counts);
238:         PetscInfo2(pc,"Aggregate processors noop: new_size=%D, neq(loc)=%D\n",new_size,ncrs_eq);
239: #if defined PETSC_GAMG_USE_LOG
240:         PetscLogEventEnd(petsc_gamg_setup_events[SET12],0,0,0,0);
241: #endif
242:         return(0);
243:       }

245:       PetscInfo1(pc,"Number of equations (loc) %D with simple aggregation\n",ncrs_eq);
246:       targetPE = rank/rfactor;
247:       ISCreateStride(comm, ncrs_eq, targetPE, 0, &is_eq_newproc);
248:     } /* end simple 'is_eq_newproc' */

250:     /*
251:      Create an index set from the is_eq_newproc index set to indicate the mapping TO
252:      */
253:     ISPartitioningToNumbering(is_eq_newproc, &is_eq_num);
254:     is_eq_num_prim = is_eq_num;
255:     /*
256:       Determine how many equations/vertices are assigned to each processor
257:      */
258:     ISPartitioningCount(is_eq_newproc, size, counts);
259:     ncrs_eq_new = counts[rank];
260:     ISDestroy(&is_eq_newproc);
261:     ncrs_new = ncrs_eq_new/cr_bs; /* eqs */

263:     PetscFree(counts);
264: #if defined PETSC_GAMG_USE_LOG
265:     PetscLogEventEnd(petsc_gamg_setup_events[SET12],0,0,0,0);
266: #endif
267:     /* data movement scope -- this could be moved to subclasses so that we don't try to cram all auxilary data into some complex abstracted thing */
268:     {
269:     Vec            src_crd, dest_crd;
270:     const PetscInt *idx,ndata_rows=pc_gamg->data_cell_rows,ndata_cols=pc_gamg->data_cell_cols,node_data_sz=ndata_rows*ndata_cols;
271:     VecScatter     vecscat;
272:     PetscScalar    *array;
273:     IS isscat;

275:     /* move data (for primal equations only) */
276:     /* Create a vector to contain the newly ordered element information */
277:     VecCreate(comm, &dest_crd);
278:     VecSetSizes(dest_crd, node_data_sz*ncrs_new, PETSC_DECIDE);
279:     VecSetType(dest_crd,VECSTANDARD); /* this is needed! */
280:     /*
281:      There are 'ndata_rows*ndata_cols' data items per node, (one can think of the vectors of having
282:      a block size of ...).  Note, ISs are expanded into equation space by 'cr_bs'.
283:      */
284:     PetscMalloc1(ncrs*node_data_sz, &tidx);
285:     ISGetIndices(is_eq_num_prim, &idx);
286:     for (ii=0,jj=0; ii<ncrs; ii++) {
287:       PetscInt id = idx[ii*cr_bs]/cr_bs; /* get node back */
288:       for (kk=0; kk<node_data_sz; kk++, jj++) tidx[jj] = id*node_data_sz + kk;
289:     }
290:     ISRestoreIndices(is_eq_num_prim, &idx);
291:     ISCreateGeneral(comm, node_data_sz*ncrs, tidx, PETSC_COPY_VALUES, &isscat);
292:     PetscFree(tidx);
293:     /*
294:      Create a vector to contain the original vertex information for each element
295:      */
296:     VecCreateSeq(PETSC_COMM_SELF, node_data_sz*ncrs, &src_crd);
297:     for (jj=0; jj<ndata_cols; jj++) {
298:       const PetscInt stride0=ncrs*pc_gamg->data_cell_rows;
299:       for (ii=0; ii<ncrs; ii++) {
300:         for (kk=0; kk<ndata_rows; kk++) {
301:           PetscInt    ix = ii*ndata_rows + kk + jj*stride0, jx = ii*node_data_sz + kk*ndata_cols + jj;
302:           PetscScalar tt = (PetscScalar)pc_gamg->data[ix];
303:           VecSetValues(src_crd, 1, &jx, &tt, INSERT_VALUES);
304:         }
305:       }
306:     }
307:     VecAssemblyBegin(src_crd);
308:     VecAssemblyEnd(src_crd);
309:     /*
310:       Scatter the element vertex information (still in the original vertex ordering)
311:       to the correct processor
312:     */
313:     VecScatterCreate(src_crd, NULL, dest_crd, isscat, &vecscat);
314:     ISDestroy(&isscat);
315:     VecScatterBegin(vecscat,src_crd,dest_crd,INSERT_VALUES,SCATTER_FORWARD);
316:     VecScatterEnd(vecscat,src_crd,dest_crd,INSERT_VALUES,SCATTER_FORWARD);
317:     VecScatterDestroy(&vecscat);
318:     VecDestroy(&src_crd);
319:     /*
320:       Put the element vertex data into a new allocation of the gdata->ele
321:     */
322:     PetscFree(pc_gamg->data);
323:     PetscMalloc1(node_data_sz*ncrs_new, &pc_gamg->data);

325:     pc_gamg->data_sz = node_data_sz*ncrs_new;
326:     strideNew        = ncrs_new*ndata_rows;

328:     VecGetArray(dest_crd, &array);
329:     for (jj=0; jj<ndata_cols; jj++) {
330:       for (ii=0; ii<ncrs_new; ii++) {
331:         for (kk=0; kk<ndata_rows; kk++) {
332:           PetscInt ix = ii*ndata_rows + kk + jj*strideNew, jx = ii*node_data_sz + kk*ndata_cols + jj;
333:           pc_gamg->data[ix] = PetscRealPart(array[jx]);
334:         }
335:       }
336:     }
337:     VecRestoreArray(dest_crd, &array);
338:     VecDestroy(&dest_crd);
339:     }
340:     /* move A and P (columns) with new layout */
341: #if defined PETSC_GAMG_USE_LOG
342:     PetscLogEventBegin(petsc_gamg_setup_events[SET13],0,0,0,0);
343: #endif

345:     /*
346:       Invert for MatCreateSubMatrix
347:     */
348:     ISInvertPermutation(is_eq_num, ncrs_eq_new, &new_eq_indices);
349:     ISSort(new_eq_indices); /* is this needed? */
350:     ISSetBlockSize(new_eq_indices, cr_bs);
351:     if (is_eq_num != is_eq_num_prim) {
352:       ISDestroy(&is_eq_num_prim); /* could be same as 'is_eq_num' */
353:     }
354:     if (Pcolumnperm) {
355:       PetscObjectReference((PetscObject)new_eq_indices);
356:       *Pcolumnperm = new_eq_indices;
357:     }
358:     ISDestroy(&is_eq_num);
359: #if defined PETSC_GAMG_USE_LOG
360:     PetscLogEventEnd(petsc_gamg_setup_events[SET13],0,0,0,0);
361:     PetscLogEventBegin(petsc_gamg_setup_events[SET14],0,0,0,0);
362: #endif
363:     /* 'a_Amat_crs' output */
364:     {
365:       Mat mat;
366:       MatCreateSubMatrix(Cmat, new_eq_indices, new_eq_indices, MAT_INITIAL_MATRIX, &mat);
367:       *a_Amat_crs = mat;
368:     }
369:     MatDestroy(&Cmat);

371: #if defined PETSC_GAMG_USE_LOG
372:     PetscLogEventEnd(petsc_gamg_setup_events[SET14],0,0,0,0);
373: #endif
374:     /* prolongator */
375:     {
376:       IS       findices;
377:       PetscInt Istart,Iend;
378:       Mat      Pnew;

380:       MatGetOwnershipRange(Pold, &Istart, &Iend);
381: #if defined PETSC_GAMG_USE_LOG
382:       PetscLogEventBegin(petsc_gamg_setup_events[SET15],0,0,0,0);
383: #endif
384:       ISCreateStride(comm,Iend-Istart,Istart,1,&findices);
385:       ISSetBlockSize(findices,f_bs);
386:       MatCreateSubMatrix(Pold, findices, new_eq_indices, MAT_INITIAL_MATRIX, &Pnew);
387:       ISDestroy(&findices);

389: #if defined PETSC_GAMG_USE_LOG
390:       PetscLogEventEnd(petsc_gamg_setup_events[SET15],0,0,0,0);
391: #endif
392:       MatDestroy(a_P_inout);

394:       /* output - repartitioned */
395:       *a_P_inout = Pnew;
396:     }
397:     ISDestroy(&new_eq_indices);

399:     *a_nactive_proc = new_size; /* output */
400:   }
401:   return(0);
402: }

404: /* -------------------------------------------------------------------------- */
405: /*
406:    PCSetUp_GAMG - Prepares for the use of the GAMG preconditioner
407:                     by setting data structures and options.

409:    Input Parameter:
410: .  pc - the preconditioner context

412: */
413: PetscErrorCode PCSetUp_GAMG(PC pc)
414: {
416:   PC_MG          *mg      = (PC_MG*)pc->data;
417:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;
418:   Mat            Pmat     = pc->pmat;
419:   PetscInt       fine_level,level,level1,bs,M,N,qq,lidx,nASMBlocksArr[PETSC_GAMG_MAXLEVELS];
420:   MPI_Comm       comm;
421:   PetscMPIInt    rank,size,nactivepe;
422:   Mat            Aarr[PETSC_GAMG_MAXLEVELS],Parr[PETSC_GAMG_MAXLEVELS];
423:   IS             *ASMLocalIDsArr[PETSC_GAMG_MAXLEVELS];
424:   PetscLogDouble nnz0=0.,nnztot=0.;
425:   MatInfo        info;
426:   PetscBool      is_last = PETSC_FALSE;

429:   PetscObjectGetComm((PetscObject)pc,&comm);
430:   MPI_Comm_rank(comm,&rank);
431:   MPI_Comm_size(comm,&size);

433:   if (pc_gamg->setup_count++ > 0) {
434:     if ((PetscBool)(!pc_gamg->reuse_prol)) {
435:       /* reset everything */
436:       PCReset_MG(pc);
437:       pc->setupcalled = 0;
438:     } else {
439:       PC_MG_Levels **mglevels = mg->levels;
440:       /* just do Galerkin grids */
441:       Mat          B,dA,dB;

443:       if (!pc->setupcalled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"PCSetUp() has not been called yet");
444:       if (pc_gamg->Nlevels > 1) {
445:         /* currently only handle case where mat and pmat are the same on coarser levels */
446:         KSPGetOperators(mglevels[pc_gamg->Nlevels-1]->smoothd,&dA,&dB);
447:         /* (re)set to get dirty flag */
448:         KSPSetOperators(mglevels[pc_gamg->Nlevels-1]->smoothd,dA,dB);

450:         for (level=pc_gamg->Nlevels-2; level>=0; level--) {
451:           /* 2nd solve, matrix structure can change from repartitioning or process reduction but don't know if we have process reduction here. Should fix */
452:           if (pc_gamg->setup_count==2 /* && pc_gamg->repart||reduction */) {
453:             PetscInfo2(pc,"new RAP after first solve level %D, %D setup\n",level,pc_gamg->setup_count);
454:             MatPtAP(dB,mglevels[level+1]->interpolate,MAT_INITIAL_MATRIX,2.0,&B);
455:             MatDestroy(&mglevels[level]->A);
456:             mglevels[level]->A = B;
457:           } else {
458:             PetscInfo2(pc,"RAP after first solve reusing matrix level %D, %D setup\n",level,pc_gamg->setup_count);
459:             KSPGetOperators(mglevels[level]->smoothd,NULL,&B);
460:             MatPtAP(dB,mglevels[level+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);
461:           }
462:           KSPSetOperators(mglevels[level]->smoothd,B,B);
463:           dB   = B;
464:         }
465:       }

467:       PCSetUp_MG(pc);
468:       return(0);
469:     }
470:   }

472:   if (!pc_gamg->data) {
473:     if (pc_gamg->orig_data) {
474:       MatGetBlockSize(Pmat, &bs);
475:       MatGetLocalSize(Pmat, &qq, NULL);

477:       pc_gamg->data_sz        = (qq/bs)*pc_gamg->orig_data_cell_rows*pc_gamg->orig_data_cell_cols;
478:       pc_gamg->data_cell_rows = pc_gamg->orig_data_cell_rows;
479:       pc_gamg->data_cell_cols = pc_gamg->orig_data_cell_cols;

481:       PetscMalloc1(pc_gamg->data_sz, &pc_gamg->data);
482:       for (qq=0; qq<pc_gamg->data_sz; qq++) pc_gamg->data[qq] = pc_gamg->orig_data[qq];
483:     } else {
484:       if (!pc_gamg->ops->createdefaultdata) SETERRQ(comm,PETSC_ERR_PLIB,"'createdefaultdata' not set(?) need to support NULL data");
485:       pc_gamg->ops->createdefaultdata(pc,Pmat);
486:     }
487:   }

489:   /* cache original data for reuse */
490:   if (!pc_gamg->orig_data && (PetscBool)(!pc_gamg->reuse_prol)) {
491:     PetscMalloc1(pc_gamg->data_sz, &pc_gamg->orig_data);
492:     for (qq=0; qq<pc_gamg->data_sz; qq++) pc_gamg->orig_data[qq] = pc_gamg->data[qq];
493:     pc_gamg->orig_data_cell_rows = pc_gamg->data_cell_rows;
494:     pc_gamg->orig_data_cell_cols = pc_gamg->data_cell_cols;
495:   }

497:   /* get basic dims */
498:   MatGetBlockSize(Pmat, &bs);
499:   MatGetSize(Pmat, &M, &N);

501:   MatGetInfo(Pmat,MAT_GLOBAL_SUM,&info); /* global reduction */
502:   nnz0   = info.nz_used;
503:   nnztot = info.nz_used;
504:   PetscInfo6(pc,"level %d) N=%D, n data rows=%d, n data cols=%d, nnz/row (ave)=%d, np=%d\n",0,M,pc_gamg->data_cell_rows,pc_gamg->data_cell_cols,(int)(nnz0/(PetscReal)M+0.5),size);

506:   /* Get A_i and R_i */
507:   for (level=0, Aarr[0]=Pmat, nactivepe = size; level < (pc_gamg->Nlevels-1) && (!level || M>pc_gamg->coarse_eq_limit); level++) {
508:     pc_gamg->current_level = level;
509:     level1 = level + 1;
510: #if defined PETSC_GAMG_USE_LOG
511:     PetscLogEventBegin(petsc_gamg_setup_events[SET1],0,0,0,0);
512: #if (defined GAMG_STAGES)
513:     PetscLogStagePush(gamg_stages[level]);
514: #endif
515: #endif
516:     { /* construct prolongator */
517:       Mat              Gmat;
518:       PetscCoarsenData *agg_lists;
519:       Mat              Prol11;

521:       pc_gamg->ops->graph(pc,Aarr[level], &Gmat);
522:       pc_gamg->ops->coarsen(pc, &Gmat, &agg_lists);
523:       pc_gamg->ops->prolongator(pc,Aarr[level],Gmat,agg_lists,&Prol11);

525:       /* could have failed to create new level */
526:       if (Prol11) {
527:         /* get new block size of coarse matrices */
528:         MatGetBlockSizes(Prol11, NULL, &bs);

530:         if (pc_gamg->ops->optprolongator) {
531:           /* smooth */
532:           pc_gamg->ops->optprolongator(pc, Aarr[level], &Prol11);
533:         }

535:         if (pc_gamg->use_aggs_in_asm) {
536:           PetscInt bs;
537:           MatGetBlockSizes(Prol11, &bs, NULL);
538:           PetscCDGetASMBlocks(agg_lists, bs, Gmat, &nASMBlocksArr[level], &ASMLocalIDsArr[level]);
539:         }

541:         Parr[level1] = Prol11;
542:       } else Parr[level1] = NULL; /* failed to coarsen */

544:       MatDestroy(&Gmat);
545:       PetscCDDestroy(agg_lists);
546:     } /* construct prolongator scope */
547: #if defined PETSC_GAMG_USE_LOG
548:     PetscLogEventEnd(petsc_gamg_setup_events[SET1],0,0,0,0);
549: #endif
550:     if (!level) Aarr[0] = Pmat; /* use Pmat for finest level setup */
551:     if (!Parr[level1]) { /* failed to coarsen */
552:        PetscInfo1(pc,"Stop gridding, level %D\n",level);
553: #if defined PETSC_GAMG_USE_LOG && defined GAMG_STAGES
554:       PetscLogStagePop();
555: #endif
556:       break;
557:     }
558: #if defined PETSC_GAMG_USE_LOG
559:     PetscLogEventBegin(petsc_gamg_setup_events[SET2],0,0,0,0);
560: #endif
561:     MatGetSize(Parr[level1], &M, &N); /* N is next M, a loop test variables */
562:     if (is_last) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Is last ????????");
563:     if (N <= pc_gamg->coarse_eq_limit) is_last = PETSC_TRUE;
564:     if (level1 == pc_gamg->Nlevels-1) is_last = PETSC_TRUE;
565:     pc_gamg->ops->createlevel(pc, Aarr[level], bs, &Parr[level1], &Aarr[level1], &nactivepe, NULL, is_last);

567: #if defined PETSC_GAMG_USE_LOG
568:     PetscLogEventEnd(petsc_gamg_setup_events[SET2],0,0,0,0);
569: #endif
570:     MatGetSize(Aarr[level1], &M, &N); /* M is loop test variables */
571:     MatGetInfo(Aarr[level1], MAT_GLOBAL_SUM, &info);
572:     nnztot += info.nz_used;
573:     PetscInfo5(pc,"%d) N=%D, n data cols=%d, nnz/row (ave)=%d, %d active pes\n",level1,M,pc_gamg->data_cell_cols,(int)(info.nz_used/(PetscReal)M),nactivepe);

575: #if (defined PETSC_GAMG_USE_LOG && defined GAMG_STAGES)
576:     PetscLogStagePop();
577: #endif
578:     /* stop if one node or one proc -- could pull back for singular problems */
579:     if ( (pc_gamg->data_cell_cols && M/pc_gamg->data_cell_cols < 2) || (!pc_gamg->data_cell_cols && M/bs < 2) ) {
580:        PetscInfo2(pc,"HARD stop of coarsening on level %D.  Grid too small: %D block nodes\n",level,M/bs);
581:       level++;
582:       break;
583:     }
584:   } /* levels */
585:   PetscFree(pc_gamg->data);

587:   PetscInfo2(pc,"%D levels, grid complexity = %g\n",level+1,nnztot/nnz0);
588:   pc_gamg->Nlevels = level + 1;
589:   fine_level       = level;
590:   PCMGSetLevels(pc,pc_gamg->Nlevels,NULL);

592:   if (pc_gamg->Nlevels > 1) { /* don't setup MG if one level */
593:     /* set default smoothers & set operators */
594:     for (lidx = 1, level = pc_gamg->Nlevels-2; lidx <= fine_level; lidx++, level--) {
595:       KSP smoother;
596:       PC  subpc;

598:       PCMGGetSmoother(pc, lidx, &smoother);
599:       KSPGetPC(smoother, &subpc);

601:       KSPSetNormType(smoother, KSP_NORM_NONE);
602:       /* set ops */
603:       KSPSetOperators(smoother, Aarr[level], Aarr[level]);
604:       PCMGSetInterpolation(pc, lidx, Parr[level+1]);

606:       /* set defaults */
607:       KSPSetType(smoother, KSPCHEBYSHEV);

609:       /* set blocks for ASM smoother that uses the 'aggregates' */
610:       if (pc_gamg->use_aggs_in_asm) {
611:         PetscInt sz;
612:         IS       *iss;

614:         sz   = nASMBlocksArr[level];
615:         iss   = ASMLocalIDsArr[level];
616:         PCSetType(subpc, PCASM);
617:         PCASMSetOverlap(subpc, 0);
618:         PCASMSetType(subpc,PC_ASM_BASIC);
619:         if (!sz) {
620:           IS       is;
621:           ISCreateGeneral(PETSC_COMM_SELF, 0, NULL, PETSC_COPY_VALUES, &is);
622:           PCASMSetLocalSubdomains(subpc, 1, NULL, &is);
623:           ISDestroy(&is);
624:         } else {
625:           PetscInt kk;
626:           PCASMSetLocalSubdomains(subpc, sz, NULL, iss);
627:           for (kk=0; kk<sz; kk++) {
628:             ISDestroy(&iss[kk]);
629:           }
630:           PetscFree(iss);
631:         }
632:         ASMLocalIDsArr[level] = NULL;
633:         nASMBlocksArr[level]  = 0;
634:       } else {
635:         PCSetType(subpc, PCSOR);
636:       }
637:     }
638:     {
639:       /* coarse grid */
640:       KSP smoother,*k2; PC subpc,pc2; PetscInt ii,first;
641:       Mat Lmat = Aarr[(level=pc_gamg->Nlevels-1)]; lidx = 0;
642:       PCMGGetSmoother(pc, lidx, &smoother);
643:       KSPSetOperators(smoother, Lmat, Lmat);
644:       if (!pc_gamg->use_parallel_coarse_grid_solver) {
645:         KSPSetNormType(smoother, KSP_NORM_NONE);
646:         KSPGetPC(smoother, &subpc);
647:         PCSetType(subpc, PCBJACOBI);
648:         PCSetUp(subpc);
649:         PCBJacobiGetSubKSP(subpc,&ii,&first,&k2);
650:         if (ii != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_PLIB,"ii %D is not one",ii);
651:         KSPGetPC(k2[0],&pc2);
652:         PCSetType(pc2, PCLU);
653:         PCFactorSetShiftType(pc2,MAT_SHIFT_INBLOCKS);
654:         KSPSetTolerances(k2[0],PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,1);
655:         KSPSetType(k2[0], KSPPREONLY);
656:         /* This flag gets reset by PCBJacobiGetSubKSP(), but our BJacobi really does the same algorithm everywhere (and in
657:          * fact, all but one process will have zero dofs), so we reset the flag to avoid having PCView_BJacobi attempt to
658:          * view every subdomain as though they were different. */
659:         ((PC_BJacobi*)subpc->data)->same_local_solves = PETSC_TRUE;
660:       }
661:     }

663:     /* should be called in PCSetFromOptions_GAMG(), but cannot be called prior to PCMGSetLevels() */
664:     PetscObjectOptionsBegin((PetscObject)pc);
665:     PCSetFromOptions_MG(PetscOptionsObject,pc);
666:     PetscOptionsEnd();
667:     PCMGSetGalerkin(pc,PC_MG_GALERKIN_EXTERNAL);

669:     /* clean up */
670:     for (level=1; level<pc_gamg->Nlevels; level++) {
671:       MatDestroy(&Parr[level]);
672:       MatDestroy(&Aarr[level]);
673:     }
674:     PCSetUp_MG(pc);
675:   } else {
676:     KSP smoother;
677:     PetscInfo(pc,"One level solver used (system is seen as DD). Using default solver.\n");
678:     PCMGGetSmoother(pc, 0, &smoother);
679:     KSPSetOperators(smoother, Aarr[0], Aarr[0]);
680:     KSPSetType(smoother, KSPPREONLY);
681:     PCSetUp_MG(pc);
682:   }
683:   return(0);
684: }

686: /* ------------------------------------------------------------------------- */
687: /*
688:  PCDestroy_GAMG - Destroys the private context for the GAMG preconditioner
689:    that was created with PCCreate_GAMG().

691:    Input Parameter:
692: .  pc - the preconditioner context

694:    Application Interface Routine: PCDestroy()
695: */
696: PetscErrorCode PCDestroy_GAMG(PC pc)
697: {
699:   PC_MG          *mg     = (PC_MG*)pc->data;
700:   PC_GAMG        *pc_gamg= (PC_GAMG*)mg->innerctx;

703:   PCReset_GAMG(pc);
704:   if (pc_gamg->ops->destroy) {
705:     (*pc_gamg->ops->destroy)(pc);
706:   }
707:   PetscFree(pc_gamg->ops);
708:   PetscFree(pc_gamg->gamg_type_name);
709:   PetscFree(pc_gamg);
710:   PCDestroy_MG(pc);
711:   return(0);
712: }

714: /*@
715:    PCGAMGSetProcEqLim - Set number of equations to aim for per process on the coarse grids via processor reduction.

717:    Logically Collective on PC

719:    Input Parameters:
720: +  pc - the preconditioner context
721: -  n - the number of equations


724:    Options Database Key:
725: .  -pc_gamg_process_eq_limit <limit>

727:    Notes:
728:     GAMG will reduce the number of MPI processes used directly on the coarse grids so that there are around <limit> equations on each process 
729:           that has degrees of freedom

731:    Level: intermediate

733:    Concepts: Unstructured multigrid preconditioner

735: .seealso: PCGAMGSetCoarseEqLim()
736: @*/
737: PetscErrorCode  PCGAMGSetProcEqLim(PC pc, PetscInt n)
738: {

743:   PetscTryMethod(pc,"PCGAMGSetProcEqLim_C",(PC,PetscInt),(pc,n));
744:   return(0);
745: }

747: static PetscErrorCode PCGAMGSetProcEqLim_GAMG(PC pc, PetscInt n)
748: {
749:   PC_MG   *mg      = (PC_MG*)pc->data;
750:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

753:   if (n>0) pc_gamg->min_eq_proc = n;
754:   return(0);
755: }

757: /*@
758:    PCGAMGSetCoarseEqLim - Set maximum number of equations on coarsest grid.

760:  Collective on PC

762:    Input Parameters:
763: +  pc - the preconditioner context
764: -  n - maximum number of equations to aim for

766:    Options Database Key:
767: .  -pc_gamg_coarse_eq_limit <limit>

769:    Notes: For example -pc_gamg_coarse_eq_limit 1000 will stop coarsening once the coarse grid 
770:      has less than 1000 unknowns.

772:    Level: intermediate

774:    Concepts: Unstructured multigrid preconditioner

776: .seealso: PCGAMGSetProcEqLim()
777: @*/
778: PetscErrorCode PCGAMGSetCoarseEqLim(PC pc, PetscInt n)
779: {

784:   PetscTryMethod(pc,"PCGAMGSetCoarseEqLim_C",(PC,PetscInt),(pc,n));
785:   return(0);
786: }

788: static PetscErrorCode PCGAMGSetCoarseEqLim_GAMG(PC pc, PetscInt n)
789: {
790:   PC_MG   *mg      = (PC_MG*)pc->data;
791:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

794:   if (n>0) pc_gamg->coarse_eq_limit = n;
795:   return(0);
796: }

798: /*@
799:    PCGAMGSetRepartition - Repartition the degrees of freedom across the processors on the coarser grids

801:    Collective on PC

803:    Input Parameters:
804: +  pc - the preconditioner context
805: -  n - PETSC_TRUE or PETSC_FALSE

807:    Options Database Key:
808: .  -pc_gamg_repartition <true,false>

810:    Notes:
811:     this will generally improve the loading balancing of the work on each level

813:    Level: intermediate

815:    Concepts: Unstructured multigrid preconditioner

817: .seealso: ()
818: @*/
819: PetscErrorCode PCGAMGSetRepartition(PC pc, PetscBool n)
820: {

825:   PetscTryMethod(pc,"PCGAMGSetRepartition_C",(PC,PetscBool),(pc,n));
826:   return(0);
827: }

829: static PetscErrorCode PCGAMGSetRepartition_GAMG(PC pc, PetscBool n)
830: {
831:   PC_MG   *mg      = (PC_MG*)pc->data;
832:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

835:   pc_gamg->repart = n;
836:   return(0);
837: }

839: /*@
840:    PCGAMGSetReuseInterpolation - Reuse prolongation when rebuilding algebraic multigrid preconditioner

842:    Collective on PC

844:    Input Parameters:
845: +  pc - the preconditioner context
846: -  n - PETSC_TRUE or PETSC_FALSE

848:    Options Database Key:
849: .  -pc_gamg_reuse_interpolation <true,false>

851:    Level: intermediate

853:    Notes:
854:     this may negatively affect the convergence rate of the method on new matrices if the matrix entries change a great deal, but allows
855:           rebuilding the preconditioner quicker.

857:    Concepts: Unstructured multigrid preconditioner

859: .seealso: ()
860: @*/
861: PetscErrorCode PCGAMGSetReuseInterpolation(PC pc, PetscBool n)
862: {

867:   PetscTryMethod(pc,"PCGAMGSetReuseInterpolation_C",(PC,PetscBool),(pc,n));
868:   return(0);
869: }

871: static PetscErrorCode PCGAMGSetReuseInterpolation_GAMG(PC pc, PetscBool n)
872: {
873:   PC_MG   *mg      = (PC_MG*)pc->data;
874:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

877:   pc_gamg->reuse_prol = n;
878:   return(0);
879: }

881: /*@
882:    PCGAMGASMSetUseAggs - Have the PCGAMG smoother on each level use the aggregates defined by the coarsening process as the subdomains for the additive Schwarz preconditioner.

884:    Collective on PC

886:    Input Parameters:
887: +  pc - the preconditioner context
888: -  flg - PETSC_TRUE to use aggregates, PETSC_FALSE to not

890:    Options Database Key:
891: .  -pc_gamg_asm_use_agg

893:    Level: intermediate

895:    Concepts: Unstructured multigrid preconditioner

897: .seealso: ()
898: @*/
899: PetscErrorCode PCGAMGASMSetUseAggs(PC pc, PetscBool flg)
900: {

905:   PetscTryMethod(pc,"PCGAMGASMSetUseAggs_C",(PC,PetscBool),(pc,flg));
906:   return(0);
907: }

909: static PetscErrorCode PCGAMGASMSetUseAggs_GAMG(PC pc, PetscBool flg)
910: {
911:   PC_MG   *mg      = (PC_MG*)pc->data;
912:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

915:   pc_gamg->use_aggs_in_asm = flg;
916:   return(0);
917: }

919: /*@
920:    PCGAMGSetUseParallelCoarseGridSolve - allow a parallel coarse grid solver

922:    Collective on PC

924:    Input Parameters:
925: +  pc - the preconditioner context
926: -  flg - PETSC_TRUE to not force coarse grid onto one processor

928:    Options Database Key:
929: .  -pc_gamg_use_parallel_coarse_grid_solver

931:    Level: intermediate

933:    Concepts: Unstructured multigrid preconditioner

935: .seealso: ()
936: @*/
937: PetscErrorCode PCGAMGSetUseParallelCoarseGridSolve(PC pc, PetscBool flg)
938: {

943:   PetscTryMethod(pc,"PCGAMGSetUseParallelCoarseGridSolve_C",(PC,PetscBool),(pc,flg));
944:   return(0);
945: }

947: static PetscErrorCode PCGAMGSetUseParallelCoarseGridSolve_GAMG(PC pc, PetscBool flg)
948: {
949:   PC_MG   *mg      = (PC_MG*)pc->data;
950:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

953:   pc_gamg->use_parallel_coarse_grid_solver = flg;
954:   return(0);
955: }

957: /*@
958:    PCGAMGSetNlevels -  Sets the maximum number of levels PCGAMG will use

960:    Not collective on PC

962:    Input Parameters:
963: +  pc - the preconditioner
964: -  n - the maximum number of levels to use

966:    Options Database Key:
967: .  -pc_mg_levels

969:    Level: intermediate

971:    Concepts: Unstructured multigrid preconditioner

973: .seealso: ()
974: @*/
975: PetscErrorCode PCGAMGSetNlevels(PC pc, PetscInt n)
976: {

981:   PetscTryMethod(pc,"PCGAMGSetNlevels_C",(PC,PetscInt),(pc,n));
982:   return(0);
983: }

985: static PetscErrorCode PCGAMGSetNlevels_GAMG(PC pc, PetscInt n)
986: {
987:   PC_MG   *mg      = (PC_MG*)pc->data;
988:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

991:   pc_gamg->Nlevels = n;
992:   return(0);
993: }

995: /*@
996:    PCGAMGSetThreshold - Relative threshold to use for dropping edges in aggregation graph

998:    Not collective on PC

1000:    Input Parameters:
1001: +  pc - the preconditioner context
1002: -  threshold - the threshold value, 0.0 means keep all nonzero entries in the graph; negative means keep even zero entries in the graph

1004:    Options Database Key:
1005: .  -pc_gamg_threshold <threshold>

1007:    Notes:
1008:     Increasing the threshold decreases the rate of coarsening. Conversely reducing the threshold increases the rate of coarsening (aggressive coarsening) and thereby reduces the complexity of the coarse grids, and generally results in slower solver converge rates. Reducing coarse grid complexity reduced the complexity of Galerkin coarse grid construction considerably.
1009:     Before coarsening or aggregating the graph, GAMG removes small values from the graph with this threshold, and thus reducing the coupling in the graph and a different (perhaps better) coarser set of points.

1011:    Level: intermediate

1013:    Concepts: Unstructured multigrid preconditioner

1015: .seealso: PCGAMGFilterGraph(), PCGAMGSetSquareGraph()
1016: @*/
1017: PetscErrorCode PCGAMGSetThreshold(PC pc, PetscReal v[], PetscInt n)
1018: {

1023:   PetscTryMethod(pc,"PCGAMGSetThreshold_C",(PC,PetscReal[],PetscInt),(pc,v,n));
1024:   return(0);
1025: }

1027: static PetscErrorCode PCGAMGSetThreshold_GAMG(PC pc, PetscReal v[], PetscInt n)
1028: {
1029:   PC_MG   *mg      = (PC_MG*)pc->data;
1030:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
1031:   PetscInt i;
1033:   for (i=0;i<n;i++) pc_gamg->threshold[i] = v[i];
1034:   do {pc_gamg->threshold[i] = pc_gamg->threshold[i-1]*pc_gamg->threshold_scale;} while (++i<PETSC_GAMG_MAXLEVELS);
1035:   return(0);
1036: }

1038: /*@
1039:    PCGAMGSetThresholdScale - Relative threshold reduction at each level

1041:    Not collective on PC

1043:    Input Parameters:
1044: +  pc - the preconditioner context
1045: -  scale - the threshold value reduction, ussually < 1.0

1047:    Options Database Key:
1048: .  -pc_gamg_threshold_scale <v>

1050:    Level: advanced

1052:    Concepts: Unstructured multigrid preconditioner

1054: .seealso: ()
1055: @*/
1056: PetscErrorCode PCGAMGSetThresholdScale(PC pc, PetscReal v)
1057: {

1062:   PetscTryMethod(pc,"PCGAMGSetThresholdScale_C",(PC,PetscReal),(pc,v));
1063:   return(0);
1064: }

1066: static PetscErrorCode PCGAMGSetThresholdScale_GAMG(PC pc, PetscReal v)
1067: {
1068:   PC_MG   *mg      = (PC_MG*)pc->data;
1069:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
1071:   pc_gamg->threshold_scale = v;
1072:   return(0);
1073: }

1075: /*@C
1076:    PCGAMGSetType - Set solution method

1078:    Collective on PC

1080:    Input Parameters:
1081: +  pc - the preconditioner context
1082: -  type - PCGAMGAGG, PCGAMGGEO, or PCGAMGCLASSICAL

1084:    Options Database Key:
1085: .  -pc_gamg_type <agg,geo,classical> - type of algebraic multigrid to apply

1087:    Level: intermediate

1089:    Concepts: Unstructured multigrid preconditioner

1091: .seealso: PCGAMGGetType(), PCGAMG, PCGAMGType
1092: @*/
1093: PetscErrorCode PCGAMGSetType(PC pc, PCGAMGType type)
1094: {

1099:   PetscTryMethod(pc,"PCGAMGSetType_C",(PC,PCGAMGType),(pc,type));
1100:   return(0);
1101: }

1103: /*@C
1104:    PCGAMGGetType - Get solution method

1106:    Collective on PC

1108:    Input Parameter:
1109: .  pc - the preconditioner context

1111:    Output Parameter:
1112: .  type - the type of algorithm used

1114:    Level: intermediate

1116:    Concepts: Unstructured multigrid preconditioner

1118: .seealso: PCGAMGSetType(), PCGAMGType
1119: @*/
1120: PetscErrorCode PCGAMGGetType(PC pc, PCGAMGType *type)
1121: {

1126:   PetscUseMethod(pc,"PCGAMGGetType_C",(PC,PCGAMGType*),(pc,type));
1127:   return(0);
1128: }

1130: static PetscErrorCode PCGAMGGetType_GAMG(PC pc, PCGAMGType *type)
1131: {
1132:   PC_MG          *mg      = (PC_MG*)pc->data;
1133:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;

1136:   *type = pc_gamg->type;
1137:   return(0);
1138: }

1140: static PetscErrorCode PCGAMGSetType_GAMG(PC pc, PCGAMGType type)
1141: {
1142:   PetscErrorCode ierr,(*r)(PC);
1143:   PC_MG          *mg      = (PC_MG*)pc->data;
1144:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;

1147:   pc_gamg->type = type;
1148:   PetscFunctionListFind(GAMGList,type,&r);
1149:   if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown GAMG type %s given",type);
1150:   if (pc_gamg->ops->destroy) {
1151:     (*pc_gamg->ops->destroy)(pc);
1152:     PetscMemzero(pc_gamg->ops,sizeof(struct _PCGAMGOps));
1153:     pc_gamg->ops->createlevel = PCGAMGCreateLevel_GAMG;
1154:     /* cleaning up common data in pc_gamg - this should disapear someday */
1155:     pc_gamg->data_cell_cols = 0;
1156:     pc_gamg->data_cell_rows = 0;
1157:     pc_gamg->orig_data_cell_cols = 0;
1158:     pc_gamg->orig_data_cell_rows = 0;
1159:     PetscFree(pc_gamg->data);
1160:     pc_gamg->data_sz = 0;
1161:   }
1162:   PetscFree(pc_gamg->gamg_type_name);
1163:   PetscStrallocpy(type,&pc_gamg->gamg_type_name);
1164:   (*r)(pc);
1165:   return(0);
1166: }

1168: /* -------------------------------------------------------------------------- */
1169: /*
1170:    PCMGGetGridComplexity - compute coarse grid complexity of MG hierarchy

1172:    Input Parameter:
1173: .  pc - the preconditioner context

1175:    Output Parameter:
1176: .  gc - grid complexity = sum_i(nnz_i) / nnz_0

1178:    Level: advanced
1179: */
1180: static PetscErrorCode PCMGGetGridComplexity(PC pc, PetscReal *gc)
1181: {
1183:   PC_MG          *mg      = (PC_MG*)pc->data;
1184:   PC_MG_Levels   **mglevels = mg->levels;
1185:   PetscInt       lev, nnz0 = -1;
1186:   MatInfo        info;
1188:   if (!mg->nlevels) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MG has no levels");
1189:   for (lev=0, *gc=0; lev<mg->nlevels; lev++) {
1190:     Mat dB;
1191:     KSPGetOperators(mglevels[lev]->smoothd,NULL,&dB);
1192:     MatGetInfo(dB,MAT_GLOBAL_SUM,&info); /* global reduction */
1193:     *gc += (PetscReal)info.nz_used;
1194:     if (lev==mg->nlevels-1) nnz0 = info.nz_used;
1195:   }
1196:   if (nnz0) *gc /= (PetscReal)nnz0;
1197:   else *gc = 0;
1198:   return(0);
1199: }

1201: static PetscErrorCode PCView_GAMG(PC pc,PetscViewer viewer)
1202: {
1203:   PetscErrorCode ierr,i;
1204:   PC_MG          *mg      = (PC_MG*)pc->data;
1205:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;
1206:   PetscReal       gc=0;
1208:   PetscViewerASCIIPrintf(viewer,"    GAMG specific options\n");
1209:   PetscViewerASCIIPrintf(viewer,"      Threshold for dropping small values in graph on each level =");
1210:   for (i=0;i<pc_gamg->current_level;i++) {
1211:     PetscViewerASCIIPrintf(viewer," %g",(double)pc_gamg->threshold[i]);
1212:   }
1213:   PetscViewerASCIIPrintf(viewer,"\n");
1214:   PetscViewerASCIIPrintf(viewer,"      Threshold scaling factor for each level not specified = %g\n",(double)pc_gamg->threshold_scale);
1215:   if (pc_gamg->use_aggs_in_asm) {
1216:     PetscViewerASCIIPrintf(viewer,"      Using aggregates from coarsening process to define subdomains for PCASM\n");
1217:   }
1218:   if (pc_gamg->use_parallel_coarse_grid_solver) {
1219:     PetscViewerASCIIPrintf(viewer,"      Using parallel coarse grid solver (all coarse grid equations not put on one process)\n");
1220:   }
1221:   if (pc_gamg->ops->view) {
1222:     (*pc_gamg->ops->view)(pc,viewer);
1223:   }
1224:   PCMGGetGridComplexity(pc,&gc);
1225:   PetscViewerASCIIPrintf(viewer,"      Complexity:    grid = %g\n",gc);
1226:   return(0);
1227: }

1229: PetscErrorCode PCSetFromOptions_GAMG(PetscOptionItems *PetscOptionsObject,PC pc)
1230: {
1232:   PC_MG          *mg      = (PC_MG*)pc->data;
1233:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;
1234:   PetscBool      flag;
1235:   MPI_Comm       comm;
1236:   char           prefix[256];
1237:   PetscInt       i,n;
1238:   const char     *pcpre;

1241:   PetscObjectGetComm((PetscObject)pc,&comm);
1242:   PetscOptionsHead(PetscOptionsObject,"GAMG options");
1243:   {
1244:     char tname[256];
1245:     PetscOptionsFList("-pc_gamg_type","Type of AMG method","PCGAMGSetType",GAMGList, pc_gamg->gamg_type_name, tname, sizeof(tname), &flag);
1246:     if (flag) {
1247:       PCGAMGSetType(pc,tname);
1248:     }
1249:     PetscOptionsBool("-pc_gamg_repartition","Repartion coarse grids","PCGAMGSetRepartition",pc_gamg->repart,&pc_gamg->repart,NULL);
1250:     PetscOptionsBool("-pc_gamg_reuse_interpolation","Reuse prolongation operator","PCGAMGReuseInterpolation",pc_gamg->reuse_prol,&pc_gamg->reuse_prol,NULL);
1251:     PetscOptionsBool("-pc_gamg_asm_use_agg","Use aggregation aggregates for ASM smoother","PCGAMGASMSetUseAggs",pc_gamg->use_aggs_in_asm,&pc_gamg->use_aggs_in_asm,NULL);
1252:     PetscOptionsBool("-pc_gamg_use_parallel_coarse_grid_solver","Use parallel coarse grid solver (otherwise put last grid on one process)","PCGAMGSetUseParallelCoarseGridSolve",pc_gamg->use_parallel_coarse_grid_solver,&pc_gamg->use_parallel_coarse_grid_solver,NULL);
1253:     PetscOptionsInt("-pc_gamg_process_eq_limit","Limit (goal) on number of equations per process on coarse grids","PCGAMGSetProcEqLim",pc_gamg->min_eq_proc,&pc_gamg->min_eq_proc,NULL);
1254:     PetscOptionsInt("-pc_gamg_coarse_eq_limit","Limit on number of equations for the coarse grid","PCGAMGSetCoarseEqLim",pc_gamg->coarse_eq_limit,&pc_gamg->coarse_eq_limit,NULL);
1255:     PetscOptionsReal("-pc_gamg_threshold_scale","Scaling of threshold for each level not specified","PCGAMGSetThresholdScale",pc_gamg->threshold_scale,&pc_gamg->threshold_scale,NULL);
1256:     n = PETSC_GAMG_MAXLEVELS;
1257:     PetscOptionsRealArray("-pc_gamg_threshold","Relative threshold to use for dropping edges in aggregation graph","PCGAMGSetThreshold",pc_gamg->threshold,&n,&flag);
1258:     if (!flag || n < PETSC_GAMG_MAXLEVELS) {
1259:       if (!flag) n = 1;
1260:       i = n;
1261:       do {pc_gamg->threshold[i] = pc_gamg->threshold[i-1]*pc_gamg->threshold_scale;} while (++i<PETSC_GAMG_MAXLEVELS);
1262:     }
1263:     PetscOptionsInt("-pc_mg_levels","Set number of MG levels","PCGAMGSetNlevels",pc_gamg->Nlevels,&pc_gamg->Nlevels,NULL);

1265:     /* set options for subtype */
1266:     if (pc_gamg->ops->setfromoptions) {(*pc_gamg->ops->setfromoptions)(PetscOptionsObject,pc);}
1267:   }
1268:   PCGetOptionsPrefix(pc, &pcpre);
1269:   PetscSNPrintf(prefix,sizeof(prefix),"%spc_gamg_",pcpre ? pcpre : "");
1270:   PetscOptionsTail();
1271:   return(0);
1272: }

1274: /* -------------------------------------------------------------------------- */
1275: /*MC
1276:      PCGAMG - Geometric algebraic multigrid (AMG) preconditioner

1278:    Options Database Keys:
1279: +   -pc_gamg_type <type> - one of agg, geo, or classical
1280: .   -pc_gamg_repartition  <true,default=false> - repartition the degrees of freedom accross the coarse grids as they are determined
1281: .   -pc_gamg_reuse_interpolation <true,default=false> - when rebuilding the algebraic multigrid preconditioner reuse the previously computed interpolations
1282: .   -pc_gamg_asm_use_agg <true,default=false> - use the aggregates from the coasening process to defined the subdomains on each level for the PCASM smoother
1283: .   -pc_gamg_process_eq_limit <limit, default=50> - GAMG will reduce the number of MPI processes used directly on the coarse grids so that there are around <limit>
1284:                                         equations on each process that has degrees of freedom
1285: .   -pc_gamg_coarse_eq_limit <limit, default=50> - Set maximum number of equations on coarsest grid to aim for.
1286: .   -pc_gamg_threshold[] <thresh,default=0> - Before aggregating the graph GAMG will remove small values from the graph on each level
1287: -   -pc_gamg_threshold_scale <scale,default=1> - Scaling of threshold on each coarser grid if not specified

1289:    Options Database Keys for default Aggregation:
1290: +  -pc_gamg_agg_nsmooths <nsmooth, default=1> - number of smoothing steps to use with smooth aggregation
1291: .  -pc_gamg_sym_graph <true,default=false> - symmetrize the graph before computing the aggregation
1292: -  -pc_gamg_square_graph <n,default=1> - number of levels to square the graph before aggregating it

1294:    Multigrid options:
1295: +  -pc_mg_cycles <v> - v or w, see PCMGSetCycleType()
1296: .  -pc_mg_distinct_smoothup - configure the up and down (pre and post) smoothers separately, see PCMGSetDistinctSmoothUp()
1297: .  -pc_mg_type <multiplicative> - (one of) additive multiplicative full kascade
1298: -  -pc_mg_levels <levels> - Number of levels of multigrid to use.


1301:   Notes:
1302:     In order to obtain good performance for PCGAMG for vector valued problems you must
1303:        Call MatSetBlockSize() to indicate the number of degrees of freedom per grid point
1304:        Call MatSetNearNullSpace() (or PCSetCoordinates() if solving the equations of elasticity) to indicate the near null space of the operator
1305:        See the Users Manual Chapter 4 for more details

1307:   Level: intermediate

1309:   Concepts: algebraic multigrid

1311: .seealso:  PCCreate(), PCSetType(), MatSetBlockSize(), PCMGType, PCSetCoordinates(), MatSetNearNullSpace(), PCGAMGSetType(), PCGAMGAGG, PCGAMGGEO, PCGAMGCLASSICAL, PCGAMGSetProcEqLim(),
1312:            PCGAMGSetCoarseEqLim(), PCGAMGSetRepartition(), PCGAMGRegister(), PCGAMGSetReuseInterpolation(), PCGAMGASMSetUseAggs(), PCGAMGSetUseParallelCoarseGridSolve(), PCGAMGSetNlevels(), PCGAMGSetThreshold(), PCGAMGGetType(), PCGAMGSetReuseInterpolation()
1313: M*/

1315: PETSC_EXTERN PetscErrorCode PCCreate_GAMG(PC pc)
1316: {
1317:   PetscErrorCode ierr,i;
1318:   PC_GAMG        *pc_gamg;
1319:   PC_MG          *mg;

1322:    /* register AMG type */
1323:   PCGAMGInitializePackage();

1325:   /* PCGAMG is an inherited class of PCMG. Initialize pc as PCMG */
1326:   PCSetType(pc, PCMG);
1327:   PetscObjectChangeTypeName((PetscObject)pc, PCGAMG);

1329:   /* create a supporting struct and attach it to pc */
1330:   PetscNewLog(pc,&pc_gamg);
1331:   PCMGSetGalerkin(pc,PC_MG_GALERKIN_EXTERNAL);
1332:   mg           = (PC_MG*)pc->data;
1333:   mg->innerctx = pc_gamg;

1335:   PetscNewLog(pc,&pc_gamg->ops);

1337:   pc_gamg->setup_count = 0;
1338:   /* these should be in subctx but repartitioning needs simple arrays */
1339:   pc_gamg->data_sz = 0;
1340:   pc_gamg->data    = 0;

1342:   /* overwrite the pointers of PCMG by the functions of base class PCGAMG */
1343:   pc->ops->setfromoptions = PCSetFromOptions_GAMG;
1344:   pc->ops->setup          = PCSetUp_GAMG;
1345:   pc->ops->reset          = PCReset_GAMG;
1346:   pc->ops->destroy        = PCDestroy_GAMG;
1347:   mg->view                = PCView_GAMG;

1349:   PetscObjectComposeFunction((PetscObject)pc,"PCMGGetLevels_C",PCMGGetLevels_MG);
1350:   PetscObjectComposeFunction((PetscObject)pc,"PCMGSetLevels_C",PCMGSetLevels_MG);
1351:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetProcEqLim_C",PCGAMGSetProcEqLim_GAMG);
1352:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetCoarseEqLim_C",PCGAMGSetCoarseEqLim_GAMG);
1353:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetRepartition_C",PCGAMGSetRepartition_GAMG);
1354:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetReuseInterpolation_C",PCGAMGSetReuseInterpolation_GAMG);
1355:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGASMSetUseAggs_C",PCGAMGASMSetUseAggs_GAMG);
1356:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetUseParallelCoarseGridSolve_C",PCGAMGSetUseParallelCoarseGridSolve_GAMG);
1357:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetThreshold_C",PCGAMGSetThreshold_GAMG);
1358:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetThresholdScale_C",PCGAMGSetThresholdScale_GAMG);
1359:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetType_C",PCGAMGSetType_GAMG);
1360:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGGetType_C",PCGAMGGetType_GAMG);
1361:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetNlevels_C",PCGAMGSetNlevels_GAMG);
1362:   pc_gamg->repart           = PETSC_FALSE;
1363:   pc_gamg->reuse_prol       = PETSC_FALSE;
1364:   pc_gamg->use_aggs_in_asm  = PETSC_FALSE;
1365:   pc_gamg->use_parallel_coarse_grid_solver = PETSC_FALSE;
1366:   pc_gamg->min_eq_proc      = 50;
1367:   pc_gamg->coarse_eq_limit  = 50;
1368:   for (i=0;i<PETSC_GAMG_MAXLEVELS;i++) pc_gamg->threshold[i] = 0.;
1369:   pc_gamg->threshold_scale = 1.;
1370:   pc_gamg->Nlevels          = PETSC_GAMG_MAXLEVELS;
1371:   pc_gamg->current_level    = 0; /* don't need to init really */
1372:   pc_gamg->ops->createlevel = PCGAMGCreateLevel_GAMG;

1374:   /* PCSetUp_GAMG assumes that the type has been set, so set it to the default now */
1375:   PCGAMGSetType(pc,PCGAMGAGG);
1376:   return(0);
1377: }

1379: /*@C
1380:  PCGAMGInitializePackage - This function initializes everything in the PCGAMG package. It is called
1381:     from PCInitializePackage().

1383:  Level: developer

1385:  .keywords: PC, PCGAMG, initialize, package
1386:  .seealso: PetscInitialize()
1387: @*/
1388: PetscErrorCode PCGAMGInitializePackage(void)
1389: {

1393:   if (PCGAMGPackageInitialized) return(0);
1394:   PCGAMGPackageInitialized = PETSC_TRUE;
1395:   PetscFunctionListAdd(&GAMGList,PCGAMGGEO,PCCreateGAMG_GEO);
1396:   PetscFunctionListAdd(&GAMGList,PCGAMGAGG,PCCreateGAMG_AGG);
1397:   PetscFunctionListAdd(&GAMGList,PCGAMGCLASSICAL,PCCreateGAMG_Classical);
1398:   PetscRegisterFinalize(PCGAMGFinalizePackage);

1400:   /* general events */
1401:   PetscLogEventRegister("PCGAMGGraph_AGG", 0, &PC_GAMGGraph_AGG);
1402:   PetscLogEventRegister("PCGAMGGraph_GEO", PC_CLASSID, &PC_GAMGGraph_GEO);
1403:   PetscLogEventRegister("PCGAMGCoarse_AGG", PC_CLASSID, &PC_GAMGCoarsen_AGG);
1404:   PetscLogEventRegister("PCGAMGCoarse_GEO", PC_CLASSID, &PC_GAMGCoarsen_GEO);
1405:   PetscLogEventRegister("PCGAMGProl_AGG", PC_CLASSID, &PC_GAMGProlongator_AGG);
1406:   PetscLogEventRegister("PCGAMGProl_GEO", PC_CLASSID, &PC_GAMGProlongator_GEO);
1407:   PetscLogEventRegister("PCGAMGPOpt_AGG", PC_CLASSID, &PC_GAMGOptProlongator_AGG);

1409: #if defined PETSC_GAMG_USE_LOG
1410:   PetscLogEventRegister("GAMG: createProl", PC_CLASSID, &petsc_gamg_setup_events[SET1]);
1411:   PetscLogEventRegister("  Graph", PC_CLASSID, &petsc_gamg_setup_events[GRAPH]);
1412:   /* PetscLogEventRegister("    G.Mat", PC_CLASSID, &petsc_gamg_setup_events[GRAPH_MAT]); */
1413:   /* PetscLogEventRegister("    G.Filter", PC_CLASSID, &petsc_gamg_setup_events[GRAPH_FILTER]); */
1414:   /* PetscLogEventRegister("    G.Square", PC_CLASSID, &petsc_gamg_setup_events[GRAPH_SQR]); */
1415:   PetscLogEventRegister("  MIS/Agg", PC_CLASSID, &petsc_gamg_setup_events[SET4]);
1416:   PetscLogEventRegister("  geo: growSupp", PC_CLASSID, &petsc_gamg_setup_events[SET5]);
1417:   PetscLogEventRegister("  geo: triangle", PC_CLASSID, &petsc_gamg_setup_events[SET6]);
1418:   PetscLogEventRegister("    search-set", PC_CLASSID, &petsc_gamg_setup_events[FIND_V]);
1419:   PetscLogEventRegister("  SA: col data", PC_CLASSID, &petsc_gamg_setup_events[SET7]);
1420:   PetscLogEventRegister("  SA: frmProl0", PC_CLASSID, &petsc_gamg_setup_events[SET8]);
1421:   PetscLogEventRegister("  SA: smooth", PC_CLASSID, &petsc_gamg_setup_events[SET9]);
1422:   PetscLogEventRegister("GAMG: partLevel", PC_CLASSID, &petsc_gamg_setup_events[SET2]);
1423:   PetscLogEventRegister("  repartition", PC_CLASSID, &petsc_gamg_setup_events[SET12]);
1424:   PetscLogEventRegister("  Invert-Sort", PC_CLASSID, &petsc_gamg_setup_events[SET13]);
1425:   PetscLogEventRegister("  Move A", PC_CLASSID, &petsc_gamg_setup_events[SET14]);
1426:   PetscLogEventRegister("  Move P", PC_CLASSID, &petsc_gamg_setup_events[SET15]);

1428:   /* PetscLogEventRegister(" PL move data", PC_CLASSID, &petsc_gamg_setup_events[SET13]); */
1429:   /* PetscLogEventRegister("GAMG: fix", PC_CLASSID, &petsc_gamg_setup_events[SET10]); */
1430:   /* PetscLogEventRegister("GAMG: set levels", PC_CLASSID, &petsc_gamg_setup_events[SET11]); */
1431:   /* create timer stages */
1432: #if defined GAMG_STAGES
1433:   {
1434:     char     str[32];
1435:     PetscInt lidx;
1436:     sprintf(str,"MG Level %d (finest)",0);
1437:     PetscLogStageRegister(str, &gamg_stages[0]);
1438:     for (lidx=1; lidx<9; lidx++) {
1439:       sprintf(str,"MG Level %d",lidx);
1440:       PetscLogStageRegister(str, &gamg_stages[lidx]);
1441:     }
1442:   }
1443: #endif
1444: #endif
1445:   return(0);
1446: }

1448: /*@C
1449:  PCGAMGFinalizePackage - This function frees everything from the PCGAMG package. It is
1450:     called from PetscFinalize() automatically.

1452:  Level: developer

1454:  .keywords: Petsc, destroy, package
1455:  .seealso: PetscFinalize()
1456: @*/
1457: PetscErrorCode PCGAMGFinalizePackage(void)
1458: {

1462:   PCGAMGPackageInitialized = PETSC_FALSE;
1463:   PetscFunctionListDestroy(&GAMGList);
1464:   return(0);
1465: }

1467: /*@C
1468:  PCGAMGRegister - Register a PCGAMG implementation.

1470:  Input Parameters:
1471:  + type - string that will be used as the name of the GAMG type.
1472:  - create - function for creating the gamg context.

1474:   Level: advanced

1476:  .seealso: PCGAMGType, PCGAMG, PCGAMGSetType()
1477: @*/
1478: PetscErrorCode PCGAMGRegister(PCGAMGType type, PetscErrorCode (*create)(PC))
1479: {

1483:   PCGAMGInitializePackage();
1484:   PetscFunctionListAdd(&GAMGList,type,create);
1485:   return(0);
1486: }