Actual source code: gamg.c
petsc-3.9.4 2018-09-11
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: if (pc_gamg->data) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_PLIB,"This should not happen, cleaned up in SetUp\n");
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) *a_Amat_crs = Cmat; /* output - no repartitioning or reduction - could bail here */
101: else {
102: PetscInt *counts,*newproc_idx,ii,jj,kk,strideNew,*tidx,ncrs_new,ncrs_eq_new,nloc_old;
103: IS is_eq_newproc,is_eq_num,is_eq_num_prim,new_eq_indices;
105: nloc_old = ncrs_eq/cr_bs;
106: 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);
107: #if defined PETSC_GAMG_USE_LOG
108: PetscLogEventBegin(petsc_gamg_setup_events[SET12],0,0,0,0);
109: #endif
110: /* make 'is_eq_newproc' */
111: PetscMalloc1(size, &counts);
112: if (pc_gamg->repart) {
113: /* Repartition Cmat_{k} and move colums of P^{k}_{k-1} and coordinates of primal part accordingly */
114: Mat adj;
116: PetscInfo3(pc,"Repartition: size (active): %D --> %D, %D local equations\n",*a_nactive_proc,new_size,ncrs_eq);
118: /* get 'adj' */
119: if (cr_bs == 1) {
120: MatConvert(Cmat, MATMPIADJ, MAT_INITIAL_MATRIX, &adj);
121: } else {
122: /* make a scalar matrix to partition (no Stokes here) */
123: Mat tMat;
124: PetscInt Istart_crs,Iend_crs,ncols,jj,Ii;
125: const PetscScalar *vals;
126: const PetscInt *idx;
127: PetscInt *d_nnz, *o_nnz, M, N;
128: static PetscInt llev = 0;
129: MatType mtype;
131: PetscMalloc2(ncrs, &d_nnz,ncrs, &o_nnz);
132: MatGetOwnershipRange(Cmat, &Istart_crs, &Iend_crs);
133: MatGetSize(Cmat, &M, &N);
134: for (Ii = Istart_crs, jj = 0; Ii < Iend_crs; Ii += cr_bs, jj++) {
135: MatGetRow(Cmat,Ii,&ncols,0,0);
136: d_nnz[jj] = ncols/cr_bs;
137: o_nnz[jj] = ncols/cr_bs;
138: MatRestoreRow(Cmat,Ii,&ncols,0,0);
139: if (d_nnz[jj] > ncrs) d_nnz[jj] = ncrs;
140: if (o_nnz[jj] > (M/cr_bs-ncrs)) o_nnz[jj] = M/cr_bs-ncrs;
141: }
143: MatGetType(Amat_fine,&mtype);
144: MatCreate(comm, &tMat);
145: MatSetSizes(tMat, ncrs, ncrs,PETSC_DETERMINE, PETSC_DETERMINE);
146: MatSetType(tMat,mtype);
147: MatSeqAIJSetPreallocation(tMat,0,d_nnz);
148: MatMPIAIJSetPreallocation(tMat,0,d_nnz,0,o_nnz);
149: PetscFree2(d_nnz,o_nnz);
151: for (ii = Istart_crs; ii < Iend_crs; ii++) {
152: PetscInt dest_row = ii/cr_bs;
153: MatGetRow(Cmat,ii,&ncols,&idx,&vals);
154: for (jj = 0; jj < ncols; jj++) {
155: PetscInt dest_col = idx[jj]/cr_bs;
156: PetscScalar v = 1.0;
157: MatSetValues(tMat,1,&dest_row,1,&dest_col,&v,ADD_VALUES);
158: }
159: MatRestoreRow(Cmat,ii,&ncols,&idx,&vals);
160: }
161: MatAssemblyBegin(tMat,MAT_FINAL_ASSEMBLY);
162: MatAssemblyEnd(tMat,MAT_FINAL_ASSEMBLY);
164: if (llev++ == -1) {
165: PetscViewer viewer; char fname[32];
166: PetscSNPrintf(fname,sizeof(fname),"part_mat_%D.mat",llev);
167: PetscViewerBinaryOpen(comm,fname,FILE_MODE_WRITE,&viewer);
168: MatView(tMat, viewer);
169: PetscViewerDestroy(&viewer);
170: }
171: MatConvert(tMat, MATMPIADJ, MAT_INITIAL_MATRIX, &adj);
172: MatDestroy(&tMat);
173: } /* create 'adj' */
175: { /* partition: get newproc_idx */
176: char prefix[256];
177: const char *pcpre;
178: const PetscInt *is_idx;
179: MatPartitioning mpart;
180: IS proc_is;
181: PetscInt targetPE;
183: MatPartitioningCreate(comm, &mpart);
184: MatPartitioningSetAdjacency(mpart, adj);
185: PCGetOptionsPrefix(pc, &pcpre);
186: PetscSNPrintf(prefix,sizeof(prefix),"%spc_gamg_",pcpre ? pcpre : "");
187: PetscObjectSetOptionsPrefix((PetscObject)mpart,prefix);
188: MatPartitioningSetFromOptions(mpart);
189: MatPartitioningSetNParts(mpart, new_size);
190: MatPartitioningApply(mpart, &proc_is);
191: MatPartitioningDestroy(&mpart);
193: /* collect IS info */
194: PetscMalloc1(ncrs_eq, &newproc_idx);
195: ISGetIndices(proc_is, &is_idx);
196: targetPE = 1; /* bring to "front" of machine */
197: /*targetPE = size/new_size;*/ /* spread partitioning across machine */
198: for (kk = jj = 0 ; kk < nloc_old ; kk++) {
199: for (ii = 0 ; ii < cr_bs ; ii++, jj++) {
200: newproc_idx[jj] = is_idx[kk] * targetPE; /* distribution */
201: }
202: }
203: ISRestoreIndices(proc_is, &is_idx);
204: ISDestroy(&proc_is);
205: }
206: MatDestroy(&adj);
208: ISCreateGeneral(comm, ncrs_eq, newproc_idx, PETSC_COPY_VALUES, &is_eq_newproc);
209: PetscFree(newproc_idx);
210: } else { /* simple aggreagtion of parts -- 'is_eq_newproc' */
211: PetscInt rfactor,targetPE;
213: /* find factor */
214: if (new_size == 1) rfactor = size; /* easy */
215: else {
216: PetscReal best_fact = 0.;
217: jj = -1;
218: for (kk = 1 ; kk <= size ; kk++) {
219: if (!(size%kk)) { /* a candidate */
220: PetscReal nactpe = (PetscReal)size/(PetscReal)kk, fact = nactpe/(PetscReal)new_size;
221: if (fact > 1.0) fact = 1./fact; /* keep fact < 1 */
222: if (fact > best_fact) {
223: best_fact = fact; jj = kk;
224: }
225: }
226: }
227: if (jj != -1) rfactor = jj;
228: else rfactor = 1; /* does this happen .. a prime */
229: }
230: new_size = size/rfactor;
232: if (new_size==nactive) {
233: *a_Amat_crs = Cmat; /* output - no repartitioning or reduction, bail out because nested here */
234: PetscFree(counts);
235: PetscInfo2(pc,"Aggregate processors noop: new_size=%D, neq(loc)=%D\n",new_size,ncrs_eq);
236: #if defined PETSC_GAMG_USE_LOG
237: PetscLogEventEnd(petsc_gamg_setup_events[SET12],0,0,0,0);
238: #endif
239: return(0);
240: }
242: PetscInfo1(pc,"Number of equations (loc) %D with simple aggregation\n",ncrs_eq);
243: targetPE = rank/rfactor;
244: ISCreateStride(comm, ncrs_eq, targetPE, 0, &is_eq_newproc);
245: } /* end simple 'is_eq_newproc' */
247: /*
248: Create an index set from the is_eq_newproc index set to indicate the mapping TO
249: */
250: ISPartitioningToNumbering(is_eq_newproc, &is_eq_num);
251: is_eq_num_prim = is_eq_num;
252: /*
253: Determine how many equations/vertices are assigned to each processor
254: */
255: ISPartitioningCount(is_eq_newproc, size, counts);
256: ncrs_eq_new = counts[rank];
257: ISDestroy(&is_eq_newproc);
258: ncrs_new = ncrs_eq_new/cr_bs; /* eqs */
260: PetscFree(counts);
261: #if defined PETSC_GAMG_USE_LOG
262: PetscLogEventEnd(petsc_gamg_setup_events[SET12],0,0,0,0);
263: #endif
264: /* 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 */
265: {
266: Vec src_crd, dest_crd;
267: const PetscInt *idx,ndata_rows=pc_gamg->data_cell_rows,ndata_cols=pc_gamg->data_cell_cols,node_data_sz=ndata_rows*ndata_cols;
268: VecScatter vecscat;
269: PetscScalar *array;
270: IS isscat;
272: /* move data (for primal equations only) */
273: /* Create a vector to contain the newly ordered element information */
274: VecCreate(comm, &dest_crd);
275: VecSetSizes(dest_crd, node_data_sz*ncrs_new, PETSC_DECIDE);
276: VecSetType(dest_crd,VECSTANDARD); /* this is needed! */
277: /*
278: There are 'ndata_rows*ndata_cols' data items per node, (one can think of the vectors of having
279: a block size of ...). Note, ISs are expanded into equation space by 'cr_bs'.
280: */
281: PetscMalloc1(ncrs*node_data_sz, &tidx);
282: ISGetIndices(is_eq_num_prim, &idx);
283: for (ii=0,jj=0; ii<ncrs; ii++) {
284: PetscInt id = idx[ii*cr_bs]/cr_bs; /* get node back */
285: for (kk=0; kk<node_data_sz; kk++, jj++) tidx[jj] = id*node_data_sz + kk;
286: }
287: ISRestoreIndices(is_eq_num_prim, &idx);
288: ISCreateGeneral(comm, node_data_sz*ncrs, tidx, PETSC_COPY_VALUES, &isscat);
289: PetscFree(tidx);
290: /*
291: Create a vector to contain the original vertex information for each element
292: */
293: VecCreateSeq(PETSC_COMM_SELF, node_data_sz*ncrs, &src_crd);
294: for (jj=0; jj<ndata_cols; jj++) {
295: const PetscInt stride0=ncrs*pc_gamg->data_cell_rows;
296: for (ii=0; ii<ncrs; ii++) {
297: for (kk=0; kk<ndata_rows; kk++) {
298: PetscInt ix = ii*ndata_rows + kk + jj*stride0, jx = ii*node_data_sz + kk*ndata_cols + jj;
299: PetscScalar tt = (PetscScalar)pc_gamg->data[ix];
300: VecSetValues(src_crd, 1, &jx, &tt, INSERT_VALUES);
301: }
302: }
303: }
304: VecAssemblyBegin(src_crd);
305: VecAssemblyEnd(src_crd);
306: /*
307: Scatter the element vertex information (still in the original vertex ordering)
308: to the correct processor
309: */
310: VecScatterCreate(src_crd, NULL, dest_crd, isscat, &vecscat);
311: ISDestroy(&isscat);
312: VecScatterBegin(vecscat,src_crd,dest_crd,INSERT_VALUES,SCATTER_FORWARD);
313: VecScatterEnd(vecscat,src_crd,dest_crd,INSERT_VALUES,SCATTER_FORWARD);
314: VecScatterDestroy(&vecscat);
315: VecDestroy(&src_crd);
316: /*
317: Put the element vertex data into a new allocation of the gdata->ele
318: */
319: PetscFree(pc_gamg->data);
320: PetscMalloc1(node_data_sz*ncrs_new, &pc_gamg->data);
322: pc_gamg->data_sz = node_data_sz*ncrs_new;
323: strideNew = ncrs_new*ndata_rows;
325: VecGetArray(dest_crd, &array);
326: for (jj=0; jj<ndata_cols; jj++) {
327: for (ii=0; ii<ncrs_new; ii++) {
328: for (kk=0; kk<ndata_rows; kk++) {
329: PetscInt ix = ii*ndata_rows + kk + jj*strideNew, jx = ii*node_data_sz + kk*ndata_cols + jj;
330: pc_gamg->data[ix] = PetscRealPart(array[jx]);
331: }
332: }
333: }
334: VecRestoreArray(dest_crd, &array);
335: VecDestroy(&dest_crd);
336: }
337: /* move A and P (columns) with new layout */
338: #if defined PETSC_GAMG_USE_LOG
339: PetscLogEventBegin(petsc_gamg_setup_events[SET13],0,0,0,0);
340: #endif
342: /*
343: Invert for MatCreateSubMatrix
344: */
345: ISInvertPermutation(is_eq_num, ncrs_eq_new, &new_eq_indices);
346: ISSort(new_eq_indices); /* is this needed? */
347: ISSetBlockSize(new_eq_indices, cr_bs);
348: if (is_eq_num != is_eq_num_prim) {
349: ISDestroy(&is_eq_num_prim); /* could be same as 'is_eq_num' */
350: }
351: if (Pcolumnperm) {
352: PetscObjectReference((PetscObject)new_eq_indices);
353: *Pcolumnperm = new_eq_indices;
354: }
355: ISDestroy(&is_eq_num);
356: #if defined PETSC_GAMG_USE_LOG
357: PetscLogEventEnd(petsc_gamg_setup_events[SET13],0,0,0,0);
358: PetscLogEventBegin(petsc_gamg_setup_events[SET14],0,0,0,0);
359: #endif
360: /* 'a_Amat_crs' output */
361: {
362: Mat mat;
363: MatCreateSubMatrix(Cmat, new_eq_indices, new_eq_indices, MAT_INITIAL_MATRIX, &mat);
364: *a_Amat_crs = mat;
365: }
366: MatDestroy(&Cmat);
368: #if defined PETSC_GAMG_USE_LOG
369: PetscLogEventEnd(petsc_gamg_setup_events[SET14],0,0,0,0);
370: #endif
371: /* prolongator */
372: {
373: IS findices;
374: PetscInt Istart,Iend;
375: Mat Pnew;
377: MatGetOwnershipRange(Pold, &Istart, &Iend);
378: #if defined PETSC_GAMG_USE_LOG
379: PetscLogEventBegin(petsc_gamg_setup_events[SET15],0,0,0,0);
380: #endif
381: ISCreateStride(comm,Iend-Istart,Istart,1,&findices);
382: ISSetBlockSize(findices,f_bs);
383: MatCreateSubMatrix(Pold, findices, new_eq_indices, MAT_INITIAL_MATRIX, &Pnew);
384: ISDestroy(&findices);
386: #if defined PETSC_GAMG_USE_LOG
387: PetscLogEventEnd(petsc_gamg_setup_events[SET15],0,0,0,0);
388: #endif
389: MatDestroy(a_P_inout);
391: /* output - repartitioned */
392: *a_P_inout = Pnew;
393: }
394: ISDestroy(&new_eq_indices);
396: *a_nactive_proc = new_size; /* output */
397: }
398: return(0);
399: }
401: /* -------------------------------------------------------------------------- */
402: /*
403: PCSetUp_GAMG - Prepares for the use of the GAMG preconditioner
404: by setting data structures and options.
406: Input Parameter:
407: . pc - the preconditioner context
409: */
410: PetscErrorCode PCSetUp_GAMG(PC pc)
411: {
413: PC_MG *mg = (PC_MG*)pc->data;
414: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
415: Mat Pmat = pc->pmat;
416: PetscInt fine_level,level,level1,bs,M,N,qq,lidx,nASMBlocksArr[PETSC_GAMG_MAXLEVELS];
417: MPI_Comm comm;
418: PetscMPIInt rank,size,nactivepe;
419: Mat Aarr[PETSC_GAMG_MAXLEVELS],Parr[PETSC_GAMG_MAXLEVELS];
420: IS *ASMLocalIDsArr[PETSC_GAMG_MAXLEVELS];
421: PetscLogDouble nnz0=0.,nnztot=0.;
422: MatInfo info;
423: PetscBool is_last = PETSC_FALSE;
426: PetscObjectGetComm((PetscObject)pc,&comm);
427: MPI_Comm_rank(comm,&rank);
428: MPI_Comm_size(comm,&size);
430: if (pc_gamg->setup_count++ > 0) {
431: if ((PetscBool)(!pc_gamg->reuse_prol)) {
432: /* reset everything */
433: PCReset_MG(pc);
434: pc->setupcalled = 0;
435: } else {
436: PC_MG_Levels **mglevels = mg->levels;
437: /* just do Galerkin grids */
438: Mat B,dA,dB;
440: if (!pc->setupcalled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"PCSetUp() has not been called yet");
441: if (pc_gamg->Nlevels > 1) {
442: /* currently only handle case where mat and pmat are the same on coarser levels */
443: KSPGetOperators(mglevels[pc_gamg->Nlevels-1]->smoothd,&dA,&dB);
444: /* (re)set to get dirty flag */
445: KSPSetOperators(mglevels[pc_gamg->Nlevels-1]->smoothd,dA,dB);
447: for (level=pc_gamg->Nlevels-2; level>=0; level--) {
448: /* the first time through the matrix structure has changed from repartitioning */
449: if (pc_gamg->setup_count==2) {
450: MatPtAP(dB,mglevels[level+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);
451: MatDestroy(&mglevels[level]->A);
453: mglevels[level]->A = B;
454: } else {
455: KSPGetOperators(mglevels[level]->smoothd,NULL,&B);
456: MatPtAP(dB,mglevels[level+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);
457: }
458: KSPSetOperators(mglevels[level]->smoothd,B,B);
459: dB = B;
460: }
461: }
463: PCSetUp_MG(pc);
464: return(0);
465: }
466: }
468: if (!pc_gamg->data) {
469: if (pc_gamg->orig_data) {
470: MatGetBlockSize(Pmat, &bs);
471: MatGetLocalSize(Pmat, &qq, NULL);
473: pc_gamg->data_sz = (qq/bs)*pc_gamg->orig_data_cell_rows*pc_gamg->orig_data_cell_cols;
474: pc_gamg->data_cell_rows = pc_gamg->orig_data_cell_rows;
475: pc_gamg->data_cell_cols = pc_gamg->orig_data_cell_cols;
477: PetscMalloc1(pc_gamg->data_sz, &pc_gamg->data);
478: for (qq=0; qq<pc_gamg->data_sz; qq++) pc_gamg->data[qq] = pc_gamg->orig_data[qq];
479: } else {
480: if (!pc_gamg->ops->createdefaultdata) SETERRQ(comm,PETSC_ERR_PLIB,"'createdefaultdata' not set(?) need to support NULL data");
481: pc_gamg->ops->createdefaultdata(pc,Pmat);
482: }
483: }
485: /* cache original data for reuse */
486: if (!pc_gamg->orig_data && (PetscBool)(!pc_gamg->reuse_prol)) {
487: PetscMalloc1(pc_gamg->data_sz, &pc_gamg->orig_data);
488: for (qq=0; qq<pc_gamg->data_sz; qq++) pc_gamg->orig_data[qq] = pc_gamg->data[qq];
489: pc_gamg->orig_data_cell_rows = pc_gamg->data_cell_rows;
490: pc_gamg->orig_data_cell_cols = pc_gamg->data_cell_cols;
491: }
493: /* get basic dims */
494: MatGetBlockSize(Pmat, &bs);
495: MatGetSize(Pmat, &M, &N);
497: MatGetInfo(Pmat,MAT_GLOBAL_SUM,&info); /* global reduction */
498: nnz0 = info.nz_used;
499: nnztot = info.nz_used;
500: 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);
502: /* Get A_i and R_i */
503: for (level=0, Aarr[0]=Pmat, nactivepe = size; level < (pc_gamg->Nlevels-1) && (!level || M>pc_gamg->coarse_eq_limit); level++) {
504: pc_gamg->current_level = level;
505: level1 = level + 1;
506: #if defined PETSC_GAMG_USE_LOG
507: PetscLogEventBegin(petsc_gamg_setup_events[SET1],0,0,0,0);
508: #if (defined GAMG_STAGES)
509: PetscLogStagePush(gamg_stages[level]);
510: #endif
511: #endif
512: { /* construct prolongator */
513: Mat Gmat;
514: PetscCoarsenData *agg_lists;
515: Mat Prol11;
517: pc_gamg->ops->graph(pc,Aarr[level], &Gmat);
518: pc_gamg->ops->coarsen(pc, &Gmat, &agg_lists);
519: pc_gamg->ops->prolongator(pc,Aarr[level],Gmat,agg_lists,&Prol11);
521: /* could have failed to create new level */
522: if (Prol11) {
523: /* get new block size of coarse matrices */
524: MatGetBlockSizes(Prol11, NULL, &bs);
526: if (pc_gamg->ops->optprolongator) {
527: /* smooth */
528: pc_gamg->ops->optprolongator(pc, Aarr[level], &Prol11);
529: }
531: Parr[level1] = Prol11;
532: } else Parr[level1] = NULL; /* failed to coarsen */
534: if (pc_gamg->use_aggs_in_asm) {
535: PetscInt bs;
536: MatGetBlockSizes(Prol11, &bs, NULL);
537: PetscCDGetASMBlocks(agg_lists, bs, Gmat, &nASMBlocksArr[level], &ASMLocalIDsArr[level]);
538: }
540: MatDestroy(&Gmat);
541: PetscCDDestroy(agg_lists);
542: } /* construct prolongator scope */
543: #if defined PETSC_GAMG_USE_LOG
544: PetscLogEventEnd(petsc_gamg_setup_events[SET1],0,0,0,0);
545: #endif
546: if (!level) Aarr[0] = Pmat; /* use Pmat for finest level setup */
547: if (!Parr[level1]) { /* failed to coarsen */
548: PetscInfo1(pc,"Stop gridding, level %D\n",level);
549: #if defined PETSC_GAMG_USE_LOG && defined GAMG_STAGES
550: PetscLogStagePop();
551: #endif
552: break;
553: }
554: #if defined PETSC_GAMG_USE_LOG
555: PetscLogEventBegin(petsc_gamg_setup_events[SET2],0,0,0,0);
556: #endif
557: MatGetSize(Parr[level1], &M, &N); /* N is next M, a loop test variables */
558: if (is_last) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Is last ????????");
559: if (N <= pc_gamg->coarse_eq_limit) is_last = PETSC_TRUE;
560: if (level1 == pc_gamg->Nlevels-1) is_last = PETSC_TRUE;
561: pc_gamg->ops->createlevel(pc, Aarr[level], bs, &Parr[level1], &Aarr[level1], &nactivepe, NULL, is_last);
563: #if defined PETSC_GAMG_USE_LOG
564: PetscLogEventEnd(petsc_gamg_setup_events[SET2],0,0,0,0);
565: #endif
566: MatGetSize(Aarr[level1], &M, &N); /* M is loop test variables */
567: MatGetInfo(Aarr[level1], MAT_GLOBAL_SUM, &info);
568: nnztot += info.nz_used;
569: 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);
571: #if (defined PETSC_GAMG_USE_LOG && defined GAMG_STAGES)
572: PetscLogStagePop();
573: #endif
574: /* stop if one node or one proc -- could pull back for singular problems */
575: if ( (pc_gamg->data_cell_cols && M/pc_gamg->data_cell_cols < 2) || (!pc_gamg->data_cell_cols && M/bs < 2) ) {
576: PetscInfo2(pc,"HARD stop of coarsening on level %D. Grid too small: %D block nodes\n",level,M/bs);
577: level++;
578: break;
579: }
580: } /* levels */
581: PetscFree(pc_gamg->data);
583: PetscInfo2(pc,"%D levels, grid complexity = %g\n",level+1,nnztot/nnz0);
584: pc_gamg->Nlevels = level + 1;
585: fine_level = level;
586: PCMGSetLevels(pc,pc_gamg->Nlevels,NULL);
588: if (pc_gamg->Nlevels > 1) { /* don't setup MG if one level */
589: /* set default smoothers & set operators */
590: for (lidx = 1, level = pc_gamg->Nlevels-2; lidx <= fine_level; lidx++, level--) {
591: KSP smoother;
592: PC subpc;
594: PCMGGetSmoother(pc, lidx, &smoother);
595: KSPGetPC(smoother, &subpc);
597: KSPSetNormType(smoother, KSP_NORM_NONE);
598: /* set ops */
599: KSPSetOperators(smoother, Aarr[level], Aarr[level]);
600: PCMGSetInterpolation(pc, lidx, Parr[level+1]);
602: /* set defaults */
603: KSPSetType(smoother, KSPCHEBYSHEV);
605: /* set blocks for ASM smoother that uses the 'aggregates' */
606: if (pc_gamg->use_aggs_in_asm) {
607: PetscInt sz;
608: IS *iss;
610: sz = nASMBlocksArr[level];
611: iss = ASMLocalIDsArr[level];
612: PCSetType(subpc, PCASM);
613: PCASMSetOverlap(subpc, 0);
614: PCASMSetType(subpc,PC_ASM_BASIC);
615: if (!sz) {
616: IS is;
617: ISCreateGeneral(PETSC_COMM_SELF, 0, NULL, PETSC_COPY_VALUES, &is);
618: PCASMSetLocalSubdomains(subpc, 1, NULL, &is);
619: ISDestroy(&is);
620: } else {
621: PetscInt kk;
622: PCASMSetLocalSubdomains(subpc, sz, NULL, iss);
623: for (kk=0; kk<sz; kk++) {
624: ISDestroy(&iss[kk]);
625: }
626: PetscFree(iss);
627: }
628: ASMLocalIDsArr[level] = NULL;
629: nASMBlocksArr[level] = 0;
630: } else {
631: PCSetType(subpc, PCSOR);
632: }
633: }
634: {
635: /* coarse grid */
636: KSP smoother,*k2; PC subpc,pc2; PetscInt ii,first;
637: Mat Lmat = Aarr[(level=pc_gamg->Nlevels-1)]; lidx = 0;
638: PCMGGetSmoother(pc, lidx, &smoother);
639: KSPSetOperators(smoother, Lmat, Lmat);
640: if (!pc_gamg->use_parallel_coarse_grid_solver) {
641: KSPSetNormType(smoother, KSP_NORM_NONE);
642: KSPGetPC(smoother, &subpc);
643: PCSetType(subpc, PCBJACOBI);
644: PCSetUp(subpc);
645: PCBJacobiGetSubKSP(subpc,&ii,&first,&k2);
646: if (ii != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_PLIB,"ii %D is not one",ii);
647: KSPGetPC(k2[0],&pc2);
648: PCSetType(pc2, PCLU);
649: PCFactorSetShiftType(pc2,MAT_SHIFT_INBLOCKS);
650: KSPSetTolerances(k2[0],PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,1);
651: KSPSetType(k2[0], KSPPREONLY);
652: /* This flag gets reset by PCBJacobiGetSubKSP(), but our BJacobi really does the same algorithm everywhere (and in
653: * fact, all but one process will have zero dofs), so we reset the flag to avoid having PCView_BJacobi attempt to
654: * view every subdomain as though they were different. */
655: ((PC_BJacobi*)subpc->data)->same_local_solves = PETSC_TRUE;
656: }
657: }
659: /* should be called in PCSetFromOptions_GAMG(), but cannot be called prior to PCMGSetLevels() */
660: PetscObjectOptionsBegin((PetscObject)pc);
661: PCSetFromOptions_MG(PetscOptionsObject,pc);
662: PetscOptionsEnd();
663: PCMGSetGalerkin(pc,PC_MG_GALERKIN_EXTERNAL);
665: /* clean up */
666: for (level=1; level<pc_gamg->Nlevels; level++) {
667: MatDestroy(&Parr[level]);
668: MatDestroy(&Aarr[level]);
669: }
670: PCSetUp_MG(pc);
671: } else {
672: KSP smoother;
673: PetscInfo(pc,"One level solver used (system is seen as DD). Using default solver.\n");
674: PCMGGetSmoother(pc, 0, &smoother);
675: KSPSetOperators(smoother, Aarr[0], Aarr[0]);
676: KSPSetType(smoother, KSPPREONLY);
677: PCSetUp_MG(pc);
678: }
679: return(0);
680: }
682: /* ------------------------------------------------------------------------- */
683: /*
684: PCDestroy_GAMG - Destroys the private context for the GAMG preconditioner
685: that was created with PCCreate_GAMG().
687: Input Parameter:
688: . pc - the preconditioner context
690: Application Interface Routine: PCDestroy()
691: */
692: PetscErrorCode PCDestroy_GAMG(PC pc)
693: {
695: PC_MG *mg = (PC_MG*)pc->data;
696: PC_GAMG *pc_gamg= (PC_GAMG*)mg->innerctx;
699: PCReset_GAMG(pc);
700: if (pc_gamg->ops->destroy) {
701: (*pc_gamg->ops->destroy)(pc);
702: }
703: PetscFree(pc_gamg->ops);
704: PetscFree(pc_gamg->gamg_type_name);
705: PetscFree(pc_gamg);
706: PCDestroy_MG(pc);
707: return(0);
708: }
710: /*@
711: PCGAMGSetProcEqLim - Set number of equations to aim for per process on the coarse grids via processor reduction.
713: Logically Collective on PC
715: Input Parameters:
716: + pc - the preconditioner context
717: - n - the number of equations
720: Options Database Key:
721: . -pc_gamg_process_eq_limit <limit>
723: Notes: GAMG will reduce the number of MPI processes used directly on the coarse grids so that there are around <limit> equations on each process
724: that has degrees of freedom
726: Level: intermediate
728: Concepts: Unstructured multigrid preconditioner
730: .seealso: PCGAMGSetCoarseEqLim()
731: @*/
732: PetscErrorCode PCGAMGSetProcEqLim(PC pc, PetscInt n)
733: {
738: PetscTryMethod(pc,"PCGAMGSetProcEqLim_C",(PC,PetscInt),(pc,n));
739: return(0);
740: }
742: static PetscErrorCode PCGAMGSetProcEqLim_GAMG(PC pc, PetscInt n)
743: {
744: PC_MG *mg = (PC_MG*)pc->data;
745: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
748: if (n>0) pc_gamg->min_eq_proc = n;
749: return(0);
750: }
752: /*@
753: PCGAMGSetCoarseEqLim - Set maximum number of equations on coarsest grid.
755: Collective on PC
757: Input Parameters:
758: + pc - the preconditioner context
759: - n - maximum number of equations to aim for
761: Options Database Key:
762: . -pc_gamg_coarse_eq_limit <limit>
764: Level: intermediate
766: Concepts: Unstructured multigrid preconditioner
768: .seealso: PCGAMGSetProcEqLim()
769: @*/
770: PetscErrorCode PCGAMGSetCoarseEqLim(PC pc, PetscInt n)
771: {
776: PetscTryMethod(pc,"PCGAMGSetCoarseEqLim_C",(PC,PetscInt),(pc,n));
777: return(0);
778: }
780: static PetscErrorCode PCGAMGSetCoarseEqLim_GAMG(PC pc, PetscInt n)
781: {
782: PC_MG *mg = (PC_MG*)pc->data;
783: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
786: if (n>0) pc_gamg->coarse_eq_limit = n;
787: return(0);
788: }
790: /*@
791: PCGAMGSetRepartition - Repartition the degrees of freedom across the processors on the coarser grids
793: Collective on PC
795: Input Parameters:
796: + pc - the preconditioner context
797: - n - PETSC_TRUE or PETSC_FALSE
799: Options Database Key:
800: . -pc_gamg_repartition <true,false>
802: Notes: this will generally improve the loading balancing of the work on each level
804: Level: intermediate
806: Concepts: Unstructured multigrid preconditioner
808: .seealso: ()
809: @*/
810: PetscErrorCode PCGAMGSetRepartition(PC pc, PetscBool n)
811: {
816: PetscTryMethod(pc,"PCGAMGSetRepartition_C",(PC,PetscBool),(pc,n));
817: return(0);
818: }
820: static PetscErrorCode PCGAMGSetRepartition_GAMG(PC pc, PetscBool n)
821: {
822: PC_MG *mg = (PC_MG*)pc->data;
823: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
826: pc_gamg->repart = n;
827: return(0);
828: }
830: /*@
831: PCGAMGSetReuseInterpolation - Reuse prolongation when rebuilding algebraic multigrid preconditioner
833: Collective on PC
835: Input Parameters:
836: + pc - the preconditioner context
837: - n - PETSC_TRUE or PETSC_FALSE
839: Options Database Key:
840: . -pc_gamg_reuse_interpolation <true,false>
842: Level: intermediate
844: Notes: this may negatively affect the convergence rate of the method on new matrices if the matrix entries change a great deal, but allows
845: rebuilding the preconditioner quicker.
847: Concepts: Unstructured multigrid preconditioner
849: .seealso: ()
850: @*/
851: PetscErrorCode PCGAMGSetReuseInterpolation(PC pc, PetscBool n)
852: {
857: PetscTryMethod(pc,"PCGAMGSetReuseInterpolation_C",(PC,PetscBool),(pc,n));
858: return(0);
859: }
861: static PetscErrorCode PCGAMGSetReuseInterpolation_GAMG(PC pc, PetscBool n)
862: {
863: PC_MG *mg = (PC_MG*)pc->data;
864: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
867: pc_gamg->reuse_prol = n;
868: return(0);
869: }
871: /*@
872: PCGAMGASMSetUseAggs - Have the PCGAMG smoother on each level use the aggregates defined by the coarsening process as the subdomains for the additive Schwarz preconditioner.
874: Collective on PC
876: Input Parameters:
877: + pc - the preconditioner context
878: - flg - PETSC_TRUE to use aggregates, PETSC_FALSE to not
880: Options Database Key:
881: . -pc_gamg_asm_use_agg
883: Level: intermediate
885: Concepts: Unstructured multigrid preconditioner
887: .seealso: ()
888: @*/
889: PetscErrorCode PCGAMGASMSetUseAggs(PC pc, PetscBool flg)
890: {
895: PetscTryMethod(pc,"PCGAMGASMSetUseAggs_C",(PC,PetscBool),(pc,flg));
896: return(0);
897: }
899: static PetscErrorCode PCGAMGASMSetUseAggs_GAMG(PC pc, PetscBool flg)
900: {
901: PC_MG *mg = (PC_MG*)pc->data;
902: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
905: pc_gamg->use_aggs_in_asm = flg;
906: return(0);
907: }
909: /*@
910: PCGAMGSetUseParallelCoarseGridSolve - allow a parallel coarse grid solver
912: Collective on PC
914: Input Parameters:
915: + pc - the preconditioner context
916: - flg - PETSC_TRUE to not force coarse grid onto one processor
918: Options Database Key:
919: . -pc_gamg_use_parallel_coarse_grid_solver
921: Level: intermediate
923: Concepts: Unstructured multigrid preconditioner
925: .seealso: ()
926: @*/
927: PetscErrorCode PCGAMGSetUseParallelCoarseGridSolve(PC pc, PetscBool flg)
928: {
933: PetscTryMethod(pc,"PCGAMGSetUseParallelCoarseGridSolve_C",(PC,PetscBool),(pc,flg));
934: return(0);
935: }
937: static PetscErrorCode PCGAMGSetUseParallelCoarseGridSolve_GAMG(PC pc, PetscBool flg)
938: {
939: PC_MG *mg = (PC_MG*)pc->data;
940: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
943: pc_gamg->use_parallel_coarse_grid_solver = flg;
944: return(0);
945: }
947: /*@
948: PCGAMGSetNlevels - Sets the maximum number of levels PCGAMG will use
950: Not collective on PC
952: Input Parameters:
953: + pc - the preconditioner
954: - n - the maximum number of levels to use
956: Options Database Key:
957: . -pc_mg_levels
959: Level: intermediate
961: Concepts: Unstructured multigrid preconditioner
963: .seealso: ()
964: @*/
965: PetscErrorCode PCGAMGSetNlevels(PC pc, PetscInt n)
966: {
971: PetscTryMethod(pc,"PCGAMGSetNlevels_C",(PC,PetscInt),(pc,n));
972: return(0);
973: }
975: static PetscErrorCode PCGAMGSetNlevels_GAMG(PC pc, PetscInt n)
976: {
977: PC_MG *mg = (PC_MG*)pc->data;
978: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
981: pc_gamg->Nlevels = n;
982: return(0);
983: }
985: /*@
986: PCGAMGSetThreshold - Relative threshold to use for dropping edges in aggregation graph
988: Not collective on PC
990: Input Parameters:
991: + pc - the preconditioner context
992: - threshold - the threshold value, 0.0 means keep all nonzero entries in the graph; negative means keep even zero entries in the graph
994: Options Database Key:
995: . -pc_gamg_threshold <threshold>
997: Notes: Before aggregating the graph GAMG will remove small values from the graph thus reducing the coupling in the graph and a different
998: (perhaps better) coarser set of points.
1000: Level: intermediate
1002: Concepts: Unstructured multigrid preconditioner
1004: .seealso: PCGAMGFilterGraph()
1005: @*/
1006: PetscErrorCode PCGAMGSetThreshold(PC pc, PetscReal v[], PetscInt n)
1007: {
1012: PetscTryMethod(pc,"PCGAMGSetThreshold_C",(PC,PetscReal[],PetscInt),(pc,v,n));
1013: return(0);
1014: }
1016: static PetscErrorCode PCGAMGSetThreshold_GAMG(PC pc, PetscReal v[], PetscInt n)
1017: {
1018: PC_MG *mg = (PC_MG*)pc->data;
1019: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
1020: PetscInt i;
1022: for (i=0;i<n;i++) pc_gamg->threshold[i] = v[i];
1023: do {pc_gamg->threshold[i] = pc_gamg->threshold[i-1]*pc_gamg->threshold_scale;} while (++i<PETSC_GAMG_MAXLEVELS);
1024: return(0);
1025: }
1027: /*@
1028: PCGAMGSetThresholdScale - Relative threshold reduction at each level
1030: Not collective on PC
1032: Input Parameters:
1033: + pc - the preconditioner context
1034: - scale - the threshold value reduction, ussually < 1.0
1036: Options Database Key:
1037: . -pc_gamg_threshold_scale <v>
1039: Level: advanced
1041: Concepts: Unstructured multigrid preconditioner
1043: .seealso: ()
1044: @*/
1045: PetscErrorCode PCGAMGSetThresholdScale(PC pc, PetscReal v)
1046: {
1051: PetscTryMethod(pc,"PCGAMGSetThresholdScale_C",(PC,PetscReal),(pc,v));
1052: return(0);
1053: }
1055: static PetscErrorCode PCGAMGSetThresholdScale_GAMG(PC pc, PetscReal v)
1056: {
1057: PC_MG *mg = (PC_MG*)pc->data;
1058: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
1060: pc_gamg->threshold_scale = v;
1061: return(0);
1062: }
1064: /*@C
1065: PCGAMGSetType - Set solution method
1067: Collective on PC
1069: Input Parameters:
1070: + pc - the preconditioner context
1071: - type - PCGAMGAGG, PCGAMGGEO, or PCGAMGCLASSICAL
1073: Options Database Key:
1074: . -pc_gamg_type <agg,geo,classical> - type of algebraic multigrid to apply
1076: Level: intermediate
1078: Concepts: Unstructured multigrid preconditioner
1080: .seealso: PCGAMGGetType(), PCGAMG, PCGAMGType
1081: @*/
1082: PetscErrorCode PCGAMGSetType(PC pc, PCGAMGType type)
1083: {
1088: PetscTryMethod(pc,"PCGAMGSetType_C",(PC,PCGAMGType),(pc,type));
1089: return(0);
1090: }
1092: /*@C
1093: PCGAMGGetType - Get solution method
1095: Collective on PC
1097: Input Parameter:
1098: . pc - the preconditioner context
1100: Output Parameter:
1101: . type - the type of algorithm used
1103: Level: intermediate
1105: Concepts: Unstructured multigrid preconditioner
1107: .seealso: PCGAMGSetType(), PCGAMGType
1108: @*/
1109: PetscErrorCode PCGAMGGetType(PC pc, PCGAMGType *type)
1110: {
1115: PetscUseMethod(pc,"PCGAMGGetType_C",(PC,PCGAMGType*),(pc,type));
1116: return(0);
1117: }
1119: static PetscErrorCode PCGAMGGetType_GAMG(PC pc, PCGAMGType *type)
1120: {
1121: PC_MG *mg = (PC_MG*)pc->data;
1122: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
1125: *type = pc_gamg->type;
1126: return(0);
1127: }
1129: static PetscErrorCode PCGAMGSetType_GAMG(PC pc, PCGAMGType type)
1130: {
1131: PetscErrorCode ierr,(*r)(PC);
1132: PC_MG *mg = (PC_MG*)pc->data;
1133: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
1136: pc_gamg->type = type;
1137: PetscFunctionListFind(GAMGList,type,&r);
1138: if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown GAMG type %s given",type);
1139: if (pc_gamg->ops->destroy) {
1140: (*pc_gamg->ops->destroy)(pc);
1141: PetscMemzero(pc_gamg->ops,sizeof(struct _PCGAMGOps));
1142: pc_gamg->ops->createlevel = PCGAMGCreateLevel_GAMG;
1143: /* cleaning up common data in pc_gamg - this should disapear someday */
1144: pc_gamg->data_cell_cols = 0;
1145: pc_gamg->data_cell_rows = 0;
1146: pc_gamg->orig_data_cell_cols = 0;
1147: pc_gamg->orig_data_cell_rows = 0;
1148: PetscFree(pc_gamg->data);
1149: pc_gamg->data_sz = 0;
1150: }
1151: PetscFree(pc_gamg->gamg_type_name);
1152: PetscStrallocpy(type,&pc_gamg->gamg_type_name);
1153: (*r)(pc);
1154: return(0);
1155: }
1157: static PetscErrorCode PCView_GAMG(PC pc,PetscViewer viewer)
1158: {
1159: PetscErrorCode ierr,i;
1160: PC_MG *mg = (PC_MG*)pc->data;
1161: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
1164: PetscViewerASCIIPrintf(viewer," GAMG specific options\n");
1165: PetscViewerASCIIPrintf(viewer," Threshold for dropping small values in graph on each level =");
1166: for (i=0;i<pc_gamg->current_level;i++) {
1167: PetscViewerASCIIPrintf(viewer," %g",(double)pc_gamg->threshold[i]);
1168: }
1169: PetscViewerASCIIPrintf(viewer,"\n");
1170: PetscViewerASCIIPrintf(viewer," Threshold scaling factor for each level not specified = %g\n",(double)pc_gamg->threshold_scale);
1171: if (pc_gamg->use_aggs_in_asm) {
1172: PetscViewerASCIIPrintf(viewer," Using aggregates from coarsening process to define subdomains for PCASM\n");
1173: }
1174: if (pc_gamg->use_parallel_coarse_grid_solver) {
1175: PetscViewerASCIIPrintf(viewer," Using parallel coarse grid solver (all coarse grid equations not put on one process)\n");
1176: }
1177: if (pc_gamg->ops->view) {
1178: (*pc_gamg->ops->view)(pc,viewer);
1179: }
1180: return(0);
1181: }
1183: PetscErrorCode PCSetFromOptions_GAMG(PetscOptionItems *PetscOptionsObject,PC pc)
1184: {
1186: PC_MG *mg = (PC_MG*)pc->data;
1187: PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
1188: PetscBool flag;
1189: MPI_Comm comm;
1190: char prefix[256];
1191: PetscInt i,n;
1192: const char *pcpre;
1195: PetscObjectGetComm((PetscObject)pc,&comm);
1196: PetscOptionsHead(PetscOptionsObject,"GAMG options");
1197: {
1198: char tname[256];
1199: PetscOptionsFList("-pc_gamg_type","Type of AMG method","PCGAMGSetType",GAMGList, pc_gamg->gamg_type_name, tname, sizeof(tname), &flag);
1200: if (flag) {
1201: PCGAMGSetType(pc,tname);
1202: }
1203: PetscOptionsBool("-pc_gamg_repartition","Repartion coarse grids","PCGAMGSetRepartition",pc_gamg->repart,&pc_gamg->repart,NULL);
1204: PetscOptionsBool("-pc_gamg_reuse_interpolation","Reuse prolongation operator","PCGAMGReuseInterpolation",pc_gamg->reuse_prol,&pc_gamg->reuse_prol,NULL);
1205: 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);
1206: 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);
1207: 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);
1208: 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);
1209: PetscOptionsReal("-pc_gamg_threshold_scale","Scaling of threshold for each level not specified","PCGAMGSetThresholdScale",pc_gamg->threshold_scale,&pc_gamg->threshold_scale,NULL);
1210: n = PETSC_GAMG_MAXLEVELS;
1211: PetscOptionsRealArray("-pc_gamg_threshold","Relative threshold to use for dropping edges in aggregation graph","PCGAMGSetThreshold",pc_gamg->threshold,&n,&flag);
1212: if (!flag || n < PETSC_GAMG_MAXLEVELS) {
1213: if (!flag) n = 1;
1214: i = n;
1215: do {pc_gamg->threshold[i] = pc_gamg->threshold[i-1]*pc_gamg->threshold_scale;} while (++i<PETSC_GAMG_MAXLEVELS);
1216: }
1217: PetscOptionsInt("-pc_mg_levels","Set number of MG levels","PCGAMGSetNlevels",pc_gamg->Nlevels,&pc_gamg->Nlevels,NULL);
1219: /* set options for subtype */
1220: if (pc_gamg->ops->setfromoptions) {(*pc_gamg->ops->setfromoptions)(PetscOptionsObject,pc);}
1221: }
1222: PCGetOptionsPrefix(pc, &pcpre);
1223: PetscSNPrintf(prefix,sizeof(prefix),"%spc_gamg_",pcpre ? pcpre : "");
1224: PetscOptionsTail();
1225: return(0);
1226: }
1228: /* -------------------------------------------------------------------------- */
1229: /*MC
1230: PCGAMG - Geometric algebraic multigrid (AMG) preconditioner
1232: Options Database Keys:
1233: + -pc_gamg_type <type> - one of agg, geo, or classical
1234: . -pc_gamg_repartition <true,default=false> - repartition the degrees of freedom accross the coarse grids as they are determined
1235: . -pc_gamg_reuse_interpolation <true,default=false> - when rebuilding the algebraic multigrid preconditioner reuse the previously computed interpolations
1236: . -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
1237: . -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>
1238: equations on each process that has degrees of freedom
1239: . -pc_gamg_coarse_eq_limit <limit, default=50> - Set maximum number of equations on coarsest grid to aim for.
1240: . -pc_gamg_threshold[] <thresh,default=0> - Before aggregating the graph GAMG will remove small values from the graph on each level
1241: - -pc_gamg_threshold_scale <scale,default=1> - Scaling of threshold on each coarser grid if not specified
1243: Options Database Keys for default Aggregation:
1244: + -pc_gamg_agg_nsmooths <nsmooth, default=1> - number of smoothing steps to use with smooth aggregation
1245: . -pc_gamg_sym_graph <true,default=false> - symmetrize the graph before computing the aggregation
1246: - -pc_gamg_square_graph <n,default=1> - number of levels to square the graph before aggregating it
1248: Multigrid options:
1249: + -pc_mg_cycles <v> - v or w, see PCMGSetCycleType()
1250: . -pc_mg_distinct_smoothup - configure the up and down (pre and post) smoothers separately, see PCMGSetDistinctSmoothUp()
1251: . -pc_mg_type <multiplicative> - (one of) additive multiplicative full kascade
1252: - -pc_mg_levels <levels> - Number of levels of multigrid to use.
1255: Notes: In order to obtain good performance for PCGAMG for vector valued problems you must
1256: Call MatSetBlockSize() to indicate the number of degrees of freedom per grid point
1257: Call MatSetNearNullSpace() (or PCSetCoordinates() if solving the equations of elasticity) to indicate the near null space of the operator
1258: See the Users Manual Chapter 4 for more details
1260: Level: intermediate
1262: Concepts: algebraic multigrid
1264: .seealso: PCCreate(), PCSetType(), MatSetBlockSize(), PCMGType, PCSetCoordinates(), MatSetNearNullSpace(), PCGAMGSetType(), PCGAMGAGG, PCGAMGGEO, PCGAMGCLASSICAL, PCGAMGSetProcEqLim(),
1265: PCGAMGSetCoarseEqLim(), PCGAMGSetRepartition(), PCGAMGRegister(), PCGAMGSetReuseInterpolation(), PCGAMGASMSetUseAggs(), PCGAMGSetUseParallelCoarseGridSolve(), PCGAMGSetNlevels(), PCGAMGSetThreshold(), PCGAMGGetType(), PCGAMGSetReuseInterpolation()
1266: M*/
1268: PETSC_EXTERN PetscErrorCode PCCreate_GAMG(PC pc)
1269: {
1270: PetscErrorCode ierr,i;
1271: PC_GAMG *pc_gamg;
1272: PC_MG *mg;
1275: /* register AMG type */
1276: PCGAMGInitializePackage();
1278: /* PCGAMG is an inherited class of PCMG. Initialize pc as PCMG */
1279: PCSetType(pc, PCMG);
1280: PetscObjectChangeTypeName((PetscObject)pc, PCGAMG);
1282: /* create a supporting struct and attach it to pc */
1283: PetscNewLog(pc,&pc_gamg);
1284: PCMGSetGalerkin(pc,PC_MG_GALERKIN_EXTERNAL);
1285: mg = (PC_MG*)pc->data;
1286: mg->innerctx = pc_gamg;
1288: PetscNewLog(pc,&pc_gamg->ops);
1290: pc_gamg->setup_count = 0;
1291: /* these should be in subctx but repartitioning needs simple arrays */
1292: pc_gamg->data_sz = 0;
1293: pc_gamg->data = 0;
1295: /* overwrite the pointers of PCMG by the functions of base class PCGAMG */
1296: pc->ops->setfromoptions = PCSetFromOptions_GAMG;
1297: pc->ops->setup = PCSetUp_GAMG;
1298: pc->ops->reset = PCReset_GAMG;
1299: pc->ops->destroy = PCDestroy_GAMG;
1300: mg->view = PCView_GAMG;
1302: PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetProcEqLim_C",PCGAMGSetProcEqLim_GAMG);
1303: PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetCoarseEqLim_C",PCGAMGSetCoarseEqLim_GAMG);
1304: PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetRepartition_C",PCGAMGSetRepartition_GAMG);
1305: PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetReuseInterpolation_C",PCGAMGSetReuseInterpolation_GAMG);
1306: PetscObjectComposeFunction((PetscObject)pc,"PCGAMGASMSetUseAggs_C",PCGAMGASMSetUseAggs_GAMG);
1307: PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetUseParallelCoarseGridSolve_C",PCGAMGSetUseParallelCoarseGridSolve_GAMG);
1308: PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetThreshold_C",PCGAMGSetThreshold_GAMG);
1309: PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetThresholdScale_C",PCGAMGSetThresholdScale_GAMG);
1310: PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetType_C",PCGAMGSetType_GAMG);
1311: PetscObjectComposeFunction((PetscObject)pc,"PCGAMGGetType_C",PCGAMGGetType_GAMG);
1312: PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetNlevels_C",PCGAMGSetNlevels_GAMG);
1313: pc_gamg->repart = PETSC_FALSE;
1314: pc_gamg->reuse_prol = PETSC_FALSE;
1315: pc_gamg->use_aggs_in_asm = PETSC_FALSE;
1316: pc_gamg->use_parallel_coarse_grid_solver = PETSC_FALSE;
1317: pc_gamg->min_eq_proc = 50;
1318: pc_gamg->coarse_eq_limit = 50;
1319: for (i=0;i<PETSC_GAMG_MAXLEVELS;i++) pc_gamg->threshold[i] = 0.;
1320: pc_gamg->threshold_scale = 1.;
1321: pc_gamg->Nlevels = PETSC_GAMG_MAXLEVELS;
1322: pc_gamg->current_level = 0; /* don't need to init really */
1323: pc_gamg->ops->createlevel = PCGAMGCreateLevel_GAMG;
1325: /* PCSetUp_GAMG assumes that the type has been set, so set it to the default now */
1326: PCGAMGSetType(pc,PCGAMGAGG);
1327: return(0);
1328: }
1330: /*@C
1331: PCGAMGInitializePackage - This function initializes everything in the PCGAMG package. It is called
1332: from PetscDLLibraryRegister() when using dynamic libraries, and on the first call to PCCreate_GAMG()
1333: when using static libraries.
1335: Level: developer
1337: .keywords: PC, PCGAMG, initialize, package
1338: .seealso: PetscInitialize()
1339: @*/
1340: PetscErrorCode PCGAMGInitializePackage(void)
1341: {
1345: if (PCGAMGPackageInitialized) return(0);
1346: PCGAMGPackageInitialized = PETSC_TRUE;
1347: PetscFunctionListAdd(&GAMGList,PCGAMGGEO,PCCreateGAMG_GEO);
1348: PetscFunctionListAdd(&GAMGList,PCGAMGAGG,PCCreateGAMG_AGG);
1349: PetscFunctionListAdd(&GAMGList,PCGAMGCLASSICAL,PCCreateGAMG_Classical);
1350: PetscRegisterFinalize(PCGAMGFinalizePackage);
1352: /* general events */
1353: PetscLogEventRegister("PCGAMGGraph_AGG", 0, &PC_GAMGGraph_AGG);
1354: PetscLogEventRegister("PCGAMGGraph_GEO", PC_CLASSID, &PC_GAMGGraph_GEO);
1355: PetscLogEventRegister("PCGAMGCoarse_AGG", PC_CLASSID, &PC_GAMGCoarsen_AGG);
1356: PetscLogEventRegister("PCGAMGCoarse_GEO", PC_CLASSID, &PC_GAMGCoarsen_GEO);
1357: PetscLogEventRegister("PCGAMGProl_AGG", PC_CLASSID, &PC_GAMGProlongator_AGG);
1358: PetscLogEventRegister("PCGAMGProl_GEO", PC_CLASSID, &PC_GAMGProlongator_GEO);
1359: PetscLogEventRegister("PCGAMGPOpt_AGG", PC_CLASSID, &PC_GAMGOptProlongator_AGG);
1361: #if defined PETSC_GAMG_USE_LOG
1362: PetscLogEventRegister("GAMG: createProl", PC_CLASSID, &petsc_gamg_setup_events[SET1]);
1363: PetscLogEventRegister(" Graph", PC_CLASSID, &petsc_gamg_setup_events[GRAPH]);
1364: /* PetscLogEventRegister(" G.Mat", PC_CLASSID, &petsc_gamg_setup_events[GRAPH_MAT]); */
1365: /* PetscLogEventRegister(" G.Filter", PC_CLASSID, &petsc_gamg_setup_events[GRAPH_FILTER]); */
1366: /* PetscLogEventRegister(" G.Square", PC_CLASSID, &petsc_gamg_setup_events[GRAPH_SQR]); */
1367: PetscLogEventRegister(" MIS/Agg", PC_CLASSID, &petsc_gamg_setup_events[SET4]);
1368: PetscLogEventRegister(" geo: growSupp", PC_CLASSID, &petsc_gamg_setup_events[SET5]);
1369: PetscLogEventRegister(" geo: triangle", PC_CLASSID, &petsc_gamg_setup_events[SET6]);
1370: PetscLogEventRegister(" search-set", PC_CLASSID, &petsc_gamg_setup_events[FIND_V]);
1371: PetscLogEventRegister(" SA: col data", PC_CLASSID, &petsc_gamg_setup_events[SET7]);
1372: PetscLogEventRegister(" SA: frmProl0", PC_CLASSID, &petsc_gamg_setup_events[SET8]);
1373: PetscLogEventRegister(" SA: smooth", PC_CLASSID, &petsc_gamg_setup_events[SET9]);
1374: PetscLogEventRegister("GAMG: partLevel", PC_CLASSID, &petsc_gamg_setup_events[SET2]);
1375: PetscLogEventRegister(" repartition", PC_CLASSID, &petsc_gamg_setup_events[SET12]);
1376: PetscLogEventRegister(" Invert-Sort", PC_CLASSID, &petsc_gamg_setup_events[SET13]);
1377: PetscLogEventRegister(" Move A", PC_CLASSID, &petsc_gamg_setup_events[SET14]);
1378: PetscLogEventRegister(" Move P", PC_CLASSID, &petsc_gamg_setup_events[SET15]);
1380: /* PetscLogEventRegister(" PL move data", PC_CLASSID, &petsc_gamg_setup_events[SET13]); */
1381: /* PetscLogEventRegister("GAMG: fix", PC_CLASSID, &petsc_gamg_setup_events[SET10]); */
1382: /* PetscLogEventRegister("GAMG: set levels", PC_CLASSID, &petsc_gamg_setup_events[SET11]); */
1383: /* create timer stages */
1384: #if defined GAMG_STAGES
1385: {
1386: char str[32];
1387: PetscInt lidx;
1388: sprintf(str,"MG Level %d (finest)",0);
1389: PetscLogStageRegister(str, &gamg_stages[0]);
1390: for (lidx=1; lidx<9; lidx++) {
1391: sprintf(str,"MG Level %d",lidx);
1392: PetscLogStageRegister(str, &gamg_stages[lidx]);
1393: }
1394: }
1395: #endif
1396: #endif
1397: return(0);
1398: }
1400: /*@C
1401: PCGAMGFinalizePackage - This function frees everything from the PCGAMG package. It is
1402: called from PetscFinalize() automatically.
1404: Level: developer
1406: .keywords: Petsc, destroy, package
1407: .seealso: PetscFinalize()
1408: @*/
1409: PetscErrorCode PCGAMGFinalizePackage(void)
1410: {
1414: PCGAMGPackageInitialized = PETSC_FALSE;
1415: PetscFunctionListDestroy(&GAMGList);
1416: return(0);
1417: }
1419: /*@C
1420: PCGAMGRegister - Register a PCGAMG implementation.
1422: Input Parameters:
1423: + type - string that will be used as the name of the GAMG type.
1424: - create - function for creating the gamg context.
1426: Level: advanced
1428: .seealso: PCGAMGType, PCGAMG, PCGAMGSetType()
1429: @*/
1430: PetscErrorCode PCGAMGRegister(PCGAMGType type, PetscErrorCode (*create)(PC))
1431: {
1435: PCGAMGInitializePackage();
1436: PetscFunctionListAdd(&GAMGList,type,create);
1437: return(0);
1438: }