Actual source code: util.c

petsc-master 2020-01-22
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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>

  7: /*
  8:    Produces a set of block column indices of the matrix row, one for each block represented in the original row

 10:    n - the number of block indices in cc[]
 11:    cc - the block indices (must be large enough to contain the indices)
 12: */
 13: PETSC_STATIC_INLINE PetscErrorCode MatCollapseRow(Mat Amat,PetscInt row,PetscInt bs,PetscInt *n,PetscInt *cc)
 14: {
 15:   PetscInt       cnt = -1,nidx,j;
 16:   const PetscInt *idx;

 20:   MatGetRow(Amat,row,&nidx,&idx,NULL);
 21:   if (nidx) {
 22:     cnt = 0;
 23:     cc[cnt] = idx[0]/bs;
 24:     for (j=1; j<nidx; j++) {
 25:       if (cc[cnt] < idx[j]/bs) cc[++cnt] = idx[j]/bs;
 26:     }
 27:   }
 28:   MatRestoreRow(Amat,row,&nidx,&idx,NULL);
 29:   *n = cnt+1;
 30:   return(0);
 31: }

 33: /*
 34:     Produces a set of block column indices of the matrix block row, one for each block represented in the original set of rows

 36:     ncollapsed - the number of block indices
 37:     collapsed - the block indices (must be large enough to contain the indices)
 38: */
 39: PETSC_STATIC_INLINE PetscErrorCode MatCollapseRows(Mat Amat,PetscInt start,PetscInt bs,PetscInt *w0,PetscInt *w1,PetscInt *w2,PetscInt *ncollapsed,PetscInt **collapsed)
 40: {
 41:   PetscInt       i,nprev,*cprev = w0,ncur = 0,*ccur = w1,*merged = w2,*cprevtmp;

 45:   MatCollapseRow(Amat,start,bs,&nprev,cprev);
 46:   for (i=start+1; i<start+bs; i++) {
 47:     MatCollapseRow(Amat,i,bs,&ncur,ccur);
 48:     PetscMergeIntArray(nprev,cprev,ncur,ccur,&nprev,&merged);
 49:     cprevtmp = cprev; cprev = merged; merged = cprevtmp;
 50:   }
 51:   *ncollapsed = nprev;
 52:   if (collapsed) *collapsed  = cprev;
 53:   return(0);
 54: }


 57: /* -------------------------------------------------------------------------- */
 58: /*
 59:    PCGAMGCreateGraph - create simple scaled scalar graph from matrix

 61:  Input Parameter:
 62:  . Amat - matrix
 63:  Output Parameter:
 64:  . a_Gmaat - eoutput scalar graph (symmetric?)
 65:  */
 66: PetscErrorCode PCGAMGCreateGraph(Mat Amat, Mat *a_Gmat)
 67: {
 69:   PetscInt       Istart,Iend,Ii,jj,kk,ncols,nloc,NN,MM,bs;
 70:   MPI_Comm       comm;
 71:   Mat            Gmat;
 72:   MatType        mtype;

 75:   PetscObjectGetComm((PetscObject)Amat,&comm);
 76:   MatGetOwnershipRange(Amat, &Istart, &Iend);
 77:   MatGetSize(Amat, &MM, &NN);
 78:   MatGetBlockSize(Amat, &bs);
 79:   nloc = (Iend-Istart)/bs;

 81: #if defined PETSC_GAMG_USE_LOG
 82:   PetscLogEventBegin(petsc_gamg_setup_events[GRAPH],0,0,0,0);
 83: #endif

 85:   if (bs > 1) {
 86:     const PetscScalar *vals;
 87:     const PetscInt    *idx;
 88:     PetscInt          *d_nnz, *o_nnz,*w0,*w1,*w2;
 89:     PetscBool         ismpiaij,isseqaij;

 91:     /*
 92:        Determine the preallocation needed for the scalar matrix derived from the vector matrix.
 93:     */

 95:     PetscObjectBaseTypeCompare((PetscObject)Amat,MATSEQAIJ,&isseqaij);
 96:     PetscObjectBaseTypeCompare((PetscObject)Amat,MATMPIAIJ,&ismpiaij);
 97:     PetscMalloc2(nloc, &d_nnz,isseqaij ? 0 : nloc, &o_nnz);

 99:     if (isseqaij) {
100:       PetscInt       max_d_nnz;

102:       /*
103:           Determine exact preallocation count for (sequential) scalar matrix
104:       */
105:       MatSeqAIJGetMaxRowNonzeros(Amat,&max_d_nnz);
106:       max_d_nnz = PetscMin(nloc,bs*max_d_nnz);
107:       PetscMalloc3(max_d_nnz, &w0,max_d_nnz, &w1,max_d_nnz, &w2);
108:       for (Ii = 0, jj = 0; Ii < Iend; Ii += bs, jj++) {
109:         MatCollapseRows(Amat,Ii,bs,w0,w1,w2,&d_nnz[jj],NULL);
110:       }
111:       PetscFree3(w0,w1,w2);

113:     } else if (ismpiaij) {
114:       Mat            Daij,Oaij;
115:       const PetscInt *garray;
116:       PetscInt       max_d_nnz;

118:       MatMPIAIJGetSeqAIJ(Amat,&Daij,&Oaij,&garray);

120:       /*
121:           Determine exact preallocation count for diagonal block portion of scalar matrix
122:       */
123:       MatSeqAIJGetMaxRowNonzeros(Daij,&max_d_nnz);
124:       max_d_nnz = PetscMin(nloc,bs*max_d_nnz);
125:       PetscMalloc3(max_d_nnz, &w0,max_d_nnz, &w1,max_d_nnz, &w2);
126:       for (Ii = 0, jj = 0; Ii < Iend - Istart; Ii += bs, jj++) {
127:         MatCollapseRows(Daij,Ii,bs,w0,w1,w2,&d_nnz[jj],NULL);
128:       }
129:       PetscFree3(w0,w1,w2);

131:       /*
132:          Over estimate (usually grossly over), preallocation count for off-diagonal portion of scalar matrix
133:       */
134:       for (Ii = 0, jj = 0; Ii < Iend - Istart; Ii += bs, jj++) {
135:         o_nnz[jj] = 0;
136:         for (kk=0; kk<bs; kk++) { /* rows that get collapsed to a single row */
137:           MatGetRow(Oaij,Ii+kk,&ncols,0,0);
138:           o_nnz[jj] += ncols;
139:           MatRestoreRow(Oaij,Ii+kk,&ncols,0,0);
140:         }
141:         if (o_nnz[jj] > (NN/bs-nloc)) o_nnz[jj] = NN/bs-nloc;
142:       }

144:     } else SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_USER,"Require AIJ matrix type");

146:     /* get scalar copy (norms) of matrix */
147:     MatGetType(Amat,&mtype);
148:     MatCreate(comm, &Gmat);
149:     MatSetSizes(Gmat,nloc,nloc,PETSC_DETERMINE,PETSC_DETERMINE);
150:     MatSetBlockSizes(Gmat, 1, 1);
151:     MatSetType(Gmat, mtype);
152:     MatSeqAIJSetPreallocation(Gmat,0,d_nnz);
153:     MatMPIAIJSetPreallocation(Gmat,0,d_nnz,0,o_nnz);
154:     PetscFree2(d_nnz,o_nnz);

156:     for (Ii = Istart; Ii < Iend; Ii++) {
157:       PetscInt dest_row = Ii/bs;
158:       MatGetRow(Amat,Ii,&ncols,&idx,&vals);
159:       for (jj=0; jj<ncols; jj++) {
160:         PetscInt    dest_col = idx[jj]/bs;
161:         PetscScalar sv       = PetscAbs(PetscRealPart(vals[jj]));
162:         MatSetValues(Gmat,1,&dest_row,1,&dest_col,&sv,ADD_VALUES);
163:       }
164:       MatRestoreRow(Amat,Ii,&ncols,&idx,&vals);
165:     }
166:     MatAssemblyBegin(Gmat,MAT_FINAL_ASSEMBLY);
167:     MatAssemblyEnd(Gmat,MAT_FINAL_ASSEMBLY);
168:   } else {
169:     /* just copy scalar matrix - abs() not taken here but scaled later */
170:     MatDuplicate(Amat, MAT_COPY_VALUES, &Gmat);
171:   }

173: #if defined PETSC_GAMG_USE_LOG
174:   PetscLogEventEnd(petsc_gamg_setup_events[GRAPH],0,0,0,0);
175: #endif

177:   *a_Gmat = Gmat;
178:   return(0);
179: }

181: /* -------------------------------------------------------------------------- */
182: /*@C
183:    PCGAMGFilterGraph - filter (remove zero and possibly small values from the) graph and make it symmetric if requested

185:    Collective on Mat

187:    Input Parameter:
188: +   a_Gmat - the graph
189: .   vfilter - threshold paramter [0,1)
190: -   symm - make the result symmetric

192:    Level: developer

194:    Notes:
195:     This is called before graph coarsers are called.

197: .seealso: PCGAMGSetThreshold()
198: @*/
199: PetscErrorCode PCGAMGFilterGraph(Mat *a_Gmat,PetscReal vfilter,PetscBool symm)
200: {
201:   PetscErrorCode    ierr;
202:   PetscInt          Istart,Iend,Ii,jj,ncols,nnz0,nnz1, NN, MM, nloc;
203:   PetscMPIInt       rank;
204:   Mat               Gmat  = *a_Gmat, tGmat, matTrans;
205:   MPI_Comm          comm;
206:   const PetscScalar *vals;
207:   const PetscInt    *idx;
208:   PetscInt          *d_nnz, *o_nnz;
209:   Vec               diag;
210:   MatType           mtype;

213: #if defined PETSC_GAMG_USE_LOG
214:   PetscLogEventBegin(petsc_gamg_setup_events[GRAPH],0,0,0,0);
215: #endif
216:   /* scale Gmat for all values between -1 and 1 */
217:   MatCreateVecs(Gmat, &diag, 0);
218:   MatGetDiagonal(Gmat, diag);
219:   VecReciprocal(diag);
220:   VecSqrtAbs(diag);
221:   MatDiagonalScale(Gmat, diag, diag);
222:   VecDestroy(&diag);

224:   if (vfilter < 0.0 && !symm) {
225:     /* Just use the provided matrix as the graph but make all values positive */
226:     MatInfo     info;
227:     PetscScalar *avals;
228:     PetscBool isaij,ismpiaij;
229:     PetscObjectBaseTypeCompare((PetscObject)Gmat,MATSEQAIJ,&isaij);
230:     PetscObjectBaseTypeCompare((PetscObject)Gmat,MATMPIAIJ,&ismpiaij);
231:     if (!isaij && !ismpiaij) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_USER,"Require (MPI)AIJ matrix type");
232:     if (isaij) {
233:       MatGetInfo(Gmat,MAT_LOCAL,&info);
234:       MatSeqAIJGetArray(Gmat,&avals);
235:       for (jj = 0; jj<info.nz_used; jj++) avals[jj] = PetscAbsScalar(avals[jj]);
236:       MatSeqAIJRestoreArray(Gmat,&avals);
237:     } else {
238:       Mat_MPIAIJ  *aij = (Mat_MPIAIJ*)Gmat->data;
239:       MatGetInfo(aij->A,MAT_LOCAL,&info);
240:       MatSeqAIJGetArray(aij->A,&avals);
241:       for (jj = 0; jj<info.nz_used; jj++) avals[jj] = PetscAbsScalar(avals[jj]);
242:       MatSeqAIJRestoreArray(aij->A,&avals);
243:       MatGetInfo(aij->B,MAT_LOCAL,&info);
244:       MatSeqAIJGetArray(aij->B,&avals);
245:       for (jj = 0; jj<info.nz_used; jj++) avals[jj] = PetscAbsScalar(avals[jj]);
246:       MatSeqAIJRestoreArray(aij->B,&avals);
247:     }
248: #if defined PETSC_GAMG_USE_LOG
249:     PetscLogEventEnd(petsc_gamg_setup_events[GRAPH],0,0,0,0);
250: #endif
251:     return(0);
252:   }

254:   PetscObjectGetComm((PetscObject)Gmat,&comm);
255:   MPI_Comm_rank(comm,&rank);
256:   MatGetOwnershipRange(Gmat, &Istart, &Iend);
257:   nloc = Iend - Istart;
258:   MatGetSize(Gmat, &MM, &NN);

260:   if (symm) {
261:     MatTranspose(Gmat, MAT_INITIAL_MATRIX, &matTrans);
262:   }

264:   /* Determine upper bound on nonzeros needed in new filtered matrix */
265:   PetscMalloc2(nloc, &d_nnz,nloc, &o_nnz);
266:   for (Ii = Istart, jj = 0; Ii < Iend; Ii++, jj++) {
267:     MatGetRow(Gmat,Ii,&ncols,NULL,NULL);
268:     d_nnz[jj] = ncols;
269:     o_nnz[jj] = ncols;
270:     MatRestoreRow(Gmat,Ii,&ncols,NULL,NULL);
271:     if (symm) {
272:       MatGetRow(matTrans,Ii,&ncols,NULL,NULL);
273:       d_nnz[jj] += ncols;
274:       o_nnz[jj] += ncols;
275:       MatRestoreRow(matTrans,Ii,&ncols,NULL,NULL);
276:     }
277:     if (d_nnz[jj] > nloc) d_nnz[jj] = nloc;
278:     if (o_nnz[jj] > (MM-nloc)) o_nnz[jj] = MM - nloc;
279:   }
280:   MatGetType(Gmat,&mtype);
281:   MatCreate(comm, &tGmat);
282:   MatSetSizes(tGmat,nloc,nloc,MM,MM);
283:   MatSetBlockSizes(tGmat, 1, 1);
284:   MatSetType(tGmat, mtype);
285:   MatSeqAIJSetPreallocation(tGmat,0,d_nnz);
286:   MatMPIAIJSetPreallocation(tGmat,0,d_nnz,0,o_nnz);
287:   PetscFree2(d_nnz,o_nnz);
288:   if (symm) {
289:     MatDestroy(&matTrans);
290:   } else {
291:     /* all entries are generated locally so MatAssembly will be slightly faster for large process counts */
292:     MatSetOption(tGmat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
293:   }

295:   for (Ii = Istart, nnz0 = nnz1 = 0; Ii < Iend; Ii++) {
296:     MatGetRow(Gmat,Ii,&ncols,&idx,&vals);
297:     for (jj=0; jj<ncols; jj++,nnz0++) {
298:       PetscScalar sv = PetscAbs(PetscRealPart(vals[jj]));
299:       if (PetscRealPart(sv) > vfilter) {
300:         nnz1++;
301:         if (symm) {
302:           sv  *= 0.5;
303:           MatSetValues(tGmat,1,&Ii,1,&idx[jj],&sv,ADD_VALUES);
304:           MatSetValues(tGmat,1,&idx[jj],1,&Ii,&sv,ADD_VALUES);
305:         } else {
306:           MatSetValues(tGmat,1,&Ii,1,&idx[jj],&sv,ADD_VALUES);
307:         }
308:       }
309:     }
310:     MatRestoreRow(Gmat,Ii,&ncols,&idx,&vals);
311:   }
312:   MatAssemblyBegin(tGmat,MAT_FINAL_ASSEMBLY);
313:   MatAssemblyEnd(tGmat,MAT_FINAL_ASSEMBLY);

315: #if defined PETSC_GAMG_USE_LOG
316:   PetscLogEventEnd(petsc_gamg_setup_events[GRAPH],0,0,0,0);
317: #endif

319: #if defined(PETSC_USE_INFO)
320:   {
321:     double t1 = (!nnz0) ? 1. : 100.*(double)nnz1/(double)nnz0, t2 = (!nloc) ? 1. : (double)nnz0/(double)nloc;
322:     PetscInfo4(*a_Gmat,"\t %g%% nnz after filtering, with threshold %g, %g nnz ave. (N=%D)\n",t1,vfilter,t2,MM);
323:   }
324: #endif
325:   MatDestroy(&Gmat);
326:   *a_Gmat = tGmat;
327:   return(0);
328: }

330: /* -------------------------------------------------------------------------- */
331: /*
332:    PCGAMGGetDataWithGhosts - hacks into Mat MPIAIJ so this must have size > 1

334:    Input Parameter:
335:    . Gmat - MPIAIJ matrix for scattters
336:    . data_sz - number of data terms per node (# cols in output)
337:    . data_in[nloc*data_sz] - column oriented data
338:    Output Parameter:
339:    . a_stride - numbrt of rows of output
340:    . a_data_out[stride*data_sz] - output data with ghosts
341: */
342: PetscErrorCode PCGAMGGetDataWithGhosts(Mat Gmat,PetscInt data_sz,PetscReal data_in[],PetscInt *a_stride,PetscReal **a_data_out)
343: {
345:   Vec            tmp_crds;
346:   Mat_MPIAIJ     *mpimat = (Mat_MPIAIJ*)Gmat->data;
347:   PetscInt       nnodes,num_ghosts,dir,kk,jj,my0,Iend,nloc;
348:   PetscScalar    *data_arr;
349:   PetscReal      *datas;
350:   PetscBool      isMPIAIJ;

353:   PetscObjectBaseTypeCompare((PetscObject)Gmat, MATMPIAIJ, &isMPIAIJ);
354:   MatGetOwnershipRange(Gmat, &my0, &Iend);
355:   nloc      = Iend - my0;
356:   VecGetLocalSize(mpimat->lvec, &num_ghosts);
357:   nnodes    = num_ghosts + nloc;
358:   *a_stride = nnodes;
359:   MatCreateVecs(Gmat, &tmp_crds, 0);

361:   PetscMalloc1(data_sz*nnodes, &datas);
362:   for (dir=0; dir<data_sz; dir++) {
363:     /* set local, and global */
364:     for (kk=0; kk<nloc; kk++) {
365:       PetscInt    gid = my0 + kk;
366:       PetscScalar crd = (PetscScalar)data_in[dir*nloc + kk]; /* col oriented */
367:       datas[dir*nnodes + kk] = PetscRealPart(crd);

369:       VecSetValues(tmp_crds, 1, &gid, &crd, INSERT_VALUES);
370:     }
371:     VecAssemblyBegin(tmp_crds);
372:     VecAssemblyEnd(tmp_crds);
373:     /* get ghost datas */
374:     VecScatterBegin(mpimat->Mvctx,tmp_crds,mpimat->lvec,INSERT_VALUES,SCATTER_FORWARD);
375:     VecScatterEnd(mpimat->Mvctx,tmp_crds,mpimat->lvec,INSERT_VALUES,SCATTER_FORWARD);
376:     VecGetArray(mpimat->lvec, &data_arr);
377:     for (kk=nloc,jj=0;jj<num_ghosts;kk++,jj++) datas[dir*nnodes + kk] = PetscRealPart(data_arr[jj]);
378:     VecRestoreArray(mpimat->lvec, &data_arr);
379:   }
380:   VecDestroy(&tmp_crds);
381:   *a_data_out = datas;
382:   return(0);
383: }

385: PetscErrorCode PCGAMGHashTableCreate(PetscInt a_size, PCGAMGHashTable *a_tab)
386: {
388:   PetscInt       kk;

391:   a_tab->size = a_size;
392:   PetscMalloc2(a_size, &a_tab->table,a_size, &a_tab->data);
393:   for (kk=0; kk<a_size; kk++) a_tab->table[kk] = -1;
394:   return(0);
395: }

397: PetscErrorCode PCGAMGHashTableDestroy(PCGAMGHashTable *a_tab)
398: {

402:   PetscFree2(a_tab->table,a_tab->data);
403:   return(0);
404: }

406: PetscErrorCode PCGAMGHashTableAdd(PCGAMGHashTable *a_tab, PetscInt a_key, PetscInt a_data)
407: {
408:   PetscInt kk,idx;

411:   if (a_key<0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_USER,"Negative key %D.",a_key);
412:   for (kk = 0, idx = GAMG_HASH(a_key); kk < a_tab->size; kk++, idx = (idx==(a_tab->size-1)) ? 0 : idx + 1) {
413:     if (a_tab->table[idx] == a_key) {
414:       /* exists */
415:       a_tab->data[idx] = a_data;
416:       break;
417:     } else if (a_tab->table[idx] == -1) {
418:       /* add */
419:       a_tab->table[idx] = a_key;
420:       a_tab->data[idx]  = a_data;
421:       break;
422:     }
423:   }
424:   if (kk==a_tab->size) {
425:     /* this is not to efficient, waiting until completely full */
426:     PetscInt       oldsize = a_tab->size, new_size = 2*a_tab->size + 5, *oldtable = a_tab->table, *olddata = a_tab->data;

429:     a_tab->size = new_size;
430:     PetscMalloc2(a_tab->size, &a_tab->table,a_tab->size, &a_tab->data);
431:     for (kk=0;kk<a_tab->size;kk++) a_tab->table[kk] = -1;
432:     for (kk=0;kk<oldsize;kk++) {
433:       if (oldtable[kk] != -1) {
434:         PCGAMGHashTableAdd(a_tab, oldtable[kk], olddata[kk]);
435:        }
436:     }
437:     PetscFree2(oldtable,olddata);
438:     PCGAMGHashTableAdd(a_tab, a_key, a_data);
439:   }
440:   return(0);
441: }