Actual source code: mpiaij.c

petsc-3.11.3 2019-06-26
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  3:  #include <../src/mat/impls/aij/mpi/mpiaij.h>
  4:  #include <petsc/private/vecimpl.h>
  5:  #include <petsc/private/vecscatterimpl.h>
  6:  #include <petsc/private/isimpl.h>
  7:  #include <petscblaslapack.h>
  8:  #include <petscsf.h>

 10: /*MC
 11:    MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices.

 13:    This matrix type is identical to MATSEQAIJ when constructed with a single process communicator,
 14:    and MATMPIAIJ otherwise.  As a result, for single process communicators,
 15:   MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation() is supported
 16:   for communicators controlling multiple processes.  It is recommended that you call both of
 17:   the above preallocation routines for simplicity.

 19:    Options Database Keys:
 20: . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions()

 22:   Developer Notes:
 23:     Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJSELL, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when
 24:    enough exist.

 26:   Level: beginner

 28: .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ, MATMPIAIJ
 29: M*/

 31: /*MC
 32:    MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices.

 34:    This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator,
 35:    and MATMPIAIJCRL otherwise.  As a result, for single process communicators,
 36:    MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported
 37:   for communicators controlling multiple processes.  It is recommended that you call both of
 38:   the above preallocation routines for simplicity.

 40:    Options Database Keys:
 41: . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions()

 43:   Level: beginner

 45: .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL
 46: M*/

 48: PetscErrorCode MatSetBlockSizes_MPIAIJ(Mat M, PetscInt rbs, PetscInt cbs)
 49: {
 51:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)M->data;

 54:   if (mat->A) {
 55:     MatSetBlockSizes(mat->A,rbs,cbs);
 56:     MatSetBlockSizes(mat->B,rbs,1);
 57:   }
 58:   return(0);
 59: }

 61: PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows)
 62: {
 63:   PetscErrorCode  ierr;
 64:   Mat_MPIAIJ      *mat = (Mat_MPIAIJ*)M->data;
 65:   Mat_SeqAIJ      *a   = (Mat_SeqAIJ*)mat->A->data;
 66:   Mat_SeqAIJ      *b   = (Mat_SeqAIJ*)mat->B->data;
 67:   const PetscInt  *ia,*ib;
 68:   const MatScalar *aa,*bb;
 69:   PetscInt        na,nb,i,j,*rows,cnt=0,n0rows;
 70:   PetscInt        m = M->rmap->n,rstart = M->rmap->rstart;

 73:   *keptrows = 0;
 74:   ia        = a->i;
 75:   ib        = b->i;
 76:   for (i=0; i<m; i++) {
 77:     na = ia[i+1] - ia[i];
 78:     nb = ib[i+1] - ib[i];
 79:     if (!na && !nb) {
 80:       cnt++;
 81:       goto ok1;
 82:     }
 83:     aa = a->a + ia[i];
 84:     for (j=0; j<na; j++) {
 85:       if (aa[j] != 0.0) goto ok1;
 86:     }
 87:     bb = b->a + ib[i];
 88:     for (j=0; j <nb; j++) {
 89:       if (bb[j] != 0.0) goto ok1;
 90:     }
 91:     cnt++;
 92: ok1:;
 93:   }
 94:   MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));
 95:   if (!n0rows) return(0);
 96:   PetscMalloc1(M->rmap->n-cnt,&rows);
 97:   cnt  = 0;
 98:   for (i=0; i<m; i++) {
 99:     na = ia[i+1] - ia[i];
100:     nb = ib[i+1] - ib[i];
101:     if (!na && !nb) continue;
102:     aa = a->a + ia[i];
103:     for (j=0; j<na;j++) {
104:       if (aa[j] != 0.0) {
105:         rows[cnt++] = rstart + i;
106:         goto ok2;
107:       }
108:     }
109:     bb = b->a + ib[i];
110:     for (j=0; j<nb; j++) {
111:       if (bb[j] != 0.0) {
112:         rows[cnt++] = rstart + i;
113:         goto ok2;
114:       }
115:     }
116: ok2:;
117:   }
118:   ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);
119:   return(0);
120: }

122: PetscErrorCode  MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is)
123: {
124:   PetscErrorCode    ierr;
125:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*) Y->data;
126:   PetscBool         cong;

129:   MatHasCongruentLayouts(Y,&cong);
130:   if (Y->assembled && cong) {
131:     MatDiagonalSet(aij->A,D,is);
132:   } else {
133:     MatDiagonalSet_Default(Y,D,is);
134:   }
135:   return(0);
136: }

138: PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows)
139: {
140:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)M->data;
142:   PetscInt       i,rstart,nrows,*rows;

145:   *zrows = NULL;
146:   MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);
147:   MatGetOwnershipRange(M,&rstart,NULL);
148:   for (i=0; i<nrows; i++) rows[i] += rstart;
149:   ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);
150:   return(0);
151: }

153: PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms)
154: {
156:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)A->data;
157:   PetscInt       i,n,*garray = aij->garray;
158:   Mat_SeqAIJ     *a_aij = (Mat_SeqAIJ*) aij->A->data;
159:   Mat_SeqAIJ     *b_aij = (Mat_SeqAIJ*) aij->B->data;
160:   PetscReal      *work;

163:   MatGetSize(A,NULL,&n);
164:   PetscCalloc1(n,&work);
165:   if (type == NORM_2) {
166:     for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
167:       work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]);
168:     }
169:     for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
170:       work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]);
171:     }
172:   } else if (type == NORM_1) {
173:     for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
174:       work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]);
175:     }
176:     for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
177:       work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]);
178:     }
179:   } else if (type == NORM_INFINITY) {
180:     for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
181:       work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]);
182:     }
183:     for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
184:       work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]);
185:     }

187:   } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
188:   if (type == NORM_INFINITY) {
189:     MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
190:   } else {
191:     MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
192:   }
193:   PetscFree(work);
194:   if (type == NORM_2) {
195:     for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]);
196:   }
197:   return(0);
198: }

200: PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is)
201: {
202:   Mat_MPIAIJ      *a  = (Mat_MPIAIJ*)A->data;
203:   IS              sis,gis;
204:   PetscErrorCode  ierr;
205:   const PetscInt  *isis,*igis;
206:   PetscInt        n,*iis,nsis,ngis,rstart,i;

209:   MatFindOffBlockDiagonalEntries(a->A,&sis);
210:   MatFindNonzeroRows(a->B,&gis);
211:   ISGetSize(gis,&ngis);
212:   ISGetSize(sis,&nsis);
213:   ISGetIndices(sis,&isis);
214:   ISGetIndices(gis,&igis);

216:   PetscMalloc1(ngis+nsis,&iis);
217:   PetscMemcpy(iis,igis,ngis*sizeof(PetscInt));
218:   PetscMemcpy(iis+ngis,isis,nsis*sizeof(PetscInt));
219:   n    = ngis + nsis;
220:   PetscSortRemoveDupsInt(&n,iis);
221:   MatGetOwnershipRange(A,&rstart,NULL);
222:   for (i=0; i<n; i++) iis[i] += rstart;
223:   ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);

225:   ISRestoreIndices(sis,&isis);
226:   ISRestoreIndices(gis,&igis);
227:   ISDestroy(&sis);
228:   ISDestroy(&gis);
229:   return(0);
230: }

232: /*
233:     Distributes a SeqAIJ matrix across a set of processes. Code stolen from
234:     MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type.

236:     Only for square matrices

238:     Used by a preconditioner, hence PETSC_EXTERN
239: */
240: PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat)
241: {
242:   PetscMPIInt    rank,size;
243:   PetscInt       *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2];
245:   Mat            mat;
246:   Mat_SeqAIJ     *gmata;
247:   PetscMPIInt    tag;
248:   MPI_Status     status;
249:   PetscBool      aij;
250:   MatScalar      *gmataa,*ao,*ad,*gmataarestore=0;

253:   MPI_Comm_rank(comm,&rank);
254:   MPI_Comm_size(comm,&size);
255:   if (!rank) {
256:     PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);
257:     if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name);
258:   }
259:   if (reuse == MAT_INITIAL_MATRIX) {
260:     MatCreate(comm,&mat);
261:     MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);
262:     MatGetBlockSizes(gmat,&bses[0],&bses[1]);
263:     MPI_Bcast(bses,2,MPIU_INT,0,comm);
264:     MatSetBlockSizes(mat,bses[0],bses[1]);
265:     MatSetType(mat,MATAIJ);
266:     PetscMalloc1(size+1,&rowners);
267:     PetscMalloc2(m,&dlens,m,&olens);
268:     MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

270:     rowners[0] = 0;
271:     for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
272:     rstart = rowners[rank];
273:     rend   = rowners[rank+1];
274:     PetscObjectGetNewTag((PetscObject)mat,&tag);
275:     if (!rank) {
276:       gmata = (Mat_SeqAIJ*) gmat->data;
277:       /* send row lengths to all processors */
278:       for (i=0; i<m; i++) dlens[i] = gmata->ilen[i];
279:       for (i=1; i<size; i++) {
280:         MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
281:       }
282:       /* determine number diagonal and off-diagonal counts */
283:       PetscMemzero(olens,m*sizeof(PetscInt));
284:       PetscCalloc1(m,&ld);
285:       jj   = 0;
286:       for (i=0; i<m; i++) {
287:         for (j=0; j<dlens[i]; j++) {
288:           if (gmata->j[jj] < rstart) ld[i]++;
289:           if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++;
290:           jj++;
291:         }
292:       }
293:       /* send column indices to other processes */
294:       for (i=1; i<size; i++) {
295:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
296:         MPI_Send(&nz,1,MPIU_INT,i,tag,comm);
297:         MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);
298:       }

300:       /* send numerical values to other processes */
301:       for (i=1; i<size; i++) {
302:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
303:         MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
304:       }
305:       gmataa = gmata->a;
306:       gmataj = gmata->j;

308:     } else {
309:       /* receive row lengths */
310:       MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);
311:       /* receive column indices */
312:       MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);
313:       PetscMalloc2(nz,&gmataa,nz,&gmataj);
314:       MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);
315:       /* determine number diagonal and off-diagonal counts */
316:       PetscMemzero(olens,m*sizeof(PetscInt));
317:       PetscCalloc1(m,&ld);
318:       jj   = 0;
319:       for (i=0; i<m; i++) {
320:         for (j=0; j<dlens[i]; j++) {
321:           if (gmataj[jj] < rstart) ld[i]++;
322:           if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++;
323:           jj++;
324:         }
325:       }
326:       /* receive numerical values */
327:       PetscMemzero(gmataa,nz*sizeof(PetscScalar));
328:       MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
329:     }
330:     /* set preallocation */
331:     for (i=0; i<m; i++) {
332:       dlens[i] -= olens[i];
333:     }
334:     MatSeqAIJSetPreallocation(mat,0,dlens);
335:     MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);

337:     for (i=0; i<m; i++) {
338:       dlens[i] += olens[i];
339:     }
340:     cnt = 0;
341:     for (i=0; i<m; i++) {
342:       row  = rstart + i;
343:       MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);
344:       cnt += dlens[i];
345:     }
346:     if (rank) {
347:       PetscFree2(gmataa,gmataj);
348:     }
349:     PetscFree2(dlens,olens);
350:     PetscFree(rowners);

352:     ((Mat_MPIAIJ*)(mat->data))->ld = ld;

354:     *inmat = mat;
355:   } else {   /* column indices are already set; only need to move over numerical values from process 0 */
356:     Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data;
357:     Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data;
358:     mat  = *inmat;
359:     PetscObjectGetNewTag((PetscObject)mat,&tag);
360:     if (!rank) {
361:       /* send numerical values to other processes */
362:       gmata  = (Mat_SeqAIJ*) gmat->data;
363:       MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);
364:       gmataa = gmata->a;
365:       for (i=1; i<size; i++) {
366:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
367:         MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
368:       }
369:       nz = gmata->i[rowners[1]]-gmata->i[rowners[0]];
370:     } else {
371:       /* receive numerical values from process 0*/
372:       nz   = Ad->nz + Ao->nz;
373:       PetscMalloc1(nz,&gmataa); gmataarestore = gmataa;
374:       MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
375:     }
376:     /* transfer numerical values into the diagonal A and off diagonal B parts of mat */
377:     ld = ((Mat_MPIAIJ*)(mat->data))->ld;
378:     ad = Ad->a;
379:     ao = Ao->a;
380:     if (mat->rmap->n) {
381:       i  = 0;
382:       nz = ld[i];                                   PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar)); ao += nz; gmataa += nz;
383:       nz = Ad->i[i+1] - Ad->i[i];                   PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar)); ad += nz; gmataa += nz;
384:     }
385:     for (i=1; i<mat->rmap->n; i++) {
386:       nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar)); ao += nz; gmataa += nz;
387:       nz = Ad->i[i+1] - Ad->i[i];                   PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar)); ad += nz; gmataa += nz;
388:     }
389:     i--;
390:     if (mat->rmap->n) {
391:       nz = Ao->i[i+1] - Ao->i[i] - ld[i];           PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));
392:     }
393:     if (rank) {
394:       PetscFree(gmataarestore);
395:     }
396:   }
397:   MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
398:   MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
399:   return(0);
400: }

402: /*
403:   Local utility routine that creates a mapping from the global column
404: number to the local number in the off-diagonal part of the local
405: storage of the matrix.  When PETSC_USE_CTABLE is used this is scalable at
406: a slightly higher hash table cost; without it it is not scalable (each processor
407: has an order N integer array but is fast to acess.
408: */
409: PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat)
410: {
411:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
413:   PetscInt       n = aij->B->cmap->n,i;

416:   if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray");
417: #if defined(PETSC_USE_CTABLE)
418:   PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);
419:   for (i=0; i<n; i++) {
420:     PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);
421:   }
422: #else
423:   PetscCalloc1(mat->cmap->N+1,&aij->colmap);
424:   PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));
425:   for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1;
426: #endif
427:   return(0);
428: }

430: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol)     \
431: { \
432:     if (col <= lastcol1)  low1 = 0;     \
433:     else                 high1 = nrow1; \
434:     lastcol1 = col;\
435:     while (high1-low1 > 5) { \
436:       t = (low1+high1)/2; \
437:       if (rp1[t] > col) high1 = t; \
438:       else              low1  = t; \
439:     } \
440:       for (_i=low1; _i<high1; _i++) { \
441:         if (rp1[_i] > col) break; \
442:         if (rp1[_i] == col) { \
443:           if (addv == ADD_VALUES) ap1[_i] += value;   \
444:           else                    ap1[_i] = value; \
445:           goto a_noinsert; \
446:         } \
447:       }  \
448:       if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
449:       if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;}                \
450:       if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
451:       MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
452:       N = nrow1++ - 1; a->nz++; high1++; \
453:       /* shift up all the later entries in this row */ \
454:       for (ii=N; ii>=_i; ii--) { \
455:         rp1[ii+1] = rp1[ii]; \
456:         ap1[ii+1] = ap1[ii]; \
457:       } \
458:       rp1[_i] = col;  \
459:       ap1[_i] = value;  \
460:       A->nonzerostate++;\
461:       a_noinsert: ; \
462:       ailen[row] = nrow1; \
463: }

465: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \
466:   { \
467:     if (col <= lastcol2) low2 = 0;                        \
468:     else high2 = nrow2;                                   \
469:     lastcol2 = col;                                       \
470:     while (high2-low2 > 5) {                              \
471:       t = (low2+high2)/2;                                 \
472:       if (rp2[t] > col) high2 = t;                        \
473:       else             low2  = t;                         \
474:     }                                                     \
475:     for (_i=low2; _i<high2; _i++) {                       \
476:       if (rp2[_i] > col) break;                           \
477:       if (rp2[_i] == col) {                               \
478:         if (addv == ADD_VALUES) ap2[_i] += value;         \
479:         else                    ap2[_i] = value;          \
480:         goto b_noinsert;                                  \
481:       }                                                   \
482:     }                                                     \
483:     if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
484:     if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;}                        \
485:     if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
486:     MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
487:     N = nrow2++ - 1; b->nz++; high2++;                    \
488:     /* shift up all the later entries in this row */      \
489:     for (ii=N; ii>=_i; ii--) {                            \
490:       rp2[ii+1] = rp2[ii];                                \
491:       ap2[ii+1] = ap2[ii];                                \
492:     }                                                     \
493:     rp2[_i] = col;                                        \
494:     ap2[_i] = value;                                      \
495:     B->nonzerostate++;                                    \
496:     b_noinsert: ;                                         \
497:     bilen[row] = nrow2;                                   \
498:   }

500: PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[])
501: {
502:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)A->data;
503:   Mat_SeqAIJ     *a   = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data;
505:   PetscInt       l,*garray = mat->garray,diag;

508:   /* code only works for square matrices A */

510:   /* find size of row to the left of the diagonal part */
511:   MatGetOwnershipRange(A,&diag,0);
512:   row  = row - diag;
513:   for (l=0; l<b->i[row+1]-b->i[row]; l++) {
514:     if (garray[b->j[b->i[row]+l]] > diag) break;
515:   }
516:   PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));

518:   /* diagonal part */
519:   PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));

521:   /* right of diagonal part */
522:   PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));
523:   return(0);
524: }

526: PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
527: {
528:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
529:   PetscScalar    value;
531:   PetscInt       i,j,rstart  = mat->rmap->rstart,rend = mat->rmap->rend;
532:   PetscInt       cstart      = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
533:   PetscBool      roworiented = aij->roworiented;

535:   /* Some Variables required in the macro */
536:   Mat        A                 = aij->A;
537:   Mat_SeqAIJ *a                = (Mat_SeqAIJ*)A->data;
538:   PetscInt   *aimax            = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
539:   MatScalar  *aa               = a->a;
540:   PetscBool  ignorezeroentries = a->ignorezeroentries;
541:   Mat        B                 = aij->B;
542:   Mat_SeqAIJ *b                = (Mat_SeqAIJ*)B->data;
543:   PetscInt   *bimax            = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
544:   MatScalar  *ba               = b->a;

546:   PetscInt  *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
547:   PetscInt  nonew;
548:   MatScalar *ap1,*ap2;

551:   for (i=0; i<m; i++) {
552:     if (im[i] < 0) continue;
553: #if defined(PETSC_USE_DEBUG)
554:     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
555: #endif
556:     if (im[i] >= rstart && im[i] < rend) {
557:       row      = im[i] - rstart;
558:       lastcol1 = -1;
559:       rp1      = aj + ai[row];
560:       ap1      = aa + ai[row];
561:       rmax1    = aimax[row];
562:       nrow1    = ailen[row];
563:       low1     = 0;
564:       high1    = nrow1;
565:       lastcol2 = -1;
566:       rp2      = bj + bi[row];
567:       ap2      = ba + bi[row];
568:       rmax2    = bimax[row];
569:       nrow2    = bilen[row];
570:       low2     = 0;
571:       high2    = nrow2;

573:       for (j=0; j<n; j++) {
574:         if (roworiented) value = v[i*n+j];
575:         else             value = v[i+j*m];
576:         if (in[j] >= cstart && in[j] < cend) {
577:           col   = in[j] - cstart;
578:           nonew = a->nonew;
579:           if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
580:           MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
581:         } else if (in[j] < 0) continue;
582: #if defined(PETSC_USE_DEBUG)
583:         else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);
584: #endif
585:         else {
586:           if (mat->was_assembled) {
587:             if (!aij->colmap) {
588:               MatCreateColmap_MPIAIJ_Private(mat);
589:             }
590: #if defined(PETSC_USE_CTABLE)
591:             PetscTableFind(aij->colmap,in[j]+1,&col);
592:             col--;
593: #else
594:             col = aij->colmap[in[j]] - 1;
595: #endif
596:             if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) {
597:               MatDisAssemble_MPIAIJ(mat);
598:               col  =  in[j];
599:               /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
600:               B     = aij->B;
601:               b     = (Mat_SeqAIJ*)B->data;
602:               bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a;
603:               rp2   = bj + bi[row];
604:               ap2   = ba + bi[row];
605:               rmax2 = bimax[row];
606:               nrow2 = bilen[row];
607:               low2  = 0;
608:               high2 = nrow2;
609:               bm    = aij->B->rmap->n;
610:               ba    = b->a;
611:             } else if (col < 0) {
612:               if (1 == ((Mat_SeqAIJ*)(aij->B->data))->nonew) {
613:                 PetscInfo3(mat,"Skipping of insertion of new nonzero location in off-diagonal portion of matrix %g(%D,%D)\n",(double)PetscRealPart(value),im[i],in[j]);
614:               } else SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]);
615:             }
616:           } else col = in[j];
617:           nonew = b->nonew;
618:           MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
619:         }
620:       }
621:     } else {
622:       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
623:       if (!aij->donotstash) {
624:         mat->assembled = PETSC_FALSE;
625:         if (roworiented) {
626:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
627:         } else {
628:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
629:         }
630:       }
631:     }
632:   }
633:   return(0);
634: }

636: /*
637:     This function sets the j and ilen arrays (of the diagonal and off-diagonal part) of an MPIAIJ-matrix.
638:     The values in mat_i have to be sorted and the values in mat_j have to be sorted for each row (CSR-like).
639:     No off-processor parts off the matrix are allowed here and mat->was_assembled has to be PETSC_FALSE.
640: */
641: PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat_Symbolic(Mat mat,const PetscInt mat_j[],const PetscInt mat_i[])
642: {
643:   Mat_MPIAIJ     *aij        = (Mat_MPIAIJ*)mat->data;
644:   Mat            A           = aij->A; /* diagonal part of the matrix */
645:   Mat            B           = aij->B; /* offdiagonal part of the matrix */
646:   Mat_SeqAIJ     *a          = (Mat_SeqAIJ*)A->data;
647:   Mat_SeqAIJ     *b          = (Mat_SeqAIJ*)B->data;
648:   PetscInt       cstart      = mat->cmap->rstart,cend = mat->cmap->rend,col;
649:   PetscInt       *ailen      = a->ilen,*aj = a->j;
650:   PetscInt       *bilen      = b->ilen,*bj = b->j;
651:   PetscInt       am          = aij->A->rmap->n,j;
652:   PetscInt       diag_so_far = 0,dnz;
653:   PetscInt       offd_so_far = 0,onz;

656:   /* Iterate over all rows of the matrix */
657:   for (j=0; j<am; j++) {
658:     dnz = onz = 0;
659:     /*  Iterate over all non-zero columns of the current row */
660:     for (col=mat_i[j]; col<mat_i[j+1]; col++) {
661:       /* If column is in the diagonal */
662:       if (mat_j[col] >= cstart && mat_j[col] < cend) {
663:         aj[diag_so_far++] = mat_j[col] - cstart;
664:         dnz++;
665:       } else { /* off-diagonal entries */
666:         bj[offd_so_far++] = mat_j[col];
667:         onz++;
668:       }
669:     }
670:     ailen[j] = dnz;
671:     bilen[j] = onz;
672:   }
673:   return(0);
674: }

676: /*
677:     This function sets the local j, a and ilen arrays (of the diagonal and off-diagonal part) of an MPIAIJ-matrix.
678:     The values in mat_i have to be sorted and the values in mat_j have to be sorted for each row (CSR-like).
679:     No off-processor parts off the matrix are allowed here, they are set at a later point by MatSetValues_MPIAIJ.
680:     Also, mat->was_assembled has to be false, otherwise the statement aj[rowstart_diag+dnz_row] = mat_j[col] - cstart;
681:     would not be true and the more complex MatSetValues_MPIAIJ has to be used.
682: */
683: PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat(Mat mat,const PetscInt mat_j[],const PetscInt mat_i[],const PetscScalar mat_a[])
684: {
685:   Mat_MPIAIJ     *aij   = (Mat_MPIAIJ*)mat->data;
686:   Mat            A      = aij->A; /* diagonal part of the matrix */
687:   Mat            B      = aij->B; /* offdiagonal part of the matrix */
688:   Mat_SeqAIJ     *aijd  =(Mat_SeqAIJ*)(aij->A)->data,*aijo=(Mat_SeqAIJ*)(aij->B)->data;
689:   Mat_SeqAIJ     *a     = (Mat_SeqAIJ*)A->data;
690:   Mat_SeqAIJ     *b     = (Mat_SeqAIJ*)B->data;
691:   PetscInt       cstart = mat->cmap->rstart,cend = mat->cmap->rend;
692:   PetscInt       *ailen = a->ilen,*aj = a->j;
693:   PetscInt       *bilen = b->ilen,*bj = b->j;
694:   PetscInt       am     = aij->A->rmap->n,j;
695:   PetscInt       *full_diag_i=aijd->i,*full_offd_i=aijo->i; /* These variables can also include non-local elements, which are set at a later point. */
696:   PetscInt       col,dnz_row,onz_row,rowstart_diag,rowstart_offd;
697:   PetscScalar    *aa = a->a,*ba = b->a;

700:   /* Iterate over all rows of the matrix */
701:   for (j=0; j<am; j++) {
702:     dnz_row = onz_row = 0;
703:     rowstart_offd = full_offd_i[j];
704:     rowstart_diag = full_diag_i[j];
705:     /*  Iterate over all non-zero columns of the current row */
706:     for (col=mat_i[j]; col<mat_i[j+1]; col++) {
707:       /* If column is in the diagonal */
708:       if (mat_j[col] >= cstart && mat_j[col] < cend) {
709:         aj[rowstart_diag+dnz_row] = mat_j[col] - cstart;
710:         aa[rowstart_diag+dnz_row] = mat_a[col];
711:         dnz_row++;
712:       } else { /* off-diagonal entries */
713:         bj[rowstart_offd+onz_row] = mat_j[col];
714:         ba[rowstart_offd+onz_row] = mat_a[col];
715:         onz_row++;
716:       }
717:     }
718:     ailen[j] = dnz_row;
719:     bilen[j] = onz_row;
720:   }
721:   return(0);
722: }

724: PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
725: {
726:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
728:   PetscInt       i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
729:   PetscInt       cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;

732:   for (i=0; i<m; i++) {
733:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
734:     if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1);
735:     if (idxm[i] >= rstart && idxm[i] < rend) {
736:       row = idxm[i] - rstart;
737:       for (j=0; j<n; j++) {
738:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
739:         if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1);
740:         if (idxn[j] >= cstart && idxn[j] < cend) {
741:           col  = idxn[j] - cstart;
742:           MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
743:         } else {
744:           if (!aij->colmap) {
745:             MatCreateColmap_MPIAIJ_Private(mat);
746:           }
747: #if defined(PETSC_USE_CTABLE)
748:           PetscTableFind(aij->colmap,idxn[j]+1,&col);
749:           col--;
750: #else
751:           col = aij->colmap[idxn[j]] - 1;
752: #endif
753:           if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
754:           else {
755:             MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
756:           }
757:         }
758:       }
759:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
760:   }
761:   return(0);
762: }

764: extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec);

766: PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode)
767: {
768:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
770:   PetscInt       nstash,reallocs;

773:   if (aij->donotstash || mat->nooffprocentries) return(0);

775:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
776:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
777:   PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
778:   return(0);
779: }

781: PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode)
782: {
783:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
784:   Mat_SeqAIJ     *a   = (Mat_SeqAIJ*)aij->A->data;
786:   PetscMPIInt    n;
787:   PetscInt       i,j,rstart,ncols,flg;
788:   PetscInt       *row,*col;
789:   PetscBool      other_disassembled;
790:   PetscScalar    *val;

792:   /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */

795:   if (!aij->donotstash && !mat->nooffprocentries) {
796:     while (1) {
797:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
798:       if (!flg) break;

800:       for (i=0; i<n; ) {
801:         /* Now identify the consecutive vals belonging to the same row */
802:         for (j=i,rstart=row[j]; j<n; j++) {
803:           if (row[j] != rstart) break;
804:         }
805:         if (j < n) ncols = j-i;
806:         else       ncols = n-i;
807:         /* Now assemble all these values with a single function call */
808:         MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);

810:         i = j;
811:       }
812:     }
813:     MatStashScatterEnd_Private(&mat->stash);
814:   }
815:   MatAssemblyBegin(aij->A,mode);
816:   MatAssemblyEnd(aij->A,mode);

818:   /* determine if any processor has disassembled, if so we must
819:      also disassemble ourselfs, in order that we may reassemble. */
820:   /*
821:      if nonzero structure of submatrix B cannot change then we know that
822:      no processor disassembled thus we can skip this stuff
823:   */
824:   if (!((Mat_SeqAIJ*)aij->B->data)->nonew) {
825:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
826:     if (mat->was_assembled && !other_disassembled) {
827:       MatDisAssemble_MPIAIJ(mat);
828:     }
829:   }
830:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
831:     MatSetUpMultiply_MPIAIJ(mat);
832:   }
833:   MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);
834:   MatAssemblyBegin(aij->B,mode);
835:   MatAssemblyEnd(aij->B,mode);

837:   PetscFree2(aij->rowvalues,aij->rowindices);

839:   aij->rowvalues = 0;

841:   VecDestroy(&aij->diag);
842:   if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ;

844:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
845:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
846:     PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate;
847:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
848:   }
849:   return(0);
850: }

852: PetscErrorCode MatZeroEntries_MPIAIJ(Mat A)
853: {
854:   Mat_MPIAIJ     *l = (Mat_MPIAIJ*)A->data;

858:   MatZeroEntries(l->A);
859:   MatZeroEntries(l->B);
860:   return(0);
861: }

863: PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
864: {
865:   Mat_MPIAIJ      *mat = (Mat_MPIAIJ *) A->data;
866:   PetscObjectState sA, sB;
867:   PetscInt        *lrows;
868:   PetscInt         r, len;
869:   PetscBool        cong, lch, gch;
870:   PetscErrorCode   ierr;

873:   /* get locally owned rows */
874:   MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);
875:   MatHasCongruentLayouts(A,&cong);
876:   /* fix right hand side if needed */
877:   if (x && b) {
878:     const PetscScalar *xx;
879:     PetscScalar       *bb;

881:     if (!cong) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Need matching row/col layout");
882:     VecGetArrayRead(x, &xx);
883:     VecGetArray(b, &bb);
884:     for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
885:     VecRestoreArrayRead(x, &xx);
886:     VecRestoreArray(b, &bb);
887:   }

889:   sA = mat->A->nonzerostate;
890:   sB = mat->B->nonzerostate;

892:   if (diag != 0.0 && cong) {
893:     MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);
894:     MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
895:   } else if (diag != 0.0) { /* non-square or non congruent layouts -> if keepnonzeropattern is false, we allow for new insertion */
896:     Mat_SeqAIJ *aijA = (Mat_SeqAIJ*)mat->A->data;
897:     Mat_SeqAIJ *aijB = (Mat_SeqAIJ*)mat->B->data;
898:     PetscInt   nnwA, nnwB;
899:     PetscBool  nnzA, nnzB;

901:     nnwA = aijA->nonew;
902:     nnwB = aijB->nonew;
903:     nnzA = aijA->keepnonzeropattern;
904:     nnzB = aijB->keepnonzeropattern;
905:     if (!nnzA) {
906:       PetscInfo(mat->A,"Requested to not keep the pattern and add a nonzero diagonal; may encounter reallocations on diagonal block.\n");
907:       aijA->nonew = 0;
908:     }
909:     if (!nnzB) {
910:       PetscInfo(mat->B,"Requested to not keep the pattern and add a nonzero diagonal; may encounter reallocations on off-diagonal block.\n");
911:       aijB->nonew = 0;
912:     }
913:     /* Must zero here before the next loop */
914:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
915:     MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
916:     for (r = 0; r < len; ++r) {
917:       const PetscInt row = lrows[r] + A->rmap->rstart;
918:       if (row >= A->cmap->N) continue;
919:       MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);
920:     }
921:     aijA->nonew = nnwA;
922:     aijB->nonew = nnwB;
923:   } else {
924:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
925:     MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
926:   }
927:   PetscFree(lrows);
928:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
929:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);

931:   /* reduce nonzerostate */
932:   lch = (PetscBool)(sA != mat->A->nonzerostate || sB != mat->B->nonzerostate);
933:   MPIU_Allreduce(&lch,&gch,1,MPIU_BOOL,MPI_LOR,PetscObjectComm((PetscObject)A));
934:   if (gch) A->nonzerostate++;
935:   return(0);
936: }

938: PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
939: {
940:   Mat_MPIAIJ        *l = (Mat_MPIAIJ*)A->data;
941:   PetscErrorCode    ierr;
942:   PetscMPIInt       n = A->rmap->n;
943:   PetscInt          i,j,r,m,p = 0,len = 0;
944:   PetscInt          *lrows,*owners = A->rmap->range;
945:   PetscSFNode       *rrows;
946:   PetscSF           sf;
947:   const PetscScalar *xx;
948:   PetscScalar       *bb,*mask;
949:   Vec               xmask,lmask;
950:   Mat_SeqAIJ        *aij = (Mat_SeqAIJ*)l->B->data;
951:   const PetscInt    *aj, *ii,*ridx;
952:   PetscScalar       *aa;

955:   /* Create SF where leaves are input rows and roots are owned rows */
956:   PetscMalloc1(n, &lrows);
957:   for (r = 0; r < n; ++r) lrows[r] = -1;
958:   PetscMalloc1(N, &rrows);
959:   for (r = 0; r < N; ++r) {
960:     const PetscInt idx   = rows[r];
961:     if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N);
962:     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
963:       PetscLayoutFindOwner(A->rmap,idx,&p);
964:     }
965:     rrows[r].rank  = p;
966:     rrows[r].index = rows[r] - owners[p];
967:   }
968:   PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
969:   PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
970:   /* Collect flags for rows to be zeroed */
971:   PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
972:   PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
973:   PetscSFDestroy(&sf);
974:   /* Compress and put in row numbers */
975:   for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
976:   /* zero diagonal part of matrix */
977:   MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
978:   /* handle off diagonal part of matrix */
979:   MatCreateVecs(A,&xmask,NULL);
980:   VecDuplicate(l->lvec,&lmask);
981:   VecGetArray(xmask,&bb);
982:   for (i=0; i<len; i++) bb[lrows[i]] = 1;
983:   VecRestoreArray(xmask,&bb);
984:   VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
985:   VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
986:   VecDestroy(&xmask);
987:   if (x && b) { /* this code is buggy when the row and column layout don't match */
988:     PetscBool cong;

990:     MatHasCongruentLayouts(A,&cong);
991:     if (!cong) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Need matching row/col layout");
992:     VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
993:     VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
994:     VecGetArrayRead(l->lvec,&xx);
995:     VecGetArray(b,&bb);
996:   }
997:   VecGetArray(lmask,&mask);
998:   /* remove zeroed rows of off diagonal matrix */
999:   ii = aij->i;
1000:   for (i=0; i<len; i++) {
1001:     PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));
1002:   }
1003:   /* loop over all elements of off process part of matrix zeroing removed columns*/
1004:   if (aij->compressedrow.use) {
1005:     m    = aij->compressedrow.nrows;
1006:     ii   = aij->compressedrow.i;
1007:     ridx = aij->compressedrow.rindex;
1008:     for (i=0; i<m; i++) {
1009:       n  = ii[i+1] - ii[i];
1010:       aj = aij->j + ii[i];
1011:       aa = aij->a + ii[i];

1013:       for (j=0; j<n; j++) {
1014:         if (PetscAbsScalar(mask[*aj])) {
1015:           if (b) bb[*ridx] -= *aa*xx[*aj];
1016:           *aa = 0.0;
1017:         }
1018:         aa++;
1019:         aj++;
1020:       }
1021:       ridx++;
1022:     }
1023:   } else { /* do not use compressed row format */
1024:     m = l->B->rmap->n;
1025:     for (i=0; i<m; i++) {
1026:       n  = ii[i+1] - ii[i];
1027:       aj = aij->j + ii[i];
1028:       aa = aij->a + ii[i];
1029:       for (j=0; j<n; j++) {
1030:         if (PetscAbsScalar(mask[*aj])) {
1031:           if (b) bb[i] -= *aa*xx[*aj];
1032:           *aa = 0.0;
1033:         }
1034:         aa++;
1035:         aj++;
1036:       }
1037:     }
1038:   }
1039:   if (x && b) {
1040:     VecRestoreArray(b,&bb);
1041:     VecRestoreArrayRead(l->lvec,&xx);
1042:   }
1043:   VecRestoreArray(lmask,&mask);
1044:   VecDestroy(&lmask);
1045:   PetscFree(lrows);

1047:   /* only change matrix nonzero state if pattern was allowed to be changed */
1048:   if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) {
1049:     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
1050:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
1051:   }
1052:   return(0);
1053: }

1055: PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy)
1056: {
1057:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
1059:   PetscInt       nt;
1060:   VecScatter     Mvctx = a->Mvctx;

1063:   VecGetLocalSize(xx,&nt);
1064:   if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt);

1066:   VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1067:   (*a->A->ops->mult)(a->A,xx,yy);
1068:   VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1069:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1070:   return(0);
1071: }

1073: PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx)
1074: {
1075:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1079:   MatMultDiagonalBlock(a->A,bb,xx);
1080:   return(0);
1081: }

1083: PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1084: {
1085:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
1087:   VecScatter     Mvctx = a->Mvctx;

1090:   if (a->Mvctx_mpi1_flg) Mvctx = a->Mvctx_mpi1;
1091:   VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1092:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
1093:   VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1094:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
1095:   return(0);
1096: }

1098: PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy)
1099: {
1100:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1104:   /* do nondiagonal part */
1105:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1106:   /* do local part */
1107:   (*a->A->ops->multtranspose)(a->A,xx,yy);
1108:   /* add partial results together */
1109:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1110:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1111:   return(0);
1112: }

1114: PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool  *f)
1115: {
1116:   MPI_Comm       comm;
1117:   Mat_MPIAIJ     *Aij = (Mat_MPIAIJ*) Amat->data, *Bij;
1118:   Mat            Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs;
1119:   IS             Me,Notme;
1121:   PetscInt       M,N,first,last,*notme,i;
1122:   PetscBool      lf;
1123:   PetscMPIInt    size;

1126:   /* Easy test: symmetric diagonal block */
1127:   Bij  = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A;
1128:   MatIsTranspose(Adia,Bdia,tol,&lf);
1129:   MPIU_Allreduce(&lf,f,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)Amat));
1130:   if (!*f) return(0);
1131:   PetscObjectGetComm((PetscObject)Amat,&comm);
1132:   MPI_Comm_size(comm,&size);
1133:   if (size == 1) return(0);

1135:   /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */
1136:   MatGetSize(Amat,&M,&N);
1137:   MatGetOwnershipRange(Amat,&first,&last);
1138:   PetscMalloc1(N-last+first,&notme);
1139:   for (i=0; i<first; i++) notme[i] = i;
1140:   for (i=last; i<M; i++) notme[i-last+first] = i;
1141:   ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
1142:   ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
1143:   MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
1144:   Aoff = Aoffs[0];
1145:   MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
1146:   Boff = Boffs[0];
1147:   MatIsTranspose(Aoff,Boff,tol,f);
1148:   MatDestroyMatrices(1,&Aoffs);
1149:   MatDestroyMatrices(1,&Boffs);
1150:   ISDestroy(&Me);
1151:   ISDestroy(&Notme);
1152:   PetscFree(notme);
1153:   return(0);
1154: }

1156: PetscErrorCode MatIsSymmetric_MPIAIJ(Mat A,PetscReal tol,PetscBool  *f)
1157: {

1161:   MatIsTranspose_MPIAIJ(A,A,tol,f);
1162:   return(0);
1163: }

1165: PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1166: {
1167:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1171:   /* do nondiagonal part */
1172:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1173:   /* do local part */
1174:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
1175:   /* add partial results together */
1176:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1177:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1178:   return(0);
1179: }

1181: /*
1182:   This only works correctly for square matrices where the subblock A->A is the
1183:    diagonal block
1184: */
1185: PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v)
1186: {
1188:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1191:   if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1192:   if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition");
1193:   MatGetDiagonal(a->A,v);
1194:   return(0);
1195: }

1197: PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa)
1198: {
1199:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1203:   MatScale(a->A,aa);
1204:   MatScale(a->B,aa);
1205:   return(0);
1206: }

1208: PetscErrorCode MatDestroy_MPIAIJ(Mat mat)
1209: {
1210:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

1214: #if defined(PETSC_USE_LOG)
1215:   PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
1216: #endif
1217:   MatStashDestroy_Private(&mat->stash);
1218:   VecDestroy(&aij->diag);
1219:   MatDestroy(&aij->A);
1220:   MatDestroy(&aij->B);
1221: #if defined(PETSC_USE_CTABLE)
1222:   PetscTableDestroy(&aij->colmap);
1223: #else
1224:   PetscFree(aij->colmap);
1225: #endif
1226:   PetscFree(aij->garray);
1227:   VecDestroy(&aij->lvec);
1228:   VecScatterDestroy(&aij->Mvctx);
1229:   if (aij->Mvctx_mpi1) {VecScatterDestroy(&aij->Mvctx_mpi1);}
1230:   PetscFree2(aij->rowvalues,aij->rowindices);
1231:   PetscFree(aij->ld);
1232:   PetscFree(mat->data);

1234:   PetscObjectChangeTypeName((PetscObject)mat,0);
1235:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1236:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1237:   PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
1238:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);
1239:   PetscObjectComposeFunction((PetscObject)mat,"MatResetPreallocation_C",NULL);
1240:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);
1241:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
1242:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);
1243: #if defined(PETSC_HAVE_ELEMENTAL)
1244:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);
1245: #endif
1246: #if defined(PETSC_HAVE_HYPRE)
1247:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);
1248:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMatMult_transpose_mpiaij_mpiaij_C",NULL);
1249: #endif
1250:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_is_C",NULL);
1251:   PetscObjectComposeFunction((PetscObject)mat,"MatPtAP_is_mpiaij_C",NULL);
1252:   return(0);
1253: }

1255: PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer)
1256: {
1257:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
1258:   Mat_SeqAIJ     *A   = (Mat_SeqAIJ*)aij->A->data;
1259:   Mat_SeqAIJ     *B   = (Mat_SeqAIJ*)aij->B->data;
1261:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
1262:   int            fd;
1263:   PetscInt       nz,header[4],*row_lengths,*range=0,rlen,i;
1264:   PetscInt       nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0;
1265:   PetscScalar    *column_values;
1266:   PetscInt       message_count,flowcontrolcount;
1267:   FILE           *file;

1270:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1271:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
1272:   nz   = A->nz + B->nz;
1273:   PetscViewerBinaryGetDescriptor(viewer,&fd);
1274:   if (!rank) {
1275:     header[0] = MAT_FILE_CLASSID;
1276:     header[1] = mat->rmap->N;
1277:     header[2] = mat->cmap->N;

1279:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1280:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
1281:     /* get largest number of rows any processor has */
1282:     rlen  = mat->rmap->n;
1283:     range = mat->rmap->range;
1284:     for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]);
1285:   } else {
1286:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1287:     rlen = mat->rmap->n;
1288:   }

1290:   /* load up the local row counts */
1291:   PetscMalloc1(rlen+1,&row_lengths);
1292:   for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];

1294:   /* store the row lengths to the file */
1295:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1296:   if (!rank) {
1297:     PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);
1298:     for (i=1; i<size; i++) {
1299:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1300:       rlen = range[i+1] - range[i];
1301:       MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1302:       PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);
1303:     }
1304:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1305:   } else {
1306:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1307:     MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1308:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1309:   }
1310:   PetscFree(row_lengths);

1312:   /* load up the local column indices */
1313:   nzmax = nz; /* th processor needs space a largest processor needs */
1314:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
1315:   PetscMalloc1(nzmax+1,&column_indices);
1316:   cnt   = 0;
1317:   for (i=0; i<mat->rmap->n; i++) {
1318:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1319:       if ((col = garray[B->j[j]]) > cstart) break;
1320:       column_indices[cnt++] = col;
1321:     }
1322:     for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart;
1323:     for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]];
1324:   }
1325:   if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);

1327:   /* store the column indices to the file */
1328:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1329:   if (!rank) {
1330:     MPI_Status status;
1331:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1332:     for (i=1; i<size; i++) {
1333:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1334:       MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1335:       if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1336:       MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1337:       PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);
1338:     }
1339:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1340:   } else {
1341:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1342:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1343:     MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1344:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1345:   }
1346:   PetscFree(column_indices);

1348:   /* load up the local column values */
1349:   PetscMalloc1(nzmax+1,&column_values);
1350:   cnt  = 0;
1351:   for (i=0; i<mat->rmap->n; i++) {
1352:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1353:       if (garray[B->j[j]] > cstart) break;
1354:       column_values[cnt++] = B->a[j];
1355:     }
1356:     for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k];
1357:     for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j];
1358:   }
1359:   if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);

1361:   /* store the column values to the file */
1362:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1363:   if (!rank) {
1364:     MPI_Status status;
1365:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1366:     for (i=1; i<size; i++) {
1367:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1368:       MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1369:       if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1370:       MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));
1371:       PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);
1372:     }
1373:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1374:   } else {
1375:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1376:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1377:     MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1378:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1379:   }
1380:   PetscFree(column_values);

1382:   PetscViewerBinaryGetInfoPointer(viewer,&file);
1383:   if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs));
1384:   return(0);
1385: }

1387:  #include <petscdraw.h>
1388: PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1389: {
1390:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*)mat->data;
1391:   PetscErrorCode    ierr;
1392:   PetscMPIInt       rank = aij->rank,size = aij->size;
1393:   PetscBool         isdraw,iascii,isbinary;
1394:   PetscViewer       sviewer;
1395:   PetscViewerFormat format;

1398:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1399:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1400:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1401:   if (iascii) {
1402:     PetscViewerGetFormat(viewer,&format);
1403:     if (format == PETSC_VIEWER_LOAD_BALANCE) {
1404:       PetscInt i,nmax = 0,nmin = PETSC_MAX_INT,navg = 0,*nz,nzlocal = ((Mat_SeqAIJ*) (aij->A->data))->nz + ((Mat_SeqAIJ*) (aij->B->data))->nz;
1405:       PetscMalloc1(size,&nz);
1406:       MPI_Allgather(&nzlocal,1,MPIU_INT,nz,1,MPIU_INT,PetscObjectComm((PetscObject)mat));
1407:       for (i=0; i<(PetscInt)size; i++) {
1408:         nmax = PetscMax(nmax,nz[i]);
1409:         nmin = PetscMin(nmin,nz[i]);
1410:         navg += nz[i];
1411:       }
1412:       PetscFree(nz);
1413:       navg = navg/size;
1414:       PetscViewerASCIIPrintf(viewer,"Load Balance - Nonzeros: Min %D  avg %D  max %D\n",nmin,navg,nmax);
1415:       return(0);
1416:     }
1417:     PetscViewerGetFormat(viewer,&format);
1418:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1419:       MatInfo   info;
1420:       PetscBool inodes;

1422:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1423:       MatGetInfo(mat,MAT_LOCAL,&info);
1424:       MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);
1425:       PetscViewerASCIIPushSynchronized(viewer);
1426:       if (!inodes) {
1427:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, not using I-node routines\n",
1428:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1429:       } else {
1430:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, using I-node routines\n",
1431:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1432:       }
1433:       MatGetInfo(aij->A,MAT_LOCAL,&info);
1434:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1435:       MatGetInfo(aij->B,MAT_LOCAL,&info);
1436:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1437:       PetscViewerFlush(viewer);
1438:       PetscViewerASCIIPopSynchronized(viewer);
1439:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
1440:       VecScatterView(aij->Mvctx,viewer);
1441:       return(0);
1442:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
1443:       PetscInt inodecount,inodelimit,*inodes;
1444:       MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);
1445:       if (inodes) {
1446:         PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
1447:       } else {
1448:         PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
1449:       }
1450:       return(0);
1451:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1452:       return(0);
1453:     }
1454:   } else if (isbinary) {
1455:     if (size == 1) {
1456:       PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1457:       MatView(aij->A,viewer);
1458:     } else {
1459:       MatView_MPIAIJ_Binary(mat,viewer);
1460:     }
1461:     return(0);
1462:   } else if (iascii && size == 1) {
1463:     PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1464:     MatView(aij->A,viewer);
1465:     return(0);
1466:   } else if (isdraw) {
1467:     PetscDraw draw;
1468:     PetscBool isnull;
1469:     PetscViewerDrawGetDraw(viewer,0,&draw);
1470:     PetscDrawIsNull(draw,&isnull);
1471:     if (isnull) return(0);
1472:   }

1474:   { /* assemble the entire matrix onto first processor */
1475:     Mat A = NULL, Av;
1476:     IS  isrow,iscol;

1478:     ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->rmap->N : 0,0,1,&isrow);
1479:     ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->cmap->N : 0,0,1,&iscol);
1480:     MatCreateSubMatrix(mat,isrow,iscol,MAT_INITIAL_MATRIX,&A);
1481:     MatMPIAIJGetSeqAIJ(A,&Av,NULL,NULL);
1482: /*  The commented code uses MatCreateSubMatrices instead */
1483: /*
1484:     Mat *AA, A = NULL, Av;
1485:     IS  isrow,iscol;

1487:     ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->rmap->N : 0,0,1,&isrow);
1488:     ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->cmap->N : 0,0,1,&iscol);
1489:     MatCreateSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&AA);
1490:     if (!rank) {
1491:        PetscObjectReference((PetscObject)AA[0]);
1492:        A    = AA[0];
1493:        Av   = AA[0];
1494:     }
1495:     MatDestroySubMatrices(1,&AA);
1496: */
1497:     ISDestroy(&iscol);
1498:     ISDestroy(&isrow);
1499:     /*
1500:        Everyone has to call to draw the matrix since the graphics waits are
1501:        synchronized across all processors that share the PetscDraw object
1502:     */
1503:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1504:     if (!rank) {
1505:       if (((PetscObject)mat)->name) {
1506:         PetscObjectSetName((PetscObject)Av,((PetscObject)mat)->name);
1507:       }
1508:       MatView_SeqAIJ(Av,sviewer);
1509:     }
1510:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1511:     PetscViewerFlush(viewer);
1512:     MatDestroy(&A);
1513:   }
1514:   return(0);
1515: }

1517: PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer)
1518: {
1520:   PetscBool      iascii,isdraw,issocket,isbinary;

1523:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1524:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1525:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1526:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1527:   if (iascii || isdraw || isbinary || issocket) {
1528:     MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);
1529:   }
1530:   return(0);
1531: }

1533: PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1534: {
1535:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1537:   Vec            bb1 = 0;
1538:   PetscBool      hasop;

1541:   if (flag == SOR_APPLY_UPPER) {
1542:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1543:     return(0);
1544:   }

1546:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1547:     VecDuplicate(bb,&bb1);
1548:   }

1550:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
1551:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1552:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1553:       its--;
1554:     }

1556:     while (its--) {
1557:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1558:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1560:       /* update rhs: bb1 = bb - B*x */
1561:       VecScale(mat->lvec,-1.0);
1562:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1564:       /* local sweep */
1565:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1566:     }
1567:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
1568:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1569:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1570:       its--;
1571:     }
1572:     while (its--) {
1573:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1574:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1576:       /* update rhs: bb1 = bb - B*x */
1577:       VecScale(mat->lvec,-1.0);
1578:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1580:       /* local sweep */
1581:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1582:     }
1583:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
1584:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1585:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1586:       its--;
1587:     }
1588:     while (its--) {
1589:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1590:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1592:       /* update rhs: bb1 = bb - B*x */
1593:       VecScale(mat->lvec,-1.0);
1594:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1596:       /* local sweep */
1597:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1598:     }
1599:   } else if (flag & SOR_EISENSTAT) {
1600:     Vec xx1;

1602:     VecDuplicate(bb,&xx1);
1603:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

1605:     VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1606:     VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1607:     if (!mat->diag) {
1608:       MatCreateVecs(matin,&mat->diag,NULL);
1609:       MatGetDiagonal(matin,mat->diag);
1610:     }
1611:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
1612:     if (hasop) {
1613:       MatMultDiagonalBlock(matin,xx,bb1);
1614:     } else {
1615:       VecPointwiseMult(bb1,mat->diag,xx);
1616:     }
1617:     VecAYPX(bb1,(omega-2.0)/omega,bb);

1619:     MatMultAdd(mat->B,mat->lvec,bb1,bb1);

1621:     /* local sweep */
1622:     (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
1623:     VecAXPY(xx,1.0,xx1);
1624:     VecDestroy(&xx1);
1625:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");

1627:   VecDestroy(&bb1);

1629:   matin->factorerrortype = mat->A->factorerrortype;
1630:   return(0);
1631: }

1633: PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B)
1634: {
1635:   Mat            aA,aB,Aperm;
1636:   const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj;
1637:   PetscScalar    *aa,*ba;
1638:   PetscInt       i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest;
1639:   PetscSF        rowsf,sf;
1640:   IS             parcolp = NULL;
1641:   PetscBool      done;

1645:   MatGetLocalSize(A,&m,&n);
1646:   ISGetIndices(rowp,&rwant);
1647:   ISGetIndices(colp,&cwant);
1648:   PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);

1650:   /* Invert row permutation to find out where my rows should go */
1651:   PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);
1652:   PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);
1653:   PetscSFSetFromOptions(rowsf);
1654:   for (i=0; i<m; i++) work[i] = A->rmap->rstart + i;
1655:   PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1656:   PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);

1658:   /* Invert column permutation to find out where my columns should go */
1659:   PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1660:   PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);
1661:   PetscSFSetFromOptions(sf);
1662:   for (i=0; i<n; i++) work[i] = A->cmap->rstart + i;
1663:   PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1664:   PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1665:   PetscSFDestroy(&sf);

1667:   ISRestoreIndices(rowp,&rwant);
1668:   ISRestoreIndices(colp,&cwant);
1669:   MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);

1671:   /* Find out where my gcols should go */
1672:   MatGetSize(aB,NULL,&ng);
1673:   PetscMalloc1(ng,&gcdest);
1674:   PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1675:   PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);
1676:   PetscSFSetFromOptions(sf);
1677:   PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);
1678:   PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);
1679:   PetscSFDestroy(&sf);

1681:   PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);
1682:   MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1683:   MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1684:   for (i=0; i<m; i++) {
1685:     PetscInt row = rdest[i],rowner;
1686:     PetscLayoutFindOwner(A->rmap,row,&rowner);
1687:     for (j=ai[i]; j<ai[i+1]; j++) {
1688:       PetscInt cowner,col = cdest[aj[j]];
1689:       PetscLayoutFindOwner(A->cmap,col,&cowner); /* Could build an index for the columns to eliminate this search */
1690:       if (rowner == cowner) dnnz[i]++;
1691:       else onnz[i]++;
1692:     }
1693:     for (j=bi[i]; j<bi[i+1]; j++) {
1694:       PetscInt cowner,col = gcdest[bj[j]];
1695:       PetscLayoutFindOwner(A->cmap,col,&cowner);
1696:       if (rowner == cowner) dnnz[i]++;
1697:       else onnz[i]++;
1698:     }
1699:   }
1700:   PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);
1701:   PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);
1702:   PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);
1703:   PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);
1704:   PetscSFDestroy(&rowsf);

1706:   MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);
1707:   MatSeqAIJGetArray(aA,&aa);
1708:   MatSeqAIJGetArray(aB,&ba);
1709:   for (i=0; i<m; i++) {
1710:     PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */
1711:     PetscInt j0,rowlen;
1712:     rowlen = ai[i+1] - ai[i];
1713:     for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */
1714:       for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]];
1715:       MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);
1716:     }
1717:     rowlen = bi[i+1] - bi[i];
1718:     for (j0=j=0; j<rowlen; j0=j) {
1719:       for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]];
1720:       MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);
1721:     }
1722:   }
1723:   MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);
1724:   MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);
1725:   MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1726:   MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1727:   MatSeqAIJRestoreArray(aA,&aa);
1728:   MatSeqAIJRestoreArray(aB,&ba);
1729:   PetscFree4(dnnz,onnz,tdnnz,tonnz);
1730:   PetscFree3(work,rdest,cdest);
1731:   PetscFree(gcdest);
1732:   if (parcolp) {ISDestroy(&colp);}
1733:   *B = Aperm;
1734:   return(0);
1735: }

1737: PetscErrorCode  MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
1738: {
1739:   Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;

1743:   MatGetSize(aij->B,NULL,nghosts);
1744:   if (ghosts) *ghosts = aij->garray;
1745:   return(0);
1746: }

1748: PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1749: {
1750:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1751:   Mat            A    = mat->A,B = mat->B;
1753:   PetscReal      isend[5],irecv[5];

1756:   info->block_size = 1.0;
1757:   MatGetInfo(A,MAT_LOCAL,info);

1759:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1760:   isend[3] = info->memory;  isend[4] = info->mallocs;

1762:   MatGetInfo(B,MAT_LOCAL,info);

1764:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1765:   isend[3] += info->memory;  isend[4] += info->mallocs;
1766:   if (flag == MAT_LOCAL) {
1767:     info->nz_used      = isend[0];
1768:     info->nz_allocated = isend[1];
1769:     info->nz_unneeded  = isend[2];
1770:     info->memory       = isend[3];
1771:     info->mallocs      = isend[4];
1772:   } else if (flag == MAT_GLOBAL_MAX) {
1773:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

1775:     info->nz_used      = irecv[0];
1776:     info->nz_allocated = irecv[1];
1777:     info->nz_unneeded  = irecv[2];
1778:     info->memory       = irecv[3];
1779:     info->mallocs      = irecv[4];
1780:   } else if (flag == MAT_GLOBAL_SUM) {
1781:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

1783:     info->nz_used      = irecv[0];
1784:     info->nz_allocated = irecv[1];
1785:     info->nz_unneeded  = irecv[2];
1786:     info->memory       = irecv[3];
1787:     info->mallocs      = irecv[4];
1788:   }
1789:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1790:   info->fill_ratio_needed = 0;
1791:   info->factor_mallocs    = 0;
1792:   return(0);
1793: }

1795: PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg)
1796: {
1797:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1801:   switch (op) {
1802:   case MAT_NEW_NONZERO_LOCATIONS:
1803:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1804:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1805:   case MAT_KEEP_NONZERO_PATTERN:
1806:   case MAT_NEW_NONZERO_LOCATION_ERR:
1807:   case MAT_USE_INODES:
1808:   case MAT_IGNORE_ZERO_ENTRIES:
1809:     MatCheckPreallocated(A,1);
1810:     MatSetOption(a->A,op,flg);
1811:     MatSetOption(a->B,op,flg);
1812:     break;
1813:   case MAT_ROW_ORIENTED:
1814:     MatCheckPreallocated(A,1);
1815:     a->roworiented = flg;

1817:     MatSetOption(a->A,op,flg);
1818:     MatSetOption(a->B,op,flg);
1819:     break;
1820:   case MAT_NEW_DIAGONALS:
1821:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1822:     break;
1823:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1824:     a->donotstash = flg;
1825:     break;
1826:   /* Symmetry flags are handled directly by MatSetOption() and they don't affect preallocation */
1827:   case MAT_SPD:
1828:   case MAT_SYMMETRIC:
1829:   case MAT_STRUCTURALLY_SYMMETRIC:
1830:   case MAT_HERMITIAN:
1831:   case MAT_SYMMETRY_ETERNAL:
1832:     break;
1833:   case MAT_SUBMAT_SINGLEIS:
1834:     A->submat_singleis = flg;
1835:     break;
1836:   case MAT_STRUCTURE_ONLY:
1837:     /* The option is handled directly by MatSetOption() */
1838:     break;
1839:   default:
1840:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1841:   }
1842:   return(0);
1843: }

1845: PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1846: {
1847:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1848:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1850:   PetscInt       i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart;
1851:   PetscInt       nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend;
1852:   PetscInt       *cmap,*idx_p;

1855:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1856:   mat->getrowactive = PETSC_TRUE;

1858:   if (!mat->rowvalues && (idx || v)) {
1859:     /*
1860:         allocate enough space to hold information from the longest row.
1861:     */
1862:     Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data;
1863:     PetscInt   max = 1,tmp;
1864:     for (i=0; i<matin->rmap->n; i++) {
1865:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1866:       if (max < tmp) max = tmp;
1867:     }
1868:     PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);
1869:   }

1871:   if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows");
1872:   lrow = row - rstart;

1874:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1875:   if (!v)   {pvA = 0; pvB = 0;}
1876:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1877:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1878:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1879:   nztot = nzA + nzB;

1881:   cmap = mat->garray;
1882:   if (v  || idx) {
1883:     if (nztot) {
1884:       /* Sort by increasing column numbers, assuming A and B already sorted */
1885:       PetscInt imark = -1;
1886:       if (v) {
1887:         *v = v_p = mat->rowvalues;
1888:         for (i=0; i<nzB; i++) {
1889:           if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i];
1890:           else break;
1891:         }
1892:         imark = i;
1893:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1894:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1895:       }
1896:       if (idx) {
1897:         *idx = idx_p = mat->rowindices;
1898:         if (imark > -1) {
1899:           for (i=0; i<imark; i++) {
1900:             idx_p[i] = cmap[cworkB[i]];
1901:           }
1902:         } else {
1903:           for (i=0; i<nzB; i++) {
1904:             if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]];
1905:             else break;
1906:           }
1907:           imark = i;
1908:         }
1909:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart + cworkA[i];
1910:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]];
1911:       }
1912:     } else {
1913:       if (idx) *idx = 0;
1914:       if (v)   *v   = 0;
1915:     }
1916:   }
1917:   *nz  = nztot;
1918:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1919:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1920:   return(0);
1921: }

1923: PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1924: {
1925:   Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;

1928:   if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1929:   aij->getrowactive = PETSC_FALSE;
1930:   return(0);
1931: }

1933: PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm)
1934: {
1935:   Mat_MPIAIJ     *aij  = (Mat_MPIAIJ*)mat->data;
1936:   Mat_SeqAIJ     *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data;
1938:   PetscInt       i,j,cstart = mat->cmap->rstart;
1939:   PetscReal      sum = 0.0;
1940:   MatScalar      *v;

1943:   if (aij->size == 1) {
1944:      MatNorm(aij->A,type,norm);
1945:   } else {
1946:     if (type == NORM_FROBENIUS) {
1947:       v = amat->a;
1948:       for (i=0; i<amat->nz; i++) {
1949:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1950:       }
1951:       v = bmat->a;
1952:       for (i=0; i<bmat->nz; i++) {
1953:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1954:       }
1955:       MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1956:       *norm = PetscSqrtReal(*norm);
1957:       PetscLogFlops(2*amat->nz+2*bmat->nz);
1958:     } else if (type == NORM_1) { /* max column norm */
1959:       PetscReal *tmp,*tmp2;
1960:       PetscInt  *jj,*garray = aij->garray;
1961:       PetscCalloc1(mat->cmap->N+1,&tmp);
1962:       PetscMalloc1(mat->cmap->N+1,&tmp2);
1963:       *norm = 0.0;
1964:       v     = amat->a; jj = amat->j;
1965:       for (j=0; j<amat->nz; j++) {
1966:         tmp[cstart + *jj++] += PetscAbsScalar(*v);  v++;
1967:       }
1968:       v = bmat->a; jj = bmat->j;
1969:       for (j=0; j<bmat->nz; j++) {
1970:         tmp[garray[*jj++]] += PetscAbsScalar(*v); v++;
1971:       }
1972:       MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1973:       for (j=0; j<mat->cmap->N; j++) {
1974:         if (tmp2[j] > *norm) *norm = tmp2[j];
1975:       }
1976:       PetscFree(tmp);
1977:       PetscFree(tmp2);
1978:       PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1979:     } else if (type == NORM_INFINITY) { /* max row norm */
1980:       PetscReal ntemp = 0.0;
1981:       for (j=0; j<aij->A->rmap->n; j++) {
1982:         v   = amat->a + amat->i[j];
1983:         sum = 0.0;
1984:         for (i=0; i<amat->i[j+1]-amat->i[j]; i++) {
1985:           sum += PetscAbsScalar(*v); v++;
1986:         }
1987:         v = bmat->a + bmat->i[j];
1988:         for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) {
1989:           sum += PetscAbsScalar(*v); v++;
1990:         }
1991:         if (sum > ntemp) ntemp = sum;
1992:       }
1993:       MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
1994:       PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1995:     } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm");
1996:   }
1997:   return(0);
1998: }

2000: PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout)
2001: {
2002:   Mat_MPIAIJ     *a    =(Mat_MPIAIJ*)A->data,*b;
2003:   Mat_SeqAIJ     *Aloc =(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data,*sub_B_diag;
2004:   PetscInt       M     = A->rmap->N,N=A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,*B_diag_ilen,*B_diag_i,i,ncol,A_diag_ncol;
2006:   Mat            B,A_diag,*B_diag;
2007:   MatScalar      *array;

2010:   ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n;
2011:   ai = Aloc->i; aj = Aloc->j;
2012:   bi = Bloc->i; bj = Bloc->j;
2013:   if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
2014:     PetscInt             *d_nnz,*g_nnz,*o_nnz;
2015:     PetscSFNode          *oloc;
2016:     PETSC_UNUSED PetscSF sf;

2018:     PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);
2019:     /* compute d_nnz for preallocation */
2020:     PetscMemzero(d_nnz,na*sizeof(PetscInt));
2021:     for (i=0; i<ai[ma]; i++) {
2022:       d_nnz[aj[i]]++;
2023:     }
2024:     /* compute local off-diagonal contributions */
2025:     PetscMemzero(g_nnz,nb*sizeof(PetscInt));
2026:     for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++;
2027:     /* map those to global */
2028:     PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
2029:     PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);
2030:     PetscSFSetFromOptions(sf);
2031:     PetscMemzero(o_nnz,na*sizeof(PetscInt));
2032:     PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2033:     PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2034:     PetscSFDestroy(&sf);

2036:     MatCreate(PetscObjectComm((PetscObject)A),&B);
2037:     MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
2038:     MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));
2039:     MatSetType(B,((PetscObject)A)->type_name);
2040:     MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
2041:     PetscFree4(d_nnz,o_nnz,g_nnz,oloc);
2042:   } else {
2043:     B    = *matout;
2044:     MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
2045:   }

2047:   b           = (Mat_MPIAIJ*)B->data;
2048:   A_diag      = a->A;
2049:   B_diag      = &b->A;
2050:   sub_B_diag  = (Mat_SeqAIJ*)(*B_diag)->data;
2051:   A_diag_ncol = A_diag->cmap->N;
2052:   B_diag_ilen = sub_B_diag->ilen;
2053:   B_diag_i    = sub_B_diag->i;

2055:   /* Set ilen for diagonal of B */
2056:   for (i=0; i<A_diag_ncol; i++) {
2057:     B_diag_ilen[i] = B_diag_i[i+1] - B_diag_i[i];
2058:   }

2060:   /* Transpose the diagonal part of the matrix. In contrast to the offdiagonal part, this can be done
2061:   very quickly (=without using MatSetValues), because all writes are local. */
2062:   MatTranspose(A_diag,MAT_REUSE_MATRIX,B_diag);

2064:   /* copy over the B part */
2065:   PetscCalloc1(bi[mb],&cols);
2066:   array = Bloc->a;
2067:   row   = A->rmap->rstart;
2068:   for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]];
2069:   cols_tmp = cols;
2070:   for (i=0; i<mb; i++) {
2071:     ncol = bi[i+1]-bi[i];
2072:     MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);
2073:     row++;
2074:     array += ncol; cols_tmp += ncol;
2075:   }
2076:   PetscFree(cols);

2078:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2079:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2080:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) {
2081:     *matout = B;
2082:   } else {
2083:     MatHeaderMerge(A,&B);
2084:   }
2085:   return(0);
2086: }

2088: PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr)
2089: {
2090:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
2091:   Mat            a    = aij->A,b = aij->B;
2093:   PetscInt       s1,s2,s3;

2096:   MatGetLocalSize(mat,&s2,&s3);
2097:   if (rr) {
2098:     VecGetLocalSize(rr,&s1);
2099:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
2100:     /* Overlap communication with computation. */
2101:     VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2102:   }
2103:   if (ll) {
2104:     VecGetLocalSize(ll,&s1);
2105:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
2106:     (*b->ops->diagonalscale)(b,ll,0);
2107:   }
2108:   /* scale  the diagonal block */
2109:   (*a->ops->diagonalscale)(a,ll,rr);

2111:   if (rr) {
2112:     /* Do a scatter end and then right scale the off-diagonal block */
2113:     VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2114:     (*b->ops->diagonalscale)(b,0,aij->lvec);
2115:   }
2116:   return(0);
2117: }

2119: PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A)
2120: {
2121:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2125:   MatSetUnfactored(a->A);
2126:   return(0);
2127: }

2129: PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool  *flag)
2130: {
2131:   Mat_MPIAIJ     *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data;
2132:   Mat            a,b,c,d;
2133:   PetscBool      flg;

2137:   a = matA->A; b = matA->B;
2138:   c = matB->A; d = matB->B;

2140:   MatEqual(a,c,&flg);
2141:   if (flg) {
2142:     MatEqual(b,d,&flg);
2143:   }
2144:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
2145:   return(0);
2146: }

2148: PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str)
2149: {
2151:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2152:   Mat_MPIAIJ     *b = (Mat_MPIAIJ*)B->data;

2155:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
2156:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
2157:     /* because of the column compression in the off-processor part of the matrix a->B,
2158:        the number of columns in a->B and b->B may be different, hence we cannot call
2159:        the MatCopy() directly on the two parts. If need be, we can provide a more
2160:        efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
2161:        then copying the submatrices */
2162:     MatCopy_Basic(A,B,str);
2163:   } else {
2164:     MatCopy(a->A,b->A,str);
2165:     MatCopy(a->B,b->B,str);
2166:   }
2167:   PetscObjectStateIncrease((PetscObject)B);
2168:   return(0);
2169: }

2171: PetscErrorCode MatSetUp_MPIAIJ(Mat A)
2172: {

2176:   MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
2177:   return(0);
2178: }

2180: /*
2181:    Computes the number of nonzeros per row needed for preallocation when X and Y
2182:    have different nonzero structure.
2183: */
2184: PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *xltog,const PetscInt *yi,const PetscInt *yj,const PetscInt *yltog,PetscInt *nnz)
2185: {
2186:   PetscInt       i,j,k,nzx,nzy;

2189:   /* Set the number of nonzeros in the new matrix */
2190:   for (i=0; i<m; i++) {
2191:     const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i];
2192:     nzx = xi[i+1] - xi[i];
2193:     nzy = yi[i+1] - yi[i];
2194:     nnz[i] = 0;
2195:     for (j=0,k=0; j<nzx; j++) {                   /* Point in X */
2196:       for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */
2197:       if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++;             /* Skip duplicate */
2198:       nnz[i]++;
2199:     }
2200:     for (; k<nzy; k++) nnz[i]++;
2201:   }
2202:   return(0);
2203: }

2205: /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */
2206: static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
2207: {
2209:   PetscInt       m = Y->rmap->N;
2210:   Mat_SeqAIJ     *x = (Mat_SeqAIJ*)X->data;
2211:   Mat_SeqAIJ     *y = (Mat_SeqAIJ*)Y->data;

2214:   MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
2215:   return(0);
2216: }

2218: PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2219: {
2221:   Mat_MPIAIJ     *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data;
2222:   PetscBLASInt   bnz,one=1;
2223:   Mat_SeqAIJ     *x,*y;

2226:   if (str == SAME_NONZERO_PATTERN) {
2227:     PetscScalar alpha = a;
2228:     x    = (Mat_SeqAIJ*)xx->A->data;
2229:     PetscBLASIntCast(x->nz,&bnz);
2230:     y    = (Mat_SeqAIJ*)yy->A->data;
2231:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2232:     x    = (Mat_SeqAIJ*)xx->B->data;
2233:     y    = (Mat_SeqAIJ*)yy->B->data;
2234:     PetscBLASIntCast(x->nz,&bnz);
2235:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2236:     PetscObjectStateIncrease((PetscObject)Y);
2237:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2238:     MatAXPY_Basic(Y,a,X,str);
2239:   } else {
2240:     Mat      B;
2241:     PetscInt *nnz_d,*nnz_o;
2242:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
2243:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
2244:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
2245:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2246:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2247:     MatSetBlockSizesFromMats(B,Y,Y);
2248:     MatSetType(B,MATMPIAIJ);
2249:     MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);
2250:     MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
2251:     MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);
2252:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2253:     MatHeaderReplace(Y,&B);
2254:     PetscFree(nnz_d);
2255:     PetscFree(nnz_o);
2256:   }
2257:   return(0);
2258: }

2260: extern PetscErrorCode  MatConjugate_SeqAIJ(Mat);

2262: PetscErrorCode  MatConjugate_MPIAIJ(Mat mat)
2263: {
2264: #if defined(PETSC_USE_COMPLEX)
2266:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2269:   MatConjugate_SeqAIJ(aij->A);
2270:   MatConjugate_SeqAIJ(aij->B);
2271: #else
2273: #endif
2274:   return(0);
2275: }

2277: PetscErrorCode MatRealPart_MPIAIJ(Mat A)
2278: {
2279:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2283:   MatRealPart(a->A);
2284:   MatRealPart(a->B);
2285:   return(0);
2286: }

2288: PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A)
2289: {
2290:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2294:   MatImaginaryPart(a->A);
2295:   MatImaginaryPart(a->B);
2296:   return(0);
2297: }

2299: PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2300: {
2301:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2303:   PetscInt       i,*idxb = 0;
2304:   PetscScalar    *va,*vb;
2305:   Vec            vtmp;

2308:   MatGetRowMaxAbs(a->A,v,idx);
2309:   VecGetArray(v,&va);
2310:   if (idx) {
2311:     for (i=0; i<A->rmap->n; i++) {
2312:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2313:     }
2314:   }

2316:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2317:   if (idx) {
2318:     PetscMalloc1(A->rmap->n,&idxb);
2319:   }
2320:   MatGetRowMaxAbs(a->B,vtmp,idxb);
2321:   VecGetArray(vtmp,&vb);

2323:   for (i=0; i<A->rmap->n; i++) {
2324:     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
2325:       va[i] = vb[i];
2326:       if (idx) idx[i] = a->garray[idxb[i]];
2327:     }
2328:   }

2330:   VecRestoreArray(v,&va);
2331:   VecRestoreArray(vtmp,&vb);
2332:   PetscFree(idxb);
2333:   VecDestroy(&vtmp);
2334:   return(0);
2335: }

2337: PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2338: {
2339:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2341:   PetscInt       i,*idxb = 0;
2342:   PetscScalar    *va,*vb;
2343:   Vec            vtmp;

2346:   MatGetRowMinAbs(a->A,v,idx);
2347:   VecGetArray(v,&va);
2348:   if (idx) {
2349:     for (i=0; i<A->cmap->n; i++) {
2350:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2351:     }
2352:   }

2354:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2355:   if (idx) {
2356:     PetscMalloc1(A->rmap->n,&idxb);
2357:   }
2358:   MatGetRowMinAbs(a->B,vtmp,idxb);
2359:   VecGetArray(vtmp,&vb);

2361:   for (i=0; i<A->rmap->n; i++) {
2362:     if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) {
2363:       va[i] = vb[i];
2364:       if (idx) idx[i] = a->garray[idxb[i]];
2365:     }
2366:   }

2368:   VecRestoreArray(v,&va);
2369:   VecRestoreArray(vtmp,&vb);
2370:   PetscFree(idxb);
2371:   VecDestroy(&vtmp);
2372:   return(0);
2373: }

2375: PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2376: {
2377:   Mat_MPIAIJ     *mat   = (Mat_MPIAIJ*) A->data;
2378:   PetscInt       n      = A->rmap->n;
2379:   PetscInt       cstart = A->cmap->rstart;
2380:   PetscInt       *cmap  = mat->garray;
2381:   PetscInt       *diagIdx, *offdiagIdx;
2382:   Vec            diagV, offdiagV;
2383:   PetscScalar    *a, *diagA, *offdiagA;
2384:   PetscInt       r;

2388:   PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2389:   VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);
2390:   VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);
2391:   MatGetRowMin(mat->A, diagV,    diagIdx);
2392:   MatGetRowMin(mat->B, offdiagV, offdiagIdx);
2393:   VecGetArray(v,        &a);
2394:   VecGetArray(diagV,    &diagA);
2395:   VecGetArray(offdiagV, &offdiagA);
2396:   for (r = 0; r < n; ++r) {
2397:     if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) {
2398:       a[r]   = diagA[r];
2399:       idx[r] = cstart + diagIdx[r];
2400:     } else {
2401:       a[r]   = offdiagA[r];
2402:       idx[r] = cmap[offdiagIdx[r]];
2403:     }
2404:   }
2405:   VecRestoreArray(v,        &a);
2406:   VecRestoreArray(diagV,    &diagA);
2407:   VecRestoreArray(offdiagV, &offdiagA);
2408:   VecDestroy(&diagV);
2409:   VecDestroy(&offdiagV);
2410:   PetscFree2(diagIdx, offdiagIdx);
2411:   return(0);
2412: }

2414: PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2415: {
2416:   Mat_MPIAIJ     *mat   = (Mat_MPIAIJ*) A->data;
2417:   PetscInt       n      = A->rmap->n;
2418:   PetscInt       cstart = A->cmap->rstart;
2419:   PetscInt       *cmap  = mat->garray;
2420:   PetscInt       *diagIdx, *offdiagIdx;
2421:   Vec            diagV, offdiagV;
2422:   PetscScalar    *a, *diagA, *offdiagA;
2423:   PetscInt       r;

2427:   PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2428:   VecCreateSeq(PETSC_COMM_SELF, n, &diagV);
2429:   VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);
2430:   MatGetRowMax(mat->A, diagV,    diagIdx);
2431:   MatGetRowMax(mat->B, offdiagV, offdiagIdx);
2432:   VecGetArray(v,        &a);
2433:   VecGetArray(diagV,    &diagA);
2434:   VecGetArray(offdiagV, &offdiagA);
2435:   for (r = 0; r < n; ++r) {
2436:     if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) {
2437:       a[r]   = diagA[r];
2438:       idx[r] = cstart + diagIdx[r];
2439:     } else {
2440:       a[r]   = offdiagA[r];
2441:       idx[r] = cmap[offdiagIdx[r]];
2442:     }
2443:   }
2444:   VecRestoreArray(v,        &a);
2445:   VecRestoreArray(diagV,    &diagA);
2446:   VecRestoreArray(offdiagV, &offdiagA);
2447:   VecDestroy(&diagV);
2448:   VecDestroy(&offdiagV);
2449:   PetscFree2(diagIdx, offdiagIdx);
2450:   return(0);
2451: }

2453: PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat)
2454: {
2456:   Mat            *dummy;

2459:   MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);
2460:   *newmat = *dummy;
2461:   PetscFree(dummy);
2462:   return(0);
2463: }

2465: PetscErrorCode  MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values)
2466: {
2467:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*) A->data;

2471:   MatInvertBlockDiagonal(a->A,values);
2472:   A->factorerrortype = a->A->factorerrortype;
2473:   return(0);
2474: }

2476: static PetscErrorCode  MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx)
2477: {
2479:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)x->data;

2482:   if (!x->assembled && !x->preallocated) SETERRQ(PetscObjectComm((PetscObject)x), PETSC_ERR_ARG_WRONGSTATE, "MatSetRandom on an unassembled and unpreallocated MATMPIAIJ is not allowed");
2483:   MatSetRandom(aij->A,rctx);
2484:   if (x->assembled) {
2485:     MatSetRandom(aij->B,rctx);
2486:   } else {
2487:     MatSetRandomSkipColumnRange_SeqAIJ_Private(aij->B,x->cmap->rstart,x->cmap->rend,rctx);
2488:   }
2489:   MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
2490:   MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
2491:   return(0);
2492: }

2494: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc)
2495: {
2497:   if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable;
2498:   else A->ops->increaseoverlap    = MatIncreaseOverlap_MPIAIJ;
2499:   return(0);
2500: }

2502: /*@
2503:    MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap

2505:    Collective on Mat

2507:    Input Parameters:
2508: +    A - the matrix
2509: -    sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm)

2511:  Level: advanced

2513: @*/
2514: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc)
2515: {
2516:   PetscErrorCode       ierr;

2519:   PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));
2520:   return(0);
2521: }

2523: PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A)
2524: {
2525:   PetscErrorCode       ierr;
2526:   PetscBool            sc = PETSC_FALSE,flg;

2529:   PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");
2530:   if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE;
2531:   PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);
2532:   if (flg) {
2533:     MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);
2534:   }
2535:   PetscOptionsTail();
2536:   return(0);
2537: }

2539: PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a)
2540: {
2542:   Mat_MPIAIJ     *maij = (Mat_MPIAIJ*)Y->data;
2543:   Mat_SeqAIJ     *aij = (Mat_SeqAIJ*)maij->A->data;

2546:   if (!Y->preallocated) {
2547:     MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);
2548:   } else if (!aij->nz) {
2549:     PetscInt nonew = aij->nonew;
2550:     MatSeqAIJSetPreallocation(maij->A,1,NULL);
2551:     aij->nonew = nonew;
2552:   }
2553:   MatShift_Basic(Y,a);
2554:   return(0);
2555: }

2557: PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool  *missing,PetscInt *d)
2558: {
2559:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2563:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
2564:   MatMissingDiagonal(a->A,missing,d);
2565:   if (d) {
2566:     PetscInt rstart;
2567:     MatGetOwnershipRange(A,&rstart,NULL);
2568:     *d += rstart;

2570:   }
2571:   return(0);
2572: }

2574: PetscErrorCode MatInvertVariableBlockDiagonal_MPIAIJ(Mat A,PetscInt nblocks,const PetscInt *bsizes,PetscScalar *diag)
2575: {
2576:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2580:   MatInvertVariableBlockDiagonal(a->A,nblocks,bsizes,diag);
2581:   return(0);
2582: }

2584: /* -------------------------------------------------------------------*/
2585: static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ,
2586:                                        MatGetRow_MPIAIJ,
2587:                                        MatRestoreRow_MPIAIJ,
2588:                                        MatMult_MPIAIJ,
2589:                                 /* 4*/ MatMultAdd_MPIAIJ,
2590:                                        MatMultTranspose_MPIAIJ,
2591:                                        MatMultTransposeAdd_MPIAIJ,
2592:                                        0,
2593:                                        0,
2594:                                        0,
2595:                                 /*10*/ 0,
2596:                                        0,
2597:                                        0,
2598:                                        MatSOR_MPIAIJ,
2599:                                        MatTranspose_MPIAIJ,
2600:                                 /*15*/ MatGetInfo_MPIAIJ,
2601:                                        MatEqual_MPIAIJ,
2602:                                        MatGetDiagonal_MPIAIJ,
2603:                                        MatDiagonalScale_MPIAIJ,
2604:                                        MatNorm_MPIAIJ,
2605:                                 /*20*/ MatAssemblyBegin_MPIAIJ,
2606:                                        MatAssemblyEnd_MPIAIJ,
2607:                                        MatSetOption_MPIAIJ,
2608:                                        MatZeroEntries_MPIAIJ,
2609:                                 /*24*/ MatZeroRows_MPIAIJ,
2610:                                        0,
2611:                                        0,
2612:                                        0,
2613:                                        0,
2614:                                 /*29*/ MatSetUp_MPIAIJ,
2615:                                        0,
2616:                                        0,
2617:                                        MatGetDiagonalBlock_MPIAIJ,
2618:                                        0,
2619:                                 /*34*/ MatDuplicate_MPIAIJ,
2620:                                        0,
2621:                                        0,
2622:                                        0,
2623:                                        0,
2624:                                 /*39*/ MatAXPY_MPIAIJ,
2625:                                        MatCreateSubMatrices_MPIAIJ,
2626:                                        MatIncreaseOverlap_MPIAIJ,
2627:                                        MatGetValues_MPIAIJ,
2628:                                        MatCopy_MPIAIJ,
2629:                                 /*44*/ MatGetRowMax_MPIAIJ,
2630:                                        MatScale_MPIAIJ,
2631:                                        MatShift_MPIAIJ,
2632:                                        MatDiagonalSet_MPIAIJ,
2633:                                        MatZeroRowsColumns_MPIAIJ,
2634:                                 /*49*/ MatSetRandom_MPIAIJ,
2635:                                        0,
2636:                                        0,
2637:                                        0,
2638:                                        0,
2639:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
2640:                                        0,
2641:                                        MatSetUnfactored_MPIAIJ,
2642:                                        MatPermute_MPIAIJ,
2643:                                        0,
2644:                                 /*59*/ MatCreateSubMatrix_MPIAIJ,
2645:                                        MatDestroy_MPIAIJ,
2646:                                        MatView_MPIAIJ,
2647:                                        0,
2648:                                        MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ,
2649:                                 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ,
2650:                                        MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ,
2651:                                        0,
2652:                                        0,
2653:                                        0,
2654:                                 /*69*/ MatGetRowMaxAbs_MPIAIJ,
2655:                                        MatGetRowMinAbs_MPIAIJ,
2656:                                        0,
2657:                                        0,
2658:                                        0,
2659:                                        0,
2660:                                 /*75*/ MatFDColoringApply_AIJ,
2661:                                        MatSetFromOptions_MPIAIJ,
2662:                                        0,
2663:                                        0,
2664:                                        MatFindZeroDiagonals_MPIAIJ,
2665:                                 /*80*/ 0,
2666:                                        0,
2667:                                        0,
2668:                                 /*83*/ MatLoad_MPIAIJ,
2669:                                        MatIsSymmetric_MPIAIJ,
2670:                                        0,
2671:                                        0,
2672:                                        0,
2673:                                        0,
2674:                                 /*89*/ MatMatMult_MPIAIJ_MPIAIJ,
2675:                                        MatMatMultSymbolic_MPIAIJ_MPIAIJ,
2676:                                        MatMatMultNumeric_MPIAIJ_MPIAIJ,
2677:                                        MatPtAP_MPIAIJ_MPIAIJ,
2678:                                        MatPtAPSymbolic_MPIAIJ_MPIAIJ,
2679:                                 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ,
2680:                                        0,
2681:                                        0,
2682:                                        0,
2683:                                        0,
2684:                                 /*99*/ 0,
2685:                                        0,
2686:                                        0,
2687:                                        MatConjugate_MPIAIJ,
2688:                                        0,
2689:                                 /*104*/MatSetValuesRow_MPIAIJ,
2690:                                        MatRealPart_MPIAIJ,
2691:                                        MatImaginaryPart_MPIAIJ,
2692:                                        0,
2693:                                        0,
2694:                                 /*109*/0,
2695:                                        0,
2696:                                        MatGetRowMin_MPIAIJ,
2697:                                        0,
2698:                                        MatMissingDiagonal_MPIAIJ,
2699:                                 /*114*/MatGetSeqNonzeroStructure_MPIAIJ,
2700:                                        0,
2701:                                        MatGetGhosts_MPIAIJ,
2702:                                        0,
2703:                                        0,
2704:                                 /*119*/0,
2705:                                        0,
2706:                                        0,
2707:                                        0,
2708:                                        MatGetMultiProcBlock_MPIAIJ,
2709:                                 /*124*/MatFindNonzeroRows_MPIAIJ,
2710:                                        MatGetColumnNorms_MPIAIJ,
2711:                                        MatInvertBlockDiagonal_MPIAIJ,
2712:                                        MatInvertVariableBlockDiagonal_MPIAIJ,
2713:                                        MatCreateSubMatricesMPI_MPIAIJ,
2714:                                 /*129*/0,
2715:                                        MatTransposeMatMult_MPIAIJ_MPIAIJ,
2716:                                        MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ,
2717:                                        MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ,
2718:                                        0,
2719:                                 /*134*/0,
2720:                                        0,
2721:                                        MatRARt_MPIAIJ_MPIAIJ,
2722:                                        0,
2723:                                        0,
2724:                                 /*139*/MatSetBlockSizes_MPIAIJ,
2725:                                        0,
2726:                                        0,
2727:                                        MatFDColoringSetUp_MPIXAIJ,
2728:                                        MatFindOffBlockDiagonalEntries_MPIAIJ,
2729:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ
2730: };

2732: /* ----------------------------------------------------------------------------------------*/

2734: PetscErrorCode  MatStoreValues_MPIAIJ(Mat mat)
2735: {
2736:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2740:   MatStoreValues(aij->A);
2741:   MatStoreValues(aij->B);
2742:   return(0);
2743: }

2745: PetscErrorCode  MatRetrieveValues_MPIAIJ(Mat mat)
2746: {
2747:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2751:   MatRetrieveValues(aij->A);
2752:   MatRetrieveValues(aij->B);
2753:   return(0);
2754: }

2756: PetscErrorCode  MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2757: {
2758:   Mat_MPIAIJ     *b;
2760:   PetscMPIInt    size;

2763:   PetscLayoutSetUp(B->rmap);
2764:   PetscLayoutSetUp(B->cmap);
2765:   b = (Mat_MPIAIJ*)B->data;

2767: #if defined(PETSC_USE_CTABLE)
2768:   PetscTableDestroy(&b->colmap);
2769: #else
2770:   PetscFree(b->colmap);
2771: #endif
2772:   PetscFree(b->garray);
2773:   VecDestroy(&b->lvec);
2774:   VecScatterDestroy(&b->Mvctx);

2776:   /* Because the B will have been resized we simply destroy it and create a new one each time */
2777:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
2778:   MatDestroy(&b->B);
2779:   MatCreate(PETSC_COMM_SELF,&b->B);
2780:   MatSetSizes(b->B,B->rmap->n,size > 1 ? B->cmap->N : 0,B->rmap->n,size > 1 ? B->cmap->N : 0);
2781:   MatSetBlockSizesFromMats(b->B,B,B);
2782:   MatSetType(b->B,MATSEQAIJ);
2783:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

2785:   if (!B->preallocated) {
2786:     MatCreate(PETSC_COMM_SELF,&b->A);
2787:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2788:     MatSetBlockSizesFromMats(b->A,B,B);
2789:     MatSetType(b->A,MATSEQAIJ);
2790:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2791:   }

2793:   MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);
2794:   MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);
2795:   B->preallocated  = PETSC_TRUE;
2796:   B->was_assembled = PETSC_FALSE;
2797:   B->assembled     = PETSC_FALSE;
2798:   return(0);
2799: }

2801: PetscErrorCode MatResetPreallocation_MPIAIJ(Mat B)
2802: {
2803:   Mat_MPIAIJ     *b;

2808:   PetscLayoutSetUp(B->rmap);
2809:   PetscLayoutSetUp(B->cmap);
2810:   b = (Mat_MPIAIJ*)B->data;

2812: #if defined(PETSC_USE_CTABLE)
2813:   PetscTableDestroy(&b->colmap);
2814: #else
2815:   PetscFree(b->colmap);
2816: #endif
2817:   PetscFree(b->garray);
2818:   VecDestroy(&b->lvec);
2819:   VecScatterDestroy(&b->Mvctx);

2821:   MatResetPreallocation(b->A);
2822:   MatResetPreallocation(b->B);
2823:   B->preallocated  = PETSC_TRUE;
2824:   B->was_assembled = PETSC_FALSE;
2825:   B->assembled = PETSC_FALSE;
2826:   return(0);
2827: }

2829: PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2830: {
2831:   Mat            mat;
2832:   Mat_MPIAIJ     *a,*oldmat = (Mat_MPIAIJ*)matin->data;

2836:   *newmat = 0;
2837:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2838:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2839:   MatSetBlockSizesFromMats(mat,matin,matin);
2840:   MatSetType(mat,((PetscObject)matin)->type_name);
2841:   a       = (Mat_MPIAIJ*)mat->data;

2843:   mat->factortype   = matin->factortype;
2844:   mat->assembled    = PETSC_TRUE;
2845:   mat->insertmode   = NOT_SET_VALUES;
2846:   mat->preallocated = PETSC_TRUE;

2848:   a->size         = oldmat->size;
2849:   a->rank         = oldmat->rank;
2850:   a->donotstash   = oldmat->donotstash;
2851:   a->roworiented  = oldmat->roworiented;
2852:   a->rowindices   = 0;
2853:   a->rowvalues    = 0;
2854:   a->getrowactive = PETSC_FALSE;

2856:   PetscLayoutReference(matin->rmap,&mat->rmap);
2857:   PetscLayoutReference(matin->cmap,&mat->cmap);

2859:   if (oldmat->colmap) {
2860: #if defined(PETSC_USE_CTABLE)
2861:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2862: #else
2863:     PetscMalloc1(mat->cmap->N,&a->colmap);
2864:     PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
2865:     PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));
2866: #endif
2867:   } else a->colmap = 0;
2868:   if (oldmat->garray) {
2869:     PetscInt len;
2870:     len  = oldmat->B->cmap->n;
2871:     PetscMalloc1(len+1,&a->garray);
2872:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2873:     if (len) { PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt)); }
2874:   } else a->garray = 0;

2876:   VecDuplicate(oldmat->lvec,&a->lvec);
2877:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2878:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2879:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

2881:   if (oldmat->Mvctx_mpi1) {
2882:     VecScatterCopy(oldmat->Mvctx_mpi1,&a->Mvctx_mpi1);
2883:     PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx_mpi1);
2884:   }

2886:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2887:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2888:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2889:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2890:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2891:   *newmat = mat;
2892:   return(0);
2893: }

2895: PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer)
2896: {
2897:   PetscBool      isbinary, ishdf5;

2903:   /* force binary viewer to load .info file if it has not yet done so */
2904:   PetscViewerSetUp(viewer);
2905:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
2906:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERHDF5,  &ishdf5);
2907:   if (isbinary) {
2908:     MatLoad_MPIAIJ_Binary(newMat,viewer);
2909:   } else if (ishdf5) {
2910: #if defined(PETSC_HAVE_HDF5)
2911:     MatLoad_AIJ_HDF5(newMat,viewer);
2912: #else
2913:     SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"HDF5 not supported in this build.\nPlease reconfigure using --download-hdf5");
2914: #endif
2915:   } else {
2916:     SETERRQ2(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newMat)->type_name);
2917:   }
2918:   return(0);
2919: }

2921: PetscErrorCode MatLoad_MPIAIJ_Binary(Mat newMat, PetscViewer viewer)
2922: {
2923:   PetscScalar    *vals,*svals;
2924:   MPI_Comm       comm;
2926:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
2927:   PetscInt       i,nz,j,rstart,rend,mmax,maxnz = 0;
2928:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols;
2929:   PetscInt       *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols;
2930:   PetscInt       cend,cstart,n,*rowners;
2931:   int            fd;
2932:   PetscInt       bs = newMat->rmap->bs;

2935:   PetscObjectGetComm((PetscObject)viewer,&comm);
2936:   MPI_Comm_size(comm,&size);
2937:   MPI_Comm_rank(comm,&rank);
2938:   PetscViewerBinaryGetDescriptor(viewer,&fd);
2939:   if (!rank) {
2940:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
2941:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2942:     if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MATMPIAIJ");
2943:   }

2945:   PetscOptionsBegin(comm,NULL,"Options for loading MATMPIAIJ matrix","Mat");
2946:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2947:   PetscOptionsEnd();
2948:   if (bs < 0) bs = 1;

2950:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2951:   M    = header[1]; N = header[2];

2953:   /* If global sizes are set, check if they are consistent with that given in the file */
2954:   if (newMat->rmap->N >= 0 && newMat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newMat->rmap->N,M);
2955:   if (newMat->cmap->N >=0 && newMat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newMat->cmap->N,N);

2957:   /* determine ownership of all (block) rows */
2958:   if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs);
2959:   if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank));    /* PETSC_DECIDE */
2960:   else m = newMat->rmap->n; /* Set by user */

2962:   PetscMalloc1(size+1,&rowners);
2963:   MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

2965:   /* First process needs enough room for process with most rows */
2966:   if (!rank) {
2967:     mmax = rowners[1];
2968:     for (i=2; i<=size; i++) {
2969:       mmax = PetscMax(mmax, rowners[i]);
2970:     }
2971:   } else mmax = -1;             /* unused, but compilers complain */

2973:   rowners[0] = 0;
2974:   for (i=2; i<=size; i++) {
2975:     rowners[i] += rowners[i-1];
2976:   }
2977:   rstart = rowners[rank];
2978:   rend   = rowners[rank+1];

2980:   /* distribute row lengths to all processors */
2981:   PetscMalloc2(m,&ourlens,m,&offlens);
2982:   if (!rank) {
2983:     PetscBinaryRead(fd,ourlens,m,PETSC_INT);
2984:     PetscMalloc1(mmax,&rowlengths);
2985:     PetscCalloc1(size,&procsnz);
2986:     for (j=0; j<m; j++) {
2987:       procsnz[0] += ourlens[j];
2988:     }
2989:     for (i=1; i<size; i++) {
2990:       PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);
2991:       /* calculate the number of nonzeros on each processor */
2992:       for (j=0; j<rowners[i+1]-rowners[i]; j++) {
2993:         procsnz[i] += rowlengths[j];
2994:       }
2995:       MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
2996:     }
2997:     PetscFree(rowlengths);
2998:   } else {
2999:     MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);
3000:   }

3002:   if (!rank) {
3003:     /* determine max buffer needed and allocate it */
3004:     maxnz = 0;
3005:     for (i=0; i<size; i++) {
3006:       maxnz = PetscMax(maxnz,procsnz[i]);
3007:     }
3008:     PetscMalloc1(maxnz,&cols);

3010:     /* read in my part of the matrix column indices  */
3011:     nz   = procsnz[0];
3012:     PetscMalloc1(nz,&mycols);
3013:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);

3015:     /* read in every one elses and ship off */
3016:     for (i=1; i<size; i++) {
3017:       nz   = procsnz[i];
3018:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
3019:       MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);
3020:     }
3021:     PetscFree(cols);
3022:   } else {
3023:     /* determine buffer space needed for message */
3024:     nz = 0;
3025:     for (i=0; i<m; i++) {
3026:       nz += ourlens[i];
3027:     }
3028:     PetscMalloc1(nz,&mycols);

3030:     /* receive message of column indices*/
3031:     MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);
3032:   }

3034:   /* determine column ownership if matrix is not square */
3035:   if (N != M) {
3036:     if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank);
3037:     else n = newMat->cmap->n;
3038:     MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);
3039:     cstart = cend - n;
3040:   } else {
3041:     cstart = rstart;
3042:     cend   = rend;
3043:     n      = cend - cstart;
3044:   }

3046:   /* loop over local rows, determining number of off diagonal entries */
3047:   PetscMemzero(offlens,m*sizeof(PetscInt));
3048:   jj   = 0;
3049:   for (i=0; i<m; i++) {
3050:     for (j=0; j<ourlens[i]; j++) {
3051:       if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++;
3052:       jj++;
3053:     }
3054:   }

3056:   for (i=0; i<m; i++) {
3057:     ourlens[i] -= offlens[i];
3058:   }
3059:   MatSetSizes(newMat,m,n,M,N);

3061:   if (bs > 1) {MatSetBlockSize(newMat,bs);}

3063:   MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);

3065:   for (i=0; i<m; i++) {
3066:     ourlens[i] += offlens[i];
3067:   }

3069:   if (!rank) {
3070:     PetscMalloc1(maxnz+1,&vals);

3072:     /* read in my part of the matrix numerical values  */
3073:     nz   = procsnz[0];
3074:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);

3076:     /* insert into matrix */
3077:     jj      = rstart;
3078:     smycols = mycols;
3079:     svals   = vals;
3080:     for (i=0; i<m; i++) {
3081:       MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3082:       smycols += ourlens[i];
3083:       svals   += ourlens[i];
3084:       jj++;
3085:     }

3087:     /* read in other processors and ship out */
3088:     for (i=1; i<size; i++) {
3089:       nz   = procsnz[i];
3090:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3091:       MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);
3092:     }
3093:     PetscFree(procsnz);
3094:   } else {
3095:     /* receive numeric values */
3096:     PetscMalloc1(nz+1,&vals);

3098:     /* receive message of values*/
3099:     MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);

3101:     /* insert into matrix */
3102:     jj      = rstart;
3103:     smycols = mycols;
3104:     svals   = vals;
3105:     for (i=0; i<m; i++) {
3106:       MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3107:       smycols += ourlens[i];
3108:       svals   += ourlens[i];
3109:       jj++;
3110:     }
3111:   }
3112:   PetscFree2(ourlens,offlens);
3113:   PetscFree(vals);
3114:   PetscFree(mycols);
3115:   PetscFree(rowners);
3116:   MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);
3117:   MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);
3118:   return(0);
3119: }

3121: /* Not scalable because of ISAllGather() unless getting all columns. */
3122: PetscErrorCode ISGetSeqIS_Private(Mat mat,IS iscol,IS *isseq)
3123: {
3125:   IS             iscol_local;
3126:   PetscBool      isstride;
3127:   PetscMPIInt    lisstride=0,gisstride;

3130:   /* check if we are grabbing all columns*/
3131:   PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);

3133:   if (isstride) {
3134:     PetscInt  start,len,mstart,mlen;
3135:     ISStrideGetInfo(iscol,&start,NULL);
3136:     ISGetLocalSize(iscol,&len);
3137:     MatGetOwnershipRangeColumn(mat,&mstart,&mlen);
3138:     if (mstart == start && mlen-mstart == len) lisstride = 1;
3139:   }

3141:   MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));
3142:   if (gisstride) {
3143:     PetscInt N;
3144:     MatGetSize(mat,NULL,&N);
3145:     ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);
3146:     ISSetIdentity(iscol_local);
3147:     PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");
3148:   } else {
3149:     PetscInt cbs;
3150:     ISGetBlockSize(iscol,&cbs);
3151:     ISAllGather(iscol,&iscol_local);
3152:     ISSetBlockSize(iscol_local,cbs);
3153:   }

3155:   *isseq = iscol_local;
3156:   return(0);
3157: }

3159: /*
3160:  Used by MatCreateSubMatrix_MPIAIJ_SameRowColDist() to avoid ISAllGather() and global size of iscol_local
3161:  (see MatCreateSubMatrix_MPIAIJ_nonscalable)

3163:  Input Parameters:
3164:    mat - matrix
3165:    isrow - parallel row index set; its local indices are a subset of local columns of mat,
3166:            i.e., mat->rstart <= isrow[i] < mat->rend
3167:    iscol - parallel column index set; its local indices are a subset of local columns of mat,
3168:            i.e., mat->cstart <= iscol[i] < mat->cend
3169:  Output Parameter:
3170:    isrow_d,iscol_d - sequential row and column index sets for retrieving mat->A
3171:    iscol_o - sequential column index set for retrieving mat->B
3172:    garray - column map; garray[i] indicates global location of iscol_o[i] in iscol
3173:  */
3174: PetscErrorCode ISGetSeqIS_SameColDist_Private(Mat mat,IS isrow,IS iscol,IS *isrow_d,IS *iscol_d,IS *iscol_o,const PetscInt *garray[])
3175: {
3177:   Vec            x,cmap;
3178:   const PetscInt *is_idx;
3179:   PetscScalar    *xarray,*cmaparray;
3180:   PetscInt       ncols,isstart,*idx,m,rstart,*cmap1,count;
3181:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)mat->data;
3182:   Mat            B=a->B;
3183:   Vec            lvec=a->lvec,lcmap;
3184:   PetscInt       i,cstart,cend,Bn=B->cmap->N;
3185:   MPI_Comm       comm;
3186:   VecScatter     Mvctx=a->Mvctx;

3189:   PetscObjectGetComm((PetscObject)mat,&comm);
3190:   ISGetLocalSize(iscol,&ncols);

3192:   /* (1) iscol is a sub-column vector of mat, pad it with '-1.' to form a full vector x */
3193:   MatCreateVecs(mat,&x,NULL);
3194:   VecSet(x,-1.0);
3195:   VecDuplicate(x,&cmap);
3196:   VecSet(cmap,-1.0);

3198:   /* Get start indices */
3199:   MPI_Scan(&ncols,&isstart,1,MPIU_INT,MPI_SUM,comm);
3200:   isstart -= ncols;
3201:   MatGetOwnershipRangeColumn(mat,&cstart,&cend);

3203:   ISGetIndices(iscol,&is_idx);
3204:   VecGetArray(x,&xarray);
3205:   VecGetArray(cmap,&cmaparray);
3206:   PetscMalloc1(ncols,&idx);
3207:   for (i=0; i<ncols; i++) {
3208:     xarray[is_idx[i]-cstart]    = (PetscScalar)is_idx[i];
3209:     cmaparray[is_idx[i]-cstart] = i + isstart;      /* global index of iscol[i] */
3210:     idx[i]                      = is_idx[i]-cstart; /* local index of iscol[i]  */
3211:   }
3212:   VecRestoreArray(x,&xarray);
3213:   VecRestoreArray(cmap,&cmaparray);
3214:   ISRestoreIndices(iscol,&is_idx);

3216:   /* Get iscol_d */
3217:   ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,iscol_d);
3218:   ISGetBlockSize(iscol,&i);
3219:   ISSetBlockSize(*iscol_d,i);

3221:   /* Get isrow_d */
3222:   ISGetLocalSize(isrow,&m);
3223:   rstart = mat->rmap->rstart;
3224:   PetscMalloc1(m,&idx);
3225:   ISGetIndices(isrow,&is_idx);
3226:   for (i=0; i<m; i++) idx[i] = is_idx[i]-rstart;
3227:   ISRestoreIndices(isrow,&is_idx);

3229:   ISCreateGeneral(PETSC_COMM_SELF,m,idx,PETSC_OWN_POINTER,isrow_d);
3230:   ISGetBlockSize(isrow,&i);
3231:   ISSetBlockSize(*isrow_d,i);

3233:   /* (2) Scatter x and cmap using aij->Mvctx to get their off-process portions (see MatMult_MPIAIJ) */
3234:   VecScatterBegin(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);
3235:   VecScatterEnd(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);

3237:   VecDuplicate(lvec,&lcmap);

3239:   VecScatterBegin(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);
3240:   VecScatterEnd(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);

3242:   /* (3) create sequential iscol_o (a subset of iscol) and isgarray */
3243:   /* off-process column indices */
3244:   count = 0;
3245:   PetscMalloc1(Bn,&idx);
3246:   PetscMalloc1(Bn,&cmap1);

3248:   VecGetArray(lvec,&xarray);
3249:   VecGetArray(lcmap,&cmaparray);
3250:   for (i=0; i<Bn; i++) {
3251:     if (PetscRealPart(xarray[i]) > -1.0) {
3252:       idx[count]     = i;                   /* local column index in off-diagonal part B */
3253:       cmap1[count] = (PetscInt)PetscRealPart(cmaparray[i]);  /* column index in submat */
3254:       count++;
3255:     }
3256:   }
3257:   VecRestoreArray(lvec,&xarray);
3258:   VecRestoreArray(lcmap,&cmaparray);

3260:   ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,iscol_o);
3261:   /* cannot ensure iscol_o has same blocksize as iscol! */

3263:   PetscFree(idx);
3264:   *garray = cmap1;

3266:   VecDestroy(&x);
3267:   VecDestroy(&cmap);
3268:   VecDestroy(&lcmap);
3269:   return(0);
3270: }

3272: /* isrow and iscol have same processor distribution as mat, output *submat is a submatrix of local mat */
3273: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *submat)
3274: {
3276:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)mat->data,*asub;
3277:   Mat            M = NULL;
3278:   MPI_Comm       comm;
3279:   IS             iscol_d,isrow_d,iscol_o;
3280:   Mat            Asub = NULL,Bsub = NULL;
3281:   PetscInt       n;

3284:   PetscObjectGetComm((PetscObject)mat,&comm);

3286:   if (call == MAT_REUSE_MATRIX) {
3287:     /* Retrieve isrow_d, iscol_d and iscol_o from submat */
3288:     PetscObjectQuery((PetscObject)*submat,"isrow_d",(PetscObject*)&isrow_d);
3289:     if (!isrow_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"isrow_d passed in was not used before, cannot reuse");

3291:     PetscObjectQuery((PetscObject)*submat,"iscol_d",(PetscObject*)&iscol_d);
3292:     if (!iscol_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_d passed in was not used before, cannot reuse");

3294:     PetscObjectQuery((PetscObject)*submat,"iscol_o",(PetscObject*)&iscol_o);
3295:     if (!iscol_o) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_o passed in was not used before, cannot reuse");

3297:     /* Update diagonal and off-diagonal portions of submat */
3298:     asub = (Mat_MPIAIJ*)(*submat)->data;
3299:     MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->A);
3300:     ISGetLocalSize(iscol_o,&n);
3301:     if (n) {
3302:       MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->B);
3303:     }
3304:     MatAssemblyBegin(*submat,MAT_FINAL_ASSEMBLY);
3305:     MatAssemblyEnd(*submat,MAT_FINAL_ASSEMBLY);

3307:   } else { /* call == MAT_INITIAL_MATRIX) */
3308:     const PetscInt *garray;
3309:     PetscInt        BsubN;

3311:     /* Create isrow_d, iscol_d, iscol_o and isgarray (replace isgarray with array?) */
3312:     ISGetSeqIS_SameColDist_Private(mat,isrow,iscol,&isrow_d,&iscol_d,&iscol_o,&garray);

3314:     /* Create local submatrices Asub and Bsub */
3315:     MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Asub);
3316:     MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Bsub);

3318:     /* Create submatrix M */
3319:     MatCreateMPIAIJWithSeqAIJ(comm,Asub,Bsub,garray,&M);

3321:     /* If Bsub has empty columns, compress iscol_o such that it will retrieve condensed Bsub from a->B during reuse */
3322:     asub = (Mat_MPIAIJ*)M->data;

3324:     ISGetLocalSize(iscol_o,&BsubN);
3325:     n = asub->B->cmap->N;
3326:     if (BsubN > n) {
3327:       /* This case can be tested using ~petsc/src/tao/bound/examples/tutorials/runplate2_3 */
3328:       const PetscInt *idx;
3329:       PetscInt       i,j,*idx_new,*subgarray = asub->garray;
3330:       PetscInfo2(M,"submatrix Bn %D != BsubN %D, update iscol_o\n",n,BsubN);

3332:       PetscMalloc1(n,&idx_new);
3333:       j = 0;
3334:       ISGetIndices(iscol_o,&idx);
3335:       for (i=0; i<n; i++) {
3336:         if (j >= BsubN) break;
3337:         while (subgarray[i] > garray[j]) j++;

3339:         if (subgarray[i] == garray[j]) {
3340:           idx_new[i] = idx[j++];
3341:         } else SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"subgarray[%D]=%D cannot < garray[%D]=%D",i,subgarray[i],j,garray[j]);
3342:       }
3343:       ISRestoreIndices(iscol_o,&idx);

3345:       ISDestroy(&iscol_o);
3346:       ISCreateGeneral(PETSC_COMM_SELF,n,idx_new,PETSC_OWN_POINTER,&iscol_o);

3348:     } else if (BsubN < n) {
3349:       SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Columns of Bsub cannot be smaller than B's",BsubN,asub->B->cmap->N);
3350:     }

3352:     PetscFree(garray);
3353:     *submat = M;

3355:     /* Save isrow_d, iscol_d and iscol_o used in processor for next request */
3356:     PetscObjectCompose((PetscObject)M,"isrow_d",(PetscObject)isrow_d);
3357:     ISDestroy(&isrow_d);

3359:     PetscObjectCompose((PetscObject)M,"iscol_d",(PetscObject)iscol_d);
3360:     ISDestroy(&iscol_d);

3362:     PetscObjectCompose((PetscObject)M,"iscol_o",(PetscObject)iscol_o);
3363:     ISDestroy(&iscol_o);
3364:   }
3365:   return(0);
3366: }

3368: PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
3369: {
3371:   IS             iscol_local=NULL,isrow_d;
3372:   PetscInt       csize;
3373:   PetscInt       n,i,j,start,end;
3374:   PetscBool      sameRowDist=PETSC_FALSE,sameDist[2],tsameDist[2];
3375:   MPI_Comm       comm;

3378:   /* If isrow has same processor distribution as mat,
3379:      call MatCreateSubMatrix_MPIAIJ_SameRowDist() to avoid using a hash table with global size of iscol */
3380:   if (call == MAT_REUSE_MATRIX) {
3381:     PetscObjectQuery((PetscObject)*newmat,"isrow_d",(PetscObject*)&isrow_d);
3382:     if (isrow_d) {
3383:       sameRowDist  = PETSC_TRUE;
3384:       tsameDist[1] = PETSC_TRUE; /* sameColDist */
3385:     } else {
3386:       PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);
3387:       if (iscol_local) {
3388:         sameRowDist  = PETSC_TRUE;
3389:         tsameDist[1] = PETSC_FALSE; /* !sameColDist */
3390:       }
3391:     }
3392:   } else {
3393:     /* Check if isrow has same processor distribution as mat */
3394:     sameDist[0] = PETSC_FALSE;
3395:     ISGetLocalSize(isrow,&n);
3396:     if (!n) {
3397:       sameDist[0] = PETSC_TRUE;
3398:     } else {
3399:       ISGetMinMax(isrow,&i,&j);
3400:       MatGetOwnershipRange(mat,&start,&end);
3401:       if (i >= start && j < end) {
3402:         sameDist[0] = PETSC_TRUE;
3403:       }
3404:     }

3406:     /* Check if iscol has same processor distribution as mat */
3407:     sameDist[1] = PETSC_FALSE;
3408:     ISGetLocalSize(iscol,&n);
3409:     if (!n) {
3410:       sameDist[1] = PETSC_TRUE;
3411:     } else {
3412:       ISGetMinMax(iscol,&i,&j);
3413:       MatGetOwnershipRangeColumn(mat,&start,&end);
3414:       if (i >= start && j < end) sameDist[1] = PETSC_TRUE;
3415:     }

3417:     PetscObjectGetComm((PetscObject)mat,&comm);
3418:     MPIU_Allreduce(&sameDist,&tsameDist,2,MPIU_BOOL,MPI_LAND,comm);
3419:     sameRowDist = tsameDist[0];
3420:   }

3422:   if (sameRowDist) {
3423:     if (tsameDist[1]) { /* sameRowDist & sameColDist */
3424:       /* isrow and iscol have same processor distribution as mat */
3425:       MatCreateSubMatrix_MPIAIJ_SameRowColDist(mat,isrow,iscol,call,newmat);
3426:       return(0);
3427:     } else { /* sameRowDist */
3428:       /* isrow has same processor distribution as mat */
3429:       if (call == MAT_INITIAL_MATRIX) {
3430:         PetscBool sorted;
3431:         ISGetSeqIS_Private(mat,iscol,&iscol_local);
3432:         ISGetLocalSize(iscol_local,&n); /* local size of iscol_local = global columns of newmat */
3433:         ISGetSize(iscol,&i);
3434:         if (n != i) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"n %d != size of iscol %d",n,i);

3436:         ISSorted(iscol_local,&sorted);
3437:         if (sorted) {
3438:           /* MatCreateSubMatrix_MPIAIJ_SameRowDist() requires iscol_local be sorted; it can have duplicate indices */
3439:           MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,iscol_local,MAT_INITIAL_MATRIX,newmat);
3440:           return(0);
3441:         }
3442:       } else { /* call == MAT_REUSE_MATRIX */
3443:         IS    iscol_sub;
3444:         PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3445:         if (iscol_sub) {
3446:           MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,NULL,call,newmat);
3447:           return(0);
3448:         }
3449:       }
3450:     }
3451:   }

3453:   /* General case: iscol -> iscol_local which has global size of iscol */
3454:   if (call == MAT_REUSE_MATRIX) {
3455:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
3456:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3457:   } else {
3458:     if (!iscol_local) {
3459:       ISGetSeqIS_Private(mat,iscol,&iscol_local);
3460:     }
3461:   }

3463:   ISGetLocalSize(iscol,&csize);
3464:   MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);

3466:   if (call == MAT_INITIAL_MATRIX) {
3467:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
3468:     ISDestroy(&iscol_local);
3469:   }
3470:   return(0);
3471: }

3473: /*@C
3474:      MatCreateMPIAIJWithSeqAIJ - creates a MPIAIJ matrix using SeqAIJ matrices that contain the "diagonal"
3475:          and "off-diagonal" part of the matrix in CSR format.

3477:    Collective on MPI_Comm

3479:    Input Parameters:
3480: +  comm - MPI communicator
3481: .  A - "diagonal" portion of matrix
3482: .  B - "off-diagonal" portion of matrix, may have empty columns, will be destroyed by this routine
3483: -  garray - global index of B columns

3485:    Output Parameter:
3486: .   mat - the matrix, with input A as its local diagonal matrix
3487:    Level: advanced

3489:    Notes:
3490:        See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix.
3491:        A becomes part of output mat, B is destroyed by this routine. The user cannot use A and B anymore.

3493: .seealso: MatCreateMPIAIJWithSplitArrays()
3494: @*/
3495: PetscErrorCode MatCreateMPIAIJWithSeqAIJ(MPI_Comm comm,Mat A,Mat B,const PetscInt garray[],Mat *mat)
3496: {
3498:   Mat_MPIAIJ     *maij;
3499:   Mat_SeqAIJ     *b=(Mat_SeqAIJ*)B->data,*bnew;
3500:   PetscInt       *oi=b->i,*oj=b->j,i,nz,col;
3501:   PetscScalar    *oa=b->a;
3502:   Mat            Bnew;
3503:   PetscInt       m,n,N;

3506:   MatCreate(comm,mat);
3507:   MatGetSize(A,&m,&n);
3508:   if (m != B->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Am %D != Bm %D",m,B->rmap->N);
3509:   if (A->rmap->bs != B->rmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A row bs %D != B row bs %D",A->rmap->bs,B->rmap->bs);
3510:   /* remove check below; When B is created using iscol_o from ISGetSeqIS_SameColDist_Private(), its bs may not be same as A */
3511:   /* if (A->cmap->bs != B->cmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A column bs %D != B column bs %D",A->cmap->bs,B->cmap->bs); */

3513:   /* Get global columns of mat */
3514:   MPIU_Allreduce(&n,&N,1,MPIU_INT,MPI_SUM,comm);

3516:   MatSetSizes(*mat,m,n,PETSC_DECIDE,N);
3517:   MatSetType(*mat,MATMPIAIJ);
3518:   MatSetBlockSizes(*mat,A->rmap->bs,A->cmap->bs);
3519:   maij = (Mat_MPIAIJ*)(*mat)->data;

3521:   (*mat)->preallocated = PETSC_TRUE;

3523:   PetscLayoutSetUp((*mat)->rmap);
3524:   PetscLayoutSetUp((*mat)->cmap);

3526:   /* Set A as diagonal portion of *mat */
3527:   maij->A = A;

3529:   nz = oi[m];
3530:   for (i=0; i<nz; i++) {
3531:     col   = oj[i];
3532:     oj[i] = garray[col];
3533:   }

3535:    /* Set Bnew as off-diagonal portion of *mat */
3536:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,N,oi,oj,oa,&Bnew);
3537:   bnew        = (Mat_SeqAIJ*)Bnew->data;
3538:   bnew->maxnz = b->maxnz; /* allocated nonzeros of B */
3539:   maij->B     = Bnew;

3541:   if (B->rmap->N != Bnew->rmap->N) SETERRQ2(PETSC_COMM_SELF,0,"BN %d != BnewN %d",B->rmap->N,Bnew->rmap->N);

3543:   b->singlemalloc = PETSC_FALSE; /* B arrays are shared by Bnew */
3544:   b->free_a       = PETSC_FALSE;
3545:   b->free_ij      = PETSC_FALSE;
3546:   MatDestroy(&B);

3548:   bnew->singlemalloc = PETSC_TRUE; /* arrays will be freed by MatDestroy(&Bnew) */
3549:   bnew->free_a       = PETSC_TRUE;
3550:   bnew->free_ij      = PETSC_TRUE;

3552:   /* condense columns of maij->B */
3553:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
3554:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
3555:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
3556:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
3557:   MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3558:   return(0);
3559: }

3561: extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*);

3563: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat mat,IS isrow,IS iscol,IS iscol_local,MatReuse call,Mat *newmat)
3564: {
3566:   PetscInt       i,m,n,rstart,row,rend,nz,j,bs,cbs;
3567:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3568:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)mat->data;
3569:   Mat            M,Msub,B=a->B;
3570:   MatScalar      *aa;
3571:   Mat_SeqAIJ     *aij;
3572:   PetscInt       *garray = a->garray,*colsub,Ncols;
3573:   PetscInt       count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend;
3574:   IS             iscol_sub,iscmap;
3575:   const PetscInt *is_idx,*cmap;
3576:   PetscBool      allcolumns=PETSC_FALSE;
3577:   MPI_Comm       comm;

3580:   PetscObjectGetComm((PetscObject)mat,&comm);

3582:   if (call == MAT_REUSE_MATRIX) {
3583:     PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3584:     if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse");
3585:     ISGetLocalSize(iscol_sub,&count);

3587:     PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);
3588:     if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse");

3590:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);
3591:     if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");

3593:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);

3595:   } else { /* call == MAT_INITIAL_MATRIX) */
3596:     PetscBool flg;

3598:     ISGetLocalSize(iscol,&n);
3599:     ISGetSize(iscol,&Ncols);

3601:     /* (1) iscol -> nonscalable iscol_local */
3602:     /* Check for special case: each processor gets entire matrix columns */
3603:     ISIdentity(iscol_local,&flg);
3604:     if (flg && n == mat->cmap->N) allcolumns = PETSC_TRUE;
3605:     if (allcolumns) {
3606:       iscol_sub = iscol_local;
3607:       PetscObjectReference((PetscObject)iscol_local);
3608:       ISCreateStride(PETSC_COMM_SELF,n,0,1,&iscmap);

3610:     } else {
3611:       /* (2) iscol_local -> iscol_sub and iscmap. Implementation below requires iscol_local be sorted, it can have duplicate indices */
3612:       PetscInt *idx,*cmap1,k;
3613:       PetscMalloc1(Ncols,&idx);
3614:       PetscMalloc1(Ncols,&cmap1);
3615:       ISGetIndices(iscol_local,&is_idx);
3616:       count = 0;
3617:       k     = 0;
3618:       for (i=0; i<Ncols; i++) {
3619:         j = is_idx[i];
3620:         if (j >= cstart && j < cend) {
3621:           /* diagonal part of mat */
3622:           idx[count]     = j;
3623:           cmap1[count++] = i; /* column index in submat */
3624:         } else if (Bn) {
3625:           /* off-diagonal part of mat */
3626:           if (j == garray[k]) {
3627:             idx[count]     = j;
3628:             cmap1[count++] = i;  /* column index in submat */
3629:           } else if (j > garray[k]) {
3630:             while (j > garray[k] && k < Bn-1) k++;
3631:             if (j == garray[k]) {
3632:               idx[count]     = j;
3633:               cmap1[count++] = i; /* column index in submat */
3634:             }
3635:           }
3636:         }
3637:       }
3638:       ISRestoreIndices(iscol_local,&is_idx);

3640:       ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_OWN_POINTER,&iscol_sub);
3641:       ISGetBlockSize(iscol,&cbs);
3642:       ISSetBlockSize(iscol_sub,cbs);

3644:       ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_OWN_POINTER,&iscmap);
3645:     }

3647:     /* (3) Create sequential Msub */
3648:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,allcolumns,&Msub);
3649:   }

3651:   ISGetLocalSize(iscol_sub,&count);
3652:   aij  = (Mat_SeqAIJ*)(Msub)->data;
3653:   ii   = aij->i;
3654:   ISGetIndices(iscmap,&cmap);

3656:   /*
3657:       m - number of local rows
3658:       Ncols - number of columns (same on all processors)
3659:       rstart - first row in new global matrix generated
3660:   */
3661:   MatGetSize(Msub,&m,NULL);

3663:   if (call == MAT_INITIAL_MATRIX) {
3664:     /* (4) Create parallel newmat */
3665:     PetscMPIInt    rank,size;
3666:     PetscInt       csize;

3668:     MPI_Comm_size(comm,&size);
3669:     MPI_Comm_rank(comm,&rank);

3671:     /*
3672:         Determine the number of non-zeros in the diagonal and off-diagonal
3673:         portions of the matrix in order to do correct preallocation
3674:     */

3676:     /* first get start and end of "diagonal" columns */
3677:     ISGetLocalSize(iscol,&csize);
3678:     if (csize == PETSC_DECIDE) {
3679:       ISGetSize(isrow,&mglobal);
3680:       if (mglobal == Ncols) { /* square matrix */
3681:         nlocal = m;
3682:       } else {
3683:         nlocal = Ncols/size + ((Ncols % size) > rank);
3684:       }
3685:     } else {
3686:       nlocal = csize;
3687:     }
3688:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3689:     rstart = rend - nlocal;
3690:     if (rank == size - 1 && rend != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,Ncols);

3692:     /* next, compute all the lengths */
3693:     jj    = aij->j;
3694:     PetscMalloc1(2*m+1,&dlens);
3695:     olens = dlens + m;
3696:     for (i=0; i<m; i++) {
3697:       jend = ii[i+1] - ii[i];
3698:       olen = 0;
3699:       dlen = 0;
3700:       for (j=0; j<jend; j++) {
3701:         if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++;
3702:         else dlen++;
3703:         jj++;
3704:       }
3705:       olens[i] = olen;
3706:       dlens[i] = dlen;
3707:     }

3709:     ISGetBlockSize(isrow,&bs);
3710:     ISGetBlockSize(iscol,&cbs);

3712:     MatCreate(comm,&M);
3713:     MatSetSizes(M,m,nlocal,PETSC_DECIDE,Ncols);
3714:     MatSetBlockSizes(M,bs,cbs);
3715:     MatSetType(M,((PetscObject)mat)->type_name);
3716:     MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3717:     PetscFree(dlens);

3719:   } else { /* call == MAT_REUSE_MATRIX */
3720:     M    = *newmat;
3721:     MatGetLocalSize(M,&i,NULL);
3722:     if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3723:     MatZeroEntries(M);
3724:     /*
3725:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3726:        rather than the slower MatSetValues().
3727:     */
3728:     M->was_assembled = PETSC_TRUE;
3729:     M->assembled     = PETSC_FALSE;
3730:   }

3732:   /* (5) Set values of Msub to *newmat */
3733:   PetscMalloc1(count,&colsub);
3734:   MatGetOwnershipRange(M,&rstart,NULL);

3736:   jj   = aij->j;
3737:   aa   = aij->a;
3738:   for (i=0; i<m; i++) {
3739:     row = rstart + i;
3740:     nz  = ii[i+1] - ii[i];
3741:     for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]];
3742:     MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);
3743:     jj += nz; aa += nz;
3744:   }
3745:   ISRestoreIndices(iscmap,&cmap);

3747:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3748:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);

3750:   PetscFree(colsub);

3752:   /* save Msub, iscol_sub and iscmap used in processor for next request */
3753:   if (call ==  MAT_INITIAL_MATRIX) {
3754:     *newmat = M;
3755:     PetscObjectCompose((PetscObject)(*newmat),"SubMatrix",(PetscObject)Msub);
3756:     MatDestroy(&Msub);

3758:     PetscObjectCompose((PetscObject)(*newmat),"SubIScol",(PetscObject)iscol_sub);
3759:     ISDestroy(&iscol_sub);

3761:     PetscObjectCompose((PetscObject)(*newmat),"Subcmap",(PetscObject)iscmap);
3762:     ISDestroy(&iscmap);

3764:     if (iscol_local) {
3765:       PetscObjectCompose((PetscObject)(*newmat),"ISAllGather",(PetscObject)iscol_local);
3766:       ISDestroy(&iscol_local);
3767:     }
3768:   }
3769:   return(0);
3770: }

3772: /*
3773:     Not great since it makes two copies of the submatrix, first an SeqAIJ
3774:   in local and then by concatenating the local matrices the end result.
3775:   Writing it directly would be much like MatCreateSubMatrices_MPIAIJ()

3777:   Note: This requires a sequential iscol with all indices.
3778: */
3779: PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
3780: {
3782:   PetscMPIInt    rank,size;
3783:   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs;
3784:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3785:   Mat            M,Mreuse;
3786:   MatScalar      *aa,*vwork;
3787:   MPI_Comm       comm;
3788:   Mat_SeqAIJ     *aij;
3789:   PetscBool      colflag,allcolumns=PETSC_FALSE;

3792:   PetscObjectGetComm((PetscObject)mat,&comm);
3793:   MPI_Comm_rank(comm,&rank);
3794:   MPI_Comm_size(comm,&size);

3796:   /* Check for special case: each processor gets entire matrix columns */
3797:   ISIdentity(iscol,&colflag);
3798:   ISGetLocalSize(iscol,&n);
3799:   if (colflag && n == mat->cmap->N) allcolumns = PETSC_TRUE;

3801:   if (call ==  MAT_REUSE_MATRIX) {
3802:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
3803:     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3804:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,allcolumns,&Mreuse);
3805:   } else {
3806:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,allcolumns,&Mreuse);
3807:   }

3809:   /*
3810:       m - number of local rows
3811:       n - number of columns (same on all processors)
3812:       rstart - first row in new global matrix generated
3813:   */
3814:   MatGetSize(Mreuse,&m,&n);
3815:   MatGetBlockSizes(Mreuse,&bs,&cbs);
3816:   if (call == MAT_INITIAL_MATRIX) {
3817:     aij = (Mat_SeqAIJ*)(Mreuse)->data;
3818:     ii  = aij->i;
3819:     jj  = aij->j;

3821:     /*
3822:         Determine the number of non-zeros in the diagonal and off-diagonal
3823:         portions of the matrix in order to do correct preallocation
3824:     */

3826:     /* first get start and end of "diagonal" columns */
3827:     if (csize == PETSC_DECIDE) {
3828:       ISGetSize(isrow,&mglobal);
3829:       if (mglobal == n) { /* square matrix */
3830:         nlocal = m;
3831:       } else {
3832:         nlocal = n/size + ((n % size) > rank);
3833:       }
3834:     } else {
3835:       nlocal = csize;
3836:     }
3837:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3838:     rstart = rend - nlocal;
3839:     if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n);

3841:     /* next, compute all the lengths */
3842:     PetscMalloc1(2*m+1,&dlens);
3843:     olens = dlens + m;
3844:     for (i=0; i<m; i++) {
3845:       jend = ii[i+1] - ii[i];
3846:       olen = 0;
3847:       dlen = 0;
3848:       for (j=0; j<jend; j++) {
3849:         if (*jj < rstart || *jj >= rend) olen++;
3850:         else dlen++;
3851:         jj++;
3852:       }
3853:       olens[i] = olen;
3854:       dlens[i] = dlen;
3855:     }
3856:     MatCreate(comm,&M);
3857:     MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);
3858:     MatSetBlockSizes(M,bs,cbs);
3859:     MatSetType(M,((PetscObject)mat)->type_name);
3860:     MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3861:     PetscFree(dlens);
3862:   } else {
3863:     PetscInt ml,nl;

3865:     M    = *newmat;
3866:     MatGetLocalSize(M,&ml,&nl);
3867:     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3868:     MatZeroEntries(M);
3869:     /*
3870:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3871:        rather than the slower MatSetValues().
3872:     */
3873:     M->was_assembled = PETSC_TRUE;
3874:     M->assembled     = PETSC_FALSE;
3875:   }
3876:   MatGetOwnershipRange(M,&rstart,&rend);
3877:   aij  = (Mat_SeqAIJ*)(Mreuse)->data;
3878:   ii   = aij->i;
3879:   jj   = aij->j;
3880:   aa   = aij->a;
3881:   for (i=0; i<m; i++) {
3882:     row   = rstart + i;
3883:     nz    = ii[i+1] - ii[i];
3884:     cwork = jj;     jj += nz;
3885:     vwork = aa;     aa += nz;
3886:     MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
3887:   }

3889:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3890:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3891:   *newmat = M;

3893:   /* save submatrix used in processor for next request */
3894:   if (call ==  MAT_INITIAL_MATRIX) {
3895:     PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
3896:     MatDestroy(&Mreuse);
3897:   }
3898:   return(0);
3899: }

3901: PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
3902: {
3903:   PetscInt       m,cstart, cend,j,nnz,i,d;
3904:   PetscInt       *d_nnz,*o_nnz,nnz_max = 0,rstart,ii;
3905:   const PetscInt *JJ;
3906:   PetscScalar    *values;
3908:   PetscBool      nooffprocentries;

3911:   if (Ii && Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]);

3913:   PetscLayoutSetUp(B->rmap);
3914:   PetscLayoutSetUp(B->cmap);
3915:   m      = B->rmap->n;
3916:   cstart = B->cmap->rstart;
3917:   cend   = B->cmap->rend;
3918:   rstart = B->rmap->rstart;

3920:   PetscCalloc2(m,&d_nnz,m,&o_nnz);

3922: #if defined(PETSC_USE_DEBUG)
3923:   for (i=0; i<m && Ii; i++) {
3924:     nnz = Ii[i+1]- Ii[i];
3925:     JJ  = J + Ii[i];
3926:     if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz);
3927:     if (nnz && (JJ[0] < 0)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,JJ[0]);
3928:     if (nnz && (JJ[nnz-1] >= B->cmap->N)) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N);
3929:   }
3930: #endif

3932:   for (i=0; i<m && Ii; i++) {
3933:     nnz     = Ii[i+1]- Ii[i];
3934:     JJ      = J + Ii[i];
3935:     nnz_max = PetscMax(nnz_max,nnz);
3936:     d       = 0;
3937:     for (j=0; j<nnz; j++) {
3938:       if (cstart <= JJ[j] && JJ[j] < cend) d++;
3939:     }
3940:     d_nnz[i] = d;
3941:     o_nnz[i] = nnz - d;
3942:   }
3943:   MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
3944:   PetscFree2(d_nnz,o_nnz);

3946:   if (v) values = (PetscScalar*)v;
3947:   else {
3948:     PetscCalloc1(nnz_max+1,&values);
3949:   }

3951:   for (i=0; i<m && Ii; i++) {
3952:     ii   = i + rstart;
3953:     nnz  = Ii[i+1]- Ii[i];
3954:     MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);
3955:   }
3956:   nooffprocentries    = B->nooffprocentries;
3957:   B->nooffprocentries = PETSC_TRUE;
3958:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3959:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
3960:   B->nooffprocentries = nooffprocentries;

3962:   if (!v) {
3963:     PetscFree(values);
3964:   }
3965:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3966:   return(0);
3967: }

3969: /*@
3970:    MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format
3971:    (the default parallel PETSc format).

3973:    Collective on MPI_Comm

3975:    Input Parameters:
3976: +  B - the matrix
3977: .  i - the indices into j for the start of each local row (starts with zero)
3978: .  j - the column indices for each local row (starts with zero)
3979: -  v - optional values in the matrix

3981:    Level: developer

3983:    Notes:
3984:        The i, j, and v arrays ARE copied by this routine into the internal format used by PETSc;
3985:      thus you CANNOT change the matrix entries by changing the values of v[] after you have
3986:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3988:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3990:        The format which is used for the sparse matrix input, is equivalent to a
3991:     row-major ordering.. i.e for the following matrix, the input data expected is
3992:     as shown

3994: $        1 0 0
3995: $        2 0 3     P0
3996: $       -------
3997: $        4 5 6     P1
3998: $
3999: $     Process0 [P0]: rows_owned=[0,1]
4000: $        i =  {0,1,3}  [size = nrow+1  = 2+1]
4001: $        j =  {0,0,2}  [size = 3]
4002: $        v =  {1,2,3}  [size = 3]
4003: $
4004: $     Process1 [P1]: rows_owned=[2]
4005: $        i =  {0,3}    [size = nrow+1  = 1+1]
4006: $        j =  {0,1,2}  [size = 3]
4007: $        v =  {4,5,6}  [size = 3]

4009: .keywords: matrix, aij, compressed row, sparse, parallel

4011: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ,
4012:           MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays()
4013: @*/
4014: PetscErrorCode  MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
4015: {

4019:   PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));
4020:   return(0);
4021: }

4023: /*@C
4024:    MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format
4025:    (the default parallel PETSc format).  For good matrix assembly performance
4026:    the user should preallocate the matrix storage by setting the parameters
4027:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
4028:    performance can be increased by more than a factor of 50.

4030:    Collective on MPI_Comm

4032:    Input Parameters:
4033: +  B - the matrix
4034: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
4035:            (same value is used for all local rows)
4036: .  d_nnz - array containing the number of nonzeros in the various rows of the
4037:            DIAGONAL portion of the local submatrix (possibly different for each row)
4038:            or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
4039:            The size of this array is equal to the number of local rows, i.e 'm'.
4040:            For matrices that will be factored, you must leave room for (and set)
4041:            the diagonal entry even if it is zero.
4042: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
4043:            submatrix (same value is used for all local rows).
4044: -  o_nnz - array containing the number of nonzeros in the various rows of the
4045:            OFF-DIAGONAL portion of the local submatrix (possibly different for
4046:            each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
4047:            structure. The size of this array is equal to the number
4048:            of local rows, i.e 'm'.

4050:    If the *_nnz parameter is given then the *_nz parameter is ignored

4052:    The AIJ format (also called the Yale sparse matrix format or
4053:    compressed row storage (CSR)), is fully compatible with standard Fortran 77
4054:    storage.  The stored row and column indices begin with zero.
4055:    See Users-Manual: ch_mat for details.

4057:    The parallel matrix is partitioned such that the first m0 rows belong to
4058:    process 0, the next m1 rows belong to process 1, the next m2 rows belong
4059:    to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.

4061:    The DIAGONAL portion of the local submatrix of a processor can be defined
4062:    as the submatrix which is obtained by extraction the part corresponding to
4063:    the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
4064:    first row that belongs to the processor, r2 is the last row belonging to
4065:    the this processor, and c1-c2 is range of indices of the local part of a
4066:    vector suitable for applying the matrix to.  This is an mxn matrix.  In the
4067:    common case of a square matrix, the row and column ranges are the same and
4068:    the DIAGONAL part is also square. The remaining portion of the local
4069:    submatrix (mxN) constitute the OFF-DIAGONAL portion.

4071:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

4073:    You can call MatGetInfo() to get information on how effective the preallocation was;
4074:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
4075:    You can also run with the option -info and look for messages with the string
4076:    malloc in them to see if additional memory allocation was needed.

4078:    Example usage:

4080:    Consider the following 8x8 matrix with 34 non-zero values, that is
4081:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
4082:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
4083:    as follows:

4085: .vb
4086:             1  2  0  |  0  3  0  |  0  4
4087:     Proc0   0  5  6  |  7  0  0  |  8  0
4088:             9  0 10  | 11  0  0  | 12  0
4089:     -------------------------------------
4090:            13  0 14  | 15 16 17  |  0  0
4091:     Proc1   0 18  0  | 19 20 21  |  0  0
4092:             0  0  0  | 22 23  0  | 24  0
4093:     -------------------------------------
4094:     Proc2  25 26 27  |  0  0 28  | 29  0
4095:            30  0  0  | 31 32 33  |  0 34
4096: .ve

4098:    This can be represented as a collection of submatrices as:

4100: .vb
4101:       A B C
4102:       D E F
4103:       G H I
4104: .ve

4106:    Where the submatrices A,B,C are owned by proc0, D,E,F are
4107:    owned by proc1, G,H,I are owned by proc2.

4109:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4110:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4111:    The 'M','N' parameters are 8,8, and have the same values on all procs.

4113:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
4114:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
4115:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
4116:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
4117:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
4118:    matrix, ans [DF] as another SeqAIJ matrix.

4120:    When d_nz, o_nz parameters are specified, d_nz storage elements are
4121:    allocated for every row of the local diagonal submatrix, and o_nz
4122:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
4123:    One way to choose d_nz and o_nz is to use the max nonzerors per local
4124:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
4125:    In this case, the values of d_nz,o_nz are:
4126: .vb
4127:      proc0 : dnz = 2, o_nz = 2
4128:      proc1 : dnz = 3, o_nz = 2
4129:      proc2 : dnz = 1, o_nz = 4
4130: .ve
4131:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
4132:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
4133:    for proc3. i.e we are using 12+15+10=37 storage locations to store
4134:    34 values.

4136:    When d_nnz, o_nnz parameters are specified, the storage is specified
4137:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
4138:    In the above case the values for d_nnz,o_nnz are:
4139: .vb
4140:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
4141:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
4142:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
4143: .ve
4144:    Here the space allocated is sum of all the above values i.e 34, and
4145:    hence pre-allocation is perfect.

4147:    Level: intermediate

4149: .keywords: matrix, aij, compressed row, sparse, parallel

4151: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(),
4152:           MATMPIAIJ, MatGetInfo(), PetscSplitOwnership()
4153: @*/
4154: PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
4155: {

4161:   PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
4162:   return(0);
4163: }

4165: /*@
4166:      MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard
4167:          CSR format the local rows.

4169:    Collective on MPI_Comm

4171:    Input Parameters:
4172: +  comm - MPI communicator
4173: .  m - number of local rows (Cannot be PETSC_DECIDE)
4174: .  n - This value should be the same as the local size used in creating the
4175:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4176:        calculated if N is given) For square matrices n is almost always m.
4177: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4178: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4179: .   i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix
4180: .   j - column indices
4181: -   a - matrix values

4183:    Output Parameter:
4184: .   mat - the matrix

4186:    Level: intermediate

4188:    Notes:
4189:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
4190:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
4191:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

4193:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

4195:        The format which is used for the sparse matrix input, is equivalent to a
4196:     row-major ordering.. i.e for the following matrix, the input data expected is
4197:     as shown

4199: $        1 0 0
4200: $        2 0 3     P0
4201: $       -------
4202: $        4 5 6     P1
4203: $
4204: $     Process0 [P0]: rows_owned=[0,1]
4205: $        i =  {0,1,3}  [size = nrow+1  = 2+1]
4206: $        j =  {0,0,2}  [size = 3]
4207: $        v =  {1,2,3}  [size = 3]
4208: $
4209: $     Process1 [P1]: rows_owned=[2]
4210: $        i =  {0,3}    [size = nrow+1  = 1+1]
4211: $        j =  {0,1,2}  [size = 3]
4212: $        v =  {4,5,6}  [size = 3]

4214: .keywords: matrix, aij, compressed row, sparse, parallel

4216: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4217:           MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
4218: @*/
4219: PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
4220: {

4224:   if (i && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4225:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4226:   MatCreate(comm,mat);
4227:   MatSetSizes(*mat,m,n,M,N);
4228:   /* MatSetBlockSizes(M,bs,cbs); */
4229:   MatSetType(*mat,MATMPIAIJ);
4230:   MatMPIAIJSetPreallocationCSR(*mat,i,j,a);
4231:   return(0);
4232: }

4234: /*@C
4235:    MatCreateAIJ - Creates a sparse parallel matrix in AIJ format
4236:    (the default parallel PETSc format).  For good matrix assembly performance
4237:    the user should preallocate the matrix storage by setting the parameters
4238:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
4239:    performance can be increased by more than a factor of 50.

4241:    Collective on MPI_Comm

4243:    Input Parameters:
4244: +  comm - MPI communicator
4245: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
4246:            This value should be the same as the local size used in creating the
4247:            y vector for the matrix-vector product y = Ax.
4248: .  n - This value should be the same as the local size used in creating the
4249:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4250:        calculated if N is given) For square matrices n is almost always m.
4251: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4252: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4253: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
4254:            (same value is used for all local rows)
4255: .  d_nnz - array containing the number of nonzeros in the various rows of the
4256:            DIAGONAL portion of the local submatrix (possibly different for each row)
4257:            or NULL, if d_nz is used to specify the nonzero structure.
4258:            The size of this array is equal to the number of local rows, i.e 'm'.
4259: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
4260:            submatrix (same value is used for all local rows).
4261: -  o_nnz - array containing the number of nonzeros in the various rows of the
4262:            OFF-DIAGONAL portion of the local submatrix (possibly different for
4263:            each row) or NULL, if o_nz is used to specify the nonzero
4264:            structure. The size of this array is equal to the number
4265:            of local rows, i.e 'm'.

4267:    Output Parameter:
4268: .  A - the matrix

4270:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
4271:    MatXXXXSetPreallocation() paradigm instead of this routine directly.
4272:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

4274:    Notes:
4275:    If the *_nnz parameter is given then the *_nz parameter is ignored

4277:    m,n,M,N parameters specify the size of the matrix, and its partitioning across
4278:    processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
4279:    storage requirements for this matrix.

4281:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one
4282:    processor than it must be used on all processors that share the object for
4283:    that argument.

4285:    The user MUST specify either the local or global matrix dimensions
4286:    (possibly both).

4288:    The parallel matrix is partitioned across processors such that the
4289:    first m0 rows belong to process 0, the next m1 rows belong to
4290:    process 1, the next m2 rows belong to process 2 etc.. where
4291:    m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
4292:    values corresponding to [m x N] submatrix.

4294:    The columns are logically partitioned with the n0 columns belonging
4295:    to 0th partition, the next n1 columns belonging to the next
4296:    partition etc.. where n0,n1,n2... are the input parameter 'n'.

4298:    The DIAGONAL portion of the local submatrix on any given processor
4299:    is the submatrix corresponding to the rows and columns m,n
4300:    corresponding to the given processor. i.e diagonal matrix on
4301:    process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
4302:    etc. The remaining portion of the local submatrix [m x (N-n)]
4303:    constitute the OFF-DIAGONAL portion. The example below better
4304:    illustrates this concept.

4306:    For a square global matrix we define each processor's diagonal portion
4307:    to be its local rows and the corresponding columns (a square submatrix);
4308:    each processor's off-diagonal portion encompasses the remainder of the
4309:    local matrix (a rectangular submatrix).

4311:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

4313:    When calling this routine with a single process communicator, a matrix of
4314:    type SEQAIJ is returned.  If a matrix of type MPIAIJ is desired for this
4315:    type of communicator, use the construction mechanism
4316: .vb
4317:      MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...);
4318: .ve

4320: $     MatCreate(...,&A);
4321: $     MatSetType(A,MATMPIAIJ);
4322: $     MatSetSizes(A, m,n,M,N);
4323: $     MatMPIAIJSetPreallocation(A,...);

4325:    By default, this format uses inodes (identical nodes) when possible.
4326:    We search for consecutive rows with the same nonzero structure, thereby
4327:    reusing matrix information to achieve increased efficiency.

4329:    Options Database Keys:
4330: +  -mat_no_inode  - Do not use inodes
4331: -  -mat_inode_limit <limit> - Sets inode limit (max limit=5)



4335:    Example usage:

4337:    Consider the following 8x8 matrix with 34 non-zero values, that is
4338:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
4339:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
4340:    as follows

4342: .vb
4343:             1  2  0  |  0  3  0  |  0  4
4344:     Proc0   0  5  6  |  7  0  0  |  8  0
4345:             9  0 10  | 11  0  0  | 12  0
4346:     -------------------------------------
4347:            13  0 14  | 15 16 17  |  0  0
4348:     Proc1   0 18  0  | 19 20 21  |  0  0
4349:             0  0  0  | 22 23  0  | 24  0
4350:     -------------------------------------
4351:     Proc2  25 26 27  |  0  0 28  | 29  0
4352:            30  0  0  | 31 32 33  |  0 34
4353: .ve

4355:    This can be represented as a collection of submatrices as

4357: .vb
4358:       A B C
4359:       D E F
4360:       G H I
4361: .ve

4363:    Where the submatrices A,B,C are owned by proc0, D,E,F are
4364:    owned by proc1, G,H,I are owned by proc2.

4366:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4367:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4368:    The 'M','N' parameters are 8,8, and have the same values on all procs.

4370:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
4371:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
4372:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
4373:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
4374:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
4375:    matrix, ans [DF] as another SeqAIJ matrix.

4377:    When d_nz, o_nz parameters are specified, d_nz storage elements are
4378:    allocated for every row of the local diagonal submatrix, and o_nz
4379:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
4380:    One way to choose d_nz and o_nz is to use the max nonzerors per local
4381:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
4382:    In this case, the values of d_nz,o_nz are
4383: .vb
4384:      proc0 : dnz = 2, o_nz = 2
4385:      proc1 : dnz = 3, o_nz = 2
4386:      proc2 : dnz = 1, o_nz = 4
4387: .ve
4388:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
4389:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
4390:    for proc3. i.e we are using 12+15+10=37 storage locations to store
4391:    34 values.

4393:    When d_nnz, o_nnz parameters are specified, the storage is specified
4394:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
4395:    In the above case the values for d_nnz,o_nnz are
4396: .vb
4397:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
4398:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
4399:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
4400: .ve
4401:    Here the space allocated is sum of all the above values i.e 34, and
4402:    hence pre-allocation is perfect.

4404:    Level: intermediate

4406: .keywords: matrix, aij, compressed row, sparse, parallel

4408: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4409:           MATMPIAIJ, MatCreateMPIAIJWithArrays()
4410: @*/
4411: PetscErrorCode  MatCreateAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A)
4412: {
4414:   PetscMPIInt    size;

4417:   MatCreate(comm,A);
4418:   MatSetSizes(*A,m,n,M,N);
4419:   MPI_Comm_size(comm,&size);
4420:   if (size > 1) {
4421:     MatSetType(*A,MATMPIAIJ);
4422:     MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
4423:   } else {
4424:     MatSetType(*A,MATSEQAIJ);
4425:     MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
4426:   }
4427:   return(0);
4428: }

4430: PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
4431: {
4432:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
4433:   PetscBool      flg;

4437:   PetscStrbeginswith(((PetscObject)A)->type_name,MATMPIAIJ,&flg);
4438:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input");
4439:   if (Ad)     *Ad     = a->A;
4440:   if (Ao)     *Ao     = a->B;
4441:   if (colmap) *colmap = a->garray;
4442:   return(0);
4443: }

4445: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
4446: {
4448:   PetscInt       m,N,i,rstart,nnz,Ii;
4449:   PetscInt       *indx;
4450:   PetscScalar    *values;

4453:   MatGetSize(inmat,&m,&N);
4454:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
4455:     PetscInt       *dnz,*onz,sum,bs,cbs;

4457:     if (n == PETSC_DECIDE) {
4458:       PetscSplitOwnership(comm,&n,&N);
4459:     }
4460:     /* Check sum(n) = N */
4461:     MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
4462:     if (sum != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns %D != global columns %D",sum,N);

4464:     MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);
4465:     rstart -= m;

4467:     MatPreallocateInitialize(comm,m,n,dnz,onz);
4468:     for (i=0; i<m; i++) {
4469:       MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4470:       MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);
4471:       MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4472:     }

4474:     MatCreate(comm,outmat);
4475:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4476:     MatGetBlockSizes(inmat,&bs,&cbs);
4477:     MatSetBlockSizes(*outmat,bs,cbs);
4478:     MatSetType(*outmat,MATAIJ);
4479:     MatSeqAIJSetPreallocation(*outmat,0,dnz);
4480:     MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);
4481:     MatPreallocateFinalize(dnz,onz);
4482:   }

4484:   /* numeric phase */
4485:   MatGetOwnershipRange(*outmat,&rstart,NULL);
4486:   for (i=0; i<m; i++) {
4487:     MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4488:     Ii   = i + rstart;
4489:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
4490:     MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4491:   }
4492:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
4493:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
4494:   return(0);
4495: }

4497: PetscErrorCode MatFileSplit(Mat A,char *outfile)
4498: {
4499:   PetscErrorCode    ierr;
4500:   PetscMPIInt       rank;
4501:   PetscInt          m,N,i,rstart,nnz;
4502:   size_t            len;
4503:   const PetscInt    *indx;
4504:   PetscViewer       out;
4505:   char              *name;
4506:   Mat               B;
4507:   const PetscScalar *values;

4510:   MatGetLocalSize(A,&m,0);
4511:   MatGetSize(A,0,&N);
4512:   /* Should this be the type of the diagonal block of A? */
4513:   MatCreate(PETSC_COMM_SELF,&B);
4514:   MatSetSizes(B,m,N,m,N);
4515:   MatSetBlockSizesFromMats(B,A,A);
4516:   MatSetType(B,MATSEQAIJ);
4517:   MatSeqAIJSetPreallocation(B,0,NULL);
4518:   MatGetOwnershipRange(A,&rstart,0);
4519:   for (i=0; i<m; i++) {
4520:     MatGetRow(A,i+rstart,&nnz,&indx,&values);
4521:     MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);
4522:     MatRestoreRow(A,i+rstart,&nnz,&indx,&values);
4523:   }
4524:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
4525:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

4527:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
4528:   PetscStrlen(outfile,&len);
4529:   PetscMalloc1(len+5,&name);
4530:   sprintf(name,"%s.%d",outfile,rank);
4531:   PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);
4532:   PetscFree(name);
4533:   MatView(B,out);
4534:   PetscViewerDestroy(&out);
4535:   MatDestroy(&B);
4536:   return(0);
4537: }

4539: PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A)
4540: {
4541:   PetscErrorCode      ierr;
4542:   Mat_Merge_SeqsToMPI *merge;
4543:   PetscContainer      container;

4546:   PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);
4547:   if (container) {
4548:     PetscContainerGetPointer(container,(void**)&merge);
4549:     PetscFree(merge->id_r);
4550:     PetscFree(merge->len_s);
4551:     PetscFree(merge->len_r);
4552:     PetscFree(merge->bi);
4553:     PetscFree(merge->bj);
4554:     PetscFree(merge->buf_ri[0]);
4555:     PetscFree(merge->buf_ri);
4556:     PetscFree(merge->buf_rj[0]);
4557:     PetscFree(merge->buf_rj);
4558:     PetscFree(merge->coi);
4559:     PetscFree(merge->coj);
4560:     PetscFree(merge->owners_co);
4561:     PetscLayoutDestroy(&merge->rowmap);
4562:     PetscFree(merge);
4563:     PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);
4564:   }
4565:   MatDestroy_MPIAIJ(A);
4566:   return(0);
4567: }

4569:  #include <../src/mat/utils/freespace.h>
4570:  #include <petscbt.h>

4572: PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat)
4573: {
4574:   PetscErrorCode      ierr;
4575:   MPI_Comm            comm;
4576:   Mat_SeqAIJ          *a  =(Mat_SeqAIJ*)seqmat->data;
4577:   PetscMPIInt         size,rank,taga,*len_s;
4578:   PetscInt            N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj;
4579:   PetscInt            proc,m;
4580:   PetscInt            **buf_ri,**buf_rj;
4581:   PetscInt            k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj;
4582:   PetscInt            nrows,**buf_ri_k,**nextrow,**nextai;
4583:   MPI_Request         *s_waits,*r_waits;
4584:   MPI_Status          *status;
4585:   MatScalar           *aa=a->a;
4586:   MatScalar           **abuf_r,*ba_i;
4587:   Mat_Merge_SeqsToMPI *merge;
4588:   PetscContainer      container;

4591:   PetscObjectGetComm((PetscObject)mpimat,&comm);
4592:   PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);

4594:   MPI_Comm_size(comm,&size);
4595:   MPI_Comm_rank(comm,&rank);

4597:   PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);
4598:   PetscContainerGetPointer(container,(void**)&merge);

4600:   bi     = merge->bi;
4601:   bj     = merge->bj;
4602:   buf_ri = merge->buf_ri;
4603:   buf_rj = merge->buf_rj;

4605:   PetscMalloc1(size,&status);
4606:   owners = merge->rowmap->range;
4607:   len_s  = merge->len_s;

4609:   /* send and recv matrix values */
4610:   /*-----------------------------*/
4611:   PetscObjectGetNewTag((PetscObject)mpimat,&taga);
4612:   PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);

4614:   PetscMalloc1(merge->nsend+1,&s_waits);
4615:   for (proc=0,k=0; proc<size; proc++) {
4616:     if (!len_s[proc]) continue;
4617:     i    = owners[proc];
4618:     MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);
4619:     k++;
4620:   }

4622:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,r_waits,status);}
4623:   if (merge->nsend) {MPI_Waitall(merge->nsend,s_waits,status);}
4624:   PetscFree(status);

4626:   PetscFree(s_waits);
4627:   PetscFree(r_waits);

4629:   /* insert mat values of mpimat */
4630:   /*----------------------------*/
4631:   PetscMalloc1(N,&ba_i);
4632:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

4634:   for (k=0; k<merge->nrecv; k++) {
4635:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4636:     nrows       = *(buf_ri_k[k]);
4637:     nextrow[k]  = buf_ri_k[k]+1;  /* next row number of k-th recved i-structure */
4638:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
4639:   }

4641:   /* set values of ba */
4642:   m = merge->rowmap->n;
4643:   for (i=0; i<m; i++) {
4644:     arow = owners[rank] + i;
4645:     bj_i = bj+bi[i];  /* col indices of the i-th row of mpimat */
4646:     bnzi = bi[i+1] - bi[i];
4647:     PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));

4649:     /* add local non-zero vals of this proc's seqmat into ba */
4650:     anzi   = ai[arow+1] - ai[arow];
4651:     aj     = a->j + ai[arow];
4652:     aa     = a->a + ai[arow];
4653:     nextaj = 0;
4654:     for (j=0; nextaj<anzi; j++) {
4655:       if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4656:         ba_i[j] += aa[nextaj++];
4657:       }
4658:     }

4660:     /* add received vals into ba */
4661:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4662:       /* i-th row */
4663:       if (i == *nextrow[k]) {
4664:         anzi   = *(nextai[k]+1) - *nextai[k];
4665:         aj     = buf_rj[k] + *(nextai[k]);
4666:         aa     = abuf_r[k] + *(nextai[k]);
4667:         nextaj = 0;
4668:         for (j=0; nextaj<anzi; j++) {
4669:           if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4670:             ba_i[j] += aa[nextaj++];
4671:           }
4672:         }
4673:         nextrow[k]++; nextai[k]++;
4674:       }
4675:     }
4676:     MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);
4677:   }
4678:   MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);
4679:   MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);

4681:   PetscFree(abuf_r[0]);
4682:   PetscFree(abuf_r);
4683:   PetscFree(ba_i);
4684:   PetscFree3(buf_ri_k,nextrow,nextai);
4685:   PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);
4686:   return(0);
4687: }

4689: PetscErrorCode  MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat)
4690: {
4691:   PetscErrorCode      ierr;
4692:   Mat                 B_mpi;
4693:   Mat_SeqAIJ          *a=(Mat_SeqAIJ*)seqmat->data;
4694:   PetscMPIInt         size,rank,tagi,tagj,*len_s,*len_si,*len_ri;
4695:   PetscInt            **buf_rj,**buf_ri,**buf_ri_k;
4696:   PetscInt            M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j;
4697:   PetscInt            len,proc,*dnz,*onz,bs,cbs;
4698:   PetscInt            k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0;
4699:   PetscInt            nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai;
4700:   MPI_Request         *si_waits,*sj_waits,*ri_waits,*rj_waits;
4701:   MPI_Status          *status;
4702:   PetscFreeSpaceList  free_space=NULL,current_space=NULL;
4703:   PetscBT             lnkbt;
4704:   Mat_Merge_SeqsToMPI *merge;
4705:   PetscContainer      container;

4708:   PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);

4710:   /* make sure it is a PETSc comm */
4711:   PetscCommDuplicate(comm,&comm,NULL);
4712:   MPI_Comm_size(comm,&size);
4713:   MPI_Comm_rank(comm,&rank);

4715:   PetscNew(&merge);
4716:   PetscMalloc1(size,&status);

4718:   /* determine row ownership */
4719:   /*---------------------------------------------------------*/
4720:   PetscLayoutCreate(comm,&merge->rowmap);
4721:   PetscLayoutSetLocalSize(merge->rowmap,m);
4722:   PetscLayoutSetSize(merge->rowmap,M);
4723:   PetscLayoutSetBlockSize(merge->rowmap,1);
4724:   PetscLayoutSetUp(merge->rowmap);
4725:   PetscMalloc1(size,&len_si);
4726:   PetscMalloc1(size,&merge->len_s);

4728:   m      = merge->rowmap->n;
4729:   owners = merge->rowmap->range;

4731:   /* determine the number of messages to send, their lengths */
4732:   /*---------------------------------------------------------*/
4733:   len_s = merge->len_s;

4735:   len          = 0; /* length of buf_si[] */
4736:   merge->nsend = 0;
4737:   for (proc=0; proc<size; proc++) {
4738:     len_si[proc] = 0;
4739:     if (proc == rank) {
4740:       len_s[proc] = 0;
4741:     } else {
4742:       len_si[proc] = owners[proc+1] - owners[proc] + 1;
4743:       len_s[proc]  = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */
4744:     }
4745:     if (len_s[proc]) {
4746:       merge->nsend++;
4747:       nrows = 0;
4748:       for (i=owners[proc]; i<owners[proc+1]; i++) {
4749:         if (ai[i+1] > ai[i]) nrows++;
4750:       }
4751:       len_si[proc] = 2*(nrows+1);
4752:       len         += len_si[proc];
4753:     }
4754:   }

4756:   /* determine the number and length of messages to receive for ij-structure */
4757:   /*-------------------------------------------------------------------------*/
4758:   PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);
4759:   PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);

4761:   /* post the Irecv of j-structure */
4762:   /*-------------------------------*/
4763:   PetscCommGetNewTag(comm,&tagj);
4764:   PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);

4766:   /* post the Isend of j-structure */
4767:   /*--------------------------------*/
4768:   PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);

4770:   for (proc=0, k=0; proc<size; proc++) {
4771:     if (!len_s[proc]) continue;
4772:     i    = owners[proc];
4773:     MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);
4774:     k++;
4775:   }

4777:   /* receives and sends of j-structure are complete */
4778:   /*------------------------------------------------*/
4779:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,rj_waits,status);}
4780:   if (merge->nsend) {MPI_Waitall(merge->nsend,sj_waits,status);}

4782:   /* send and recv i-structure */
4783:   /*---------------------------*/
4784:   PetscCommGetNewTag(comm,&tagi);
4785:   PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);

4787:   PetscMalloc1(len+1,&buf_s);
4788:   buf_si = buf_s;  /* points to the beginning of k-th msg to be sent */
4789:   for (proc=0,k=0; proc<size; proc++) {
4790:     if (!len_s[proc]) continue;
4791:     /* form outgoing message for i-structure:
4792:          buf_si[0]:                 nrows to be sent
4793:                [1:nrows]:           row index (global)
4794:                [nrows+1:2*nrows+1]: i-structure index
4795:     */
4796:     /*-------------------------------------------*/
4797:     nrows       = len_si[proc]/2 - 1;
4798:     buf_si_i    = buf_si + nrows+1;
4799:     buf_si[0]   = nrows;
4800:     buf_si_i[0] = 0;
4801:     nrows       = 0;
4802:     for (i=owners[proc]; i<owners[proc+1]; i++) {
4803:       anzi = ai[i+1] - ai[i];
4804:       if (anzi) {
4805:         buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */
4806:         buf_si[nrows+1]   = i-owners[proc]; /* local row index */
4807:         nrows++;
4808:       }
4809:     }
4810:     MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);
4811:     k++;
4812:     buf_si += len_si[proc];
4813:   }

4815:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,ri_waits,status);}
4816:   if (merge->nsend) {MPI_Waitall(merge->nsend,si_waits,status);}

4818:   PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);
4819:   for (i=0; i<merge->nrecv; i++) {
4820:     PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);
4821:   }

4823:   PetscFree(len_si);
4824:   PetscFree(len_ri);
4825:   PetscFree(rj_waits);
4826:   PetscFree2(si_waits,sj_waits);
4827:   PetscFree(ri_waits);
4828:   PetscFree(buf_s);
4829:   PetscFree(status);

4831:   /* compute a local seq matrix in each processor */
4832:   /*----------------------------------------------*/
4833:   /* allocate bi array and free space for accumulating nonzero column info */
4834:   PetscMalloc1(m+1,&bi);
4835:   bi[0] = 0;

4837:   /* create and initialize a linked list */
4838:   nlnk = N+1;
4839:   PetscLLCreate(N,N,nlnk,lnk,lnkbt);

4841:   /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */
4842:   len  = ai[owners[rank+1]] - ai[owners[rank]];
4843:   PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);

4845:   current_space = free_space;

4847:   /* determine symbolic info for each local row */
4848:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

4850:   for (k=0; k<merge->nrecv; k++) {
4851:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4852:     nrows       = *buf_ri_k[k];
4853:     nextrow[k]  = buf_ri_k[k] + 1;  /* next row number of k-th recved i-structure */
4854:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
4855:   }

4857:   MatPreallocateInitialize(comm,m,n,dnz,onz);
4858:   len  = 0;
4859:   for (i=0; i<m; i++) {
4860:     bnzi = 0;
4861:     /* add local non-zero cols of this proc's seqmat into lnk */
4862:     arow  = owners[rank] + i;
4863:     anzi  = ai[arow+1] - ai[arow];
4864:     aj    = a->j + ai[arow];
4865:     PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4866:     bnzi += nlnk;
4867:     /* add received col data into lnk */
4868:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4869:       if (i == *nextrow[k]) { /* i-th row */
4870:         anzi  = *(nextai[k]+1) - *nextai[k];
4871:         aj    = buf_rj[k] + *nextai[k];
4872:         PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4873:         bnzi += nlnk;
4874:         nextrow[k]++; nextai[k]++;
4875:       }
4876:     }
4877:     if (len < bnzi) len = bnzi;  /* =max(bnzi) */

4879:     /* if free space is not available, make more free space */
4880:     if (current_space->local_remaining<bnzi) {
4881:       PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),&current_space);
4882:       nspacedouble++;
4883:     }
4884:     /* copy data into free space, then initialize lnk */
4885:     PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);
4886:     MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);

4888:     current_space->array           += bnzi;
4889:     current_space->local_used      += bnzi;
4890:     current_space->local_remaining -= bnzi;

4892:     bi[i+1] = bi[i] + bnzi;
4893:   }

4895:   PetscFree3(buf_ri_k,nextrow,nextai);

4897:   PetscMalloc1(bi[m]+1,&bj);
4898:   PetscFreeSpaceContiguous(&free_space,bj);
4899:   PetscLLDestroy(lnk,lnkbt);

4901:   /* create symbolic parallel matrix B_mpi */
4902:   /*---------------------------------------*/
4903:   MatGetBlockSizes(seqmat,&bs,&cbs);
4904:   MatCreate(comm,&B_mpi);
4905:   if (n==PETSC_DECIDE) {
4906:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);
4907:   } else {
4908:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4909:   }
4910:   MatSetBlockSizes(B_mpi,bs,cbs);
4911:   MatSetType(B_mpi,MATMPIAIJ);
4912:   MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);
4913:   MatPreallocateFinalize(dnz,onz);
4914:   MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);

4916:   /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */
4917:   B_mpi->assembled    = PETSC_FALSE;
4918:   B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI;
4919:   merge->bi           = bi;
4920:   merge->bj           = bj;
4921:   merge->buf_ri       = buf_ri;
4922:   merge->buf_rj       = buf_rj;
4923:   merge->coi          = NULL;
4924:   merge->coj          = NULL;
4925:   merge->owners_co    = NULL;

4927:   PetscCommDestroy(&comm);

4929:   /* attach the supporting struct to B_mpi for reuse */
4930:   PetscContainerCreate(PETSC_COMM_SELF,&container);
4931:   PetscContainerSetPointer(container,merge);
4932:   PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);
4933:   PetscContainerDestroy(&container);
4934:   *mpimat = B_mpi;

4936:   PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);
4937:   return(0);
4938: }

4940: /*@C
4941:       MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential
4942:                  matrices from each processor

4944:     Collective on MPI_Comm

4946:    Input Parameters:
4947: +    comm - the communicators the parallel matrix will live on
4948: .    seqmat - the input sequential matrices
4949: .    m - number of local rows (or PETSC_DECIDE)
4950: .    n - number of local columns (or PETSC_DECIDE)
4951: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

4953:    Output Parameter:
4954: .    mpimat - the parallel matrix generated

4956:     Level: advanced

4958:    Notes:
4959:      The dimensions of the sequential matrix in each processor MUST be the same.
4960:      The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be
4961:      destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat.
4962: @*/
4963: PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat)
4964: {
4966:   PetscMPIInt    size;

4969:   MPI_Comm_size(comm,&size);
4970:   if (size == 1) {
4971:     PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4972:     if (scall == MAT_INITIAL_MATRIX) {
4973:       MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);
4974:     } else {
4975:       MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);
4976:     }
4977:     PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4978:     return(0);
4979:   }
4980:   PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4981:   if (scall == MAT_INITIAL_MATRIX) {
4982:     MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);
4983:   }
4984:   MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);
4985:   PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4986:   return(0);
4987: }

4989: /*@
4990:      MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential matrix with
4991:           mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained
4992:           with MatGetSize()

4994:     Not Collective

4996:    Input Parameters:
4997: +    A - the matrix
4998: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

5000:    Output Parameter:
5001: .    A_loc - the local sequential matrix generated

5003:     Level: developer

5005: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMatCondensed()

5007: @*/
5008: PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc)
5009: {
5011:   Mat_MPIAIJ     *mpimat=(Mat_MPIAIJ*)A->data;
5012:   Mat_SeqAIJ     *mat,*a,*b;
5013:   PetscInt       *ai,*aj,*bi,*bj,*cmap=mpimat->garray;
5014:   MatScalar      *aa,*ba,*cam;
5015:   PetscScalar    *ca;
5016:   PetscInt       am=A->rmap->n,i,j,k,cstart=A->cmap->rstart;
5017:   PetscInt       *ci,*cj,col,ncols_d,ncols_o,jo;
5018:   PetscBool      match;
5019:   MPI_Comm       comm;
5020:   PetscMPIInt    size;

5023:   PetscStrbeginswith(((PetscObject)A)->type_name,MATMPIAIJ,&match);
5024:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
5025:   PetscObjectGetComm((PetscObject)A,&comm);
5026:   MPI_Comm_size(comm,&size);
5027:   if (size == 1 && scall == MAT_REUSE_MATRIX) return(0);

5029:   PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);
5030:   a = (Mat_SeqAIJ*)(mpimat->A)->data;
5031:   b = (Mat_SeqAIJ*)(mpimat->B)->data;
5032:   ai = a->i; aj = a->j; bi = b->i; bj = b->j;
5033:   aa = a->a; ba = b->a;
5034:   if (scall == MAT_INITIAL_MATRIX) {
5035:     if (size == 1) {
5036:       MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);
5037:       return(0);
5038:     }

5040:     PetscMalloc1(1+am,&ci);
5041:     ci[0] = 0;
5042:     for (i=0; i<am; i++) {
5043:       ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]);
5044:     }
5045:     PetscMalloc1(1+ci[am],&cj);
5046:     PetscMalloc1(1+ci[am],&ca);
5047:     k    = 0;
5048:     for (i=0; i<am; i++) {
5049:       ncols_o = bi[i+1] - bi[i];
5050:       ncols_d = ai[i+1] - ai[i];
5051:       /* off-diagonal portion of A */
5052:       for (jo=0; jo<ncols_o; jo++) {
5053:         col = cmap[*bj];
5054:         if (col >= cstart) break;
5055:         cj[k]   = col; bj++;
5056:         ca[k++] = *ba++;
5057:       }
5058:       /* diagonal portion of A */
5059:       for (j=0; j<ncols_d; j++) {
5060:         cj[k]   = cstart + *aj++;
5061:         ca[k++] = *aa++;
5062:       }
5063:       /* off-diagonal portion of A */
5064:       for (j=jo; j<ncols_o; j++) {
5065:         cj[k]   = cmap[*bj++];
5066:         ca[k++] = *ba++;
5067:       }
5068:     }
5069:     /* put together the new matrix */
5070:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);
5071:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5072:     /* Since these are PETSc arrays, change flags to free them as necessary. */
5073:     mat          = (Mat_SeqAIJ*)(*A_loc)->data;
5074:     mat->free_a  = PETSC_TRUE;
5075:     mat->free_ij = PETSC_TRUE;
5076:     mat->nonew   = 0;
5077:   } else if (scall == MAT_REUSE_MATRIX) {
5078:     mat=(Mat_SeqAIJ*)(*A_loc)->data;
5079:     ci = mat->i; cj = mat->j; cam = mat->a;
5080:     for (i=0; i<am; i++) {
5081:       /* off-diagonal portion of A */
5082:       ncols_o = bi[i+1] - bi[i];
5083:       for (jo=0; jo<ncols_o; jo++) {
5084:         col = cmap[*bj];
5085:         if (col >= cstart) break;
5086:         *cam++ = *ba++; bj++;
5087:       }
5088:       /* diagonal portion of A */
5089:       ncols_d = ai[i+1] - ai[i];
5090:       for (j=0; j<ncols_d; j++) *cam++ = *aa++;
5091:       /* off-diagonal portion of A */
5092:       for (j=jo; j<ncols_o; j++) {
5093:         *cam++ = *ba++; bj++;
5094:       }
5095:     }
5096:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
5097:   PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);
5098:   return(0);
5099: }

5101: /*@C
5102:      MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns

5104:     Not Collective

5106:    Input Parameters:
5107: +    A - the matrix
5108: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5109: -    row, col - index sets of rows and columns to extract (or NULL)

5111:    Output Parameter:
5112: .    A_loc - the local sequential matrix generated

5114:     Level: developer

5116: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat()

5118: @*/
5119: PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
5120: {
5121:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
5123:   PetscInt       i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
5124:   IS             isrowa,iscola;
5125:   Mat            *aloc;
5126:   PetscBool      match;

5129:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
5130:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
5131:   PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
5132:   if (!row) {
5133:     start = A->rmap->rstart; end = A->rmap->rend;
5134:     ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
5135:   } else {
5136:     isrowa = *row;
5137:   }
5138:   if (!col) {
5139:     start = A->cmap->rstart;
5140:     cmap  = a->garray;
5141:     nzA   = a->A->cmap->n;
5142:     nzB   = a->B->cmap->n;
5143:     PetscMalloc1(nzA+nzB, &idx);
5144:     ncols = 0;
5145:     for (i=0; i<nzB; i++) {
5146:       if (cmap[i] < start) idx[ncols++] = cmap[i];
5147:       else break;
5148:     }
5149:     imark = i;
5150:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;
5151:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
5152:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
5153:   } else {
5154:     iscola = *col;
5155:   }
5156:   if (scall != MAT_INITIAL_MATRIX) {
5157:     PetscMalloc1(1,&aloc);
5158:     aloc[0] = *A_loc;
5159:   }
5160:   MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
5161:   if (!col) { /* attach global id of condensed columns */
5162:     PetscObjectCompose((PetscObject)aloc[0],"_petsc_GetLocalMatCondensed_iscol",(PetscObject)iscola);
5163:   }
5164:   *A_loc = aloc[0];
5165:   PetscFree(aloc);
5166:   if (!row) {
5167:     ISDestroy(&isrowa);
5168:   }
5169:   if (!col) {
5170:     ISDestroy(&iscola);
5171:   }
5172:   PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
5173:   return(0);
5174: }

5176: /*@C
5177:     MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A

5179:     Collective on Mat

5181:    Input Parameters:
5182: +    A,B - the matrices in mpiaij format
5183: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5184: -    rowb, colb - index sets of rows and columns of B to extract (or NULL)

5186:    Output Parameter:
5187: +    rowb, colb - index sets of rows and columns of B to extract
5188: -    B_seq - the sequential matrix generated

5190:     Level: developer

5192: @*/
5193: PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq)
5194: {
5195:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
5197:   PetscInt       *idx,i,start,ncols,nzA,nzB,*cmap,imark;
5198:   IS             isrowb,iscolb;
5199:   Mat            *bseq=NULL;

5202:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5203:     SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend);
5204:   }
5205:   PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);

5207:   if (scall == MAT_INITIAL_MATRIX) {
5208:     start = A->cmap->rstart;
5209:     cmap  = a->garray;
5210:     nzA   = a->A->cmap->n;
5211:     nzB   = a->B->cmap->n;
5212:     PetscMalloc1(nzA+nzB, &idx);
5213:     ncols = 0;
5214:     for (i=0; i<nzB; i++) {  /* row < local row index */
5215:       if (cmap[i] < start) idx[ncols++] = cmap[i];
5216:       else break;
5217:     }
5218:     imark = i;
5219:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;  /* local rows */
5220:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */
5221:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);
5222:     ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);
5223:   } else {
5224:     if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX");
5225:     isrowb  = *rowb; iscolb = *colb;
5226:     PetscMalloc1(1,&bseq);
5227:     bseq[0] = *B_seq;
5228:   }
5229:   MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);
5230:   *B_seq = bseq[0];
5231:   PetscFree(bseq);
5232:   if (!rowb) {
5233:     ISDestroy(&isrowb);
5234:   } else {
5235:     *rowb = isrowb;
5236:   }
5237:   if (!colb) {
5238:     ISDestroy(&iscolb);
5239:   } else {
5240:     *colb = iscolb;
5241:   }
5242:   PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);
5243:   return(0);
5244: }

5246: /*
5247:     MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns
5248:     of the OFF-DIAGONAL portion of local A

5250:     Collective on Mat

5252:    Input Parameters:
5253: +    A,B - the matrices in mpiaij format
5254: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

5256:    Output Parameter:
5257: +    startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL)
5258: .    startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL)
5259: .    bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL)
5260: -    B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N

5262:     Developer Notes: This directly accesses information inside the VecScatter associated with the matrix-vector product
5263:      for this matrix. This is not desirable..

5265:     Level: developer

5267: */
5268: PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth)
5269: {
5270:   PetscErrorCode         ierr;
5271:   Mat_MPIAIJ             *a=(Mat_MPIAIJ*)A->data;
5272:   Mat_SeqAIJ             *b_oth;
5273:   VecScatter             ctx;
5274:   MPI_Comm               comm;
5275:   const PetscMPIInt      *rprocs,*sprocs;
5276:   const PetscInt         *srow,*rstarts,*sstarts;
5277:   PetscInt               *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj,*rvalues=NULL,*svalues=NULL,*cols,sbs,rbs;
5278:   PetscInt               i,j,k=0,l,ll,nrecvs,nsends,nrows,*rstartsj = 0,*sstartsj,len;
5279:   PetscScalar              *b_otha,*bufa,*bufA,*vals;
5280:   MPI_Request            *rwaits = NULL,*swaits = NULL;
5281:   MPI_Status             rstatus;
5282:   PetscMPIInt            jj,size,tag,rank,nsends_mpi,nrecvs_mpi;

5285:   PetscObjectGetComm((PetscObject)A,&comm);
5286:   MPI_Comm_size(comm,&size);

5288:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5289:     SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%d, %d) != (%d,%d)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend);
5290:   }
5291:   PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);
5292:   MPI_Comm_rank(comm,&rank);

5294:   if (size == 1) {
5295:     startsj_s = NULL;
5296:     bufa_ptr  = NULL;
5297:     *B_oth    = NULL;
5298:     return(0);
5299:   }

5301:   ctx = a->Mvctx;
5302:   tag = ((PetscObject)ctx)->tag;

5304:   if (ctx->inuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE," Scatter ctx already in use");
5305:   VecScatterGetRemote_Private(ctx,PETSC_TRUE/*send*/,&nsends,&sstarts,&srow,&sprocs,&sbs);
5306:   /* rprocs[] must be ordered so that indices received from them are ordered in rvalues[], which is key to algorithms used in this subroutine */
5307:   VecScatterGetRemoteOrdered_Private(ctx,PETSC_FALSE/*recv*/,&nrecvs,&rstarts,NULL/*indices not needed*/,&rprocs,&rbs);
5308:   PetscMPIIntCast(nsends,&nsends_mpi);
5309:   PetscMPIIntCast(nrecvs,&nrecvs_mpi);
5310:   PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);

5312:   if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX;
5313:   if (scall == MAT_INITIAL_MATRIX) {
5314:     /* i-array */
5315:     /*---------*/
5316:     /*  post receives */
5317:     if (nrecvs) {PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);} /* rstarts can be NULL when nrecvs=0 */
5318:     for (i=0; i<nrecvs; i++) {
5319:       rowlen = rvalues + rstarts[i]*rbs;
5320:       nrows  = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */
5321:       MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5322:     }

5324:     /* pack the outgoing message */
5325:     PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);

5327:     sstartsj[0] = 0;
5328:     rstartsj[0] = 0;
5329:     len         = 0; /* total length of j or a array to be sent */
5330:     if (nsends) {
5331:       k    = sstarts[0]; /* ATTENTION: sstarts[0] and rstarts[0] are not necessarily zero */
5332:       PetscMalloc1(sbs*(sstarts[nsends]-sstarts[0]),&svalues);
5333:     }
5334:     for (i=0; i<nsends; i++) {
5335:       rowlen = svalues + (sstarts[i]-sstarts[0])*sbs;
5336:       nrows  = sstarts[i+1]-sstarts[i]; /* num of block rows */
5337:       for (j=0; j<nrows; j++) {
5338:         row = srow[k] + B->rmap->range[rank]; /* global row idx */
5339:         for (l=0; l<sbs; l++) {
5340:           MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL); /* rowlength */

5342:           rowlen[j*sbs+l] = ncols;

5344:           len += ncols;
5345:           MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);
5346:         }
5347:         k++;
5348:       }
5349:       MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);

5351:       sstartsj[i+1] = len;  /* starting point of (i+1)-th outgoing msg in bufj and bufa */
5352:     }
5353:     /* recvs and sends of i-array are completed */
5354:     i = nrecvs;
5355:     while (i--) {
5356:       MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5357:     }
5358:     if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5359:     PetscFree(svalues);

5361:     /* allocate buffers for sending j and a arrays */
5362:     PetscMalloc1(len+1,&bufj);
5363:     PetscMalloc1(len+1,&bufa);

5365:     /* create i-array of B_oth */
5366:     PetscMalloc1(aBn+2,&b_othi);

5368:     b_othi[0] = 0;
5369:     len       = 0; /* total length of j or a array to be received */
5370:     k         = 0;
5371:     for (i=0; i<nrecvs; i++) {
5372:       rowlen = rvalues + (rstarts[i]-rstarts[0])*rbs;
5373:       nrows  = (rstarts[i+1]-rstarts[i])*rbs; /* num of rows to be received */
5374:       for (j=0; j<nrows; j++) {
5375:         b_othi[k+1] = b_othi[k] + rowlen[j];
5376:         PetscIntSumError(rowlen[j],len,&len);
5377:         k++;
5378:       }
5379:       rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */
5380:     }
5381:     PetscFree(rvalues);

5383:     /* allocate space for j and a arrrays of B_oth */
5384:     PetscMalloc1(b_othi[aBn]+1,&b_othj);
5385:     PetscMalloc1(b_othi[aBn]+1,&b_otha);

5387:     /* j-array */
5388:     /*---------*/
5389:     /*  post receives of j-array */
5390:     for (i=0; i<nrecvs; i++) {
5391:       nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5392:       MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5393:     }

5395:     /* pack the outgoing message j-array */
5396:     if (nsends) k = sstarts[0];
5397:     for (i=0; i<nsends; i++) {
5398:       nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5399:       bufJ  = bufj+sstartsj[i];
5400:       for (j=0; j<nrows; j++) {
5401:         row = srow[k++] + B->rmap->range[rank];  /* global row idx */
5402:         for (ll=0; ll<sbs; ll++) {
5403:           MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5404:           for (l=0; l<ncols; l++) {
5405:             *bufJ++ = cols[l];
5406:           }
5407:           MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5408:         }
5409:       }
5410:       MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);
5411:     }

5413:     /* recvs and sends of j-array are completed */
5414:     i = nrecvs;
5415:     while (i--) {
5416:       MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5417:     }
5418:     if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5419:   } else if (scall == MAT_REUSE_MATRIX) {
5420:     sstartsj = *startsj_s;
5421:     rstartsj = *startsj_r;
5422:     bufa     = *bufa_ptr;
5423:     b_oth    = (Mat_SeqAIJ*)(*B_oth)->data;
5424:     b_otha   = b_oth->a;
5425:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container");

5427:   /* a-array */
5428:   /*---------*/
5429:   /*  post receives of a-array */
5430:   for (i=0; i<nrecvs; i++) {
5431:     nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5432:     MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);
5433:   }

5435:   /* pack the outgoing message a-array */
5436:   if (nsends) k = sstarts[0];
5437:   for (i=0; i<nsends; i++) {
5438:     nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5439:     bufA  = bufa+sstartsj[i];
5440:     for (j=0; j<nrows; j++) {
5441:       row = srow[k++] + B->rmap->range[rank];  /* global row idx */
5442:       for (ll=0; ll<sbs; ll++) {
5443:         MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5444:         for (l=0; l<ncols; l++) {
5445:           *bufA++ = vals[l];
5446:         }
5447:         MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5448:       }
5449:     }
5450:     MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);
5451:   }
5452:   /* recvs and sends of a-array are completed */
5453:   i = nrecvs;
5454:   while (i--) {
5455:     MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5456:   }
5457:   if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5458:   PetscFree2(rwaits,swaits);

5460:   if (scall == MAT_INITIAL_MATRIX) {
5461:     /* put together the new matrix */
5462:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);

5464:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5465:     /* Since these are PETSc arrays, change flags to free them as necessary. */
5466:     b_oth          = (Mat_SeqAIJ*)(*B_oth)->data;
5467:     b_oth->free_a  = PETSC_TRUE;
5468:     b_oth->free_ij = PETSC_TRUE;
5469:     b_oth->nonew   = 0;

5471:     PetscFree(bufj);
5472:     if (!startsj_s || !bufa_ptr) {
5473:       PetscFree2(sstartsj,rstartsj);
5474:       PetscFree(bufa_ptr);
5475:     } else {
5476:       *startsj_s = sstartsj;
5477:       *startsj_r = rstartsj;
5478:       *bufa_ptr  = bufa;
5479:     }
5480:   }

5482:   VecScatterRestoreRemote_Private(ctx,PETSC_TRUE,&nsends,&sstarts,&srow,&sprocs,&sbs);
5483:   VecScatterRestoreRemoteOrdered_Private(ctx,PETSC_FALSE,&nrecvs,&rstarts,NULL,&rprocs,&rbs);
5484:   PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);
5485:   return(0);
5486: }

5488: /*@C
5489:   MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication.

5491:   Not Collective

5493:   Input Parameters:
5494: . A - The matrix in mpiaij format

5496:   Output Parameter:
5497: + lvec - The local vector holding off-process values from the argument to a matrix-vector product
5498: . colmap - A map from global column index to local index into lvec
5499: - multScatter - A scatter from the argument of a matrix-vector product to lvec

5501:   Level: developer

5503: @*/
5504: #if defined(PETSC_USE_CTABLE)
5505: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter)
5506: #else
5507: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter)
5508: #endif
5509: {
5510:   Mat_MPIAIJ *a;

5517:   a = (Mat_MPIAIJ*) A->data;
5518:   if (lvec) *lvec = a->lvec;
5519:   if (colmap) *colmap = a->colmap;
5520:   if (multScatter) *multScatter = a->Mvctx;
5521:   return(0);
5522: }

5524: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*);
5525: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*);
5526: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJSELL(Mat,MatType,MatReuse,Mat*);
5527: #if defined(PETSC_HAVE_MKL_SPARSE)
5528: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJMKL(Mat,MatType,MatReuse,Mat*);
5529: #endif
5530: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*);
5531: #if defined(PETSC_HAVE_ELEMENTAL)
5532: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
5533: #endif
5534: #if defined(PETSC_HAVE_HYPRE)
5535: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
5536: PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*);
5537: #endif
5538: PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*);
5539: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISELL(Mat,MatType,MatReuse,Mat*);
5540: PETSC_INTERN PetscErrorCode MatPtAP_IS_XAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);

5542: /*
5543:     Computes (B'*A')' since computing B*A directly is untenable

5545:                n                       p                          p
5546:         (              )       (              )         (                  )
5547:       m (      A       )  *  n (       B      )   =   m (         C        )
5548:         (              )       (              )         (                  )

5550: */
5551: PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C)
5552: {
5554:   Mat            At,Bt,Ct;

5557:   MatTranspose(A,MAT_INITIAL_MATRIX,&At);
5558:   MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);
5559:   MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);
5560:   MatDestroy(&At);
5561:   MatDestroy(&Bt);
5562:   MatTranspose(Ct,MAT_REUSE_MATRIX,&C);
5563:   MatDestroy(&Ct);
5564:   return(0);
5565: }

5567: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
5568: {
5570:   PetscInt       m=A->rmap->n,n=B->cmap->n;
5571:   Mat            Cmat;

5574:   if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n);
5575:   MatCreate(PetscObjectComm((PetscObject)A),&Cmat);
5576:   MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
5577:   MatSetBlockSizesFromMats(Cmat,A,B);
5578:   MatSetType(Cmat,MATMPIDENSE);
5579:   MatMPIDenseSetPreallocation(Cmat,NULL);
5580:   MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);
5581:   MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);

5583:   Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ;

5585:   *C = Cmat;
5586:   return(0);
5587: }

5589: /* ----------------------------------------------------------------*/
5590: PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
5591: {

5595:   if (scall == MAT_INITIAL_MATRIX) {
5596:     PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);
5597:     MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);
5598:     PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);
5599:   }
5600:   PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);
5601:   MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);
5602:   PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);
5603:   return(0);
5604: }

5606: /*MC
5607:    MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices.

5609:    Options Database Keys:
5610: . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions()

5612:   Level: beginner

5614: .seealso: MatCreateAIJ()
5615: M*/

5617: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B)
5618: {
5619:   Mat_MPIAIJ     *b;
5621:   PetscMPIInt    size;

5624:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);

5626:   PetscNewLog(B,&b);
5627:   B->data       = (void*)b;
5628:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
5629:   B->assembled  = PETSC_FALSE;
5630:   B->insertmode = NOT_SET_VALUES;
5631:   b->size       = size;

5633:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);

5635:   /* build cache for off array entries formed */
5636:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

5638:   b->donotstash  = PETSC_FALSE;
5639:   b->colmap      = 0;
5640:   b->garray      = 0;
5641:   b->roworiented = PETSC_TRUE;

5643:   /* stuff used for matrix vector multiply */
5644:   b->lvec  = NULL;
5645:   b->Mvctx = NULL;

5647:   /* stuff for MatGetRow() */
5648:   b->rowindices   = 0;
5649:   b->rowvalues    = 0;
5650:   b->getrowactive = PETSC_FALSE;

5652:   /* flexible pointer used in CUSP/CUSPARSE classes */
5653:   b->spptr = NULL;

5655:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);
5656:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);
5657:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);
5658:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);
5659:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);
5660:   PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_MPIAIJ);
5661:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);
5662:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);
5663:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);
5664:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijsell_C",MatConvert_MPIAIJ_MPIAIJSELL);
5665: #if defined(PETSC_HAVE_MKL_SPARSE)
5666:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijmkl_C",MatConvert_MPIAIJ_MPIAIJMKL);
5667: #endif
5668:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);
5669:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);
5670: #if defined(PETSC_HAVE_ELEMENTAL)
5671:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);
5672: #endif
5673: #if defined(PETSC_HAVE_HYPRE)
5674:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);
5675: #endif
5676:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_XAIJ_IS);
5677:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisell_C",MatConvert_MPIAIJ_MPISELL);
5678:   PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);
5679:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);
5680:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);
5681: #if defined(PETSC_HAVE_HYPRE)
5682:   PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);
5683: #endif
5684:   PetscObjectComposeFunction((PetscObject)B,"MatPtAP_is_mpiaij_C",MatPtAP_IS_XAIJ);
5685:   PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);
5686:   return(0);
5687: }

5689: /*@C
5690:      MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal"
5691:          and "off-diagonal" part of the matrix in CSR format.

5693:    Collective on MPI_Comm

5695:    Input Parameters:
5696: +  comm - MPI communicator
5697: .  m - number of local rows (Cannot be PETSC_DECIDE)
5698: .  n - This value should be the same as the local size used in creating the
5699:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
5700:        calculated if N is given) For square matrices n is almost always m.
5701: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
5702: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
5703: .   i - row indices for "diagonal" portion of matrix; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix
5704: .   j - column indices
5705: .   a - matrix values
5706: .   oi - row indices for "off-diagonal" portion of matrix; that is oi[0] = 0, oi[row] = oi[row-1] + number of elements in that row of the matrix
5707: .   oj - column indices
5708: -   oa - matrix values

5710:    Output Parameter:
5711: .   mat - the matrix

5713:    Level: advanced

5715:    Notes:
5716:        The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user
5717:        must free the arrays once the matrix has been destroyed and not before.

5719:        The i and j indices are 0 based

5721:        See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix

5723:        This sets local rows and cannot be used to set off-processor values.

5725:        Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a
5726:        legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does
5727:        not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because
5728:        the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to
5729:        keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all
5730:        communication if it is known that only local entries will be set.

5732: .keywords: matrix, aij, compressed row, sparse, parallel

5734: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
5735:           MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays()
5736: @*/
5737: PetscErrorCode MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[],PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat)
5738: {
5740:   Mat_MPIAIJ     *maij;

5743:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
5744:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
5745:   if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0");
5746:   MatCreate(comm,mat);
5747:   MatSetSizes(*mat,m,n,M,N);
5748:   MatSetType(*mat,MATMPIAIJ);
5749:   maij = (Mat_MPIAIJ*) (*mat)->data;

5751:   (*mat)->preallocated = PETSC_TRUE;

5753:   PetscLayoutSetUp((*mat)->rmap);
5754:   PetscLayoutSetUp((*mat)->cmap);

5756:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);
5757:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);

5759:   MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);
5760:   MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);
5761:   MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);
5762:   MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);

5764:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
5765:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
5766:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
5767:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
5768:   MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
5769:   return(0);
5770: }

5772: /*
5773:     Special version for direct calls from Fortran
5774: */
5775:  #include <petsc/private/fortranimpl.h>

5777: /* Change these macros so can be used in void function */
5778: #undef CHKERRQ
5779: #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr)
5780: #undef SETERRQ2
5781: #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr)
5782: #undef SETERRQ3
5783: #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr)
5784: #undef SETERRQ
5785: #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr)

5787: #if defined(PETSC_HAVE_FORTRAN_CAPS)
5788: #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ
5789: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
5790: #define matsetvaluesmpiaij_ matsetvaluesmpiaij
5791: #else
5792: #endif
5793: PETSC_EXTERN void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr)
5794: {
5795:   Mat            mat  = *mmat;
5796:   PetscInt       m    = *mm, n = *mn;
5797:   InsertMode     addv = *maddv;
5798:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
5799:   PetscScalar    value;

5802:   MatCheckPreallocated(mat,1);
5803:   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;

5805: #if defined(PETSC_USE_DEBUG)
5806:   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
5807: #endif
5808:   {
5809:     PetscInt  i,j,rstart  = mat->rmap->rstart,rend = mat->rmap->rend;
5810:     PetscInt  cstart      = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
5811:     PetscBool roworiented = aij->roworiented;

5813:     /* Some Variables required in the macro */
5814:     Mat        A                 = aij->A;
5815:     Mat_SeqAIJ *a                = (Mat_SeqAIJ*)A->data;
5816:     PetscInt   *aimax            = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
5817:     MatScalar  *aa               = a->a;
5818:     PetscBool  ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE);
5819:     Mat        B                 = aij->B;
5820:     Mat_SeqAIJ *b                = (Mat_SeqAIJ*)B->data;
5821:     PetscInt   *bimax            = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
5822:     MatScalar  *ba               = b->a;

5824:     PetscInt  *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
5825:     PetscInt  nonew = a->nonew;
5826:     MatScalar *ap1,*ap2;

5829:     for (i=0; i<m; i++) {
5830:       if (im[i] < 0) continue;
5831: #if defined(PETSC_USE_DEBUG)
5832:       if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
5833: #endif
5834:       if (im[i] >= rstart && im[i] < rend) {
5835:         row      = im[i] - rstart;
5836:         lastcol1 = -1;
5837:         rp1      = aj + ai[row];
5838:         ap1      = aa + ai[row];
5839:         rmax1    = aimax[row];
5840:         nrow1    = ailen[row];
5841:         low1     = 0;
5842:         high1    = nrow1;
5843:         lastcol2 = -1;
5844:         rp2      = bj + bi[row];
5845:         ap2      = ba + bi[row];
5846:         rmax2    = bimax[row];
5847:         nrow2    = bilen[row];
5848:         low2     = 0;
5849:         high2    = nrow2;

5851:         for (j=0; j<n; j++) {
5852:           if (roworiented) value = v[i*n+j];
5853:           else value = v[i+j*m];
5854:           if (in[j] >= cstart && in[j] < cend) {
5855:             col = in[j] - cstart;
5856:             if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
5857:             MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
5858:           } else if (in[j] < 0) continue;
5859: #if defined(PETSC_USE_DEBUG)
5860:           /* extra brace on SETERRQ2() is required for --with-errorchecking=0 - due to the next 'else' clause */
5861:           else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);}
5862: #endif
5863:           else {
5864:             if (mat->was_assembled) {
5865:               if (!aij->colmap) {
5866:                 MatCreateColmap_MPIAIJ_Private(mat);
5867:               }
5868: #if defined(PETSC_USE_CTABLE)
5869:               PetscTableFind(aij->colmap,in[j]+1,&col);
5870:               col--;
5871: #else
5872:               col = aij->colmap[in[j]] - 1;
5873: #endif
5874:               if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
5875:               if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
5876:                 MatDisAssemble_MPIAIJ(mat);
5877:                 col  =  in[j];
5878:                 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
5879:                 B     = aij->B;
5880:                 b     = (Mat_SeqAIJ*)B->data;
5881:                 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
5882:                 rp2   = bj + bi[row];
5883:                 ap2   = ba + bi[row];
5884:                 rmax2 = bimax[row];
5885:                 nrow2 = bilen[row];
5886:                 low2  = 0;
5887:                 high2 = nrow2;
5888:                 bm    = aij->B->rmap->n;
5889:                 ba    = b->a;
5890:               }
5891:             } else col = in[j];
5892:             MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
5893:           }
5894:         }
5895:       } else if (!aij->donotstash) {
5896:         if (roworiented) {
5897:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5898:         } else {
5899:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5900:         }
5901:       }
5902:     }
5903:   }
5904:   PetscFunctionReturnVoid();
5905: }