Actual source code: mpiaij.c

petsc-3.9.3 2018-07-02
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  3:  #include <../src/mat/impls/aij/mpi/mpiaij.h>
  4:  #include <petsc/private/vecimpl.h>
  5:  #include <petsc/private/isimpl.h>
  6:  #include <petscblaslapack.h>
  7:  #include <petscsf.h>

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

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

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

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

 24:   Level: beginner

 26: .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ, MATMPIAIJ
 27: M*/

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

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

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

 41:   Level: beginner

 43: .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL
 44: M*/

 46: PetscErrorCode MatSetBlockSizes_MPIAIJ(Mat M, PetscInt rbs, PetscInt cbs)
 47: {
 49:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)M->data;

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

 59: PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows)
 60: {
 61:   PetscErrorCode  ierr;
 62:   Mat_MPIAIJ      *mat = (Mat_MPIAIJ*)M->data;
 63:   Mat_SeqAIJ      *a   = (Mat_SeqAIJ*)mat->A->data;
 64:   Mat_SeqAIJ      *b   = (Mat_SeqAIJ*)mat->B->data;
 65:   const PetscInt  *ia,*ib;
 66:   const MatScalar *aa,*bb;
 67:   PetscInt        na,nb,i,j,*rows,cnt=0,n0rows;
 68:   PetscInt        m = M->rmap->n,rstart = M->rmap->rstart;

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

120: PetscErrorCode  MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is)
121: {
122:   PetscErrorCode    ierr;
123:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*) Y->data;

126:   if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) {
127:     MatDiagonalSet(aij->A,D,is);
128:   } else {
129:     MatDiagonalSet_Default(Y,D,is);
130:   }
131:   return(0);
132: }

134: PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows)
135: {
136:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)M->data;
138:   PetscInt       i,rstart,nrows,*rows;

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

149: PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms)
150: {
152:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)A->data;
153:   PetscInt       i,n,*garray = aij->garray;
154:   Mat_SeqAIJ     *a_aij = (Mat_SeqAIJ*) aij->A->data;
155:   Mat_SeqAIJ     *b_aij = (Mat_SeqAIJ*) aij->B->data;
156:   PetscReal      *work;

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

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

196: PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is)
197: {
198:   Mat_MPIAIJ      *a  = (Mat_MPIAIJ*)A->data;
199:   IS              sis,gis;
200:   PetscErrorCode  ierr;
201:   const PetscInt  *isis,*igis;
202:   PetscInt        n,*iis,nsis,ngis,rstart,i;

205:   MatFindOffBlockDiagonalEntries(a->A,&sis);
206:   MatFindNonzeroRows(a->B,&gis);
207:   ISGetSize(gis,&ngis);
208:   ISGetSize(sis,&nsis);
209:   ISGetIndices(sis,&isis);
210:   ISGetIndices(gis,&igis);

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

221:   ISRestoreIndices(sis,&isis);
222:   ISRestoreIndices(gis,&igis);
223:   ISDestroy(&sis);
224:   ISDestroy(&gis);
225:   return(0);
226: }

228: /*
229:     Distributes a SeqAIJ matrix across a set of processes. Code stolen from
230:     MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type.

232:     Only for square matrices

234:     Used by a preconditioner, hence PETSC_EXTERN
235: */
236: PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat)
237: {
238:   PetscMPIInt    rank,size;
239:   PetscInt       *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2];
241:   Mat            mat;
242:   Mat_SeqAIJ     *gmata;
243:   PetscMPIInt    tag;
244:   MPI_Status     status;
245:   PetscBool      aij;
246:   MatScalar      *gmataa,*ao,*ad,*gmataarestore=0;

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

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

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

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

333:     for (i=0; i<m; i++) {
334:       dlens[i] += olens[i];
335:     }
336:     cnt = 0;
337:     for (i=0; i<m; i++) {
338:       row  = rstart + i;
339:       MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);
340:       cnt += dlens[i];
341:     }
342:     if (rank) {
343:       PetscFree2(gmataa,gmataj);
344:     }
345:     PetscFree2(dlens,olens);
346:     PetscFree(rowners);

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

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

398: /*
399:   Local utility routine that creates a mapping from the global column
400: number to the local number in the off-diagonal part of the local
401: storage of the matrix.  When PETSC_USE_CTABLE is used this is scalable at
402: a slightly higher hash table cost; without it it is not scalable (each processor
403: has an order N integer array but is fast to acess.
404: */
405: PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat)
406: {
407:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
409:   PetscInt       n = aij->B->cmap->n,i;

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

426: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol)     \
427: { \
428:     if (col <= lastcol1)  low1 = 0;     \
429:     else                 high1 = nrow1; \
430:     lastcol1 = col;\
431:     while (high1-low1 > 5) { \
432:       t = (low1+high1)/2; \
433:       if (rp1[t] > col) high1 = t; \
434:       else              low1  = t; \
435:     } \
436:       for (_i=low1; _i<high1; _i++) { \
437:         if (rp1[_i] > col) break; \
438:         if (rp1[_i] == col) { \
439:           if (addv == ADD_VALUES) ap1[_i] += value;   \
440:           else                    ap1[_i] = value; \
441:           goto a_noinsert; \
442:         } \
443:       }  \
444:       if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
445:       if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;}                \
446:       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); \
447:       MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
448:       N = nrow1++ - 1; a->nz++; high1++; \
449:       /* shift up all the later entries in this row */ \
450:       for (ii=N; ii>=_i; ii--) { \
451:         rp1[ii+1] = rp1[ii]; \
452:         ap1[ii+1] = ap1[ii]; \
453:       } \
454:       rp1[_i] = col;  \
455:       ap1[_i] = value;  \
456:       A->nonzerostate++;\
457:       a_noinsert: ; \
458:       ailen[row] = nrow1; \
459: }

461: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \
462:   { \
463:     if (col <= lastcol2) low2 = 0;                        \
464:     else high2 = nrow2;                                   \
465:     lastcol2 = col;                                       \
466:     while (high2-low2 > 5) {                              \
467:       t = (low2+high2)/2;                                 \
468:       if (rp2[t] > col) high2 = t;                        \
469:       else             low2  = t;                         \
470:     }                                                     \
471:     for (_i=low2; _i<high2; _i++) {                       \
472:       if (rp2[_i] > col) break;                           \
473:       if (rp2[_i] == col) {                               \
474:         if (addv == ADD_VALUES) ap2[_i] += value;         \
475:         else                    ap2[_i] = value;          \
476:         goto b_noinsert;                                  \
477:       }                                                   \
478:     }                                                     \
479:     if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
480:     if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;}                        \
481:     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); \
482:     MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
483:     N = nrow2++ - 1; b->nz++; high2++;                    \
484:     /* shift up all the later entries in this row */      \
485:     for (ii=N; ii>=_i; ii--) {                            \
486:       rp2[ii+1] = rp2[ii];                                \
487:       ap2[ii+1] = ap2[ii];                                \
488:     }                                                     \
489:     rp2[_i] = col;                                        \
490:     ap2[_i] = value;                                      \
491:     B->nonzerostate++;                                    \
492:     b_noinsert: ;                                         \
493:     bilen[row] = nrow2;                                   \
494:   }

496: PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[])
497: {
498:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)A->data;
499:   Mat_SeqAIJ     *a   = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data;
501:   PetscInt       l,*garray = mat->garray,diag;

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

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

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

517:   /* right of diagonal part */
518:   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));
519:   return(0);
520: }

522: PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
523: {
524:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
525:   PetscScalar    value;
527:   PetscInt       i,j,rstart  = mat->rmap->rstart,rend = mat->rmap->rend;
528:   PetscInt       cstart      = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
529:   PetscBool      roworiented = aij->roworiented;

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

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

547:   for (i=0; i<m; i++) {
548:     if (im[i] < 0) continue;
549: #if defined(PETSC_USE_DEBUG)
550:     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);
551: #endif
552:     if (im[i] >= rstart && im[i] < rend) {
553:       row      = im[i] - rstart;
554:       lastcol1 = -1;
555:       rp1      = aj + ai[row];
556:       ap1      = aa + ai[row];
557:       rmax1    = aimax[row];
558:       nrow1    = ailen[row];
559:       low1     = 0;
560:       high1    = nrow1;
561:       lastcol2 = -1;
562:       rp2      = bj + bi[row];
563:       ap2      = ba + bi[row];
564:       rmax2    = bimax[row];
565:       nrow2    = bilen[row];
566:       low2     = 0;
567:       high2    = nrow2;

569:       for (j=0; j<n; j++) {
570:         if (roworiented) value = v[i*n+j];
571:         else             value = v[i+j*m];
572:         if (in[j] >= cstart && in[j] < cend) {
573:           col   = in[j] - cstart;
574:           nonew = a->nonew;
575:           if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
576:           MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
577:         } else if (in[j] < 0) continue;
578: #if defined(PETSC_USE_DEBUG)
579:         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);
580: #endif
581:         else {
582:           if (mat->was_assembled) {
583:             if (!aij->colmap) {
584:               MatCreateColmap_MPIAIJ_Private(mat);
585:             }
586: #if defined(PETSC_USE_CTABLE)
587:             PetscTableFind(aij->colmap,in[j]+1,&col);
588:             col--;
589: #else
590:             col = aij->colmap[in[j]] - 1;
591: #endif
592:             if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) {
593:               MatDisAssemble_MPIAIJ(mat);
594:               col  =  in[j];
595:               /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
596:               B     = aij->B;
597:               b     = (Mat_SeqAIJ*)B->data;
598:               bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a;
599:               rp2   = bj + bi[row];
600:               ap2   = ba + bi[row];
601:               rmax2 = bimax[row];
602:               nrow2 = bilen[row];
603:               low2  = 0;
604:               high2 = nrow2;
605:               bm    = aij->B->rmap->n;
606:               ba    = b->a;
607:             } else if (col < 0) {
608:               if (1 == ((Mat_SeqAIJ*)(aij->B->data))->nonew) {
609:                 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]);
610:               } 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]);
611:             }
612:           } else col = in[j];
613:           nonew = b->nonew;
614:           MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
615:         }
616:       }
617:     } else {
618:       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]);
619:       if (!aij->donotstash) {
620:         mat->assembled = PETSC_FALSE;
621:         if (roworiented) {
622:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
623:         } else {
624:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
625:         }
626:       }
627:     }
628:   }
629:   return(0);
630: }

632: PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
633: {
634:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
636:   PetscInt       i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
637:   PetscInt       cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;

640:   for (i=0; i<m; i++) {
641:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
642:     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);
643:     if (idxm[i] >= rstart && idxm[i] < rend) {
644:       row = idxm[i] - rstart;
645:       for (j=0; j<n; j++) {
646:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
647:         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);
648:         if (idxn[j] >= cstart && idxn[j] < cend) {
649:           col  = idxn[j] - cstart;
650:           MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
651:         } else {
652:           if (!aij->colmap) {
653:             MatCreateColmap_MPIAIJ_Private(mat);
654:           }
655: #if defined(PETSC_USE_CTABLE)
656:           PetscTableFind(aij->colmap,idxn[j]+1,&col);
657:           col--;
658: #else
659:           col = aij->colmap[idxn[j]] - 1;
660: #endif
661:           if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
662:           else {
663:             MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
664:           }
665:         }
666:       }
667:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
668:   }
669:   return(0);
670: }

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

674: PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode)
675: {
676:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
678:   PetscInt       nstash,reallocs;

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

683:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
684:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
685:   PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
686:   return(0);
687: }

689: PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode)
690: {
691:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
692:   Mat_SeqAIJ     *a   = (Mat_SeqAIJ*)aij->A->data;
694:   PetscMPIInt    n;
695:   PetscInt       i,j,rstart,ncols,flg;
696:   PetscInt       *row,*col;
697:   PetscBool      other_disassembled;
698:   PetscScalar    *val;

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

703:   if (!aij->donotstash && !mat->nooffprocentries) {
704:     while (1) {
705:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
706:       if (!flg) break;

708:       for (i=0; i<n; ) {
709:         /* Now identify the consecutive vals belonging to the same row */
710:         for (j=i,rstart=row[j]; j<n; j++) {
711:           if (row[j] != rstart) break;
712:         }
713:         if (j < n) ncols = j-i;
714:         else       ncols = n-i;
715:         /* Now assemble all these values with a single function call */
716:         MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);

718:         i = j;
719:       }
720:     }
721:     MatStashScatterEnd_Private(&mat->stash);
722:   }
723:   MatAssemblyBegin(aij->A,mode);
724:   MatAssemblyEnd(aij->A,mode);

726:   /* determine if any processor has disassembled, if so we must
727:      also disassemble ourselfs, in order that we may reassemble. */
728:   /*
729:      if nonzero structure of submatrix B cannot change then we know that
730:      no processor disassembled thus we can skip this stuff
731:   */
732:   if (!((Mat_SeqAIJ*)aij->B->data)->nonew) {
733:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
734:     if (mat->was_assembled && !other_disassembled) {
735:       MatDisAssemble_MPIAIJ(mat);
736:     }
737:   }
738:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
739:     MatSetUpMultiply_MPIAIJ(mat);
740:   }
741:   MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);
742:   MatAssemblyBegin(aij->B,mode);
743:   MatAssemblyEnd(aij->B,mode);

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

747:   aij->rowvalues = 0;

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

752:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
753:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
754:     PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate;
755:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
756:   }
757:   return(0);
758: }

760: PetscErrorCode MatZeroEntries_MPIAIJ(Mat A)
761: {
762:   Mat_MPIAIJ     *l = (Mat_MPIAIJ*)A->data;

766:   MatZeroEntries(l->A);
767:   MatZeroEntries(l->B);
768:   return(0);
769: }

771: PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
772: {
773:   Mat_MPIAIJ    *mat    = (Mat_MPIAIJ *) A->data;
774:   PetscInt      *lrows;
775:   PetscInt       r, len;

779:   /* get locally owned rows */
780:   MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);
781:   /* fix right hand side if needed */
782:   if (x && b) {
783:     const PetscScalar *xx;
784:     PetscScalar       *bb;

786:     VecGetArrayRead(x, &xx);
787:     VecGetArray(b, &bb);
788:     for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
789:     VecRestoreArrayRead(x, &xx);
790:     VecRestoreArray(b, &bb);
791:   }
792:   /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/
793:   MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
794:   if (A->congruentlayouts == -1) { /* first time we compare rows and cols layouts */
795:     PetscBool cong;
796:     PetscLayoutCompare(A->rmap,A->cmap,&cong);
797:     if (cong) A->congruentlayouts = 1;
798:     else      A->congruentlayouts = 0;
799:   }
800:   if ((diag != 0.0) && A->congruentlayouts) {
801:     MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);
802:   } else if (diag != 0.0) {
803:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
804:     if (((Mat_SeqAIJ *) mat->A->data)->nonew) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
805:     for (r = 0; r < len; ++r) {
806:       const PetscInt row = lrows[r] + A->rmap->rstart;
807:       MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);
808:     }
809:     MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
810:     MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);
811:   } else {
812:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
813:   }
814:   PetscFree(lrows);

816:   /* only change matrix nonzero state if pattern was allowed to be changed */
817:   if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) {
818:     PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate;
819:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
820:   }
821:   return(0);
822: }

824: PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
825: {
826:   Mat_MPIAIJ        *l = (Mat_MPIAIJ*)A->data;
827:   PetscErrorCode    ierr;
828:   PetscMPIInt       n = A->rmap->n;
829:   PetscInt          i,j,r,m,p = 0,len = 0;
830:   PetscInt          *lrows,*owners = A->rmap->range;
831:   PetscSFNode       *rrows;
832:   PetscSF           sf;
833:   const PetscScalar *xx;
834:   PetscScalar       *bb,*mask;
835:   Vec               xmask,lmask;
836:   Mat_SeqAIJ        *aij = (Mat_SeqAIJ*)l->B->data;
837:   const PetscInt    *aj, *ii,*ridx;
838:   PetscScalar       *aa;

841:   /* Create SF where leaves are input rows and roots are owned rows */
842:   PetscMalloc1(n, &lrows);
843:   for (r = 0; r < n; ++r) lrows[r] = -1;
844:   PetscMalloc1(N, &rrows);
845:   for (r = 0; r < N; ++r) {
846:     const PetscInt idx   = rows[r];
847:     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);
848:     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
849:       PetscLayoutFindOwner(A->rmap,idx,&p);
850:     }
851:     rrows[r].rank  = p;
852:     rrows[r].index = rows[r] - owners[p];
853:   }
854:   PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
855:   PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
856:   /* Collect flags for rows to be zeroed */
857:   PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
858:   PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
859:   PetscSFDestroy(&sf);
860:   /* Compress and put in row numbers */
861:   for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
862:   /* zero diagonal part of matrix */
863:   MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
864:   /* handle off diagonal part of matrix */
865:   MatCreateVecs(A,&xmask,NULL);
866:   VecDuplicate(l->lvec,&lmask);
867:   VecGetArray(xmask,&bb);
868:   for (i=0; i<len; i++) bb[lrows[i]] = 1;
869:   VecRestoreArray(xmask,&bb);
870:   VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
871:   VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
872:   VecDestroy(&xmask);
873:   if (x) {
874:     VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
875:     VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
876:     VecGetArrayRead(l->lvec,&xx);
877:     VecGetArray(b,&bb);
878:   }
879:   VecGetArray(lmask,&mask);
880:   /* remove zeroed rows of off diagonal matrix */
881:   ii = aij->i;
882:   for (i=0; i<len; i++) {
883:     PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));
884:   }
885:   /* loop over all elements of off process part of matrix zeroing removed columns*/
886:   if (aij->compressedrow.use) {
887:     m    = aij->compressedrow.nrows;
888:     ii   = aij->compressedrow.i;
889:     ridx = aij->compressedrow.rindex;
890:     for (i=0; i<m; i++) {
891:       n  = ii[i+1] - ii[i];
892:       aj = aij->j + ii[i];
893:       aa = aij->a + ii[i];

895:       for (j=0; j<n; j++) {
896:         if (PetscAbsScalar(mask[*aj])) {
897:           if (b) bb[*ridx] -= *aa*xx[*aj];
898:           *aa = 0.0;
899:         }
900:         aa++;
901:         aj++;
902:       }
903:       ridx++;
904:     }
905:   } else { /* do not use compressed row format */
906:     m = l->B->rmap->n;
907:     for (i=0; i<m; i++) {
908:       n  = ii[i+1] - ii[i];
909:       aj = aij->j + ii[i];
910:       aa = aij->a + ii[i];
911:       for (j=0; j<n; j++) {
912:         if (PetscAbsScalar(mask[*aj])) {
913:           if (b) bb[i] -= *aa*xx[*aj];
914:           *aa = 0.0;
915:         }
916:         aa++;
917:         aj++;
918:       }
919:     }
920:   }
921:   if (x) {
922:     VecRestoreArray(b,&bb);
923:     VecRestoreArrayRead(l->lvec,&xx);
924:   }
925:   VecRestoreArray(lmask,&mask);
926:   VecDestroy(&lmask);
927:   PetscFree(lrows);

929:   /* only change matrix nonzero state if pattern was allowed to be changed */
930:   if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) {
931:     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
932:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
933:   }
934:   return(0);
935: }

937: PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy)
938: {
939:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
941:   PetscInt       nt;
942:   VecScatter     Mvctx = a->Mvctx;

945:   VecGetLocalSize(xx,&nt);
946:   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);

948:   VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
949:   (*a->A->ops->mult)(a->A,xx,yy);
950:   VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
951:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
952:   return(0);
953: }

955: PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx)
956: {
957:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

961:   MatMultDiagonalBlock(a->A,bb,xx);
962:   return(0);
963: }

965: PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
966: {
967:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
969:   VecScatter     Mvctx = a->Mvctx;

972:   if (a->Mvctx_mpi1_flg) Mvctx = a->Mvctx_mpi1;
973:   VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
974:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
975:   VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
976:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
977:   return(0);
978: }

980: PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy)
981: {
982:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
984:   PetscBool      merged;

987:   VecScatterGetMerged(a->Mvctx,&merged);
988:   /* do nondiagonal part */
989:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
990:   if (!merged) {
991:     /* send it on its way */
992:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
993:     /* do local part */
994:     (*a->A->ops->multtranspose)(a->A,xx,yy);
995:     /* receive remote parts: note this assumes the values are not actually */
996:     /* added in yy until the next line, */
997:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
998:   } else {
999:     /* do local part */
1000:     (*a->A->ops->multtranspose)(a->A,xx,yy);
1001:     /* send it on its way */
1002:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1003:     /* values actually were received in the Begin() but we need to call this nop */
1004:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1005:   }
1006:   return(0);
1007: }

1009: PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool  *f)
1010: {
1011:   MPI_Comm       comm;
1012:   Mat_MPIAIJ     *Aij = (Mat_MPIAIJ*) Amat->data, *Bij;
1013:   Mat            Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs;
1014:   IS             Me,Notme;
1016:   PetscInt       M,N,first,last,*notme,i;
1017:   PetscMPIInt    size;

1020:   /* Easy test: symmetric diagonal block */
1021:   Bij  = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A;
1022:   MatIsTranspose(Adia,Bdia,tol,f);
1023:   if (!*f) return(0);
1024:   PetscObjectGetComm((PetscObject)Amat,&comm);
1025:   MPI_Comm_size(comm,&size);
1026:   if (size == 1) return(0);

1028:   /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */
1029:   MatGetSize(Amat,&M,&N);
1030:   MatGetOwnershipRange(Amat,&first,&last);
1031:   PetscMalloc1(N-last+first,&notme);
1032:   for (i=0; i<first; i++) notme[i] = i;
1033:   for (i=last; i<M; i++) notme[i-last+first] = i;
1034:   ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
1035:   ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
1036:   MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
1037:   Aoff = Aoffs[0];
1038:   MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
1039:   Boff = Boffs[0];
1040:   MatIsTranspose(Aoff,Boff,tol,f);
1041:   MatDestroyMatrices(1,&Aoffs);
1042:   MatDestroyMatrices(1,&Boffs);
1043:   ISDestroy(&Me);
1044:   ISDestroy(&Notme);
1045:   PetscFree(notme);
1046:   return(0);
1047: }

1049: PetscErrorCode MatIsSymmetric_MPIAIJ(Mat A,PetscReal tol,PetscBool  *f)
1050: {

1054:   MatIsTranspose_MPIAIJ(A,A,tol,f);
1055:   return(0);
1056: }

1058: PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1059: {
1060:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1064:   /* do nondiagonal part */
1065:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1066:   /* send it on its way */
1067:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1068:   /* do local part */
1069:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
1070:   /* receive remote parts */
1071:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1072:   return(0);
1073: }

1075: /*
1076:   This only works correctly for square matrices where the subblock A->A is the
1077:    diagonal block
1078: */
1079: PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v)
1080: {
1082:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1085:   if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1086:   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");
1087:   MatGetDiagonal(a->A,v);
1088:   return(0);
1089: }

1091: PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa)
1092: {
1093:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1097:   MatScale(a->A,aa);
1098:   MatScale(a->B,aa);
1099:   return(0);
1100: }

1102: PetscErrorCode MatDestroy_MPIAIJ(Mat mat)
1103: {
1104:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

1108: #if defined(PETSC_USE_LOG)
1109:   PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
1110: #endif
1111:   MatStashDestroy_Private(&mat->stash);
1112:   VecDestroy(&aij->diag);
1113:   MatDestroy(&aij->A);
1114:   MatDestroy(&aij->B);
1115: #if defined(PETSC_USE_CTABLE)
1116:   PetscTableDestroy(&aij->colmap);
1117: #else
1118:   PetscFree(aij->colmap);
1119: #endif
1120:   PetscFree(aij->garray);
1121:   VecDestroy(&aij->lvec);
1122:   VecScatterDestroy(&aij->Mvctx);
1123:   if (aij->Mvctx_mpi1) {VecScatterDestroy(&aij->Mvctx_mpi1);}
1124:   PetscFree2(aij->rowvalues,aij->rowindices);
1125:   PetscFree(aij->ld);
1126:   PetscFree(mat->data);

1128:   PetscObjectChangeTypeName((PetscObject)mat,0);
1129:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1130:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1131:   PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
1132:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);
1133:   PetscObjectComposeFunction((PetscObject)mat,"MatResetPreallocation_C",NULL);
1134:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);
1135:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
1136:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);
1137: #if defined(PETSC_HAVE_ELEMENTAL)
1138:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);
1139: #endif
1140: #if defined(PETSC_HAVE_HYPRE)
1141:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);
1142:   PetscObjectComposeFunction((PetscObject)mat,"MatMatMatMult_transpose_mpiaij_mpiaij_C",NULL);
1143: #endif
1144:   return(0);
1145: }

1147: PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer)
1148: {
1149:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
1150:   Mat_SeqAIJ     *A   = (Mat_SeqAIJ*)aij->A->data;
1151:   Mat_SeqAIJ     *B   = (Mat_SeqAIJ*)aij->B->data;
1153:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
1154:   int            fd;
1155:   PetscInt       nz,header[4],*row_lengths,*range=0,rlen,i;
1156:   PetscInt       nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0;
1157:   PetscScalar    *column_values;
1158:   PetscInt       message_count,flowcontrolcount;
1159:   FILE           *file;

1162:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1163:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
1164:   nz   = A->nz + B->nz;
1165:   PetscViewerBinaryGetDescriptor(viewer,&fd);
1166:   if (!rank) {
1167:     header[0] = MAT_FILE_CLASSID;
1168:     header[1] = mat->rmap->N;
1169:     header[2] = mat->cmap->N;

1171:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1172:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
1173:     /* get largest number of rows any processor has */
1174:     rlen  = mat->rmap->n;
1175:     range = mat->rmap->range;
1176:     for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]);
1177:   } else {
1178:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1179:     rlen = mat->rmap->n;
1180:   }

1182:   /* load up the local row counts */
1183:   PetscMalloc1(rlen+1,&row_lengths);
1184:   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];

1186:   /* store the row lengths to the file */
1187:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1188:   if (!rank) {
1189:     PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);
1190:     for (i=1; i<size; i++) {
1191:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1192:       rlen = range[i+1] - range[i];
1193:       MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1194:       PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);
1195:     }
1196:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1197:   } else {
1198:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1199:     MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1200:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1201:   }
1202:   PetscFree(row_lengths);

1204:   /* load up the local column indices */
1205:   nzmax = nz; /* th processor needs space a largest processor needs */
1206:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
1207:   PetscMalloc1(nzmax+1,&column_indices);
1208:   cnt   = 0;
1209:   for (i=0; i<mat->rmap->n; i++) {
1210:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1211:       if ((col = garray[B->j[j]]) > cstart) break;
1212:       column_indices[cnt++] = col;
1213:     }
1214:     for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart;
1215:     for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]];
1216:   }
1217:   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);

1219:   /* store the column indices to the file */
1220:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1221:   if (!rank) {
1222:     MPI_Status status;
1223:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1224:     for (i=1; i<size; i++) {
1225:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1226:       MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1227:       if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1228:       MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1229:       PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);
1230:     }
1231:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1232:   } else {
1233:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1234:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1235:     MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1236:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1237:   }
1238:   PetscFree(column_indices);

1240:   /* load up the local column values */
1241:   PetscMalloc1(nzmax+1,&column_values);
1242:   cnt  = 0;
1243:   for (i=0; i<mat->rmap->n; i++) {
1244:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1245:       if (garray[B->j[j]] > cstart) break;
1246:       column_values[cnt++] = B->a[j];
1247:     }
1248:     for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k];
1249:     for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j];
1250:   }
1251:   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);

1253:   /* store the column values to the file */
1254:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1255:   if (!rank) {
1256:     MPI_Status status;
1257:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1258:     for (i=1; i<size; i++) {
1259:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1260:       MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1261:       if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1262:       MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));
1263:       PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);
1264:     }
1265:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1266:   } else {
1267:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1268:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1269:     MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1270:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1271:   }
1272:   PetscFree(column_values);

1274:   PetscViewerBinaryGetInfoPointer(viewer,&file);
1275:   if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs));
1276:   return(0);
1277: }

1279:  #include <petscdraw.h>
1280: PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1281: {
1282:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*)mat->data;
1283:   PetscErrorCode    ierr;
1284:   PetscMPIInt       rank = aij->rank,size = aij->size;
1285:   PetscBool         isdraw,iascii,isbinary;
1286:   PetscViewer       sviewer;
1287:   PetscViewerFormat format;

1290:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1291:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1292:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1293:   if (iascii) {
1294:     PetscViewerGetFormat(viewer,&format);
1295:     if (format == PETSC_VIEWER_LOAD_BALANCE) {
1296:       PetscInt i,nmax = 0,nmin = PETSC_MAX_INT,navg = 0,*nz,nzlocal = ((Mat_SeqAIJ*) (aij->A->data))->nz + ((Mat_SeqAIJ*) (aij->B->data))->nz;
1297:       PetscMalloc1(size,&nz);
1298:       MPI_Allgather(&nzlocal,1,MPIU_INT,nz,1,MPIU_INT,PetscObjectComm((PetscObject)mat));
1299:       for (i=0; i<(PetscInt)size; i++) {
1300:         nmax = PetscMax(nmax,nz[i]);
1301:         nmin = PetscMin(nmin,nz[i]);
1302:         navg += nz[i];
1303:       }
1304:       PetscFree(nz);
1305:       navg = navg/size;
1306:       PetscViewerASCIIPrintf(viewer,"Load Balance - Nonzeros: Min %D  avg %D  max %D\n",nmin,navg,nmax);
1307:       return(0);
1308:     }
1309:     PetscViewerGetFormat(viewer,&format);
1310:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1311:       MatInfo   info;
1312:       PetscBool inodes;

1314:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1315:       MatGetInfo(mat,MAT_LOCAL,&info);
1316:       MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);
1317:       PetscViewerASCIIPushSynchronized(viewer);
1318:       if (!inodes) {
1319:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, not using I-node routines\n",
1320:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1321:       } else {
1322:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, using I-node routines\n",
1323:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1324:       }
1325:       MatGetInfo(aij->A,MAT_LOCAL,&info);
1326:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1327:       MatGetInfo(aij->B,MAT_LOCAL,&info);
1328:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1329:       PetscViewerFlush(viewer);
1330:       PetscViewerASCIIPopSynchronized(viewer);
1331:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
1332:       VecScatterView(aij->Mvctx,viewer);
1333:       return(0);
1334:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
1335:       PetscInt inodecount,inodelimit,*inodes;
1336:       MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);
1337:       if (inodes) {
1338:         PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
1339:       } else {
1340:         PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
1341:       }
1342:       return(0);
1343:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1344:       return(0);
1345:     }
1346:   } else if (isbinary) {
1347:     if (size == 1) {
1348:       PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1349:       MatView(aij->A,viewer);
1350:     } else {
1351:       MatView_MPIAIJ_Binary(mat,viewer);
1352:     }
1353:     return(0);
1354:   } else if (isdraw) {
1355:     PetscDraw draw;
1356:     PetscBool isnull;
1357:     PetscViewerDrawGetDraw(viewer,0,&draw);
1358:     PetscDrawIsNull(draw,&isnull);
1359:     if (isnull) return(0);
1360:   }

1362:   {
1363:     /* assemble the entire matrix onto first processor. */
1364:     Mat        A;
1365:     Mat_SeqAIJ *Aloc;
1366:     PetscInt   M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct;
1367:     MatScalar  *a;

1369:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
1370:     if (!rank) {
1371:       MatSetSizes(A,M,N,M,N);
1372:     } else {
1373:       MatSetSizes(A,0,0,M,N);
1374:     }
1375:     /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */
1376:     MatSetType(A,MATMPIAIJ);
1377:     MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);
1378:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
1379:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

1381:     /* copy over the A part */
1382:     Aloc = (Mat_SeqAIJ*)aij->A->data;
1383:     m    = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1384:     row  = mat->rmap->rstart;
1385:     for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart;
1386:     for (i=0; i<m; i++) {
1387:       MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);
1388:       row++;
1389:       a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i];
1390:     }
1391:     aj = Aloc->j;
1392:     for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart;

1394:     /* copy over the B part */
1395:     Aloc = (Mat_SeqAIJ*)aij->B->data;
1396:     m    = aij->B->rmap->n;  ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1397:     row  = mat->rmap->rstart;
1398:     PetscMalloc1(ai[m]+1,&cols);
1399:     ct   = cols;
1400:     for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]];
1401:     for (i=0; i<m; i++) {
1402:       MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);
1403:       row++;
1404:       a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i];
1405:     }
1406:     PetscFree(ct);
1407:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1408:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1409:     /*
1410:        Everyone has to call to draw the matrix since the graphics waits are
1411:        synchronized across all processors that share the PetscDraw object
1412:     */
1413:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1414:     if (!rank) {
1415:       PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);
1416:       MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);
1417:     }
1418:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1419:     PetscViewerFlush(viewer);
1420:     MatDestroy(&A);
1421:   }
1422:   return(0);
1423: }

1425: PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer)
1426: {
1428:   PetscBool      iascii,isdraw,issocket,isbinary;

1431:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1432:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1433:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1434:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1435:   if (iascii || isdraw || isbinary || issocket) {
1436:     MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);
1437:   }
1438:   return(0);
1439: }

1441: PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1442: {
1443:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1445:   Vec            bb1 = 0;
1446:   PetscBool      hasop;

1449:   if (flag == SOR_APPLY_UPPER) {
1450:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1451:     return(0);
1452:   }

1454:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1455:     VecDuplicate(bb,&bb1);
1456:   }

1458:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
1459:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1460:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1461:       its--;
1462:     }

1464:     while (its--) {
1465:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1466:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1468:       /* update rhs: bb1 = bb - B*x */
1469:       VecScale(mat->lvec,-1.0);
1470:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1472:       /* local sweep */
1473:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1474:     }
1475:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
1476:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1477:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1478:       its--;
1479:     }
1480:     while (its--) {
1481:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1482:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1484:       /* update rhs: bb1 = bb - B*x */
1485:       VecScale(mat->lvec,-1.0);
1486:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1488:       /* local sweep */
1489:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1490:     }
1491:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
1492:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1493:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1494:       its--;
1495:     }
1496:     while (its--) {
1497:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1498:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1500:       /* update rhs: bb1 = bb - B*x */
1501:       VecScale(mat->lvec,-1.0);
1502:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1504:       /* local sweep */
1505:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1506:     }
1507:   } else if (flag & SOR_EISENSTAT) {
1508:     Vec xx1;

1510:     VecDuplicate(bb,&xx1);
1511:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

1513:     VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1514:     VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1515:     if (!mat->diag) {
1516:       MatCreateVecs(matin,&mat->diag,NULL);
1517:       MatGetDiagonal(matin,mat->diag);
1518:     }
1519:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
1520:     if (hasop) {
1521:       MatMultDiagonalBlock(matin,xx,bb1);
1522:     } else {
1523:       VecPointwiseMult(bb1,mat->diag,xx);
1524:     }
1525:     VecAYPX(bb1,(omega-2.0)/omega,bb);

1527:     MatMultAdd(mat->B,mat->lvec,bb1,bb1);

1529:     /* local sweep */
1530:     (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
1531:     VecAXPY(xx,1.0,xx1);
1532:     VecDestroy(&xx1);
1533:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");

1535:   VecDestroy(&bb1);

1537:   matin->factorerrortype = mat->A->factorerrortype;
1538:   return(0);
1539: }

1541: PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B)
1542: {
1543:   Mat            aA,aB,Aperm;
1544:   const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj;
1545:   PetscScalar    *aa,*ba;
1546:   PetscInt       i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest;
1547:   PetscSF        rowsf,sf;
1548:   IS             parcolp = NULL;
1549:   PetscBool      done;

1553:   MatGetLocalSize(A,&m,&n);
1554:   ISGetIndices(rowp,&rwant);
1555:   ISGetIndices(colp,&cwant);
1556:   PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);

1558:   /* Invert row permutation to find out where my rows should go */
1559:   PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);
1560:   PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);
1561:   PetscSFSetFromOptions(rowsf);
1562:   for (i=0; i<m; i++) work[i] = A->rmap->rstart + i;
1563:   PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1564:   PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);

1566:   /* Invert column permutation to find out where my columns should go */
1567:   PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1568:   PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);
1569:   PetscSFSetFromOptions(sf);
1570:   for (i=0; i<n; i++) work[i] = A->cmap->rstart + i;
1571:   PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1572:   PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1573:   PetscSFDestroy(&sf);

1575:   ISRestoreIndices(rowp,&rwant);
1576:   ISRestoreIndices(colp,&cwant);
1577:   MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);

1579:   /* Find out where my gcols should go */
1580:   MatGetSize(aB,NULL,&ng);
1581:   PetscMalloc1(ng,&gcdest);
1582:   PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1583:   PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);
1584:   PetscSFSetFromOptions(sf);
1585:   PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);
1586:   PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);
1587:   PetscSFDestroy(&sf);

1589:   PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);
1590:   MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1591:   MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1592:   for (i=0; i<m; i++) {
1593:     PetscInt row = rdest[i],rowner;
1594:     PetscLayoutFindOwner(A->rmap,row,&rowner);
1595:     for (j=ai[i]; j<ai[i+1]; j++) {
1596:       PetscInt cowner,col = cdest[aj[j]];
1597:       PetscLayoutFindOwner(A->cmap,col,&cowner); /* Could build an index for the columns to eliminate this search */
1598:       if (rowner == cowner) dnnz[i]++;
1599:       else onnz[i]++;
1600:     }
1601:     for (j=bi[i]; j<bi[i+1]; j++) {
1602:       PetscInt cowner,col = gcdest[bj[j]];
1603:       PetscLayoutFindOwner(A->cmap,col,&cowner);
1604:       if (rowner == cowner) dnnz[i]++;
1605:       else onnz[i]++;
1606:     }
1607:   }
1608:   PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);
1609:   PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);
1610:   PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);
1611:   PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);
1612:   PetscSFDestroy(&rowsf);

1614:   MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);
1615:   MatSeqAIJGetArray(aA,&aa);
1616:   MatSeqAIJGetArray(aB,&ba);
1617:   for (i=0; i<m; i++) {
1618:     PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */
1619:     PetscInt j0,rowlen;
1620:     rowlen = ai[i+1] - ai[i];
1621:     for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */
1622:       for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]];
1623:       MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);
1624:     }
1625:     rowlen = bi[i+1] - bi[i];
1626:     for (j0=j=0; j<rowlen; j0=j) {
1627:       for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]];
1628:       MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);
1629:     }
1630:   }
1631:   MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);
1632:   MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);
1633:   MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1634:   MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1635:   MatSeqAIJRestoreArray(aA,&aa);
1636:   MatSeqAIJRestoreArray(aB,&ba);
1637:   PetscFree4(dnnz,onnz,tdnnz,tonnz);
1638:   PetscFree3(work,rdest,cdest);
1639:   PetscFree(gcdest);
1640:   if (parcolp) {ISDestroy(&colp);}
1641:   *B = Aperm;
1642:   return(0);
1643: }

1645: PetscErrorCode  MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
1646: {
1647:   Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;

1651:   MatGetSize(aij->B,NULL,nghosts);
1652:   if (ghosts) *ghosts = aij->garray;
1653:   return(0);
1654: }

1656: PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1657: {
1658:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1659:   Mat            A    = mat->A,B = mat->B;
1661:   PetscReal      isend[5],irecv[5];

1664:   info->block_size = 1.0;
1665:   MatGetInfo(A,MAT_LOCAL,info);

1667:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1668:   isend[3] = info->memory;  isend[4] = info->mallocs;

1670:   MatGetInfo(B,MAT_LOCAL,info);

1672:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1673:   isend[3] += info->memory;  isend[4] += info->mallocs;
1674:   if (flag == MAT_LOCAL) {
1675:     info->nz_used      = isend[0];
1676:     info->nz_allocated = isend[1];
1677:     info->nz_unneeded  = isend[2];
1678:     info->memory       = isend[3];
1679:     info->mallocs      = isend[4];
1680:   } else if (flag == MAT_GLOBAL_MAX) {
1681:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

1683:     info->nz_used      = irecv[0];
1684:     info->nz_allocated = irecv[1];
1685:     info->nz_unneeded  = irecv[2];
1686:     info->memory       = irecv[3];
1687:     info->mallocs      = irecv[4];
1688:   } else if (flag == MAT_GLOBAL_SUM) {
1689:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

1691:     info->nz_used      = irecv[0];
1692:     info->nz_allocated = irecv[1];
1693:     info->nz_unneeded  = irecv[2];
1694:     info->memory       = irecv[3];
1695:     info->mallocs      = irecv[4];
1696:   }
1697:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1698:   info->fill_ratio_needed = 0;
1699:   info->factor_mallocs    = 0;
1700:   return(0);
1701: }

1703: PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg)
1704: {
1705:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1709:   switch (op) {
1710:   case MAT_NEW_NONZERO_LOCATIONS:
1711:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1712:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1713:   case MAT_KEEP_NONZERO_PATTERN:
1714:   case MAT_NEW_NONZERO_LOCATION_ERR:
1715:   case MAT_USE_INODES:
1716:   case MAT_IGNORE_ZERO_ENTRIES:
1717:     MatCheckPreallocated(A,1);
1718:     MatSetOption(a->A,op,flg);
1719:     MatSetOption(a->B,op,flg);
1720:     break;
1721:   case MAT_ROW_ORIENTED:
1722:     MatCheckPreallocated(A,1);
1723:     a->roworiented = flg;

1725:     MatSetOption(a->A,op,flg);
1726:     MatSetOption(a->B,op,flg);
1727:     break;
1728:   case MAT_NEW_DIAGONALS:
1729:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1730:     break;
1731:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1732:     a->donotstash = flg;
1733:     break;
1734:   case MAT_SPD:
1735:     A->spd_set = PETSC_TRUE;
1736:     A->spd     = flg;
1737:     if (flg) {
1738:       A->symmetric                  = PETSC_TRUE;
1739:       A->structurally_symmetric     = PETSC_TRUE;
1740:       A->symmetric_set              = PETSC_TRUE;
1741:       A->structurally_symmetric_set = PETSC_TRUE;
1742:     }
1743:     break;
1744:   case MAT_SYMMETRIC:
1745:     MatCheckPreallocated(A,1);
1746:     MatSetOption(a->A,op,flg);
1747:     break;
1748:   case MAT_STRUCTURALLY_SYMMETRIC:
1749:     MatCheckPreallocated(A,1);
1750:     MatSetOption(a->A,op,flg);
1751:     break;
1752:   case MAT_HERMITIAN:
1753:     MatCheckPreallocated(A,1);
1754:     MatSetOption(a->A,op,flg);
1755:     break;
1756:   case MAT_SYMMETRY_ETERNAL:
1757:     MatCheckPreallocated(A,1);
1758:     MatSetOption(a->A,op,flg);
1759:     break;
1760:   case MAT_SUBMAT_SINGLEIS:
1761:     A->submat_singleis = flg;
1762:     break;
1763:   case MAT_STRUCTURE_ONLY:
1764:     /* The option is handled directly by MatSetOption() */
1765:     break;
1766:   default:
1767:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1768:   }
1769:   return(0);
1770: }

1772: PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1773: {
1774:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1775:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1777:   PetscInt       i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart;
1778:   PetscInt       nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend;
1779:   PetscInt       *cmap,*idx_p;

1782:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1783:   mat->getrowactive = PETSC_TRUE;

1785:   if (!mat->rowvalues && (idx || v)) {
1786:     /*
1787:         allocate enough space to hold information from the longest row.
1788:     */
1789:     Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data;
1790:     PetscInt   max = 1,tmp;
1791:     for (i=0; i<matin->rmap->n; i++) {
1792:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1793:       if (max < tmp) max = tmp;
1794:     }
1795:     PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);
1796:   }

1798:   if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows");
1799:   lrow = row - rstart;

1801:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1802:   if (!v)   {pvA = 0; pvB = 0;}
1803:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1804:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1805:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1806:   nztot = nzA + nzB;

1808:   cmap = mat->garray;
1809:   if (v  || idx) {
1810:     if (nztot) {
1811:       /* Sort by increasing column numbers, assuming A and B already sorted */
1812:       PetscInt imark = -1;
1813:       if (v) {
1814:         *v = v_p = mat->rowvalues;
1815:         for (i=0; i<nzB; i++) {
1816:           if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i];
1817:           else break;
1818:         }
1819:         imark = i;
1820:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1821:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1822:       }
1823:       if (idx) {
1824:         *idx = idx_p = mat->rowindices;
1825:         if (imark > -1) {
1826:           for (i=0; i<imark; i++) {
1827:             idx_p[i] = cmap[cworkB[i]];
1828:           }
1829:         } else {
1830:           for (i=0; i<nzB; i++) {
1831:             if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]];
1832:             else break;
1833:           }
1834:           imark = i;
1835:         }
1836:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart + cworkA[i];
1837:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]];
1838:       }
1839:     } else {
1840:       if (idx) *idx = 0;
1841:       if (v)   *v   = 0;
1842:     }
1843:   }
1844:   *nz  = nztot;
1845:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1846:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1847:   return(0);
1848: }

1850: PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1851: {
1852:   Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;

1855:   if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1856:   aij->getrowactive = PETSC_FALSE;
1857:   return(0);
1858: }

1860: PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm)
1861: {
1862:   Mat_MPIAIJ     *aij  = (Mat_MPIAIJ*)mat->data;
1863:   Mat_SeqAIJ     *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data;
1865:   PetscInt       i,j,cstart = mat->cmap->rstart;
1866:   PetscReal      sum = 0.0;
1867:   MatScalar      *v;

1870:   if (aij->size == 1) {
1871:      MatNorm(aij->A,type,norm);
1872:   } else {
1873:     if (type == NORM_FROBENIUS) {
1874:       v = amat->a;
1875:       for (i=0; i<amat->nz; i++) {
1876:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1877:       }
1878:       v = bmat->a;
1879:       for (i=0; i<bmat->nz; i++) {
1880:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1881:       }
1882:       MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1883:       *norm = PetscSqrtReal(*norm);
1884:       PetscLogFlops(2*amat->nz+2*bmat->nz);
1885:     } else if (type == NORM_1) { /* max column norm */
1886:       PetscReal *tmp,*tmp2;
1887:       PetscInt  *jj,*garray = aij->garray;
1888:       PetscCalloc1(mat->cmap->N+1,&tmp);
1889:       PetscMalloc1(mat->cmap->N+1,&tmp2);
1890:       *norm = 0.0;
1891:       v     = amat->a; jj = amat->j;
1892:       for (j=0; j<amat->nz; j++) {
1893:         tmp[cstart + *jj++] += PetscAbsScalar(*v);  v++;
1894:       }
1895:       v = bmat->a; jj = bmat->j;
1896:       for (j=0; j<bmat->nz; j++) {
1897:         tmp[garray[*jj++]] += PetscAbsScalar(*v); v++;
1898:       }
1899:       MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1900:       for (j=0; j<mat->cmap->N; j++) {
1901:         if (tmp2[j] > *norm) *norm = tmp2[j];
1902:       }
1903:       PetscFree(tmp);
1904:       PetscFree(tmp2);
1905:       PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1906:     } else if (type == NORM_INFINITY) { /* max row norm */
1907:       PetscReal ntemp = 0.0;
1908:       for (j=0; j<aij->A->rmap->n; j++) {
1909:         v   = amat->a + amat->i[j];
1910:         sum = 0.0;
1911:         for (i=0; i<amat->i[j+1]-amat->i[j]; i++) {
1912:           sum += PetscAbsScalar(*v); v++;
1913:         }
1914:         v = bmat->a + bmat->i[j];
1915:         for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) {
1916:           sum += PetscAbsScalar(*v); v++;
1917:         }
1918:         if (sum > ntemp) ntemp = sum;
1919:       }
1920:       MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
1921:       PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1922:     } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm");
1923:   }
1924:   return(0);
1925: }

1927: PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout)
1928: {
1929:   Mat_MPIAIJ     *a   = (Mat_MPIAIJ*)A->data;
1930:   Mat_SeqAIJ     *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data;
1932:   PetscInt       M      = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i;
1933:   PetscInt       cstart = A->cmap->rstart,ncol;
1934:   Mat            B;
1935:   MatScalar      *array;

1938:   ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n;
1939:   ai = Aloc->i; aj = Aloc->j;
1940:   bi = Bloc->i; bj = Bloc->j;
1941:   if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
1942:     PetscInt             *d_nnz,*g_nnz,*o_nnz;
1943:     PetscSFNode          *oloc;
1944:     PETSC_UNUSED PetscSF sf;

1946:     PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);
1947:     /* compute d_nnz for preallocation */
1948:     PetscMemzero(d_nnz,na*sizeof(PetscInt));
1949:     for (i=0; i<ai[ma]; i++) {
1950:       d_nnz[aj[i]]++;
1951:       aj[i] += cstart; /* global col index to be used by MatSetValues() */
1952:     }
1953:     /* compute local off-diagonal contributions */
1954:     PetscMemzero(g_nnz,nb*sizeof(PetscInt));
1955:     for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++;
1956:     /* map those to global */
1957:     PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1958:     PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);
1959:     PetscSFSetFromOptions(sf);
1960:     PetscMemzero(o_nnz,na*sizeof(PetscInt));
1961:     PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
1962:     PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
1963:     PetscSFDestroy(&sf);

1965:     MatCreate(PetscObjectComm((PetscObject)A),&B);
1966:     MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
1967:     MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));
1968:     MatSetType(B,((PetscObject)A)->type_name);
1969:     MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
1970:     PetscFree4(d_nnz,o_nnz,g_nnz,oloc);
1971:   } else {
1972:     B    = *matout;
1973:     MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
1974:     for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */
1975:   }

1977:   /* copy over the A part */
1978:   array = Aloc->a;
1979:   row   = A->rmap->rstart;
1980:   for (i=0; i<ma; i++) {
1981:     ncol = ai[i+1]-ai[i];
1982:     MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);
1983:     row++;
1984:     array += ncol; aj += ncol;
1985:   }
1986:   aj = Aloc->j;
1987:   for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */

1989:   /* copy over the B part */
1990:   PetscCalloc1(bi[mb],&cols);
1991:   array = Bloc->a;
1992:   row   = A->rmap->rstart;
1993:   for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]];
1994:   cols_tmp = cols;
1995:   for (i=0; i<mb; i++) {
1996:     ncol = bi[i+1]-bi[i];
1997:     MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);
1998:     row++;
1999:     array += ncol; cols_tmp += ncol;
2000:   }
2001:   PetscFree(cols);

2003:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2004:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2005:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) {
2006:     *matout = B;
2007:   } else {
2008:     MatHeaderMerge(A,&B);
2009:   }
2010:   return(0);
2011: }

2013: PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr)
2014: {
2015:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
2016:   Mat            a    = aij->A,b = aij->B;
2018:   PetscInt       s1,s2,s3;

2021:   MatGetLocalSize(mat,&s2,&s3);
2022:   if (rr) {
2023:     VecGetLocalSize(rr,&s1);
2024:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
2025:     /* Overlap communication with computation. */
2026:     VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2027:   }
2028:   if (ll) {
2029:     VecGetLocalSize(ll,&s1);
2030:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
2031:     (*b->ops->diagonalscale)(b,ll,0);
2032:   }
2033:   /* scale  the diagonal block */
2034:   (*a->ops->diagonalscale)(a,ll,rr);

2036:   if (rr) {
2037:     /* Do a scatter end and then right scale the off-diagonal block */
2038:     VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2039:     (*b->ops->diagonalscale)(b,0,aij->lvec);
2040:   }
2041:   return(0);
2042: }

2044: PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A)
2045: {
2046:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2050:   MatSetUnfactored(a->A);
2051:   return(0);
2052: }

2054: PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool  *flag)
2055: {
2056:   Mat_MPIAIJ     *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data;
2057:   Mat            a,b,c,d;
2058:   PetscBool      flg;

2062:   a = matA->A; b = matA->B;
2063:   c = matB->A; d = matB->B;

2065:   MatEqual(a,c,&flg);
2066:   if (flg) {
2067:     MatEqual(b,d,&flg);
2068:   }
2069:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
2070:   return(0);
2071: }

2073: PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str)
2074: {
2076:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2077:   Mat_MPIAIJ     *b = (Mat_MPIAIJ*)B->data;

2080:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
2081:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
2082:     /* because of the column compression in the off-processor part of the matrix a->B,
2083:        the number of columns in a->B and b->B may be different, hence we cannot call
2084:        the MatCopy() directly on the two parts. If need be, we can provide a more
2085:        efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
2086:        then copying the submatrices */
2087:     MatCopy_Basic(A,B,str);
2088:   } else {
2089:     MatCopy(a->A,b->A,str);
2090:     MatCopy(a->B,b->B,str);
2091:   }
2092:   PetscObjectStateIncrease((PetscObject)B);
2093:   return(0);
2094: }

2096: PetscErrorCode MatSetUp_MPIAIJ(Mat A)
2097: {

2101:    MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
2102:   return(0);
2103: }

2105: /*
2106:    Computes the number of nonzeros per row needed for preallocation when X and Y
2107:    have different nonzero structure.
2108: */
2109: 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)
2110: {
2111:   PetscInt       i,j,k,nzx,nzy;

2114:   /* Set the number of nonzeros in the new matrix */
2115:   for (i=0; i<m; i++) {
2116:     const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i];
2117:     nzx = xi[i+1] - xi[i];
2118:     nzy = yi[i+1] - yi[i];
2119:     nnz[i] = 0;
2120:     for (j=0,k=0; j<nzx; j++) {                   /* Point in X */
2121:       for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */
2122:       if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++;             /* Skip duplicate */
2123:       nnz[i]++;
2124:     }
2125:     for (; k<nzy; k++) nnz[i]++;
2126:   }
2127:   return(0);
2128: }

2130: /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */
2131: static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
2132: {
2134:   PetscInt       m = Y->rmap->N;
2135:   Mat_SeqAIJ     *x = (Mat_SeqAIJ*)X->data;
2136:   Mat_SeqAIJ     *y = (Mat_SeqAIJ*)Y->data;

2139:   MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
2140:   return(0);
2141: }

2143: PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2144: {
2146:   Mat_MPIAIJ     *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data;
2147:   PetscBLASInt   bnz,one=1;
2148:   Mat_SeqAIJ     *x,*y;

2151:   if (str == SAME_NONZERO_PATTERN) {
2152:     PetscScalar alpha = a;
2153:     x    = (Mat_SeqAIJ*)xx->A->data;
2154:     PetscBLASIntCast(x->nz,&bnz);
2155:     y    = (Mat_SeqAIJ*)yy->A->data;
2156:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2157:     x    = (Mat_SeqAIJ*)xx->B->data;
2158:     y    = (Mat_SeqAIJ*)yy->B->data;
2159:     PetscBLASIntCast(x->nz,&bnz);
2160:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2161:     PetscObjectStateIncrease((PetscObject)Y);
2162:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2163:     MatAXPY_Basic(Y,a,X,str);
2164:   } else {
2165:     Mat      B;
2166:     PetscInt *nnz_d,*nnz_o;
2167:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
2168:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
2169:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
2170:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2171:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2172:     MatSetBlockSizesFromMats(B,Y,Y);
2173:     MatSetType(B,MATMPIAIJ);
2174:     MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);
2175:     MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
2176:     MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);
2177:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2178:     MatHeaderReplace(Y,&B);
2179:     PetscFree(nnz_d);
2180:     PetscFree(nnz_o);
2181:   }
2182:   return(0);
2183: }

2185: extern PetscErrorCode  MatConjugate_SeqAIJ(Mat);

2187: PetscErrorCode  MatConjugate_MPIAIJ(Mat mat)
2188: {
2189: #if defined(PETSC_USE_COMPLEX)
2191:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2194:   MatConjugate_SeqAIJ(aij->A);
2195:   MatConjugate_SeqAIJ(aij->B);
2196: #else
2198: #endif
2199:   return(0);
2200: }

2202: PetscErrorCode MatRealPart_MPIAIJ(Mat A)
2203: {
2204:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2208:   MatRealPart(a->A);
2209:   MatRealPart(a->B);
2210:   return(0);
2211: }

2213: PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A)
2214: {
2215:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2219:   MatImaginaryPart(a->A);
2220:   MatImaginaryPart(a->B);
2221:   return(0);
2222: }

2224: PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2225: {
2226:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2228:   PetscInt       i,*idxb = 0;
2229:   PetscScalar    *va,*vb;
2230:   Vec            vtmp;

2233:   MatGetRowMaxAbs(a->A,v,idx);
2234:   VecGetArray(v,&va);
2235:   if (idx) {
2236:     for (i=0; i<A->rmap->n; i++) {
2237:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2238:     }
2239:   }

2241:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2242:   if (idx) {
2243:     PetscMalloc1(A->rmap->n,&idxb);
2244:   }
2245:   MatGetRowMaxAbs(a->B,vtmp,idxb);
2246:   VecGetArray(vtmp,&vb);

2248:   for (i=0; i<A->rmap->n; i++) {
2249:     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
2250:       va[i] = vb[i];
2251:       if (idx) idx[i] = a->garray[idxb[i]];
2252:     }
2253:   }

2255:   VecRestoreArray(v,&va);
2256:   VecRestoreArray(vtmp,&vb);
2257:   PetscFree(idxb);
2258:   VecDestroy(&vtmp);
2259:   return(0);
2260: }

2262: PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2263: {
2264:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2266:   PetscInt       i,*idxb = 0;
2267:   PetscScalar    *va,*vb;
2268:   Vec            vtmp;

2271:   MatGetRowMinAbs(a->A,v,idx);
2272:   VecGetArray(v,&va);
2273:   if (idx) {
2274:     for (i=0; i<A->cmap->n; i++) {
2275:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2276:     }
2277:   }

2279:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2280:   if (idx) {
2281:     PetscMalloc1(A->rmap->n,&idxb);
2282:   }
2283:   MatGetRowMinAbs(a->B,vtmp,idxb);
2284:   VecGetArray(vtmp,&vb);

2286:   for (i=0; i<A->rmap->n; i++) {
2287:     if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) {
2288:       va[i] = vb[i];
2289:       if (idx) idx[i] = a->garray[idxb[i]];
2290:     }
2291:   }

2293:   VecRestoreArray(v,&va);
2294:   VecRestoreArray(vtmp,&vb);
2295:   PetscFree(idxb);
2296:   VecDestroy(&vtmp);
2297:   return(0);
2298: }

2300: PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2301: {
2302:   Mat_MPIAIJ     *mat   = (Mat_MPIAIJ*) A->data;
2303:   PetscInt       n      = A->rmap->n;
2304:   PetscInt       cstart = A->cmap->rstart;
2305:   PetscInt       *cmap  = mat->garray;
2306:   PetscInt       *diagIdx, *offdiagIdx;
2307:   Vec            diagV, offdiagV;
2308:   PetscScalar    *a, *diagA, *offdiagA;
2309:   PetscInt       r;

2313:   PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2314:   VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);
2315:   VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);
2316:   MatGetRowMin(mat->A, diagV,    diagIdx);
2317:   MatGetRowMin(mat->B, offdiagV, offdiagIdx);
2318:   VecGetArray(v,        &a);
2319:   VecGetArray(diagV,    &diagA);
2320:   VecGetArray(offdiagV, &offdiagA);
2321:   for (r = 0; r < n; ++r) {
2322:     if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) {
2323:       a[r]   = diagA[r];
2324:       idx[r] = cstart + diagIdx[r];
2325:     } else {
2326:       a[r]   = offdiagA[r];
2327:       idx[r] = cmap[offdiagIdx[r]];
2328:     }
2329:   }
2330:   VecRestoreArray(v,        &a);
2331:   VecRestoreArray(diagV,    &diagA);
2332:   VecRestoreArray(offdiagV, &offdiagA);
2333:   VecDestroy(&diagV);
2334:   VecDestroy(&offdiagV);
2335:   PetscFree2(diagIdx, offdiagIdx);
2336:   return(0);
2337: }

2339: PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2340: {
2341:   Mat_MPIAIJ     *mat   = (Mat_MPIAIJ*) A->data;
2342:   PetscInt       n      = A->rmap->n;
2343:   PetscInt       cstart = A->cmap->rstart;
2344:   PetscInt       *cmap  = mat->garray;
2345:   PetscInt       *diagIdx, *offdiagIdx;
2346:   Vec            diagV, offdiagV;
2347:   PetscScalar    *a, *diagA, *offdiagA;
2348:   PetscInt       r;

2352:   PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2353:   VecCreateSeq(PETSC_COMM_SELF, n, &diagV);
2354:   VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);
2355:   MatGetRowMax(mat->A, diagV,    diagIdx);
2356:   MatGetRowMax(mat->B, offdiagV, offdiagIdx);
2357:   VecGetArray(v,        &a);
2358:   VecGetArray(diagV,    &diagA);
2359:   VecGetArray(offdiagV, &offdiagA);
2360:   for (r = 0; r < n; ++r) {
2361:     if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) {
2362:       a[r]   = diagA[r];
2363:       idx[r] = cstart + diagIdx[r];
2364:     } else {
2365:       a[r]   = offdiagA[r];
2366:       idx[r] = cmap[offdiagIdx[r]];
2367:     }
2368:   }
2369:   VecRestoreArray(v,        &a);
2370:   VecRestoreArray(diagV,    &diagA);
2371:   VecRestoreArray(offdiagV, &offdiagA);
2372:   VecDestroy(&diagV);
2373:   VecDestroy(&offdiagV);
2374:   PetscFree2(diagIdx, offdiagIdx);
2375:   return(0);
2376: }

2378: PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat)
2379: {
2381:   Mat            *dummy;

2384:   MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);
2385:   *newmat = *dummy;
2386:   PetscFree(dummy);
2387:   return(0);
2388: }

2390: PetscErrorCode  MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values)
2391: {
2392:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*) A->data;

2396:   MatInvertBlockDiagonal(a->A,values);
2397:   A->factorerrortype = a->A->factorerrortype;
2398:   return(0);
2399: }

2401: static PetscErrorCode  MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx)
2402: {
2404:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)x->data;

2407:   MatSetRandom(aij->A,rctx);
2408:   MatSetRandom(aij->B,rctx);
2409:   MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
2410:   MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
2411:   return(0);
2412: }

2414: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc)
2415: {
2417:   if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable;
2418:   else A->ops->increaseoverlap    = MatIncreaseOverlap_MPIAIJ;
2419:   return(0);
2420: }

2422: /*@
2423:    MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap

2425:    Collective on Mat

2427:    Input Parameters:
2428: +    A - the matrix
2429: -    sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm)

2431:  Level: advanced

2433: @*/
2434: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc)
2435: {
2436:   PetscErrorCode       ierr;

2439:   PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));
2440:   return(0);
2441: }

2443: PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A)
2444: {
2445:   PetscErrorCode       ierr;
2446:   PetscBool            sc = PETSC_FALSE,flg;

2449:   PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");
2450:   PetscObjectOptionsBegin((PetscObject)A);
2451:   if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE;
2452:   PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);
2453:   if (flg) {
2454:     MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);
2455:   }
2456:   PetscOptionsEnd();
2457:   return(0);
2458: }

2460: PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a)
2461: {
2463:   Mat_MPIAIJ     *maij = (Mat_MPIAIJ*)Y->data;
2464:   Mat_SeqAIJ     *aij = (Mat_SeqAIJ*)maij->A->data;

2467:   if (!Y->preallocated) {
2468:     MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);
2469:   } else if (!aij->nz) {
2470:     PetscInt nonew = aij->nonew;
2471:     MatSeqAIJSetPreallocation(maij->A,1,NULL);
2472:     aij->nonew = nonew;
2473:   }
2474:   MatShift_Basic(Y,a);
2475:   return(0);
2476: }

2478: PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool  *missing,PetscInt *d)
2479: {
2480:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2484:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
2485:   MatMissingDiagonal(a->A,missing,d);
2486:   if (d) {
2487:     PetscInt rstart;
2488:     MatGetOwnershipRange(A,&rstart,NULL);
2489:     *d += rstart;

2491:   }
2492:   return(0);
2493: }


2496: /* -------------------------------------------------------------------*/
2497: static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ,
2498:                                        MatGetRow_MPIAIJ,
2499:                                        MatRestoreRow_MPIAIJ,
2500:                                        MatMult_MPIAIJ,
2501:                                 /* 4*/ MatMultAdd_MPIAIJ,
2502:                                        MatMultTranspose_MPIAIJ,
2503:                                        MatMultTransposeAdd_MPIAIJ,
2504:                                        0,
2505:                                        0,
2506:                                        0,
2507:                                 /*10*/ 0,
2508:                                        0,
2509:                                        0,
2510:                                        MatSOR_MPIAIJ,
2511:                                        MatTranspose_MPIAIJ,
2512:                                 /*15*/ MatGetInfo_MPIAIJ,
2513:                                        MatEqual_MPIAIJ,
2514:                                        MatGetDiagonal_MPIAIJ,
2515:                                        MatDiagonalScale_MPIAIJ,
2516:                                        MatNorm_MPIAIJ,
2517:                                 /*20*/ MatAssemblyBegin_MPIAIJ,
2518:                                        MatAssemblyEnd_MPIAIJ,
2519:                                        MatSetOption_MPIAIJ,
2520:                                        MatZeroEntries_MPIAIJ,
2521:                                 /*24*/ MatZeroRows_MPIAIJ,
2522:                                        0,
2523:                                        0,
2524:                                        0,
2525:                                        0,
2526:                                 /*29*/ MatSetUp_MPIAIJ,
2527:                                        0,
2528:                                        0,
2529:                                        MatGetDiagonalBlock_MPIAIJ,
2530:                                        0,
2531:                                 /*34*/ MatDuplicate_MPIAIJ,
2532:                                        0,
2533:                                        0,
2534:                                        0,
2535:                                        0,
2536:                                 /*39*/ MatAXPY_MPIAIJ,
2537:                                        MatCreateSubMatrices_MPIAIJ,
2538:                                        MatIncreaseOverlap_MPIAIJ,
2539:                                        MatGetValues_MPIAIJ,
2540:                                        MatCopy_MPIAIJ,
2541:                                 /*44*/ MatGetRowMax_MPIAIJ,
2542:                                        MatScale_MPIAIJ,
2543:                                        MatShift_MPIAIJ,
2544:                                        MatDiagonalSet_MPIAIJ,
2545:                                        MatZeroRowsColumns_MPIAIJ,
2546:                                 /*49*/ MatSetRandom_MPIAIJ,
2547:                                        0,
2548:                                        0,
2549:                                        0,
2550:                                        0,
2551:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
2552:                                        0,
2553:                                        MatSetUnfactored_MPIAIJ,
2554:                                        MatPermute_MPIAIJ,
2555:                                        0,
2556:                                 /*59*/ MatCreateSubMatrix_MPIAIJ,
2557:                                        MatDestroy_MPIAIJ,
2558:                                        MatView_MPIAIJ,
2559:                                        0,
2560:                                        MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ,
2561:                                 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ,
2562:                                        MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ,
2563:                                        0,
2564:                                        0,
2565:                                        0,
2566:                                 /*69*/ MatGetRowMaxAbs_MPIAIJ,
2567:                                        MatGetRowMinAbs_MPIAIJ,
2568:                                        0,
2569:                                        0,
2570:                                        0,
2571:                                        0,
2572:                                 /*75*/ MatFDColoringApply_AIJ,
2573:                                        MatSetFromOptions_MPIAIJ,
2574:                                        0,
2575:                                        0,
2576:                                        MatFindZeroDiagonals_MPIAIJ,
2577:                                 /*80*/ 0,
2578:                                        0,
2579:                                        0,
2580:                                 /*83*/ MatLoad_MPIAIJ,
2581:                                        MatIsSymmetric_MPIAIJ,
2582:                                        0,
2583:                                        0,
2584:                                        0,
2585:                                        0,
2586:                                 /*89*/ MatMatMult_MPIAIJ_MPIAIJ,
2587:                                        MatMatMultSymbolic_MPIAIJ_MPIAIJ,
2588:                                        MatMatMultNumeric_MPIAIJ_MPIAIJ,
2589:                                        MatPtAP_MPIAIJ_MPIAIJ,
2590:                                        MatPtAPSymbolic_MPIAIJ_MPIAIJ,
2591:                                 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ,
2592:                                        0,
2593:                                        0,
2594:                                        0,
2595:                                        0,
2596:                                 /*99*/ 0,
2597:                                        0,
2598:                                        0,
2599:                                        MatConjugate_MPIAIJ,
2600:                                        0,
2601:                                 /*104*/MatSetValuesRow_MPIAIJ,
2602:                                        MatRealPart_MPIAIJ,
2603:                                        MatImaginaryPart_MPIAIJ,
2604:                                        0,
2605:                                        0,
2606:                                 /*109*/0,
2607:                                        0,
2608:                                        MatGetRowMin_MPIAIJ,
2609:                                        0,
2610:                                        MatMissingDiagonal_MPIAIJ,
2611:                                 /*114*/MatGetSeqNonzeroStructure_MPIAIJ,
2612:                                        0,
2613:                                        MatGetGhosts_MPIAIJ,
2614:                                        0,
2615:                                        0,
2616:                                 /*119*/0,
2617:                                        0,
2618:                                        0,
2619:                                        0,
2620:                                        MatGetMultiProcBlock_MPIAIJ,
2621:                                 /*124*/MatFindNonzeroRows_MPIAIJ,
2622:                                        MatGetColumnNorms_MPIAIJ,
2623:                                        MatInvertBlockDiagonal_MPIAIJ,
2624:                                        0,
2625:                                        MatCreateSubMatricesMPI_MPIAIJ,
2626:                                 /*129*/0,
2627:                                        MatTransposeMatMult_MPIAIJ_MPIAIJ,
2628:                                        MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ,
2629:                                        MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ,
2630:                                        0,
2631:                                 /*134*/0,
2632:                                        0,
2633:                                        MatRARt_MPIAIJ_MPIAIJ,
2634:                                        0,
2635:                                        0,
2636:                                 /*139*/MatSetBlockSizes_MPIAIJ,
2637:                                        0,
2638:                                        0,
2639:                                        MatFDColoringSetUp_MPIXAIJ,
2640:                                        MatFindOffBlockDiagonalEntries_MPIAIJ,
2641:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ
2642: };

2644: /* ----------------------------------------------------------------------------------------*/

2646: PetscErrorCode  MatStoreValues_MPIAIJ(Mat mat)
2647: {
2648:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2652:   MatStoreValues(aij->A);
2653:   MatStoreValues(aij->B);
2654:   return(0);
2655: }

2657: PetscErrorCode  MatRetrieveValues_MPIAIJ(Mat mat)
2658: {
2659:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2663:   MatRetrieveValues(aij->A);
2664:   MatRetrieveValues(aij->B);
2665:   return(0);
2666: }

2668: PetscErrorCode  MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2669: {
2670:   Mat_MPIAIJ     *b;

2674:   PetscLayoutSetUp(B->rmap);
2675:   PetscLayoutSetUp(B->cmap);
2676:   b = (Mat_MPIAIJ*)B->data;

2678: #if defined(PETSC_USE_CTABLE)
2679:   PetscTableDestroy(&b->colmap);
2680: #else
2681:   PetscFree(b->colmap);
2682: #endif
2683:   PetscFree(b->garray);
2684:   VecDestroy(&b->lvec);
2685:   VecScatterDestroy(&b->Mvctx);

2687:   /* Because the B will have been resized we simply destroy it and create a new one each time */
2688:   MatDestroy(&b->B);
2689:   MatCreate(PETSC_COMM_SELF,&b->B);
2690:   MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
2691:   MatSetBlockSizesFromMats(b->B,B,B);
2692:   MatSetType(b->B,MATSEQAIJ);
2693:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

2695:   if (!B->preallocated) {
2696:     MatCreate(PETSC_COMM_SELF,&b->A);
2697:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2698:     MatSetBlockSizesFromMats(b->A,B,B);
2699:     MatSetType(b->A,MATSEQAIJ);
2700:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2701:   }

2703:   MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);
2704:   MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);
2705:   B->preallocated  = PETSC_TRUE;
2706:   B->was_assembled = PETSC_FALSE;
2707:   B->assembled     = PETSC_FALSE;;
2708:   return(0);
2709: }

2711: PetscErrorCode MatResetPreallocation_MPIAIJ(Mat B)
2712: {
2713:   Mat_MPIAIJ     *b;

2718:   PetscLayoutSetUp(B->rmap);
2719:   PetscLayoutSetUp(B->cmap);
2720:   b = (Mat_MPIAIJ*)B->data;

2722: #if defined(PETSC_USE_CTABLE)
2723:   PetscTableDestroy(&b->colmap);
2724: #else
2725:   PetscFree(b->colmap);
2726: #endif
2727:   PetscFree(b->garray);
2728:   VecDestroy(&b->lvec);
2729:   VecScatterDestroy(&b->Mvctx);

2731:   MatResetPreallocation(b->A);
2732:   MatResetPreallocation(b->B);
2733:   B->preallocated  = PETSC_TRUE;
2734:   B->was_assembled = PETSC_FALSE;
2735:   B->assembled = PETSC_FALSE;
2736:   return(0);
2737: }

2739: PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2740: {
2741:   Mat            mat;
2742:   Mat_MPIAIJ     *a,*oldmat = (Mat_MPIAIJ*)matin->data;

2746:   *newmat = 0;
2747:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2748:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2749:   MatSetBlockSizesFromMats(mat,matin,matin);
2750:   MatSetType(mat,((PetscObject)matin)->type_name);
2751:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
2752:   a       = (Mat_MPIAIJ*)mat->data;

2754:   mat->factortype   = matin->factortype;
2755:   mat->assembled    = PETSC_TRUE;
2756:   mat->insertmode   = NOT_SET_VALUES;
2757:   mat->preallocated = PETSC_TRUE;

2759:   a->size         = oldmat->size;
2760:   a->rank         = oldmat->rank;
2761:   a->donotstash   = oldmat->donotstash;
2762:   a->roworiented  = oldmat->roworiented;
2763:   a->rowindices   = 0;
2764:   a->rowvalues    = 0;
2765:   a->getrowactive = PETSC_FALSE;

2767:   PetscLayoutReference(matin->rmap,&mat->rmap);
2768:   PetscLayoutReference(matin->cmap,&mat->cmap);

2770:   if (oldmat->colmap) {
2771: #if defined(PETSC_USE_CTABLE)
2772:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2773: #else
2774:     PetscMalloc1(mat->cmap->N,&a->colmap);
2775:     PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
2776:     PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));
2777: #endif
2778:   } else a->colmap = 0;
2779:   if (oldmat->garray) {
2780:     PetscInt len;
2781:     len  = oldmat->B->cmap->n;
2782:     PetscMalloc1(len+1,&a->garray);
2783:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2784:     if (len) { PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt)); }
2785:   } else a->garray = 0;

2787:   VecDuplicate(oldmat->lvec,&a->lvec);
2788:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2789:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2790:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

2792:   if (oldmat->Mvctx_mpi1) {
2793:     VecScatterCopy(oldmat->Mvctx_mpi1,&a->Mvctx_mpi1);
2794:     PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx_mpi1);
2795:   }

2797:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2798:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2799:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2800:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2801:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2802:   *newmat = mat;
2803:   return(0);
2804: }

2806: PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer)
2807: {
2808:   PetscScalar    *vals,*svals;
2809:   MPI_Comm       comm;
2811:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
2812:   PetscInt       i,nz,j,rstart,rend,mmax,maxnz = 0;
2813:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols;
2814:   PetscInt       *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols;
2815:   PetscInt       cend,cstart,n,*rowners;
2816:   int            fd;
2817:   PetscInt       bs = newMat->rmap->bs;

2820:   /* force binary viewer to load .info file if it has not yet done so */
2821:   PetscViewerSetUp(viewer);
2822:   PetscObjectGetComm((PetscObject)viewer,&comm);
2823:   MPI_Comm_size(comm,&size);
2824:   MPI_Comm_rank(comm,&rank);
2825:   PetscViewerBinaryGetDescriptor(viewer,&fd);
2826:   if (!rank) {
2827:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
2828:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2829:     if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MATMPIAIJ");
2830:   }

2832:   PetscOptionsBegin(comm,NULL,"Options for loading MATMPIAIJ matrix","Mat");
2833:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2834:   PetscOptionsEnd();
2835:   if (bs < 0) bs = 1;

2837:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2838:   M    = header[1]; N = header[2];

2840:   /* If global sizes are set, check if they are consistent with that given in the file */
2841:   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);
2842:   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);

2844:   /* determine ownership of all (block) rows */
2845:   if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs);
2846:   if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank));    /* PETSC_DECIDE */
2847:   else m = newMat->rmap->n; /* Set by user */

2849:   PetscMalloc1(size+1,&rowners);
2850:   MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

2852:   /* First process needs enough room for process with most rows */
2853:   if (!rank) {
2854:     mmax = rowners[1];
2855:     for (i=2; i<=size; i++) {
2856:       mmax = PetscMax(mmax, rowners[i]);
2857:     }
2858:   } else mmax = -1;             /* unused, but compilers complain */

2860:   rowners[0] = 0;
2861:   for (i=2; i<=size; i++) {
2862:     rowners[i] += rowners[i-1];
2863:   }
2864:   rstart = rowners[rank];
2865:   rend   = rowners[rank+1];

2867:   /* distribute row lengths to all processors */
2868:   PetscMalloc2(m,&ourlens,m,&offlens);
2869:   if (!rank) {
2870:     PetscBinaryRead(fd,ourlens,m,PETSC_INT);
2871:     PetscMalloc1(mmax,&rowlengths);
2872:     PetscCalloc1(size,&procsnz);
2873:     for (j=0; j<m; j++) {
2874:       procsnz[0] += ourlens[j];
2875:     }
2876:     for (i=1; i<size; i++) {
2877:       PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);
2878:       /* calculate the number of nonzeros on each processor */
2879:       for (j=0; j<rowners[i+1]-rowners[i]; j++) {
2880:         procsnz[i] += rowlengths[j];
2881:       }
2882:       MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
2883:     }
2884:     PetscFree(rowlengths);
2885:   } else {
2886:     MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);
2887:   }

2889:   if (!rank) {
2890:     /* determine max buffer needed and allocate it */
2891:     maxnz = 0;
2892:     for (i=0; i<size; i++) {
2893:       maxnz = PetscMax(maxnz,procsnz[i]);
2894:     }
2895:     PetscMalloc1(maxnz,&cols);

2897:     /* read in my part of the matrix column indices  */
2898:     nz   = procsnz[0];
2899:     PetscMalloc1(nz,&mycols);
2900:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);

2902:     /* read in every one elses and ship off */
2903:     for (i=1; i<size; i++) {
2904:       nz   = procsnz[i];
2905:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
2906:       MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);
2907:     }
2908:     PetscFree(cols);
2909:   } else {
2910:     /* determine buffer space needed for message */
2911:     nz = 0;
2912:     for (i=0; i<m; i++) {
2913:       nz += ourlens[i];
2914:     }
2915:     PetscMalloc1(nz,&mycols);

2917:     /* receive message of column indices*/
2918:     MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);
2919:   }

2921:   /* determine column ownership if matrix is not square */
2922:   if (N != M) {
2923:     if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank);
2924:     else n = newMat->cmap->n;
2925:     MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);
2926:     cstart = cend - n;
2927:   } else {
2928:     cstart = rstart;
2929:     cend   = rend;
2930:     n      = cend - cstart;
2931:   }

2933:   /* loop over local rows, determining number of off diagonal entries */
2934:   PetscMemzero(offlens,m*sizeof(PetscInt));
2935:   jj   = 0;
2936:   for (i=0; i<m; i++) {
2937:     for (j=0; j<ourlens[i]; j++) {
2938:       if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++;
2939:       jj++;
2940:     }
2941:   }

2943:   for (i=0; i<m; i++) {
2944:     ourlens[i] -= offlens[i];
2945:   }
2946:   MatSetSizes(newMat,m,n,M,N);

2948:   if (bs > 1) {MatSetBlockSize(newMat,bs);}

2950:   MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);

2952:   for (i=0; i<m; i++) {
2953:     ourlens[i] += offlens[i];
2954:   }

2956:   if (!rank) {
2957:     PetscMalloc1(maxnz+1,&vals);

2959:     /* read in my part of the matrix numerical values  */
2960:     nz   = procsnz[0];
2961:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);

2963:     /* insert into matrix */
2964:     jj      = rstart;
2965:     smycols = mycols;
2966:     svals   = vals;
2967:     for (i=0; i<m; i++) {
2968:       MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
2969:       smycols += ourlens[i];
2970:       svals   += ourlens[i];
2971:       jj++;
2972:     }

2974:     /* read in other processors and ship out */
2975:     for (i=1; i<size; i++) {
2976:       nz   = procsnz[i];
2977:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2978:       MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);
2979:     }
2980:     PetscFree(procsnz);
2981:   } else {
2982:     /* receive numeric values */
2983:     PetscMalloc1(nz+1,&vals);

2985:     /* receive message of values*/
2986:     MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);

2988:     /* insert into matrix */
2989:     jj      = rstart;
2990:     smycols = mycols;
2991:     svals   = vals;
2992:     for (i=0; i<m; i++) {
2993:       MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
2994:       smycols += ourlens[i];
2995:       svals   += ourlens[i];
2996:       jj++;
2997:     }
2998:   }
2999:   PetscFree2(ourlens,offlens);
3000:   PetscFree(vals);
3001:   PetscFree(mycols);
3002:   PetscFree(rowners);
3003:   MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);
3004:   MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);
3005:   return(0);
3006: }

3008: /* Not scalable because of ISAllGather() unless getting all columns. */
3009: PetscErrorCode ISGetSeqIS_Private(Mat mat,IS iscol,IS *isseq)
3010: {
3012:   IS             iscol_local;
3013:   PetscBool      isstride;
3014:   PetscMPIInt    lisstride=0,gisstride;

3017:   /* check if we are grabbing all columns*/
3018:   PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);

3020:   if (isstride) {
3021:     PetscInt  start,len,mstart,mlen;
3022:     ISStrideGetInfo(iscol,&start,NULL);
3023:     ISGetLocalSize(iscol,&len);
3024:     MatGetOwnershipRangeColumn(mat,&mstart,&mlen);
3025:     if (mstart == start && mlen-mstart == len) lisstride = 1;
3026:   }

3028:   MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));
3029:   if (gisstride) {
3030:     PetscInt N;
3031:     MatGetSize(mat,NULL,&N);
3032:     ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);
3033:     ISSetIdentity(iscol_local);
3034:     PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");
3035:   } else {
3036:     PetscInt cbs;
3037:     ISGetBlockSize(iscol,&cbs);
3038:     ISAllGather(iscol,&iscol_local);
3039:     ISSetBlockSize(iscol_local,cbs);
3040:   }

3042:   *isseq = iscol_local;
3043:   return(0);
3044: }

3046: /*
3047:  Used by MatCreateSubMatrix_MPIAIJ_SameRowColDist() to avoid ISAllGather() and global size of iscol_local
3048:  (see MatCreateSubMatrix_MPIAIJ_nonscalable)

3050:  Input Parameters:
3051:    mat - matrix
3052:    isrow - parallel row index set; its local indices are a subset of local columns of mat,
3053:            i.e., mat->rstart <= isrow[i] < mat->rend
3054:    iscol - parallel column index set; its local indices are a subset of local columns of mat,
3055:            i.e., mat->cstart <= iscol[i] < mat->cend
3056:  Output Parameter:
3057:    isrow_d,iscol_d - sequential row and column index sets for retrieving mat->A
3058:    iscol_o - sequential column index set for retrieving mat->B
3059:    garray - column map; garray[i] indicates global location of iscol_o[i] in iscol
3060:  */
3061: PetscErrorCode ISGetSeqIS_SameColDist_Private(Mat mat,IS isrow,IS iscol,IS *isrow_d,IS *iscol_d,IS *iscol_o,const PetscInt *garray[])
3062: {
3064:   Vec            x,cmap;
3065:   const PetscInt *is_idx;
3066:   PetscScalar    *xarray,*cmaparray;
3067:   PetscInt       ncols,isstart,*idx,m,rstart,*cmap1,count;
3068:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)mat->data;
3069:   Mat            B=a->B;
3070:   Vec            lvec=a->lvec,lcmap;
3071:   PetscInt       i,cstart,cend,Bn=B->cmap->N;
3072:   MPI_Comm       comm;
3073:   VecScatter     Mvctx=a->Mvctx;

3076:   PetscObjectGetComm((PetscObject)mat,&comm);
3077:   ISGetLocalSize(iscol,&ncols);

3079:   /* (1) iscol is a sub-column vector of mat, pad it with '-1.' to form a full vector x */
3080:   MatCreateVecs(mat,&x,NULL);
3081:   VecSet(x,-1.0);
3082:   VecDuplicate(x,&cmap);
3083:   VecSet(cmap,-1.0);

3085:   /* Get start indices */
3086:   MPI_Scan(&ncols,&isstart,1,MPIU_INT,MPI_SUM,comm);
3087:   isstart -= ncols;
3088:   MatGetOwnershipRangeColumn(mat,&cstart,&cend);

3090:   ISGetIndices(iscol,&is_idx);
3091:   VecGetArray(x,&xarray);
3092:   VecGetArray(cmap,&cmaparray);
3093:   PetscMalloc1(ncols,&idx);
3094:   for (i=0; i<ncols; i++) {
3095:     xarray[is_idx[i]-cstart]    = (PetscScalar)is_idx[i];
3096:     cmaparray[is_idx[i]-cstart] = i + isstart;      /* global index of iscol[i] */
3097:     idx[i]                      = is_idx[i]-cstart; /* local index of iscol[i]  */
3098:   }
3099:   VecRestoreArray(x,&xarray);
3100:   VecRestoreArray(cmap,&cmaparray);
3101:   ISRestoreIndices(iscol,&is_idx);

3103:   /* Get iscol_d */
3104:   ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,iscol_d);
3105:   ISGetBlockSize(iscol,&i);
3106:   ISSetBlockSize(*iscol_d,i);

3108:   /* Get isrow_d */
3109:   ISGetLocalSize(isrow,&m);
3110:   rstart = mat->rmap->rstart;
3111:   PetscMalloc1(m,&idx);
3112:   ISGetIndices(isrow,&is_idx);
3113:   for (i=0; i<m; i++) idx[i] = is_idx[i]-rstart;
3114:   ISRestoreIndices(isrow,&is_idx);

3116:   ISCreateGeneral(PETSC_COMM_SELF,m,idx,PETSC_OWN_POINTER,isrow_d);
3117:   ISGetBlockSize(isrow,&i);
3118:   ISSetBlockSize(*isrow_d,i);

3120:   /* (2) Scatter x and cmap using aij->Mvctx to get their off-process portions (see MatMult_MPIAIJ) */
3121:   VecScatterBegin(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);
3122:   VecScatterEnd(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);

3124:   VecDuplicate(lvec,&lcmap);

3126:   VecScatterBegin(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);
3127:   VecScatterEnd(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);

3129:   /* (3) create sequential iscol_o (a subset of iscol) and isgarray */
3130:   /* off-process column indices */
3131:   count = 0;
3132:   PetscMalloc1(Bn,&idx);
3133:   PetscMalloc1(Bn,&cmap1);

3135:   VecGetArray(lvec,&xarray);
3136:   VecGetArray(lcmap,&cmaparray);
3137:   for (i=0; i<Bn; i++) {
3138:     if (PetscRealPart(xarray[i]) > -1.0) {
3139:       idx[count]     = i;                   /* local column index in off-diagonal part B */
3140:       cmap1[count] = (PetscInt)PetscRealPart(cmaparray[i]);  /* column index in submat */
3141:       count++;
3142:     }
3143:   }
3144:   VecRestoreArray(lvec,&xarray);
3145:   VecRestoreArray(lcmap,&cmaparray);

3147:   ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,iscol_o);
3148:   /* cannot ensure iscol_o has same blocksize as iscol! */

3150:   PetscFree(idx);
3151:   *garray = cmap1;

3153:   VecDestroy(&x);
3154:   VecDestroy(&cmap);
3155:   VecDestroy(&lcmap);
3156:   return(0);
3157: }

3159: /* isrow and iscol have same processor distribution as mat, output *submat is a submatrix of local mat */
3160: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *submat)
3161: {
3163:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)mat->data,*asub;
3164:   Mat            M = NULL;
3165:   MPI_Comm       comm;
3166:   IS             iscol_d,isrow_d,iscol_o;
3167:   Mat            Asub = NULL,Bsub = NULL;
3168:   PetscInt       n;

3171:   PetscObjectGetComm((PetscObject)mat,&comm);

3173:   if (call == MAT_REUSE_MATRIX) {
3174:     /* Retrieve isrow_d, iscol_d and iscol_o from submat */
3175:     PetscObjectQuery((PetscObject)*submat,"isrow_d",(PetscObject*)&isrow_d);
3176:     if (!isrow_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"isrow_d passed in was not used before, cannot reuse");

3178:     PetscObjectQuery((PetscObject)*submat,"iscol_d",(PetscObject*)&iscol_d);
3179:     if (!iscol_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_d passed in was not used before, cannot reuse");

3181:     PetscObjectQuery((PetscObject)*submat,"iscol_o",(PetscObject*)&iscol_o);
3182:     if (!iscol_o) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_o passed in was not used before, cannot reuse");

3184:     /* Update diagonal and off-diagonal portions of submat */
3185:     asub = (Mat_MPIAIJ*)(*submat)->data;
3186:     MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->A);
3187:     ISGetLocalSize(iscol_o,&n);
3188:     if (n) {
3189:       MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->B);
3190:     }
3191:     MatAssemblyBegin(*submat,MAT_FINAL_ASSEMBLY);
3192:     MatAssemblyEnd(*submat,MAT_FINAL_ASSEMBLY);

3194:   } else { /* call == MAT_INITIAL_MATRIX) */
3195:     const PetscInt *garray;
3196:     PetscInt        BsubN;

3198:     /* Create isrow_d, iscol_d, iscol_o and isgarray (replace isgarray with array?) */
3199:     ISGetSeqIS_SameColDist_Private(mat,isrow,iscol,&isrow_d,&iscol_d,&iscol_o,&garray);

3201:     /* Create local submatrices Asub and Bsub */
3202:     MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Asub);
3203:     MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Bsub);

3205:     /* Create submatrix M */
3206:     MatCreateMPIAIJWithSeqAIJ(comm,Asub,Bsub,garray,&M);

3208:     /* If Bsub has empty columns, compress iscol_o such that it will retrieve condensed Bsub from a->B during reuse */
3209:     asub = (Mat_MPIAIJ*)M->data;

3211:     ISGetLocalSize(iscol_o,&BsubN);
3212:     n = asub->B->cmap->N;
3213:     if (BsubN > n) {
3214:       /* This case can be tested using ~petsc/src/tao/bound/examples/tutorials/runplate2_3 */
3215:       const PetscInt *idx;
3216:       PetscInt       i,j,*idx_new,*subgarray = asub->garray;
3217:       PetscInfo2(M,"submatrix Bn %D != BsubN %D, update iscol_o\n",n,BsubN);

3219:       PetscMalloc1(n,&idx_new);
3220:       j = 0;
3221:       ISGetIndices(iscol_o,&idx);
3222:       for (i=0; i<n; i++) {
3223:         if (j >= BsubN) break;
3224:         while (subgarray[i] > garray[j]) j++;

3226:         if (subgarray[i] == garray[j]) {
3227:           idx_new[i] = idx[j++];
3228:         } else SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"subgarray[%D]=%D cannot < garray[%D]=%D",i,subgarray[i],j,garray[j]);
3229:       }
3230:       ISRestoreIndices(iscol_o,&idx);

3232:       ISDestroy(&iscol_o);
3233:       ISCreateGeneral(PETSC_COMM_SELF,n,idx_new,PETSC_OWN_POINTER,&iscol_o);

3235:     } else if (BsubN < n) {
3236:       SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Columns of Bsub cannot be smaller than B's",BsubN,asub->B->cmap->N);
3237:     }

3239:     PetscFree(garray);
3240:     *submat = M;

3242:     /* Save isrow_d, iscol_d and iscol_o used in processor for next request */
3243:     PetscObjectCompose((PetscObject)M,"isrow_d",(PetscObject)isrow_d);
3244:     ISDestroy(&isrow_d);

3246:     PetscObjectCompose((PetscObject)M,"iscol_d",(PetscObject)iscol_d);
3247:     ISDestroy(&iscol_d);

3249:     PetscObjectCompose((PetscObject)M,"iscol_o",(PetscObject)iscol_o);
3250:     ISDestroy(&iscol_o);
3251:   }
3252:   return(0);
3253: }

3255: PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
3256: {
3258:   IS             iscol_local=NULL,isrow_d;
3259:   PetscInt       csize;
3260:   PetscInt       n,i,j,start,end;
3261:   PetscBool      sameRowDist=PETSC_FALSE,sameDist[2],tsameDist[2];
3262:   MPI_Comm       comm;

3265:   /* If isrow has same processor distribution as mat,
3266:      call MatCreateSubMatrix_MPIAIJ_SameRowDist() to avoid using a hash table with global size of iscol */
3267:   if (call == MAT_REUSE_MATRIX) {
3268:     PetscObjectQuery((PetscObject)*newmat,"isrow_d",(PetscObject*)&isrow_d);
3269:     if (isrow_d) {
3270:       sameRowDist  = PETSC_TRUE;
3271:       tsameDist[1] = PETSC_TRUE; /* sameColDist */
3272:     } else {
3273:       PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);
3274:       if (iscol_local) {
3275:         sameRowDist  = PETSC_TRUE;
3276:         tsameDist[1] = PETSC_FALSE; /* !sameColDist */
3277:       }
3278:     }
3279:   } else {
3280:     /* Check if isrow has same processor distribution as mat */
3281:     sameDist[0] = PETSC_FALSE;
3282:     ISGetLocalSize(isrow,&n);
3283:     if (!n) {
3284:       sameDist[0] = PETSC_TRUE;
3285:     } else {
3286:       ISGetMinMax(isrow,&i,&j);
3287:       MatGetOwnershipRange(mat,&start,&end);
3288:       if (i >= start && j < end) {
3289:         sameDist[0] = PETSC_TRUE;
3290:       }
3291:     }

3293:     /* Check if iscol has same processor distribution as mat */
3294:     sameDist[1] = PETSC_FALSE;
3295:     ISGetLocalSize(iscol,&n);
3296:     if (!n) {
3297:       sameDist[1] = PETSC_TRUE;
3298:     } else {
3299:       ISGetMinMax(iscol,&i,&j);
3300:       MatGetOwnershipRangeColumn(mat,&start,&end);
3301:       if (i >= start && j < end) sameDist[1] = PETSC_TRUE;
3302:     }

3304:     PetscObjectGetComm((PetscObject)mat,&comm);
3305:     MPIU_Allreduce(&sameDist,&tsameDist,2,MPIU_BOOL,MPI_LAND,comm);
3306:     sameRowDist = tsameDist[0];
3307:   }

3309:   if (sameRowDist) {
3310:     if (tsameDist[1]) { /* sameRowDist & sameColDist */
3311:       /* isrow and iscol have same processor distribution as mat */
3312:       MatCreateSubMatrix_MPIAIJ_SameRowColDist(mat,isrow,iscol,call,newmat);
3313:       return(0);
3314:     } else { /* sameRowDist */
3315:       /* isrow has same processor distribution as mat */
3316:       if (call == MAT_INITIAL_MATRIX) {
3317:         PetscBool sorted;
3318:         ISGetSeqIS_Private(mat,iscol,&iscol_local);
3319:         ISGetLocalSize(iscol_local,&n); /* local size of iscol_local = global columns of newmat */
3320:         ISGetSize(iscol,&i);
3321:         if (n != i) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"n %d != size of iscol %d",n,i);

3323:         ISSorted(iscol_local,&sorted);
3324:         if (sorted) {
3325:           /* MatCreateSubMatrix_MPIAIJ_SameRowDist() requires iscol_local be sorted; it can have duplicate indices */
3326:           MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,iscol_local,MAT_INITIAL_MATRIX,newmat);
3327:           return(0);
3328:         }
3329:       } else { /* call == MAT_REUSE_MATRIX */
3330:         IS    iscol_sub;
3331:         PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3332:         if (iscol_sub) {
3333:           MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,NULL,call,newmat);
3334:           return(0);
3335:         }
3336:       }
3337:     }
3338:   }

3340:   /* General case: iscol -> iscol_local which has global size of iscol */
3341:   if (call == MAT_REUSE_MATRIX) {
3342:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
3343:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3344:   } else {
3345:     if (!iscol_local) {
3346:       ISGetSeqIS_Private(mat,iscol,&iscol_local);
3347:     }
3348:   }

3350:   ISGetLocalSize(iscol,&csize);
3351:   MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);

3353:   if (call == MAT_INITIAL_MATRIX) {
3354:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
3355:     ISDestroy(&iscol_local);
3356:   }
3357:   return(0);
3358: }

3360: /*@C
3361:      MatCreateMPIAIJWithSeqAIJ - creates a MPIAIJ matrix using SeqAIJ matrices that contain the "diagonal"
3362:          and "off-diagonal" part of the matrix in CSR format.

3364:    Collective on MPI_Comm

3366:    Input Parameters:
3367: +  comm - MPI communicator
3368: .  A - "diagonal" portion of matrix
3369: .  B - "off-diagonal" portion of matrix, may have empty columns, will be destroyed by this routine
3370: -  garray - global index of B columns

3372:    Output Parameter:
3373: .   mat - the matrix, with input A as its local diagonal matrix
3374:    Level: advanced

3376:    Notes:
3377:        See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix.
3378:        A becomes part of output mat, B is destroyed by this routine. The user cannot use A and B anymore.

3380: .seealso: MatCreateMPIAIJWithSplitArrays()
3381: @*/
3382: PetscErrorCode MatCreateMPIAIJWithSeqAIJ(MPI_Comm comm,Mat A,Mat B,const PetscInt garray[],Mat *mat)
3383: {
3385:   Mat_MPIAIJ     *maij;
3386:   Mat_SeqAIJ     *b=(Mat_SeqAIJ*)B->data,*bnew;
3387:   PetscInt       *oi=b->i,*oj=b->j,i,nz,col;
3388:   PetscScalar    *oa=b->a;
3389:   Mat            Bnew;
3390:   PetscInt       m,n,N;

3393:   MatCreate(comm,mat);
3394:   MatGetSize(A,&m,&n);
3395:   if (m != B->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Am %D != Bm %D",m,B->rmap->N);
3396:   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);
3397:   /* remove check below; When B is created using iscol_o from ISGetSeqIS_SameColDist_Private(), its bs may not be same as A */
3398:   /* 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); */

3400:   /* Get global columns of mat */
3401:   MPIU_Allreduce(&n,&N,1,MPIU_INT,MPI_SUM,comm);

3403:   MatSetSizes(*mat,m,n,PETSC_DECIDE,N);
3404:   MatSetType(*mat,MATMPIAIJ);
3405:   MatSetBlockSizes(*mat,A->rmap->bs,A->cmap->bs);
3406:   maij = (Mat_MPIAIJ*)(*mat)->data;

3408:   (*mat)->preallocated = PETSC_TRUE;

3410:   PetscLayoutSetUp((*mat)->rmap);
3411:   PetscLayoutSetUp((*mat)->cmap);

3413:   /* Set A as diagonal portion of *mat */
3414:   maij->A = A;

3416:   nz = oi[m];
3417:   for (i=0; i<nz; i++) {
3418:     col   = oj[i];
3419:     oj[i] = garray[col];
3420:   }

3422:    /* Set Bnew as off-diagonal portion of *mat */
3423:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,N,oi,oj,oa,&Bnew);
3424:   bnew        = (Mat_SeqAIJ*)Bnew->data;
3425:   bnew->maxnz = b->maxnz; /* allocated nonzeros of B */
3426:   maij->B     = Bnew;

3428:   if (B->rmap->N != Bnew->rmap->N) SETERRQ2(PETSC_COMM_SELF,0,"BN %d != BnewN %d",B->rmap->N,Bnew->rmap->N);

3430:   b->singlemalloc = PETSC_FALSE; /* B arrays are shared by Bnew */
3431:   b->free_a       = PETSC_FALSE;
3432:   b->free_ij      = PETSC_FALSE;
3433:   MatDestroy(&B);

3435:   bnew->singlemalloc = PETSC_TRUE; /* arrays will be freed by MatDestroy(&Bnew) */
3436:   bnew->free_a       = PETSC_TRUE;
3437:   bnew->free_ij      = PETSC_TRUE;

3439:   /* condense columns of maij->B */
3440:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
3441:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
3442:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
3443:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
3444:   MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3445:   return(0);
3446: }

3448: extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*);

3450: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat mat,IS isrow,IS iscol,IS iscol_local,MatReuse call,Mat *newmat)
3451: {
3453:   PetscInt       i,m,n,rstart,row,rend,nz,j,bs,cbs;
3454:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3455:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)mat->data;
3456:   Mat            M,Msub,B=a->B;
3457:   MatScalar      *aa;
3458:   Mat_SeqAIJ     *aij;
3459:   PetscInt       *garray = a->garray,*colsub,Ncols;
3460:   PetscInt       count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend;
3461:   IS             iscol_sub,iscmap;
3462:   const PetscInt *is_idx,*cmap;
3463:   PetscBool      allcolumns=PETSC_FALSE;
3464:   MPI_Comm       comm;

3467:   PetscObjectGetComm((PetscObject)mat,&comm);

3469:   if (call == MAT_REUSE_MATRIX) {
3470:     PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3471:     if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse");
3472:     ISGetLocalSize(iscol_sub,&count);

3474:     PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);
3475:     if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse");

3477:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);
3478:     if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");

3480:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);

3482:   } else { /* call == MAT_INITIAL_MATRIX) */
3483:     PetscBool flg;

3485:     ISGetLocalSize(iscol,&n);
3486:     ISGetSize(iscol,&Ncols);

3488:     /* (1) iscol -> nonscalable iscol_local */
3489:     /* Check for special case: each processor gets entire matrix columns */
3490:     ISIdentity(iscol_local,&flg);
3491:     if (flg && n == mat->cmap->N) allcolumns = PETSC_TRUE;
3492:     if (allcolumns) {
3493:       iscol_sub = iscol_local;
3494:       PetscObjectReference((PetscObject)iscol_local);
3495:       ISCreateStride(PETSC_COMM_SELF,n,0,1,&iscmap);

3497:     } else {
3498:       /* (2) iscol_local -> iscol_sub and iscmap. Implementation below requires iscol_local be sorted, it can have duplicate indices */
3499:       PetscInt *idx,*cmap1,k;
3500:       PetscMalloc1(Ncols,&idx);
3501:       PetscMalloc1(Ncols,&cmap1);
3502:       ISGetIndices(iscol_local,&is_idx);
3503:       count = 0;
3504:       k     = 0;
3505:       for (i=0; i<Ncols; i++) {
3506:         j = is_idx[i];
3507:         if (j >= cstart && j < cend) {
3508:           /* diagonal part of mat */
3509:           idx[count]     = j;
3510:           cmap1[count++] = i; /* column index in submat */
3511:         } else if (Bn) {
3512:           /* off-diagonal part of mat */
3513:           if (j == garray[k]) {
3514:             idx[count]     = j;
3515:             cmap1[count++] = i;  /* column index in submat */
3516:           } else if (j > garray[k]) {
3517:             while (j > garray[k] && k < Bn-1) k++;
3518:             if (j == garray[k]) {
3519:               idx[count]     = j;
3520:               cmap1[count++] = i; /* column index in submat */
3521:             }
3522:           }
3523:         }
3524:       }
3525:       ISRestoreIndices(iscol_local,&is_idx);

3527:       ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_OWN_POINTER,&iscol_sub);
3528:       ISGetBlockSize(iscol,&cbs);
3529:       ISSetBlockSize(iscol_sub,cbs);

3531:       ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_OWN_POINTER,&iscmap);
3532:     }

3534:     /* (3) Create sequential Msub */
3535:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,allcolumns,&Msub);
3536:   }

3538:   ISGetLocalSize(iscol_sub,&count);
3539:   aij  = (Mat_SeqAIJ*)(Msub)->data;
3540:   ii   = aij->i;
3541:   ISGetIndices(iscmap,&cmap);

3543:   /*
3544:       m - number of local rows
3545:       Ncols - number of columns (same on all processors)
3546:       rstart - first row in new global matrix generated
3547:   */
3548:   MatGetSize(Msub,&m,NULL);

3550:   if (call == MAT_INITIAL_MATRIX) {
3551:     /* (4) Create parallel newmat */
3552:     PetscMPIInt    rank,size;
3553:     PetscInt       csize;

3555:     MPI_Comm_size(comm,&size);
3556:     MPI_Comm_rank(comm,&rank);

3558:     /*
3559:         Determine the number of non-zeros in the diagonal and off-diagonal
3560:         portions of the matrix in order to do correct preallocation
3561:     */

3563:     /* first get start and end of "diagonal" columns */
3564:     ISGetLocalSize(iscol,&csize);
3565:     if (csize == PETSC_DECIDE) {
3566:       ISGetSize(isrow,&mglobal);
3567:       if (mglobal == Ncols) { /* square matrix */
3568:         nlocal = m;
3569:       } else {
3570:         nlocal = Ncols/size + ((Ncols % size) > rank);
3571:       }
3572:     } else {
3573:       nlocal = csize;
3574:     }
3575:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3576:     rstart = rend - nlocal;
3577:     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);

3579:     /* next, compute all the lengths */
3580:     jj    = aij->j;
3581:     PetscMalloc1(2*m+1,&dlens);
3582:     olens = dlens + m;
3583:     for (i=0; i<m; i++) {
3584:       jend = ii[i+1] - ii[i];
3585:       olen = 0;
3586:       dlen = 0;
3587:       for (j=0; j<jend; j++) {
3588:         if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++;
3589:         else dlen++;
3590:         jj++;
3591:       }
3592:       olens[i] = olen;
3593:       dlens[i] = dlen;
3594:     }

3596:     ISGetBlockSize(isrow,&bs);
3597:     ISGetBlockSize(iscol,&cbs);

3599:     MatCreate(comm,&M);
3600:     MatSetSizes(M,m,nlocal,PETSC_DECIDE,Ncols);
3601:     MatSetBlockSizes(M,bs,cbs);
3602:     MatSetType(M,((PetscObject)mat)->type_name);
3603:     MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3604:     PetscFree(dlens);

3606:   } else { /* call == MAT_REUSE_MATRIX */
3607:     M    = *newmat;
3608:     MatGetLocalSize(M,&i,NULL);
3609:     if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3610:     MatZeroEntries(M);
3611:     /*
3612:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3613:        rather than the slower MatSetValues().
3614:     */
3615:     M->was_assembled = PETSC_TRUE;
3616:     M->assembled     = PETSC_FALSE;
3617:   }

3619:   /* (5) Set values of Msub to *newmat */
3620:   PetscMalloc1(count,&colsub);
3621:   MatGetOwnershipRange(M,&rstart,NULL);

3623:   jj   = aij->j;
3624:   aa   = aij->a;
3625:   for (i=0; i<m; i++) {
3626:     row = rstart + i;
3627:     nz  = ii[i+1] - ii[i];
3628:     for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]];
3629:     MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);
3630:     jj += nz; aa += nz;
3631:   }
3632:   ISRestoreIndices(iscmap,&cmap);

3634:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3635:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);

3637:   PetscFree(colsub);

3639:   /* save Msub, iscol_sub and iscmap used in processor for next request */
3640:   if (call ==  MAT_INITIAL_MATRIX) {
3641:     *newmat = M;
3642:     PetscObjectCompose((PetscObject)(*newmat),"SubMatrix",(PetscObject)Msub);
3643:     MatDestroy(&Msub);

3645:     PetscObjectCompose((PetscObject)(*newmat),"SubIScol",(PetscObject)iscol_sub);
3646:     ISDestroy(&iscol_sub);

3648:     PetscObjectCompose((PetscObject)(*newmat),"Subcmap",(PetscObject)iscmap);
3649:     ISDestroy(&iscmap);

3651:     if (iscol_local) {
3652:       PetscObjectCompose((PetscObject)(*newmat),"ISAllGather",(PetscObject)iscol_local);
3653:       ISDestroy(&iscol_local);
3654:     }
3655:   }
3656:   return(0);
3657: }

3659: /*
3660:     Not great since it makes two copies of the submatrix, first an SeqAIJ
3661:   in local and then by concatenating the local matrices the end result.
3662:   Writing it directly would be much like MatCreateSubMatrices_MPIAIJ()

3664:   Note: This requires a sequential iscol with all indices.
3665: */
3666: PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
3667: {
3669:   PetscMPIInt    rank,size;
3670:   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs;
3671:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3672:   Mat            M,Mreuse;
3673:   MatScalar      *aa,*vwork;
3674:   MPI_Comm       comm;
3675:   Mat_SeqAIJ     *aij;
3676:   PetscBool      colflag,allcolumns=PETSC_FALSE;

3679:   PetscObjectGetComm((PetscObject)mat,&comm);
3680:   MPI_Comm_rank(comm,&rank);
3681:   MPI_Comm_size(comm,&size);

3683:   /* Check for special case: each processor gets entire matrix columns */
3684:   ISIdentity(iscol,&colflag);
3685:   ISGetLocalSize(iscol,&n);
3686:   if (colflag && n == mat->cmap->N) allcolumns = PETSC_TRUE;

3688:   if (call ==  MAT_REUSE_MATRIX) {
3689:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
3690:     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3691:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,allcolumns,&Mreuse);
3692:   } else {
3693:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,allcolumns,&Mreuse);
3694:   }

3696:   /*
3697:       m - number of local rows
3698:       n - number of columns (same on all processors)
3699:       rstart - first row in new global matrix generated
3700:   */
3701:   MatGetSize(Mreuse,&m,&n);
3702:   MatGetBlockSizes(Mreuse,&bs,&cbs);
3703:   if (call == MAT_INITIAL_MATRIX) {
3704:     aij = (Mat_SeqAIJ*)(Mreuse)->data;
3705:     ii  = aij->i;
3706:     jj  = aij->j;

3708:     /*
3709:         Determine the number of non-zeros in the diagonal and off-diagonal
3710:         portions of the matrix in order to do correct preallocation
3711:     */

3713:     /* first get start and end of "diagonal" columns */
3714:     if (csize == PETSC_DECIDE) {
3715:       ISGetSize(isrow,&mglobal);
3716:       if (mglobal == n) { /* square matrix */
3717:         nlocal = m;
3718:       } else {
3719:         nlocal = n/size + ((n % size) > rank);
3720:       }
3721:     } else {
3722:       nlocal = csize;
3723:     }
3724:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3725:     rstart = rend - nlocal;
3726:     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);

3728:     /* next, compute all the lengths */
3729:     PetscMalloc1(2*m+1,&dlens);
3730:     olens = dlens + m;
3731:     for (i=0; i<m; i++) {
3732:       jend = ii[i+1] - ii[i];
3733:       olen = 0;
3734:       dlen = 0;
3735:       for (j=0; j<jend; j++) {
3736:         if (*jj < rstart || *jj >= rend) olen++;
3737:         else dlen++;
3738:         jj++;
3739:       }
3740:       olens[i] = olen;
3741:       dlens[i] = dlen;
3742:     }
3743:     MatCreate(comm,&M);
3744:     MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);
3745:     MatSetBlockSizes(M,bs,cbs);
3746:     MatSetType(M,((PetscObject)mat)->type_name);
3747:     MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3748:     PetscFree(dlens);
3749:   } else {
3750:     PetscInt ml,nl;

3752:     M    = *newmat;
3753:     MatGetLocalSize(M,&ml,&nl);
3754:     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3755:     MatZeroEntries(M);
3756:     /*
3757:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3758:        rather than the slower MatSetValues().
3759:     */
3760:     M->was_assembled = PETSC_TRUE;
3761:     M->assembled     = PETSC_FALSE;
3762:   }
3763:   MatGetOwnershipRange(M,&rstart,&rend);
3764:   aij  = (Mat_SeqAIJ*)(Mreuse)->data;
3765:   ii   = aij->i;
3766:   jj   = aij->j;
3767:   aa   = aij->a;
3768:   for (i=0; i<m; i++) {
3769:     row   = rstart + i;
3770:     nz    = ii[i+1] - ii[i];
3771:     cwork = jj;     jj += nz;
3772:     vwork = aa;     aa += nz;
3773:     MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
3774:   }

3776:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3777:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3778:   *newmat = M;

3780:   /* save submatrix used in processor for next request */
3781:   if (call ==  MAT_INITIAL_MATRIX) {
3782:     PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
3783:     MatDestroy(&Mreuse);
3784:   }
3785:   return(0);
3786: }

3788: PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
3789: {
3790:   PetscInt       m,cstart, cend,j,nnz,i,d;
3791:   PetscInt       *d_nnz,*o_nnz,nnz_max = 0,rstart,ii;
3792:   const PetscInt *JJ;
3793:   PetscScalar    *values;
3795:   PetscBool      nooffprocentries;

3798:   if (Ii && Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]);

3800:   PetscLayoutSetUp(B->rmap);
3801:   PetscLayoutSetUp(B->cmap);
3802:   m      = B->rmap->n;
3803:   cstart = B->cmap->rstart;
3804:   cend   = B->cmap->rend;
3805:   rstart = B->rmap->rstart;

3807:   PetscMalloc2(m,&d_nnz,m,&o_nnz);

3809: #if defined(PETSC_USE_DEBUG)
3810:   for (i=0; i<m; i++) {
3811:     nnz = Ii[i+1]- Ii[i];
3812:     JJ  = J + Ii[i];
3813:     if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz);
3814:     if (nnz && (JJ[0] < 0)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,JJ[0]);
3815:     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);
3816:   }
3817: #endif

3819:   for (i=0; i<m; i++) {
3820:     nnz     = Ii[i+1]- Ii[i];
3821:     JJ      = J + Ii[i];
3822:     nnz_max = PetscMax(nnz_max,nnz);
3823:     d       = 0;
3824:     for (j=0; j<nnz; j++) {
3825:       if (cstart <= JJ[j] && JJ[j] < cend) d++;
3826:     }
3827:     d_nnz[i] = d;
3828:     o_nnz[i] = nnz - d;
3829:   }
3830:   MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
3831:   PetscFree2(d_nnz,o_nnz);

3833:   if (v) values = (PetscScalar*)v;
3834:   else {
3835:     PetscCalloc1(nnz_max+1,&values);
3836:   }

3838:   for (i=0; i<m; i++) {
3839:     ii   = i + rstart;
3840:     nnz  = Ii[i+1]- Ii[i];
3841:     MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);
3842:   }
3843:   nooffprocentries    = B->nooffprocentries;
3844:   B->nooffprocentries = PETSC_TRUE;
3845:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3846:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
3847:   B->nooffprocentries = nooffprocentries;

3849:   if (!v) {
3850:     PetscFree(values);
3851:   }
3852:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3853:   return(0);
3854: }

3856: /*@
3857:    MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format
3858:    (the default parallel PETSc format).

3860:    Collective on MPI_Comm

3862:    Input Parameters:
3863: +  B - the matrix
3864: .  i - the indices into j for the start of each local row (starts with zero)
3865: .  j - the column indices for each local row (starts with zero)
3866: -  v - optional values in the matrix

3868:    Level: developer

3870:    Notes:
3871:        The i, j, and v arrays ARE copied by this routine into the internal format used by PETSc;
3872:      thus you CANNOT change the matrix entries by changing the values of v[] after you have
3873:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3875:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3877:        The format which is used for the sparse matrix input, is equivalent to a
3878:     row-major ordering.. i.e for the following matrix, the input data expected is
3879:     as shown

3881: $        1 0 0
3882: $        2 0 3     P0
3883: $       -------
3884: $        4 5 6     P1
3885: $
3886: $     Process0 [P0]: rows_owned=[0,1]
3887: $        i =  {0,1,3}  [size = nrow+1  = 2+1]
3888: $        j =  {0,0,2}  [size = 3]
3889: $        v =  {1,2,3}  [size = 3]
3890: $
3891: $     Process1 [P1]: rows_owned=[2]
3892: $        i =  {0,3}    [size = nrow+1  = 1+1]
3893: $        j =  {0,1,2}  [size = 3]
3894: $        v =  {4,5,6}  [size = 3]

3896: .keywords: matrix, aij, compressed row, sparse, parallel

3898: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ,
3899:           MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays()
3900: @*/
3901: PetscErrorCode  MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3902: {

3906:   PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));
3907:   return(0);
3908: }

3910: /*@C
3911:    MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format
3912:    (the default parallel PETSc format).  For good matrix assembly performance
3913:    the user should preallocate the matrix storage by setting the parameters
3914:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3915:    performance can be increased by more than a factor of 50.

3917:    Collective on MPI_Comm

3919:    Input Parameters:
3920: +  B - the matrix
3921: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
3922:            (same value is used for all local rows)
3923: .  d_nnz - array containing the number of nonzeros in the various rows of the
3924:            DIAGONAL portion of the local submatrix (possibly different for each row)
3925:            or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
3926:            The size of this array is equal to the number of local rows, i.e 'm'.
3927:            For matrices that will be factored, you must leave room for (and set)
3928:            the diagonal entry even if it is zero.
3929: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
3930:            submatrix (same value is used for all local rows).
3931: -  o_nnz - array containing the number of nonzeros in the various rows of the
3932:            OFF-DIAGONAL portion of the local submatrix (possibly different for
3933:            each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
3934:            structure. The size of this array is equal to the number
3935:            of local rows, i.e 'm'.

3937:    If the *_nnz parameter is given then the *_nz parameter is ignored

3939:    The AIJ format (also called the Yale sparse matrix format or
3940:    compressed row storage (CSR)), is fully compatible with standard Fortran 77
3941:    storage.  The stored row and column indices begin with zero.
3942:    See Users-Manual: ch_mat for details.

3944:    The parallel matrix is partitioned such that the first m0 rows belong to
3945:    process 0, the next m1 rows belong to process 1, the next m2 rows belong
3946:    to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.

3948:    The DIAGONAL portion of the local submatrix of a processor can be defined
3949:    as the submatrix which is obtained by extraction the part corresponding to
3950:    the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
3951:    first row that belongs to the processor, r2 is the last row belonging to
3952:    the this processor, and c1-c2 is range of indices of the local part of a
3953:    vector suitable for applying the matrix to.  This is an mxn matrix.  In the
3954:    common case of a square matrix, the row and column ranges are the same and
3955:    the DIAGONAL part is also square. The remaining portion of the local
3956:    submatrix (mxN) constitute the OFF-DIAGONAL portion.

3958:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

3960:    You can call MatGetInfo() to get information on how effective the preallocation was;
3961:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3962:    You can also run with the option -info and look for messages with the string
3963:    malloc in them to see if additional memory allocation was needed.

3965:    Example usage:

3967:    Consider the following 8x8 matrix with 34 non-zero values, that is
3968:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
3969:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
3970:    as follows:

3972: .vb
3973:             1  2  0  |  0  3  0  |  0  4
3974:     Proc0   0  5  6  |  7  0  0  |  8  0
3975:             9  0 10  | 11  0  0  | 12  0
3976:     -------------------------------------
3977:            13  0 14  | 15 16 17  |  0  0
3978:     Proc1   0 18  0  | 19 20 21  |  0  0
3979:             0  0  0  | 22 23  0  | 24  0
3980:     -------------------------------------
3981:     Proc2  25 26 27  |  0  0 28  | 29  0
3982:            30  0  0  | 31 32 33  |  0 34
3983: .ve

3985:    This can be represented as a collection of submatrices as:

3987: .vb
3988:       A B C
3989:       D E F
3990:       G H I
3991: .ve

3993:    Where the submatrices A,B,C are owned by proc0, D,E,F are
3994:    owned by proc1, G,H,I are owned by proc2.

3996:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3997:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3998:    The 'M','N' parameters are 8,8, and have the same values on all procs.

4000:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
4001:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
4002:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
4003:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
4004:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
4005:    matrix, ans [DF] as another SeqAIJ matrix.

4007:    When d_nz, o_nz parameters are specified, d_nz storage elements are
4008:    allocated for every row of the local diagonal submatrix, and o_nz
4009:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
4010:    One way to choose d_nz and o_nz is to use the max nonzerors per local
4011:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
4012:    In this case, the values of d_nz,o_nz are:
4013: .vb
4014:      proc0 : dnz = 2, o_nz = 2
4015:      proc1 : dnz = 3, o_nz = 2
4016:      proc2 : dnz = 1, o_nz = 4
4017: .ve
4018:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
4019:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
4020:    for proc3. i.e we are using 12+15+10=37 storage locations to store
4021:    34 values.

4023:    When d_nnz, o_nnz parameters are specified, the storage is specified
4024:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
4025:    In the above case the values for d_nnz,o_nnz are:
4026: .vb
4027:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
4028:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
4029:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
4030: .ve
4031:    Here the space allocated is sum of all the above values i.e 34, and
4032:    hence pre-allocation is perfect.

4034:    Level: intermediate

4036: .keywords: matrix, aij, compressed row, sparse, parallel

4038: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(),
4039:           MATMPIAIJ, MatGetInfo(), PetscSplitOwnership()
4040: @*/
4041: PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
4042: {

4048:   PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
4049:   return(0);
4050: }

4052: /*@
4053:      MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard
4054:          CSR format the local rows.

4056:    Collective on MPI_Comm

4058:    Input Parameters:
4059: +  comm - MPI communicator
4060: .  m - number of local rows (Cannot be PETSC_DECIDE)
4061: .  n - This value should be the same as the local size used in creating the
4062:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4063:        calculated if N is given) For square matrices n is almost always m.
4064: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4065: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4066: .   i - row indices
4067: .   j - column indices
4068: -   a - matrix values

4070:    Output Parameter:
4071: .   mat - the matrix

4073:    Level: intermediate

4075:    Notes:
4076:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
4077:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
4078:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

4080:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

4082:        The format which is used for the sparse matrix input, is equivalent to a
4083:     row-major ordering.. i.e for the following matrix, the input data expected is
4084:     as shown

4086: $        1 0 0
4087: $        2 0 3     P0
4088: $       -------
4089: $        4 5 6     P1
4090: $
4091: $     Process0 [P0]: rows_owned=[0,1]
4092: $        i =  {0,1,3}  [size = nrow+1  = 2+1]
4093: $        j =  {0,0,2}  [size = 3]
4094: $        v =  {1,2,3}  [size = 3]
4095: $
4096: $     Process1 [P1]: rows_owned=[2]
4097: $        i =  {0,3}    [size = nrow+1  = 1+1]
4098: $        j =  {0,1,2}  [size = 3]
4099: $        v =  {4,5,6}  [size = 3]

4101: .keywords: matrix, aij, compressed row, sparse, parallel

4103: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4104:           MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
4105: @*/
4106: PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
4107: {

4111:   if (i && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4112:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4113:   MatCreate(comm,mat);
4114:   MatSetSizes(*mat,m,n,M,N);
4115:   /* MatSetBlockSizes(M,bs,cbs); */
4116:   MatSetType(*mat,MATMPIAIJ);
4117:   MatMPIAIJSetPreallocationCSR(*mat,i,j,a);
4118:   return(0);
4119: }

4121: /*@C
4122:    MatCreateAIJ - Creates a sparse parallel matrix in AIJ format
4123:    (the default parallel PETSc format).  For good matrix assembly performance
4124:    the user should preallocate the matrix storage by setting the parameters
4125:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
4126:    performance can be increased by more than a factor of 50.

4128:    Collective on MPI_Comm

4130:    Input Parameters:
4131: +  comm - MPI communicator
4132: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
4133:            This value should be the same as the local size used in creating the
4134:            y vector for the matrix-vector product y = Ax.
4135: .  n - This value should be the same as the local size used in creating the
4136:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4137:        calculated if N is given) For square matrices n is almost always m.
4138: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4139: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4140: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
4141:            (same value is used for all local rows)
4142: .  d_nnz - array containing the number of nonzeros in the various rows of the
4143:            DIAGONAL portion of the local submatrix (possibly different for each row)
4144:            or NULL, if d_nz is used to specify the nonzero structure.
4145:            The size of this array is equal to the number of local rows, i.e 'm'.
4146: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
4147:            submatrix (same value is used for all local rows).
4148: -  o_nnz - array containing the number of nonzeros in the various rows of the
4149:            OFF-DIAGONAL portion of the local submatrix (possibly different for
4150:            each row) or NULL, if o_nz is used to specify the nonzero
4151:            structure. The size of this array is equal to the number
4152:            of local rows, i.e 'm'.

4154:    Output Parameter:
4155: .  A - the matrix

4157:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
4158:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
4159:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

4161:    Notes:
4162:    If the *_nnz parameter is given then the *_nz parameter is ignored

4164:    m,n,M,N parameters specify the size of the matrix, and its partitioning across
4165:    processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
4166:    storage requirements for this matrix.

4168:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one
4169:    processor than it must be used on all processors that share the object for
4170:    that argument.

4172:    The user MUST specify either the local or global matrix dimensions
4173:    (possibly both).

4175:    The parallel matrix is partitioned across processors such that the
4176:    first m0 rows belong to process 0, the next m1 rows belong to
4177:    process 1, the next m2 rows belong to process 2 etc.. where
4178:    m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
4179:    values corresponding to [m x N] submatrix.

4181:    The columns are logically partitioned with the n0 columns belonging
4182:    to 0th partition, the next n1 columns belonging to the next
4183:    partition etc.. where n0,n1,n2... are the input parameter 'n'.

4185:    The DIAGONAL portion of the local submatrix on any given processor
4186:    is the submatrix corresponding to the rows and columns m,n
4187:    corresponding to the given processor. i.e diagonal matrix on
4188:    process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
4189:    etc. The remaining portion of the local submatrix [m x (N-n)]
4190:    constitute the OFF-DIAGONAL portion. The example below better
4191:    illustrates this concept.

4193:    For a square global matrix we define each processor's diagonal portion
4194:    to be its local rows and the corresponding columns (a square submatrix);
4195:    each processor's off-diagonal portion encompasses the remainder of the
4196:    local matrix (a rectangular submatrix).

4198:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

4200:    When calling this routine with a single process communicator, a matrix of
4201:    type SEQAIJ is returned.  If a matrix of type MPIAIJ is desired for this
4202:    type of communicator, use the construction mechanism
4203: .vb
4204:      MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...);
4205: .ve

4207: $     MatCreate(...,&A);
4208: $     MatSetType(A,MATMPIAIJ);
4209: $     MatSetSizes(A, m,n,M,N);
4210: $     MatMPIAIJSetPreallocation(A,...);

4212:    By default, this format uses inodes (identical nodes) when possible.
4213:    We search for consecutive rows with the same nonzero structure, thereby
4214:    reusing matrix information to achieve increased efficiency.

4216:    Options Database Keys:
4217: +  -mat_no_inode  - Do not use inodes
4218: -  -mat_inode_limit <limit> - Sets inode limit (max limit=5)



4222:    Example usage:

4224:    Consider the following 8x8 matrix with 34 non-zero values, that is
4225:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
4226:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
4227:    as follows

4229: .vb
4230:             1  2  0  |  0  3  0  |  0  4
4231:     Proc0   0  5  6  |  7  0  0  |  8  0
4232:             9  0 10  | 11  0  0  | 12  0
4233:     -------------------------------------
4234:            13  0 14  | 15 16 17  |  0  0
4235:     Proc1   0 18  0  | 19 20 21  |  0  0
4236:             0  0  0  | 22 23  0  | 24  0
4237:     -------------------------------------
4238:     Proc2  25 26 27  |  0  0 28  | 29  0
4239:            30  0  0  | 31 32 33  |  0 34
4240: .ve

4242:    This can be represented as a collection of submatrices as

4244: .vb
4245:       A B C
4246:       D E F
4247:       G H I
4248: .ve

4250:    Where the submatrices A,B,C are owned by proc0, D,E,F are
4251:    owned by proc1, G,H,I are owned by proc2.

4253:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4254:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4255:    The 'M','N' parameters are 8,8, and have the same values on all procs.

4257:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
4258:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
4259:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
4260:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
4261:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
4262:    matrix, ans [DF] as another SeqAIJ matrix.

4264:    When d_nz, o_nz parameters are specified, d_nz storage elements are
4265:    allocated for every row of the local diagonal submatrix, and o_nz
4266:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
4267:    One way to choose d_nz and o_nz is to use the max nonzerors per local
4268:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
4269:    In this case, the values of d_nz,o_nz are
4270: .vb
4271:      proc0 : dnz = 2, o_nz = 2
4272:      proc1 : dnz = 3, o_nz = 2
4273:      proc2 : dnz = 1, o_nz = 4
4274: .ve
4275:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
4276:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
4277:    for proc3. i.e we are using 12+15+10=37 storage locations to store
4278:    34 values.

4280:    When d_nnz, o_nnz parameters are specified, the storage is specified
4281:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
4282:    In the above case the values for d_nnz,o_nnz are
4283: .vb
4284:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
4285:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
4286:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
4287: .ve
4288:    Here the space allocated is sum of all the above values i.e 34, and
4289:    hence pre-allocation is perfect.

4291:    Level: intermediate

4293: .keywords: matrix, aij, compressed row, sparse, parallel

4295: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4296:           MATMPIAIJ, MatCreateMPIAIJWithArrays()
4297: @*/
4298: 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)
4299: {
4301:   PetscMPIInt    size;

4304:   MatCreate(comm,A);
4305:   MatSetSizes(*A,m,n,M,N);
4306:   MPI_Comm_size(comm,&size);
4307:   if (size > 1) {
4308:     MatSetType(*A,MATMPIAIJ);
4309:     MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
4310:   } else {
4311:     MatSetType(*A,MATSEQAIJ);
4312:     MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
4313:   }
4314:   return(0);
4315: }

4317: PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
4318: {
4319:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
4320:   PetscBool      flg;
4322: 
4324:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);
4325:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input");
4326:   if (Ad)     *Ad     = a->A;
4327:   if (Ao)     *Ao     = a->B;
4328:   if (colmap) *colmap = a->garray;
4329:   return(0);
4330: }

4332: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
4333: {
4335:   PetscInt       m,N,i,rstart,nnz,Ii;
4336:   PetscInt       *indx;
4337:   PetscScalar    *values;

4340:   MatGetSize(inmat,&m,&N);
4341:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
4342:     PetscInt       *dnz,*onz,sum,bs,cbs;

4344:     if (n == PETSC_DECIDE) {
4345:       PetscSplitOwnership(comm,&n,&N);
4346:     }
4347:     /* Check sum(n) = N */
4348:     MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
4349:     if (sum != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns %D != global columns %D",sum,N);

4351:     MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);
4352:     rstart -= m;

4354:     MatPreallocateInitialize(comm,m,n,dnz,onz);
4355:     for (i=0; i<m; i++) {
4356:       MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4357:       MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);
4358:       MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4359:     }

4361:     MatCreate(comm,outmat);
4362:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4363:     MatGetBlockSizes(inmat,&bs,&cbs);
4364:     MatSetBlockSizes(*outmat,bs,cbs);
4365:     MatSetType(*outmat,MATAIJ);
4366:     MatSeqAIJSetPreallocation(*outmat,0,dnz);
4367:     MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);
4368:     MatPreallocateFinalize(dnz,onz);
4369:   }

4371:   /* numeric phase */
4372:   MatGetOwnershipRange(*outmat,&rstart,NULL);
4373:   for (i=0; i<m; i++) {
4374:     MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4375:     Ii   = i + rstart;
4376:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
4377:     MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4378:   }
4379:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
4380:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
4381:   return(0);
4382: }

4384: PetscErrorCode MatFileSplit(Mat A,char *outfile)
4385: {
4386:   PetscErrorCode    ierr;
4387:   PetscMPIInt       rank;
4388:   PetscInt          m,N,i,rstart,nnz;
4389:   size_t            len;
4390:   const PetscInt    *indx;
4391:   PetscViewer       out;
4392:   char              *name;
4393:   Mat               B;
4394:   const PetscScalar *values;

4397:   MatGetLocalSize(A,&m,0);
4398:   MatGetSize(A,0,&N);
4399:   /* Should this be the type of the diagonal block of A? */
4400:   MatCreate(PETSC_COMM_SELF,&B);
4401:   MatSetSizes(B,m,N,m,N);
4402:   MatSetBlockSizesFromMats(B,A,A);
4403:   MatSetType(B,MATSEQAIJ);
4404:   MatSeqAIJSetPreallocation(B,0,NULL);
4405:   MatGetOwnershipRange(A,&rstart,0);
4406:   for (i=0; i<m; i++) {
4407:     MatGetRow(A,i+rstart,&nnz,&indx,&values);
4408:     MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);
4409:     MatRestoreRow(A,i+rstart,&nnz,&indx,&values);
4410:   }
4411:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
4412:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

4414:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
4415:   PetscStrlen(outfile,&len);
4416:   PetscMalloc1(len+5,&name);
4417:   sprintf(name,"%s.%d",outfile,rank);
4418:   PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);
4419:   PetscFree(name);
4420:   MatView(B,out);
4421:   PetscViewerDestroy(&out);
4422:   MatDestroy(&B);
4423:   return(0);
4424: }

4426: PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A)
4427: {
4428:   PetscErrorCode      ierr;
4429:   Mat_Merge_SeqsToMPI *merge;
4430:   PetscContainer      container;

4433:   PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);
4434:   if (container) {
4435:     PetscContainerGetPointer(container,(void**)&merge);
4436:     PetscFree(merge->id_r);
4437:     PetscFree(merge->len_s);
4438:     PetscFree(merge->len_r);
4439:     PetscFree(merge->bi);
4440:     PetscFree(merge->bj);
4441:     PetscFree(merge->buf_ri[0]);
4442:     PetscFree(merge->buf_ri);
4443:     PetscFree(merge->buf_rj[0]);
4444:     PetscFree(merge->buf_rj);
4445:     PetscFree(merge->coi);
4446:     PetscFree(merge->coj);
4447:     PetscFree(merge->owners_co);
4448:     PetscLayoutDestroy(&merge->rowmap);
4449:     PetscFree(merge);
4450:     PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);
4451:   }
4452:   MatDestroy_MPIAIJ(A);
4453:   return(0);
4454: }

4456:  #include <../src/mat/utils/freespace.h>
4457:  #include <petscbt.h>

4459: PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat)
4460: {
4461:   PetscErrorCode      ierr;
4462:   MPI_Comm            comm;
4463:   Mat_SeqAIJ          *a  =(Mat_SeqAIJ*)seqmat->data;
4464:   PetscMPIInt         size,rank,taga,*len_s;
4465:   PetscInt            N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj;
4466:   PetscInt            proc,m;
4467:   PetscInt            **buf_ri,**buf_rj;
4468:   PetscInt            k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj;
4469:   PetscInt            nrows,**buf_ri_k,**nextrow,**nextai;
4470:   MPI_Request         *s_waits,*r_waits;
4471:   MPI_Status          *status;
4472:   MatScalar           *aa=a->a;
4473:   MatScalar           **abuf_r,*ba_i;
4474:   Mat_Merge_SeqsToMPI *merge;
4475:   PetscContainer      container;

4478:   PetscObjectGetComm((PetscObject)mpimat,&comm);
4479:   PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);

4481:   MPI_Comm_size(comm,&size);
4482:   MPI_Comm_rank(comm,&rank);

4484:   PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);
4485:   PetscContainerGetPointer(container,(void**)&merge);

4487:   bi     = merge->bi;
4488:   bj     = merge->bj;
4489:   buf_ri = merge->buf_ri;
4490:   buf_rj = merge->buf_rj;

4492:   PetscMalloc1(size,&status);
4493:   owners = merge->rowmap->range;
4494:   len_s  = merge->len_s;

4496:   /* send and recv matrix values */
4497:   /*-----------------------------*/
4498:   PetscObjectGetNewTag((PetscObject)mpimat,&taga);
4499:   PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);

4501:   PetscMalloc1(merge->nsend+1,&s_waits);
4502:   for (proc=0,k=0; proc<size; proc++) {
4503:     if (!len_s[proc]) continue;
4504:     i    = owners[proc];
4505:     MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);
4506:     k++;
4507:   }

4509:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,r_waits,status);}
4510:   if (merge->nsend) {MPI_Waitall(merge->nsend,s_waits,status);}
4511:   PetscFree(status);

4513:   PetscFree(s_waits);
4514:   PetscFree(r_waits);

4516:   /* insert mat values of mpimat */
4517:   /*----------------------------*/
4518:   PetscMalloc1(N,&ba_i);
4519:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

4521:   for (k=0; k<merge->nrecv; k++) {
4522:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4523:     nrows       = *(buf_ri_k[k]);
4524:     nextrow[k]  = buf_ri_k[k]+1;  /* next row number of k-th recved i-structure */
4525:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
4526:   }

4528:   /* set values of ba */
4529:   m = merge->rowmap->n;
4530:   for (i=0; i<m; i++) {
4531:     arow = owners[rank] + i;
4532:     bj_i = bj+bi[i];  /* col indices of the i-th row of mpimat */
4533:     bnzi = bi[i+1] - bi[i];
4534:     PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));

4536:     /* add local non-zero vals of this proc's seqmat into ba */
4537:     anzi   = ai[arow+1] - ai[arow];
4538:     aj     = a->j + ai[arow];
4539:     aa     = a->a + ai[arow];
4540:     nextaj = 0;
4541:     for (j=0; nextaj<anzi; j++) {
4542:       if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4543:         ba_i[j] += aa[nextaj++];
4544:       }
4545:     }

4547:     /* add received vals into ba */
4548:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4549:       /* i-th row */
4550:       if (i == *nextrow[k]) {
4551:         anzi   = *(nextai[k]+1) - *nextai[k];
4552:         aj     = buf_rj[k] + *(nextai[k]);
4553:         aa     = abuf_r[k] + *(nextai[k]);
4554:         nextaj = 0;
4555:         for (j=0; nextaj<anzi; j++) {
4556:           if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4557:             ba_i[j] += aa[nextaj++];
4558:           }
4559:         }
4560:         nextrow[k]++; nextai[k]++;
4561:       }
4562:     }
4563:     MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);
4564:   }
4565:   MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);
4566:   MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);

4568:   PetscFree(abuf_r[0]);
4569:   PetscFree(abuf_r);
4570:   PetscFree(ba_i);
4571:   PetscFree3(buf_ri_k,nextrow,nextai);
4572:   PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);
4573:   return(0);
4574: }

4576: PetscErrorCode  MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat)
4577: {
4578:   PetscErrorCode      ierr;
4579:   Mat                 B_mpi;
4580:   Mat_SeqAIJ          *a=(Mat_SeqAIJ*)seqmat->data;
4581:   PetscMPIInt         size,rank,tagi,tagj,*len_s,*len_si,*len_ri;
4582:   PetscInt            **buf_rj,**buf_ri,**buf_ri_k;
4583:   PetscInt            M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j;
4584:   PetscInt            len,proc,*dnz,*onz,bs,cbs;
4585:   PetscInt            k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0;
4586:   PetscInt            nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai;
4587:   MPI_Request         *si_waits,*sj_waits,*ri_waits,*rj_waits;
4588:   MPI_Status          *status;
4589:   PetscFreeSpaceList  free_space=NULL,current_space=NULL;
4590:   PetscBT             lnkbt;
4591:   Mat_Merge_SeqsToMPI *merge;
4592:   PetscContainer      container;

4595:   PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);

4597:   /* make sure it is a PETSc comm */
4598:   PetscCommDuplicate(comm,&comm,NULL);
4599:   MPI_Comm_size(comm,&size);
4600:   MPI_Comm_rank(comm,&rank);

4602:   PetscNew(&merge);
4603:   PetscMalloc1(size,&status);

4605:   /* determine row ownership */
4606:   /*---------------------------------------------------------*/
4607:   PetscLayoutCreate(comm,&merge->rowmap);
4608:   PetscLayoutSetLocalSize(merge->rowmap,m);
4609:   PetscLayoutSetSize(merge->rowmap,M);
4610:   PetscLayoutSetBlockSize(merge->rowmap,1);
4611:   PetscLayoutSetUp(merge->rowmap);
4612:   PetscMalloc1(size,&len_si);
4613:   PetscMalloc1(size,&merge->len_s);

4615:   m      = merge->rowmap->n;
4616:   owners = merge->rowmap->range;

4618:   /* determine the number of messages to send, their lengths */
4619:   /*---------------------------------------------------------*/
4620:   len_s = merge->len_s;

4622:   len          = 0; /* length of buf_si[] */
4623:   merge->nsend = 0;
4624:   for (proc=0; proc<size; proc++) {
4625:     len_si[proc] = 0;
4626:     if (proc == rank) {
4627:       len_s[proc] = 0;
4628:     } else {
4629:       len_si[proc] = owners[proc+1] - owners[proc] + 1;
4630:       len_s[proc]  = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */
4631:     }
4632:     if (len_s[proc]) {
4633:       merge->nsend++;
4634:       nrows = 0;
4635:       for (i=owners[proc]; i<owners[proc+1]; i++) {
4636:         if (ai[i+1] > ai[i]) nrows++;
4637:       }
4638:       len_si[proc] = 2*(nrows+1);
4639:       len         += len_si[proc];
4640:     }
4641:   }

4643:   /* determine the number and length of messages to receive for ij-structure */
4644:   /*-------------------------------------------------------------------------*/
4645:   PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);
4646:   PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);

4648:   /* post the Irecv of j-structure */
4649:   /*-------------------------------*/
4650:   PetscCommGetNewTag(comm,&tagj);
4651:   PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);

4653:   /* post the Isend of j-structure */
4654:   /*--------------------------------*/
4655:   PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);

4657:   for (proc=0, k=0; proc<size; proc++) {
4658:     if (!len_s[proc]) continue;
4659:     i    = owners[proc];
4660:     MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);
4661:     k++;
4662:   }

4664:   /* receives and sends of j-structure are complete */
4665:   /*------------------------------------------------*/
4666:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,rj_waits,status);}
4667:   if (merge->nsend) {MPI_Waitall(merge->nsend,sj_waits,status);}

4669:   /* send and recv i-structure */
4670:   /*---------------------------*/
4671:   PetscCommGetNewTag(comm,&tagi);
4672:   PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);

4674:   PetscMalloc1(len+1,&buf_s);
4675:   buf_si = buf_s;  /* points to the beginning of k-th msg to be sent */
4676:   for (proc=0,k=0; proc<size; proc++) {
4677:     if (!len_s[proc]) continue;
4678:     /* form outgoing message for i-structure:
4679:          buf_si[0]:                 nrows to be sent
4680:                [1:nrows]:           row index (global)
4681:                [nrows+1:2*nrows+1]: i-structure index
4682:     */
4683:     /*-------------------------------------------*/
4684:     nrows       = len_si[proc]/2 - 1;
4685:     buf_si_i    = buf_si + nrows+1;
4686:     buf_si[0]   = nrows;
4687:     buf_si_i[0] = 0;
4688:     nrows       = 0;
4689:     for (i=owners[proc]; i<owners[proc+1]; i++) {
4690:       anzi = ai[i+1] - ai[i];
4691:       if (anzi) {
4692:         buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */
4693:         buf_si[nrows+1]   = i-owners[proc]; /* local row index */
4694:         nrows++;
4695:       }
4696:     }
4697:     MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);
4698:     k++;
4699:     buf_si += len_si[proc];
4700:   }

4702:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,ri_waits,status);}
4703:   if (merge->nsend) {MPI_Waitall(merge->nsend,si_waits,status);}

4705:   PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);
4706:   for (i=0; i<merge->nrecv; i++) {
4707:     PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);
4708:   }

4710:   PetscFree(len_si);
4711:   PetscFree(len_ri);
4712:   PetscFree(rj_waits);
4713:   PetscFree2(si_waits,sj_waits);
4714:   PetscFree(ri_waits);
4715:   PetscFree(buf_s);
4716:   PetscFree(status);

4718:   /* compute a local seq matrix in each processor */
4719:   /*----------------------------------------------*/
4720:   /* allocate bi array and free space for accumulating nonzero column info */
4721:   PetscMalloc1(m+1,&bi);
4722:   bi[0] = 0;

4724:   /* create and initialize a linked list */
4725:   nlnk = N+1;
4726:   PetscLLCreate(N,N,nlnk,lnk,lnkbt);

4728:   /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */
4729:   len  = ai[owners[rank+1]] - ai[owners[rank]];
4730:   PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);

4732:   current_space = free_space;

4734:   /* determine symbolic info for each local row */
4735:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

4737:   for (k=0; k<merge->nrecv; k++) {
4738:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4739:     nrows       = *buf_ri_k[k];
4740:     nextrow[k]  = buf_ri_k[k] + 1;  /* next row number of k-th recved i-structure */
4741:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
4742:   }

4744:   MatPreallocateInitialize(comm,m,n,dnz,onz);
4745:   len  = 0;
4746:   for (i=0; i<m; i++) {
4747:     bnzi = 0;
4748:     /* add local non-zero cols of this proc's seqmat into lnk */
4749:     arow  = owners[rank] + i;
4750:     anzi  = ai[arow+1] - ai[arow];
4751:     aj    = a->j + ai[arow];
4752:     PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4753:     bnzi += nlnk;
4754:     /* add received col data into lnk */
4755:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4756:       if (i == *nextrow[k]) { /* i-th row */
4757:         anzi  = *(nextai[k]+1) - *nextai[k];
4758:         aj    = buf_rj[k] + *nextai[k];
4759:         PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4760:         bnzi += nlnk;
4761:         nextrow[k]++; nextai[k]++;
4762:       }
4763:     }
4764:     if (len < bnzi) len = bnzi;  /* =max(bnzi) */

4766:     /* if free space is not available, make more free space */
4767:     if (current_space->local_remaining<bnzi) {
4768:       PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),&current_space);
4769:       nspacedouble++;
4770:     }
4771:     /* copy data into free space, then initialize lnk */
4772:     PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);
4773:     MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);

4775:     current_space->array           += bnzi;
4776:     current_space->local_used      += bnzi;
4777:     current_space->local_remaining -= bnzi;

4779:     bi[i+1] = bi[i] + bnzi;
4780:   }

4782:   PetscFree3(buf_ri_k,nextrow,nextai);

4784:   PetscMalloc1(bi[m]+1,&bj);
4785:   PetscFreeSpaceContiguous(&free_space,bj);
4786:   PetscLLDestroy(lnk,lnkbt);

4788:   /* create symbolic parallel matrix B_mpi */
4789:   /*---------------------------------------*/
4790:   MatGetBlockSizes(seqmat,&bs,&cbs);
4791:   MatCreate(comm,&B_mpi);
4792:   if (n==PETSC_DECIDE) {
4793:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);
4794:   } else {
4795:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4796:   }
4797:   MatSetBlockSizes(B_mpi,bs,cbs);
4798:   MatSetType(B_mpi,MATMPIAIJ);
4799:   MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);
4800:   MatPreallocateFinalize(dnz,onz);
4801:   MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);

4803:   /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */
4804:   B_mpi->assembled    = PETSC_FALSE;
4805:   B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI;
4806:   merge->bi           = bi;
4807:   merge->bj           = bj;
4808:   merge->buf_ri       = buf_ri;
4809:   merge->buf_rj       = buf_rj;
4810:   merge->coi          = NULL;
4811:   merge->coj          = NULL;
4812:   merge->owners_co    = NULL;

4814:   PetscCommDestroy(&comm);

4816:   /* attach the supporting struct to B_mpi for reuse */
4817:   PetscContainerCreate(PETSC_COMM_SELF,&container);
4818:   PetscContainerSetPointer(container,merge);
4819:   PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);
4820:   PetscContainerDestroy(&container);
4821:   *mpimat = B_mpi;

4823:   PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);
4824:   return(0);
4825: }

4827: /*@C
4828:       MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential
4829:                  matrices from each processor

4831:     Collective on MPI_Comm

4833:    Input Parameters:
4834: +    comm - the communicators the parallel matrix will live on
4835: .    seqmat - the input sequential matrices
4836: .    m - number of local rows (or PETSC_DECIDE)
4837: .    n - number of local columns (or PETSC_DECIDE)
4838: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

4840:    Output Parameter:
4841: .    mpimat - the parallel matrix generated

4843:     Level: advanced

4845:    Notes:
4846:      The dimensions of the sequential matrix in each processor MUST be the same.
4847:      The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be
4848:      destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat.
4849: @*/
4850: PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat)
4851: {
4853:   PetscMPIInt    size;

4856:   MPI_Comm_size(comm,&size);
4857:   if (size == 1) {
4858:     PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4859:     if (scall == MAT_INITIAL_MATRIX) {
4860:       MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);
4861:     } else {
4862:       MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);
4863:     }
4864:     PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4865:     return(0);
4866:   }
4867:   PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4868:   if (scall == MAT_INITIAL_MATRIX) {
4869:     MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);
4870:   }
4871:   MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);
4872:   PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4873:   return(0);
4874: }

4876: /*@
4877:      MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential matrix with
4878:           mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained
4879:           with MatGetSize()

4881:     Not Collective

4883:    Input Parameters:
4884: +    A - the matrix
4885: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

4887:    Output Parameter:
4888: .    A_loc - the local sequential matrix generated

4890:     Level: developer

4892: .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed()

4894: @*/
4895: PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc)
4896: {
4898:   Mat_MPIAIJ     *mpimat=(Mat_MPIAIJ*)A->data;
4899:   Mat_SeqAIJ     *mat,*a,*b;
4900:   PetscInt       *ai,*aj,*bi,*bj,*cmap=mpimat->garray;
4901:   MatScalar      *aa,*ba,*cam;
4902:   PetscScalar    *ca;
4903:   PetscInt       am=A->rmap->n,i,j,k,cstart=A->cmap->rstart;
4904:   PetscInt       *ci,*cj,col,ncols_d,ncols_o,jo;
4905:   PetscBool      match;
4906:   MPI_Comm       comm;
4907:   PetscMPIInt    size;

4910:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
4911:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
4912:   PetscObjectGetComm((PetscObject)A,&comm);
4913:   MPI_Comm_size(comm,&size);
4914:   if (size == 1 && scall == MAT_REUSE_MATRIX) return(0);

4916:   PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);
4917:   a = (Mat_SeqAIJ*)(mpimat->A)->data;
4918:   b = (Mat_SeqAIJ*)(mpimat->B)->data;
4919:   ai = a->i; aj = a->j; bi = b->i; bj = b->j;
4920:   aa = a->a; ba = b->a;
4921:   if (scall == MAT_INITIAL_MATRIX) {
4922:     if (size == 1) {
4923:       MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);
4924:       return(0);
4925:     }

4927:     PetscMalloc1(1+am,&ci);
4928:     ci[0] = 0;
4929:     for (i=0; i<am; i++) {
4930:       ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]);
4931:     }
4932:     PetscMalloc1(1+ci[am],&cj);
4933:     PetscMalloc1(1+ci[am],&ca);
4934:     k    = 0;
4935:     for (i=0; i<am; i++) {
4936:       ncols_o = bi[i+1] - bi[i];
4937:       ncols_d = ai[i+1] - ai[i];
4938:       /* off-diagonal portion of A */
4939:       for (jo=0; jo<ncols_o; jo++) {
4940:         col = cmap[*bj];
4941:         if (col >= cstart) break;
4942:         cj[k]   = col; bj++;
4943:         ca[k++] = *ba++;
4944:       }
4945:       /* diagonal portion of A */
4946:       for (j=0; j<ncols_d; j++) {
4947:         cj[k]   = cstart + *aj++;
4948:         ca[k++] = *aa++;
4949:       }
4950:       /* off-diagonal portion of A */
4951:       for (j=jo; j<ncols_o; j++) {
4952:         cj[k]   = cmap[*bj++];
4953:         ca[k++] = *ba++;
4954:       }
4955:     }
4956:     /* put together the new matrix */
4957:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);
4958:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
4959:     /* Since these are PETSc arrays, change flags to free them as necessary. */
4960:     mat          = (Mat_SeqAIJ*)(*A_loc)->data;
4961:     mat->free_a  = PETSC_TRUE;
4962:     mat->free_ij = PETSC_TRUE;
4963:     mat->nonew   = 0;
4964:   } else if (scall == MAT_REUSE_MATRIX) {
4965:     mat=(Mat_SeqAIJ*)(*A_loc)->data;
4966:     ci = mat->i; cj = mat->j; cam = mat->a;
4967:     for (i=0; i<am; i++) {
4968:       /* off-diagonal portion of A */
4969:       ncols_o = bi[i+1] - bi[i];
4970:       for (jo=0; jo<ncols_o; jo++) {
4971:         col = cmap[*bj];
4972:         if (col >= cstart) break;
4973:         *cam++ = *ba++; bj++;
4974:       }
4975:       /* diagonal portion of A */
4976:       ncols_d = ai[i+1] - ai[i];
4977:       for (j=0; j<ncols_d; j++) *cam++ = *aa++;
4978:       /* off-diagonal portion of A */
4979:       for (j=jo; j<ncols_o; j++) {
4980:         *cam++ = *ba++; bj++;
4981:       }
4982:     }
4983:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
4984:   PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);
4985:   return(0);
4986: }

4988: /*@C
4989:      MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns

4991:     Not Collective

4993:    Input Parameters:
4994: +    A - the matrix
4995: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4996: -    row, col - index sets of rows and columns to extract (or NULL)

4998:    Output Parameter:
4999: .    A_loc - the local sequential matrix generated

5001:     Level: developer

5003: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat()

5005: @*/
5006: PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
5007: {
5008:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
5010:   PetscInt       i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
5011:   IS             isrowa,iscola;
5012:   Mat            *aloc;
5013:   PetscBool      match;

5016:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
5017:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
5018:   PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
5019:   if (!row) {
5020:     start = A->rmap->rstart; end = A->rmap->rend;
5021:     ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
5022:   } else {
5023:     isrowa = *row;
5024:   }
5025:   if (!col) {
5026:     start = A->cmap->rstart;
5027:     cmap  = a->garray;
5028:     nzA   = a->A->cmap->n;
5029:     nzB   = a->B->cmap->n;
5030:     PetscMalloc1(nzA+nzB, &idx);
5031:     ncols = 0;
5032:     for (i=0; i<nzB; i++) {
5033:       if (cmap[i] < start) idx[ncols++] = cmap[i];
5034:       else break;
5035:     }
5036:     imark = i;
5037:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;
5038:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
5039:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
5040:   } else {
5041:     iscola = *col;
5042:   }
5043:   if (scall != MAT_INITIAL_MATRIX) {
5044:     PetscMalloc1(1,&aloc);
5045:     aloc[0] = *A_loc;
5046:   }
5047:   MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
5048:   *A_loc = aloc[0];
5049:   PetscFree(aloc);
5050:   if (!row) {
5051:     ISDestroy(&isrowa);
5052:   }
5053:   if (!col) {
5054:     ISDestroy(&iscola);
5055:   }
5056:   PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
5057:   return(0);
5058: }

5060: /*@C
5061:     MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A

5063:     Collective on Mat

5065:    Input Parameters:
5066: +    A,B - the matrices in mpiaij format
5067: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5068: -    rowb, colb - index sets of rows and columns of B to extract (or NULL)

5070:    Output Parameter:
5071: +    rowb, colb - index sets of rows and columns of B to extract
5072: -    B_seq - the sequential matrix generated

5074:     Level: developer

5076: @*/
5077: PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq)
5078: {
5079:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
5081:   PetscInt       *idx,i,start,ncols,nzA,nzB,*cmap,imark;
5082:   IS             isrowb,iscolb;
5083:   Mat            *bseq=NULL;

5086:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5087:     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);
5088:   }
5089:   PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);

5091:   if (scall == MAT_INITIAL_MATRIX) {
5092:     start = A->cmap->rstart;
5093:     cmap  = a->garray;
5094:     nzA   = a->A->cmap->n;
5095:     nzB   = a->B->cmap->n;
5096:     PetscMalloc1(nzA+nzB, &idx);
5097:     ncols = 0;
5098:     for (i=0; i<nzB; i++) {  /* row < local row index */
5099:       if (cmap[i] < start) idx[ncols++] = cmap[i];
5100:       else break;
5101:     }
5102:     imark = i;
5103:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;  /* local rows */
5104:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */
5105:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);
5106:     ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);
5107:   } else {
5108:     if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX");
5109:     isrowb  = *rowb; iscolb = *colb;
5110:     PetscMalloc1(1,&bseq);
5111:     bseq[0] = *B_seq;
5112:   }
5113:   MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);
5114:   *B_seq = bseq[0];
5115:   PetscFree(bseq);
5116:   if (!rowb) {
5117:     ISDestroy(&isrowb);
5118:   } else {
5119:     *rowb = isrowb;
5120:   }
5121:   if (!colb) {
5122:     ISDestroy(&iscolb);
5123:   } else {
5124:     *colb = iscolb;
5125:   }
5126:   PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);
5127:   return(0);
5128: }

5130: /*
5131:     MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns
5132:     of the OFF-DIAGONAL portion of local A

5134:     Collective on Mat

5136:    Input Parameters:
5137: +    A,B - the matrices in mpiaij format
5138: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

5140:    Output Parameter:
5141: +    startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL)
5142: .    startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL)
5143: .    bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL)
5144: -    B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N

5146:     Level: developer

5148: */
5149: PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth)
5150: {
5151:   VecScatter_MPI_General *gen_to,*gen_from;
5152:   PetscErrorCode         ierr;
5153:   Mat_MPIAIJ             *a=(Mat_MPIAIJ*)A->data;
5154:   Mat_SeqAIJ             *b_oth;
5155:   VecScatter             ctx;
5156:   MPI_Comm               comm;
5157:   PetscMPIInt            *rprocs,*sprocs,tag,rank;
5158:   PetscInt               *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj;
5159:   PetscInt               *rvalues,*svalues,*cols,sbs,rbs;
5160:   PetscScalar              *b_otha,*bufa,*bufA,*vals;
5161:   PetscInt               i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len;
5162:   MPI_Request            *rwaits = NULL,*swaits = NULL;
5163:   MPI_Status             *sstatus,rstatus;
5164:   PetscMPIInt            jj,size;
5165:   VecScatterType         type;
5166:   PetscBool              mpi1;

5169:   PetscObjectGetComm((PetscObject)A,&comm);
5170:   MPI_Comm_size(comm,&size);

5172:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5173:     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);
5174:   }
5175:   PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);
5176:   MPI_Comm_rank(comm,&rank);

5178:   if (size == 1) {
5179:     startsj_s = NULL;
5180:     bufa_ptr  = NULL;
5181:     *B_oth    = NULL;
5182:     return(0);
5183:   }

5185:   ctx = a->Mvctx;
5186:   VecScatterGetType(ctx,&type);
5187:   PetscStrcmp(type,"mpi1",&mpi1);
5188:   if (!mpi1) {
5189:     /* a->Mvctx is not type MPI1 which is not implemented for Mat-Mat ops,
5190:      thus create a->Mvctx_mpi1 */
5191:     if (!a->Mvctx_mpi1) {
5192:       a->Mvctx_mpi1_flg = PETSC_TRUE;
5193:       MatSetUpMultiply_MPIAIJ(A);
5194:     }
5195:     ctx = a->Mvctx_mpi1;
5196:   }
5197:   tag = ((PetscObject)ctx)->tag;

5199:   gen_to   = (VecScatter_MPI_General*)ctx->todata;
5200:   gen_from = (VecScatter_MPI_General*)ctx->fromdata;
5201:   nrecvs   = gen_from->n;
5202:   nsends   = gen_to->n;

5204:   PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);
5205:   srow    = gen_to->indices;    /* local row index to be sent */
5206:   sstarts = gen_to->starts;
5207:   sprocs  = gen_to->procs;
5208:   sstatus = gen_to->sstatus;
5209:   sbs     = gen_to->bs;
5210:   rstarts = gen_from->starts;
5211:   rprocs  = gen_from->procs;
5212:   rbs     = gen_from->bs;

5214:   if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX;
5215:   if (scall == MAT_INITIAL_MATRIX) {
5216:     /* i-array */
5217:     /*---------*/
5218:     /*  post receives */
5219:     PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);
5220:     for (i=0; i<nrecvs; i++) {
5221:       rowlen = rvalues + rstarts[i]*rbs;
5222:       nrows  = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */
5223:       MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5224:     }

5226:     /* pack the outgoing message */
5227:     PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);

5229:     sstartsj[0] = 0;
5230:     rstartsj[0] = 0;
5231:     len         = 0; /* total length of j or a array to be sent */
5232:     k           = 0;
5233:     PetscMalloc1(sbs*(sstarts[nsends] - sstarts[0]),&svalues);
5234:     for (i=0; i<nsends; i++) {
5235:       rowlen = svalues + sstarts[i]*sbs;
5236:       nrows  = sstarts[i+1]-sstarts[i]; /* num of block rows */
5237:       for (j=0; j<nrows; j++) {
5238:         row = srow[k] + B->rmap->range[rank]; /* global row idx */
5239:         for (l=0; l<sbs; l++) {
5240:           MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL); /* rowlength */

5242:           rowlen[j*sbs+l] = ncols;

5244:           len += ncols;
5245:           MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);
5246:         }
5247:         k++;
5248:       }
5249:       MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);

5251:       sstartsj[i+1] = len;  /* starting point of (i+1)-th outgoing msg in bufj and bufa */
5252:     }
5253:     /* recvs and sends of i-array are completed */
5254:     i = nrecvs;
5255:     while (i--) {
5256:       MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
5257:     }
5258:     if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
5259:     PetscFree(svalues);

5261:     /* allocate buffers for sending j and a arrays */
5262:     PetscMalloc1(len+1,&bufj);
5263:     PetscMalloc1(len+1,&bufa);

5265:     /* create i-array of B_oth */
5266:     PetscMalloc1(aBn+2,&b_othi);

5268:     b_othi[0] = 0;
5269:     len       = 0; /* total length of j or a array to be received */
5270:     k         = 0;
5271:     for (i=0; i<nrecvs; i++) {
5272:       rowlen = rvalues + rstarts[i]*rbs;
5273:       nrows  = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be received */
5274:       for (j=0; j<nrows; j++) {
5275:         b_othi[k+1] = b_othi[k] + rowlen[j];
5276:         PetscIntSumError(rowlen[j],len,&len);
5277:         k++;
5278:       }
5279:       rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */
5280:     }
5281:     PetscFree(rvalues);

5283:     /* allocate space for j and a arrrays of B_oth */
5284:     PetscMalloc1(b_othi[aBn]+1,&b_othj);
5285:     PetscMalloc1(b_othi[aBn]+1,&b_otha);

5287:     /* j-array */
5288:     /*---------*/
5289:     /*  post receives of j-array */
5290:     for (i=0; i<nrecvs; i++) {
5291:       nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5292:       MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5293:     }

5295:     /* pack the outgoing message j-array */
5296:     k = 0;
5297:     for (i=0; i<nsends; i++) {
5298:       nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5299:       bufJ  = bufj+sstartsj[i];
5300:       for (j=0; j<nrows; j++) {
5301:         row = srow[k++] + B->rmap->range[rank];  /* global row idx */
5302:         for (ll=0; ll<sbs; ll++) {
5303:           MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5304:           for (l=0; l<ncols; l++) {
5305:             *bufJ++ = cols[l];
5306:           }
5307:           MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5308:         }
5309:       }
5310:       MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);
5311:     }

5313:     /* recvs and sends of j-array are completed */
5314:     i = nrecvs;
5315:     while (i--) {
5316:       MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
5317:     }
5318:     if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
5319:   } else if (scall == MAT_REUSE_MATRIX) {
5320:     sstartsj = *startsj_s;
5321:     rstartsj = *startsj_r;
5322:     bufa     = *bufa_ptr;
5323:     b_oth    = (Mat_SeqAIJ*)(*B_oth)->data;
5324:     b_otha   = b_oth->a;
5325:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container");

5327:   /* a-array */
5328:   /*---------*/
5329:   /*  post receives of a-array */
5330:   for (i=0; i<nrecvs; i++) {
5331:     nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5332:     MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);
5333:   }

5335:   /* pack the outgoing message a-array */
5336:   k = 0;
5337:   for (i=0; i<nsends; i++) {
5338:     nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5339:     bufA  = bufa+sstartsj[i];
5340:     for (j=0; j<nrows; j++) {
5341:       row = srow[k++] + B->rmap->range[rank];  /* global row idx */
5342:       for (ll=0; ll<sbs; ll++) {
5343:         MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5344:         for (l=0; l<ncols; l++) {
5345:           *bufA++ = vals[l];
5346:         }
5347:         MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5348:       }
5349:     }
5350:     MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);
5351:   }
5352:   /* recvs and sends of a-array are completed */
5353:   i = nrecvs;
5354:   while (i--) {
5355:     MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
5356:   }
5357:   if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
5358:   PetscFree2(rwaits,swaits);

5360:   if (scall == MAT_INITIAL_MATRIX) {
5361:     /* put together the new matrix */
5362:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);

5364:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5365:     /* Since these are PETSc arrays, change flags to free them as necessary. */
5366:     b_oth          = (Mat_SeqAIJ*)(*B_oth)->data;
5367:     b_oth->free_a  = PETSC_TRUE;
5368:     b_oth->free_ij = PETSC_TRUE;
5369:     b_oth->nonew   = 0;

5371:     PetscFree(bufj);
5372:     if (!startsj_s || !bufa_ptr) {
5373:       PetscFree2(sstartsj,rstartsj);
5374:       PetscFree(bufa_ptr);
5375:     } else {
5376:       *startsj_s = sstartsj;
5377:       *startsj_r = rstartsj;
5378:       *bufa_ptr  = bufa;
5379:     }
5380:   }
5381:   PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);
5382:   return(0);
5383: }

5385: /*@C
5386:   MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication.

5388:   Not Collective

5390:   Input Parameters:
5391: . A - The matrix in mpiaij format

5393:   Output Parameter:
5394: + lvec - The local vector holding off-process values from the argument to a matrix-vector product
5395: . colmap - A map from global column index to local index into lvec
5396: - multScatter - A scatter from the argument of a matrix-vector product to lvec

5398:   Level: developer

5400: @*/
5401: #if defined(PETSC_USE_CTABLE)
5402: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter)
5403: #else
5404: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter)
5405: #endif
5406: {
5407:   Mat_MPIAIJ *a;

5414:   a = (Mat_MPIAIJ*) A->data;
5415:   if (lvec) *lvec = a->lvec;
5416:   if (colmap) *colmap = a->colmap;
5417:   if (multScatter) *multScatter = a->Mvctx;
5418:   return(0);
5419: }

5421: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*);
5422: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*);
5423: #if defined(PETSC_HAVE_MKL_SPARSE)
5424: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJMKL(Mat,MatType,MatReuse,Mat*);
5425: #endif
5426: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*);
5427: #if defined(PETSC_HAVE_ELEMENTAL)
5428: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
5429: #endif
5430: #if defined(PETSC_HAVE_HYPRE)
5431: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
5432: PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*);
5433: #endif
5434: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_IS(Mat,MatType,MatReuse,Mat*);
5435: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISELL(Mat,MatType,MatReuse,Mat*);

5437: /*
5438:     Computes (B'*A')' since computing B*A directly is untenable

5440:                n                       p                          p
5441:         (              )       (              )         (                  )
5442:       m (      A       )  *  n (       B      )   =   m (         C        )
5443:         (              )       (              )         (                  )

5445: */
5446: PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C)
5447: {
5449:   Mat            At,Bt,Ct;

5452:   MatTranspose(A,MAT_INITIAL_MATRIX,&At);
5453:   MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);
5454:   MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);
5455:   MatDestroy(&At);
5456:   MatDestroy(&Bt);
5457:   MatTranspose(Ct,MAT_REUSE_MATRIX,&C);
5458:   MatDestroy(&Ct);
5459:   return(0);
5460: }

5462: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
5463: {
5465:   PetscInt       m=A->rmap->n,n=B->cmap->n;
5466:   Mat            Cmat;

5469:   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);
5470:   MatCreate(PetscObjectComm((PetscObject)A),&Cmat);
5471:   MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
5472:   MatSetBlockSizesFromMats(Cmat,A,B);
5473:   MatSetType(Cmat,MATMPIDENSE);
5474:   MatMPIDenseSetPreallocation(Cmat,NULL);
5475:   MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);
5476:   MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);

5478:   Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ;

5480:   *C = Cmat;
5481:   return(0);
5482: }

5484: /* ----------------------------------------------------------------*/
5485: PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
5486: {

5490:   if (scall == MAT_INITIAL_MATRIX) {
5491:     PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);
5492:     MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);
5493:     PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);
5494:   }
5495:   PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);
5496:   MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);
5497:   PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);
5498:   return(0);
5499: }

5501: /*MC
5502:    MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices.

5504:    Options Database Keys:
5505: . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions()

5507:   Level: beginner

5509: .seealso: MatCreateAIJ()
5510: M*/

5512: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B)
5513: {
5514:   Mat_MPIAIJ     *b;
5516:   PetscMPIInt    size;

5519:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);

5521:   PetscNewLog(B,&b);
5522:   B->data       = (void*)b;
5523:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
5524:   B->assembled  = PETSC_FALSE;
5525:   B->insertmode = NOT_SET_VALUES;
5526:   b->size       = size;

5528:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);

5530:   /* build cache for off array entries formed */
5531:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

5533:   b->donotstash  = PETSC_FALSE;
5534:   b->colmap      = 0;
5535:   b->garray      = 0;
5536:   b->roworiented = PETSC_TRUE;

5538:   /* stuff used for matrix vector multiply */
5539:   b->lvec  = NULL;
5540:   b->Mvctx = NULL;

5542:   /* stuff for MatGetRow() */
5543:   b->rowindices   = 0;
5544:   b->rowvalues    = 0;
5545:   b->getrowactive = PETSC_FALSE;

5547:   /* flexible pointer used in CUSP/CUSPARSE classes */
5548:   b->spptr = NULL;

5550:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);
5551:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);
5552:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);
5553:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);
5554:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);
5555:   PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_MPIAIJ);
5556:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);
5557:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);
5558:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);
5559: #if defined(PETSC_HAVE_MKL_SPARSE)
5560:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijmkl_C",MatConvert_MPIAIJ_MPIAIJMKL);
5561: #endif
5562:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);
5563:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);
5564: #if defined(PETSC_HAVE_ELEMENTAL)
5565:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);
5566: #endif
5567: #if defined(PETSC_HAVE_HYPRE)
5568:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);
5569: #endif
5570:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_MPIAIJ_IS);
5571:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisell_C",MatConvert_MPIAIJ_MPISELL);
5572:   PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);
5573:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);
5574:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);
5575: #if defined(PETSC_HAVE_HYPRE)
5576:   PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);
5577: #endif
5578:   PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);
5579:   return(0);
5580: }

5582: /*@C
5583:      MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal"
5584:          and "off-diagonal" part of the matrix in CSR format.

5586:    Collective on MPI_Comm

5588:    Input Parameters:
5589: +  comm - MPI communicator
5590: .  m - number of local rows (Cannot be PETSC_DECIDE)
5591: .  n - This value should be the same as the local size used in creating the
5592:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
5593:        calculated if N is given) For square matrices n is almost always m.
5594: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
5595: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
5596: .   i - row indices for "diagonal" portion of matrix
5597: .   j - column indices
5598: .   a - matrix values
5599: .   oi - row indices for "off-diagonal" portion of matrix
5600: .   oj - column indices
5601: -   oa - matrix values

5603:    Output Parameter:
5604: .   mat - the matrix

5606:    Level: advanced

5608:    Notes:
5609:        The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user
5610:        must free the arrays once the matrix has been destroyed and not before.

5612:        The i and j indices are 0 based

5614:        See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix

5616:        This sets local rows and cannot be used to set off-processor values.

5618:        Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a
5619:        legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does
5620:        not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because
5621:        the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to
5622:        keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all
5623:        communication if it is known that only local entries will be set.

5625: .keywords: matrix, aij, compressed row, sparse, parallel

5627: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
5628:           MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays()
5629: @*/
5630: 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)
5631: {
5633:   Mat_MPIAIJ     *maij;

5636:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
5637:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
5638:   if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0");
5639:   MatCreate(comm,mat);
5640:   MatSetSizes(*mat,m,n,M,N);
5641:   MatSetType(*mat,MATMPIAIJ);
5642:   maij = (Mat_MPIAIJ*) (*mat)->data;

5644:   (*mat)->preallocated = PETSC_TRUE;

5646:   PetscLayoutSetUp((*mat)->rmap);
5647:   PetscLayoutSetUp((*mat)->cmap);

5649:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);
5650:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);

5652:   MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);
5653:   MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);
5654:   MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);
5655:   MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);

5657:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
5658:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
5659:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
5660:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
5661:   MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
5662:   return(0);
5663: }

5665: /*
5666:     Special version for direct calls from Fortran
5667: */
5668:  #include <petsc/private/fortranimpl.h>

5670: /* Change these macros so can be used in void function */
5671: #undef CHKERRQ
5672: #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr)
5673: #undef SETERRQ2
5674: #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr)
5675: #undef SETERRQ3
5676: #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr)
5677: #undef SETERRQ
5678: #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr)

5680: #if defined(PETSC_HAVE_FORTRAN_CAPS)
5681: #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ
5682: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
5683: #define matsetvaluesmpiaij_ matsetvaluesmpiaij
5684: #else
5685: #endif
5686: 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)
5687: {
5688:   Mat            mat  = *mmat;
5689:   PetscInt       m    = *mm, n = *mn;
5690:   InsertMode     addv = *maddv;
5691:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
5692:   PetscScalar    value;

5695:   MatCheckPreallocated(mat,1);
5696:   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;

5698: #if defined(PETSC_USE_DEBUG)
5699:   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
5700: #endif
5701:   {
5702:     PetscInt  i,j,rstart  = mat->rmap->rstart,rend = mat->rmap->rend;
5703:     PetscInt  cstart      = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
5704:     PetscBool roworiented = aij->roworiented;

5706:     /* Some Variables required in the macro */
5707:     Mat        A                 = aij->A;
5708:     Mat_SeqAIJ *a                = (Mat_SeqAIJ*)A->data;
5709:     PetscInt   *aimax            = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
5710:     MatScalar  *aa               = a->a;
5711:     PetscBool  ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE);
5712:     Mat        B                 = aij->B;
5713:     Mat_SeqAIJ *b                = (Mat_SeqAIJ*)B->data;
5714:     PetscInt   *bimax            = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
5715:     MatScalar  *ba               = b->a;

5717:     PetscInt  *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
5718:     PetscInt  nonew = a->nonew;
5719:     MatScalar *ap1,*ap2;

5722:     for (i=0; i<m; i++) {
5723:       if (im[i] < 0) continue;
5724: #if defined(PETSC_USE_DEBUG)
5725:       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);
5726: #endif
5727:       if (im[i] >= rstart && im[i] < rend) {
5728:         row      = im[i] - rstart;
5729:         lastcol1 = -1;
5730:         rp1      = aj + ai[row];
5731:         ap1      = aa + ai[row];
5732:         rmax1    = aimax[row];
5733:         nrow1    = ailen[row];
5734:         low1     = 0;
5735:         high1    = nrow1;
5736:         lastcol2 = -1;
5737:         rp2      = bj + bi[row];
5738:         ap2      = ba + bi[row];
5739:         rmax2    = bimax[row];
5740:         nrow2    = bilen[row];
5741:         low2     = 0;
5742:         high2    = nrow2;

5744:         for (j=0; j<n; j++) {
5745:           if (roworiented) value = v[i*n+j];
5746:           else value = v[i+j*m];
5747:           if (in[j] >= cstart && in[j] < cend) {
5748:             col = in[j] - cstart;
5749:             if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
5750:             MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
5751:           } else if (in[j] < 0) continue;
5752: #if defined(PETSC_USE_DEBUG)
5753:           /* extra brace on SETERRQ2() is required for --with-errorchecking=0 - due to the next 'else' clause */
5754:           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);}
5755: #endif
5756:           else {
5757:             if (mat->was_assembled) {
5758:               if (!aij->colmap) {
5759:                 MatCreateColmap_MPIAIJ_Private(mat);
5760:               }
5761: #if defined(PETSC_USE_CTABLE)
5762:               PetscTableFind(aij->colmap,in[j]+1,&col);
5763:               col--;
5764: #else
5765:               col = aij->colmap[in[j]] - 1;
5766: #endif
5767:               if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
5768:               if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
5769:                 MatDisAssemble_MPIAIJ(mat);
5770:                 col  =  in[j];
5771:                 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
5772:                 B     = aij->B;
5773:                 b     = (Mat_SeqAIJ*)B->data;
5774:                 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
5775:                 rp2   = bj + bi[row];
5776:                 ap2   = ba + bi[row];
5777:                 rmax2 = bimax[row];
5778:                 nrow2 = bilen[row];
5779:                 low2  = 0;
5780:                 high2 = nrow2;
5781:                 bm    = aij->B->rmap->n;
5782:                 ba    = b->a;
5783:               }
5784:             } else col = in[j];
5785:             MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
5786:           }
5787:         }
5788:       } else if (!aij->donotstash) {
5789:         if (roworiented) {
5790:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5791:         } else {
5792:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5793:         }
5794:       }
5795:     }
5796:   }
5797:   PetscFunctionReturnVoid();
5798: }