Actual source code: mpiaij.c

petsc-3.6.3 2015-12-03
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  2: #include <../src/mat/impls/aij/mpi/mpiaij.h>   /*I "petscmat.h" I*/
  3: #include <petsc/private/vecimpl.h>
  4: #include <petsc/private/isimpl.h>
  5: #include <petscblaslapack.h>
  6: #include <petscsf.h>

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

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

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

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

 23:   Level: beginner

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

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

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

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

 40:   Level: beginner

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

 47: PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows)
 48: {
 49:   PetscErrorCode  ierr;
 50:   Mat_MPIAIJ      *mat = (Mat_MPIAIJ*)M->data;
 51:   Mat_SeqAIJ      *a   = (Mat_SeqAIJ*)mat->A->data;
 52:   Mat_SeqAIJ      *b   = (Mat_SeqAIJ*)mat->B->data;
 53:   const PetscInt  *ia,*ib;
 54:   const MatScalar *aa,*bb;
 55:   PetscInt        na,nb,i,j,*rows,cnt=0,n0rows;
 56:   PetscInt        m = M->rmap->n,rstart = M->rmap->rstart;

 59:   *keptrows = 0;
 60:   ia        = a->i;
 61:   ib        = b->i;
 62:   for (i=0; i<m; i++) {
 63:     na = ia[i+1] - ia[i];
 64:     nb = ib[i+1] - ib[i];
 65:     if (!na && !nb) {
 66:       cnt++;
 67:       goto ok1;
 68:     }
 69:     aa = a->a + ia[i];
 70:     for (j=0; j<na; j++) {
 71:       if (aa[j] != 0.0) goto ok1;
 72:     }
 73:     bb = b->a + ib[i];
 74:     for (j=0; j <nb; j++) {
 75:       if (bb[j] != 0.0) goto ok1;
 76:     }
 77:     cnt++;
 78: ok1:;
 79:   }
 80:   MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));
 81:   if (!n0rows) return(0);
 82:   PetscMalloc1(M->rmap->n-cnt,&rows);
 83:   cnt  = 0;
 84:   for (i=0; i<m; i++) {
 85:     na = ia[i+1] - ia[i];
 86:     nb = ib[i+1] - ib[i];
 87:     if (!na && !nb) continue;
 88:     aa = a->a + ia[i];
 89:     for (j=0; j<na;j++) {
 90:       if (aa[j] != 0.0) {
 91:         rows[cnt++] = rstart + i;
 92:         goto ok2;
 93:       }
 94:     }
 95:     bb = b->a + ib[i];
 96:     for (j=0; j<nb; j++) {
 97:       if (bb[j] != 0.0) {
 98:         rows[cnt++] = rstart + i;
 99:         goto ok2;
100:       }
101:     }
102: ok2:;
103:   }
104:   ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);
105:   return(0);
106: }

110: PetscErrorCode  MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is)
111: {
112:   PetscErrorCode    ierr;
113:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*) Y->data;

116:   if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) {
117:     MatDiagonalSet(aij->A,D,is);
118:   } else {
119:     MatDiagonalSet_Default(Y,D,is);
120:   }
121:   return(0);
122: }


127: PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows)
128: {
129:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)M->data;
131:   PetscInt       i,rstart,nrows,*rows;

134:   *zrows = NULL;
135:   MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);
136:   MatGetOwnershipRange(M,&rstart,NULL);
137:   for (i=0; i<nrows; i++) rows[i] += rstart;
138:   ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);
139:   return(0);
140: }

144: PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms)
145: {
147:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)A->data;
148:   PetscInt       i,n,*garray = aij->garray;
149:   Mat_SeqAIJ     *a_aij = (Mat_SeqAIJ*) aij->A->data;
150:   Mat_SeqAIJ     *b_aij = (Mat_SeqAIJ*) aij->B->data;
151:   PetscReal      *work;

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

178:   } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
179:   if (type == NORM_INFINITY) {
180:     MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
181:   } else {
182:     MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
183:   }
184:   PetscFree(work);
185:   if (type == NORM_2) {
186:     for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]);
187:   }
188:   return(0);
189: }

193: PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is)
194: {
195:   Mat_MPIAIJ      *a  = (Mat_MPIAIJ*)A->data;
196:   IS              sis,gis;
197:   PetscErrorCode  ierr;
198:   const PetscInt  *isis,*igis;
199:   PetscInt        n,*iis,nsis,ngis,rstart,i;

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

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

218:   ISRestoreIndices(sis,&isis);
219:   ISRestoreIndices(gis,&igis);
220:   ISDestroy(&sis);
221:   ISDestroy(&gis);
222:   return(0);
223: }

227: /*
228:     Distributes a SeqAIJ matrix across a set of processes. Code stolen from
229:     MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type.

231:     Only for square matrices

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

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

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

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

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

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

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

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

397: /*
398:   Local utility routine that creates a mapping from the global column
399: number to the local number in the off-diagonal part of the local
400: storage of the matrix.  When PETSC_USE_CTABLE is used this is scalable at
401: a slightly higher hash table cost; without it it is not scalable (each processor
402: has an order N integer array but is fast to acess.
403: */
406: PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat)
407: {
408:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
410:   PetscInt       n = aij->B->cmap->n,i;

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

427: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol)     \
428: { \
429:     if (col <= lastcol1)  low1 = 0;     \
430:     else                 high1 = nrow1; \
431:     lastcol1 = col;\
432:     while (high1-low1 > 5) { \
433:       t = (low1+high1)/2; \
434:       if (rp1[t] > col) high1 = t; \
435:       else              low1  = t; \
436:     } \
437:       for (_i=low1; _i<high1; _i++) { \
438:         if (rp1[_i] > col) break; \
439:         if (rp1[_i] == col) { \
440:           if (addv == ADD_VALUES) ap1[_i] += value;   \
441:           else                    ap1[_i] = value; \
442:           goto a_noinsert; \
443:         } \
444:       }  \
445:       if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
446:       if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;}                \
447:       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); \
448:       MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
449:       N = nrow1++ - 1; a->nz++; high1++; \
450:       /* shift up all the later entries in this row */ \
451:       for (ii=N; ii>=_i; ii--) { \
452:         rp1[ii+1] = rp1[ii]; \
453:         ap1[ii+1] = ap1[ii]; \
454:       } \
455:       rp1[_i] = col;  \
456:       ap1[_i] = value;  \
457:       A->nonzerostate++;\
458:       a_noinsert: ; \
459:       ailen[row] = nrow1; \
460: }


463: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \
464:   { \
465:     if (col <= lastcol2) low2 = 0;                        \
466:     else high2 = nrow2;                                   \
467:     lastcol2 = col;                                       \
468:     while (high2-low2 > 5) {                              \
469:       t = (low2+high2)/2;                                 \
470:       if (rp2[t] > col) high2 = t;                        \
471:       else             low2  = t;                         \
472:     }                                                     \
473:     for (_i=low2; _i<high2; _i++) {                       \
474:       if (rp2[_i] > col) break;                           \
475:       if (rp2[_i] == col) {                               \
476:         if (addv == ADD_VALUES) ap2[_i] += value;         \
477:         else                    ap2[_i] = value;          \
478:         goto b_noinsert;                                  \
479:       }                                                   \
480:     }                                                     \
481:     if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
482:     if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;}                        \
483:     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); \
484:     MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
485:     N = nrow2++ - 1; b->nz++; high2++;                    \
486:     /* shift up all the later entries in this row */      \
487:     for (ii=N; ii>=_i; ii--) {                            \
488:       rp2[ii+1] = rp2[ii];                                \
489:       ap2[ii+1] = ap2[ii];                                \
490:     }                                                     \
491:     rp2[_i] = col;                                        \
492:     ap2[_i] = value;                                      \
493:     B->nonzerostate++;                                    \
494:     b_noinsert: ;                                         \
495:     bilen[row] = nrow2;                                   \
496:   }

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

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

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

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

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

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

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

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

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

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

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

644:   for (i=0; i<m; i++) {
645:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
646:     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);
647:     if (idxm[i] >= rstart && idxm[i] < rend) {
648:       row = idxm[i] - rstart;
649:       for (j=0; j<n; j++) {
650:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
651:         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);
652:         if (idxn[j] >= cstart && idxn[j] < cend) {
653:           col  = idxn[j] - cstart;
654:           MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
655:         } else {
656:           if (!aij->colmap) {
657:             MatCreateColmap_MPIAIJ_Private(mat);
658:           }
659: #if defined(PETSC_USE_CTABLE)
660:           PetscTableFind(aij->colmap,idxn[j]+1,&col);
661:           col--;
662: #else
663:           col = aij->colmap[idxn[j]] - 1;
664: #endif
665:           if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
666:           else {
667:             MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
668:           }
669:         }
670:       }
671:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
672:   }
673:   return(0);
674: }

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

680: PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode)
681: {
682:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
684:   PetscInt       nstash,reallocs;
685:   InsertMode     addv;

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

690:   /* make sure all processors are either in INSERTMODE or ADDMODE */
691:   MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));
692:   if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added");
693:   mat->insertmode = addv; /* in case this processor had no cache */

695:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
696:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
697:   PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
698:   return(0);
699: }

703: PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode)
704: {
705:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
706:   Mat_SeqAIJ     *a   = (Mat_SeqAIJ*)aij->A->data;
708:   PetscMPIInt    n;
709:   PetscInt       i,j,rstart,ncols,flg;
710:   PetscInt       *row,*col;
711:   PetscBool      other_disassembled;
712:   PetscScalar    *val;
713:   InsertMode     addv = mat->insertmode;

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

718:   if (!aij->donotstash && !mat->nooffprocentries) {
719:     while (1) {
720:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
721:       if (!flg) break;

723:       for (i=0; i<n; ) {
724:         /* Now identify the consecutive vals belonging to the same row */
725:         for (j=i,rstart=row[j]; j<n; j++) {
726:           if (row[j] != rstart) break;
727:         }
728:         if (j < n) ncols = j-i;
729:         else       ncols = n-i;
730:         /* Now assemble all these values with a single function call */
731:         MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);

733:         i = j;
734:       }
735:     }
736:     MatStashScatterEnd_Private(&mat->stash);
737:   }
738:   MatAssemblyBegin(aij->A,mode);
739:   MatAssemblyEnd(aij->A,mode);

741:   /* determine if any processor has disassembled, if so we must
742:      also disassemble ourselfs, in order that we may reassemble. */
743:   /*
744:      if nonzero structure of submatrix B cannot change then we know that
745:      no processor disassembled thus we can skip this stuff
746:   */
747:   if (!((Mat_SeqAIJ*)aij->B->data)->nonew) {
748:     MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
749:     if (mat->was_assembled && !other_disassembled) {
750:       MatDisAssemble_MPIAIJ(mat);
751:     }
752:   }
753:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
754:     MatSetUpMultiply_MPIAIJ(mat);
755:   }
756:   MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);
757:   MatAssemblyBegin(aij->B,mode);
758:   MatAssemblyEnd(aij->B,mode);

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

762:   aij->rowvalues = 0;

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

767:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
768:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
769:     PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate;
770:     MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
771:   }
772:   return(0);
773: }

777: PetscErrorCode MatZeroEntries_MPIAIJ(Mat A)
778: {
779:   Mat_MPIAIJ     *l = (Mat_MPIAIJ*)A->data;

783:   MatZeroEntries(l->A);
784:   MatZeroEntries(l->B);
785:   return(0);
786: }

790: PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
791: {
792:   Mat_MPIAIJ    *mat    = (Mat_MPIAIJ *) A->data;
793:   PetscInt      *owners = A->rmap->range;
794:   PetscInt       n      = A->rmap->n;
795:   PetscSF        sf;
796:   PetscInt      *lrows;
797:   PetscSFNode   *rrows;
798:   PetscInt       r, p = 0, len = 0;

802:   /* Create SF where leaves are input rows and roots are owned rows */
803:   PetscMalloc1(n, &lrows);
804:   for (r = 0; r < n; ++r) lrows[r] = -1;
805:   if (!A->nooffproczerorows) {PetscMalloc1(N, &rrows);}
806:   for (r = 0; r < N; ++r) {
807:     const PetscInt idx   = rows[r];
808:     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);
809:     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
810:       PetscLayoutFindOwner(A->rmap,idx,&p);
811:     }
812:     if (A->nooffproczerorows) {
813:       if (p != mat->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,mat->rank);
814:       lrows[len++] = idx - owners[p];
815:     } else {
816:       rrows[r].rank = p;
817:       rrows[r].index = rows[r] - owners[p];
818:     }
819:   }
820:   if (!A->nooffproczerorows) {
821:     PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
822:     PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
823:     /* Collect flags for rows to be zeroed */
824:     PetscSFReduceBegin(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);
825:     PetscSFReduceEnd(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);
826:     PetscSFDestroy(&sf);
827:     /* Compress and put in row numbers */
828:     for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
829:   }
830:   /* fix right hand side if needed */
831:   if (x && b) {
832:     const PetscScalar *xx;
833:     PetscScalar       *bb;

835:     VecGetArrayRead(x, &xx);
836:     VecGetArray(b, &bb);
837:     for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
838:     VecRestoreArrayRead(x, &xx);
839:     VecRestoreArray(b, &bb);
840:   }
841:   /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/
842:   MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
843:   if ((diag != 0.0) && (mat->A->rmap->N == mat->A->cmap->N)) {
844:     MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);
845:   } else if (diag != 0.0) {
846:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
847:     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");
848:     for (r = 0; r < len; ++r) {
849:       const PetscInt row = lrows[r] + A->rmap->rstart;
850:       MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);
851:     }
852:     MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
853:     MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);
854:   } else {
855:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
856:   }
857:   PetscFree(lrows);

859:   /* only change matrix nonzero state if pattern was allowed to be changed */
860:   if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) {
861:     PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate;
862:     MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
863:   }
864:   return(0);
865: }

869: PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
870: {
871:   Mat_MPIAIJ        *l = (Mat_MPIAIJ*)A->data;
872:   PetscErrorCode    ierr;
873:   PetscMPIInt       n = A->rmap->n;
874:   PetscInt          i,j,r,m,p = 0,len = 0;
875:   PetscInt          *lrows,*owners = A->rmap->range;
876:   PetscSFNode       *rrows;
877:   PetscSF           sf;
878:   const PetscScalar *xx;
879:   PetscScalar       *bb,*mask;
880:   Vec               xmask,lmask;
881:   Mat_SeqAIJ        *aij = (Mat_SeqAIJ*)l->B->data;
882:   const PetscInt    *aj, *ii,*ridx;
883:   PetscScalar       *aa;

886:   /* Create SF where leaves are input rows and roots are owned rows */
887:   PetscMalloc1(n, &lrows);
888:   for (r = 0; r < n; ++r) lrows[r] = -1;
889:   PetscMalloc1(N, &rrows);
890:   for (r = 0; r < N; ++r) {
891:     const PetscInt idx   = rows[r];
892:     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);
893:     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
894:       PetscLayoutFindOwner(A->rmap,idx,&p);
895:     }
896:     rrows[r].rank  = p;
897:     rrows[r].index = rows[r] - owners[p];
898:   }
899:   PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
900:   PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
901:   /* Collect flags for rows to be zeroed */
902:   PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
903:   PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
904:   PetscSFDestroy(&sf);
905:   /* Compress and put in row numbers */
906:   for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
907:   /* zero diagonal part of matrix */
908:   MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
909:   /* handle off diagonal part of matrix */
910:   MatCreateVecs(A,&xmask,NULL);
911:   VecDuplicate(l->lvec,&lmask);
912:   VecGetArray(xmask,&bb);
913:   for (i=0; i<len; i++) bb[lrows[i]] = 1;
914:   VecRestoreArray(xmask,&bb);
915:   VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
916:   VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
917:   VecDestroy(&xmask);
918:   if (x) {
919:     VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
920:     VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
921:     VecGetArrayRead(l->lvec,&xx);
922:     VecGetArray(b,&bb);
923:   }
924:   VecGetArray(lmask,&mask);
925:   /* remove zeroed rows of off diagonal matrix */
926:   ii = aij->i;
927:   for (i=0; i<len; i++) {
928:     PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));
929:   }
930:   /* loop over all elements of off process part of matrix zeroing removed columns*/
931:   if (aij->compressedrow.use) {
932:     m    = aij->compressedrow.nrows;
933:     ii   = aij->compressedrow.i;
934:     ridx = aij->compressedrow.rindex;
935:     for (i=0; i<m; i++) {
936:       n  = ii[i+1] - ii[i];
937:       aj = aij->j + ii[i];
938:       aa = aij->a + ii[i];

940:       for (j=0; j<n; j++) {
941:         if (PetscAbsScalar(mask[*aj])) {
942:           if (b) bb[*ridx] -= *aa*xx[*aj];
943:           *aa = 0.0;
944:         }
945:         aa++;
946:         aj++;
947:       }
948:       ridx++;
949:     }
950:   } else { /* do not use compressed row format */
951:     m = l->B->rmap->n;
952:     for (i=0; i<m; i++) {
953:       n  = ii[i+1] - ii[i];
954:       aj = aij->j + ii[i];
955:       aa = aij->a + ii[i];
956:       for (j=0; j<n; j++) {
957:         if (PetscAbsScalar(mask[*aj])) {
958:           if (b) bb[i] -= *aa*xx[*aj];
959:           *aa = 0.0;
960:         }
961:         aa++;
962:         aj++;
963:       }
964:     }
965:   }
966:   if (x) {
967:     VecRestoreArray(b,&bb);
968:     VecRestoreArrayRead(l->lvec,&xx);
969:   }
970:   VecRestoreArray(lmask,&mask);
971:   VecDestroy(&lmask);
972:   PetscFree(lrows);

974:   /* only change matrix nonzero state if pattern was allowed to be changed */
975:   if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) {
976:     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
977:     MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
978:   }
979:   return(0);
980: }

984: PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy)
985: {
986:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
988:   PetscInt       nt;

991:   VecGetLocalSize(xx,&nt);
992:   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);
993:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
994:   (*a->A->ops->mult)(a->A,xx,yy);
995:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
996:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
997:   return(0);
998: }

1002: PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx)
1003: {
1004:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1008:   MatMultDiagonalBlock(a->A,bb,xx);
1009:   return(0);
1010: }

1014: PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1015: {
1016:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1020:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1021:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
1022:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1023:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
1024:   return(0);
1025: }

1029: PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy)
1030: {
1031:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
1033:   PetscBool      merged;

1036:   VecScatterGetMerged(a->Mvctx,&merged);
1037:   /* do nondiagonal part */
1038:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1039:   if (!merged) {
1040:     /* send it on its way */
1041:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1042:     /* do local part */
1043:     (*a->A->ops->multtranspose)(a->A,xx,yy);
1044:     /* receive remote parts: note this assumes the values are not actually */
1045:     /* added in yy until the next line, */
1046:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1047:   } else {
1048:     /* do local part */
1049:     (*a->A->ops->multtranspose)(a->A,xx,yy);
1050:     /* send it on its way */
1051:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1052:     /* values actually were received in the Begin() but we need to call this nop */
1053:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1054:   }
1055:   return(0);
1056: }

1060: PetscErrorCode  MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool  *f)
1061: {
1062:   MPI_Comm       comm;
1063:   Mat_MPIAIJ     *Aij = (Mat_MPIAIJ*) Amat->data, *Bij;
1064:   Mat            Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs;
1065:   IS             Me,Notme;
1067:   PetscInt       M,N,first,last,*notme,i;
1068:   PetscMPIInt    size;

1071:   /* Easy test: symmetric diagonal block */
1072:   Bij  = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A;
1073:   MatIsTranspose(Adia,Bdia,tol,f);
1074:   if (!*f) return(0);
1075:   PetscObjectGetComm((PetscObject)Amat,&comm);
1076:   MPI_Comm_size(comm,&size);
1077:   if (size == 1) return(0);

1079:   /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */
1080:   MatGetSize(Amat,&M,&N);
1081:   MatGetOwnershipRange(Amat,&first,&last);
1082:   PetscMalloc1(N-last+first,&notme);
1083:   for (i=0; i<first; i++) notme[i] = i;
1084:   for (i=last; i<M; i++) notme[i-last+first] = i;
1085:   ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
1086:   ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
1087:   MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
1088:   Aoff = Aoffs[0];
1089:   MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
1090:   Boff = Boffs[0];
1091:   MatIsTranspose(Aoff,Boff,tol,f);
1092:   MatDestroyMatrices(1,&Aoffs);
1093:   MatDestroyMatrices(1,&Boffs);
1094:   ISDestroy(&Me);
1095:   ISDestroy(&Notme);
1096:   PetscFree(notme);
1097:   return(0);
1098: }

1102: PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1103: {
1104:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1108:   /* do nondiagonal part */
1109:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1110:   /* send it on its way */
1111:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1112:   /* do local part */
1113:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
1114:   /* receive remote parts */
1115:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1116:   return(0);
1117: }

1119: /*
1120:   This only works correctly for square matrices where the subblock A->A is the
1121:    diagonal block
1122: */
1125: PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v)
1126: {
1128:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1131:   if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1132:   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");
1133:   MatGetDiagonal(a->A,v);
1134:   return(0);
1135: }

1139: PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa)
1140: {
1141:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1145:   MatScale(a->A,aa);
1146:   MatScale(a->B,aa);
1147:   return(0);
1148: }

1152: PetscErrorCode MatDestroy_MPIAIJ(Mat mat)
1153: {
1154:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

1158: #if defined(PETSC_USE_LOG)
1159:   PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
1160: #endif
1161:   MatStashDestroy_Private(&mat->stash);
1162:   VecDestroy(&aij->diag);
1163:   MatDestroy(&aij->A);
1164:   MatDestroy(&aij->B);
1165: #if defined(PETSC_USE_CTABLE)
1166:   PetscTableDestroy(&aij->colmap);
1167: #else
1168:   PetscFree(aij->colmap);
1169: #endif
1170:   PetscFree(aij->garray);
1171:   VecDestroy(&aij->lvec);
1172:   VecScatterDestroy(&aij->Mvctx);
1173:   PetscFree2(aij->rowvalues,aij->rowindices);
1174:   PetscFree(aij->ld);
1175:   PetscFree(mat->data);

1177:   PetscObjectChangeTypeName((PetscObject)mat,0);
1178:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1179:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1180:   PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);
1181:   PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
1182:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);
1183:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);
1184:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
1185:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);
1186: #if defined(PETSC_HAVE_ELEMENTAL)
1187:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);
1188: #endif
1189:   return(0);
1190: }

1194: PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer)
1195: {
1196:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
1197:   Mat_SeqAIJ     *A   = (Mat_SeqAIJ*)aij->A->data;
1198:   Mat_SeqAIJ     *B   = (Mat_SeqAIJ*)aij->B->data;
1200:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
1201:   int            fd;
1202:   PetscInt       nz,header[4],*row_lengths,*range=0,rlen,i;
1203:   PetscInt       nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0;
1204:   PetscScalar    *column_values;
1205:   PetscInt       message_count,flowcontrolcount;
1206:   FILE           *file;

1209:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1210:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
1211:   nz   = A->nz + B->nz;
1212:   PetscViewerBinaryGetDescriptor(viewer,&fd);
1213:   if (!rank) {
1214:     header[0] = MAT_FILE_CLASSID;
1215:     header[1] = mat->rmap->N;
1216:     header[2] = mat->cmap->N;

1218:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1219:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
1220:     /* get largest number of rows any processor has */
1221:     rlen  = mat->rmap->n;
1222:     range = mat->rmap->range;
1223:     for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]);
1224:   } else {
1225:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1226:     rlen = mat->rmap->n;
1227:   }

1229:   /* load up the local row counts */
1230:   PetscMalloc1(rlen+1,&row_lengths);
1231:   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];

1233:   /* store the row lengths to the file */
1234:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1235:   if (!rank) {
1236:     PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);
1237:     for (i=1; i<size; i++) {
1238:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1239:       rlen = range[i+1] - range[i];
1240:       MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1241:       PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);
1242:     }
1243:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1244:   } else {
1245:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1246:     MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1247:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1248:   }
1249:   PetscFree(row_lengths);

1251:   /* load up the local column indices */
1252:   nzmax = nz; /* th processor needs space a largest processor needs */
1253:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
1254:   PetscMalloc1(nzmax+1,&column_indices);
1255:   cnt   = 0;
1256:   for (i=0; i<mat->rmap->n; i++) {
1257:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1258:       if ((col = garray[B->j[j]]) > cstart) break;
1259:       column_indices[cnt++] = col;
1260:     }
1261:     for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart;
1262:     for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]];
1263:   }
1264:   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);

1266:   /* store the column indices to the file */
1267:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1268:   if (!rank) {
1269:     MPI_Status status;
1270:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1271:     for (i=1; i<size; i++) {
1272:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1273:       MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1274:       if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1275:       MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1276:       PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);
1277:     }
1278:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1279:   } else {
1280:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1281:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1282:     MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1283:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1284:   }
1285:   PetscFree(column_indices);

1287:   /* load up the local column values */
1288:   PetscMalloc1(nzmax+1,&column_values);
1289:   cnt  = 0;
1290:   for (i=0; i<mat->rmap->n; i++) {
1291:     for (j=B->i[i]; j<B->i[i+1]; j++) {
1292:       if (garray[B->j[j]] > cstart) break;
1293:       column_values[cnt++] = B->a[j];
1294:     }
1295:     for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k];
1296:     for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j];
1297:   }
1298:   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);

1300:   /* store the column values to the file */
1301:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1302:   if (!rank) {
1303:     MPI_Status status;
1304:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1305:     for (i=1; i<size; i++) {
1306:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1307:       MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1308:       if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1309:       MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));
1310:       PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);
1311:     }
1312:     PetscViewerFlowControlEndMaster(viewer,&message_count);
1313:   } else {
1314:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1315:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1316:     MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1317:     PetscViewerFlowControlEndWorker(viewer,&message_count);
1318:   }
1319:   PetscFree(column_values);

1321:   PetscViewerBinaryGetInfoPointer(viewer,&file);
1322:   if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs));
1323:   return(0);
1324: }

1326: #include <petscdraw.h>
1329: PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1330: {
1331:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*)mat->data;
1332:   PetscErrorCode    ierr;
1333:   PetscMPIInt       rank = aij->rank,size = aij->size;
1334:   PetscBool         isdraw,iascii,isbinary;
1335:   PetscViewer       sviewer;
1336:   PetscViewerFormat format;

1339:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1340:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1341:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1342:   if (iascii) {
1343:     PetscViewerGetFormat(viewer,&format);
1344:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1345:       MatInfo   info;
1346:       PetscBool inodes;

1348:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1349:       MatGetInfo(mat,MAT_LOCAL,&info);
1350:       MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);
1351:       PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);
1352:       if (!inodes) {
1353:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n",
1354:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
1355:       } else {
1356:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n",
1357:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
1358:       }
1359:       MatGetInfo(aij->A,MAT_LOCAL,&info);
1360:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1361:       MatGetInfo(aij->B,MAT_LOCAL,&info);
1362:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1363:       PetscViewerFlush(viewer);
1364:       PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);
1365:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
1366:       VecScatterView(aij->Mvctx,viewer);
1367:       return(0);
1368:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
1369:       PetscInt inodecount,inodelimit,*inodes;
1370:       MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);
1371:       if (inodes) {
1372:         PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
1373:       } else {
1374:         PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
1375:       }
1376:       return(0);
1377:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1378:       return(0);
1379:     }
1380:   } else if (isbinary) {
1381:     if (size == 1) {
1382:       PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1383:       MatView(aij->A,viewer);
1384:     } else {
1385:       MatView_MPIAIJ_Binary(mat,viewer);
1386:     }
1387:     return(0);
1388:   } else if (isdraw) {
1389:     PetscDraw draw;
1390:     PetscBool isnull;
1391:     PetscViewerDrawGetDraw(viewer,0,&draw);
1392:     PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
1393:   }

1395:   {
1396:     /* assemble the entire matrix onto first processor. */
1397:     Mat        A;
1398:     Mat_SeqAIJ *Aloc;
1399:     PetscInt   M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct;
1400:     MatScalar  *a;

1402:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
1403:     if (!rank) {
1404:       MatSetSizes(A,M,N,M,N);
1405:     } else {
1406:       MatSetSizes(A,0,0,M,N);
1407:     }
1408:     /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */
1409:     MatSetType(A,MATMPIAIJ);
1410:     MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);
1411:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
1412:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

1414:     /* copy over the A part */
1415:     Aloc = (Mat_SeqAIJ*)aij->A->data;
1416:     m    = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1417:     row  = mat->rmap->rstart;
1418:     for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart;
1419:     for (i=0; i<m; i++) {
1420:       MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);
1421:       row++;
1422:       a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i];
1423:     }
1424:     aj = Aloc->j;
1425:     for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart;

1427:     /* copy over the B part */
1428:     Aloc = (Mat_SeqAIJ*)aij->B->data;
1429:     m    = aij->B->rmap->n;  ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
1430:     row  = mat->rmap->rstart;
1431:     PetscMalloc1(ai[m]+1,&cols);
1432:     ct   = cols;
1433:     for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]];
1434:     for (i=0; i<m; i++) {
1435:       MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);
1436:       row++;
1437:       a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i];
1438:     }
1439:     PetscFree(ct);
1440:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
1441:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
1442:     /*
1443:        Everyone has to call to draw the matrix since the graphics waits are
1444:        synchronized across all processors that share the PetscDraw object
1445:     */
1446:     PetscViewerGetSingleton(viewer,&sviewer);
1447:     if (!rank) {
1448:       PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);
1449:       MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);
1450:     }
1451:     PetscViewerRestoreSingleton(viewer,&sviewer);
1452:     MatDestroy(&A);
1453:   }
1454:   return(0);
1455: }

1459: PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer)
1460: {
1462:   PetscBool      iascii,isdraw,issocket,isbinary;

1465:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1466:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1467:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1468:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1469:   if (iascii || isdraw || isbinary || issocket) {
1470:     MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);
1471:   }
1472:   return(0);
1473: }

1477: PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1478: {
1479:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1481:   Vec            bb1 = 0;
1482:   PetscBool      hasop;

1485:   if (flag == SOR_APPLY_UPPER) {
1486:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1487:     return(0);
1488:   }

1490:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1491:     VecDuplicate(bb,&bb1);
1492:   }

1494:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
1495:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1496:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1497:       its--;
1498:     }

1500:     while (its--) {
1501:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1502:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1504:       /* update rhs: bb1 = bb - B*x */
1505:       VecScale(mat->lvec,-1.0);
1506:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1508:       /* local sweep */
1509:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1510:     }
1511:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
1512:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1513:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1514:       its--;
1515:     }
1516:     while (its--) {
1517:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1518:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1520:       /* update rhs: bb1 = bb - B*x */
1521:       VecScale(mat->lvec,-1.0);
1522:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1524:       /* local sweep */
1525:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1526:     }
1527:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
1528:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1529:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1530:       its--;
1531:     }
1532:     while (its--) {
1533:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1534:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1536:       /* update rhs: bb1 = bb - B*x */
1537:       VecScale(mat->lvec,-1.0);
1538:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1540:       /* local sweep */
1541:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1542:     }
1543:   } else if (flag & SOR_EISENSTAT) {
1544:     Vec xx1;

1546:     VecDuplicate(bb,&xx1);
1547:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

1549:     VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1550:     VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1551:     if (!mat->diag) {
1552:       MatCreateVecs(matin,&mat->diag,NULL);
1553:       MatGetDiagonal(matin,mat->diag);
1554:     }
1555:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
1556:     if (hasop) {
1557:       MatMultDiagonalBlock(matin,xx,bb1);
1558:     } else {
1559:       VecPointwiseMult(bb1,mat->diag,xx);
1560:     }
1561:     VecAYPX(bb1,(omega-2.0)/omega,bb);

1563:     MatMultAdd(mat->B,mat->lvec,bb1,bb1);

1565:     /* local sweep */
1566:     (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
1567:     VecAXPY(xx,1.0,xx1);
1568:     VecDestroy(&xx1);
1569:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");

1571:   VecDestroy(&bb1);
1572:   return(0);
1573: }

1577: PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B)
1578: {
1579:   Mat            aA,aB,Aperm;
1580:   const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj;
1581:   PetscScalar    *aa,*ba;
1582:   PetscInt       i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest;
1583:   PetscSF        rowsf,sf;
1584:   IS             parcolp = NULL;
1585:   PetscBool      done;

1589:   MatGetLocalSize(A,&m,&n);
1590:   ISGetIndices(rowp,&rwant);
1591:   ISGetIndices(colp,&cwant);
1592:   PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);

1594:   /* Invert row permutation to find out where my rows should go */
1595:   PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);
1596:   PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);
1597:   PetscSFSetFromOptions(rowsf);
1598:   for (i=0; i<m; i++) work[i] = A->rmap->rstart + i;
1599:   PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1600:   PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);

1602:   /* Invert column permutation to find out where my columns should go */
1603:   PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1604:   PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);
1605:   PetscSFSetFromOptions(sf);
1606:   for (i=0; i<n; i++) work[i] = A->cmap->rstart + i;
1607:   PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1608:   PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1609:   PetscSFDestroy(&sf);

1611:   ISRestoreIndices(rowp,&rwant);
1612:   ISRestoreIndices(colp,&cwant);
1613:   MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);

1615:   /* Find out where my gcols should go */
1616:   MatGetSize(aB,NULL,&ng);
1617:   PetscMalloc1(ng,&gcdest);
1618:   PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1619:   PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);
1620:   PetscSFSetFromOptions(sf);
1621:   PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);
1622:   PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);
1623:   PetscSFDestroy(&sf);

1625:   PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);
1626:   MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1627:   MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1628:   for (i=0; i<m; i++) {
1629:     PetscInt row = rdest[i],rowner;
1630:     PetscLayoutFindOwner(A->rmap,row,&rowner);
1631:     for (j=ai[i]; j<ai[i+1]; j++) {
1632:       PetscInt cowner,col = cdest[aj[j]];
1633:       PetscLayoutFindOwner(A->cmap,col,&cowner); /* Could build an index for the columns to eliminate this search */
1634:       if (rowner == cowner) dnnz[i]++;
1635:       else onnz[i]++;
1636:     }
1637:     for (j=bi[i]; j<bi[i+1]; j++) {
1638:       PetscInt cowner,col = gcdest[bj[j]];
1639:       PetscLayoutFindOwner(A->cmap,col,&cowner);
1640:       if (rowner == cowner) dnnz[i]++;
1641:       else onnz[i]++;
1642:     }
1643:   }
1644:   PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);
1645:   PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);
1646:   PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);
1647:   PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);
1648:   PetscSFDestroy(&rowsf);

1650:   MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);
1651:   MatSeqAIJGetArray(aA,&aa);
1652:   MatSeqAIJGetArray(aB,&ba);
1653:   for (i=0; i<m; i++) {
1654:     PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */
1655:     PetscInt j0,rowlen;
1656:     rowlen = ai[i+1] - ai[i];
1657:     for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */
1658:       for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]];
1659:       MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);
1660:     }
1661:     rowlen = bi[i+1] - bi[i];
1662:     for (j0=j=0; j<rowlen; j0=j) {
1663:       for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]];
1664:       MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);
1665:     }
1666:   }
1667:   MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);
1668:   MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);
1669:   MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1670:   MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1671:   MatSeqAIJRestoreArray(aA,&aa);
1672:   MatSeqAIJRestoreArray(aB,&ba);
1673:   PetscFree4(dnnz,onnz,tdnnz,tonnz);
1674:   PetscFree3(work,rdest,cdest);
1675:   PetscFree(gcdest);
1676:   if (parcolp) {ISDestroy(&colp);}
1677:   *B = Aperm;
1678:   return(0);
1679: }

1683: PetscErrorCode  MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
1684: {
1685:   Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;

1689:   MatGetSize(aij->B,NULL,nghosts);
1690:   if (ghosts) *ghosts = aij->garray;
1691:   return(0);
1692: }

1696: PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1697: {
1698:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1699:   Mat            A    = mat->A,B = mat->B;
1701:   PetscReal      isend[5],irecv[5];

1704:   info->block_size = 1.0;
1705:   MatGetInfo(A,MAT_LOCAL,info);

1707:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1708:   isend[3] = info->memory;  isend[4] = info->mallocs;

1710:   MatGetInfo(B,MAT_LOCAL,info);

1712:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1713:   isend[3] += info->memory;  isend[4] += info->mallocs;
1714:   if (flag == MAT_LOCAL) {
1715:     info->nz_used      = isend[0];
1716:     info->nz_allocated = isend[1];
1717:     info->nz_unneeded  = isend[2];
1718:     info->memory       = isend[3];
1719:     info->mallocs      = isend[4];
1720:   } else if (flag == MAT_GLOBAL_MAX) {
1721:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

1723:     info->nz_used      = irecv[0];
1724:     info->nz_allocated = irecv[1];
1725:     info->nz_unneeded  = irecv[2];
1726:     info->memory       = irecv[3];
1727:     info->mallocs      = irecv[4];
1728:   } else if (flag == MAT_GLOBAL_SUM) {
1729:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

1731:     info->nz_used      = irecv[0];
1732:     info->nz_allocated = irecv[1];
1733:     info->nz_unneeded  = irecv[2];
1734:     info->memory       = irecv[3];
1735:     info->mallocs      = irecv[4];
1736:   }
1737:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1738:   info->fill_ratio_needed = 0;
1739:   info->factor_mallocs    = 0;
1740:   return(0);
1741: }

1745: PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg)
1746: {
1747:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1751:   switch (op) {
1752:   case MAT_NEW_NONZERO_LOCATIONS:
1753:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1754:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1755:   case MAT_KEEP_NONZERO_PATTERN:
1756:   case MAT_NEW_NONZERO_LOCATION_ERR:
1757:   case MAT_USE_INODES:
1758:   case MAT_IGNORE_ZERO_ENTRIES:
1759:     MatCheckPreallocated(A,1);
1760:     MatSetOption(a->A,op,flg);
1761:     MatSetOption(a->B,op,flg);
1762:     break;
1763:   case MAT_ROW_ORIENTED:
1764:     a->roworiented = flg;

1766:     MatSetOption(a->A,op,flg);
1767:     MatSetOption(a->B,op,flg);
1768:     break;
1769:   case MAT_NEW_DIAGONALS:
1770:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1771:     break;
1772:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1773:     a->donotstash = flg;
1774:     break;
1775:   case MAT_SPD:
1776:     A->spd_set = PETSC_TRUE;
1777:     A->spd     = flg;
1778:     if (flg) {
1779:       A->symmetric                  = PETSC_TRUE;
1780:       A->structurally_symmetric     = PETSC_TRUE;
1781:       A->symmetric_set              = PETSC_TRUE;
1782:       A->structurally_symmetric_set = PETSC_TRUE;
1783:     }
1784:     break;
1785:   case MAT_SYMMETRIC:
1786:     MatSetOption(a->A,op,flg);
1787:     break;
1788:   case MAT_STRUCTURALLY_SYMMETRIC:
1789:     MatSetOption(a->A,op,flg);
1790:     break;
1791:   case MAT_HERMITIAN:
1792:     MatSetOption(a->A,op,flg);
1793:     break;
1794:   case MAT_SYMMETRY_ETERNAL:
1795:     MatSetOption(a->A,op,flg);
1796:     break;
1797:   default:
1798:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1799:   }
1800:   return(0);
1801: }

1805: PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1806: {
1807:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1808:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1810:   PetscInt       i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart;
1811:   PetscInt       nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend;
1812:   PetscInt       *cmap,*idx_p;

1815:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1816:   mat->getrowactive = PETSC_TRUE;

1818:   if (!mat->rowvalues && (idx || v)) {
1819:     /*
1820:         allocate enough space to hold information from the longest row.
1821:     */
1822:     Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data;
1823:     PetscInt   max = 1,tmp;
1824:     for (i=0; i<matin->rmap->n; i++) {
1825:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1826:       if (max < tmp) max = tmp;
1827:     }
1828:     PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);
1829:   }

1831:   if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows");
1832:   lrow = row - rstart;

1834:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1835:   if (!v)   {pvA = 0; pvB = 0;}
1836:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1837:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1838:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1839:   nztot = nzA + nzB;

1841:   cmap = mat->garray;
1842:   if (v  || idx) {
1843:     if (nztot) {
1844:       /* Sort by increasing column numbers, assuming A and B already sorted */
1845:       PetscInt imark = -1;
1846:       if (v) {
1847:         *v = v_p = mat->rowvalues;
1848:         for (i=0; i<nzB; i++) {
1849:           if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i];
1850:           else break;
1851:         }
1852:         imark = i;
1853:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1854:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1855:       }
1856:       if (idx) {
1857:         *idx = idx_p = mat->rowindices;
1858:         if (imark > -1) {
1859:           for (i=0; i<imark; i++) {
1860:             idx_p[i] = cmap[cworkB[i]];
1861:           }
1862:         } else {
1863:           for (i=0; i<nzB; i++) {
1864:             if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]];
1865:             else break;
1866:           }
1867:           imark = i;
1868:         }
1869:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart + cworkA[i];
1870:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]];
1871:       }
1872:     } else {
1873:       if (idx) *idx = 0;
1874:       if (v)   *v   = 0;
1875:     }
1876:   }
1877:   *nz  = nztot;
1878:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1879:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1880:   return(0);
1881: }

1885: PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1886: {
1887:   Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;

1890:   if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1891:   aij->getrowactive = PETSC_FALSE;
1892:   return(0);
1893: }

1897: PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm)
1898: {
1899:   Mat_MPIAIJ     *aij  = (Mat_MPIAIJ*)mat->data;
1900:   Mat_SeqAIJ     *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data;
1902:   PetscInt       i,j,cstart = mat->cmap->rstart;
1903:   PetscReal      sum = 0.0;
1904:   MatScalar      *v;

1907:   if (aij->size == 1) {
1908:      MatNorm(aij->A,type,norm);
1909:   } else {
1910:     if (type == NORM_FROBENIUS) {
1911:       v = amat->a;
1912:       for (i=0; i<amat->nz; i++) {
1913:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1914:       }
1915:       v = bmat->a;
1916:       for (i=0; i<bmat->nz; i++) {
1917:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1918:       }
1919:       MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1920:       *norm = PetscSqrtReal(*norm);
1921:     } else if (type == NORM_1) { /* max column norm */
1922:       PetscReal *tmp,*tmp2;
1923:       PetscInt  *jj,*garray = aij->garray;
1924:       PetscCalloc1(mat->cmap->N+1,&tmp);
1925:       PetscMalloc1(mat->cmap->N+1,&tmp2);
1926:       *norm = 0.0;
1927:       v     = amat->a; jj = amat->j;
1928:       for (j=0; j<amat->nz; j++) {
1929:         tmp[cstart + *jj++] += PetscAbsScalar(*v);  v++;
1930:       }
1931:       v = bmat->a; jj = bmat->j;
1932:       for (j=0; j<bmat->nz; j++) {
1933:         tmp[garray[*jj++]] += PetscAbsScalar(*v); v++;
1934:       }
1935:       MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1936:       for (j=0; j<mat->cmap->N; j++) {
1937:         if (tmp2[j] > *norm) *norm = tmp2[j];
1938:       }
1939:       PetscFree(tmp);
1940:       PetscFree(tmp2);
1941:     } else if (type == NORM_INFINITY) { /* max row norm */
1942:       PetscReal ntemp = 0.0;
1943:       for (j=0; j<aij->A->rmap->n; j++) {
1944:         v   = amat->a + amat->i[j];
1945:         sum = 0.0;
1946:         for (i=0; i<amat->i[j+1]-amat->i[j]; i++) {
1947:           sum += PetscAbsScalar(*v); v++;
1948:         }
1949:         v = bmat->a + bmat->i[j];
1950:         for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) {
1951:           sum += PetscAbsScalar(*v); v++;
1952:         }
1953:         if (sum > ntemp) ntemp = sum;
1954:       }
1955:       MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
1956:     } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm");
1957:   }
1958:   return(0);
1959: }

1963: PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout)
1964: {
1965:   Mat_MPIAIJ     *a   = (Mat_MPIAIJ*)A->data;
1966:   Mat_SeqAIJ     *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data;
1968:   PetscInt       M      = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i;
1969:   PetscInt       cstart = A->cmap->rstart,ncol;
1970:   Mat            B;
1971:   MatScalar      *array;

1974:   if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");

1976:   ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n;
1977:   ai = Aloc->i; aj = Aloc->j;
1978:   bi = Bloc->i; bj = Bloc->j;
1979:   if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
1980:     PetscInt             *d_nnz,*g_nnz,*o_nnz;
1981:     PetscSFNode          *oloc;
1982:     PETSC_UNUSED PetscSF sf;

1984:     PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);
1985:     /* compute d_nnz for preallocation */
1986:     PetscMemzero(d_nnz,na*sizeof(PetscInt));
1987:     for (i=0; i<ai[ma]; i++) {
1988:       d_nnz[aj[i]]++;
1989:       aj[i] += cstart; /* global col index to be used by MatSetValues() */
1990:     }
1991:     /* compute local off-diagonal contributions */
1992:     PetscMemzero(g_nnz,nb*sizeof(PetscInt));
1993:     for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++;
1994:     /* map those to global */
1995:     PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1996:     PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);
1997:     PetscSFSetFromOptions(sf);
1998:     PetscMemzero(o_nnz,na*sizeof(PetscInt));
1999:     PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2000:     PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2001:     PetscSFDestroy(&sf);

2003:     MatCreate(PetscObjectComm((PetscObject)A),&B);
2004:     MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
2005:     MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));
2006:     MatSetType(B,((PetscObject)A)->type_name);
2007:     MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
2008:     PetscFree4(d_nnz,o_nnz,g_nnz,oloc);
2009:   } else {
2010:     B    = *matout;
2011:     MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
2012:     for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */
2013:   }

2015:   /* copy over the A part */
2016:   array = Aloc->a;
2017:   row   = A->rmap->rstart;
2018:   for (i=0; i<ma; i++) {
2019:     ncol = ai[i+1]-ai[i];
2020:     MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);
2021:     row++;
2022:     array += ncol; aj += ncol;
2023:   }
2024:   aj = Aloc->j;
2025:   for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */

2027:   /* copy over the B part */
2028:   PetscCalloc1(bi[mb],&cols);
2029:   array = Bloc->a;
2030:   row   = A->rmap->rstart;
2031:   for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]];
2032:   cols_tmp = cols;
2033:   for (i=0; i<mb; i++) {
2034:     ncol = bi[i+1]-bi[i];
2035:     MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);
2036:     row++;
2037:     array += ncol; cols_tmp += ncol;
2038:   }
2039:   PetscFree(cols);

2041:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2042:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2043:   if (reuse == MAT_INITIAL_MATRIX || *matout != A) {
2044:     *matout = B;
2045:   } else {
2046:     MatHeaderMerge(A,B);
2047:   }
2048:   return(0);
2049: }

2053: PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr)
2054: {
2055:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
2056:   Mat            a    = aij->A,b = aij->B;
2058:   PetscInt       s1,s2,s3;

2061:   MatGetLocalSize(mat,&s2,&s3);
2062:   if (rr) {
2063:     VecGetLocalSize(rr,&s1);
2064:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
2065:     /* Overlap communication with computation. */
2066:     VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2067:   }
2068:   if (ll) {
2069:     VecGetLocalSize(ll,&s1);
2070:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
2071:     (*b->ops->diagonalscale)(b,ll,0);
2072:   }
2073:   /* scale  the diagonal block */
2074:   (*a->ops->diagonalscale)(a,ll,rr);

2076:   if (rr) {
2077:     /* Do a scatter end and then right scale the off-diagonal block */
2078:     VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2079:     (*b->ops->diagonalscale)(b,0,aij->lvec);
2080:   }
2081:   return(0);
2082: }

2086: PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A)
2087: {
2088:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2092:   MatSetUnfactored(a->A);
2093:   return(0);
2094: }

2098: PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool  *flag)
2099: {
2100:   Mat_MPIAIJ     *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data;
2101:   Mat            a,b,c,d;
2102:   PetscBool      flg;

2106:   a = matA->A; b = matA->B;
2107:   c = matB->A; d = matB->B;

2109:   MatEqual(a,c,&flg);
2110:   if (flg) {
2111:     MatEqual(b,d,&flg);
2112:   }
2113:   MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
2114:   return(0);
2115: }

2119: PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str)
2120: {
2122:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2123:   Mat_MPIAIJ     *b = (Mat_MPIAIJ*)B->data;

2126:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
2127:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
2128:     /* because of the column compression in the off-processor part of the matrix a->B,
2129:        the number of columns in a->B and b->B may be different, hence we cannot call
2130:        the MatCopy() directly on the two parts. If need be, we can provide a more
2131:        efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
2132:        then copying the submatrices */
2133:     MatCopy_Basic(A,B,str);
2134:   } else {
2135:     MatCopy(a->A,b->A,str);
2136:     MatCopy(a->B,b->B,str);
2137:   }
2138:   return(0);
2139: }

2143: PetscErrorCode MatSetUp_MPIAIJ(Mat A)
2144: {

2148:    MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
2149:   return(0);
2150: }

2152: /*
2153:    Computes the number of nonzeros per row needed for preallocation when X and Y
2154:    have different nonzero structure.
2155: */
2158: 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)
2159: {
2160:   PetscInt       i,j,k,nzx,nzy;

2163:   /* Set the number of nonzeros in the new matrix */
2164:   for (i=0; i<m; i++) {
2165:     const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i];
2166:     nzx = xi[i+1] - xi[i];
2167:     nzy = yi[i+1] - yi[i];
2168:     nnz[i] = 0;
2169:     for (j=0,k=0; j<nzx; j++) {                   /* Point in X */
2170:       for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */
2171:       if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++;             /* Skip duplicate */
2172:       nnz[i]++;
2173:     }
2174:     for (; k<nzy; k++) nnz[i]++;
2175:   }
2176:   return(0);
2177: }

2179: /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */
2182: static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
2183: {
2185:   PetscInt       m = Y->rmap->N;
2186:   Mat_SeqAIJ     *x = (Mat_SeqAIJ*)X->data;
2187:   Mat_SeqAIJ     *y = (Mat_SeqAIJ*)Y->data;

2190:   MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
2191:   return(0);
2192: }

2196: PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2197: {
2199:   Mat_MPIAIJ     *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data;
2200:   PetscBLASInt   bnz,one=1;
2201:   Mat_SeqAIJ     *x,*y;

2204:   if (str == SAME_NONZERO_PATTERN) {
2205:     PetscScalar alpha = a;
2206:     x    = (Mat_SeqAIJ*)xx->A->data;
2207:     PetscBLASIntCast(x->nz,&bnz);
2208:     y    = (Mat_SeqAIJ*)yy->A->data;
2209:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2210:     x    = (Mat_SeqAIJ*)xx->B->data;
2211:     y    = (Mat_SeqAIJ*)yy->B->data;
2212:     PetscBLASIntCast(x->nz,&bnz);
2213:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2214:     PetscObjectStateIncrease((PetscObject)Y);
2215:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2216:     MatAXPY_Basic(Y,a,X,str);
2217:   } else {
2218:     Mat      B;
2219:     PetscInt *nnz_d,*nnz_o;
2220:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
2221:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
2222:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
2223:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2224:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2225:     MatSetBlockSizesFromMats(B,Y,Y);
2226:     MatSetType(B,MATMPIAIJ);
2227:     MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);
2228:     MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
2229:     MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);
2230:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2231:     MatHeaderReplace(Y,B);
2232:     PetscFree(nnz_d);
2233:     PetscFree(nnz_o);
2234:   }
2235:   return(0);
2236: }

2238: extern PetscErrorCode  MatConjugate_SeqAIJ(Mat);

2242: PetscErrorCode  MatConjugate_MPIAIJ(Mat mat)
2243: {
2244: #if defined(PETSC_USE_COMPLEX)
2246:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2249:   MatConjugate_SeqAIJ(aij->A);
2250:   MatConjugate_SeqAIJ(aij->B);
2251: #else
2253: #endif
2254:   return(0);
2255: }

2259: PetscErrorCode MatRealPart_MPIAIJ(Mat A)
2260: {
2261:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2265:   MatRealPart(a->A);
2266:   MatRealPart(a->B);
2267:   return(0);
2268: }

2272: PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A)
2273: {
2274:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2278:   MatImaginaryPart(a->A);
2279:   MatImaginaryPart(a->B);
2280:   return(0);
2281: }

2283: #if defined(PETSC_HAVE_PBGL)

2285: #include <boost/parallel/mpi/bsp_process_group.hpp>
2286: #include <boost/graph/distributed/ilu_default_graph.hpp>
2287: #include <boost/graph/distributed/ilu_0_block.hpp>
2288: #include <boost/graph/distributed/ilu_preconditioner.hpp>
2289: #include <boost/graph/distributed/petsc/interface.hpp>
2290: #include <boost/multi_array.hpp>
2291: #include <boost/parallel/distributed_property_map.hpp>

2295: /*
2296:   This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu>
2297: */
2298: PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info)
2299: {
2300:   namespace petsc = boost::distributed::petsc;

2302:   namespace graph_dist = boost::graph::distributed;
2303:   using boost::graph::distributed::ilu_default::process_group_type;
2304:   using boost::graph::ilu_permuted;

2306:   PetscBool      row_identity, col_identity;
2307:   PetscContainer c;
2308:   PetscInt       m, n, M, N;

2312:   if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu");
2313:   ISIdentity(isrow, &row_identity);
2314:   ISIdentity(iscol, &col_identity);
2315:   if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU");

2317:   process_group_type pg;
2318:   typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type;
2319:   lgraph_type  *lgraph_p   = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg));
2320:   lgraph_type& level_graph = *lgraph_p;
2321:   graph_dist::ilu_default::graph_type&            graph(level_graph.graph);

2323:   petsc::read_matrix(A, graph, get(boost::edge_weight, graph));
2324:   ilu_permuted(level_graph);

2326:   /* put together the new matrix */
2327:   MatCreate(PetscObjectComm((PetscObject)A), fact);
2328:   MatGetLocalSize(A, &m, &n);
2329:   MatGetSize(A, &M, &N);
2330:   MatSetSizes(fact, m, n, M, N);
2331:   MatSetBlockSizesFromMats(fact,A,A);
2332:   MatSetType(fact, ((PetscObject)A)->type_name);
2333:   MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);
2334:   MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);

2336:   PetscContainerCreate(PetscObjectComm((PetscObject)A), &c);
2337:   PetscContainerSetPointer(c, lgraph_p);
2338:   PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c);
2339:   PetscContainerDestroy(&c);
2340:   return(0);
2341: }

2345: PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info)
2346: {
2348:   return(0);
2349: }

2353: /*
2354:   This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu>
2355: */
2356: PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x)
2357: {
2358:   namespace graph_dist = boost::graph::distributed;

2360:   typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type;
2361:   lgraph_type    *lgraph_p;
2362:   PetscContainer c;

2366:   PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);
2367:   PetscContainerGetPointer(c, (void**) &lgraph_p);
2368:   VecCopy(b, x);

2370:   PetscScalar *array_x;
2371:   VecGetArray(x, &array_x);
2372:   PetscInt sx;
2373:   VecGetSize(x, &sx);

2375:   PetscScalar *array_b;
2376:   VecGetArray(b, &array_b);
2377:   PetscInt sb;
2378:   VecGetSize(b, &sb);

2380:   lgraph_type& level_graph = *lgraph_p;
2381:   graph_dist::ilu_default::graph_type&            graph(level_graph.graph);

2383:   typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type;
2384:   array_ref_type                                 ref_b(array_b, boost::extents[num_vertices(graph)]);
2385:   array_ref_type                                 ref_x(array_x, boost::extents[num_vertices(graph)]);

2387:   typedef boost::iterator_property_map<array_ref_type::iterator,
2388:                                        boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type>  gvector_type;
2389:   gvector_type                                   vector_b(ref_b.begin(), get(boost::vertex_index, graph));
2390:   gvector_type                                   vector_x(ref_x.begin(), get(boost::vertex_index, graph));

2392:   ilu_set_solve(*lgraph_p, vector_b, vector_x);
2393:   return(0);
2394: }
2395: #endif

2399: PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2400: {
2401:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2403:   PetscInt       i,*idxb = 0;
2404:   PetscScalar    *va,*vb;
2405:   Vec            vtmp;

2408:   MatGetRowMaxAbs(a->A,v,idx);
2409:   VecGetArray(v,&va);
2410:   if (idx) {
2411:     for (i=0; i<A->rmap->n; i++) {
2412:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2413:     }
2414:   }

2416:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2417:   if (idx) {
2418:     PetscMalloc1(A->rmap->n,&idxb);
2419:   }
2420:   MatGetRowMaxAbs(a->B,vtmp,idxb);
2421:   VecGetArray(vtmp,&vb);

2423:   for (i=0; i<A->rmap->n; i++) {
2424:     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
2425:       va[i] = vb[i];
2426:       if (idx) idx[i] = a->garray[idxb[i]];
2427:     }
2428:   }

2430:   VecRestoreArray(v,&va);
2431:   VecRestoreArray(vtmp,&vb);
2432:   PetscFree(idxb);
2433:   VecDestroy(&vtmp);
2434:   return(0);
2435: }

2439: PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2440: {
2441:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2443:   PetscInt       i,*idxb = 0;
2444:   PetscScalar    *va,*vb;
2445:   Vec            vtmp;

2448:   MatGetRowMinAbs(a->A,v,idx);
2449:   VecGetArray(v,&va);
2450:   if (idx) {
2451:     for (i=0; i<A->cmap->n; i++) {
2452:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2453:     }
2454:   }

2456:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2457:   if (idx) {
2458:     PetscMalloc1(A->rmap->n,&idxb);
2459:   }
2460:   MatGetRowMinAbs(a->B,vtmp,idxb);
2461:   VecGetArray(vtmp,&vb);

2463:   for (i=0; i<A->rmap->n; i++) {
2464:     if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) {
2465:       va[i] = vb[i];
2466:       if (idx) idx[i] = a->garray[idxb[i]];
2467:     }
2468:   }

2470:   VecRestoreArray(v,&va);
2471:   VecRestoreArray(vtmp,&vb);
2472:   PetscFree(idxb);
2473:   VecDestroy(&vtmp);
2474:   return(0);
2475: }

2479: PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2480: {
2481:   Mat_MPIAIJ     *mat   = (Mat_MPIAIJ*) A->data;
2482:   PetscInt       n      = A->rmap->n;
2483:   PetscInt       cstart = A->cmap->rstart;
2484:   PetscInt       *cmap  = mat->garray;
2485:   PetscInt       *diagIdx, *offdiagIdx;
2486:   Vec            diagV, offdiagV;
2487:   PetscScalar    *a, *diagA, *offdiagA;
2488:   PetscInt       r;

2492:   PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2493:   VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);
2494:   VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);
2495:   MatGetRowMin(mat->A, diagV,    diagIdx);
2496:   MatGetRowMin(mat->B, offdiagV, offdiagIdx);
2497:   VecGetArray(v,        &a);
2498:   VecGetArray(diagV,    &diagA);
2499:   VecGetArray(offdiagV, &offdiagA);
2500:   for (r = 0; r < n; ++r) {
2501:     if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) {
2502:       a[r]   = diagA[r];
2503:       idx[r] = cstart + diagIdx[r];
2504:     } else {
2505:       a[r]   = offdiagA[r];
2506:       idx[r] = cmap[offdiagIdx[r]];
2507:     }
2508:   }
2509:   VecRestoreArray(v,        &a);
2510:   VecRestoreArray(diagV,    &diagA);
2511:   VecRestoreArray(offdiagV, &offdiagA);
2512:   VecDestroy(&diagV);
2513:   VecDestroy(&offdiagV);
2514:   PetscFree2(diagIdx, offdiagIdx);
2515:   return(0);
2516: }

2520: PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2521: {
2522:   Mat_MPIAIJ     *mat   = (Mat_MPIAIJ*) A->data;
2523:   PetscInt       n      = A->rmap->n;
2524:   PetscInt       cstart = A->cmap->rstart;
2525:   PetscInt       *cmap  = mat->garray;
2526:   PetscInt       *diagIdx, *offdiagIdx;
2527:   Vec            diagV, offdiagV;
2528:   PetscScalar    *a, *diagA, *offdiagA;
2529:   PetscInt       r;

2533:   PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2534:   VecCreateSeq(PETSC_COMM_SELF, n, &diagV);
2535:   VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);
2536:   MatGetRowMax(mat->A, diagV,    diagIdx);
2537:   MatGetRowMax(mat->B, offdiagV, offdiagIdx);
2538:   VecGetArray(v,        &a);
2539:   VecGetArray(diagV,    &diagA);
2540:   VecGetArray(offdiagV, &offdiagA);
2541:   for (r = 0; r < n; ++r) {
2542:     if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) {
2543:       a[r]   = diagA[r];
2544:       idx[r] = cstart + diagIdx[r];
2545:     } else {
2546:       a[r]   = offdiagA[r];
2547:       idx[r] = cmap[offdiagIdx[r]];
2548:     }
2549:   }
2550:   VecRestoreArray(v,        &a);
2551:   VecRestoreArray(diagV,    &diagA);
2552:   VecRestoreArray(offdiagV, &offdiagA);
2553:   VecDestroy(&diagV);
2554:   VecDestroy(&offdiagV);
2555:   PetscFree2(diagIdx, offdiagIdx);
2556:   return(0);
2557: }

2561: PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat)
2562: {
2564:   Mat            *dummy;

2567:   MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);
2568:   *newmat = *dummy;
2569:   PetscFree(dummy);
2570:   return(0);
2571: }

2575: PetscErrorCode  MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values)
2576: {
2577:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*) A->data;

2581:   MatInvertBlockDiagonal(a->A,values);
2582:   return(0);
2583: }

2587: static PetscErrorCode  MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx)
2588: {
2590:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)x->data;

2593:   MatSetRandom(aij->A,rctx);
2594:   MatSetRandom(aij->B,rctx);
2595:   MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
2596:   MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
2597:   return(0);
2598: }

2602: PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a)
2603: {
2605:   Mat_MPIAIJ     *maij = (Mat_MPIAIJ*)Y->data;
2606:   Mat_SeqAIJ     *aij = (Mat_SeqAIJ*)maij->A->data;

2609:   if (!Y->preallocated) {
2610:     MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);
2611:   } else if (!aij->nz) {
2612:     PetscInt nonew = aij->nonew;
2613:     MatSeqAIJSetPreallocation(maij->A,1,NULL);
2614:     aij->nonew = nonew;
2615:   }
2616:   MatShift_Basic(Y,a);
2617:   return(0);
2618: }

2620: /* -------------------------------------------------------------------*/
2621: static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ,
2622:                                        MatGetRow_MPIAIJ,
2623:                                        MatRestoreRow_MPIAIJ,
2624:                                        MatMult_MPIAIJ,
2625:                                 /* 4*/ MatMultAdd_MPIAIJ,
2626:                                        MatMultTranspose_MPIAIJ,
2627:                                        MatMultTransposeAdd_MPIAIJ,
2628: #if defined(PETSC_HAVE_PBGL)
2629:                                        MatSolve_MPIAIJ,
2630: #else
2631:                                        0,
2632: #endif
2633:                                        0,
2634:                                        0,
2635:                                 /*10*/ 0,
2636:                                        0,
2637:                                        0,
2638:                                        MatSOR_MPIAIJ,
2639:                                        MatTranspose_MPIAIJ,
2640:                                 /*15*/ MatGetInfo_MPIAIJ,
2641:                                        MatEqual_MPIAIJ,
2642:                                        MatGetDiagonal_MPIAIJ,
2643:                                        MatDiagonalScale_MPIAIJ,
2644:                                        MatNorm_MPIAIJ,
2645:                                 /*20*/ MatAssemblyBegin_MPIAIJ,
2646:                                        MatAssemblyEnd_MPIAIJ,
2647:                                        MatSetOption_MPIAIJ,
2648:                                        MatZeroEntries_MPIAIJ,
2649:                                 /*24*/ MatZeroRows_MPIAIJ,
2650:                                        0,
2651: #if defined(PETSC_HAVE_PBGL)
2652:                                        0,
2653: #else
2654:                                        0,
2655: #endif
2656:                                        0,
2657:                                        0,
2658:                                 /*29*/ MatSetUp_MPIAIJ,
2659: #if defined(PETSC_HAVE_PBGL)
2660:                                        0,
2661: #else
2662:                                        0,
2663: #endif
2664:                                        0,
2665:                                        0,
2666:                                        0,
2667:                                 /*34*/ MatDuplicate_MPIAIJ,
2668:                                        0,
2669:                                        0,
2670:                                        0,
2671:                                        0,
2672:                                 /*39*/ MatAXPY_MPIAIJ,
2673:                                        MatGetSubMatrices_MPIAIJ,
2674:                                        MatIncreaseOverlap_MPIAIJ,
2675:                                        MatGetValues_MPIAIJ,
2676:                                        MatCopy_MPIAIJ,
2677:                                 /*44*/ MatGetRowMax_MPIAIJ,
2678:                                        MatScale_MPIAIJ,
2679:                                        MatShift_MPIAIJ,
2680:                                        MatDiagonalSet_MPIAIJ,
2681:                                        MatZeroRowsColumns_MPIAIJ,
2682:                                 /*49*/ MatSetRandom_MPIAIJ,
2683:                                        0,
2684:                                        0,
2685:                                        0,
2686:                                        0,
2687:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
2688:                                        0,
2689:                                        MatSetUnfactored_MPIAIJ,
2690:                                        MatPermute_MPIAIJ,
2691:                                        0,
2692:                                 /*59*/ MatGetSubMatrix_MPIAIJ,
2693:                                        MatDestroy_MPIAIJ,
2694:                                        MatView_MPIAIJ,
2695:                                        0,
2696:                                        MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ,
2697:                                 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ,
2698:                                        MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ,
2699:                                        0,
2700:                                        0,
2701:                                        0,
2702:                                 /*69*/ MatGetRowMaxAbs_MPIAIJ,
2703:                                        MatGetRowMinAbs_MPIAIJ,
2704:                                        0,
2705:                                        MatSetColoring_MPIAIJ,
2706:                                        0,
2707:                                        MatSetValuesAdifor_MPIAIJ,
2708:                                 /*75*/ MatFDColoringApply_AIJ,
2709:                                        0,
2710:                                        0,
2711:                                        0,
2712:                                        MatFindZeroDiagonals_MPIAIJ,
2713:                                 /*80*/ 0,
2714:                                        0,
2715:                                        0,
2716:                                 /*83*/ MatLoad_MPIAIJ,
2717:                                        0,
2718:                                        0,
2719:                                        0,
2720:                                        0,
2721:                                        0,
2722:                                 /*89*/ MatMatMult_MPIAIJ_MPIAIJ,
2723:                                        MatMatMultSymbolic_MPIAIJ_MPIAIJ,
2724:                                        MatMatMultNumeric_MPIAIJ_MPIAIJ,
2725:                                        MatPtAP_MPIAIJ_MPIAIJ,
2726:                                        MatPtAPSymbolic_MPIAIJ_MPIAIJ,
2727:                                 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ,
2728:                                        0,
2729:                                        0,
2730:                                        0,
2731:                                        0,
2732:                                 /*99*/ 0,
2733:                                        0,
2734:                                        0,
2735:                                        MatConjugate_MPIAIJ,
2736:                                        0,
2737:                                 /*104*/MatSetValuesRow_MPIAIJ,
2738:                                        MatRealPart_MPIAIJ,
2739:                                        MatImaginaryPart_MPIAIJ,
2740:                                        0,
2741:                                        0,
2742:                                 /*109*/0,
2743:                                        0,
2744:                                        MatGetRowMin_MPIAIJ,
2745:                                        0,
2746:                                        0,
2747:                                 /*114*/MatGetSeqNonzeroStructure_MPIAIJ,
2748:                                        0,
2749:                                        MatGetGhosts_MPIAIJ,
2750:                                        0,
2751:                                        0,
2752:                                 /*119*/0,
2753:                                        0,
2754:                                        0,
2755:                                        0,
2756:                                        MatGetMultiProcBlock_MPIAIJ,
2757:                                 /*124*/MatFindNonzeroRows_MPIAIJ,
2758:                                        MatGetColumnNorms_MPIAIJ,
2759:                                        MatInvertBlockDiagonal_MPIAIJ,
2760:                                        0,
2761:                                        MatGetSubMatricesMPI_MPIAIJ,
2762:                                 /*129*/0,
2763:                                        MatTransposeMatMult_MPIAIJ_MPIAIJ,
2764:                                        MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ,
2765:                                        MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ,
2766:                                        0,
2767:                                 /*134*/0,
2768:                                        0,
2769:                                        0,
2770:                                        0,
2771:                                        0,
2772:                                 /*139*/0,
2773:                                        0,
2774:                                        0,
2775:                                        MatFDColoringSetUp_MPIXAIJ,
2776:                                        MatFindOffBlockDiagonalEntries_MPIAIJ,
2777:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ
2778: };

2780: /* ----------------------------------------------------------------------------------------*/

2784: PetscErrorCode  MatStoreValues_MPIAIJ(Mat mat)
2785: {
2786:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2790:   MatStoreValues(aij->A);
2791:   MatStoreValues(aij->B);
2792:   return(0);
2793: }

2797: PetscErrorCode  MatRetrieveValues_MPIAIJ(Mat mat)
2798: {
2799:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2803:   MatRetrieveValues(aij->A);
2804:   MatRetrieveValues(aij->B);
2805:   return(0);
2806: }

2810: PetscErrorCode  MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2811: {
2812:   Mat_MPIAIJ     *b;

2816:   PetscLayoutSetUp(B->rmap);
2817:   PetscLayoutSetUp(B->cmap);
2818:   b = (Mat_MPIAIJ*)B->data;

2820:   if (!B->preallocated) {
2821:     /* Explicitly create 2 MATSEQAIJ matrices. */
2822:     MatCreate(PETSC_COMM_SELF,&b->A);
2823:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2824:     MatSetBlockSizesFromMats(b->A,B,B);
2825:     MatSetType(b->A,MATSEQAIJ);
2826:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2827:     MatCreate(PETSC_COMM_SELF,&b->B);
2828:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
2829:     MatSetBlockSizesFromMats(b->B,B,B);
2830:     MatSetType(b->B,MATSEQAIJ);
2831:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
2832:   }

2834:   MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);
2835:   MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);
2836:   B->preallocated = PETSC_TRUE;
2837:   return(0);
2838: }

2842: PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2843: {
2844:   Mat            mat;
2845:   Mat_MPIAIJ     *a,*oldmat = (Mat_MPIAIJ*)matin->data;

2849:   *newmat = 0;
2850:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2851:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2852:   MatSetBlockSizesFromMats(mat,matin,matin);
2853:   MatSetType(mat,((PetscObject)matin)->type_name);
2854:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
2855:   a       = (Mat_MPIAIJ*)mat->data;

2857:   mat->factortype   = matin->factortype;
2858:   mat->assembled    = PETSC_TRUE;
2859:   mat->insertmode   = NOT_SET_VALUES;
2860:   mat->preallocated = PETSC_TRUE;

2862:   a->size         = oldmat->size;
2863:   a->rank         = oldmat->rank;
2864:   a->donotstash   = oldmat->donotstash;
2865:   a->roworiented  = oldmat->roworiented;
2866:   a->rowindices   = 0;
2867:   a->rowvalues    = 0;
2868:   a->getrowactive = PETSC_FALSE;

2870:   PetscLayoutReference(matin->rmap,&mat->rmap);
2871:   PetscLayoutReference(matin->cmap,&mat->cmap);

2873:   if (oldmat->colmap) {
2874: #if defined(PETSC_USE_CTABLE)
2875:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2876: #else
2877:     PetscMalloc1(mat->cmap->N,&a->colmap);
2878:     PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
2879:     PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));
2880: #endif
2881:   } else a->colmap = 0;
2882:   if (oldmat->garray) {
2883:     PetscInt len;
2884:     len  = oldmat->B->cmap->n;
2885:     PetscMalloc1(len+1,&a->garray);
2886:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2887:     if (len) { PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt)); }
2888:   } else a->garray = 0;

2890:   VecDuplicate(oldmat->lvec,&a->lvec);
2891:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2892:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2893:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
2894:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2895:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2896:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2897:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2898:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2899:   *newmat = mat;
2900:   return(0);
2901: }



2907: PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer)
2908: {
2909:   PetscScalar    *vals,*svals;
2910:   MPI_Comm       comm;
2912:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
2913:   PetscInt       i,nz,j,rstart,rend,mmax,maxnz = 0;
2914:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols;
2915:   PetscInt       *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols;
2916:   PetscInt       cend,cstart,n,*rowners;
2917:   int            fd;
2918:   PetscInt       bs = newMat->rmap->bs;

2921:   /* force binary viewer to load .info file if it has not yet done so */
2922:   PetscViewerSetUp(viewer);
2923:   PetscObjectGetComm((PetscObject)viewer,&comm);
2924:   MPI_Comm_size(comm,&size);
2925:   MPI_Comm_rank(comm,&rank);
2926:   PetscViewerBinaryGetDescriptor(viewer,&fd);
2927:   if (!rank) {
2928:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
2929:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2930:   }

2932:   PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");
2933:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2934:   PetscOptionsEnd();
2935:   if (bs < 0) bs = 1;

2937:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2938:   M    = header[1]; N = header[2];

2940:   /* If global sizes are set, check if they are consistent with that given in the file */
2941:   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);
2942:   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);

2944:   /* determine ownership of all (block) rows */
2945:   if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs);
2946:   if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank));    /* PETSC_DECIDE */
2947:   else m = newMat->rmap->n; /* Set by user */

2949:   PetscMalloc1(size+1,&rowners);
2950:   MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

2952:   /* First process needs enough room for process with most rows */
2953:   if (!rank) {
2954:     mmax = rowners[1];
2955:     for (i=2; i<=size; i++) {
2956:       mmax = PetscMax(mmax, rowners[i]);
2957:     }
2958:   } else mmax = -1;             /* unused, but compilers complain */

2960:   rowners[0] = 0;
2961:   for (i=2; i<=size; i++) {
2962:     rowners[i] += rowners[i-1];
2963:   }
2964:   rstart = rowners[rank];
2965:   rend   = rowners[rank+1];

2967:   /* distribute row lengths to all processors */
2968:   PetscMalloc2(m,&ourlens,m,&offlens);
2969:   if (!rank) {
2970:     PetscBinaryRead(fd,ourlens,m,PETSC_INT);
2971:     PetscMalloc1(mmax,&rowlengths);
2972:     PetscCalloc1(size,&procsnz);
2973:     for (j=0; j<m; j++) {
2974:       procsnz[0] += ourlens[j];
2975:     }
2976:     for (i=1; i<size; i++) {
2977:       PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);
2978:       /* calculate the number of nonzeros on each processor */
2979:       for (j=0; j<rowners[i+1]-rowners[i]; j++) {
2980:         procsnz[i] += rowlengths[j];
2981:       }
2982:       MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
2983:     }
2984:     PetscFree(rowlengths);
2985:   } else {
2986:     MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);
2987:   }

2989:   if (!rank) {
2990:     /* determine max buffer needed and allocate it */
2991:     maxnz = 0;
2992:     for (i=0; i<size; i++) {
2993:       maxnz = PetscMax(maxnz,procsnz[i]);
2994:     }
2995:     PetscMalloc1(maxnz,&cols);

2997:     /* read in my part of the matrix column indices  */
2998:     nz   = procsnz[0];
2999:     PetscMalloc1(nz,&mycols);
3000:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);

3002:     /* read in every one elses and ship off */
3003:     for (i=1; i<size; i++) {
3004:       nz   = procsnz[i];
3005:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
3006:       MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);
3007:     }
3008:     PetscFree(cols);
3009:   } else {
3010:     /* determine buffer space needed for message */
3011:     nz = 0;
3012:     for (i=0; i<m; i++) {
3013:       nz += ourlens[i];
3014:     }
3015:     PetscMalloc1(nz,&mycols);

3017:     /* receive message of column indices*/
3018:     MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);
3019:   }

3021:   /* determine column ownership if matrix is not square */
3022:   if (N != M) {
3023:     if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank);
3024:     else n = newMat->cmap->n;
3025:     MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);
3026:     cstart = cend - n;
3027:   } else {
3028:     cstart = rstart;
3029:     cend   = rend;
3030:     n      = cend - cstart;
3031:   }

3033:   /* loop over local rows, determining number of off diagonal entries */
3034:   PetscMemzero(offlens,m*sizeof(PetscInt));
3035:   jj   = 0;
3036:   for (i=0; i<m; i++) {
3037:     for (j=0; j<ourlens[i]; j++) {
3038:       if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++;
3039:       jj++;
3040:     }
3041:   }

3043:   for (i=0; i<m; i++) {
3044:     ourlens[i] -= offlens[i];
3045:   }
3046:   MatSetSizes(newMat,m,n,M,N);

3048:   if (bs > 1) {MatSetBlockSize(newMat,bs);}

3050:   MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);

3052:   for (i=0; i<m; i++) {
3053:     ourlens[i] += offlens[i];
3054:   }

3056:   if (!rank) {
3057:     PetscMalloc1(maxnz+1,&vals);

3059:     /* read in my part of the matrix numerical values  */
3060:     nz   = procsnz[0];
3061:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);

3063:     /* insert into matrix */
3064:     jj      = rstart;
3065:     smycols = mycols;
3066:     svals   = vals;
3067:     for (i=0; i<m; i++) {
3068:       MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3069:       smycols += ourlens[i];
3070:       svals   += ourlens[i];
3071:       jj++;
3072:     }

3074:     /* read in other processors and ship out */
3075:     for (i=1; i<size; i++) {
3076:       nz   = procsnz[i];
3077:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
3078:       MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);
3079:     }
3080:     PetscFree(procsnz);
3081:   } else {
3082:     /* receive numeric values */
3083:     PetscMalloc1(nz+1,&vals);

3085:     /* receive message of values*/
3086:     MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);

3088:     /* insert into matrix */
3089:     jj      = rstart;
3090:     smycols = mycols;
3091:     svals   = vals;
3092:     for (i=0; i<m; i++) {
3093:       MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3094:       smycols += ourlens[i];
3095:       svals   += ourlens[i];
3096:       jj++;
3097:     }
3098:   }
3099:   PetscFree2(ourlens,offlens);
3100:   PetscFree(vals);
3101:   PetscFree(mycols);
3102:   PetscFree(rowners);
3103:   MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);
3104:   MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);
3105:   return(0);
3106: }

3110: /* TODO: Not scalable because of ISAllGather(). */
3111: PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
3112: {
3114:   IS             iscol_local;
3115:   PetscInt       csize;

3118:   ISGetLocalSize(iscol,&csize);
3119:   if (call == MAT_REUSE_MATRIX) {
3120:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
3121:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3122:   } else {
3123:     PetscInt cbs;
3124:     ISGetBlockSize(iscol,&cbs);
3125:     ISAllGather(iscol,&iscol_local);
3126:     ISSetBlockSize(iscol_local,cbs);
3127:   }
3128:   MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
3129:   if (call == MAT_INITIAL_MATRIX) {
3130:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
3131:     ISDestroy(&iscol_local);
3132:   }
3133:   return(0);
3134: }

3136: extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*);
3139: /*
3140:     Not great since it makes two copies of the submatrix, first an SeqAIJ
3141:   in local and then by concatenating the local matrices the end result.
3142:   Writing it directly would be much like MatGetSubMatrices_MPIAIJ()

3144:   Note: This requires a sequential iscol with all indices.
3145: */
3146: PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
3147: {
3149:   PetscMPIInt    rank,size;
3150:   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs;
3151:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol;
3152:   PetscBool      allcolumns, colflag;
3153:   Mat            M,Mreuse;
3154:   MatScalar      *vwork,*aa;
3155:   MPI_Comm       comm;
3156:   Mat_SeqAIJ     *aij;

3159:   PetscObjectGetComm((PetscObject)mat,&comm);
3160:   MPI_Comm_rank(comm,&rank);
3161:   MPI_Comm_size(comm,&size);

3163:   ISIdentity(iscol,&colflag);
3164:   ISGetLocalSize(iscol,&ncol);
3165:   if (colflag && ncol == mat->cmap->N) {
3166:     allcolumns = PETSC_TRUE;
3167:   } else {
3168:     allcolumns = PETSC_FALSE;
3169:   }
3170:   if (call ==  MAT_REUSE_MATRIX) {
3171:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
3172:     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3173:     MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);
3174:   } else {
3175:     MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);
3176:   }

3178:   /*
3179:       m - number of local rows
3180:       n - number of columns (same on all processors)
3181:       rstart - first row in new global matrix generated
3182:   */
3183:   MatGetSize(Mreuse,&m,&n);
3184:   MatGetBlockSizes(Mreuse,&bs,&cbs);
3185:   if (call == MAT_INITIAL_MATRIX) {
3186:     aij = (Mat_SeqAIJ*)(Mreuse)->data;
3187:     ii  = aij->i;
3188:     jj  = aij->j;

3190:     /*
3191:         Determine the number of non-zeros in the diagonal and off-diagonal
3192:         portions of the matrix in order to do correct preallocation
3193:     */

3195:     /* first get start and end of "diagonal" columns */
3196:     if (csize == PETSC_DECIDE) {
3197:       ISGetSize(isrow,&mglobal);
3198:       if (mglobal == n) { /* square matrix */
3199:         nlocal = m;
3200:       } else {
3201:         nlocal = n/size + ((n % size) > rank);
3202:       }
3203:     } else {
3204:       nlocal = csize;
3205:     }
3206:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3207:     rstart = rend - nlocal;
3208:     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);

3210:     /* next, compute all the lengths */
3211:     PetscMalloc1(2*m+1,&dlens);
3212:     olens = dlens + m;
3213:     for (i=0; i<m; i++) {
3214:       jend = ii[i+1] - ii[i];
3215:       olen = 0;
3216:       dlen = 0;
3217:       for (j=0; j<jend; j++) {
3218:         if (*jj < rstart || *jj >= rend) olen++;
3219:         else dlen++;
3220:         jj++;
3221:       }
3222:       olens[i] = olen;
3223:       dlens[i] = dlen;
3224:     }
3225:     MatCreate(comm,&M);
3226:     MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);
3227:     MatSetBlockSizes(M,bs,cbs);
3228:     MatSetType(M,((PetscObject)mat)->type_name);
3229:     MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3230:     PetscFree(dlens);
3231:   } else {
3232:     PetscInt ml,nl;

3234:     M    = *newmat;
3235:     MatGetLocalSize(M,&ml,&nl);
3236:     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3237:     MatZeroEntries(M);
3238:     /*
3239:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3240:        rather than the slower MatSetValues().
3241:     */
3242:     M->was_assembled = PETSC_TRUE;
3243:     M->assembled     = PETSC_FALSE;
3244:   }
3245:   MatGetOwnershipRange(M,&rstart,&rend);
3246:   aij  = (Mat_SeqAIJ*)(Mreuse)->data;
3247:   ii   = aij->i;
3248:   jj   = aij->j;
3249:   aa   = aij->a;
3250:   for (i=0; i<m; i++) {
3251:     row   = rstart + i;
3252:     nz    = ii[i+1] - ii[i];
3253:     cwork = jj;     jj += nz;
3254:     vwork = aa;     aa += nz;
3255:     MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
3256:   }

3258:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3259:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3260:   *newmat = M;

3262:   /* save submatrix used in processor for next request */
3263:   if (call ==  MAT_INITIAL_MATRIX) {
3264:     PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
3265:     MatDestroy(&Mreuse);
3266:   }
3267:   return(0);
3268: }

3272: PetscErrorCode  MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
3273: {
3274:   PetscInt       m,cstart, cend,j,nnz,i,d;
3275:   PetscInt       *d_nnz,*o_nnz,nnz_max = 0,rstart,ii;
3276:   const PetscInt *JJ;
3277:   PetscScalar    *values;

3281:   if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]);

3283:   PetscLayoutSetUp(B->rmap);
3284:   PetscLayoutSetUp(B->cmap);
3285:   m      = B->rmap->n;
3286:   cstart = B->cmap->rstart;
3287:   cend   = B->cmap->rend;
3288:   rstart = B->rmap->rstart;

3290:   PetscMalloc2(m,&d_nnz,m,&o_nnz);

3292: #if defined(PETSC_USE_DEBUGGING)
3293:   for (i=0; i<m; i++) {
3294:     nnz = Ii[i+1]- Ii[i];
3295:     JJ  = J + Ii[i];
3296:     if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz);
3297:     if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j);
3298:     if (nnz && (JJ[nnz-1] >= B->cmap->N) SETERRRQ3(PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N);
3299:   }
3300: #endif

3302:   for (i=0; i<m; i++) {
3303:     nnz     = Ii[i+1]- Ii[i];
3304:     JJ      = J + Ii[i];
3305:     nnz_max = PetscMax(nnz_max,nnz);
3306:     d       = 0;
3307:     for (j=0; j<nnz; j++) {
3308:       if (cstart <= JJ[j] && JJ[j] < cend) d++;
3309:     }
3310:     d_nnz[i] = d;
3311:     o_nnz[i] = nnz - d;
3312:   }
3313:   MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
3314:   PetscFree2(d_nnz,o_nnz);

3316:   if (v) values = (PetscScalar*)v;
3317:   else {
3318:     PetscCalloc1(nnz_max+1,&values);
3319:   }

3321:   for (i=0; i<m; i++) {
3322:     ii   = i + rstart;
3323:     nnz  = Ii[i+1]- Ii[i];
3324:     MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);
3325:   }
3326:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3327:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

3329:   if (!v) {
3330:     PetscFree(values);
3331:   }
3332:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3333:   return(0);
3334: }

3338: /*@
3339:    MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format
3340:    (the default parallel PETSc format).

3342:    Collective on MPI_Comm

3344:    Input Parameters:
3345: +  B - the matrix
3346: .  i - the indices into j for the start of each local row (starts with zero)
3347: .  j - the column indices for each local row (starts with zero)
3348: -  v - optional values in the matrix

3350:    Level: developer

3352:    Notes:
3353:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3354:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
3355:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3357:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3359:        The format which is used for the sparse matrix input, is equivalent to a
3360:     row-major ordering.. i.e for the following matrix, the input data expected is
3361:     as shown:

3363:         1 0 0
3364:         2 0 3     P0
3365:        -------
3366:         4 5 6     P1

3368:      Process0 [P0]: rows_owned=[0,1]
3369:         i =  {0,1,3}  [size = nrow+1  = 2+1]
3370:         j =  {0,0,2}  [size = nz = 6]
3371:         v =  {1,2,3}  [size = nz = 6]

3373:      Process1 [P1]: rows_owned=[2]
3374:         i =  {0,3}    [size = nrow+1  = 1+1]
3375:         j =  {0,1,2}  [size = nz = 6]
3376:         v =  {4,5,6}  [size = nz = 6]

3378: .keywords: matrix, aij, compressed row, sparse, parallel

3380: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ,
3381:           MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays()
3382: @*/
3383: PetscErrorCode  MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3384: {

3388:   PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));
3389:   return(0);
3390: }

3394: /*@C
3395:    MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format
3396:    (the default parallel PETSc format).  For good matrix assembly performance
3397:    the user should preallocate the matrix storage by setting the parameters
3398:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3399:    performance can be increased by more than a factor of 50.

3401:    Collective on MPI_Comm

3403:    Input Parameters:
3404: +  B - the matrix
3405: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
3406:            (same value is used for all local rows)
3407: .  d_nnz - array containing the number of nonzeros in the various rows of the
3408:            DIAGONAL portion of the local submatrix (possibly different for each row)
3409:            or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
3410:            The size of this array is equal to the number of local rows, i.e 'm'.
3411:            For matrices that will be factored, you must leave room for (and set)
3412:            the diagonal entry even if it is zero.
3413: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
3414:            submatrix (same value is used for all local rows).
3415: -  o_nnz - array containing the number of nonzeros in the various rows of the
3416:            OFF-DIAGONAL portion of the local submatrix (possibly different for
3417:            each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
3418:            structure. The size of this array is equal to the number
3419:            of local rows, i.e 'm'.

3421:    If the *_nnz parameter is given then the *_nz parameter is ignored

3423:    The AIJ format (also called the Yale sparse matrix format or
3424:    compressed row storage (CSR)), is fully compatible with standard Fortran 77
3425:    storage.  The stored row and column indices begin with zero.
3426:    See Users-Manual: ch_mat for details.

3428:    The parallel matrix is partitioned such that the first m0 rows belong to
3429:    process 0, the next m1 rows belong to process 1, the next m2 rows belong
3430:    to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.

3432:    The DIAGONAL portion of the local submatrix of a processor can be defined
3433:    as the submatrix which is obtained by extraction the part corresponding to
3434:    the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
3435:    first row that belongs to the processor, r2 is the last row belonging to
3436:    the this processor, and c1-c2 is range of indices of the local part of a
3437:    vector suitable for applying the matrix to.  This is an mxn matrix.  In the
3438:    common case of a square matrix, the row and column ranges are the same and
3439:    the DIAGONAL part is also square. The remaining portion of the local
3440:    submatrix (mxN) constitute the OFF-DIAGONAL portion.

3442:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

3444:    You can call MatGetInfo() to get information on how effective the preallocation was;
3445:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3446:    You can also run with the option -info and look for messages with the string
3447:    malloc in them to see if additional memory allocation was needed.

3449:    Example usage:

3451:    Consider the following 8x8 matrix with 34 non-zero values, that is
3452:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
3453:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
3454:    as follows:

3456: .vb
3457:             1  2  0  |  0  3  0  |  0  4
3458:     Proc0   0  5  6  |  7  0  0  |  8  0
3459:             9  0 10  | 11  0  0  | 12  0
3460:     -------------------------------------
3461:            13  0 14  | 15 16 17  |  0  0
3462:     Proc1   0 18  0  | 19 20 21  |  0  0
3463:             0  0  0  | 22 23  0  | 24  0
3464:     -------------------------------------
3465:     Proc2  25 26 27  |  0  0 28  | 29  0
3466:            30  0  0  | 31 32 33  |  0 34
3467: .ve

3469:    This can be represented as a collection of submatrices as:

3471: .vb
3472:       A B C
3473:       D E F
3474:       G H I
3475: .ve

3477:    Where the submatrices A,B,C are owned by proc0, D,E,F are
3478:    owned by proc1, G,H,I are owned by proc2.

3480:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3481:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3482:    The 'M','N' parameters are 8,8, and have the same values on all procs.

3484:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
3485:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
3486:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
3487:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
3488:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
3489:    matrix, ans [DF] as another SeqAIJ matrix.

3491:    When d_nz, o_nz parameters are specified, d_nz storage elements are
3492:    allocated for every row of the local diagonal submatrix, and o_nz
3493:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
3494:    One way to choose d_nz and o_nz is to use the max nonzerors per local
3495:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
3496:    In this case, the values of d_nz,o_nz are:
3497: .vb
3498:      proc0 : dnz = 2, o_nz = 2
3499:      proc1 : dnz = 3, o_nz = 2
3500:      proc2 : dnz = 1, o_nz = 4
3501: .ve
3502:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
3503:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
3504:    for proc3. i.e we are using 12+15+10=37 storage locations to store
3505:    34 values.

3507:    When d_nnz, o_nnz parameters are specified, the storage is specified
3508:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
3509:    In the above case the values for d_nnz,o_nnz are:
3510: .vb
3511:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
3512:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
3513:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
3514: .ve
3515:    Here the space allocated is sum of all the above values i.e 34, and
3516:    hence pre-allocation is perfect.

3518:    Level: intermediate

3520: .keywords: matrix, aij, compressed row, sparse, parallel

3522: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(),
3523:           MPIAIJ, MatGetInfo(), PetscSplitOwnership()
3524: @*/
3525: PetscErrorCode  MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
3526: {

3532:   PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
3533:   return(0);
3534: }

3538: /*@
3539:      MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard
3540:          CSR format the local rows.

3542:    Collective on MPI_Comm

3544:    Input Parameters:
3545: +  comm - MPI communicator
3546: .  m - number of local rows (Cannot be PETSC_DECIDE)
3547: .  n - This value should be the same as the local size used in creating the
3548:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3549:        calculated if N is given) For square matrices n is almost always m.
3550: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3551: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3552: .   i - row indices
3553: .   j - column indices
3554: -   a - matrix values

3556:    Output Parameter:
3557: .   mat - the matrix

3559:    Level: intermediate

3561:    Notes:
3562:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3563:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
3564:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3566:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3568:        The format which is used for the sparse matrix input, is equivalent to a
3569:     row-major ordering.. i.e for the following matrix, the input data expected is
3570:     as shown:

3572:         1 0 0
3573:         2 0 3     P0
3574:        -------
3575:         4 5 6     P1

3577:      Process0 [P0]: rows_owned=[0,1]
3578:         i =  {0,1,3}  [size = nrow+1  = 2+1]
3579:         j =  {0,0,2}  [size = nz = 6]
3580:         v =  {1,2,3}  [size = nz = 6]

3582:      Process1 [P1]: rows_owned=[2]
3583:         i =  {0,3}    [size = nrow+1  = 1+1]
3584:         j =  {0,1,2}  [size = nz = 6]
3585:         v =  {4,5,6}  [size = nz = 6]

3587: .keywords: matrix, aij, compressed row, sparse, parallel

3589: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3590:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
3591: @*/
3592: PetscErrorCode  MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
3593: {

3597:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3598:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
3599:   MatCreate(comm,mat);
3600:   MatSetSizes(*mat,m,n,M,N);
3601:   /* MatSetBlockSizes(M,bs,cbs); */
3602:   MatSetType(*mat,MATMPIAIJ);
3603:   MatMPIAIJSetPreallocationCSR(*mat,i,j,a);
3604:   return(0);
3605: }

3609: /*@C
3610:    MatCreateAIJ - Creates a sparse parallel matrix in AIJ format
3611:    (the default parallel PETSc format).  For good matrix assembly performance
3612:    the user should preallocate the matrix storage by setting the parameters
3613:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3614:    performance can be increased by more than a factor of 50.

3616:    Collective on MPI_Comm

3618:    Input Parameters:
3619: +  comm - MPI communicator
3620: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
3621:            This value should be the same as the local size used in creating the
3622:            y vector for the matrix-vector product y = Ax.
3623: .  n - This value should be the same as the local size used in creating the
3624:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3625:        calculated if N is given) For square matrices n is almost always m.
3626: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3627: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3628: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
3629:            (same value is used for all local rows)
3630: .  d_nnz - array containing the number of nonzeros in the various rows of the
3631:            DIAGONAL portion of the local submatrix (possibly different for each row)
3632:            or NULL, if d_nz is used to specify the nonzero structure.
3633:            The size of this array is equal to the number of local rows, i.e 'm'.
3634: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
3635:            submatrix (same value is used for all local rows).
3636: -  o_nnz - array containing the number of nonzeros in the various rows of the
3637:            OFF-DIAGONAL portion of the local submatrix (possibly different for
3638:            each row) or NULL, if o_nz is used to specify the nonzero
3639:            structure. The size of this array is equal to the number
3640:            of local rows, i.e 'm'.

3642:    Output Parameter:
3643: .  A - the matrix

3645:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
3646:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
3647:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

3649:    Notes:
3650:    If the *_nnz parameter is given then the *_nz parameter is ignored

3652:    m,n,M,N parameters specify the size of the matrix, and its partitioning across
3653:    processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
3654:    storage requirements for this matrix.

3656:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one
3657:    processor than it must be used on all processors that share the object for
3658:    that argument.

3660:    The user MUST specify either the local or global matrix dimensions
3661:    (possibly both).

3663:    The parallel matrix is partitioned across processors such that the
3664:    first m0 rows belong to process 0, the next m1 rows belong to
3665:    process 1, the next m2 rows belong to process 2 etc.. where
3666:    m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
3667:    values corresponding to [m x N] submatrix.

3669:    The columns are logically partitioned with the n0 columns belonging
3670:    to 0th partition, the next n1 columns belonging to the next
3671:    partition etc.. where n0,n1,n2... are the input parameter 'n'.

3673:    The DIAGONAL portion of the local submatrix on any given processor
3674:    is the submatrix corresponding to the rows and columns m,n
3675:    corresponding to the given processor. i.e diagonal matrix on
3676:    process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
3677:    etc. The remaining portion of the local submatrix [m x (N-n)]
3678:    constitute the OFF-DIAGONAL portion. The example below better
3679:    illustrates this concept.

3681:    For a square global matrix we define each processor's diagonal portion
3682:    to be its local rows and the corresponding columns (a square submatrix);
3683:    each processor's off-diagonal portion encompasses the remainder of the
3684:    local matrix (a rectangular submatrix).

3686:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

3688:    When calling this routine with a single process communicator, a matrix of
3689:    type SEQAIJ is returned.  If a matrix of type MPIAIJ is desired for this
3690:    type of communicator, use the construction mechanism:
3691:      MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...);

3693:    By default, this format uses inodes (identical nodes) when possible.
3694:    We search for consecutive rows with the same nonzero structure, thereby
3695:    reusing matrix information to achieve increased efficiency.

3697:    Options Database Keys:
3698: +  -mat_no_inode  - Do not use inodes
3699: .  -mat_inode_limit <limit> - Sets inode limit (max limit=5)
3700: -  -mat_aij_oneindex - Internally use indexing starting at 1
3701:         rather than 0.  Note that when calling MatSetValues(),
3702:         the user still MUST index entries starting at 0!


3705:    Example usage:

3707:    Consider the following 8x8 matrix with 34 non-zero values, that is
3708:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
3709:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
3710:    as follows:

3712: .vb
3713:             1  2  0  |  0  3  0  |  0  4
3714:     Proc0   0  5  6  |  7  0  0  |  8  0
3715:             9  0 10  | 11  0  0  | 12  0
3716:     -------------------------------------
3717:            13  0 14  | 15 16 17  |  0  0
3718:     Proc1   0 18  0  | 19 20 21  |  0  0
3719:             0  0  0  | 22 23  0  | 24  0
3720:     -------------------------------------
3721:     Proc2  25 26 27  |  0  0 28  | 29  0
3722:            30  0  0  | 31 32 33  |  0 34
3723: .ve

3725:    This can be represented as a collection of submatrices as:

3727: .vb
3728:       A B C
3729:       D E F
3730:       G H I
3731: .ve

3733:    Where the submatrices A,B,C are owned by proc0, D,E,F are
3734:    owned by proc1, G,H,I are owned by proc2.

3736:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3737:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3738:    The 'M','N' parameters are 8,8, and have the same values on all procs.

3740:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
3741:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
3742:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
3743:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
3744:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
3745:    matrix, ans [DF] as another SeqAIJ matrix.

3747:    When d_nz, o_nz parameters are specified, d_nz storage elements are
3748:    allocated for every row of the local diagonal submatrix, and o_nz
3749:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
3750:    One way to choose d_nz and o_nz is to use the max nonzerors per local
3751:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
3752:    In this case, the values of d_nz,o_nz are:
3753: .vb
3754:      proc0 : dnz = 2, o_nz = 2
3755:      proc1 : dnz = 3, o_nz = 2
3756:      proc2 : dnz = 1, o_nz = 4
3757: .ve
3758:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
3759:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
3760:    for proc3. i.e we are using 12+15+10=37 storage locations to store
3761:    34 values.

3763:    When d_nnz, o_nnz parameters are specified, the storage is specified
3764:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
3765:    In the above case the values for d_nnz,o_nnz are:
3766: .vb
3767:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
3768:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
3769:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
3770: .ve
3771:    Here the space allocated is sum of all the above values i.e 34, and
3772:    hence pre-allocation is perfect.

3774:    Level: intermediate

3776: .keywords: matrix, aij, compressed row, sparse, parallel

3778: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3779:           MPIAIJ, MatCreateMPIAIJWithArrays()
3780: @*/
3781: 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)
3782: {
3784:   PetscMPIInt    size;

3787:   MatCreate(comm,A);
3788:   MatSetSizes(*A,m,n,M,N);
3789:   MPI_Comm_size(comm,&size);
3790:   if (size > 1) {
3791:     MatSetType(*A,MATMPIAIJ);
3792:     MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
3793:   } else {
3794:     MatSetType(*A,MATSEQAIJ);
3795:     MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
3796:   }
3797:   return(0);
3798: }

3802: PetscErrorCode  MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
3803: {
3804:   Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;

3807:   if (Ad)     *Ad     = a->A;
3808:   if (Ao)     *Ao     = a->B;
3809:   if (colmap) *colmap = a->garray;
3810:   return(0);
3811: }

3815: PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring)
3816: {
3818:   PetscInt       i;
3819:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

3822:   if (coloring->ctype == IS_COLORING_GLOBAL) {
3823:     ISColoringValue *allcolors,*colors;
3824:     ISColoring      ocoloring;

3826:     /* set coloring for diagonal portion */
3827:     MatSetColoring_SeqAIJ(a->A,coloring);

3829:     /* set coloring for off-diagonal portion */
3830:     ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);
3831:     PetscMalloc1(a->B->cmap->n+1,&colors);
3832:     for (i=0; i<a->B->cmap->n; i++) {
3833:       colors[i] = allcolors[a->garray[i]];
3834:     }
3835:     PetscFree(allcolors);
3836:     ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);
3837:     MatSetColoring_SeqAIJ(a->B,ocoloring);
3838:     ISColoringDestroy(&ocoloring);
3839:   } else if (coloring->ctype == IS_COLORING_GHOSTED) {
3840:     ISColoringValue *colors;
3841:     PetscInt        *larray;
3842:     ISColoring      ocoloring;

3844:     /* set coloring for diagonal portion */
3845:     PetscMalloc1(a->A->cmap->n+1,&larray);
3846:     for (i=0; i<a->A->cmap->n; i++) {
3847:       larray[i] = i + A->cmap->rstart;
3848:     }
3849:     ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);
3850:     PetscMalloc1(a->A->cmap->n+1,&colors);
3851:     for (i=0; i<a->A->cmap->n; i++) {
3852:       colors[i] = coloring->colors[larray[i]];
3853:     }
3854:     PetscFree(larray);
3855:     ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);
3856:     MatSetColoring_SeqAIJ(a->A,ocoloring);
3857:     ISColoringDestroy(&ocoloring);

3859:     /* set coloring for off-diagonal portion */
3860:     PetscMalloc1(a->B->cmap->n+1,&larray);
3861:     ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);
3862:     PetscMalloc1(a->B->cmap->n+1,&colors);
3863:     for (i=0; i<a->B->cmap->n; i++) {
3864:       colors[i] = coloring->colors[larray[i]];
3865:     }
3866:     PetscFree(larray);
3867:     ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);
3868:     MatSetColoring_SeqAIJ(a->B,ocoloring);
3869:     ISColoringDestroy(&ocoloring);
3870:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype);
3871:   return(0);
3872: }

3876: PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues)
3877: {
3878:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

3882:   MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);
3883:   MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);
3884:   return(0);
3885: }

3889: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
3890: {
3892:   PetscInt       m,N,i,rstart,nnz,Ii;
3893:   PetscInt       *indx;
3894:   PetscScalar    *values;

3897:   MatGetSize(inmat,&m,&N);
3898:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
3899:     PetscInt       *dnz,*onz,sum,bs,cbs;

3901:     if (n == PETSC_DECIDE) {
3902:       PetscSplitOwnership(comm,&n,&N);
3903:     }
3904:     /* Check sum(n) = N */
3905:     MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
3906:     if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N);

3908:     MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);
3909:     rstart -= m;

3911:     MatPreallocateInitialize(comm,m,n,dnz,onz);
3912:     for (i=0; i<m; i++) {
3913:       MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
3914:       MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);
3915:       MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
3916:     }

3918:     MatCreate(comm,outmat);
3919:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
3920:     MatGetBlockSizes(inmat,&bs,&cbs);
3921:     MatSetBlockSizes(*outmat,bs,cbs);
3922:     MatSetType(*outmat,MATMPIAIJ);
3923:     MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);
3924:     MatPreallocateFinalize(dnz,onz);
3925:   }

3927:   /* numeric phase */
3928:   MatGetOwnershipRange(*outmat,&rstart,NULL);
3929:   for (i=0; i<m; i++) {
3930:     MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
3931:     Ii   = i + rstart;
3932:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
3933:     MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
3934:   }
3935:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
3936:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
3937:   return(0);
3938: }

3942: PetscErrorCode MatFileSplit(Mat A,char *outfile)
3943: {
3944:   PetscErrorCode    ierr;
3945:   PetscMPIInt       rank;
3946:   PetscInt          m,N,i,rstart,nnz;
3947:   size_t            len;
3948:   const PetscInt    *indx;
3949:   PetscViewer       out;
3950:   char              *name;
3951:   Mat               B;
3952:   const PetscScalar *values;

3955:   MatGetLocalSize(A,&m,0);
3956:   MatGetSize(A,0,&N);
3957:   /* Should this be the type of the diagonal block of A? */
3958:   MatCreate(PETSC_COMM_SELF,&B);
3959:   MatSetSizes(B,m,N,m,N);
3960:   MatSetBlockSizesFromMats(B,A,A);
3961:   MatSetType(B,MATSEQAIJ);
3962:   MatSeqAIJSetPreallocation(B,0,NULL);
3963:   MatGetOwnershipRange(A,&rstart,0);
3964:   for (i=0; i<m; i++) {
3965:     MatGetRow(A,i+rstart,&nnz,&indx,&values);
3966:     MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);
3967:     MatRestoreRow(A,i+rstart,&nnz,&indx,&values);
3968:   }
3969:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3970:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

3972:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
3973:   PetscStrlen(outfile,&len);
3974:   PetscMalloc1(len+5,&name);
3975:   sprintf(name,"%s.%d",outfile,rank);
3976:   PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);
3977:   PetscFree(name);
3978:   MatView(B,out);
3979:   PetscViewerDestroy(&out);
3980:   MatDestroy(&B);
3981:   return(0);
3982: }

3984: extern PetscErrorCode MatDestroy_MPIAIJ(Mat);
3987: PetscErrorCode  MatDestroy_MPIAIJ_SeqsToMPI(Mat A)
3988: {
3989:   PetscErrorCode      ierr;
3990:   Mat_Merge_SeqsToMPI *merge;
3991:   PetscContainer      container;

3994:   PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);
3995:   if (container) {
3996:     PetscContainerGetPointer(container,(void**)&merge);
3997:     PetscFree(merge->id_r);
3998:     PetscFree(merge->len_s);
3999:     PetscFree(merge->len_r);
4000:     PetscFree(merge->bi);
4001:     PetscFree(merge->bj);
4002:     PetscFree(merge->buf_ri[0]);
4003:     PetscFree(merge->buf_ri);
4004:     PetscFree(merge->buf_rj[0]);
4005:     PetscFree(merge->buf_rj);
4006:     PetscFree(merge->coi);
4007:     PetscFree(merge->coj);
4008:     PetscFree(merge->owners_co);
4009:     PetscLayoutDestroy(&merge->rowmap);
4010:     PetscFree(merge);
4011:     PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);
4012:   }
4013:   MatDestroy_MPIAIJ(A);
4014:   return(0);
4015: }

4017: #include <../src/mat/utils/freespace.h>
4018: #include <petscbt.h>

4022: PetscErrorCode  MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat)
4023: {
4024:   PetscErrorCode      ierr;
4025:   MPI_Comm            comm;
4026:   Mat_SeqAIJ          *a  =(Mat_SeqAIJ*)seqmat->data;
4027:   PetscMPIInt         size,rank,taga,*len_s;
4028:   PetscInt            N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj;
4029:   PetscInt            proc,m;
4030:   PetscInt            **buf_ri,**buf_rj;
4031:   PetscInt            k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj;
4032:   PetscInt            nrows,**buf_ri_k,**nextrow,**nextai;
4033:   MPI_Request         *s_waits,*r_waits;
4034:   MPI_Status          *status;
4035:   MatScalar           *aa=a->a;
4036:   MatScalar           **abuf_r,*ba_i;
4037:   Mat_Merge_SeqsToMPI *merge;
4038:   PetscContainer      container;

4041:   PetscObjectGetComm((PetscObject)mpimat,&comm);
4042:   PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);

4044:   MPI_Comm_size(comm,&size);
4045:   MPI_Comm_rank(comm,&rank);

4047:   PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);
4048:   PetscContainerGetPointer(container,(void**)&merge);

4050:   bi     = merge->bi;
4051:   bj     = merge->bj;
4052:   buf_ri = merge->buf_ri;
4053:   buf_rj = merge->buf_rj;

4055:   PetscMalloc1(size,&status);
4056:   owners = merge->rowmap->range;
4057:   len_s  = merge->len_s;

4059:   /* send and recv matrix values */
4060:   /*-----------------------------*/
4061:   PetscObjectGetNewTag((PetscObject)mpimat,&taga);
4062:   PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);

4064:   PetscMalloc1(merge->nsend+1,&s_waits);
4065:   for (proc=0,k=0; proc<size; proc++) {
4066:     if (!len_s[proc]) continue;
4067:     i    = owners[proc];
4068:     MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);
4069:     k++;
4070:   }

4072:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,r_waits,status);}
4073:   if (merge->nsend) {MPI_Waitall(merge->nsend,s_waits,status);}
4074:   PetscFree(status);

4076:   PetscFree(s_waits);
4077:   PetscFree(r_waits);

4079:   /* insert mat values of mpimat */
4080:   /*----------------------------*/
4081:   PetscMalloc1(N,&ba_i);
4082:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

4084:   for (k=0; k<merge->nrecv; k++) {
4085:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4086:     nrows       = *(buf_ri_k[k]);
4087:     nextrow[k]  = buf_ri_k[k]+1;  /* next row number of k-th recved i-structure */
4088:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
4089:   }

4091:   /* set values of ba */
4092:   m = merge->rowmap->n;
4093:   for (i=0; i<m; i++) {
4094:     arow = owners[rank] + i;
4095:     bj_i = bj+bi[i];  /* col indices of the i-th row of mpimat */
4096:     bnzi = bi[i+1] - bi[i];
4097:     PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));

4099:     /* add local non-zero vals of this proc's seqmat into ba */
4100:     anzi   = ai[arow+1] - ai[arow];
4101:     aj     = a->j + ai[arow];
4102:     aa     = a->a + ai[arow];
4103:     nextaj = 0;
4104:     for (j=0; nextaj<anzi; j++) {
4105:       if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4106:         ba_i[j] += aa[nextaj++];
4107:       }
4108:     }

4110:     /* add received vals into ba */
4111:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4112:       /* i-th row */
4113:       if (i == *nextrow[k]) {
4114:         anzi   = *(nextai[k]+1) - *nextai[k];
4115:         aj     = buf_rj[k] + *(nextai[k]);
4116:         aa     = abuf_r[k] + *(nextai[k]);
4117:         nextaj = 0;
4118:         for (j=0; nextaj<anzi; j++) {
4119:           if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4120:             ba_i[j] += aa[nextaj++];
4121:           }
4122:         }
4123:         nextrow[k]++; nextai[k]++;
4124:       }
4125:     }
4126:     MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);
4127:   }
4128:   MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);
4129:   MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);

4131:   PetscFree(abuf_r[0]);
4132:   PetscFree(abuf_r);
4133:   PetscFree(ba_i);
4134:   PetscFree3(buf_ri_k,nextrow,nextai);
4135:   PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);
4136:   return(0);
4137: }

4139: extern PetscErrorCode  MatDestroy_MPIAIJ_SeqsToMPI(Mat);

4143: PetscErrorCode  MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat)
4144: {
4145:   PetscErrorCode      ierr;
4146:   Mat                 B_mpi;
4147:   Mat_SeqAIJ          *a=(Mat_SeqAIJ*)seqmat->data;
4148:   PetscMPIInt         size,rank,tagi,tagj,*len_s,*len_si,*len_ri;
4149:   PetscInt            **buf_rj,**buf_ri,**buf_ri_k;
4150:   PetscInt            M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j;
4151:   PetscInt            len,proc,*dnz,*onz,bs,cbs;
4152:   PetscInt            k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0;
4153:   PetscInt            nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai;
4154:   MPI_Request         *si_waits,*sj_waits,*ri_waits,*rj_waits;
4155:   MPI_Status          *status;
4156:   PetscFreeSpaceList  free_space=NULL,current_space=NULL;
4157:   PetscBT             lnkbt;
4158:   Mat_Merge_SeqsToMPI *merge;
4159:   PetscContainer      container;

4162:   PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);

4164:   /* make sure it is a PETSc comm */
4165:   PetscCommDuplicate(comm,&comm,NULL);
4166:   MPI_Comm_size(comm,&size);
4167:   MPI_Comm_rank(comm,&rank);

4169:   PetscNew(&merge);
4170:   PetscMalloc1(size,&status);

4172:   /* determine row ownership */
4173:   /*---------------------------------------------------------*/
4174:   PetscLayoutCreate(comm,&merge->rowmap);
4175:   PetscLayoutSetLocalSize(merge->rowmap,m);
4176:   PetscLayoutSetSize(merge->rowmap,M);
4177:   PetscLayoutSetBlockSize(merge->rowmap,1);
4178:   PetscLayoutSetUp(merge->rowmap);
4179:   PetscMalloc1(size,&len_si);
4180:   PetscMalloc1(size,&merge->len_s);

4182:   m      = merge->rowmap->n;
4183:   owners = merge->rowmap->range;

4185:   /* determine the number of messages to send, their lengths */
4186:   /*---------------------------------------------------------*/
4187:   len_s = merge->len_s;

4189:   len          = 0; /* length of buf_si[] */
4190:   merge->nsend = 0;
4191:   for (proc=0; proc<size; proc++) {
4192:     len_si[proc] = 0;
4193:     if (proc == rank) {
4194:       len_s[proc] = 0;
4195:     } else {
4196:       len_si[proc] = owners[proc+1] - owners[proc] + 1;
4197:       len_s[proc]  = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */
4198:     }
4199:     if (len_s[proc]) {
4200:       merge->nsend++;
4201:       nrows = 0;
4202:       for (i=owners[proc]; i<owners[proc+1]; i++) {
4203:         if (ai[i+1] > ai[i]) nrows++;
4204:       }
4205:       len_si[proc] = 2*(nrows+1);
4206:       len         += len_si[proc];
4207:     }
4208:   }

4210:   /* determine the number and length of messages to receive for ij-structure */
4211:   /*-------------------------------------------------------------------------*/
4212:   PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);
4213:   PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);

4215:   /* post the Irecv of j-structure */
4216:   /*-------------------------------*/
4217:   PetscCommGetNewTag(comm,&tagj);
4218:   PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);

4220:   /* post the Isend of j-structure */
4221:   /*--------------------------------*/
4222:   PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);

4224:   for (proc=0, k=0; proc<size; proc++) {
4225:     if (!len_s[proc]) continue;
4226:     i    = owners[proc];
4227:     MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);
4228:     k++;
4229:   }

4231:   /* receives and sends of j-structure are complete */
4232:   /*------------------------------------------------*/
4233:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,rj_waits,status);}
4234:   if (merge->nsend) {MPI_Waitall(merge->nsend,sj_waits,status);}

4236:   /* send and recv i-structure */
4237:   /*---------------------------*/
4238:   PetscCommGetNewTag(comm,&tagi);
4239:   PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);

4241:   PetscMalloc1(len+1,&buf_s);
4242:   buf_si = buf_s;  /* points to the beginning of k-th msg to be sent */
4243:   for (proc=0,k=0; proc<size; proc++) {
4244:     if (!len_s[proc]) continue;
4245:     /* form outgoing message for i-structure:
4246:          buf_si[0]:                 nrows to be sent
4247:                [1:nrows]:           row index (global)
4248:                [nrows+1:2*nrows+1]: i-structure index
4249:     */
4250:     /*-------------------------------------------*/
4251:     nrows       = len_si[proc]/2 - 1;
4252:     buf_si_i    = buf_si + nrows+1;
4253:     buf_si[0]   = nrows;
4254:     buf_si_i[0] = 0;
4255:     nrows       = 0;
4256:     for (i=owners[proc]; i<owners[proc+1]; i++) {
4257:       anzi = ai[i+1] - ai[i];
4258:       if (anzi) {
4259:         buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */
4260:         buf_si[nrows+1]   = i-owners[proc]; /* local row index */
4261:         nrows++;
4262:       }
4263:     }
4264:     MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);
4265:     k++;
4266:     buf_si += len_si[proc];
4267:   }

4269:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,ri_waits,status);}
4270:   if (merge->nsend) {MPI_Waitall(merge->nsend,si_waits,status);}

4272:   PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);
4273:   for (i=0; i<merge->nrecv; i++) {
4274:     PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);
4275:   }

4277:   PetscFree(len_si);
4278:   PetscFree(len_ri);
4279:   PetscFree(rj_waits);
4280:   PetscFree2(si_waits,sj_waits);
4281:   PetscFree(ri_waits);
4282:   PetscFree(buf_s);
4283:   PetscFree(status);

4285:   /* compute a local seq matrix in each processor */
4286:   /*----------------------------------------------*/
4287:   /* allocate bi array and free space for accumulating nonzero column info */
4288:   PetscMalloc1(m+1,&bi);
4289:   bi[0] = 0;

4291:   /* create and initialize a linked list */
4292:   nlnk = N+1;
4293:   PetscLLCreate(N,N,nlnk,lnk,lnkbt);

4295:   /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */
4296:   len  = ai[owners[rank+1]] - ai[owners[rank]];
4297:   PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);

4299:   current_space = free_space;

4301:   /* determine symbolic info for each local row */
4302:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

4304:   for (k=0; k<merge->nrecv; k++) {
4305:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4306:     nrows       = *buf_ri_k[k];
4307:     nextrow[k]  = buf_ri_k[k] + 1;  /* next row number of k-th recved i-structure */
4308:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
4309:   }

4311:   MatPreallocateInitialize(comm,m,n,dnz,onz);
4312:   len  = 0;
4313:   for (i=0; i<m; i++) {
4314:     bnzi = 0;
4315:     /* add local non-zero cols of this proc's seqmat into lnk */
4316:     arow  = owners[rank] + i;
4317:     anzi  = ai[arow+1] - ai[arow];
4318:     aj    = a->j + ai[arow];
4319:     PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4320:     bnzi += nlnk;
4321:     /* add received col data into lnk */
4322:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4323:       if (i == *nextrow[k]) { /* i-th row */
4324:         anzi  = *(nextai[k]+1) - *nextai[k];
4325:         aj    = buf_rj[k] + *nextai[k];
4326:         PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4327:         bnzi += nlnk;
4328:         nextrow[k]++; nextai[k]++;
4329:       }
4330:     }
4331:     if (len < bnzi) len = bnzi;  /* =max(bnzi) */

4333:     /* if free space is not available, make more free space */
4334:     if (current_space->local_remaining<bnzi) {
4335:       PetscFreeSpaceGet(bnzi+current_space->total_array_size,&current_space);
4336:       nspacedouble++;
4337:     }
4338:     /* copy data into free space, then initialize lnk */
4339:     PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);
4340:     MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);

4342:     current_space->array           += bnzi;
4343:     current_space->local_used      += bnzi;
4344:     current_space->local_remaining -= bnzi;

4346:     bi[i+1] = bi[i] + bnzi;
4347:   }

4349:   PetscFree3(buf_ri_k,nextrow,nextai);

4351:   PetscMalloc1(bi[m]+1,&bj);
4352:   PetscFreeSpaceContiguous(&free_space,bj);
4353:   PetscLLDestroy(lnk,lnkbt);

4355:   /* create symbolic parallel matrix B_mpi */
4356:   /*---------------------------------------*/
4357:   MatGetBlockSizes(seqmat,&bs,&cbs);
4358:   MatCreate(comm,&B_mpi);
4359:   if (n==PETSC_DECIDE) {
4360:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);
4361:   } else {
4362:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4363:   }
4364:   MatSetBlockSizes(B_mpi,bs,cbs);
4365:   MatSetType(B_mpi,MATMPIAIJ);
4366:   MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);
4367:   MatPreallocateFinalize(dnz,onz);
4368:   MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);

4370:   /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */
4371:   B_mpi->assembled    = PETSC_FALSE;
4372:   B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI;
4373:   merge->bi           = bi;
4374:   merge->bj           = bj;
4375:   merge->buf_ri       = buf_ri;
4376:   merge->buf_rj       = buf_rj;
4377:   merge->coi          = NULL;
4378:   merge->coj          = NULL;
4379:   merge->owners_co    = NULL;

4381:   PetscCommDestroy(&comm);

4383:   /* attach the supporting struct to B_mpi for reuse */
4384:   PetscContainerCreate(PETSC_COMM_SELF,&container);
4385:   PetscContainerSetPointer(container,merge);
4386:   PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);
4387:   PetscContainerDestroy(&container);
4388:   *mpimat = B_mpi;

4390:   PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);
4391:   return(0);
4392: }

4396: /*@C
4397:       MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential
4398:                  matrices from each processor

4400:     Collective on MPI_Comm

4402:    Input Parameters:
4403: +    comm - the communicators the parallel matrix will live on
4404: .    seqmat - the input sequential matrices
4405: .    m - number of local rows (or PETSC_DECIDE)
4406: .    n - number of local columns (or PETSC_DECIDE)
4407: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

4409:    Output Parameter:
4410: .    mpimat - the parallel matrix generated

4412:     Level: advanced

4414:    Notes:
4415:      The dimensions of the sequential matrix in each processor MUST be the same.
4416:      The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be
4417:      destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat.
4418: @*/
4419: PetscErrorCode  MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat)
4420: {
4422:   PetscMPIInt    size;

4425:   MPI_Comm_size(comm,&size);
4426:   if (size == 1) {
4427:     PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4428:     if (scall == MAT_INITIAL_MATRIX) {
4429:       MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);
4430:     } else {
4431:       MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);
4432:     }
4433:     PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4434:     return(0);
4435:   }
4436:   PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4437:   if (scall == MAT_INITIAL_MATRIX) {
4438:     MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);
4439:   }
4440:   MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);
4441:   PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4442:   return(0);
4443: }

4447: /*@
4448:      MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with
4449:           mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained
4450:           with MatGetSize()

4452:     Not Collective

4454:    Input Parameters:
4455: +    A - the matrix
4456: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

4458:    Output Parameter:
4459: .    A_loc - the local sequential matrix generated

4461:     Level: developer

4463: .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed()

4465: @*/
4466: PetscErrorCode  MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc)
4467: {
4469:   Mat_MPIAIJ     *mpimat=(Mat_MPIAIJ*)A->data;
4470:   Mat_SeqAIJ     *mat,*a,*b;
4471:   PetscInt       *ai,*aj,*bi,*bj,*cmap=mpimat->garray;
4472:   MatScalar      *aa,*ba,*cam;
4473:   PetscScalar    *ca;
4474:   PetscInt       am=A->rmap->n,i,j,k,cstart=A->cmap->rstart;
4475:   PetscInt       *ci,*cj,col,ncols_d,ncols_o,jo;
4476:   PetscBool      match;
4477:   MPI_Comm       comm;
4478:   PetscMPIInt    size;

4481:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
4482:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input");
4483:   PetscObjectGetComm((PetscObject)A,&comm);
4484:   MPI_Comm_size(comm,&size);
4485:   if (size == 1 && scall == MAT_REUSE_MATRIX) return(0);

4487:   PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);
4488:   a = (Mat_SeqAIJ*)(mpimat->A)->data;
4489:   b = (Mat_SeqAIJ*)(mpimat->B)->data;
4490:   ai = a->i; aj = a->j; bi = b->i; bj = b->j;
4491:   aa = a->a; ba = b->a;
4492:   if (scall == MAT_INITIAL_MATRIX) {
4493:     if (size == 1) {
4494:       MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);
4495:       return(0);
4496:     }

4498:     PetscMalloc1(1+am,&ci);
4499:     ci[0] = 0;
4500:     for (i=0; i<am; i++) {
4501:       ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]);
4502:     }
4503:     PetscMalloc1(1+ci[am],&cj);
4504:     PetscMalloc1(1+ci[am],&ca);
4505:     k    = 0;
4506:     for (i=0; i<am; i++) {
4507:       ncols_o = bi[i+1] - bi[i];
4508:       ncols_d = ai[i+1] - ai[i];
4509:       /* off-diagonal portion of A */
4510:       for (jo=0; jo<ncols_o; jo++) {
4511:         col = cmap[*bj];
4512:         if (col >= cstart) break;
4513:         cj[k]   = col; bj++;
4514:         ca[k++] = *ba++;
4515:       }
4516:       /* diagonal portion of A */
4517:       for (j=0; j<ncols_d; j++) {
4518:         cj[k]   = cstart + *aj++;
4519:         ca[k++] = *aa++;
4520:       }
4521:       /* off-diagonal portion of A */
4522:       for (j=jo; j<ncols_o; j++) {
4523:         cj[k]   = cmap[*bj++];
4524:         ca[k++] = *ba++;
4525:       }
4526:     }
4527:     /* put together the new matrix */
4528:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);
4529:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
4530:     /* Since these are PETSc arrays, change flags to free them as necessary. */
4531:     mat          = (Mat_SeqAIJ*)(*A_loc)->data;
4532:     mat->free_a  = PETSC_TRUE;
4533:     mat->free_ij = PETSC_TRUE;
4534:     mat->nonew   = 0;
4535:   } else if (scall == MAT_REUSE_MATRIX) {
4536:     mat=(Mat_SeqAIJ*)(*A_loc)->data;
4537:     ci = mat->i; cj = mat->j; cam = mat->a;
4538:     for (i=0; i<am; i++) {
4539:       /* off-diagonal portion of A */
4540:       ncols_o = bi[i+1] - bi[i];
4541:       for (jo=0; jo<ncols_o; jo++) {
4542:         col = cmap[*bj];
4543:         if (col >= cstart) break;
4544:         *cam++ = *ba++; bj++;
4545:       }
4546:       /* diagonal portion of A */
4547:       ncols_d = ai[i+1] - ai[i];
4548:       for (j=0; j<ncols_d; j++) *cam++ = *aa++;
4549:       /* off-diagonal portion of A */
4550:       for (j=jo; j<ncols_o; j++) {
4551:         *cam++ = *ba++; bj++;
4552:       }
4553:     }
4554:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
4555:   PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);
4556:   return(0);
4557: }

4561: /*@C
4562:      MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns

4564:     Not Collective

4566:    Input Parameters:
4567: +    A - the matrix
4568: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4569: -    row, col - index sets of rows and columns to extract (or NULL)

4571:    Output Parameter:
4572: .    A_loc - the local sequential matrix generated

4574:     Level: developer

4576: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat()

4578: @*/
4579: PetscErrorCode  MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
4580: {
4581:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
4583:   PetscInt       i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
4584:   IS             isrowa,iscola;
4585:   Mat            *aloc;
4586:   PetscBool      match;

4589:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
4590:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input");
4591:   PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
4592:   if (!row) {
4593:     start = A->rmap->rstart; end = A->rmap->rend;
4594:     ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
4595:   } else {
4596:     isrowa = *row;
4597:   }
4598:   if (!col) {
4599:     start = A->cmap->rstart;
4600:     cmap  = a->garray;
4601:     nzA   = a->A->cmap->n;
4602:     nzB   = a->B->cmap->n;
4603:     PetscMalloc1(nzA+nzB, &idx);
4604:     ncols = 0;
4605:     for (i=0; i<nzB; i++) {
4606:       if (cmap[i] < start) idx[ncols++] = cmap[i];
4607:       else break;
4608:     }
4609:     imark = i;
4610:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;
4611:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
4612:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
4613:   } else {
4614:     iscola = *col;
4615:   }
4616:   if (scall != MAT_INITIAL_MATRIX) {
4617:     PetscMalloc1(1,&aloc);
4618:     aloc[0] = *A_loc;
4619:   }
4620:   MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
4621:   *A_loc = aloc[0];
4622:   PetscFree(aloc);
4623:   if (!row) {
4624:     ISDestroy(&isrowa);
4625:   }
4626:   if (!col) {
4627:     ISDestroy(&iscola);
4628:   }
4629:   PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
4630:   return(0);
4631: }

4635: /*@C
4636:     MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A

4638:     Collective on Mat

4640:    Input Parameters:
4641: +    A,B - the matrices in mpiaij format
4642: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
4643: -    rowb, colb - index sets of rows and columns of B to extract (or NULL)

4645:    Output Parameter:
4646: +    rowb, colb - index sets of rows and columns of B to extract
4647: -    B_seq - the sequential matrix generated

4649:     Level: developer

4651: @*/
4652: PetscErrorCode  MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq)
4653: {
4654:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
4656:   PetscInt       *idx,i,start,ncols,nzA,nzB,*cmap,imark;
4657:   IS             isrowb,iscolb;
4658:   Mat            *bseq=NULL;

4661:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
4662:     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);
4663:   }
4664:   PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);

4666:   if (scall == MAT_INITIAL_MATRIX) {
4667:     start = A->cmap->rstart;
4668:     cmap  = a->garray;
4669:     nzA   = a->A->cmap->n;
4670:     nzB   = a->B->cmap->n;
4671:     PetscMalloc1(nzA+nzB, &idx);
4672:     ncols = 0;
4673:     for (i=0; i<nzB; i++) {  /* row < local row index */
4674:       if (cmap[i] < start) idx[ncols++] = cmap[i];
4675:       else break;
4676:     }
4677:     imark = i;
4678:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;  /* local rows */
4679:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */
4680:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);
4681:     ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);
4682:   } else {
4683:     if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX");
4684:     isrowb  = *rowb; iscolb = *colb;
4685:     PetscMalloc1(1,&bseq);
4686:     bseq[0] = *B_seq;
4687:   }
4688:   MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);
4689:   *B_seq = bseq[0];
4690:   PetscFree(bseq);
4691:   if (!rowb) {
4692:     ISDestroy(&isrowb);
4693:   } else {
4694:     *rowb = isrowb;
4695:   }
4696:   if (!colb) {
4697:     ISDestroy(&iscolb);
4698:   } else {
4699:     *colb = iscolb;
4700:   }
4701:   PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);
4702:   return(0);
4703: }

4707: /*
4708:     MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns
4709:     of the OFF-DIAGONAL portion of local A

4711:     Collective on Mat

4713:    Input Parameters:
4714: +    A,B - the matrices in mpiaij format
4715: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

4717:    Output Parameter:
4718: +    startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL)
4719: .    startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL)
4720: .    bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL)
4721: -    B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N

4723:     Level: developer

4725: */
4726: PetscErrorCode  MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth)
4727: {
4728:   VecScatter_MPI_General *gen_to,*gen_from;
4729:   PetscErrorCode         ierr;
4730:   Mat_MPIAIJ             *a=(Mat_MPIAIJ*)A->data;
4731:   Mat_SeqAIJ             *b_oth;
4732:   VecScatter             ctx =a->Mvctx;
4733:   MPI_Comm               comm;
4734:   PetscMPIInt            *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank;
4735:   PetscInt               *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj;
4736:   PetscScalar            *rvalues,*svalues;
4737:   MatScalar              *b_otha,*bufa,*bufA;
4738:   PetscInt               i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len;
4739:   MPI_Request            *rwaits = NULL,*swaits = NULL;
4740:   MPI_Status             *sstatus,rstatus;
4741:   PetscMPIInt            jj,size;
4742:   PetscInt               *cols,sbs,rbs;
4743:   PetscScalar            *vals;

4746:   PetscObjectGetComm((PetscObject)A,&comm);
4747:   MPI_Comm_size(comm,&size);

4749:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
4750:     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);
4751:   }
4752:   PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);
4753:   MPI_Comm_rank(comm,&rank);

4755:   gen_to   = (VecScatter_MPI_General*)ctx->todata;
4756:   gen_from = (VecScatter_MPI_General*)ctx->fromdata;
4757:   rvalues  = gen_from->values; /* holds the length of receiving row */
4758:   svalues  = gen_to->values;   /* holds the length of sending row */
4759:   nrecvs   = gen_from->n;
4760:   nsends   = gen_to->n;

4762:   PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);
4763:   srow    = gen_to->indices;    /* local row index to be sent */
4764:   sstarts = gen_to->starts;
4765:   sprocs  = gen_to->procs;
4766:   sstatus = gen_to->sstatus;
4767:   sbs     = gen_to->bs;
4768:   rstarts = gen_from->starts;
4769:   rprocs  = gen_from->procs;
4770:   rbs     = gen_from->bs;

4772:   if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX;
4773:   if (scall == MAT_INITIAL_MATRIX) {
4774:     /* i-array */
4775:     /*---------*/
4776:     /*  post receives */
4777:     for (i=0; i<nrecvs; i++) {
4778:       rowlen = (PetscInt*)rvalues + rstarts[i]*rbs;
4779:       nrows  = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */
4780:       MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
4781:     }

4783:     /* pack the outgoing message */
4784:     PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);

4786:     sstartsj[0] = 0;
4787:     rstartsj[0] = 0;
4788:     len         = 0; /* total length of j or a array to be sent */
4789:     k           = 0;
4790:     for (i=0; i<nsends; i++) {
4791:       rowlen = (PetscInt*)svalues + sstarts[i]*sbs;
4792:       nrows  = sstarts[i+1]-sstarts[i]; /* num of block rows */
4793:       for (j=0; j<nrows; j++) {
4794:         row = srow[k] + B->rmap->range[rank]; /* global row idx */
4795:         for (l=0; l<sbs; l++) {
4796:           MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL); /* rowlength */

4798:           rowlen[j*sbs+l] = ncols;

4800:           len += ncols;
4801:           MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);
4802:         }
4803:         k++;
4804:       }
4805:       MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);

4807:       sstartsj[i+1] = len;  /* starting point of (i+1)-th outgoing msg in bufj and bufa */
4808:     }
4809:     /* recvs and sends of i-array are completed */
4810:     i = nrecvs;
4811:     while (i--) {
4812:       MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
4813:     }
4814:     if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}

4816:     /* allocate buffers for sending j and a arrays */
4817:     PetscMalloc1(len+1,&bufj);
4818:     PetscMalloc1(len+1,&bufa);

4820:     /* create i-array of B_oth */
4821:     PetscMalloc1(aBn+2,&b_othi);

4823:     b_othi[0] = 0;
4824:     len       = 0; /* total length of j or a array to be received */
4825:     k         = 0;
4826:     for (i=0; i<nrecvs; i++) {
4827:       rowlen = (PetscInt*)rvalues + rstarts[i]*rbs;
4828:       nrows  = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */
4829:       for (j=0; j<nrows; j++) {
4830:         b_othi[k+1] = b_othi[k] + rowlen[j];
4831:         len        += rowlen[j]; k++;
4832:       }
4833:       rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */
4834:     }

4836:     /* allocate space for j and a arrrays of B_oth */
4837:     PetscMalloc1(b_othi[aBn]+1,&b_othj);
4838:     PetscMalloc1(b_othi[aBn]+1,&b_otha);

4840:     /* j-array */
4841:     /*---------*/
4842:     /*  post receives of j-array */
4843:     for (i=0; i<nrecvs; i++) {
4844:       nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
4845:       MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
4846:     }

4848:     /* pack the outgoing message j-array */
4849:     k = 0;
4850:     for (i=0; i<nsends; i++) {
4851:       nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
4852:       bufJ  = bufj+sstartsj[i];
4853:       for (j=0; j<nrows; j++) {
4854:         row = srow[k++] + B->rmap->range[rank];  /* global row idx */
4855:         for (ll=0; ll<sbs; ll++) {
4856:           MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
4857:           for (l=0; l<ncols; l++) {
4858:             *bufJ++ = cols[l];
4859:           }
4860:           MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
4861:         }
4862:       }
4863:       MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);
4864:     }

4866:     /* recvs and sends of j-array are completed */
4867:     i = nrecvs;
4868:     while (i--) {
4869:       MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
4870:     }
4871:     if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
4872:   } else if (scall == MAT_REUSE_MATRIX) {
4873:     sstartsj = *startsj_s;
4874:     rstartsj = *startsj_r;
4875:     bufa     = *bufa_ptr;
4876:     b_oth    = (Mat_SeqAIJ*)(*B_oth)->data;
4877:     b_otha   = b_oth->a;
4878:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container");

4880:   /* a-array */
4881:   /*---------*/
4882:   /*  post receives of a-array */
4883:   for (i=0; i<nrecvs; i++) {
4884:     nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
4885:     MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);
4886:   }

4888:   /* pack the outgoing message a-array */
4889:   k = 0;
4890:   for (i=0; i<nsends; i++) {
4891:     nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
4892:     bufA  = bufa+sstartsj[i];
4893:     for (j=0; j<nrows; j++) {
4894:       row = srow[k++] + B->rmap->range[rank];  /* global row idx */
4895:       for (ll=0; ll<sbs; ll++) {
4896:         MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
4897:         for (l=0; l<ncols; l++) {
4898:           *bufA++ = vals[l];
4899:         }
4900:         MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
4901:       }
4902:     }
4903:     MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);
4904:   }
4905:   /* recvs and sends of a-array are completed */
4906:   i = nrecvs;
4907:   while (i--) {
4908:     MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
4909:   }
4910:   if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
4911:   PetscFree2(rwaits,swaits);

4913:   if (scall == MAT_INITIAL_MATRIX) {
4914:     /* put together the new matrix */
4915:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);

4917:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
4918:     /* Since these are PETSc arrays, change flags to free them as necessary. */
4919:     b_oth          = (Mat_SeqAIJ*)(*B_oth)->data;
4920:     b_oth->free_a  = PETSC_TRUE;
4921:     b_oth->free_ij = PETSC_TRUE;
4922:     b_oth->nonew   = 0;

4924:     PetscFree(bufj);
4925:     if (!startsj_s || !bufa_ptr) {
4926:       PetscFree2(sstartsj,rstartsj);
4927:       PetscFree(bufa_ptr);
4928:     } else {
4929:       *startsj_s = sstartsj;
4930:       *startsj_r = rstartsj;
4931:       *bufa_ptr  = bufa;
4932:     }
4933:   }
4934:   PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);
4935:   return(0);
4936: }

4940: /*@C
4941:   MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication.

4943:   Not Collective

4945:   Input Parameters:
4946: . A - The matrix in mpiaij format

4948:   Output Parameter:
4949: + lvec - The local vector holding off-process values from the argument to a matrix-vector product
4950: . colmap - A map from global column index to local index into lvec
4951: - multScatter - A scatter from the argument of a matrix-vector product to lvec

4953:   Level: developer

4955: @*/
4956: #if defined(PETSC_USE_CTABLE)
4957: PetscErrorCode  MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter)
4958: #else
4959: PetscErrorCode  MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter)
4960: #endif
4961: {
4962:   Mat_MPIAIJ *a;

4969:   a = (Mat_MPIAIJ*) A->data;
4970:   if (lvec) *lvec = a->lvec;
4971:   if (colmap) *colmap = a->colmap;
4972:   if (multScatter) *multScatter = a->Mvctx;
4973:   return(0);
4974: }

4976: PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*);
4977: PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*);
4978: PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*);
4979: #if defined(PETSC_HAVE_ELEMENTAL)
4980: PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
4981: #endif

4985: /*
4986:     Computes (B'*A')' since computing B*A directly is untenable

4988:                n                       p                          p
4989:         (              )       (              )         (                  )
4990:       m (      A       )  *  n (       B      )   =   m (         C        )
4991:         (              )       (              )         (                  )

4993: */
4994: PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C)
4995: {
4997:   Mat            At,Bt,Ct;

5000:   MatTranspose(A,MAT_INITIAL_MATRIX,&At);
5001:   MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);
5002:   MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);
5003:   MatDestroy(&At);
5004:   MatDestroy(&Bt);
5005:   MatTranspose(Ct,MAT_REUSE_MATRIX,&C);
5006:   MatDestroy(&Ct);
5007:   return(0);
5008: }

5012: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
5013: {
5015:   PetscInt       m=A->rmap->n,n=B->cmap->n;
5016:   Mat            Cmat;

5019:   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);
5020:   MatCreate(PetscObjectComm((PetscObject)A),&Cmat);
5021:   MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
5022:   MatSetBlockSizesFromMats(Cmat,A,B);
5023:   MatSetType(Cmat,MATMPIDENSE);
5024:   MatMPIDenseSetPreallocation(Cmat,NULL);
5025:   MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);
5026:   MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);

5028:   Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ;

5030:   *C = Cmat;
5031:   return(0);
5032: }

5034: /* ----------------------------------------------------------------*/
5037: PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
5038: {

5042:   if (scall == MAT_INITIAL_MATRIX) {
5043:     PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);
5044:     MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);
5045:     PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);
5046:   }
5047:   PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);
5048:   MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);
5049:   PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);
5050:   return(0);
5051: }

5053: /*MC
5054:    MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices.

5056:    Options Database Keys:
5057: . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions()

5059:   Level: beginner

5061: .seealso: MatCreateAIJ()
5062: M*/

5066: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B)
5067: {
5068:   Mat_MPIAIJ     *b;
5070:   PetscMPIInt    size;

5073:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);

5075:   PetscNewLog(B,&b);
5076:   B->data       = (void*)b;
5077:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
5078:   B->assembled  = PETSC_FALSE;
5079:   B->insertmode = NOT_SET_VALUES;
5080:   b->size       = size;

5082:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);

5084:   /* build cache for off array entries formed */
5085:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

5087:   b->donotstash  = PETSC_FALSE;
5088:   b->colmap      = 0;
5089:   b->garray      = 0;
5090:   b->roworiented = PETSC_TRUE;

5092:   /* stuff used for matrix vector multiply */
5093:   b->lvec  = NULL;
5094:   b->Mvctx = NULL;

5096:   /* stuff for MatGetRow() */
5097:   b->rowindices   = 0;
5098:   b->rowvalues    = 0;
5099:   b->getrowactive = PETSC_FALSE;

5101:   /* flexible pointer used in CUSP/CUSPARSE classes */
5102:   b->spptr = NULL;

5104:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);
5105:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);
5106:   PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);
5107:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);
5108:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);
5109:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);
5110:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);
5111:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);
5112:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);
5113:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);
5114: #if defined(PETSC_HAVE_ELEMENTAL)
5115:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);
5116: #endif
5117:   PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);
5118:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);
5119:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);
5120:   PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);
5121:   return(0);
5122: }

5126: /*@C
5127:      MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal"
5128:          and "off-diagonal" part of the matrix in CSR format.

5130:    Collective on MPI_Comm

5132:    Input Parameters:
5133: +  comm - MPI communicator
5134: .  m - number of local rows (Cannot be PETSC_DECIDE)
5135: .  n - This value should be the same as the local size used in creating the
5136:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
5137:        calculated if N is given) For square matrices n is almost always m.
5138: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
5139: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
5140: .   i - row indices for "diagonal" portion of matrix
5141: .   j - column indices
5142: .   a - matrix values
5143: .   oi - row indices for "off-diagonal" portion of matrix
5144: .   oj - column indices
5145: -   oa - matrix values

5147:    Output Parameter:
5148: .   mat - the matrix

5150:    Level: advanced

5152:    Notes:
5153:        The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user
5154:        must free the arrays once the matrix has been destroyed and not before.

5156:        The i and j indices are 0 based

5158:        See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix

5160:        This sets local rows and cannot be used to set off-processor values.

5162:        Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a
5163:        legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does
5164:        not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because
5165:        the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to
5166:        keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all
5167:        communication if it is known that only local entries will be set.

5169: .keywords: matrix, aij, compressed row, sparse, parallel

5171: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
5172:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays()
5173: @*/
5174: 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)
5175: {
5177:   Mat_MPIAIJ     *maij;

5180:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
5181:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
5182:   if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0");
5183:   MatCreate(comm,mat);
5184:   MatSetSizes(*mat,m,n,M,N);
5185:   MatSetType(*mat,MATMPIAIJ);
5186:   maij = (Mat_MPIAIJ*) (*mat)->data;

5188:   (*mat)->preallocated = PETSC_TRUE;

5190:   PetscLayoutSetUp((*mat)->rmap);
5191:   PetscLayoutSetUp((*mat)->cmap);

5193:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);
5194:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);

5196:   MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);
5197:   MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);
5198:   MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);
5199:   MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);

5201:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
5202:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
5203:   MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
5204:   return(0);
5205: }

5207: /*
5208:     Special version for direct calls from Fortran
5209: */
5210: #include <petsc/private/fortranimpl.h>

5212: #if defined(PETSC_HAVE_FORTRAN_CAPS)
5213: #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ
5214: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
5215: #define matsetvaluesmpiaij_ matsetvaluesmpiaij
5216: #endif

5218: /* Change these macros so can be used in void function */
5219: #undef CHKERRQ
5220: #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr)
5221: #undef SETERRQ2
5222: #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr)
5223: #undef SETERRQ3
5224: #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr)
5225: #undef SETERRQ
5226: #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr)

5230: 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)
5231: {
5232:   Mat            mat  = *mmat;
5233:   PetscInt       m    = *mm, n = *mn;
5234:   InsertMode     addv = *maddv;
5235:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
5236:   PetscScalar    value;

5239:   MatCheckPreallocated(mat,1);
5240:   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;

5242: #if defined(PETSC_USE_DEBUG)
5243:   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
5244: #endif
5245:   {
5246:     PetscInt  i,j,rstart  = mat->rmap->rstart,rend = mat->rmap->rend;
5247:     PetscInt  cstart      = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
5248:     PetscBool roworiented = aij->roworiented;

5250:     /* Some Variables required in the macro */
5251:     Mat        A                 = aij->A;
5252:     Mat_SeqAIJ *a                = (Mat_SeqAIJ*)A->data;
5253:     PetscInt   *aimax            = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
5254:     MatScalar  *aa               = a->a;
5255:     PetscBool  ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE);
5256:     Mat        B                 = aij->B;
5257:     Mat_SeqAIJ *b                = (Mat_SeqAIJ*)B->data;
5258:     PetscInt   *bimax            = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
5259:     MatScalar  *ba               = b->a;

5261:     PetscInt  *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
5262:     PetscInt  nonew = a->nonew;
5263:     MatScalar *ap1,*ap2;

5266:     for (i=0; i<m; i++) {
5267:       if (im[i] < 0) continue;
5268: #if defined(PETSC_USE_DEBUG)
5269:       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);
5270: #endif
5271:       if (im[i] >= rstart && im[i] < rend) {
5272:         row      = im[i] - rstart;
5273:         lastcol1 = -1;
5274:         rp1      = aj + ai[row];
5275:         ap1      = aa + ai[row];
5276:         rmax1    = aimax[row];
5277:         nrow1    = ailen[row];
5278:         low1     = 0;
5279:         high1    = nrow1;
5280:         lastcol2 = -1;
5281:         rp2      = bj + bi[row];
5282:         ap2      = ba + bi[row];
5283:         rmax2    = bimax[row];
5284:         nrow2    = bilen[row];
5285:         low2     = 0;
5286:         high2    = nrow2;

5288:         for (j=0; j<n; j++) {
5289:           if (roworiented) value = v[i*n+j];
5290:           else value = v[i+j*m];
5291:           if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue;
5292:           if (in[j] >= cstart && in[j] < cend) {
5293:             col = in[j] - cstart;
5294:             MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
5295:           } else if (in[j] < 0) continue;
5296: #if defined(PETSC_USE_DEBUG)
5297:           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);
5298: #endif
5299:           else {
5300:             if (mat->was_assembled) {
5301:               if (!aij->colmap) {
5302:                 MatCreateColmap_MPIAIJ_Private(mat);
5303:               }
5304: #if defined(PETSC_USE_CTABLE)
5305:               PetscTableFind(aij->colmap,in[j]+1,&col);
5306:               col--;
5307: #else
5308:               col = aij->colmap[in[j]] - 1;
5309: #endif
5310:               if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
5311:                 MatDisAssemble_MPIAIJ(mat);
5312:                 col  =  in[j];
5313:                 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
5314:                 B     = aij->B;
5315:                 b     = (Mat_SeqAIJ*)B->data;
5316:                 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
5317:                 rp2   = bj + bi[row];
5318:                 ap2   = ba + bi[row];
5319:                 rmax2 = bimax[row];
5320:                 nrow2 = bilen[row];
5321:                 low2  = 0;
5322:                 high2 = nrow2;
5323:                 bm    = aij->B->rmap->n;
5324:                 ba    = b->a;
5325:               }
5326:             } else col = in[j];
5327:             MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
5328:           }
5329:         }
5330:       } else if (!aij->donotstash) {
5331:         if (roworiented) {
5332:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5333:         } else {
5334:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
5335:         }
5336:       }
5337:     }
5338:   }
5339:   PetscFunctionReturnVoid();
5340: }