Actual source code: mpiaij.c

petsc-3.13.2 2020-06-02
Report Typos and Errors
  1:  #include <../src/mat/impls/aij/mpi/mpiaij.h>
  2:  #include <petsc/private/vecimpl.h>
  3:  #include <petsc/private/vecscatterimpl.h>
  4:  #include <petsc/private/isimpl.h>
  5:  #include <petscblaslapack.h>
  6:  #include <petscsf.h>
  7:  #include <petsc/private/hashmapi.h>

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

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

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

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

 25:   Level: beginner

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

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

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

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

 42:   Level: beginner

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

 47: static PetscErrorCode MatBindToCPU_MPIAIJ(Mat A,PetscBool flg)
 48: {
 49:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

 53: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL)
 54:   A->boundtocpu = flg;
 55: #endif
 56:   if (a->A) {
 57:     MatBindToCPU(a->A,flg);
 58:   }
 59:   if (a->B) {
 60:     MatBindToCPU(a->B,flg);
 61:   }
 62:   return(0);
 63: }


 66: PetscErrorCode MatSetBlockSizes_MPIAIJ(Mat M, PetscInt rbs, PetscInt cbs)
 67: {
 69:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)M->data;

 72:   if (mat->A) {
 73:     MatSetBlockSizes(mat->A,rbs,cbs);
 74:     MatSetBlockSizes(mat->B,rbs,1);
 75:   }
 76:   return(0);
 77: }

 79: PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows)
 80: {
 81:   PetscErrorCode  ierr;
 82:   Mat_MPIAIJ      *mat = (Mat_MPIAIJ*)M->data;
 83:   Mat_SeqAIJ      *a   = (Mat_SeqAIJ*)mat->A->data;
 84:   Mat_SeqAIJ      *b   = (Mat_SeqAIJ*)mat->B->data;
 85:   const PetscInt  *ia,*ib;
 86:   const MatScalar *aa,*bb;
 87:   PetscInt        na,nb,i,j,*rows,cnt=0,n0rows;
 88:   PetscInt        m = M->rmap->n,rstart = M->rmap->rstart;

 91:   *keptrows = 0;
 92:   ia        = a->i;
 93:   ib        = b->i;
 94:   for (i=0; i<m; i++) {
 95:     na = ia[i+1] - ia[i];
 96:     nb = ib[i+1] - ib[i];
 97:     if (!na && !nb) {
 98:       cnt++;
 99:       goto ok1;
100:     }
101:     aa = a->a + ia[i];
102:     for (j=0; j<na; j++) {
103:       if (aa[j] != 0.0) goto ok1;
104:     }
105:     bb = b->a + ib[i];
106:     for (j=0; j <nb; j++) {
107:       if (bb[j] != 0.0) goto ok1;
108:     }
109:     cnt++;
110: ok1:;
111:   }
112:   MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));
113:   if (!n0rows) return(0);
114:   PetscMalloc1(M->rmap->n-cnt,&rows);
115:   cnt  = 0;
116:   for (i=0; i<m; i++) {
117:     na = ia[i+1] - ia[i];
118:     nb = ib[i+1] - ib[i];
119:     if (!na && !nb) continue;
120:     aa = a->a + ia[i];
121:     for (j=0; j<na;j++) {
122:       if (aa[j] != 0.0) {
123:         rows[cnt++] = rstart + i;
124:         goto ok2;
125:       }
126:     }
127:     bb = b->a + ib[i];
128:     for (j=0; j<nb; j++) {
129:       if (bb[j] != 0.0) {
130:         rows[cnt++] = rstart + i;
131:         goto ok2;
132:       }
133:     }
134: ok2:;
135:   }
136:   ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);
137:   return(0);
138: }

140: PetscErrorCode  MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is)
141: {
142:   PetscErrorCode    ierr;
143:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*) Y->data;
144:   PetscBool         cong;

147:   MatHasCongruentLayouts(Y,&cong);
148:   if (Y->assembled && cong) {
149:     MatDiagonalSet(aij->A,D,is);
150:   } else {
151:     MatDiagonalSet_Default(Y,D,is);
152:   }
153:   return(0);
154: }

156: PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows)
157: {
158:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)M->data;
160:   PetscInt       i,rstart,nrows,*rows;

163:   *zrows = NULL;
164:   MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);
165:   MatGetOwnershipRange(M,&rstart,NULL);
166:   for (i=0; i<nrows; i++) rows[i] += rstart;
167:   ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);
168:   return(0);
169: }

171: PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms)
172: {
174:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)A->data;
175:   PetscInt       i,n,*garray = aij->garray;
176:   Mat_SeqAIJ     *a_aij = (Mat_SeqAIJ*) aij->A->data;
177:   Mat_SeqAIJ     *b_aij = (Mat_SeqAIJ*) aij->B->data;
178:   PetscReal      *work;

181:   MatGetSize(A,NULL,&n);
182:   PetscCalloc1(n,&work);
183:   if (type == NORM_2) {
184:     for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
185:       work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]);
186:     }
187:     for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
188:       work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]);
189:     }
190:   } else if (type == NORM_1) {
191:     for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
192:       work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]);
193:     }
194:     for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
195:       work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]);
196:     }
197:   } else if (type == NORM_INFINITY) {
198:     for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
199:       work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]);
200:     }
201:     for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
202:       work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]);
203:     }

205:   } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
206:   if (type == NORM_INFINITY) {
207:     MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
208:   } else {
209:     MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
210:   }
211:   PetscFree(work);
212:   if (type == NORM_2) {
213:     for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]);
214:   }
215:   return(0);
216: }

218: PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is)
219: {
220:   Mat_MPIAIJ      *a  = (Mat_MPIAIJ*)A->data;
221:   IS              sis,gis;
222:   PetscErrorCode  ierr;
223:   const PetscInt  *isis,*igis;
224:   PetscInt        n,*iis,nsis,ngis,rstart,i;

227:   MatFindOffBlockDiagonalEntries(a->A,&sis);
228:   MatFindNonzeroRows(a->B,&gis);
229:   ISGetSize(gis,&ngis);
230:   ISGetSize(sis,&nsis);
231:   ISGetIndices(sis,&isis);
232:   ISGetIndices(gis,&igis);

234:   PetscMalloc1(ngis+nsis,&iis);
235:   PetscArraycpy(iis,igis,ngis);
236:   PetscArraycpy(iis+ngis,isis,nsis);
237:   n    = ngis + nsis;
238:   PetscSortRemoveDupsInt(&n,iis);
239:   MatGetOwnershipRange(A,&rstart,NULL);
240:   for (i=0; i<n; i++) iis[i] += rstart;
241:   ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);

243:   ISRestoreIndices(sis,&isis);
244:   ISRestoreIndices(gis,&igis);
245:   ISDestroy(&sis);
246:   ISDestroy(&gis);
247:   return(0);
248: }

250: /*
251:     Distributes a SeqAIJ matrix across a set of processes. Code stolen from
252:     MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type.

254:     Only for square matrices

256:     Used by a preconditioner, hence PETSC_EXTERN
257: */
258: PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat)
259: {
260:   PetscMPIInt    rank,size;
261:   PetscInt       *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2];
263:   Mat            mat;
264:   Mat_SeqAIJ     *gmata;
265:   PetscMPIInt    tag;
266:   MPI_Status     status;
267:   PetscBool      aij;
268:   MatScalar      *gmataa,*ao,*ad,*gmataarestore=0;

271:   MPI_Comm_rank(comm,&rank);
272:   MPI_Comm_size(comm,&size);
273:   if (!rank) {
274:     PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);
275:     if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name);
276:   }
277:   if (reuse == MAT_INITIAL_MATRIX) {
278:     MatCreate(comm,&mat);
279:     MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);
280:     MatGetBlockSizes(gmat,&bses[0],&bses[1]);
281:     MPI_Bcast(bses,2,MPIU_INT,0,comm);
282:     MatSetBlockSizes(mat,bses[0],bses[1]);
283:     MatSetType(mat,MATAIJ);
284:     PetscMalloc1(size+1,&rowners);
285:     PetscMalloc2(m,&dlens,m,&olens);
286:     MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

288:     rowners[0] = 0;
289:     for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
290:     rstart = rowners[rank];
291:     rend   = rowners[rank+1];
292:     PetscObjectGetNewTag((PetscObject)mat,&tag);
293:     if (!rank) {
294:       gmata = (Mat_SeqAIJ*) gmat->data;
295:       /* send row lengths to all processors */
296:       for (i=0; i<m; i++) dlens[i] = gmata->ilen[i];
297:       for (i=1; i<size; i++) {
298:         MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
299:       }
300:       /* determine number diagonal and off-diagonal counts */
301:       PetscArrayzero(olens,m);
302:       PetscCalloc1(m,&ld);
303:       jj   = 0;
304:       for (i=0; i<m; i++) {
305:         for (j=0; j<dlens[i]; j++) {
306:           if (gmata->j[jj] < rstart) ld[i]++;
307:           if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++;
308:           jj++;
309:         }
310:       }
311:       /* send column indices to other processes */
312:       for (i=1; i<size; i++) {
313:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
314:         MPI_Send(&nz,1,MPIU_INT,i,tag,comm);
315:         MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);
316:       }

318:       /* send numerical values to other processes */
319:       for (i=1; i<size; i++) {
320:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
321:         MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
322:       }
323:       gmataa = gmata->a;
324:       gmataj = gmata->j;

326:     } else {
327:       /* receive row lengths */
328:       MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);
329:       /* receive column indices */
330:       MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);
331:       PetscMalloc2(nz,&gmataa,nz,&gmataj);
332:       MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);
333:       /* determine number diagonal and off-diagonal counts */
334:       PetscArrayzero(olens,m);
335:       PetscCalloc1(m,&ld);
336:       jj   = 0;
337:       for (i=0; i<m; i++) {
338:         for (j=0; j<dlens[i]; j++) {
339:           if (gmataj[jj] < rstart) ld[i]++;
340:           if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++;
341:           jj++;
342:         }
343:       }
344:       /* receive numerical values */
345:       PetscArrayzero(gmataa,nz);
346:       MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
347:     }
348:     /* set preallocation */
349:     for (i=0; i<m; i++) {
350:       dlens[i] -= olens[i];
351:     }
352:     MatSeqAIJSetPreallocation(mat,0,dlens);
353:     MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);

355:     for (i=0; i<m; i++) {
356:       dlens[i] += olens[i];
357:     }
358:     cnt = 0;
359:     for (i=0; i<m; i++) {
360:       row  = rstart + i;
361:       MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);
362:       cnt += dlens[i];
363:     }
364:     if (rank) {
365:       PetscFree2(gmataa,gmataj);
366:     }
367:     PetscFree2(dlens,olens);
368:     PetscFree(rowners);

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

372:     *inmat = mat;
373:   } else {   /* column indices are already set; only need to move over numerical values from process 0 */
374:     Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data;
375:     Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data;
376:     mat  = *inmat;
377:     PetscObjectGetNewTag((PetscObject)mat,&tag);
378:     if (!rank) {
379:       /* send numerical values to other processes */
380:       gmata  = (Mat_SeqAIJ*) gmat->data;
381:       MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);
382:       gmataa = gmata->a;
383:       for (i=1; i<size; i++) {
384:         nz   = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
385:         MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
386:       }
387:       nz = gmata->i[rowners[1]]-gmata->i[rowners[0]];
388:     } else {
389:       /* receive numerical values from process 0*/
390:       nz   = Ad->nz + Ao->nz;
391:       PetscMalloc1(nz,&gmataa); gmataarestore = gmataa;
392:       MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
393:     }
394:     /* transfer numerical values into the diagonal A and off diagonal B parts of mat */
395:     ld = ((Mat_MPIAIJ*)(mat->data))->ld;
396:     ad = Ad->a;
397:     ao = Ao->a;
398:     if (mat->rmap->n) {
399:       i  = 0;
400:       nz = ld[i];                                   PetscArraycpy(ao,gmataa,nz); ao += nz; gmataa += nz;
401:       nz = Ad->i[i+1] - Ad->i[i];                   PetscArraycpy(ad,gmataa,nz); ad += nz; gmataa += nz;
402:     }
403:     for (i=1; i<mat->rmap->n; i++) {
404:       nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; PetscArraycpy(ao,gmataa,nz); ao += nz; gmataa += nz;
405:       nz = Ad->i[i+1] - Ad->i[i];                   PetscArraycpy(ad,gmataa,nz); ad += nz; gmataa += nz;
406:     }
407:     i--;
408:     if (mat->rmap->n) {
409:       nz = Ao->i[i+1] - Ao->i[i] - ld[i];           PetscArraycpy(ao,gmataa,nz);
410:     }
411:     if (rank) {
412:       PetscFree(gmataarestore);
413:     }
414:   }
415:   MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
416:   MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
417:   return(0);
418: }

420: /*
421:   Local utility routine that creates a mapping from the global column
422: number to the local number in the off-diagonal part of the local
423: storage of the matrix.  When PETSC_USE_CTABLE is used this is scalable at
424: a slightly higher hash table cost; without it it is not scalable (each processor
425: has an order N integer array but is fast to acess.
426: */
427: PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat)
428: {
429:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
431:   PetscInt       n = aij->B->cmap->n,i;

434:   if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray");
435: #if defined(PETSC_USE_CTABLE)
436:   PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);
437:   for (i=0; i<n; i++) {
438:     PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);
439:   }
440: #else
441:   PetscCalloc1(mat->cmap->N+1,&aij->colmap);
442:   PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));
443:   for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1;
444: #endif
445:   return(0);
446: }

448: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol)     \
449: { \
450:     if (col <= lastcol1)  low1 = 0;     \
451:     else                 high1 = nrow1; \
452:     lastcol1 = col;\
453:     while (high1-low1 > 5) { \
454:       t = (low1+high1)/2; \
455:       if (rp1[t] > col) high1 = t; \
456:       else              low1  = t; \
457:     } \
458:       for (_i=low1; _i<high1; _i++) { \
459:         if (rp1[_i] > col) break; \
460:         if (rp1[_i] == col) { \
461:           if (addv == ADD_VALUES) { \
462:             ap1[_i] += value;   \
463:             /* Not sure LogFlops will slow dow the code or not */ \
464:             (void)PetscLogFlops(1.0);   \
465:            } \
466:           else                    ap1[_i] = value; \
467:           inserted = PETSC_TRUE; \
468:           goto a_noinsert; \
469:         } \
470:       }  \
471:       if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
472:       if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;}                \
473:       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); \
474:       MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
475:       N = nrow1++ - 1; a->nz++; high1++; \
476:       /* shift up all the later entries in this row */ \
477:       PetscArraymove(rp1+_i+1,rp1+_i,N-_i+1);\
478:       PetscArraymove(ap1+_i+1,ap1+_i,N-_i+1);\
479:       rp1[_i] = col;  \
480:       ap1[_i] = value;  \
481:       A->nonzerostate++;\
482:       a_noinsert: ; \
483:       ailen[row] = nrow1; \
484: }

486: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \
487:   { \
488:     if (col <= lastcol2) low2 = 0;                        \
489:     else high2 = nrow2;                                   \
490:     lastcol2 = col;                                       \
491:     while (high2-low2 > 5) {                              \
492:       t = (low2+high2)/2;                                 \
493:       if (rp2[t] > col) high2 = t;                        \
494:       else             low2  = t;                         \
495:     }                                                     \
496:     for (_i=low2; _i<high2; _i++) {                       \
497:       if (rp2[_i] > col) break;                           \
498:       if (rp2[_i] == col) {                               \
499:         if (addv == ADD_VALUES) {                         \
500:           ap2[_i] += value;                               \
501:           (void)PetscLogFlops(1.0);                       \
502:         }                                                 \
503:         else                    ap2[_i] = value;          \
504:         inserted = PETSC_TRUE;                            \
505:         goto b_noinsert;                                  \
506:       }                                                   \
507:     }                                                     \
508:     if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
509:     if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;}                        \
510:     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); \
511:     MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
512:     N = nrow2++ - 1; b->nz++; high2++;                    \
513:     /* shift up all the later entries in this row */      \
514:     PetscArraymove(rp2+_i+1,rp2+_i,N-_i+1);\
515:     PetscArraymove(ap2+_i+1,ap2+_i,N-_i+1);\
516:     rp2[_i] = col;                                        \
517:     ap2[_i] = value;                                      \
518:     B->nonzerostate++;                                    \
519:     b_noinsert: ;                                         \
520:     bilen[row] = nrow2;                                   \
521:   }

523: PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[])
524: {
525:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)A->data;
526:   Mat_SeqAIJ     *a   = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data;
528:   PetscInt       l,*garray = mat->garray,diag;

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

533:   /* find size of row to the left of the diagonal part */
534:   MatGetOwnershipRange(A,&diag,0);
535:   row  = row - diag;
536:   for (l=0; l<b->i[row+1]-b->i[row]; l++) {
537:     if (garray[b->j[b->i[row]+l]] > diag) break;
538:   }
539:   PetscArraycpy(b->a+b->i[row],v,l);

541:   /* diagonal part */
542:   PetscArraycpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row]));

544:   /* right of diagonal part */
545:   PetscArraycpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],b->i[row+1]-b->i[row]-l);
546: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
547:   if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && (l || (a->i[row+1]-a->i[row]) || (b->i[row+1]-b->i[row]-l))) A->offloadmask = PETSC_OFFLOAD_CPU;
548: #endif
549:   return(0);
550: }

552: PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
553: {
554:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
555:   PetscScalar    value = 0.0;
557:   PetscInt       i,j,rstart  = mat->rmap->rstart,rend = mat->rmap->rend;
558:   PetscInt       cstart      = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
559:   PetscBool      roworiented = aij->roworiented;

561:   /* Some Variables required in the macro */
562:   Mat        A                    = aij->A;
563:   Mat_SeqAIJ *a                   = (Mat_SeqAIJ*)A->data;
564:   PetscInt   *aimax               = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
565:   MatScalar  *aa                  = a->a;
566:   PetscBool  ignorezeroentries    = a->ignorezeroentries;
567:   Mat        B                    = aij->B;
568:   Mat_SeqAIJ *b                   = (Mat_SeqAIJ*)B->data;
569:   PetscInt   *bimax               = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
570:   MatScalar  *ba                  = b->a;
571:   /* This variable below is only for the PETSC_HAVE_VIENNACL or PETSC_HAVE_CUDA cases, but we define it in all cases because we
572:    * cannot use "#if defined" inside a macro. */
573:   PETSC_UNUSED PetscBool inserted = PETSC_FALSE;

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

580:   for (i=0; i<m; i++) {
581:     if (im[i] < 0) continue;
582: #if defined(PETSC_USE_DEBUG)
583:     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);
584: #endif
585:     if (im[i] >= rstart && im[i] < rend) {
586:       row      = im[i] - rstart;
587:       lastcol1 = -1;
588:       rp1      = aj + ai[row];
589:       ap1      = aa + ai[row];
590:       rmax1    = aimax[row];
591:       nrow1    = ailen[row];
592:       low1     = 0;
593:       high1    = nrow1;
594:       lastcol2 = -1;
595:       rp2      = bj + bi[row];
596:       ap2      = ba + bi[row];
597:       rmax2    = bimax[row];
598:       nrow2    = bilen[row];
599:       low2     = 0;
600:       high2    = nrow2;

602:       for (j=0; j<n; j++) {
603:         if (v)  value = roworiented ? v[i*n+j] : v[i+j*m];
604:         if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && im[i] != in[j]) continue;
605:         if (in[j] >= cstart && in[j] < cend) {
606:           col   = in[j] - cstart;
607:           nonew = a->nonew;
608:           MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
609: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
610:           if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && inserted) A->offloadmask = PETSC_OFFLOAD_CPU;
611: #endif
612:         } else if (in[j] < 0) continue;
613: #if defined(PETSC_USE_DEBUG)
614:         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);
615: #endif
616:         else {
617:           if (mat->was_assembled) {
618:             if (!aij->colmap) {
619:               MatCreateColmap_MPIAIJ_Private(mat);
620:             }
621: #if defined(PETSC_USE_CTABLE)
622:             PetscTableFind(aij->colmap,in[j]+1,&col);
623:             col--;
624: #else
625:             col = aij->colmap[in[j]] - 1;
626: #endif
627:             if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) {
628:               MatDisAssemble_MPIAIJ(mat);
629:               col  =  in[j];
630:               /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
631:               B        = aij->B;
632:               b        = (Mat_SeqAIJ*)B->data;
633:               bimax    = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a;
634:               rp2      = bj + bi[row];
635:               ap2      = ba + bi[row];
636:               rmax2    = bimax[row];
637:               nrow2    = bilen[row];
638:               low2     = 0;
639:               high2    = nrow2;
640:               bm       = aij->B->rmap->n;
641:               ba       = b->a;
642:               inserted = PETSC_FALSE;
643:             } else if (col < 0) {
644:               if (1 == ((Mat_SeqAIJ*)(aij->B->data))->nonew) {
645:                 PetscInfo3(mat,"Skipping of insertion of new nonzero location in off-diagonal portion of matrix %g(%D,%D)\n",(double)PetscRealPart(value),im[i],in[j]);
646:               } else SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]);
647:             }
648:           } else col = in[j];
649:           nonew = b->nonew;
650:           MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
651: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
652:           if (B->offloadmask != PETSC_OFFLOAD_UNALLOCATED && inserted) B->offloadmask = PETSC_OFFLOAD_CPU;
653: #endif
654:         }
655:       }
656:     } else {
657:       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]);
658:       if (!aij->donotstash) {
659:         mat->assembled = PETSC_FALSE;
660:         if (roworiented) {
661:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
662:         } else {
663:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
664:         }
665:       }
666:     }
667:   }
668:   return(0);
669: }

671: /*
672:     This function sets the j and ilen arrays (of the diagonal and off-diagonal part) of an MPIAIJ-matrix.
673:     The values in mat_i have to be sorted and the values in mat_j have to be sorted for each row (CSR-like).
674:     No off-processor parts off the matrix are allowed here and mat->was_assembled has to be PETSC_FALSE.
675: */
676: PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat_Symbolic(Mat mat,const PetscInt mat_j[],const PetscInt mat_i[])
677: {
678:   Mat_MPIAIJ     *aij        = (Mat_MPIAIJ*)mat->data;
679:   Mat            A           = aij->A; /* diagonal part of the matrix */
680:   Mat            B           = aij->B; /* offdiagonal part of the matrix */
681:   Mat_SeqAIJ     *a          = (Mat_SeqAIJ*)A->data;
682:   Mat_SeqAIJ     *b          = (Mat_SeqAIJ*)B->data;
683:   PetscInt       cstart      = mat->cmap->rstart,cend = mat->cmap->rend,col;
684:   PetscInt       *ailen      = a->ilen,*aj = a->j;
685:   PetscInt       *bilen      = b->ilen,*bj = b->j;
686:   PetscInt       am          = aij->A->rmap->n,j;
687:   PetscInt       diag_so_far = 0,dnz;
688:   PetscInt       offd_so_far = 0,onz;

691:   /* Iterate over all rows of the matrix */
692:   for (j=0; j<am; j++) {
693:     dnz = onz = 0;
694:     /*  Iterate over all non-zero columns of the current row */
695:     for (col=mat_i[j]; col<mat_i[j+1]; col++) {
696:       /* If column is in the diagonal */
697:       if (mat_j[col] >= cstart && mat_j[col] < cend) {
698:         aj[diag_so_far++] = mat_j[col] - cstart;
699:         dnz++;
700:       } else { /* off-diagonal entries */
701:         bj[offd_so_far++] = mat_j[col];
702:         onz++;
703:       }
704:     }
705:     ailen[j] = dnz;
706:     bilen[j] = onz;
707:   }
708:   return(0);
709: }

711: /*
712:     This function sets the local j, a and ilen arrays (of the diagonal and off-diagonal part) of an MPIAIJ-matrix.
713:     The values in mat_i have to be sorted and the values in mat_j have to be sorted for each row (CSR-like).
714:     No off-processor parts off the matrix are allowed here, they are set at a later point by MatSetValues_MPIAIJ.
715:     Also, mat->was_assembled has to be false, otherwise the statement aj[rowstart_diag+dnz_row] = mat_j[col] - cstart;
716:     would not be true and the more complex MatSetValues_MPIAIJ has to be used.
717: */
718: PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat(Mat mat,const PetscInt mat_j[],const PetscInt mat_i[],const PetscScalar mat_a[])
719: {
720:   Mat_MPIAIJ     *aij   = (Mat_MPIAIJ*)mat->data;
721:   Mat            A      = aij->A; /* diagonal part of the matrix */
722:   Mat            B      = aij->B; /* offdiagonal part of the matrix */
723:   Mat_SeqAIJ     *aijd  =(Mat_SeqAIJ*)(aij->A)->data,*aijo=(Mat_SeqAIJ*)(aij->B)->data;
724:   Mat_SeqAIJ     *a     = (Mat_SeqAIJ*)A->data;
725:   Mat_SeqAIJ     *b     = (Mat_SeqAIJ*)B->data;
726:   PetscInt       cstart = mat->cmap->rstart,cend = mat->cmap->rend;
727:   PetscInt       *ailen = a->ilen,*aj = a->j;
728:   PetscInt       *bilen = b->ilen,*bj = b->j;
729:   PetscInt       am     = aij->A->rmap->n,j;
730:   PetscInt       *full_diag_i=aijd->i,*full_offd_i=aijo->i; /* These variables can also include non-local elements, which are set at a later point. */
731:   PetscInt       col,dnz_row,onz_row,rowstart_diag,rowstart_offd;
732:   PetscScalar    *aa = a->a,*ba = b->a;

735:   /* Iterate over all rows of the matrix */
736:   for (j=0; j<am; j++) {
737:     dnz_row = onz_row = 0;
738:     rowstart_offd = full_offd_i[j];
739:     rowstart_diag = full_diag_i[j];
740:     /*  Iterate over all non-zero columns of the current row */
741:     for (col=mat_i[j]; col<mat_i[j+1]; col++) {
742:       /* If column is in the diagonal */
743:       if (mat_j[col] >= cstart && mat_j[col] < cend) {
744:         aj[rowstart_diag+dnz_row] = mat_j[col] - cstart;
745:         aa[rowstart_diag+dnz_row] = mat_a[col];
746:         dnz_row++;
747:       } else { /* off-diagonal entries */
748:         bj[rowstart_offd+onz_row] = mat_j[col];
749:         ba[rowstart_offd+onz_row] = mat_a[col];
750:         onz_row++;
751:       }
752:     }
753:     ailen[j] = dnz_row;
754:     bilen[j] = onz_row;
755:   }
756:   return(0);
757: }

759: PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
760: {
761:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
763:   PetscInt       i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
764:   PetscInt       cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;

767:   for (i=0; i<m; i++) {
768:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
769:     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);
770:     if (idxm[i] >= rstart && idxm[i] < rend) {
771:       row = idxm[i] - rstart;
772:       for (j=0; j<n; j++) {
773:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
774:         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);
775:         if (idxn[j] >= cstart && idxn[j] < cend) {
776:           col  = idxn[j] - cstart;
777:           MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
778:         } else {
779:           if (!aij->colmap) {
780:             MatCreateColmap_MPIAIJ_Private(mat);
781:           }
782: #if defined(PETSC_USE_CTABLE)
783:           PetscTableFind(aij->colmap,idxn[j]+1,&col);
784:           col--;
785: #else
786:           col = aij->colmap[idxn[j]] - 1;
787: #endif
788:           if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
789:           else {
790:             MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
791:           }
792:         }
793:       }
794:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
795:   }
796:   return(0);
797: }

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

801: PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode)
802: {
803:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
805:   PetscInt       nstash,reallocs;

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

810:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
811:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
812:   PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
813:   return(0);
814: }

816: PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode)
817: {
818:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
819:   Mat_SeqAIJ     *a   = (Mat_SeqAIJ*)aij->A->data;
821:   PetscMPIInt    n;
822:   PetscInt       i,j,rstart,ncols,flg;
823:   PetscInt       *row,*col;
824:   PetscBool      other_disassembled;
825:   PetscScalar    *val;

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

830:   if (!aij->donotstash && !mat->nooffprocentries) {
831:     while (1) {
832:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
833:       if (!flg) break;

835:       for (i=0; i<n; ) {
836:         /* Now identify the consecutive vals belonging to the same row */
837:         for (j=i,rstart=row[j]; j<n; j++) {
838:           if (row[j] != rstart) break;
839:         }
840:         if (j < n) ncols = j-i;
841:         else       ncols = n-i;
842:         /* Now assemble all these values with a single function call */
843:         MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
844:         i    = j;
845:       }
846:     }
847:     MatStashScatterEnd_Private(&mat->stash);
848:   }
849: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
850:   if (mat->offloadmask == PETSC_OFFLOAD_CPU) aij->A->offloadmask = PETSC_OFFLOAD_CPU;
851:   /* We call MatBindToCPU() on aij->A and aij->B here, because if MatBindToCPU_MPIAIJ() is called before assembly, it cannot bind these. */
852:   if (mat->boundtocpu) {
853:     MatBindToCPU(aij->A,PETSC_TRUE);
854:     MatBindToCPU(aij->B,PETSC_TRUE);
855:   }
856: #endif
857:   MatAssemblyBegin(aij->A,mode);
858:   MatAssemblyEnd(aij->A,mode);

860:   /* determine if any processor has disassembled, if so we must
861:      also disassemble ourself, in order that we may reassemble. */
862:   /*
863:      if nonzero structure of submatrix B cannot change then we know that
864:      no processor disassembled thus we can skip this stuff
865:   */
866:   if (!((Mat_SeqAIJ*)aij->B->data)->nonew) {
867:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
868:     if (mat->was_assembled && !other_disassembled) {
869: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
870:       aij->B->offloadmask = PETSC_OFFLOAD_BOTH; /* do not copy on the GPU when assembling inside MatDisAssemble_MPIAIJ */
871: #endif
872:       MatDisAssemble_MPIAIJ(mat);
873:     }
874:   }
875:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
876:     MatSetUpMultiply_MPIAIJ(mat);
877:   }
878:   MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);
879: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
880:   if (mat->offloadmask == PETSC_OFFLOAD_CPU && aij->B->offloadmask != PETSC_OFFLOAD_UNALLOCATED) aij->B->offloadmask = PETSC_OFFLOAD_CPU;
881: #endif
882:   MatAssemblyBegin(aij->B,mode);
883:   MatAssemblyEnd(aij->B,mode);

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

887:   aij->rowvalues = 0;

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

892:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
893:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
894:     PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate;
895:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
896:   }
897: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
898:   mat->offloadmask = PETSC_OFFLOAD_BOTH;
899: #endif
900:   return(0);
901: }

903: PetscErrorCode MatZeroEntries_MPIAIJ(Mat A)
904: {
905:   Mat_MPIAIJ     *l = (Mat_MPIAIJ*)A->data;

909:   MatZeroEntries(l->A);
910:   MatZeroEntries(l->B);
911:   return(0);
912: }

914: PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
915: {
916:   Mat_MPIAIJ      *mat = (Mat_MPIAIJ *) A->data;
917:   PetscObjectState sA, sB;
918:   PetscInt        *lrows;
919:   PetscInt         r, len;
920:   PetscBool        cong, lch, gch;
921:   PetscErrorCode   ierr;

924:   /* get locally owned rows */
925:   MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);
926:   MatHasCongruentLayouts(A,&cong);
927:   /* fix right hand side if needed */
928:   if (x && b) {
929:     const PetscScalar *xx;
930:     PetscScalar       *bb;

932:     if (!cong) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Need matching row/col layout");
933:     VecGetArrayRead(x, &xx);
934:     VecGetArray(b, &bb);
935:     for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
936:     VecRestoreArrayRead(x, &xx);
937:     VecRestoreArray(b, &bb);
938:   }

940:   sA = mat->A->nonzerostate;
941:   sB = mat->B->nonzerostate;

943:   if (diag != 0.0 && cong) {
944:     MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);
945:     MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
946:   } else if (diag != 0.0) { /* non-square or non congruent layouts -> if keepnonzeropattern is false, we allow for new insertion */
947:     Mat_SeqAIJ *aijA = (Mat_SeqAIJ*)mat->A->data;
948:     Mat_SeqAIJ *aijB = (Mat_SeqAIJ*)mat->B->data;
949:     PetscInt   nnwA, nnwB;
950:     PetscBool  nnzA, nnzB;

952:     nnwA = aijA->nonew;
953:     nnwB = aijB->nonew;
954:     nnzA = aijA->keepnonzeropattern;
955:     nnzB = aijB->keepnonzeropattern;
956:     if (!nnzA) {
957:       PetscInfo(mat->A,"Requested to not keep the pattern and add a nonzero diagonal; may encounter reallocations on diagonal block.\n");
958:       aijA->nonew = 0;
959:     }
960:     if (!nnzB) {
961:       PetscInfo(mat->B,"Requested to not keep the pattern and add a nonzero diagonal; may encounter reallocations on off-diagonal block.\n");
962:       aijB->nonew = 0;
963:     }
964:     /* Must zero here before the next loop */
965:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
966:     MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
967:     for (r = 0; r < len; ++r) {
968:       const PetscInt row = lrows[r] + A->rmap->rstart;
969:       if (row >= A->cmap->N) continue;
970:       MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);
971:     }
972:     aijA->nonew = nnwA;
973:     aijB->nonew = nnwB;
974:   } else {
975:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
976:     MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
977:   }
978:   PetscFree(lrows);
979:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
980:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);

982:   /* reduce nonzerostate */
983:   lch = (PetscBool)(sA != mat->A->nonzerostate || sB != mat->B->nonzerostate);
984:   MPIU_Allreduce(&lch,&gch,1,MPIU_BOOL,MPI_LOR,PetscObjectComm((PetscObject)A));
985:   if (gch) A->nonzerostate++;
986:   return(0);
987: }

989: PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
990: {
991:   Mat_MPIAIJ        *l = (Mat_MPIAIJ*)A->data;
992:   PetscErrorCode    ierr;
993:   PetscMPIInt       n = A->rmap->n;
994:   PetscInt          i,j,r,m,len = 0;
995:   PetscInt          *lrows,*owners = A->rmap->range;
996:   PetscMPIInt       p = 0;
997:   PetscSFNode       *rrows;
998:   PetscSF           sf;
999:   const PetscScalar *xx;
1000:   PetscScalar       *bb,*mask;
1001:   Vec               xmask,lmask;
1002:   Mat_SeqAIJ        *aij = (Mat_SeqAIJ*)l->B->data;
1003:   const PetscInt    *aj, *ii,*ridx;
1004:   PetscScalar       *aa;

1007:   /* Create SF where leaves are input rows and roots are owned rows */
1008:   PetscMalloc1(n, &lrows);
1009:   for (r = 0; r < n; ++r) lrows[r] = -1;
1010:   PetscMalloc1(N, &rrows);
1011:   for (r = 0; r < N; ++r) {
1012:     const PetscInt idx   = rows[r];
1013:     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);
1014:     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
1015:       PetscLayoutFindOwner(A->rmap,idx,&p);
1016:     }
1017:     rrows[r].rank  = p;
1018:     rrows[r].index = rows[r] - owners[p];
1019:   }
1020:   PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
1021:   PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
1022:   /* Collect flags for rows to be zeroed */
1023:   PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
1024:   PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
1025:   PetscSFDestroy(&sf);
1026:   /* Compress and put in row numbers */
1027:   for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
1028:   /* zero diagonal part of matrix */
1029:   MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
1030:   /* handle off diagonal part of matrix */
1031:   MatCreateVecs(A,&xmask,NULL);
1032:   VecDuplicate(l->lvec,&lmask);
1033:   VecGetArray(xmask,&bb);
1034:   for (i=0; i<len; i++) bb[lrows[i]] = 1;
1035:   VecRestoreArray(xmask,&bb);
1036:   VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
1037:   VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
1038:   VecDestroy(&xmask);
1039:   if (x && b) { /* this code is buggy when the row and column layout don't match */
1040:     PetscBool cong;

1042:     MatHasCongruentLayouts(A,&cong);
1043:     if (!cong) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Need matching row/col layout");
1044:     VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
1045:     VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
1046:     VecGetArrayRead(l->lvec,&xx);
1047:     VecGetArray(b,&bb);
1048:   }
1049:   VecGetArray(lmask,&mask);
1050:   /* remove zeroed rows of off diagonal matrix */
1051:   ii = aij->i;
1052:   for (i=0; i<len; i++) {
1053:     PetscArrayzero(aij->a + ii[lrows[i]],ii[lrows[i]+1] - ii[lrows[i]]);
1054:   }
1055:   /* loop over all elements of off process part of matrix zeroing removed columns*/
1056:   if (aij->compressedrow.use) {
1057:     m    = aij->compressedrow.nrows;
1058:     ii   = aij->compressedrow.i;
1059:     ridx = aij->compressedrow.rindex;
1060:     for (i=0; i<m; i++) {
1061:       n  = ii[i+1] - ii[i];
1062:       aj = aij->j + ii[i];
1063:       aa = aij->a + ii[i];

1065:       for (j=0; j<n; j++) {
1066:         if (PetscAbsScalar(mask[*aj])) {
1067:           if (b) bb[*ridx] -= *aa*xx[*aj];
1068:           *aa = 0.0;
1069:         }
1070:         aa++;
1071:         aj++;
1072:       }
1073:       ridx++;
1074:     }
1075:   } else { /* do not use compressed row format */
1076:     m = l->B->rmap->n;
1077:     for (i=0; i<m; i++) {
1078:       n  = ii[i+1] - ii[i];
1079:       aj = aij->j + ii[i];
1080:       aa = aij->a + ii[i];
1081:       for (j=0; j<n; j++) {
1082:         if (PetscAbsScalar(mask[*aj])) {
1083:           if (b) bb[i] -= *aa*xx[*aj];
1084:           *aa = 0.0;
1085:         }
1086:         aa++;
1087:         aj++;
1088:       }
1089:     }
1090:   }
1091:   if (x && b) {
1092:     VecRestoreArray(b,&bb);
1093:     VecRestoreArrayRead(l->lvec,&xx);
1094:   }
1095:   VecRestoreArray(lmask,&mask);
1096:   VecDestroy(&lmask);
1097:   PetscFree(lrows);

1099:   /* only change matrix nonzero state if pattern was allowed to be changed */
1100:   if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) {
1101:     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
1102:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
1103:   }
1104:   return(0);
1105: }

1107: PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy)
1108: {
1109:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
1111:   PetscInt       nt;
1112:   VecScatter     Mvctx = a->Mvctx;

1115:   VecGetLocalSize(xx,&nt);
1116:   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);

1118:   VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1119:   (*a->A->ops->mult)(a->A,xx,yy);
1120:   VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1121:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1122:   return(0);
1123: }

1125: PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx)
1126: {
1127:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1131:   MatMultDiagonalBlock(a->A,bb,xx);
1132:   return(0);
1133: }

1135: PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1136: {
1137:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
1139:   VecScatter     Mvctx = a->Mvctx;

1142:   if (a->Mvctx_mpi1_flg) Mvctx = a->Mvctx_mpi1;
1143:   VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1144:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
1145:   VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1146:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
1147:   return(0);
1148: }

1150: PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy)
1151: {
1152:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1156:   /* do nondiagonal part */
1157:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1158:   /* do local part */
1159:   (*a->A->ops->multtranspose)(a->A,xx,yy);
1160:   /* add partial results together */
1161:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1162:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1163:   return(0);
1164: }

1166: PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool  *f)
1167: {
1168:   MPI_Comm       comm;
1169:   Mat_MPIAIJ     *Aij = (Mat_MPIAIJ*) Amat->data, *Bij;
1170:   Mat            Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs;
1171:   IS             Me,Notme;
1173:   PetscInt       M,N,first,last,*notme,i;
1174:   PetscBool      lf;
1175:   PetscMPIInt    size;

1178:   /* Easy test: symmetric diagonal block */
1179:   Bij  = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A;
1180:   MatIsTranspose(Adia,Bdia,tol,&lf);
1181:   MPIU_Allreduce(&lf,f,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)Amat));
1182:   if (!*f) return(0);
1183:   PetscObjectGetComm((PetscObject)Amat,&comm);
1184:   MPI_Comm_size(comm,&size);
1185:   if (size == 1) return(0);

1187:   /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */
1188:   MatGetSize(Amat,&M,&N);
1189:   MatGetOwnershipRange(Amat,&first,&last);
1190:   PetscMalloc1(N-last+first,&notme);
1191:   for (i=0; i<first; i++) notme[i] = i;
1192:   for (i=last; i<M; i++) notme[i-last+first] = i;
1193:   ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
1194:   ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
1195:   MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
1196:   Aoff = Aoffs[0];
1197:   MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
1198:   Boff = Boffs[0];
1199:   MatIsTranspose(Aoff,Boff,tol,f);
1200:   MatDestroyMatrices(1,&Aoffs);
1201:   MatDestroyMatrices(1,&Boffs);
1202:   ISDestroy(&Me);
1203:   ISDestroy(&Notme);
1204:   PetscFree(notme);
1205:   return(0);
1206: }

1208: PetscErrorCode MatIsSymmetric_MPIAIJ(Mat A,PetscReal tol,PetscBool  *f)
1209: {

1213:   MatIsTranspose_MPIAIJ(A,A,tol,f);
1214:   return(0);
1215: }

1217: PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1218: {
1219:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1223:   /* do nondiagonal part */
1224:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1225:   /* do local part */
1226:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
1227:   /* add partial results together */
1228:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1229:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1230:   return(0);
1231: }

1233: /*
1234:   This only works correctly for square matrices where the subblock A->A is the
1235:    diagonal block
1236: */
1237: PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v)
1238: {
1240:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1243:   if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1244:   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");
1245:   MatGetDiagonal(a->A,v);
1246:   return(0);
1247: }

1249: PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa)
1250: {
1251:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1255:   MatScale(a->A,aa);
1256:   MatScale(a->B,aa);
1257:   return(0);
1258: }

1260: PetscErrorCode MatDestroy_MPIAIJ(Mat mat)
1261: {
1262:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

1266: #if defined(PETSC_USE_LOG)
1267:   PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
1268: #endif
1269:   MatStashDestroy_Private(&mat->stash);
1270:   VecDestroy(&aij->diag);
1271:   MatDestroy(&aij->A);
1272:   MatDestroy(&aij->B);
1273: #if defined(PETSC_USE_CTABLE)
1274:   PetscTableDestroy(&aij->colmap);
1275: #else
1276:   PetscFree(aij->colmap);
1277: #endif
1278:   PetscFree(aij->garray);
1279:   VecDestroy(&aij->lvec);
1280:   VecScatterDestroy(&aij->Mvctx);
1281:   if (aij->Mvctx_mpi1) {VecScatterDestroy(&aij->Mvctx_mpi1);}
1282:   PetscFree2(aij->rowvalues,aij->rowindices);
1283:   PetscFree(aij->ld);
1284:   PetscFree(mat->data);

1286:   PetscObjectChangeTypeName((PetscObject)mat,0);
1287:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1288:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1289:   PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
1290:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);
1291:   PetscObjectComposeFunction((PetscObject)mat,"MatResetPreallocation_C",NULL);
1292:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);
1293:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
1294:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpibaij_C",NULL);
1295:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);
1296: #if defined(PETSC_HAVE_ELEMENTAL)
1297:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);
1298: #endif
1299: #if defined(PETSC_HAVE_HYPRE)
1300:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);
1301:   PetscObjectComposeFunction((PetscObject)mat,"MatProductSetFromOptions_transpose_mpiaij_mpiaij_C",NULL);
1302: #endif
1303:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_is_C",NULL);
1304:   PetscObjectComposeFunction((PetscObject)mat,"MatProductSetFromOptions_is_mpiaij_C",NULL);
1305:   PetscObjectComposeFunction((PetscObject)mat,"MatProductSetFromOptions_mpiaij_mpiaij_C",NULL);
1306:   return(0);
1307: }

1309: PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer)
1310: {
1311:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*)mat->data;
1312:   Mat_SeqAIJ        *A   = (Mat_SeqAIJ*)aij->A->data;
1313:   Mat_SeqAIJ        *B   = (Mat_SeqAIJ*)aij->B->data;
1314:   const PetscInt    *garray = aij->garray;
1315:   PetscInt          header[4],M,N,m,rs,cs,nz,cnt,i,ja,jb;
1316:   PetscInt          *rowlens;
1317:   PetscInt          *colidxs;
1318:   PetscScalar       *matvals;
1319:   PetscErrorCode    ierr;

1322:   PetscViewerSetUp(viewer);

1324:   M  = mat->rmap->N;
1325:   N  = mat->cmap->N;
1326:   m  = mat->rmap->n;
1327:   rs = mat->rmap->rstart;
1328:   cs = mat->cmap->rstart;
1329:   nz = A->nz + B->nz;

1331:   /* write matrix header */
1332:   header[0] = MAT_FILE_CLASSID;
1333:   header[1] = M; header[2] = N; header[3] = nz;
1334:   MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1335:   PetscViewerBinaryWrite(viewer,header,4,PETSC_INT);

1337:   /* fill in and store row lengths  */
1338:   PetscMalloc1(m,&rowlens);
1339:   for (i=0; i<m; i++) rowlens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
1340:   PetscViewerBinaryWriteAll(viewer,rowlens,m,rs,M,PETSC_INT);
1341:   PetscFree(rowlens);

1343:   /* fill in and store column indices */
1344:   PetscMalloc1(nz,&colidxs);
1345:   for (cnt=0, i=0; i<m; i++) {
1346:     for (jb=B->i[i]; jb<B->i[i+1]; jb++) {
1347:       if (garray[B->j[jb]] > cs) break;
1348:       colidxs[cnt++] = garray[B->j[jb]];
1349:     }
1350:     for (ja=A->i[i]; ja<A->i[i+1]; ja++)
1351:       colidxs[cnt++] = A->j[ja] + cs;
1352:     for (; jb<B->i[i+1]; jb++)
1353:       colidxs[cnt++] = garray[B->j[jb]];
1354:   }
1355:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);
1356:   PetscViewerBinaryWriteAll(viewer,colidxs,nz,PETSC_DETERMINE,PETSC_DETERMINE,PETSC_INT);
1357:   PetscFree(colidxs);

1359:   /* fill in and store nonzero values */
1360:   PetscMalloc1(nz,&matvals);
1361:   for (cnt=0, i=0; i<m; i++) {
1362:     for (jb=B->i[i]; jb<B->i[i+1]; jb++) {
1363:       if (garray[B->j[jb]] > cs) break;
1364:       matvals[cnt++] = B->a[jb];
1365:     }
1366:     for (ja=A->i[i]; ja<A->i[i+1]; ja++)
1367:       matvals[cnt++] = A->a[ja];
1368:     for (; jb<B->i[i+1]; jb++)
1369:       matvals[cnt++] = B->a[jb];
1370:   }
1371:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);
1372:   PetscViewerBinaryWriteAll(viewer,matvals,nz,PETSC_DETERMINE,PETSC_DETERMINE,PETSC_SCALAR);
1373:   PetscFree(matvals);

1375:   /* write block size option to the viewer's .info file */
1376:   MatView_Binary_BlockSizes(mat,viewer);
1377:   return(0);
1378: }

1380:  #include <petscdraw.h>
1381: PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1382: {
1383:   Mat_MPIAIJ        *aij = (Mat_MPIAIJ*)mat->data;
1384:   PetscErrorCode    ierr;
1385:   PetscMPIInt       rank = aij->rank,size = aij->size;
1386:   PetscBool         isdraw,iascii,isbinary;
1387:   PetscViewer       sviewer;
1388:   PetscViewerFormat format;

1391:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1392:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1393:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1394:   if (iascii) {
1395:     PetscViewerGetFormat(viewer,&format);
1396:     if (format == PETSC_VIEWER_LOAD_BALANCE) {
1397:       PetscInt i,nmax = 0,nmin = PETSC_MAX_INT,navg = 0,*nz,nzlocal = ((Mat_SeqAIJ*) (aij->A->data))->nz + ((Mat_SeqAIJ*) (aij->B->data))->nz;
1398:       PetscMalloc1(size,&nz);
1399:       MPI_Allgather(&nzlocal,1,MPIU_INT,nz,1,MPIU_INT,PetscObjectComm((PetscObject)mat));
1400:       for (i=0; i<(PetscInt)size; i++) {
1401:         nmax = PetscMax(nmax,nz[i]);
1402:         nmin = PetscMin(nmin,nz[i]);
1403:         navg += nz[i];
1404:       }
1405:       PetscFree(nz);
1406:       navg = navg/size;
1407:       PetscViewerASCIIPrintf(viewer,"Load Balance - Nonzeros: Min %D  avg %D  max %D\n",nmin,navg,nmax);
1408:       return(0);
1409:     }
1410:     PetscViewerGetFormat(viewer,&format);
1411:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1412:       MatInfo   info;
1413:       PetscBool inodes;

1415:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1416:       MatGetInfo(mat,MAT_LOCAL,&info);
1417:       MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);
1418:       PetscViewerASCIIPushSynchronized(viewer);
1419:       if (!inodes) {
1420:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, not using I-node routines\n",
1421:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1422:       } else {
1423:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, using I-node routines\n",
1424:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1425:       }
1426:       MatGetInfo(aij->A,MAT_LOCAL,&info);
1427:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1428:       MatGetInfo(aij->B,MAT_LOCAL,&info);
1429:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1430:       PetscViewerFlush(viewer);
1431:       PetscViewerASCIIPopSynchronized(viewer);
1432:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
1433:       VecScatterView(aij->Mvctx,viewer);
1434:       return(0);
1435:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
1436:       PetscInt inodecount,inodelimit,*inodes;
1437:       MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);
1438:       if (inodes) {
1439:         PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
1440:       } else {
1441:         PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
1442:       }
1443:       return(0);
1444:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1445:       return(0);
1446:     }
1447:   } else if (isbinary) {
1448:     if (size == 1) {
1449:       PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1450:       MatView(aij->A,viewer);
1451:     } else {
1452:       MatView_MPIAIJ_Binary(mat,viewer);
1453:     }
1454:     return(0);
1455:   } else if (iascii && size == 1) {
1456:     PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1457:     MatView(aij->A,viewer);
1458:     return(0);
1459:   } else if (isdraw) {
1460:     PetscDraw draw;
1461:     PetscBool isnull;
1462:     PetscViewerDrawGetDraw(viewer,0,&draw);
1463:     PetscDrawIsNull(draw,&isnull);
1464:     if (isnull) return(0);
1465:   }

1467:   { /* assemble the entire matrix onto first processor */
1468:     Mat A = NULL, Av;
1469:     IS  isrow,iscol;

1471:     ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->rmap->N : 0,0,1,&isrow);
1472:     ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->cmap->N : 0,0,1,&iscol);
1473:     MatCreateSubMatrix(mat,isrow,iscol,MAT_INITIAL_MATRIX,&A);
1474:     MatMPIAIJGetSeqAIJ(A,&Av,NULL,NULL);
1475: /*  The commented code uses MatCreateSubMatrices instead */
1476: /*
1477:     Mat *AA, A = NULL, Av;
1478:     IS  isrow,iscol;

1480:     ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->rmap->N : 0,0,1,&isrow);
1481:     ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->cmap->N : 0,0,1,&iscol);
1482:     MatCreateSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&AA);
1483:     if (!rank) {
1484:        PetscObjectReference((PetscObject)AA[0]);
1485:        A    = AA[0];
1486:        Av   = AA[0];
1487:     }
1488:     MatDestroySubMatrices(1,&AA);
1489: */
1490:     ISDestroy(&iscol);
1491:     ISDestroy(&isrow);
1492:     /*
1493:        Everyone has to call to draw the matrix since the graphics waits are
1494:        synchronized across all processors that share the PetscDraw object
1495:     */
1496:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1497:     if (!rank) {
1498:       if (((PetscObject)mat)->name) {
1499:         PetscObjectSetName((PetscObject)Av,((PetscObject)mat)->name);
1500:       }
1501:       MatView_SeqAIJ(Av,sviewer);
1502:     }
1503:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1504:     PetscViewerFlush(viewer);
1505:     MatDestroy(&A);
1506:   }
1507:   return(0);
1508: }

1510: PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer)
1511: {
1513:   PetscBool      iascii,isdraw,issocket,isbinary;

1516:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1517:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1518:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1519:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1520:   if (iascii || isdraw || isbinary || issocket) {
1521:     MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);
1522:   }
1523:   return(0);
1524: }

1526: PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1527: {
1528:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1530:   Vec            bb1 = 0;
1531:   PetscBool      hasop;

1534:   if (flag == SOR_APPLY_UPPER) {
1535:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1536:     return(0);
1537:   }

1539:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1540:     VecDuplicate(bb,&bb1);
1541:   }

1543:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
1544:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1545:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1546:       its--;
1547:     }

1549:     while (its--) {
1550:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1551:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1553:       /* update rhs: bb1 = bb - B*x */
1554:       VecScale(mat->lvec,-1.0);
1555:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1557:       /* local sweep */
1558:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1559:     }
1560:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
1561:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1562:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1563:       its--;
1564:     }
1565:     while (its--) {
1566:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1567:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1569:       /* update rhs: bb1 = bb - B*x */
1570:       VecScale(mat->lvec,-1.0);
1571:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1573:       /* local sweep */
1574:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1575:     }
1576:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
1577:     if (flag & SOR_ZERO_INITIAL_GUESS) {
1578:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1579:       its--;
1580:     }
1581:     while (its--) {
1582:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1583:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

1585:       /* update rhs: bb1 = bb - B*x */
1586:       VecScale(mat->lvec,-1.0);
1587:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

1589:       /* local sweep */
1590:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1591:     }
1592:   } else if (flag & SOR_EISENSTAT) {
1593:     Vec xx1;

1595:     VecDuplicate(bb,&xx1);
1596:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

1598:     VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1599:     VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1600:     if (!mat->diag) {
1601:       MatCreateVecs(matin,&mat->diag,NULL);
1602:       MatGetDiagonal(matin,mat->diag);
1603:     }
1604:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
1605:     if (hasop) {
1606:       MatMultDiagonalBlock(matin,xx,bb1);
1607:     } else {
1608:       VecPointwiseMult(bb1,mat->diag,xx);
1609:     }
1610:     VecAYPX(bb1,(omega-2.0)/omega,bb);

1612:     MatMultAdd(mat->B,mat->lvec,bb1,bb1);

1614:     /* local sweep */
1615:     (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
1616:     VecAXPY(xx,1.0,xx1);
1617:     VecDestroy(&xx1);
1618:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");

1620:   VecDestroy(&bb1);

1622:   matin->factorerrortype = mat->A->factorerrortype;
1623:   return(0);
1624: }

1626: PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B)
1627: {
1628:   Mat            aA,aB,Aperm;
1629:   const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj;
1630:   PetscScalar    *aa,*ba;
1631:   PetscInt       i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest;
1632:   PetscSF        rowsf,sf;
1633:   IS             parcolp = NULL;
1634:   PetscBool      done;

1638:   MatGetLocalSize(A,&m,&n);
1639:   ISGetIndices(rowp,&rwant);
1640:   ISGetIndices(colp,&cwant);
1641:   PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);

1643:   /* Invert row permutation to find out where my rows should go */
1644:   PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);
1645:   PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);
1646:   PetscSFSetFromOptions(rowsf);
1647:   for (i=0; i<m; i++) work[i] = A->rmap->rstart + i;
1648:   PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1649:   PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);

1651:   /* Invert column permutation to find out where my columns should go */
1652:   PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1653:   PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);
1654:   PetscSFSetFromOptions(sf);
1655:   for (i=0; i<n; i++) work[i] = A->cmap->rstart + i;
1656:   PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1657:   PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1658:   PetscSFDestroy(&sf);

1660:   ISRestoreIndices(rowp,&rwant);
1661:   ISRestoreIndices(colp,&cwant);
1662:   MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);

1664:   /* Find out where my gcols should go */
1665:   MatGetSize(aB,NULL,&ng);
1666:   PetscMalloc1(ng,&gcdest);
1667:   PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1668:   PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);
1669:   PetscSFSetFromOptions(sf);
1670:   PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);
1671:   PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);
1672:   PetscSFDestroy(&sf);

1674:   PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);
1675:   MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1676:   MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1677:   for (i=0; i<m; i++) {
1678:     PetscInt    row = rdest[i];
1679:     PetscMPIInt rowner;
1680:     PetscLayoutFindOwner(A->rmap,row,&rowner);
1681:     for (j=ai[i]; j<ai[i+1]; j++) {
1682:       PetscInt    col = cdest[aj[j]];
1683:       PetscMPIInt cowner;
1684:       PetscLayoutFindOwner(A->cmap,col,&cowner); /* Could build an index for the columns to eliminate this search */
1685:       if (rowner == cowner) dnnz[i]++;
1686:       else onnz[i]++;
1687:     }
1688:     for (j=bi[i]; j<bi[i+1]; j++) {
1689:       PetscInt    col = gcdest[bj[j]];
1690:       PetscMPIInt cowner;
1691:       PetscLayoutFindOwner(A->cmap,col,&cowner);
1692:       if (rowner == cowner) dnnz[i]++;
1693:       else onnz[i]++;
1694:     }
1695:   }
1696:   PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);
1697:   PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);
1698:   PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);
1699:   PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);
1700:   PetscSFDestroy(&rowsf);

1702:   MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);
1703:   MatSeqAIJGetArray(aA,&aa);
1704:   MatSeqAIJGetArray(aB,&ba);
1705:   for (i=0; i<m; i++) {
1706:     PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */
1707:     PetscInt j0,rowlen;
1708:     rowlen = ai[i+1] - ai[i];
1709:     for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */
1710:       for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]];
1711:       MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);
1712:     }
1713:     rowlen = bi[i+1] - bi[i];
1714:     for (j0=j=0; j<rowlen; j0=j) {
1715:       for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]];
1716:       MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);
1717:     }
1718:   }
1719:   MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);
1720:   MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);
1721:   MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1722:   MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1723:   MatSeqAIJRestoreArray(aA,&aa);
1724:   MatSeqAIJRestoreArray(aB,&ba);
1725:   PetscFree4(dnnz,onnz,tdnnz,tonnz);
1726:   PetscFree3(work,rdest,cdest);
1727:   PetscFree(gcdest);
1728:   if (parcolp) {ISDestroy(&colp);}
1729:   *B = Aperm;
1730:   return(0);
1731: }

1733: PetscErrorCode  MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
1734: {
1735:   Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;

1739:   MatGetSize(aij->B,NULL,nghosts);
1740:   if (ghosts) *ghosts = aij->garray;
1741:   return(0);
1742: }

1744: PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1745: {
1746:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1747:   Mat            A    = mat->A,B = mat->B;
1749:   PetscLogDouble isend[5],irecv[5];

1752:   info->block_size = 1.0;
1753:   MatGetInfo(A,MAT_LOCAL,info);

1755:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1756:   isend[3] = info->memory;  isend[4] = info->mallocs;

1758:   MatGetInfo(B,MAT_LOCAL,info);

1760:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1761:   isend[3] += info->memory;  isend[4] += info->mallocs;
1762:   if (flag == MAT_LOCAL) {
1763:     info->nz_used      = isend[0];
1764:     info->nz_allocated = isend[1];
1765:     info->nz_unneeded  = isend[2];
1766:     info->memory       = isend[3];
1767:     info->mallocs      = isend[4];
1768:   } else if (flag == MAT_GLOBAL_MAX) {
1769:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_MAX,PetscObjectComm((PetscObject)matin));

1771:     info->nz_used      = irecv[0];
1772:     info->nz_allocated = irecv[1];
1773:     info->nz_unneeded  = irecv[2];
1774:     info->memory       = irecv[3];
1775:     info->mallocs      = irecv[4];
1776:   } else if (flag == MAT_GLOBAL_SUM) {
1777:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_SUM,PetscObjectComm((PetscObject)matin));

1779:     info->nz_used      = irecv[0];
1780:     info->nz_allocated = irecv[1];
1781:     info->nz_unneeded  = irecv[2];
1782:     info->memory       = irecv[3];
1783:     info->mallocs      = irecv[4];
1784:   }
1785:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1786:   info->fill_ratio_needed = 0;
1787:   info->factor_mallocs    = 0;
1788:   return(0);
1789: }

1791: PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg)
1792: {
1793:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

1797:   switch (op) {
1798:   case MAT_NEW_NONZERO_LOCATIONS:
1799:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1800:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1801:   case MAT_KEEP_NONZERO_PATTERN:
1802:   case MAT_NEW_NONZERO_LOCATION_ERR:
1803:   case MAT_USE_INODES:
1804:   case MAT_IGNORE_ZERO_ENTRIES:
1805:     MatCheckPreallocated(A,1);
1806:     MatSetOption(a->A,op,flg);
1807:     MatSetOption(a->B,op,flg);
1808:     break;
1809:   case MAT_ROW_ORIENTED:
1810:     MatCheckPreallocated(A,1);
1811:     a->roworiented = flg;

1813:     MatSetOption(a->A,op,flg);
1814:     MatSetOption(a->B,op,flg);
1815:     break;
1816:   case MAT_NEW_DIAGONALS:
1817:   case MAT_SORTED_FULL:
1818:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1819:     break;
1820:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1821:     a->donotstash = flg;
1822:     break;
1823:   /* Symmetry flags are handled directly by MatSetOption() and they don't affect preallocation */
1824:   case MAT_SPD:
1825:   case MAT_SYMMETRIC:
1826:   case MAT_STRUCTURALLY_SYMMETRIC:
1827:   case MAT_HERMITIAN:
1828:   case MAT_SYMMETRY_ETERNAL:
1829:     break;
1830:   case MAT_SUBMAT_SINGLEIS:
1831:     A->submat_singleis = flg;
1832:     break;
1833:   case MAT_STRUCTURE_ONLY:
1834:     /* The option is handled directly by MatSetOption() */
1835:     break;
1836:   default:
1837:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1838:   }
1839:   return(0);
1840: }

1842: PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1843: {
1844:   Mat_MPIAIJ     *mat = (Mat_MPIAIJ*)matin->data;
1845:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1847:   PetscInt       i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart;
1848:   PetscInt       nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend;
1849:   PetscInt       *cmap,*idx_p;

1852:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1853:   mat->getrowactive = PETSC_TRUE;

1855:   if (!mat->rowvalues && (idx || v)) {
1856:     /*
1857:         allocate enough space to hold information from the longest row.
1858:     */
1859:     Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data;
1860:     PetscInt   max = 1,tmp;
1861:     for (i=0; i<matin->rmap->n; i++) {
1862:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1863:       if (max < tmp) max = tmp;
1864:     }
1865:     PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);
1866:   }

1868:   if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows");
1869:   lrow = row - rstart;

1871:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1872:   if (!v)   {pvA = 0; pvB = 0;}
1873:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1874:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1875:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1876:   nztot = nzA + nzB;

1878:   cmap = mat->garray;
1879:   if (v  || idx) {
1880:     if (nztot) {
1881:       /* Sort by increasing column numbers, assuming A and B already sorted */
1882:       PetscInt imark = -1;
1883:       if (v) {
1884:         *v = v_p = mat->rowvalues;
1885:         for (i=0; i<nzB; i++) {
1886:           if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i];
1887:           else break;
1888:         }
1889:         imark = i;
1890:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1891:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1892:       }
1893:       if (idx) {
1894:         *idx = idx_p = mat->rowindices;
1895:         if (imark > -1) {
1896:           for (i=0; i<imark; i++) {
1897:             idx_p[i] = cmap[cworkB[i]];
1898:           }
1899:         } else {
1900:           for (i=0; i<nzB; i++) {
1901:             if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]];
1902:             else break;
1903:           }
1904:           imark = i;
1905:         }
1906:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart + cworkA[i];
1907:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]];
1908:       }
1909:     } else {
1910:       if (idx) *idx = 0;
1911:       if (v)   *v   = 0;
1912:     }
1913:   }
1914:   *nz  = nztot;
1915:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1916:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1917:   return(0);
1918: }

1920: PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1921: {
1922:   Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;

1925:   if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1926:   aij->getrowactive = PETSC_FALSE;
1927:   return(0);
1928: }

1930: PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm)
1931: {
1932:   Mat_MPIAIJ     *aij  = (Mat_MPIAIJ*)mat->data;
1933:   Mat_SeqAIJ     *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data;
1935:   PetscInt       i,j,cstart = mat->cmap->rstart;
1936:   PetscReal      sum = 0.0;
1937:   MatScalar      *v;

1940:   if (aij->size == 1) {
1941:      MatNorm(aij->A,type,norm);
1942:   } else {
1943:     if (type == NORM_FROBENIUS) {
1944:       v = amat->a;
1945:       for (i=0; i<amat->nz; i++) {
1946:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1947:       }
1948:       v = bmat->a;
1949:       for (i=0; i<bmat->nz; i++) {
1950:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1951:       }
1952:       MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1953:       *norm = PetscSqrtReal(*norm);
1954:       PetscLogFlops(2*amat->nz+2*bmat->nz);
1955:     } else if (type == NORM_1) { /* max column norm */
1956:       PetscReal *tmp,*tmp2;
1957:       PetscInt  *jj,*garray = aij->garray;
1958:       PetscCalloc1(mat->cmap->N+1,&tmp);
1959:       PetscMalloc1(mat->cmap->N+1,&tmp2);
1960:       *norm = 0.0;
1961:       v     = amat->a; jj = amat->j;
1962:       for (j=0; j<amat->nz; j++) {
1963:         tmp[cstart + *jj++] += PetscAbsScalar(*v);  v++;
1964:       }
1965:       v = bmat->a; jj = bmat->j;
1966:       for (j=0; j<bmat->nz; j++) {
1967:         tmp[garray[*jj++]] += PetscAbsScalar(*v); v++;
1968:       }
1969:       MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1970:       for (j=0; j<mat->cmap->N; j++) {
1971:         if (tmp2[j] > *norm) *norm = tmp2[j];
1972:       }
1973:       PetscFree(tmp);
1974:       PetscFree(tmp2);
1975:       PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1976:     } else if (type == NORM_INFINITY) { /* max row norm */
1977:       PetscReal ntemp = 0.0;
1978:       for (j=0; j<aij->A->rmap->n; j++) {
1979:         v   = amat->a + amat->i[j];
1980:         sum = 0.0;
1981:         for (i=0; i<amat->i[j+1]-amat->i[j]; i++) {
1982:           sum += PetscAbsScalar(*v); v++;
1983:         }
1984:         v = bmat->a + bmat->i[j];
1985:         for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) {
1986:           sum += PetscAbsScalar(*v); v++;
1987:         }
1988:         if (sum > ntemp) ntemp = sum;
1989:       }
1990:       MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
1991:       PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
1992:     } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm");
1993:   }
1994:   return(0);
1995: }

1997: PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout)
1998: {
1999:   Mat_MPIAIJ      *a    =(Mat_MPIAIJ*)A->data,*b;
2000:   Mat_SeqAIJ      *Aloc =(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data,*sub_B_diag;
2001:   PetscInt        M     = A->rmap->N,N=A->cmap->N,ma,na,mb,nb,row,*cols,*cols_tmp,*B_diag_ilen,i,ncol,A_diag_ncol;
2002:   const PetscInt  *ai,*aj,*bi,*bj,*B_diag_i;
2003:   PetscErrorCode  ierr;
2004:   Mat             B,A_diag,*B_diag;
2005:   const MatScalar *array;

2008:   ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n;
2009:   ai = Aloc->i; aj = Aloc->j;
2010:   bi = Bloc->i; bj = Bloc->j;
2011:   if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
2012:     PetscInt             *d_nnz,*g_nnz,*o_nnz;
2013:     PetscSFNode          *oloc;
2014:     PETSC_UNUSED PetscSF sf;

2016:     PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);
2017:     /* compute d_nnz for preallocation */
2018:     PetscArrayzero(d_nnz,na);
2019:     for (i=0; i<ai[ma]; i++) {
2020:       d_nnz[aj[i]]++;
2021:     }
2022:     /* compute local off-diagonal contributions */
2023:     PetscArrayzero(g_nnz,nb);
2024:     for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++;
2025:     /* map those to global */
2026:     PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
2027:     PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);
2028:     PetscSFSetFromOptions(sf);
2029:     PetscArrayzero(o_nnz,na);
2030:     PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2031:     PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2032:     PetscSFDestroy(&sf);

2034:     MatCreate(PetscObjectComm((PetscObject)A),&B);
2035:     MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
2036:     MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));
2037:     MatSetType(B,((PetscObject)A)->type_name);
2038:     MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
2039:     PetscFree4(d_nnz,o_nnz,g_nnz,oloc);
2040:   } else {
2041:     B    = *matout;
2042:     MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
2043:   }

2045:   b           = (Mat_MPIAIJ*)B->data;
2046:   A_diag      = a->A;
2047:   B_diag      = &b->A;
2048:   sub_B_diag  = (Mat_SeqAIJ*)(*B_diag)->data;
2049:   A_diag_ncol = A_diag->cmap->N;
2050:   B_diag_ilen = sub_B_diag->ilen;
2051:   B_diag_i    = sub_B_diag->i;

2053:   /* Set ilen for diagonal of B */
2054:   for (i=0; i<A_diag_ncol; i++) {
2055:     B_diag_ilen[i] = B_diag_i[i+1] - B_diag_i[i];
2056:   }

2058:   /* Transpose the diagonal part of the matrix. In contrast to the offdiagonal part, this can be done
2059:   very quickly (=without using MatSetValues), because all writes are local. */
2060:   MatTranspose(A_diag,MAT_REUSE_MATRIX,B_diag);

2062:   /* copy over the B part */
2063:   PetscMalloc1(bi[mb],&cols);
2064:   array = Bloc->a;
2065:   row   = A->rmap->rstart;
2066:   for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]];
2067:   cols_tmp = cols;
2068:   for (i=0; i<mb; i++) {
2069:     ncol = bi[i+1]-bi[i];
2070:     MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);
2071:     row++;
2072:     array += ncol; cols_tmp += ncol;
2073:   }
2074:   PetscFree(cols);

2076:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2077:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2078:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) {
2079:     *matout = B;
2080:   } else {
2081:     MatHeaderMerge(A,&B);
2082:   }
2083:   return(0);
2084: }

2086: PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr)
2087: {
2088:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
2089:   Mat            a    = aij->A,b = aij->B;
2091:   PetscInt       s1,s2,s3;

2094:   MatGetLocalSize(mat,&s2,&s3);
2095:   if (rr) {
2096:     VecGetLocalSize(rr,&s1);
2097:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
2098:     /* Overlap communication with computation. */
2099:     VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2100:   }
2101:   if (ll) {
2102:     VecGetLocalSize(ll,&s1);
2103:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
2104:     (*b->ops->diagonalscale)(b,ll,0);
2105:   }
2106:   /* scale  the diagonal block */
2107:   (*a->ops->diagonalscale)(a,ll,rr);

2109:   if (rr) {
2110:     /* Do a scatter end and then right scale the off-diagonal block */
2111:     VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2112:     (*b->ops->diagonalscale)(b,0,aij->lvec);
2113:   }
2114:   return(0);
2115: }

2117: PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A)
2118: {
2119:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2123:   MatSetUnfactored(a->A);
2124:   return(0);
2125: }

2127: PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool  *flag)
2128: {
2129:   Mat_MPIAIJ     *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data;
2130:   Mat            a,b,c,d;
2131:   PetscBool      flg;

2135:   a = matA->A; b = matA->B;
2136:   c = matB->A; d = matB->B;

2138:   MatEqual(a,c,&flg);
2139:   if (flg) {
2140:     MatEqual(b,d,&flg);
2141:   }
2142:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
2143:   return(0);
2144: }

2146: PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str)
2147: {
2149:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2150:   Mat_MPIAIJ     *b = (Mat_MPIAIJ*)B->data;

2153:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
2154:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
2155:     /* because of the column compression in the off-processor part of the matrix a->B,
2156:        the number of columns in a->B and b->B may be different, hence we cannot call
2157:        the MatCopy() directly on the two parts. If need be, we can provide a more
2158:        efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
2159:        then copying the submatrices */
2160:     MatCopy_Basic(A,B,str);
2161:   } else {
2162:     MatCopy(a->A,b->A,str);
2163:     MatCopy(a->B,b->B,str);
2164:   }
2165:   PetscObjectStateIncrease((PetscObject)B);
2166:   return(0);
2167: }

2169: PetscErrorCode MatSetUp_MPIAIJ(Mat A)
2170: {

2174:   MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
2175:   return(0);
2176: }

2178: /*
2179:    Computes the number of nonzeros per row needed for preallocation when X and Y
2180:    have different nonzero structure.
2181: */
2182: 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)
2183: {
2184:   PetscInt       i,j,k,nzx,nzy;

2187:   /* Set the number of nonzeros in the new matrix */
2188:   for (i=0; i<m; i++) {
2189:     const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i];
2190:     nzx = xi[i+1] - xi[i];
2191:     nzy = yi[i+1] - yi[i];
2192:     nnz[i] = 0;
2193:     for (j=0,k=0; j<nzx; j++) {                   /* Point in X */
2194:       for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */
2195:       if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++;             /* Skip duplicate */
2196:       nnz[i]++;
2197:     }
2198:     for (; k<nzy; k++) nnz[i]++;
2199:   }
2200:   return(0);
2201: }

2203: /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */
2204: static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
2205: {
2207:   PetscInt       m = Y->rmap->N;
2208:   Mat_SeqAIJ     *x = (Mat_SeqAIJ*)X->data;
2209:   Mat_SeqAIJ     *y = (Mat_SeqAIJ*)Y->data;

2212:   MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
2213:   return(0);
2214: }

2216: PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2217: {
2219:   Mat_MPIAIJ     *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data;
2220:   PetscBLASInt   bnz,one=1;
2221:   Mat_SeqAIJ     *x,*y;

2224:   if (str == SAME_NONZERO_PATTERN) {
2225:     PetscScalar alpha = a;
2226:     x    = (Mat_SeqAIJ*)xx->A->data;
2227:     PetscBLASIntCast(x->nz,&bnz);
2228:     y    = (Mat_SeqAIJ*)yy->A->data;
2229:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2230:     x    = (Mat_SeqAIJ*)xx->B->data;
2231:     y    = (Mat_SeqAIJ*)yy->B->data;
2232:     PetscBLASIntCast(x->nz,&bnz);
2233:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2234:     PetscObjectStateIncrease((PetscObject)Y);
2235:     /* the MatAXPY_Basic* subroutines calls MatAssembly, so the matrix on the GPU
2236:        will be updated */
2237: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
2238:     if (Y->offloadmask != PETSC_OFFLOAD_UNALLOCATED) {
2239:       Y->offloadmask = PETSC_OFFLOAD_CPU;
2240:     }
2241: #endif
2242:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2243:     MatAXPY_Basic(Y,a,X,str);
2244:   } else {
2245:     Mat      B;
2246:     PetscInt *nnz_d,*nnz_o;
2247:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
2248:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
2249:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
2250:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2251:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2252:     MatSetBlockSizesFromMats(B,Y,Y);
2253:     MatSetType(B,MATMPIAIJ);
2254:     MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);
2255:     MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
2256:     MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);
2257:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2258:     MatHeaderReplace(Y,&B);
2259:     PetscFree(nnz_d);
2260:     PetscFree(nnz_o);
2261:   }
2262:   return(0);
2263: }

2265: extern PetscErrorCode  MatConjugate_SeqAIJ(Mat);

2267: PetscErrorCode  MatConjugate_MPIAIJ(Mat mat)
2268: {
2269: #if defined(PETSC_USE_COMPLEX)
2271:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2274:   MatConjugate_SeqAIJ(aij->A);
2275:   MatConjugate_SeqAIJ(aij->B);
2276: #else
2278: #endif
2279:   return(0);
2280: }

2282: PetscErrorCode MatRealPart_MPIAIJ(Mat A)
2283: {
2284:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2288:   MatRealPart(a->A);
2289:   MatRealPart(a->B);
2290:   return(0);
2291: }

2293: PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A)
2294: {
2295:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2299:   MatImaginaryPart(a->A);
2300:   MatImaginaryPart(a->B);
2301:   return(0);
2302: }

2304: PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2305: {
2306:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2308:   PetscInt       i,*idxb = 0;
2309:   PetscScalar    *va,*vb;
2310:   Vec            vtmp;

2313:   MatGetRowMaxAbs(a->A,v,idx);
2314:   VecGetArray(v,&va);
2315:   if (idx) {
2316:     for (i=0; i<A->rmap->n; i++) {
2317:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2318:     }
2319:   }

2321:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2322:   if (idx) {
2323:     PetscMalloc1(A->rmap->n,&idxb);
2324:   }
2325:   MatGetRowMaxAbs(a->B,vtmp,idxb);
2326:   VecGetArray(vtmp,&vb);

2328:   for (i=0; i<A->rmap->n; i++) {
2329:     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
2330:       va[i] = vb[i];
2331:       if (idx) idx[i] = a->garray[idxb[i]];
2332:     }
2333:   }

2335:   VecRestoreArray(v,&va);
2336:   VecRestoreArray(vtmp,&vb);
2337:   PetscFree(idxb);
2338:   VecDestroy(&vtmp);
2339:   return(0);
2340: }

2342: PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2343: {
2344:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
2346:   PetscInt       i,*idxb = 0;
2347:   PetscScalar    *va,*vb;
2348:   Vec            vtmp;

2351:   MatGetRowMinAbs(a->A,v,idx);
2352:   VecGetArray(v,&va);
2353:   if (idx) {
2354:     for (i=0; i<A->cmap->n; i++) {
2355:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2356:     }
2357:   }

2359:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2360:   if (idx) {
2361:     PetscMalloc1(A->rmap->n,&idxb);
2362:   }
2363:   MatGetRowMinAbs(a->B,vtmp,idxb);
2364:   VecGetArray(vtmp,&vb);

2366:   for (i=0; i<A->rmap->n; i++) {
2367:     if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) {
2368:       va[i] = vb[i];
2369:       if (idx) idx[i] = a->garray[idxb[i]];
2370:     }
2371:   }

2373:   VecRestoreArray(v,&va);
2374:   VecRestoreArray(vtmp,&vb);
2375:   PetscFree(idxb);
2376:   VecDestroy(&vtmp);
2377:   return(0);
2378: }

2380: PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2381: {
2382:   Mat_MPIAIJ     *mat   = (Mat_MPIAIJ*) A->data;
2383:   PetscInt       n      = A->rmap->n;
2384:   PetscInt       cstart = A->cmap->rstart;
2385:   PetscInt       *cmap  = mat->garray;
2386:   PetscInt       *diagIdx, *offdiagIdx;
2387:   Vec            diagV, offdiagV;
2388:   PetscScalar    *a, *diagA, *offdiagA;
2389:   PetscInt       r;

2393:   PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2394:   VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);
2395:   VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);
2396:   MatGetRowMin(mat->A, diagV,    diagIdx);
2397:   MatGetRowMin(mat->B, offdiagV, offdiagIdx);
2398:   VecGetArray(v,        &a);
2399:   VecGetArray(diagV,    &diagA);
2400:   VecGetArray(offdiagV, &offdiagA);
2401:   for (r = 0; r < n; ++r) {
2402:     if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) {
2403:       a[r]   = diagA[r];
2404:       idx[r] = cstart + diagIdx[r];
2405:     } else {
2406:       a[r]   = offdiagA[r];
2407:       idx[r] = cmap[offdiagIdx[r]];
2408:     }
2409:   }
2410:   VecRestoreArray(v,        &a);
2411:   VecRestoreArray(diagV,    &diagA);
2412:   VecRestoreArray(offdiagV, &offdiagA);
2413:   VecDestroy(&diagV);
2414:   VecDestroy(&offdiagV);
2415:   PetscFree2(diagIdx, offdiagIdx);
2416:   return(0);
2417: }

2419: PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2420: {
2421:   Mat_MPIAIJ     *mat   = (Mat_MPIAIJ*) A->data;
2422:   PetscInt       n      = A->rmap->n;
2423:   PetscInt       cstart = A->cmap->rstart;
2424:   PetscInt       *cmap  = mat->garray;
2425:   PetscInt       *diagIdx, *offdiagIdx;
2426:   Vec            diagV, offdiagV;
2427:   PetscScalar    *a, *diagA, *offdiagA;
2428:   PetscInt       r;

2432:   PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2433:   VecCreateSeq(PETSC_COMM_SELF, n, &diagV);
2434:   VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);
2435:   MatGetRowMax(mat->A, diagV,    diagIdx);
2436:   MatGetRowMax(mat->B, offdiagV, offdiagIdx);
2437:   VecGetArray(v,        &a);
2438:   VecGetArray(diagV,    &diagA);
2439:   VecGetArray(offdiagV, &offdiagA);
2440:   for (r = 0; r < n; ++r) {
2441:     if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) {
2442:       a[r]   = diagA[r];
2443:       idx[r] = cstart + diagIdx[r];
2444:     } else {
2445:       a[r]   = offdiagA[r];
2446:       idx[r] = cmap[offdiagIdx[r]];
2447:     }
2448:   }
2449:   VecRestoreArray(v,        &a);
2450:   VecRestoreArray(diagV,    &diagA);
2451:   VecRestoreArray(offdiagV, &offdiagA);
2452:   VecDestroy(&diagV);
2453:   VecDestroy(&offdiagV);
2454:   PetscFree2(diagIdx, offdiagIdx);
2455:   return(0);
2456: }

2458: PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat)
2459: {
2461:   Mat            *dummy;

2464:   MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);
2465:   *newmat = *dummy;
2466:   PetscFree(dummy);
2467:   return(0);
2468: }

2470: PetscErrorCode  MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values)
2471: {
2472:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*) A->data;

2476:   MatInvertBlockDiagonal(a->A,values);
2477:   A->factorerrortype = a->A->factorerrortype;
2478:   return(0);
2479: }

2481: static PetscErrorCode  MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx)
2482: {
2484:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)x->data;

2487:   if (!x->assembled && !x->preallocated) SETERRQ(PetscObjectComm((PetscObject)x), PETSC_ERR_ARG_WRONGSTATE, "MatSetRandom on an unassembled and unpreallocated MATMPIAIJ is not allowed");
2488:   MatSetRandom(aij->A,rctx);
2489:   if (x->assembled) {
2490:     MatSetRandom(aij->B,rctx);
2491:   } else {
2492:     MatSetRandomSkipColumnRange_SeqAIJ_Private(aij->B,x->cmap->rstart,x->cmap->rend,rctx);
2493:   }
2494:   MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
2495:   MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
2496:   return(0);
2497: }

2499: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc)
2500: {
2502:   if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable;
2503:   else A->ops->increaseoverlap    = MatIncreaseOverlap_MPIAIJ;
2504:   return(0);
2505: }

2507: /*@
2508:    MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap

2510:    Collective on Mat

2512:    Input Parameters:
2513: +    A - the matrix
2514: -    sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm)

2516:  Level: advanced

2518: @*/
2519: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc)
2520: {
2521:   PetscErrorCode       ierr;

2524:   PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));
2525:   return(0);
2526: }

2528: PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A)
2529: {
2530:   PetscErrorCode       ierr;
2531:   PetscBool            sc = PETSC_FALSE,flg;

2534:   PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");
2535:   if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE;
2536:   PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);
2537:   if (flg) {
2538:     MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);
2539:   }
2540:   PetscOptionsTail();
2541:   return(0);
2542: }

2544: PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a)
2545: {
2547:   Mat_MPIAIJ     *maij = (Mat_MPIAIJ*)Y->data;
2548:   Mat_SeqAIJ     *aij = (Mat_SeqAIJ*)maij->A->data;

2551:   if (!Y->preallocated) {
2552:     MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);
2553:   } else if (!aij->nz) {
2554:     PetscInt nonew = aij->nonew;
2555:     MatSeqAIJSetPreallocation(maij->A,1,NULL);
2556:     aij->nonew = nonew;
2557:   }
2558:   MatShift_Basic(Y,a);
2559:   return(0);
2560: }

2562: PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool  *missing,PetscInt *d)
2563: {
2564:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2568:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
2569:   MatMissingDiagonal(a->A,missing,d);
2570:   if (d) {
2571:     PetscInt rstart;
2572:     MatGetOwnershipRange(A,&rstart,NULL);
2573:     *d += rstart;

2575:   }
2576:   return(0);
2577: }

2579: PetscErrorCode MatInvertVariableBlockDiagonal_MPIAIJ(Mat A,PetscInt nblocks,const PetscInt *bsizes,PetscScalar *diag)
2580: {
2581:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

2585:   MatInvertVariableBlockDiagonal(a->A,nblocks,bsizes,diag);
2586:   return(0);
2587: }

2589: /* -------------------------------------------------------------------*/
2590: static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ,
2591:                                        MatGetRow_MPIAIJ,
2592:                                        MatRestoreRow_MPIAIJ,
2593:                                        MatMult_MPIAIJ,
2594:                                 /* 4*/ MatMultAdd_MPIAIJ,
2595:                                        MatMultTranspose_MPIAIJ,
2596:                                        MatMultTransposeAdd_MPIAIJ,
2597:                                        0,
2598:                                        0,
2599:                                        0,
2600:                                 /*10*/ 0,
2601:                                        0,
2602:                                        0,
2603:                                        MatSOR_MPIAIJ,
2604:                                        MatTranspose_MPIAIJ,
2605:                                 /*15*/ MatGetInfo_MPIAIJ,
2606:                                        MatEqual_MPIAIJ,
2607:                                        MatGetDiagonal_MPIAIJ,
2608:                                        MatDiagonalScale_MPIAIJ,
2609:                                        MatNorm_MPIAIJ,
2610:                                 /*20*/ MatAssemblyBegin_MPIAIJ,
2611:                                        MatAssemblyEnd_MPIAIJ,
2612:                                        MatSetOption_MPIAIJ,
2613:                                        MatZeroEntries_MPIAIJ,
2614:                                 /*24*/ MatZeroRows_MPIAIJ,
2615:                                        0,
2616:                                        0,
2617:                                        0,
2618:                                        0,
2619:                                 /*29*/ MatSetUp_MPIAIJ,
2620:                                        0,
2621:                                        0,
2622:                                        MatGetDiagonalBlock_MPIAIJ,
2623:                                        0,
2624:                                 /*34*/ MatDuplicate_MPIAIJ,
2625:                                        0,
2626:                                        0,
2627:                                        0,
2628:                                        0,
2629:                                 /*39*/ MatAXPY_MPIAIJ,
2630:                                        MatCreateSubMatrices_MPIAIJ,
2631:                                        MatIncreaseOverlap_MPIAIJ,
2632:                                        MatGetValues_MPIAIJ,
2633:                                        MatCopy_MPIAIJ,
2634:                                 /*44*/ MatGetRowMax_MPIAIJ,
2635:                                        MatScale_MPIAIJ,
2636:                                        MatShift_MPIAIJ,
2637:                                        MatDiagonalSet_MPIAIJ,
2638:                                        MatZeroRowsColumns_MPIAIJ,
2639:                                 /*49*/ MatSetRandom_MPIAIJ,
2640:                                        0,
2641:                                        0,
2642:                                        0,
2643:                                        0,
2644:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
2645:                                        0,
2646:                                        MatSetUnfactored_MPIAIJ,
2647:                                        MatPermute_MPIAIJ,
2648:                                        0,
2649:                                 /*59*/ MatCreateSubMatrix_MPIAIJ,
2650:                                        MatDestroy_MPIAIJ,
2651:                                        MatView_MPIAIJ,
2652:                                        0,
2653:                                        0,
2654:                                 /*64*/ 0,
2655:                                        MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ,
2656:                                        0,
2657:                                        0,
2658:                                        0,
2659:                                 /*69*/ MatGetRowMaxAbs_MPIAIJ,
2660:                                        MatGetRowMinAbs_MPIAIJ,
2661:                                        0,
2662:                                        0,
2663:                                        0,
2664:                                        0,
2665:                                 /*75*/ MatFDColoringApply_AIJ,
2666:                                        MatSetFromOptions_MPIAIJ,
2667:                                        0,
2668:                                        0,
2669:                                        MatFindZeroDiagonals_MPIAIJ,
2670:                                 /*80*/ 0,
2671:                                        0,
2672:                                        0,
2673:                                 /*83*/ MatLoad_MPIAIJ,
2674:                                        MatIsSymmetric_MPIAIJ,
2675:                                        0,
2676:                                        0,
2677:                                        0,
2678:                                        0,
2679:                                 /*89*/ 0,
2680:                                        0,
2681:                                        MatMatMultNumeric_MPIAIJ_MPIAIJ,
2682:                                        0,
2683:                                        0,
2684:                                 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ,
2685:                                        0,
2686:                                        0,
2687:                                        0,
2688:                                        MatBindToCPU_MPIAIJ,
2689:                                 /*99*/ MatProductSetFromOptions_MPIAIJ,
2690:                                        0,
2691:                                        0,
2692:                                        MatConjugate_MPIAIJ,
2693:                                        0,
2694:                                 /*104*/MatSetValuesRow_MPIAIJ,
2695:                                        MatRealPart_MPIAIJ,
2696:                                        MatImaginaryPart_MPIAIJ,
2697:                                        0,
2698:                                        0,
2699:                                 /*109*/0,
2700:                                        0,
2701:                                        MatGetRowMin_MPIAIJ,
2702:                                        0,
2703:                                        MatMissingDiagonal_MPIAIJ,
2704:                                 /*114*/MatGetSeqNonzeroStructure_MPIAIJ,
2705:                                        0,
2706:                                        MatGetGhosts_MPIAIJ,
2707:                                        0,
2708:                                        0,
2709:                                 /*119*/0,
2710:                                        0,
2711:                                        0,
2712:                                        0,
2713:                                        MatGetMultiProcBlock_MPIAIJ,
2714:                                 /*124*/MatFindNonzeroRows_MPIAIJ,
2715:                                        MatGetColumnNorms_MPIAIJ,
2716:                                        MatInvertBlockDiagonal_MPIAIJ,
2717:                                        MatInvertVariableBlockDiagonal_MPIAIJ,
2718:                                        MatCreateSubMatricesMPI_MPIAIJ,
2719:                                 /*129*/0,
2720:                                        0,
2721:                                        0,
2722:                                        MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ,
2723:                                        0,
2724:                                 /*134*/0,
2725:                                        0,
2726:                                        0,
2727:                                        0,
2728:                                        0,
2729:                                 /*139*/MatSetBlockSizes_MPIAIJ,
2730:                                        0,
2731:                                        0,
2732:                                        MatFDColoringSetUp_MPIXAIJ,
2733:                                        MatFindOffBlockDiagonalEntries_MPIAIJ,
2734:                                        MatCreateMPIMatConcatenateSeqMat_MPIAIJ,
2735:                                 /*145*/0,
2736:                                        0,
2737:                                        0
2738: };

2740: /* ----------------------------------------------------------------------------------------*/

2742: PetscErrorCode  MatStoreValues_MPIAIJ(Mat mat)
2743: {
2744:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2748:   MatStoreValues(aij->A);
2749:   MatStoreValues(aij->B);
2750:   return(0);
2751: }

2753: PetscErrorCode  MatRetrieveValues_MPIAIJ(Mat mat)
2754: {
2755:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

2759:   MatRetrieveValues(aij->A);
2760:   MatRetrieveValues(aij->B);
2761:   return(0);
2762: }

2764: PetscErrorCode  MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2765: {
2766:   Mat_MPIAIJ     *b;
2768:   PetscMPIInt    size;

2771:   PetscLayoutSetUp(B->rmap);
2772:   PetscLayoutSetUp(B->cmap);
2773:   b = (Mat_MPIAIJ*)B->data;

2775: #if defined(PETSC_USE_CTABLE)
2776:   PetscTableDestroy(&b->colmap);
2777: #else
2778:   PetscFree(b->colmap);
2779: #endif
2780:   PetscFree(b->garray);
2781:   VecDestroy(&b->lvec);
2782:   VecScatterDestroy(&b->Mvctx);

2784:   /* Because the B will have been resized we simply destroy it and create a new one each time */
2785:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
2786:   MatDestroy(&b->B);
2787:   MatCreate(PETSC_COMM_SELF,&b->B);
2788:   MatSetSizes(b->B,B->rmap->n,size > 1 ? B->cmap->N : 0,B->rmap->n,size > 1 ? B->cmap->N : 0);
2789:   MatSetBlockSizesFromMats(b->B,B,B);
2790:   MatSetType(b->B,MATSEQAIJ);
2791:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

2793:   if (!B->preallocated) {
2794:     MatCreate(PETSC_COMM_SELF,&b->A);
2795:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2796:     MatSetBlockSizesFromMats(b->A,B,B);
2797:     MatSetType(b->A,MATSEQAIJ);
2798:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2799:   }

2801:   MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);
2802:   MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);
2803:   B->preallocated  = PETSC_TRUE;
2804:   B->was_assembled = PETSC_FALSE;
2805:   B->assembled     = PETSC_FALSE;
2806:   return(0);
2807: }

2809: PetscErrorCode MatResetPreallocation_MPIAIJ(Mat B)
2810: {
2811:   Mat_MPIAIJ     *b;

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

2820: #if defined(PETSC_USE_CTABLE)
2821:   PetscTableDestroy(&b->colmap);
2822: #else
2823:   PetscFree(b->colmap);
2824: #endif
2825:   PetscFree(b->garray);
2826:   VecDestroy(&b->lvec);
2827:   VecScatterDestroy(&b->Mvctx);

2829:   MatResetPreallocation(b->A);
2830:   MatResetPreallocation(b->B);
2831:   B->preallocated  = PETSC_TRUE;
2832:   B->was_assembled = PETSC_FALSE;
2833:   B->assembled = PETSC_FALSE;
2834:   return(0);
2835: }

2837: PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2838: {
2839:   Mat            mat;
2840:   Mat_MPIAIJ     *a,*oldmat = (Mat_MPIAIJ*)matin->data;

2844:   *newmat = 0;
2845:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2846:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2847:   MatSetBlockSizesFromMats(mat,matin,matin);
2848:   MatSetType(mat,((PetscObject)matin)->type_name);
2849:   a       = (Mat_MPIAIJ*)mat->data;

2851:   mat->factortype   = matin->factortype;
2852:   mat->assembled    = matin->assembled;
2853:   mat->insertmode   = NOT_SET_VALUES;
2854:   mat->preallocated = matin->preallocated;

2856:   a->size         = oldmat->size;
2857:   a->rank         = oldmat->rank;
2858:   a->donotstash   = oldmat->donotstash;
2859:   a->roworiented  = oldmat->roworiented;
2860:   a->rowindices   = NULL;
2861:   a->rowvalues    = NULL;
2862:   a->getrowactive = PETSC_FALSE;

2864:   PetscLayoutReference(matin->rmap,&mat->rmap);
2865:   PetscLayoutReference(matin->cmap,&mat->cmap);

2867:   if (oldmat->colmap) {
2868: #if defined(PETSC_USE_CTABLE)
2869:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2870: #else
2871:     PetscMalloc1(mat->cmap->N,&a->colmap);
2872:     PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
2873:     PetscArraycpy(a->colmap,oldmat->colmap,mat->cmap->N);
2874: #endif
2875:   } else a->colmap = NULL;
2876:   if (oldmat->garray) {
2877:     PetscInt len;
2878:     len  = oldmat->B->cmap->n;
2879:     PetscMalloc1(len+1,&a->garray);
2880:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2881:     if (len) { PetscArraycpy(a->garray,oldmat->garray,len); }
2882:   } else a->garray = NULL;

2884:   /* It may happen MatDuplicate is called with a non-assembled matrix
2885:      In fact, MatDuplicate only requires the matrix to be preallocated
2886:      This may happen inside a DMCreateMatrix_Shell */
2887:   if (oldmat->lvec) {
2888:     VecDuplicate(oldmat->lvec,&a->lvec);
2889:     PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2890:   }
2891:   if (oldmat->Mvctx) {
2892:     VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2893:     PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
2894:   }
2895:   if (oldmat->Mvctx_mpi1) {
2896:     VecScatterCopy(oldmat->Mvctx_mpi1,&a->Mvctx_mpi1);
2897:     PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx_mpi1);
2898:   }

2900:   MatDuplicate(oldmat->A,cpvalues,&a->A);
2901:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2902:   MatDuplicate(oldmat->B,cpvalues,&a->B);
2903:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2904:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2905:   *newmat = mat;
2906:   return(0);
2907: }

2909: PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer)
2910: {
2911:   PetscBool      isbinary, ishdf5;

2917:   /* force binary viewer to load .info file if it has not yet done so */
2918:   PetscViewerSetUp(viewer);
2919:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
2920:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERHDF5,  &ishdf5);
2921:   if (isbinary) {
2922:     MatLoad_MPIAIJ_Binary(newMat,viewer);
2923:   } else if (ishdf5) {
2924: #if defined(PETSC_HAVE_HDF5)
2925:     MatLoad_AIJ_HDF5(newMat,viewer);
2926: #else
2927:     SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"HDF5 not supported in this build.\nPlease reconfigure using --download-hdf5");
2928: #endif
2929:   } else {
2930:     SETERRQ2(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newMat)->type_name);
2931:   }
2932:   return(0);
2933: }

2935: PetscErrorCode MatLoad_MPIAIJ_Binary(Mat mat, PetscViewer viewer)
2936: {
2937:   PetscInt       header[4],M,N,m,nz,rows,cols,sum,i;
2938:   PetscInt       *rowidxs,*colidxs;
2939:   PetscScalar    *matvals;

2943:   PetscViewerSetUp(viewer);

2945:   /* read in matrix header */
2946:   PetscViewerBinaryRead(viewer,header,4,NULL,PETSC_INT);
2947:   if (header[0] != MAT_FILE_CLASSID) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Not a matrix object in file");
2948:   M  = header[1]; N = header[2]; nz = header[3];
2949:   if (M < 0) SETERRQ1(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Matrix row size (%D) in file is negative",M);
2950:   if (N < 0) SETERRQ1(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Matrix column size (%D) in file is negative",N);
2951:   if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk, cannot load as MPIAIJ");

2953:   /* set block sizes from the viewer's .info file */
2954:   MatLoad_Binary_BlockSizes(mat,viewer);
2955:   /* set global sizes if not set already */
2956:   if (mat->rmap->N < 0) mat->rmap->N = M;
2957:   if (mat->cmap->N < 0) mat->cmap->N = N;
2958:   PetscLayoutSetUp(mat->rmap);
2959:   PetscLayoutSetUp(mat->cmap);

2961:   /* check if the matrix sizes are correct */
2962:   MatGetSize(mat,&rows,&cols);
2963:   if (M != rows || N != cols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different sizes (%D, %D) than the input matrix (%D, %D)",M,N,rows,cols);

2965:   /* read in row lengths and build row indices */
2966:   MatGetLocalSize(mat,&m,NULL);
2967:   PetscMalloc1(m+1,&rowidxs);
2968:   PetscViewerBinaryReadAll(viewer,rowidxs+1,m,PETSC_DECIDE,M,PETSC_INT);
2969:   rowidxs[0] = 0; for (i=0; i<m; i++) rowidxs[i+1] += rowidxs[i];
2970:   MPIU_Allreduce(&rowidxs[m],&sum,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)viewer));
2971:   if (sum != nz) SETERRQ2(PetscObjectComm((PetscObject)viewer),PETSC_ERR_FILE_UNEXPECTED,"Inconsistent matrix data in file: nonzeros = %D, sum-row-lengths = %D\n",nz,sum);
2972:   /* read in column indices and matrix values */
2973:   PetscMalloc2(rowidxs[m],&colidxs,rowidxs[m],&matvals);
2974:   PetscViewerBinaryReadAll(viewer,colidxs,rowidxs[m],PETSC_DETERMINE,PETSC_DETERMINE,PETSC_INT);
2975:   PetscViewerBinaryReadAll(viewer,matvals,rowidxs[m],PETSC_DETERMINE,PETSC_DETERMINE,PETSC_SCALAR);
2976:   /* store matrix indices and values */
2977:   MatMPIAIJSetPreallocationCSR(mat,rowidxs,colidxs,matvals);
2978:   PetscFree(rowidxs);
2979:   PetscFree2(colidxs,matvals);
2980:   return(0);
2981: }

2983: /* Not scalable because of ISAllGather() unless getting all columns. */
2984: PetscErrorCode ISGetSeqIS_Private(Mat mat,IS iscol,IS *isseq)
2985: {
2987:   IS             iscol_local;
2988:   PetscBool      isstride;
2989:   PetscMPIInt    lisstride=0,gisstride;

2992:   /* check if we are grabbing all columns*/
2993:   PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);

2995:   if (isstride) {
2996:     PetscInt  start,len,mstart,mlen;
2997:     ISStrideGetInfo(iscol,&start,NULL);
2998:     ISGetLocalSize(iscol,&len);
2999:     MatGetOwnershipRangeColumn(mat,&mstart,&mlen);
3000:     if (mstart == start && mlen-mstart == len) lisstride = 1;
3001:   }

3003:   MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));
3004:   if (gisstride) {
3005:     PetscInt N;
3006:     MatGetSize(mat,NULL,&N);
3007:     ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol_local);
3008:     ISSetIdentity(iscol_local);
3009:     PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");
3010:   } else {
3011:     PetscInt cbs;
3012:     ISGetBlockSize(iscol,&cbs);
3013:     ISAllGather(iscol,&iscol_local);
3014:     ISSetBlockSize(iscol_local,cbs);
3015:   }

3017:   *isseq = iscol_local;
3018:   return(0);
3019: }

3021: /*
3022:  Used by MatCreateSubMatrix_MPIAIJ_SameRowColDist() to avoid ISAllGather() and global size of iscol_local
3023:  (see MatCreateSubMatrix_MPIAIJ_nonscalable)

3025:  Input Parameters:
3026:    mat - matrix
3027:    isrow - parallel row index set; its local indices are a subset of local columns of mat,
3028:            i.e., mat->rstart <= isrow[i] < mat->rend
3029:    iscol - parallel column index set; its local indices are a subset of local columns of mat,
3030:            i.e., mat->cstart <= iscol[i] < mat->cend
3031:  Output Parameter:
3032:    isrow_d,iscol_d - sequential row and column index sets for retrieving mat->A
3033:    iscol_o - sequential column index set for retrieving mat->B
3034:    garray - column map; garray[i] indicates global location of iscol_o[i] in iscol
3035:  */
3036: PetscErrorCode ISGetSeqIS_SameColDist_Private(Mat mat,IS isrow,IS iscol,IS *isrow_d,IS *iscol_d,IS *iscol_o,const PetscInt *garray[])
3037: {
3039:   Vec            x,cmap;
3040:   const PetscInt *is_idx;
3041:   PetscScalar    *xarray,*cmaparray;
3042:   PetscInt       ncols,isstart,*idx,m,rstart,*cmap1,count;
3043:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)mat->data;
3044:   Mat            B=a->B;
3045:   Vec            lvec=a->lvec,lcmap;
3046:   PetscInt       i,cstart,cend,Bn=B->cmap->N;
3047:   MPI_Comm       comm;
3048:   VecScatter     Mvctx=a->Mvctx;

3051:   PetscObjectGetComm((PetscObject)mat,&comm);
3052:   ISGetLocalSize(iscol,&ncols);

3054:   /* (1) iscol is a sub-column vector of mat, pad it with '-1.' to form a full vector x */
3055:   MatCreateVecs(mat,&x,NULL);
3056:   VecSet(x,-1.0);
3057:   VecDuplicate(x,&cmap);
3058:   VecSet(cmap,-1.0);

3060:   /* Get start indices */
3061:   MPI_Scan(&ncols,&isstart,1,MPIU_INT,MPI_SUM,comm);
3062:   isstart -= ncols;
3063:   MatGetOwnershipRangeColumn(mat,&cstart,&cend);

3065:   ISGetIndices(iscol,&is_idx);
3066:   VecGetArray(x,&xarray);
3067:   VecGetArray(cmap,&cmaparray);
3068:   PetscMalloc1(ncols,&idx);
3069:   for (i=0; i<ncols; i++) {
3070:     xarray[is_idx[i]-cstart]    = (PetscScalar)is_idx[i];
3071:     cmaparray[is_idx[i]-cstart] = i + isstart;      /* global index of iscol[i] */
3072:     idx[i]                      = is_idx[i]-cstart; /* local index of iscol[i]  */
3073:   }
3074:   VecRestoreArray(x,&xarray);
3075:   VecRestoreArray(cmap,&cmaparray);
3076:   ISRestoreIndices(iscol,&is_idx);

3078:   /* Get iscol_d */
3079:   ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,iscol_d);
3080:   ISGetBlockSize(iscol,&i);
3081:   ISSetBlockSize(*iscol_d,i);

3083:   /* Get isrow_d */
3084:   ISGetLocalSize(isrow,&m);
3085:   rstart = mat->rmap->rstart;
3086:   PetscMalloc1(m,&idx);
3087:   ISGetIndices(isrow,&is_idx);
3088:   for (i=0; i<m; i++) idx[i] = is_idx[i]-rstart;
3089:   ISRestoreIndices(isrow,&is_idx);

3091:   ISCreateGeneral(PETSC_COMM_SELF,m,idx,PETSC_OWN_POINTER,isrow_d);
3092:   ISGetBlockSize(isrow,&i);
3093:   ISSetBlockSize(*isrow_d,i);

3095:   /* (2) Scatter x and cmap using aij->Mvctx to get their off-process portions (see MatMult_MPIAIJ) */
3096:   VecScatterBegin(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);
3097:   VecScatterEnd(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);

3099:   VecDuplicate(lvec,&lcmap);

3101:   VecScatterBegin(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);
3102:   VecScatterEnd(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);

3104:   /* (3) create sequential iscol_o (a subset of iscol) and isgarray */
3105:   /* off-process column indices */
3106:   count = 0;
3107:   PetscMalloc1(Bn,&idx);
3108:   PetscMalloc1(Bn,&cmap1);

3110:   VecGetArray(lvec,&xarray);
3111:   VecGetArray(lcmap,&cmaparray);
3112:   for (i=0; i<Bn; i++) {
3113:     if (PetscRealPart(xarray[i]) > -1.0) {
3114:       idx[count]     = i;                   /* local column index in off-diagonal part B */
3115:       cmap1[count] = (PetscInt)PetscRealPart(cmaparray[i]);  /* column index in submat */
3116:       count++;
3117:     }
3118:   }
3119:   VecRestoreArray(lvec,&xarray);
3120:   VecRestoreArray(lcmap,&cmaparray);

3122:   ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,iscol_o);
3123:   /* cannot ensure iscol_o has same blocksize as iscol! */

3125:   PetscFree(idx);
3126:   *garray = cmap1;

3128:   VecDestroy(&x);
3129:   VecDestroy(&cmap);
3130:   VecDestroy(&lcmap);
3131:   return(0);
3132: }

3134: /* isrow and iscol have same processor distribution as mat, output *submat is a submatrix of local mat */
3135: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *submat)
3136: {
3138:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)mat->data,*asub;
3139:   Mat            M = NULL;
3140:   MPI_Comm       comm;
3141:   IS             iscol_d,isrow_d,iscol_o;
3142:   Mat            Asub = NULL,Bsub = NULL;
3143:   PetscInt       n;

3146:   PetscObjectGetComm((PetscObject)mat,&comm);

3148:   if (call == MAT_REUSE_MATRIX) {
3149:     /* Retrieve isrow_d, iscol_d and iscol_o from submat */
3150:     PetscObjectQuery((PetscObject)*submat,"isrow_d",(PetscObject*)&isrow_d);
3151:     if (!isrow_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"isrow_d passed in was not used before, cannot reuse");

3153:     PetscObjectQuery((PetscObject)*submat,"iscol_d",(PetscObject*)&iscol_d);
3154:     if (!iscol_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_d passed in was not used before, cannot reuse");

3156:     PetscObjectQuery((PetscObject)*submat,"iscol_o",(PetscObject*)&iscol_o);
3157:     if (!iscol_o) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_o passed in was not used before, cannot reuse");

3159:     /* Update diagonal and off-diagonal portions of submat */
3160:     asub = (Mat_MPIAIJ*)(*submat)->data;
3161:     MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->A);
3162:     ISGetLocalSize(iscol_o,&n);
3163:     if (n) {
3164:       MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->B);
3165:     }
3166:     MatAssemblyBegin(*submat,MAT_FINAL_ASSEMBLY);
3167:     MatAssemblyEnd(*submat,MAT_FINAL_ASSEMBLY);

3169:   } else { /* call == MAT_INITIAL_MATRIX) */
3170:     const PetscInt *garray;
3171:     PetscInt        BsubN;

3173:     /* Create isrow_d, iscol_d, iscol_o and isgarray (replace isgarray with array?) */
3174:     ISGetSeqIS_SameColDist_Private(mat,isrow,iscol,&isrow_d,&iscol_d,&iscol_o,&garray);

3176:     /* Create local submatrices Asub and Bsub */
3177:     MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Asub);
3178:     MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Bsub);

3180:     /* Create submatrix M */
3181:     MatCreateMPIAIJWithSeqAIJ(comm,Asub,Bsub,garray,&M);

3183:     /* If Bsub has empty columns, compress iscol_o such that it will retrieve condensed Bsub from a->B during reuse */
3184:     asub = (Mat_MPIAIJ*)M->data;

3186:     ISGetLocalSize(iscol_o,&BsubN);
3187:     n = asub->B->cmap->N;
3188:     if (BsubN > n) {
3189:       /* This case can be tested using ~petsc/src/tao/bound/tutorials/runplate2_3 */
3190:       const PetscInt *idx;
3191:       PetscInt       i,j,*idx_new,*subgarray = asub->garray;
3192:       PetscInfo2(M,"submatrix Bn %D != BsubN %D, update iscol_o\n",n,BsubN);

3194:       PetscMalloc1(n,&idx_new);
3195:       j = 0;
3196:       ISGetIndices(iscol_o,&idx);
3197:       for (i=0; i<n; i++) {
3198:         if (j >= BsubN) break;
3199:         while (subgarray[i] > garray[j]) j++;

3201:         if (subgarray[i] == garray[j]) {
3202:           idx_new[i] = idx[j++];
3203:         } else SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"subgarray[%D]=%D cannot < garray[%D]=%D",i,subgarray[i],j,garray[j]);
3204:       }
3205:       ISRestoreIndices(iscol_o,&idx);

3207:       ISDestroy(&iscol_o);
3208:       ISCreateGeneral(PETSC_COMM_SELF,n,idx_new,PETSC_OWN_POINTER,&iscol_o);

3210:     } else if (BsubN < n) {
3211:       SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Columns of Bsub cannot be smaller than B's",BsubN,asub->B->cmap->N);
3212:     }

3214:     PetscFree(garray);
3215:     *submat = M;

3217:     /* Save isrow_d, iscol_d and iscol_o used in processor for next request */
3218:     PetscObjectCompose((PetscObject)M,"isrow_d",(PetscObject)isrow_d);
3219:     ISDestroy(&isrow_d);

3221:     PetscObjectCompose((PetscObject)M,"iscol_d",(PetscObject)iscol_d);
3222:     ISDestroy(&iscol_d);

3224:     PetscObjectCompose((PetscObject)M,"iscol_o",(PetscObject)iscol_o);
3225:     ISDestroy(&iscol_o);
3226:   }
3227:   return(0);
3228: }

3230: PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
3231: {
3233:   IS             iscol_local=NULL,isrow_d;
3234:   PetscInt       csize;
3235:   PetscInt       n,i,j,start,end;
3236:   PetscBool      sameRowDist=PETSC_FALSE,sameDist[2],tsameDist[2];
3237:   MPI_Comm       comm;

3240:   /* If isrow has same processor distribution as mat,
3241:      call MatCreateSubMatrix_MPIAIJ_SameRowDist() to avoid using a hash table with global size of iscol */
3242:   if (call == MAT_REUSE_MATRIX) {
3243:     PetscObjectQuery((PetscObject)*newmat,"isrow_d",(PetscObject*)&isrow_d);
3244:     if (isrow_d) {
3245:       sameRowDist  = PETSC_TRUE;
3246:       tsameDist[1] = PETSC_TRUE; /* sameColDist */
3247:     } else {
3248:       PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);
3249:       if (iscol_local) {
3250:         sameRowDist  = PETSC_TRUE;
3251:         tsameDist[1] = PETSC_FALSE; /* !sameColDist */
3252:       }
3253:     }
3254:   } else {
3255:     /* Check if isrow has same processor distribution as mat */
3256:     sameDist[0] = PETSC_FALSE;
3257:     ISGetLocalSize(isrow,&n);
3258:     if (!n) {
3259:       sameDist[0] = PETSC_TRUE;
3260:     } else {
3261:       ISGetMinMax(isrow,&i,&j);
3262:       MatGetOwnershipRange(mat,&start,&end);
3263:       if (i >= start && j < end) {
3264:         sameDist[0] = PETSC_TRUE;
3265:       }
3266:     }

3268:     /* Check if iscol has same processor distribution as mat */
3269:     sameDist[1] = PETSC_FALSE;
3270:     ISGetLocalSize(iscol,&n);
3271:     if (!n) {
3272:       sameDist[1] = PETSC_TRUE;
3273:     } else {
3274:       ISGetMinMax(iscol,&i,&j);
3275:       MatGetOwnershipRangeColumn(mat,&start,&end);
3276:       if (i >= start && j < end) sameDist[1] = PETSC_TRUE;
3277:     }

3279:     PetscObjectGetComm((PetscObject)mat,&comm);
3280:     MPIU_Allreduce(&sameDist,&tsameDist,2,MPIU_BOOL,MPI_LAND,comm);
3281:     sameRowDist = tsameDist[0];
3282:   }

3284:   if (sameRowDist) {
3285:     if (tsameDist[1]) { /* sameRowDist & sameColDist */
3286:       /* isrow and iscol have same processor distribution as mat */
3287:       MatCreateSubMatrix_MPIAIJ_SameRowColDist(mat,isrow,iscol,call,newmat);
3288:       return(0);
3289:     } else { /* sameRowDist */
3290:       /* isrow has same processor distribution as mat */
3291:       if (call == MAT_INITIAL_MATRIX) {
3292:         PetscBool sorted;
3293:         ISGetSeqIS_Private(mat,iscol,&iscol_local);
3294:         ISGetLocalSize(iscol_local,&n); /* local size of iscol_local = global columns of newmat */
3295:         ISGetSize(iscol,&i);
3296:         if (n != i) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"n %d != size of iscol %d",n,i);

3298:         ISSorted(iscol_local,&sorted);
3299:         if (sorted) {
3300:           /* MatCreateSubMatrix_MPIAIJ_SameRowDist() requires iscol_local be sorted; it can have duplicate indices */
3301:           MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,iscol_local,MAT_INITIAL_MATRIX,newmat);
3302:           return(0);
3303:         }
3304:       } else { /* call == MAT_REUSE_MATRIX */
3305:         IS    iscol_sub;
3306:         PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3307:         if (iscol_sub) {
3308:           MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,NULL,call,newmat);
3309:           return(0);
3310:         }
3311:       }
3312:     }
3313:   }

3315:   /* General case: iscol -> iscol_local which has global size of iscol */
3316:   if (call == MAT_REUSE_MATRIX) {
3317:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
3318:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3319:   } else {
3320:     if (!iscol_local) {
3321:       ISGetSeqIS_Private(mat,iscol,&iscol_local);
3322:     }
3323:   }

3325:   ISGetLocalSize(iscol,&csize);
3326:   MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);

3328:   if (call == MAT_INITIAL_MATRIX) {
3329:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
3330:     ISDestroy(&iscol_local);
3331:   }
3332:   return(0);
3333: }

3335: /*@C
3336:      MatCreateMPIAIJWithSeqAIJ - creates a MPIAIJ matrix using SeqAIJ matrices that contain the "diagonal"
3337:          and "off-diagonal" part of the matrix in CSR format.

3339:    Collective

3341:    Input Parameters:
3342: +  comm - MPI communicator
3343: .  A - "diagonal" portion of matrix
3344: .  B - "off-diagonal" portion of matrix, may have empty columns, will be destroyed by this routine
3345: -  garray - global index of B columns

3347:    Output Parameter:
3348: .   mat - the matrix, with input A as its local diagonal matrix
3349:    Level: advanced

3351:    Notes:
3352:        See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix.
3353:        A becomes part of output mat, B is destroyed by this routine. The user cannot use A and B anymore.

3355: .seealso: MatCreateMPIAIJWithSplitArrays()
3356: @*/
3357: PetscErrorCode MatCreateMPIAIJWithSeqAIJ(MPI_Comm comm,Mat A,Mat B,const PetscInt garray[],Mat *mat)
3358: {
3360:   Mat_MPIAIJ     *maij;
3361:   Mat_SeqAIJ     *b=(Mat_SeqAIJ*)B->data,*bnew;
3362:   PetscInt       *oi=b->i,*oj=b->j,i,nz,col;
3363:   PetscScalar    *oa=b->a;
3364:   Mat            Bnew;
3365:   PetscInt       m,n,N;

3368:   MatCreate(comm,mat);
3369:   MatGetSize(A,&m,&n);
3370:   if (m != B->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Am %D != Bm %D",m,B->rmap->N);
3371:   if (A->rmap->bs != B->rmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A row bs %D != B row bs %D",A->rmap->bs,B->rmap->bs);
3372:   /* remove check below; When B is created using iscol_o from ISGetSeqIS_SameColDist_Private(), its bs may not be same as A */
3373:   /* if (A->cmap->bs != B->cmap->bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"A column bs %D != B column bs %D",A->cmap->bs,B->cmap->bs); */

3375:   /* Get global columns of mat */
3376:   MPIU_Allreduce(&n,&N,1,MPIU_INT,MPI_SUM,comm);

3378:   MatSetSizes(*mat,m,n,PETSC_DECIDE,N);
3379:   MatSetType(*mat,MATMPIAIJ);
3380:   MatSetBlockSizes(*mat,A->rmap->bs,A->cmap->bs);
3381:   maij = (Mat_MPIAIJ*)(*mat)->data;

3383:   (*mat)->preallocated = PETSC_TRUE;

3385:   PetscLayoutSetUp((*mat)->rmap);
3386:   PetscLayoutSetUp((*mat)->cmap);

3388:   /* Set A as diagonal portion of *mat */
3389:   maij->A = A;

3391:   nz = oi[m];
3392:   for (i=0; i<nz; i++) {
3393:     col   = oj[i];
3394:     oj[i] = garray[col];
3395:   }

3397:    /* Set Bnew as off-diagonal portion of *mat */
3398:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,N,oi,oj,oa,&Bnew);
3399:   bnew        = (Mat_SeqAIJ*)Bnew->data;
3400:   bnew->maxnz = b->maxnz; /* allocated nonzeros of B */
3401:   maij->B     = Bnew;

3403:   if (B->rmap->N != Bnew->rmap->N) SETERRQ2(PETSC_COMM_SELF,0,"BN %d != BnewN %d",B->rmap->N,Bnew->rmap->N);

3405:   b->singlemalloc = PETSC_FALSE; /* B arrays are shared by Bnew */
3406:   b->free_a       = PETSC_FALSE;
3407:   b->free_ij      = PETSC_FALSE;
3408:   MatDestroy(&B);

3410:   bnew->singlemalloc = PETSC_TRUE; /* arrays will be freed by MatDestroy(&Bnew) */
3411:   bnew->free_a       = PETSC_TRUE;
3412:   bnew->free_ij      = PETSC_TRUE;

3414:   /* condense columns of maij->B */
3415:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
3416:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
3417:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
3418:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
3419:   MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3420:   return(0);
3421: }

3423: extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*);

3425: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat mat,IS isrow,IS iscol,IS iscol_local,MatReuse call,Mat *newmat)
3426: {
3428:   PetscInt       i,m,n,rstart,row,rend,nz,j,bs,cbs;
3429:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3430:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)mat->data;
3431:   Mat            M,Msub,B=a->B;
3432:   MatScalar      *aa;
3433:   Mat_SeqAIJ     *aij;
3434:   PetscInt       *garray = a->garray,*colsub,Ncols;
3435:   PetscInt       count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend;
3436:   IS             iscol_sub,iscmap;
3437:   const PetscInt *is_idx,*cmap;
3438:   PetscBool      allcolumns=PETSC_FALSE;
3439:   MPI_Comm       comm;

3442:   PetscObjectGetComm((PetscObject)mat,&comm);

3444:   if (call == MAT_REUSE_MATRIX) {
3445:     PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3446:     if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse");
3447:     ISGetLocalSize(iscol_sub,&count);

3449:     PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);
3450:     if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse");

3452:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);
3453:     if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");

3455:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);

3457:   } else { /* call == MAT_INITIAL_MATRIX) */
3458:     PetscBool flg;

3460:     ISGetLocalSize(iscol,&n);
3461:     ISGetSize(iscol,&Ncols);

3463:     /* (1) iscol -> nonscalable iscol_local */
3464:     /* Check for special case: each processor gets entire matrix columns */
3465:     ISIdentity(iscol_local,&flg);
3466:     if (flg && n == mat->cmap->N) allcolumns = PETSC_TRUE;
3467:     if (allcolumns) {
3468:       iscol_sub = iscol_local;
3469:       PetscObjectReference((PetscObject)iscol_local);
3470:       ISCreateStride(PETSC_COMM_SELF,n,0,1,&iscmap);

3472:     } else {
3473:       /* (2) iscol_local -> iscol_sub and iscmap. Implementation below requires iscol_local be sorted, it can have duplicate indices */
3474:       PetscInt *idx,*cmap1,k;
3475:       PetscMalloc1(Ncols,&idx);
3476:       PetscMalloc1(Ncols,&cmap1);
3477:       ISGetIndices(iscol_local,&is_idx);
3478:       count = 0;
3479:       k     = 0;
3480:       for (i=0; i<Ncols; i++) {
3481:         j = is_idx[i];
3482:         if (j >= cstart && j < cend) {
3483:           /* diagonal part of mat */
3484:           idx[count]     = j;
3485:           cmap1[count++] = i; /* column index in submat */
3486:         } else if (Bn) {
3487:           /* off-diagonal part of mat */
3488:           if (j == garray[k]) {
3489:             idx[count]     = j;
3490:             cmap1[count++] = i;  /* column index in submat */
3491:           } else if (j > garray[k]) {
3492:             while (j > garray[k] && k < Bn-1) k++;
3493:             if (j == garray[k]) {
3494:               idx[count]     = j;
3495:               cmap1[count++] = i; /* column index in submat */
3496:             }
3497:           }
3498:         }
3499:       }
3500:       ISRestoreIndices(iscol_local,&is_idx);

3502:       ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_OWN_POINTER,&iscol_sub);
3503:       ISGetBlockSize(iscol,&cbs);
3504:       ISSetBlockSize(iscol_sub,cbs);

3506:       ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_OWN_POINTER,&iscmap);
3507:     }

3509:     /* (3) Create sequential Msub */
3510:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,allcolumns,&Msub);
3511:   }

3513:   ISGetLocalSize(iscol_sub,&count);
3514:   aij  = (Mat_SeqAIJ*)(Msub)->data;
3515:   ii   = aij->i;
3516:   ISGetIndices(iscmap,&cmap);

3518:   /*
3519:       m - number of local rows
3520:       Ncols - number of columns (same on all processors)
3521:       rstart - first row in new global matrix generated
3522:   */
3523:   MatGetSize(Msub,&m,NULL);

3525:   if (call == MAT_INITIAL_MATRIX) {
3526:     /* (4) Create parallel newmat */
3527:     PetscMPIInt    rank,size;
3528:     PetscInt       csize;

3530:     MPI_Comm_size(comm,&size);
3531:     MPI_Comm_rank(comm,&rank);

3533:     /*
3534:         Determine the number of non-zeros in the diagonal and off-diagonal
3535:         portions of the matrix in order to do correct preallocation
3536:     */

3538:     /* first get start and end of "diagonal" columns */
3539:     ISGetLocalSize(iscol,&csize);
3540:     if (csize == PETSC_DECIDE) {
3541:       ISGetSize(isrow,&mglobal);
3542:       if (mglobal == Ncols) { /* square matrix */
3543:         nlocal = m;
3544:       } else {
3545:         nlocal = Ncols/size + ((Ncols % size) > rank);
3546:       }
3547:     } else {
3548:       nlocal = csize;
3549:     }
3550:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3551:     rstart = rend - nlocal;
3552:     if (rank == size - 1 && rend != Ncols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,Ncols);

3554:     /* next, compute all the lengths */
3555:     jj    = aij->j;
3556:     PetscMalloc1(2*m+1,&dlens);
3557:     olens = dlens + m;
3558:     for (i=0; i<m; i++) {
3559:       jend = ii[i+1] - ii[i];
3560:       olen = 0;
3561:       dlen = 0;
3562:       for (j=0; j<jend; j++) {
3563:         if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++;
3564:         else dlen++;
3565:         jj++;
3566:       }
3567:       olens[i] = olen;
3568:       dlens[i] = dlen;
3569:     }

3571:     ISGetBlockSize(isrow,&bs);
3572:     ISGetBlockSize(iscol,&cbs);

3574:     MatCreate(comm,&M);
3575:     MatSetSizes(M,m,nlocal,PETSC_DECIDE,Ncols);
3576:     MatSetBlockSizes(M,bs,cbs);
3577:     MatSetType(M,((PetscObject)mat)->type_name);
3578:     MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3579:     PetscFree(dlens);

3581:   } else { /* call == MAT_REUSE_MATRIX */
3582:     M    = *newmat;
3583:     MatGetLocalSize(M,&i,NULL);
3584:     if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3585:     MatZeroEntries(M);
3586:     /*
3587:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3588:        rather than the slower MatSetValues().
3589:     */
3590:     M->was_assembled = PETSC_TRUE;
3591:     M->assembled     = PETSC_FALSE;
3592:   }

3594:   /* (5) Set values of Msub to *newmat */
3595:   PetscMalloc1(count,&colsub);
3596:   MatGetOwnershipRange(M,&rstart,NULL);

3598:   jj   = aij->j;
3599:   aa   = aij->a;
3600:   for (i=0; i<m; i++) {
3601:     row = rstart + i;
3602:     nz  = ii[i+1] - ii[i];
3603:     for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]];
3604:     MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);
3605:     jj += nz; aa += nz;
3606:   }
3607:   ISRestoreIndices(iscmap,&cmap);

3609:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3610:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);

3612:   PetscFree(colsub);

3614:   /* save Msub, iscol_sub and iscmap used in processor for next request */
3615:   if (call ==  MAT_INITIAL_MATRIX) {
3616:     *newmat = M;
3617:     PetscObjectCompose((PetscObject)(*newmat),"SubMatrix",(PetscObject)Msub);
3618:     MatDestroy(&Msub);

3620:     PetscObjectCompose((PetscObject)(*newmat),"SubIScol",(PetscObject)iscol_sub);
3621:     ISDestroy(&iscol_sub);

3623:     PetscObjectCompose((PetscObject)(*newmat),"Subcmap",(PetscObject)iscmap);
3624:     ISDestroy(&iscmap);

3626:     if (iscol_local) {
3627:       PetscObjectCompose((PetscObject)(*newmat),"ISAllGather",(PetscObject)iscol_local);
3628:       ISDestroy(&iscol_local);
3629:     }
3630:   }
3631:   return(0);
3632: }

3634: /*
3635:     Not great since it makes two copies of the submatrix, first an SeqAIJ
3636:   in local and then by concatenating the local matrices the end result.
3637:   Writing it directly would be much like MatCreateSubMatrices_MPIAIJ()

3639:   Note: This requires a sequential iscol with all indices.
3640: */
3641: PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
3642: {
3644:   PetscMPIInt    rank,size;
3645:   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs;
3646:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3647:   Mat            M,Mreuse;
3648:   MatScalar      *aa,*vwork;
3649:   MPI_Comm       comm;
3650:   Mat_SeqAIJ     *aij;
3651:   PetscBool      colflag,allcolumns=PETSC_FALSE;

3654:   PetscObjectGetComm((PetscObject)mat,&comm);
3655:   MPI_Comm_rank(comm,&rank);
3656:   MPI_Comm_size(comm,&size);

3658:   /* Check for special case: each processor gets entire matrix columns */
3659:   ISIdentity(iscol,&colflag);
3660:   ISGetLocalSize(iscol,&n);
3661:   if (colflag && n == mat->cmap->N) allcolumns = PETSC_TRUE;

3663:   if (call ==  MAT_REUSE_MATRIX) {
3664:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
3665:     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3666:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,allcolumns,&Mreuse);
3667:   } else {
3668:     MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,allcolumns,&Mreuse);
3669:   }

3671:   /*
3672:       m - number of local rows
3673:       n - number of columns (same on all processors)
3674:       rstart - first row in new global matrix generated
3675:   */
3676:   MatGetSize(Mreuse,&m,&n);
3677:   MatGetBlockSizes(Mreuse,&bs,&cbs);
3678:   if (call == MAT_INITIAL_MATRIX) {
3679:     aij = (Mat_SeqAIJ*)(Mreuse)->data;
3680:     ii  = aij->i;
3681:     jj  = aij->j;

3683:     /*
3684:         Determine the number of non-zeros in the diagonal and off-diagonal
3685:         portions of the matrix in order to do correct preallocation
3686:     */

3688:     /* first get start and end of "diagonal" columns */
3689:     if (csize == PETSC_DECIDE) {
3690:       ISGetSize(isrow,&mglobal);
3691:       if (mglobal == n) { /* square matrix */
3692:         nlocal = m;
3693:       } else {
3694:         nlocal = n/size + ((n % size) > rank);
3695:       }
3696:     } else {
3697:       nlocal = csize;
3698:     }
3699:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3700:     rstart = rend - nlocal;
3701:     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);

3703:     /* next, compute all the lengths */
3704:     PetscMalloc1(2*m+1,&dlens);
3705:     olens = dlens + m;
3706:     for (i=0; i<m; i++) {
3707:       jend = ii[i+1] - ii[i];
3708:       olen = 0;
3709:       dlen = 0;
3710:       for (j=0; j<jend; j++) {
3711:         if (*jj < rstart || *jj >= rend) olen++;
3712:         else dlen++;
3713:         jj++;
3714:       }
3715:       olens[i] = olen;
3716:       dlens[i] = dlen;
3717:     }
3718:     MatCreate(comm,&M);
3719:     MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);
3720:     MatSetBlockSizes(M,bs,cbs);
3721:     MatSetType(M,((PetscObject)mat)->type_name);
3722:     MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3723:     PetscFree(dlens);
3724:   } else {
3725:     PetscInt ml,nl;

3727:     M    = *newmat;
3728:     MatGetLocalSize(M,&ml,&nl);
3729:     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3730:     MatZeroEntries(M);
3731:     /*
3732:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3733:        rather than the slower MatSetValues().
3734:     */
3735:     M->was_assembled = PETSC_TRUE;
3736:     M->assembled     = PETSC_FALSE;
3737:   }
3738:   MatGetOwnershipRange(M,&rstart,&rend);
3739:   aij  = (Mat_SeqAIJ*)(Mreuse)->data;
3740:   ii   = aij->i;
3741:   jj   = aij->j;
3742:   aa   = aij->a;
3743:   for (i=0; i<m; i++) {
3744:     row   = rstart + i;
3745:     nz    = ii[i+1] - ii[i];
3746:     cwork = jj;     jj += nz;
3747:     vwork = aa;     aa += nz;
3748:     MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
3749:   }

3751:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3752:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3753:   *newmat = M;

3755:   /* save submatrix used in processor for next request */
3756:   if (call ==  MAT_INITIAL_MATRIX) {
3757:     PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
3758:     MatDestroy(&Mreuse);
3759:   }
3760:   return(0);
3761: }

3763: PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
3764: {
3765:   PetscInt       m,cstart, cend,j,nnz,i,d;
3766:   PetscInt       *d_nnz,*o_nnz,nnz_max = 0,rstart,ii;
3767:   const PetscInt *JJ;
3769:   PetscBool      nooffprocentries;

3772:   if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]);

3774:   PetscLayoutSetUp(B->rmap);
3775:   PetscLayoutSetUp(B->cmap);
3776:   m      = B->rmap->n;
3777:   cstart = B->cmap->rstart;
3778:   cend   = B->cmap->rend;
3779:   rstart = B->rmap->rstart;

3781:   PetscCalloc2(m,&d_nnz,m,&o_nnz);

3783: #if defined(PETSC_USE_DEBUG)
3784:   for (i=0; i<m; i++) {
3785:     nnz = Ii[i+1]- Ii[i];
3786:     JJ  = J + Ii[i];
3787:     if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz);
3788:     if (nnz && (JJ[0] < 0)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,JJ[0]);
3789:     if (nnz && (JJ[nnz-1] >= B->cmap->N)) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N);
3790:   }
3791: #endif

3793:   for (i=0; i<m; i++) {
3794:     nnz     = Ii[i+1]- Ii[i];
3795:     JJ      = J + Ii[i];
3796:     nnz_max = PetscMax(nnz_max,nnz);
3797:     d       = 0;
3798:     for (j=0; j<nnz; j++) {
3799:       if (cstart <= JJ[j] && JJ[j] < cend) d++;
3800:     }
3801:     d_nnz[i] = d;
3802:     o_nnz[i] = nnz - d;
3803:   }
3804:   MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
3805:   PetscFree2(d_nnz,o_nnz);

3807:   for (i=0; i<m; i++) {
3808:     ii   = i + rstart;
3809:     MatSetValues_MPIAIJ(B,1,&ii,Ii[i+1] - Ii[i],J+Ii[i], v ? v + Ii[i] : NULL,INSERT_VALUES);
3810:   }
3811:   nooffprocentries    = B->nooffprocentries;
3812:   B->nooffprocentries = PETSC_TRUE;
3813:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3814:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
3815:   B->nooffprocentries = nooffprocentries;

3817:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3818:   return(0);
3819: }

3821: /*@
3822:    MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format
3823:    (the default parallel PETSc format).

3825:    Collective

3827:    Input Parameters:
3828: +  B - the matrix
3829: .  i - the indices into j for the start of each local row (starts with zero)
3830: .  j - the column indices for each local row (starts with zero)
3831: -  v - optional values in the matrix

3833:    Level: developer

3835:    Notes:
3836:        The i, j, and v arrays ARE copied by this routine into the internal format used by PETSc;
3837:      thus you CANNOT change the matrix entries by changing the values of v[] after you have
3838:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

3840:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

3842:        The format which is used for the sparse matrix input, is equivalent to a
3843:     row-major ordering.. i.e for the following matrix, the input data expected is
3844:     as shown

3846: $        1 0 0
3847: $        2 0 3     P0
3848: $       -------
3849: $        4 5 6     P1
3850: $
3851: $     Process0 [P0]: rows_owned=[0,1]
3852: $        i =  {0,1,3}  [size = nrow+1  = 2+1]
3853: $        j =  {0,0,2}  [size = 3]
3854: $        v =  {1,2,3}  [size = 3]
3855: $
3856: $     Process1 [P1]: rows_owned=[2]
3857: $        i =  {0,3}    [size = nrow+1  = 1+1]
3858: $        j =  {0,1,2}  [size = 3]
3859: $        v =  {4,5,6}  [size = 3]

3861: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ,
3862:           MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays()
3863: @*/
3864: PetscErrorCode  MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3865: {

3869:   PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));
3870:   return(0);
3871: }

3873: /*@C
3874:    MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format
3875:    (the default parallel PETSc format).  For good matrix assembly performance
3876:    the user should preallocate the matrix storage by setting the parameters
3877:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3878:    performance can be increased by more than a factor of 50.

3880:    Collective

3882:    Input Parameters:
3883: +  B - the matrix
3884: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
3885:            (same value is used for all local rows)
3886: .  d_nnz - array containing the number of nonzeros in the various rows of the
3887:            DIAGONAL portion of the local submatrix (possibly different for each row)
3888:            or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
3889:            The size of this array is equal to the number of local rows, i.e 'm'.
3890:            For matrices that will be factored, you must leave room for (and set)
3891:            the diagonal entry even if it is zero.
3892: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
3893:            submatrix (same value is used for all local rows).
3894: -  o_nnz - array containing the number of nonzeros in the various rows of the
3895:            OFF-DIAGONAL portion of the local submatrix (possibly different for
3896:            each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
3897:            structure. The size of this array is equal to the number
3898:            of local rows, i.e 'm'.

3900:    If the *_nnz parameter is given then the *_nz parameter is ignored

3902:    The AIJ format (also called the Yale sparse matrix format or
3903:    compressed row storage (CSR)), is fully compatible with standard Fortran 77
3904:    storage.  The stored row and column indices begin with zero.
3905:    See Users-Manual: ch_mat for details.

3907:    The parallel matrix is partitioned such that the first m0 rows belong to
3908:    process 0, the next m1 rows belong to process 1, the next m2 rows belong
3909:    to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.

3911:    The DIAGONAL portion of the local submatrix of a processor can be defined
3912:    as the submatrix which is obtained by extraction the part corresponding to
3913:    the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
3914:    first row that belongs to the processor, r2 is the last row belonging to
3915:    the this processor, and c1-c2 is range of indices of the local part of a
3916:    vector suitable for applying the matrix to.  This is an mxn matrix.  In the
3917:    common case of a square matrix, the row and column ranges are the same and
3918:    the DIAGONAL part is also square. The remaining portion of the local
3919:    submatrix (mxN) constitute the OFF-DIAGONAL portion.

3921:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

3923:    You can call MatGetInfo() to get information on how effective the preallocation was;
3924:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3925:    You can also run with the option -info and look for messages with the string
3926:    malloc in them to see if additional memory allocation was needed.

3928:    Example usage:

3930:    Consider the following 8x8 matrix with 34 non-zero values, that is
3931:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
3932:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
3933:    as follows:

3935: .vb
3936:             1  2  0  |  0  3  0  |  0  4
3937:     Proc0   0  5  6  |  7  0  0  |  8  0
3938:             9  0 10  | 11  0  0  | 12  0
3939:     -------------------------------------
3940:            13  0 14  | 15 16 17  |  0  0
3941:     Proc1   0 18  0  | 19 20 21  |  0  0
3942:             0  0  0  | 22 23  0  | 24  0
3943:     -------------------------------------
3944:     Proc2  25 26 27  |  0  0 28  | 29  0
3945:            30  0  0  | 31 32 33  |  0 34
3946: .ve

3948:    This can be represented as a collection of submatrices as:

3950: .vb
3951:       A B C
3952:       D E F
3953:       G H I
3954: .ve

3956:    Where the submatrices A,B,C are owned by proc0, D,E,F are
3957:    owned by proc1, G,H,I are owned by proc2.

3959:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3960:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
3961:    The 'M','N' parameters are 8,8, and have the same values on all procs.

3963:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
3964:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
3965:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
3966:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
3967:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
3968:    matrix, ans [DF] as another SeqAIJ matrix.

3970:    When d_nz, o_nz parameters are specified, d_nz storage elements are
3971:    allocated for every row of the local diagonal submatrix, and o_nz
3972:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
3973:    One way to choose d_nz and o_nz is to use the max nonzerors per local
3974:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
3975:    In this case, the values of d_nz,o_nz are:
3976: .vb
3977:      proc0 : dnz = 2, o_nz = 2
3978:      proc1 : dnz = 3, o_nz = 2
3979:      proc2 : dnz = 1, o_nz = 4
3980: .ve
3981:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
3982:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
3983:    for proc3. i.e we are using 12+15+10=37 storage locations to store
3984:    34 values.

3986:    When d_nnz, o_nnz parameters are specified, the storage is specified
3987:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
3988:    In the above case the values for d_nnz,o_nnz are:
3989: .vb
3990:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
3991:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
3992:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
3993: .ve
3994:    Here the space allocated is sum of all the above values i.e 34, and
3995:    hence pre-allocation is perfect.

3997:    Level: intermediate

3999: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(),
4000:           MATMPIAIJ, MatGetInfo(), PetscSplitOwnership()
4001: @*/
4002: PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
4003: {

4009:   PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
4010:   return(0);
4011: }

4013: /*@
4014:      MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard
4015:          CSR format for the local rows.

4017:    Collective

4019:    Input Parameters:
4020: +  comm - MPI communicator
4021: .  m - number of local rows (Cannot be PETSC_DECIDE)
4022: .  n - This value should be the same as the local size used in creating the
4023:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4024:        calculated if N is given) For square matrices n is almost always m.
4025: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4026: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4027: .   i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix
4028: .   j - column indices
4029: -   a - matrix values

4031:    Output Parameter:
4032: .   mat - the matrix

4034:    Level: intermediate

4036:    Notes:
4037:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
4038:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
4039:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

4041:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

4043:        The format which is used for the sparse matrix input, is equivalent to a
4044:     row-major ordering.. i.e for the following matrix, the input data expected is
4045:     as shown

4047:        Once you have created the matrix you can update it with new numerical values using MatUpdateMPIAIJWithArrays

4049: $        1 0 0
4050: $        2 0 3     P0
4051: $       -------
4052: $        4 5 6     P1
4053: $
4054: $     Process0 [P0]: rows_owned=[0,1]
4055: $        i =  {0,1,3}  [size = nrow+1  = 2+1]
4056: $        j =  {0,0,2}  [size = 3]
4057: $        v =  {1,2,3}  [size = 3]
4058: $
4059: $     Process1 [P1]: rows_owned=[2]
4060: $        i =  {0,3}    [size = nrow+1  = 1+1]
4061: $        j =  {0,1,2}  [size = 3]
4062: $        v =  {4,5,6}  [size = 3]

4064: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4065:           MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays(), MatUpdateMPIAIJWithArrays()
4066: @*/
4067: PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
4068: {

4072:   if (i && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4073:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4074:   MatCreate(comm,mat);
4075:   MatSetSizes(*mat,m,n,M,N);
4076:   /* MatSetBlockSizes(M,bs,cbs); */
4077:   MatSetType(*mat,MATMPIAIJ);
4078:   MatMPIAIJSetPreallocationCSR(*mat,i,j,a);
4079:   return(0);
4080: }

4082: /*@
4083:      MatUpdateMPIAIJWithArrays - updates a MPI AIJ matrix using arrays that contain in standard
4084:          CSR format for the local rows. Only the numerical values are updated the other arrays must be identical

4086:    Collective

4088:    Input Parameters:
4089: +  mat - the matrix
4090: .  m - number of local rows (Cannot be PETSC_DECIDE)
4091: .  n - This value should be the same as the local size used in creating the
4092:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4093:        calculated if N is given) For square matrices n is almost always m.
4094: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4095: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4096: .  Ii - row indices; that is Ii[0] = 0, Ii[row] = Ii[row-1] + number of elements in that row of the matrix
4097: .  J - column indices
4098: -  v - matrix values

4100:    Level: intermediate

4102: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4103:           MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays(), MatUpdateMPIAIJWithArrays()
4104: @*/
4105: PetscErrorCode MatUpdateMPIAIJWithArrays(Mat mat,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
4106: {
4108:   PetscInt       cstart,nnz,i,j;
4109:   PetscInt       *ld;
4110:   PetscBool      nooffprocentries;
4111:   Mat_MPIAIJ     *Aij = (Mat_MPIAIJ*)mat->data;
4112:   Mat_SeqAIJ     *Ad  = (Mat_SeqAIJ*)Aij->A->data, *Ao  = (Mat_SeqAIJ*)Aij->B->data;
4113:   PetscScalar    *ad = Ad->a, *ao = Ao->a;
4114:   const PetscInt *Adi = Ad->i;
4115:   PetscInt       ldi,Iii,md;

4118:   if (Ii[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4119:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4120:   if (m != mat->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Local number of rows cannot change from call to MatUpdateMPIAIJWithArrays()");
4121:   if (n != mat->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Local number of columns cannot change from call to MatUpdateMPIAIJWithArrays()");

4123:   cstart = mat->cmap->rstart;
4124:   if (!Aij->ld) {
4125:     /* count number of entries below block diagonal */
4126:     PetscCalloc1(m,&ld);
4127:     Aij->ld = ld;
4128:     for (i=0; i<m; i++) {
4129:       nnz  = Ii[i+1]- Ii[i];
4130:       j     = 0;
4131:       while  (J[j] < cstart && j < nnz) {j++;}
4132:       J    += nnz;
4133:       ld[i] = j;
4134:     }
4135:   } else {
4136:     ld = Aij->ld;
4137:   }

4139:   for (i=0; i<m; i++) {
4140:     nnz  = Ii[i+1]- Ii[i];
4141:     Iii  = Ii[i];
4142:     ldi  = ld[i];
4143:     md   = Adi[i+1]-Adi[i];
4144:     PetscArraycpy(ao,v + Iii,ldi);
4145:     PetscArraycpy(ad,v + Iii + ldi,md);
4146:     PetscArraycpy(ao + ldi,v + Iii + ldi + md,nnz - ldi - md);
4147:     ad  += md;
4148:     ao  += nnz - md;
4149:   }
4150:   nooffprocentries      = mat->nooffprocentries;
4151:   mat->nooffprocentries = PETSC_TRUE;
4152:   PetscObjectStateIncrease((PetscObject)Aij->A);
4153:   PetscObjectStateIncrease((PetscObject)Aij->B);
4154:   PetscObjectStateIncrease((PetscObject)mat);
4155:   MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
4156:   MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
4157:   mat->nooffprocentries = nooffprocentries;
4158:   return(0);
4159: }

4161: /*@C
4162:    MatCreateAIJ - Creates a sparse parallel matrix in AIJ format
4163:    (the default parallel PETSc format).  For good matrix assembly performance
4164:    the user should preallocate the matrix storage by setting the parameters
4165:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
4166:    performance can be increased by more than a factor of 50.

4168:    Collective

4170:    Input Parameters:
4171: +  comm - MPI communicator
4172: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
4173:            This value should be the same as the local size used in creating the
4174:            y vector for the matrix-vector product y = Ax.
4175: .  n - This value should be the same as the local size used in creating the
4176:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4177:        calculated if N is given) For square matrices n is almost always m.
4178: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4179: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4180: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
4181:            (same value is used for all local rows)
4182: .  d_nnz - array containing the number of nonzeros in the various rows of the
4183:            DIAGONAL portion of the local submatrix (possibly different for each row)
4184:            or NULL, if d_nz is used to specify the nonzero structure.
4185:            The size of this array is equal to the number of local rows, i.e 'm'.
4186: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
4187:            submatrix (same value is used for all local rows).
4188: -  o_nnz - array containing the number of nonzeros in the various rows of the
4189:            OFF-DIAGONAL portion of the local submatrix (possibly different for
4190:            each row) or NULL, if o_nz is used to specify the nonzero
4191:            structure. The size of this array is equal to the number
4192:            of local rows, i.e 'm'.

4194:    Output Parameter:
4195: .  A - the matrix

4197:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
4198:    MatXXXXSetPreallocation() paradigm instead of this routine directly.
4199:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

4201:    Notes:
4202:    If the *_nnz parameter is given then the *_nz parameter is ignored

4204:    m,n,M,N parameters specify the size of the matrix, and its partitioning across
4205:    processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
4206:    storage requirements for this matrix.

4208:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one
4209:    processor than it must be used on all processors that share the object for
4210:    that argument.

4212:    The user MUST specify either the local or global matrix dimensions
4213:    (possibly both).

4215:    The parallel matrix is partitioned across processors such that the
4216:    first m0 rows belong to process 0, the next m1 rows belong to
4217:    process 1, the next m2 rows belong to process 2 etc.. where
4218:    m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
4219:    values corresponding to [m x N] submatrix.

4221:    The columns are logically partitioned with the n0 columns belonging
4222:    to 0th partition, the next n1 columns belonging to the next
4223:    partition etc.. where n0,n1,n2... are the input parameter 'n'.

4225:    The DIAGONAL portion of the local submatrix on any given processor
4226:    is the submatrix corresponding to the rows and columns m,n
4227:    corresponding to the given processor. i.e diagonal matrix on
4228:    process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
4229:    etc. The remaining portion of the local submatrix [m x (N-n)]
4230:    constitute the OFF-DIAGONAL portion. The example below better
4231:    illustrates this concept.

4233:    For a square global matrix we define each processor's diagonal portion
4234:    to be its local rows and the corresponding columns (a square submatrix);
4235:    each processor's off-diagonal portion encompasses the remainder of the
4236:    local matrix (a rectangular submatrix).

4238:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

4240:    When calling this routine with a single process communicator, a matrix of
4241:    type SEQAIJ is returned.  If a matrix of type MPIAIJ is desired for this
4242:    type of communicator, use the construction mechanism
4243: .vb
4244:      MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...);
4245: .ve

4247: $     MatCreate(...,&A);
4248: $     MatSetType(A,MATMPIAIJ);
4249: $     MatSetSizes(A, m,n,M,N);
4250: $     MatMPIAIJSetPreallocation(A,...);

4252:    By default, this format uses inodes (identical nodes) when possible.
4253:    We search for consecutive rows with the same nonzero structure, thereby
4254:    reusing matrix information to achieve increased efficiency.

4256:    Options Database Keys:
4257: +  -mat_no_inode  - Do not use inodes
4258: -  -mat_inode_limit <limit> - Sets inode limit (max limit=5)



4262:    Example usage:

4264:    Consider the following 8x8 matrix with 34 non-zero values, that is
4265:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
4266:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
4267:    as follows

4269: .vb
4270:             1  2  0  |  0  3  0  |  0  4
4271:     Proc0   0  5  6  |  7  0  0  |  8  0
4272:             9  0 10  | 11  0  0  | 12  0
4273:     -------------------------------------
4274:            13  0 14  | 15 16 17  |  0  0
4275:     Proc1   0 18  0  | 19 20 21  |  0  0
4276:             0  0  0  | 22 23  0  | 24  0
4277:     -------------------------------------
4278:     Proc2  25 26 27  |  0  0 28  | 29  0
4279:            30  0  0  | 31 32 33  |  0 34
4280: .ve

4282:    This can be represented as a collection of submatrices as

4284: .vb
4285:       A B C
4286:       D E F
4287:       G H I
4288: .ve

4290:    Where the submatrices A,B,C are owned by proc0, D,E,F are
4291:    owned by proc1, G,H,I are owned by proc2.

4293:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4294:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4295:    The 'M','N' parameters are 8,8, and have the same values on all procs.

4297:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
4298:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
4299:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
4300:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
4301:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
4302:    matrix, ans [DF] as another SeqAIJ matrix.

4304:    When d_nz, o_nz parameters are specified, d_nz storage elements are
4305:    allocated for every row of the local diagonal submatrix, and o_nz
4306:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
4307:    One way to choose d_nz and o_nz is to use the max nonzerors per local
4308:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
4309:    In this case, the values of d_nz,o_nz are
4310: .vb
4311:      proc0 : dnz = 2, o_nz = 2
4312:      proc1 : dnz = 3, o_nz = 2
4313:      proc2 : dnz = 1, o_nz = 4
4314: .ve
4315:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
4316:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
4317:    for proc3. i.e we are using 12+15+10=37 storage locations to store
4318:    34 values.

4320:    When d_nnz, o_nnz parameters are specified, the storage is specified
4321:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
4322:    In the above case the values for d_nnz,o_nnz are
4323: .vb
4324:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
4325:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
4326:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
4327: .ve
4328:    Here the space allocated is sum of all the above values i.e 34, and
4329:    hence pre-allocation is perfect.

4331:    Level: intermediate

4333: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4334:           MATMPIAIJ, MatCreateMPIAIJWithArrays()
4335: @*/
4336: 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)
4337: {
4339:   PetscMPIInt    size;

4342:   MatCreate(comm,A);
4343:   MatSetSizes(*A,m,n,M,N);
4344:   MPI_Comm_size(comm,&size);
4345:   if (size > 1) {
4346:     MatSetType(*A,MATMPIAIJ);
4347:     MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
4348:   } else {
4349:     MatSetType(*A,MATSEQAIJ);
4350:     MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
4351:   }
4352:   return(0);
4353: }

4355: /*@C
4356:   MatMPIAIJGetSeqAIJ - Returns the local piece of this distributed matrix
4357:   
4358:   Not collective
4359:   
4360:   Input Parameter:
4361: . A - The MPIAIJ matrix

4363:   Output Parameters:
4364: + Ad - The local diagonal block as a SeqAIJ matrix
4365: . Ao - The local off-diagonal block as a SeqAIJ matrix
4366: - colmap - An array mapping local column numbers of Ao to global column numbers of the parallel matrix

4368:   Note: The rows in Ad and Ao are in [0, Nr), where Nr is the number of local rows on this process. The columns
4369:   in Ad are in [0, Nc) where Nc is the number of local columns. The columns are Ao are in [0, Nco), where Nco is
4370:   the number of nonzero columns in the local off-diagonal piece of the matrix A. The array colmap maps these
4371:   local column numbers to global column numbers in the original matrix.

4373:   Level: intermediate

4375: .seealso: MatMPIAIJGetLocalMat(), MatMPIAIJGetLocalMatCondensed(), MatCreateAIJ(), MATMPIAIJ, MATSEQAIJ
4376: @*/
4377: PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
4378: {
4379:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;
4380:   PetscBool      flg;

4384:   PetscStrbeginswith(((PetscObject)A)->type_name,MATMPIAIJ,&flg);
4385:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input");
4386:   if (Ad)     *Ad     = a->A;
4387:   if (Ao)     *Ao     = a->B;
4388:   if (colmap) *colmap = a->garray;
4389:   return(0);
4390: }

4392: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
4393: {
4395:   PetscInt       m,N,i,rstart,nnz,Ii;
4396:   PetscInt       *indx;
4397:   PetscScalar    *values;

4400:   MatGetSize(inmat,&m,&N);
4401:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
4402:     PetscInt       *dnz,*onz,sum,bs,cbs;

4404:     if (n == PETSC_DECIDE) {
4405:       PetscSplitOwnership(comm,&n,&N);
4406:     }
4407:     /* Check sum(n) = N */
4408:     MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
4409:     if (sum != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns %D != global columns %D",sum,N);

4411:     MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);
4412:     rstart -= m;

4414:     MatPreallocateInitialize(comm,m,n,dnz,onz);
4415:     for (i=0; i<m; i++) {
4416:       MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4417:       MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);
4418:       MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4419:     }

4421:     MatCreate(comm,outmat);
4422:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4423:     MatGetBlockSizes(inmat,&bs,&cbs);
4424:     MatSetBlockSizes(*outmat,bs,cbs);
4425:     MatSetType(*outmat,MATAIJ);
4426:     MatSeqAIJSetPreallocation(*outmat,0,dnz);
4427:     MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);
4428:     MatPreallocateFinalize(dnz,onz);
4429:   }

4431:   /* numeric phase */
4432:   MatGetOwnershipRange(*outmat,&rstart,NULL);
4433:   for (i=0; i<m; i++) {
4434:     MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4435:     Ii   = i + rstart;
4436:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
4437:     MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4438:   }
4439:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
4440:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
4441:   return(0);
4442: }

4444: PetscErrorCode MatFileSplit(Mat A,char *outfile)
4445: {
4446:   PetscErrorCode    ierr;
4447:   PetscMPIInt       rank;
4448:   PetscInt          m,N,i,rstart,nnz;
4449:   size_t            len;
4450:   const PetscInt    *indx;
4451:   PetscViewer       out;
4452:   char              *name;
4453:   Mat               B;
4454:   const PetscScalar *values;

4457:   MatGetLocalSize(A,&m,0);
4458:   MatGetSize(A,0,&N);
4459:   /* Should this be the type of the diagonal block of A? */
4460:   MatCreate(PETSC_COMM_SELF,&B);
4461:   MatSetSizes(B,m,N,m,N);
4462:   MatSetBlockSizesFromMats(B,A,A);
4463:   MatSetType(B,MATSEQAIJ);
4464:   MatSeqAIJSetPreallocation(B,0,NULL);
4465:   MatGetOwnershipRange(A,&rstart,0);
4466:   for (i=0; i<m; i++) {
4467:     MatGetRow(A,i+rstart,&nnz,&indx,&values);
4468:     MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);
4469:     MatRestoreRow(A,i+rstart,&nnz,&indx,&values);
4470:   }
4471:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
4472:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

4474:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
4475:   PetscStrlen(outfile,&len);
4476:   PetscMalloc1(len+5,&name);
4477:   sprintf(name,"%s.%d",outfile,rank);
4478:   PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);
4479:   PetscFree(name);
4480:   MatView(B,out);
4481:   PetscViewerDestroy(&out);
4482:   MatDestroy(&B);
4483:   return(0);
4484: }

4486: PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A)
4487: {
4488:   PetscErrorCode      ierr;
4489:   Mat_Merge_SeqsToMPI *merge;
4490:   PetscContainer      container;

4493:   PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);
4494:   if (container) {
4495:     PetscContainerGetPointer(container,(void**)&merge);
4496:     PetscFree(merge->id_r);
4497:     PetscFree(merge->len_s);
4498:     PetscFree(merge->len_r);
4499:     PetscFree(merge->bi);
4500:     PetscFree(merge->bj);
4501:     PetscFree(merge->buf_ri[0]);
4502:     PetscFree(merge->buf_ri);
4503:     PetscFree(merge->buf_rj[0]);
4504:     PetscFree(merge->buf_rj);
4505:     PetscFree(merge->coi);
4506:     PetscFree(merge->coj);
4507:     PetscFree(merge->owners_co);
4508:     PetscLayoutDestroy(&merge->rowmap);
4509:     PetscFree(merge);
4510:     PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);
4511:   }
4512:   MatDestroy_MPIAIJ(A);
4513:   return(0);
4514: }

4516:  #include <../src/mat/utils/freespace.h>
4517:  #include <petscbt.h>

4519: PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat)
4520: {
4521:   PetscErrorCode      ierr;
4522:   MPI_Comm            comm;
4523:   Mat_SeqAIJ          *a  =(Mat_SeqAIJ*)seqmat->data;
4524:   PetscMPIInt         size,rank,taga,*len_s;
4525:   PetscInt            N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj;
4526:   PetscInt            proc,m;
4527:   PetscInt            **buf_ri,**buf_rj;
4528:   PetscInt            k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj;
4529:   PetscInt            nrows,**buf_ri_k,**nextrow,**nextai;
4530:   MPI_Request         *s_waits,*r_waits;
4531:   MPI_Status          *status;
4532:   MatScalar           *aa=a->a;
4533:   MatScalar           **abuf_r,*ba_i;
4534:   Mat_Merge_SeqsToMPI *merge;
4535:   PetscContainer      container;

4538:   PetscObjectGetComm((PetscObject)mpimat,&comm);
4539:   PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);

4541:   MPI_Comm_size(comm,&size);
4542:   MPI_Comm_rank(comm,&rank);

4544:   PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);
4545:   PetscContainerGetPointer(container,(void**)&merge);

4547:   bi     = merge->bi;
4548:   bj     = merge->bj;
4549:   buf_ri = merge->buf_ri;
4550:   buf_rj = merge->buf_rj;

4552:   PetscMalloc1(size,&status);
4553:   owners = merge->rowmap->range;
4554:   len_s  = merge->len_s;

4556:   /* send and recv matrix values */
4557:   /*-----------------------------*/
4558:   PetscObjectGetNewTag((PetscObject)mpimat,&taga);
4559:   PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);

4561:   PetscMalloc1(merge->nsend+1,&s_waits);
4562:   for (proc=0,k=0; proc<size; proc++) {
4563:     if (!len_s[proc]) continue;
4564:     i    = owners[proc];
4565:     MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);
4566:     k++;
4567:   }

4569:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,r_waits,status);}
4570:   if (merge->nsend) {MPI_Waitall(merge->nsend,s_waits,status);}
4571:   PetscFree(status);

4573:   PetscFree(s_waits);
4574:   PetscFree(r_waits);

4576:   /* insert mat values of mpimat */
4577:   /*----------------------------*/
4578:   PetscMalloc1(N,&ba_i);
4579:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

4581:   for (k=0; k<merge->nrecv; k++) {
4582:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4583:     nrows       = *(buf_ri_k[k]);
4584:     nextrow[k]  = buf_ri_k[k]+1;  /* next row number of k-th recved i-structure */
4585:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
4586:   }

4588:   /* set values of ba */
4589:   m = merge->rowmap->n;
4590:   for (i=0; i<m; i++) {
4591:     arow = owners[rank] + i;
4592:     bj_i = bj+bi[i];  /* col indices of the i-th row of mpimat */
4593:     bnzi = bi[i+1] - bi[i];
4594:     PetscArrayzero(ba_i,bnzi);

4596:     /* add local non-zero vals of this proc's seqmat into ba */
4597:     anzi   = ai[arow+1] - ai[arow];
4598:     aj     = a->j + ai[arow];
4599:     aa     = a->a + ai[arow];
4600:     nextaj = 0;
4601:     for (j=0; nextaj<anzi; j++) {
4602:       if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4603:         ba_i[j] += aa[nextaj++];
4604:       }
4605:     }

4607:     /* add received vals into ba */
4608:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4609:       /* i-th row */
4610:       if (i == *nextrow[k]) {
4611:         anzi   = *(nextai[k]+1) - *nextai[k];
4612:         aj     = buf_rj[k] + *(nextai[k]);
4613:         aa     = abuf_r[k] + *(nextai[k]);
4614:         nextaj = 0;
4615:         for (j=0; nextaj<anzi; j++) {
4616:           if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4617:             ba_i[j] += aa[nextaj++];
4618:           }
4619:         }
4620:         nextrow[k]++; nextai[k]++;
4621:       }
4622:     }
4623:     MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);
4624:   }
4625:   MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);
4626:   MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);

4628:   PetscFree(abuf_r[0]);
4629:   PetscFree(abuf_r);
4630:   PetscFree(ba_i);
4631:   PetscFree3(buf_ri_k,nextrow,nextai);
4632:   PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);
4633:   return(0);
4634: }

4636: PetscErrorCode  MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat)
4637: {
4638:   PetscErrorCode      ierr;
4639:   Mat                 B_mpi;
4640:   Mat_SeqAIJ          *a=(Mat_SeqAIJ*)seqmat->data;
4641:   PetscMPIInt         size,rank,tagi,tagj,*len_s,*len_si,*len_ri;
4642:   PetscInt            **buf_rj,**buf_ri,**buf_ri_k;
4643:   PetscInt            M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j;
4644:   PetscInt            len,proc,*dnz,*onz,bs,cbs;
4645:   PetscInt            k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0;
4646:   PetscInt            nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai;
4647:   MPI_Request         *si_waits,*sj_waits,*ri_waits,*rj_waits;
4648:   MPI_Status          *status;
4649:   PetscFreeSpaceList  free_space=NULL,current_space=NULL;
4650:   PetscBT             lnkbt;
4651:   Mat_Merge_SeqsToMPI *merge;
4652:   PetscContainer      container;

4655:   PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);

4657:   /* make sure it is a PETSc comm */
4658:   PetscCommDuplicate(comm,&comm,NULL);
4659:   MPI_Comm_size(comm,&size);
4660:   MPI_Comm_rank(comm,&rank);

4662:   PetscNew(&merge);
4663:   PetscMalloc1(size,&status);

4665:   /* determine row ownership */
4666:   /*---------------------------------------------------------*/
4667:   PetscLayoutCreate(comm,&merge->rowmap);
4668:   PetscLayoutSetLocalSize(merge->rowmap,m);
4669:   PetscLayoutSetSize(merge->rowmap,M);
4670:   PetscLayoutSetBlockSize(merge->rowmap,1);
4671:   PetscLayoutSetUp(merge->rowmap);
4672:   PetscMalloc1(size,&len_si);
4673:   PetscMalloc1(size,&merge->len_s);

4675:   m      = merge->rowmap->n;
4676:   owners = merge->rowmap->range;

4678:   /* determine the number of messages to send, their lengths */
4679:   /*---------------------------------------------------------*/
4680:   len_s = merge->len_s;

4682:   len          = 0; /* length of buf_si[] */
4683:   merge->nsend = 0;
4684:   for (proc=0; proc<size; proc++) {
4685:     len_si[proc] = 0;
4686:     if (proc == rank) {
4687:       len_s[proc] = 0;
4688:     } else {
4689:       len_si[proc] = owners[proc+1] - owners[proc] + 1;
4690:       len_s[proc]  = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */
4691:     }
4692:     if (len_s[proc]) {
4693:       merge->nsend++;
4694:       nrows = 0;
4695:       for (i=owners[proc]; i<owners[proc+1]; i++) {
4696:         if (ai[i+1] > ai[i]) nrows++;
4697:       }
4698:       len_si[proc] = 2*(nrows+1);
4699:       len         += len_si[proc];
4700:     }
4701:   }

4703:   /* determine the number and length of messages to receive for ij-structure */
4704:   /*-------------------------------------------------------------------------*/
4705:   PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);
4706:   PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);

4708:   /* post the Irecv of j-structure */
4709:   /*-------------------------------*/
4710:   PetscCommGetNewTag(comm,&tagj);
4711:   PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);

4713:   /* post the Isend of j-structure */
4714:   /*--------------------------------*/
4715:   PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);

4717:   for (proc=0, k=0; proc<size; proc++) {
4718:     if (!len_s[proc]) continue;
4719:     i    = owners[proc];
4720:     MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);
4721:     k++;
4722:   }

4724:   /* receives and sends of j-structure are complete */
4725:   /*------------------------------------------------*/
4726:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,rj_waits,status);}
4727:   if (merge->nsend) {MPI_Waitall(merge->nsend,sj_waits,status);}

4729:   /* send and recv i-structure */
4730:   /*---------------------------*/
4731:   PetscCommGetNewTag(comm,&tagi);
4732:   PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);

4734:   PetscMalloc1(len+1,&buf_s);
4735:   buf_si = buf_s;  /* points to the beginning of k-th msg to be sent */
4736:   for (proc=0,k=0; proc<size; proc++) {
4737:     if (!len_s[proc]) continue;
4738:     /* form outgoing message for i-structure:
4739:          buf_si[0]:                 nrows to be sent
4740:                [1:nrows]:           row index (global)
4741:                [nrows+1:2*nrows+1]: i-structure index
4742:     */
4743:     /*-------------------------------------------*/
4744:     nrows       = len_si[proc]/2 - 1;
4745:     buf_si_i    = buf_si + nrows+1;
4746:     buf_si[0]   = nrows;
4747:     buf_si_i[0] = 0;
4748:     nrows       = 0;
4749:     for (i=owners[proc]; i<owners[proc+1]; i++) {
4750:       anzi = ai[i+1] - ai[i];
4751:       if (anzi) {
4752:         buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */
4753:         buf_si[nrows+1]   = i-owners[proc]; /* local row index */
4754:         nrows++;
4755:       }
4756:     }
4757:     MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);
4758:     k++;
4759:     buf_si += len_si[proc];
4760:   }

4762:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,ri_waits,status);}
4763:   if (merge->nsend) {MPI_Waitall(merge->nsend,si_waits,status);}

4765:   PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);
4766:   for (i=0; i<merge->nrecv; i++) {
4767:     PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);
4768:   }

4770:   PetscFree(len_si);
4771:   PetscFree(len_ri);
4772:   PetscFree(rj_waits);
4773:   PetscFree2(si_waits,sj_waits);
4774:   PetscFree(ri_waits);
4775:   PetscFree(buf_s);
4776:   PetscFree(status);

4778:   /* compute a local seq matrix in each processor */
4779:   /*----------------------------------------------*/
4780:   /* allocate bi array and free space for accumulating nonzero column info */
4781:   PetscMalloc1(m+1,&bi);
4782:   bi[0] = 0;

4784:   /* create and initialize a linked list */
4785:   nlnk = N+1;
4786:   PetscLLCreate(N,N,nlnk,lnk,lnkbt);

4788:   /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */
4789:   len  = ai[owners[rank+1]] - ai[owners[rank]];
4790:   PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);

4792:   current_space = free_space;

4794:   /* determine symbolic info for each local row */
4795:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

4797:   for (k=0; k<merge->nrecv; k++) {
4798:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4799:     nrows       = *buf_ri_k[k];
4800:     nextrow[k]  = buf_ri_k[k] + 1;  /* next row number of k-th recved i-structure */
4801:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
4802:   }

4804:   MatPreallocateInitialize(comm,m,n,dnz,onz);
4805:   len  = 0;
4806:   for (i=0; i<m; i++) {
4807:     bnzi = 0;
4808:     /* add local non-zero cols of this proc's seqmat into lnk */
4809:     arow  = owners[rank] + i;
4810:     anzi  = ai[arow+1] - ai[arow];
4811:     aj    = a->j + ai[arow];
4812:     PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4813:     bnzi += nlnk;
4814:     /* add received col data into lnk */
4815:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4816:       if (i == *nextrow[k]) { /* i-th row */
4817:         anzi  = *(nextai[k]+1) - *nextai[k];
4818:         aj    = buf_rj[k] + *nextai[k];
4819:         PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4820:         bnzi += nlnk;
4821:         nextrow[k]++; nextai[k]++;
4822:       }
4823:     }
4824:     if (len < bnzi) len = bnzi;  /* =max(bnzi) */

4826:     /* if free space is not available, make more free space */
4827:     if (current_space->local_remaining<bnzi) {
4828:       PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),&current_space);
4829:       nspacedouble++;
4830:     }
4831:     /* copy data into free space, then initialize lnk */
4832:     PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);
4833:     MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);

4835:     current_space->array           += bnzi;
4836:     current_space->local_used      += bnzi;
4837:     current_space->local_remaining -= bnzi;

4839:     bi[i+1] = bi[i] + bnzi;
4840:   }

4842:   PetscFree3(buf_ri_k,nextrow,nextai);

4844:   PetscMalloc1(bi[m]+1,&bj);
4845:   PetscFreeSpaceContiguous(&free_space,bj);
4846:   PetscLLDestroy(lnk,lnkbt);

4848:   /* create symbolic parallel matrix B_mpi */
4849:   /*---------------------------------------*/
4850:   MatGetBlockSizes(seqmat,&bs,&cbs);
4851:   MatCreate(comm,&B_mpi);
4852:   if (n==PETSC_DECIDE) {
4853:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);
4854:   } else {
4855:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4856:   }
4857:   MatSetBlockSizes(B_mpi,bs,cbs);
4858:   MatSetType(B_mpi,MATMPIAIJ);
4859:   MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);
4860:   MatPreallocateFinalize(dnz,onz);
4861:   MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);

4863:   /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */
4864:   B_mpi->assembled    = PETSC_FALSE;
4865:   B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI;
4866:   merge->bi           = bi;
4867:   merge->bj           = bj;
4868:   merge->buf_ri       = buf_ri;
4869:   merge->buf_rj       = buf_rj;
4870:   merge->coi          = NULL;
4871:   merge->coj          = NULL;
4872:   merge->owners_co    = NULL;

4874:   PetscCommDestroy(&comm);

4876:   /* attach the supporting struct to B_mpi for reuse */
4877:   PetscContainerCreate(PETSC_COMM_SELF,&container);
4878:   PetscContainerSetPointer(container,merge);
4879:   PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);
4880:   PetscContainerDestroy(&container);
4881:   *mpimat = B_mpi;

4883:   PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);
4884:   return(0);
4885: }

4887: /*@C
4888:       MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential
4889:                  matrices from each processor

4891:     Collective

4893:    Input Parameters:
4894: +    comm - the communicators the parallel matrix will live on
4895: .    seqmat - the input sequential matrices
4896: .    m - number of local rows (or PETSC_DECIDE)
4897: .    n - number of local columns (or PETSC_DECIDE)
4898: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

4900:    Output Parameter:
4901: .    mpimat - the parallel matrix generated

4903:     Level: advanced

4905:    Notes:
4906:      The dimensions of the sequential matrix in each processor MUST be the same.
4907:      The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be
4908:      destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat.
4909: @*/
4910: PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat)
4911: {
4913:   PetscMPIInt    size;

4916:   MPI_Comm_size(comm,&size);
4917:   if (size == 1) {
4918:     PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4919:     if (scall == MAT_INITIAL_MATRIX) {
4920:       MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);
4921:     } else {
4922:       MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);
4923:     }
4924:     PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4925:     return(0);
4926:   }
4927:   PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
4928:   if (scall == MAT_INITIAL_MATRIX) {
4929:     MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);
4930:   }
4931:   MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);
4932:   PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
4933:   return(0);
4934: }

4936: /*@
4937:      MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential matrix with
4938:           mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained
4939:           with MatGetSize()

4941:     Not Collective

4943:    Input Parameters:
4944: +    A - the matrix
4945: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

4947:    Output Parameter:
4948: .    A_loc - the local sequential matrix generated

4950:     Level: developer

4952:    Notes:
4953:      When the communicator associated with A has size 1 and MAT_INITIAL_MATRIX is requested, the matrix returned is the diagonal part of A.
4954:      If MAT_REUSE_MATRIX is requested with comm size 1, MatCopy(Adiag,*A_loc,SAME_NONZERO_PATTERN) is called.
4955:      This means that one can preallocate the proper sequential matrix first and then call this routine with MAT_REUSE_MATRIX to safely
4956:      modify the values of the returned A_loc.

4958: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMatCondensed()

4960: @*/
4961: PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc)
4962: {
4964:   Mat_MPIAIJ     *mpimat=(Mat_MPIAIJ*)A->data;
4965:   Mat_SeqAIJ     *mat,*a,*b;
4966:   PetscInt       *ai,*aj,*bi,*bj,*cmap=mpimat->garray;
4967:   MatScalar      *aa,*ba,*cam;
4968:   PetscScalar    *ca;
4969:   PetscMPIInt    size;
4970:   PetscInt       am=A->rmap->n,i,j,k,cstart=A->cmap->rstart;
4971:   PetscInt       *ci,*cj,col,ncols_d,ncols_o,jo;
4972:   PetscBool      match;

4975:   PetscStrbeginswith(((PetscObject)A)->type_name,MATMPIAIJ,&match);
4976:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
4977:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
4978:   if (size == 1) {
4979:     if (scall == MAT_INITIAL_MATRIX) {
4980:       PetscObjectReference((PetscObject)mpimat->A);
4981:       *A_loc = mpimat->A;
4982:     } else if (scall == MAT_REUSE_MATRIX) {
4983:       MatCopy(mpimat->A,*A_loc,SAME_NONZERO_PATTERN);
4984:     }
4985:     return(0);
4986:   }

4988:   PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);
4989:   a = (Mat_SeqAIJ*)(mpimat->A)->data;
4990:   b = (Mat_SeqAIJ*)(mpimat->B)->data;
4991:   ai = a->i; aj = a->j; bi = b->i; bj = b->j;
4992:   aa = a->a; ba = b->a;
4993:   if (scall == MAT_INITIAL_MATRIX) {
4994:     PetscMalloc1(1+am,&ci);
4995:     ci[0] = 0;
4996:     for (i=0; i<am; i++) {
4997:       ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]);
4998:     }
4999:     PetscMalloc1(1+ci[am],&cj);
5000:     PetscMalloc1(1+ci[am],&ca);
5001:     k    = 0;
5002:     for (i=0; i<am; i++) {
5003:       ncols_o = bi[i+1] - bi[i];
5004:       ncols_d = ai[i+1] - ai[i];
5005:       /* off-diagonal portion of A */
5006:       for (jo=0; jo<ncols_o; jo++) {
5007:         col = cmap[*bj];
5008:         if (col >= cstart) break;
5009:         cj[k]   = col; bj++;
5010:         ca[k++] = *ba++;
5011:       }
5012:       /* diagonal portion of A */
5013:       for (j=0; j<ncols_d; j++) {
5014:         cj[k]   = cstart + *aj++;
5015:         ca[k++] = *aa++;
5016:       }
5017:       /* off-diagonal portion of A */
5018:       for (j=jo; j<ncols_o; j++) {
5019:         cj[k]   = cmap[*bj++];
5020:         ca[k++] = *ba++;
5021:       }
5022:     }
5023:     /* put together the new matrix */
5024:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);
5025:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5026:     /* Since these are PETSc arrays, change flags to free them as necessary. */
5027:     mat          = (Mat_SeqAIJ*)(*A_loc)->data;
5028:     mat->free_a  = PETSC_TRUE;
5029:     mat->free_ij = PETSC_TRUE;
5030:     mat->nonew   = 0;
5031:   } else if (scall == MAT_REUSE_MATRIX) {
5032:     mat=(Mat_SeqAIJ*)(*A_loc)->data;
5033:     ci = mat->i; cj = mat->j; cam = mat->a;
5034:     for (i=0; i<am; i++) {
5035:       /* off-diagonal portion of A */
5036:       ncols_o = bi[i+1] - bi[i];
5037:       for (jo=0; jo<ncols_o; jo++) {
5038:         col = cmap[*bj];
5039:         if (col >= cstart) break;
5040:         *cam++ = *ba++; bj++;
5041:       }
5042:       /* diagonal portion of A */
5043:       ncols_d = ai[i+1] - ai[i];
5044:       for (j=0; j<ncols_d; j++) *cam++ = *aa++;
5045:       /* off-diagonal portion of A */
5046:       for (j=jo; j<ncols_o; j++) {
5047:         *cam++ = *ba++; bj++;
5048:       }
5049:     }
5050:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
5051:   PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);
5052:   return(0);
5053: }

5055: /*@C
5056:      MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns

5058:     Not Collective

5060:    Input Parameters:
5061: +    A - the matrix
5062: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5063: -    row, col - index sets of rows and columns to extract (or NULL)

5065:    Output Parameter:
5066: .    A_loc - the local sequential matrix generated

5068:     Level: developer

5070: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat()

5072: @*/
5073: PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
5074: {
5075:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
5077:   PetscInt       i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
5078:   IS             isrowa,iscola;
5079:   Mat            *aloc;
5080:   PetscBool      match;

5083:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
5084:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
5085:   PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
5086:   if (!row) {
5087:     start = A->rmap->rstart; end = A->rmap->rend;
5088:     ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
5089:   } else {
5090:     isrowa = *row;
5091:   }
5092:   if (!col) {
5093:     start = A->cmap->rstart;
5094:     cmap  = a->garray;
5095:     nzA   = a->A->cmap->n;
5096:     nzB   = a->B->cmap->n;
5097:     PetscMalloc1(nzA+nzB, &idx);
5098:     ncols = 0;
5099:     for (i=0; i<nzB; i++) {
5100:       if (cmap[i] < start) idx[ncols++] = cmap[i];
5101:       else break;
5102:     }
5103:     imark = i;
5104:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;
5105:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
5106:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
5107:   } else {
5108:     iscola = *col;
5109:   }
5110:   if (scall != MAT_INITIAL_MATRIX) {
5111:     PetscMalloc1(1,&aloc);
5112:     aloc[0] = *A_loc;
5113:   }
5114:   MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
5115:   if (!col) { /* attach global id of condensed columns */
5116:     PetscObjectCompose((PetscObject)aloc[0],"_petsc_GetLocalMatCondensed_iscol",(PetscObject)iscola);
5117:   }
5118:   *A_loc = aloc[0];
5119:   PetscFree(aloc);
5120:   if (!row) {
5121:     ISDestroy(&isrowa);
5122:   }
5123:   if (!col) {
5124:     ISDestroy(&iscola);
5125:   }
5126:   PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
5127:   return(0);
5128: }

5130: /*
5131:  * Destroy a mat that may be composed with PetscSF communication objects.
5132:  * The SF objects were created in MatCreateSeqSubMatrixWithRows_Private.
5133:  * */
5134: PetscErrorCode MatDestroy_SeqAIJ_PetscSF(Mat mat)
5135: {
5136:   PetscSF          sf,osf;
5137:   IS               map;
5138:   PetscErrorCode   ierr;

5141:   PetscObjectQuery((PetscObject)mat,"diagsf",(PetscObject*)&sf);
5142:   PetscObjectQuery((PetscObject)mat,"offdiagsf",(PetscObject*)&osf);
5143:   PetscSFDestroy(&sf);
5144:   PetscSFDestroy(&osf);
5145:   PetscObjectQuery((PetscObject)mat,"aoffdiagtopothmapping",(PetscObject*)&map);
5146:   ISDestroy(&map);
5147:   MatDestroy_SeqAIJ(mat);
5148:   return(0);
5149: }

5151: /*
5152:  * Create a sequential AIJ matrix based on row indices. a whole column is extracted once a row is matched.
5153:  * Row could be local or remote.The routine is designed to be scalable in memory so that nothing is based
5154:  * on a global size.
5155:  * */
5156: PetscErrorCode MatCreateSeqSubMatrixWithRows_Private(Mat P,IS rows,Mat *P_oth)
5157: {
5158:   Mat_MPIAIJ               *p=(Mat_MPIAIJ*)P->data;
5159:   Mat_SeqAIJ               *pd=(Mat_SeqAIJ*)(p->A)->data,*po=(Mat_SeqAIJ*)(p->B)->data,*p_oth;
5160:   PetscInt                 plocalsize,nrows,*ilocal,*oilocal,i,lidx,*nrcols,*nlcols,ncol;
5161:   PetscMPIInt              owner;
5162:   PetscSFNode              *iremote,*oiremote;
5163:   const PetscInt           *lrowindices;
5164:   PetscErrorCode           ierr;
5165:   PetscSF                  sf,osf;
5166:   PetscInt                 pcstart,*roffsets,*loffsets,*pnnz,j;
5167:   PetscInt                 ontotalcols,dntotalcols,ntotalcols,nout;
5168:   MPI_Comm                 comm;
5169:   ISLocalToGlobalMapping   mapping;

5172:   PetscObjectGetComm((PetscObject)P,&comm);
5173:   /* plocalsize is the number of roots
5174:    * nrows is the number of leaves
5175:    * */
5176:   MatGetLocalSize(P,&plocalsize,NULL);
5177:   ISGetLocalSize(rows,&nrows);
5178:   PetscCalloc1(nrows,&iremote);
5179:   ISGetIndices(rows,&lrowindices);
5180:   for (i=0;i<nrows;i++) {
5181:     /* Find a remote index and an owner for a row
5182:      * The row could be local or remote
5183:      * */
5184:     owner = 0;
5185:     lidx  = 0;
5186:     PetscLayoutFindOwnerIndex(P->rmap,lrowindices[i],&owner,&lidx);
5187:     iremote[i].index = lidx;
5188:     iremote[i].rank  = owner;
5189:   }
5190:   /* Create SF to communicate how many nonzero columns for each row */
5191:   PetscSFCreate(comm,&sf);
5192:   /* SF will figure out the number of nonzero colunms for each row, and their
5193:    * offsets
5194:    * */
5195:   PetscSFSetGraph(sf,plocalsize,nrows,NULL,PETSC_OWN_POINTER,iremote,PETSC_OWN_POINTER);
5196:   PetscSFSetFromOptions(sf);
5197:   PetscSFSetUp(sf);

5199:   PetscCalloc1(2*(plocalsize+1),&roffsets);
5200:   PetscCalloc1(2*plocalsize,&nrcols);
5201:   PetscCalloc1(nrows,&pnnz);
5202:   roffsets[0] = 0;
5203:   roffsets[1] = 0;
5204:   for (i=0;i<plocalsize;i++) {
5205:     /* diag */
5206:     nrcols[i*2+0] = pd->i[i+1] - pd->i[i];
5207:     /* off diag */
5208:     nrcols[i*2+1] = po->i[i+1] - po->i[i];
5209:     /* compute offsets so that we relative location for each row */
5210:     roffsets[(i+1)*2+0] = roffsets[i*2+0] + nrcols[i*2+0];
5211:     roffsets[(i+1)*2+1] = roffsets[i*2+1] + nrcols[i*2+1];
5212:   }
5213:   PetscCalloc1(2*nrows,&nlcols);
5214:   PetscCalloc1(2*nrows,&loffsets);
5215:   /* 'r' means root, and 'l' means leaf */
5216:   PetscSFBcastBegin(sf,MPIU_2INT,nrcols,nlcols);
5217:   PetscSFBcastBegin(sf,MPIU_2INT,roffsets,loffsets);
5218:   PetscSFBcastEnd(sf,MPIU_2INT,nrcols,nlcols);
5219:   PetscSFBcastEnd(sf,MPIU_2INT,roffsets,loffsets);
5220:   PetscSFDestroy(&sf);
5221:   PetscFree(roffsets);
5222:   PetscFree(nrcols);
5223:   dntotalcols = 0;
5224:   ontotalcols = 0;
5225:   ncol = 0;
5226:   for (i=0;i<nrows;i++) {
5227:     pnnz[i] = nlcols[i*2+0] + nlcols[i*2+1];
5228:     ncol = PetscMax(pnnz[i],ncol);
5229:     /* diag */
5230:     dntotalcols += nlcols[i*2+0];
5231:     /* off diag */
5232:     ontotalcols += nlcols[i*2+1];
5233:   }
5234:   /* We do not need to figure the right number of columns
5235:    * since all the calculations will be done by going through the raw data
5236:    * */
5237:   MatCreateSeqAIJ(PETSC_COMM_SELF,nrows,ncol,0,pnnz,P_oth);
5238:   MatSetUp(*P_oth);
5239:   PetscFree(pnnz);
5240:   p_oth = (Mat_SeqAIJ*) (*P_oth)->data;
5241:   /* diag */
5242:   PetscCalloc1(dntotalcols,&iremote);
5243:   /* off diag */
5244:   PetscCalloc1(ontotalcols,&oiremote);
5245:   /* diag */
5246:   PetscCalloc1(dntotalcols,&ilocal);
5247:   /* off diag */
5248:   PetscCalloc1(ontotalcols,&oilocal);
5249:   dntotalcols = 0;
5250:   ontotalcols = 0;
5251:   ntotalcols  = 0;
5252:   for (i=0;i<nrows;i++) {
5253:     owner = 0;
5254:     PetscLayoutFindOwnerIndex(P->rmap,lrowindices[i],&owner,NULL);
5255:     /* Set iremote for diag matrix */
5256:     for (j=0;j<nlcols[i*2+0];j++) {
5257:       iremote[dntotalcols].index   = loffsets[i*2+0] + j;
5258:       iremote[dntotalcols].rank    = owner;
5259:       /* P_oth is seqAIJ so that ilocal need to point to the first part of memory */
5260:       ilocal[dntotalcols++]        = ntotalcols++;
5261:     }
5262:     /* off diag */
5263:     for (j=0;j<nlcols[i*2+1];j++) {
5264:       oiremote[ontotalcols].index   = loffsets[i*2+1] + j;
5265:       oiremote[ontotalcols].rank    = owner;
5266:       oilocal[ontotalcols++]        = ntotalcols++;
5267:     }
5268:   }
5269:   ISRestoreIndices(rows,&lrowindices);
5270:   PetscFree(loffsets);
5271:   PetscFree(nlcols);
5272:   PetscSFCreate(comm,&sf);
5273:   /* P serves as roots and P_oth is leaves
5274:    * Diag matrix
5275:    * */
5276:   PetscSFSetGraph(sf,pd->i[plocalsize],dntotalcols,ilocal,PETSC_OWN_POINTER,iremote,PETSC_OWN_POINTER);
5277:   PetscSFSetFromOptions(sf);
5278:   PetscSFSetUp(sf);

5280:   PetscSFCreate(comm,&osf);
5281:   /* Off diag */
5282:   PetscSFSetGraph(osf,po->i[plocalsize],ontotalcols,oilocal,PETSC_OWN_POINTER,oiremote,PETSC_OWN_POINTER);
5283:   PetscSFSetFromOptions(osf);
5284:   PetscSFSetUp(osf);
5285:   /* We operate on the matrix internal data for saving memory */
5286:   PetscSFBcastBegin(sf,MPIU_SCALAR,pd->a,p_oth->a);
5287:   PetscSFBcastBegin(osf,MPIU_SCALAR,po->a,p_oth->a);
5288:   MatGetOwnershipRangeColumn(P,&pcstart,NULL);
5289:   /* Convert to global indices for diag matrix */
5290:   for (i=0;i<pd->i[plocalsize];i++) pd->j[i] += pcstart;
5291:   PetscSFBcastBegin(sf,MPIU_INT,pd->j,p_oth->j);
5292:   /* We want P_oth store global indices */
5293:   ISLocalToGlobalMappingCreate(comm,1,p->B->cmap->n,p->garray,PETSC_COPY_VALUES,&mapping);
5294:   /* Use memory scalable approach */
5295:   ISLocalToGlobalMappingSetType(mapping,ISLOCALTOGLOBALMAPPINGHASH);
5296:   ISLocalToGlobalMappingApply(mapping,po->i[plocalsize],po->j,po->j);
5297:   PetscSFBcastBegin(osf,MPIU_INT,po->j,p_oth->j);
5298:   PetscSFBcastEnd(sf,MPIU_INT,pd->j,p_oth->j);
5299:   /* Convert back to local indices */
5300:   for (i=0;i<pd->i[plocalsize];i++) pd->j[i] -= pcstart;
5301:   PetscSFBcastEnd(osf,MPIU_INT,po->j,p_oth->j);
5302:   nout = 0;
5303:   ISGlobalToLocalMappingApply(mapping,IS_GTOLM_DROP,po->i[plocalsize],po->j,&nout,po->j);
5304:   if (nout != po->i[plocalsize]) SETERRQ2(comm,PETSC_ERR_ARG_INCOMP,"n %D does not equal to nout %D \n",po->i[plocalsize],nout);
5305:   ISLocalToGlobalMappingDestroy(&mapping);
5306:   /* Exchange values */
5307:   PetscSFBcastEnd(sf,MPIU_SCALAR,pd->a,p_oth->a);
5308:   PetscSFBcastEnd(osf,MPIU_SCALAR,po->a,p_oth->a);
5309:   /* Stop PETSc from shrinking memory */
5310:   for (i=0;i<nrows;i++) p_oth->ilen[i] = p_oth->imax[i];
5311:   MatAssemblyBegin(*P_oth,MAT_FINAL_ASSEMBLY);
5312:   MatAssemblyEnd(*P_oth,MAT_FINAL_ASSEMBLY);
5313:   /* Attach PetscSF objects to P_oth so that we can reuse it later */
5314:   PetscObjectCompose((PetscObject)*P_oth,"diagsf",(PetscObject)sf);
5315:   PetscObjectCompose((PetscObject)*P_oth,"offdiagsf",(PetscObject)osf);
5316:   /* ``New MatDestroy" takes care of PetscSF objects as well */
5317:   (*P_oth)->ops->destroy = MatDestroy_SeqAIJ_PetscSF;
5318:   return(0);
5319: }

5321: /*
5322:  * Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A
5323:  * This supports MPIAIJ and MAIJ
5324:  * */
5325: PetscErrorCode MatGetBrowsOfAcols_MPIXAIJ(Mat A,Mat P,PetscInt dof,MatReuse reuse,Mat *P_oth)
5326: {
5327:   Mat_MPIAIJ            *a=(Mat_MPIAIJ*)A->data,*p=(Mat_MPIAIJ*)P->data;
5328:   Mat_SeqAIJ            *p_oth;
5329:   Mat_SeqAIJ            *pd=(Mat_SeqAIJ*)(p->A)->data,*po=(Mat_SeqAIJ*)(p->B)->data;
5330:   IS                    rows,map;
5331:   PetscHMapI            hamp;
5332:   PetscInt              i,htsize,*rowindices,off,*mapping,key,count;
5333:   MPI_Comm              comm;
5334:   PetscSF               sf,osf;
5335:   PetscBool             has;
5336:   PetscErrorCode        ierr;

5339:   PetscObjectGetComm((PetscObject)A,&comm);
5340:   PetscLogEventBegin(MAT_GetBrowsOfAocols,A,P,0,0);
5341:   /* If it is the first time, create an index set of off-diag nonzero columns of A,
5342:    *  and then create a submatrix (that often is an overlapping matrix)
5343:    * */
5344:   if (reuse==MAT_INITIAL_MATRIX) {
5345:     /* Use a hash table to figure out unique keys */
5346:     PetscHMapICreate(&hamp);
5347:     PetscHMapIResize(hamp,a->B->cmap->n);
5348:     PetscCalloc1(a->B->cmap->n,&mapping);
5349:     count = 0;
5350:     /* Assume that  a->g is sorted, otherwise the following does not make sense */
5351:     for (i=0;i<a->B->cmap->n;i++) {
5352:       key  = a->garray[i]/dof;
5353:       PetscHMapIHas(hamp,key,&has);
5354:       if (!has) {
5355:         mapping[i] = count;
5356:         PetscHMapISet(hamp,key,count++);
5357:       } else {
5358:         /* Current 'i' has the same value the previous step */
5359:         mapping[i] = count-1;
5360:       }
5361:     }
5362:     ISCreateGeneral(comm,a->B->cmap->n,mapping,PETSC_OWN_POINTER,&map);
5363:     PetscHMapIGetSize(hamp,&htsize);
5364:     if (htsize!=count) SETERRQ2(comm,PETSC_ERR_ARG_INCOMP," Size of hash map %D is inconsistent with count %D \n",htsize,count);
5365:     PetscCalloc1(htsize,&rowindices);
5366:     off = 0;
5367:     PetscHMapIGetKeys(hamp,&off,rowindices);
5368:     PetscHMapIDestroy(&hamp);
5369:     PetscSortInt(htsize,rowindices);
5370:     ISCreateGeneral(comm,htsize,rowindices,PETSC_OWN_POINTER,&rows);
5371:     /* In case, the matrix was already created but users want to recreate the matrix */
5372:     MatDestroy(P_oth);
5373:     MatCreateSeqSubMatrixWithRows_Private(P,rows,P_oth);
5374:     PetscObjectCompose((PetscObject)*P_oth,"aoffdiagtopothmapping",(PetscObject)map);
5375:     ISDestroy(&rows);
5376:   } else if (reuse==MAT_REUSE_MATRIX) {
5377:     /* If matrix was already created, we simply update values using SF objects
5378:      * that as attached to the matrix ealier.
5379:      *  */
5380:     PetscObjectQuery((PetscObject)*P_oth,"diagsf",(PetscObject*)&sf);
5381:     PetscObjectQuery((PetscObject)*P_oth,"offdiagsf",(PetscObject*)&osf);
5382:     if (!sf || !osf) {
5383:       SETERRQ(comm,PETSC_ERR_ARG_NULL,"Matrix is not initialized yet \n");
5384:     }
5385:     p_oth = (Mat_SeqAIJ*) (*P_oth)->data;
5386:     /* Update values in place */
5387:     PetscSFBcastBegin(sf,MPIU_SCALAR,pd->a,p_oth->a);
5388:     PetscSFBcastBegin(osf,MPIU_SCALAR,po->a,p_oth->a);
5389:     PetscSFBcastEnd(sf,MPIU_SCALAR,pd->a,p_oth->a);
5390:     PetscSFBcastEnd(osf,MPIU_SCALAR,po->a,p_oth->a);
5391:   } else {
5392:     SETERRQ(comm,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown reuse type \n");
5393:   }
5394:   PetscLogEventEnd(MAT_GetBrowsOfAocols,A,P,0,0);
5395:   return(0);
5396: }

5398: /*@C
5399:     MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A

5401:     Collective on Mat

5403:    Input Parameters:
5404: +    A,B - the matrices in mpiaij format
5405: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5406: -    rowb, colb - index sets of rows and columns of B to extract (or NULL)

5408:    Output Parameter:
5409: +    rowb, colb - index sets of rows and columns of B to extract
5410: -    B_seq - the sequential matrix generated

5412:     Level: developer

5414: @*/
5415: PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq)
5416: {
5417:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
5419:   PetscInt       *idx,i,start,ncols,nzA,nzB,*cmap,imark;
5420:   IS             isrowb,iscolb;
5421:   Mat            *bseq=NULL;

5424:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5425:     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);
5426:   }
5427:   PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);

5429:   if (scall == MAT_INITIAL_MATRIX) {
5430:     start = A->cmap->rstart;
5431:     cmap  = a->garray;
5432:     nzA   = a->A->cmap->n;
5433:     nzB   = a->B->cmap->n;
5434:     PetscMalloc1(nzA+nzB, &idx);
5435:     ncols = 0;
5436:     for (i=0; i<nzB; i++) {  /* row < local row index */
5437:       if (cmap[i] < start) idx[ncols++] = cmap[i];
5438:       else break;
5439:     }
5440:     imark = i;
5441:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;  /* local rows */
5442:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */
5443:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);
5444:     ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);
5445:   } else {
5446:     if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX");
5447:     isrowb  = *rowb; iscolb = *colb;
5448:     PetscMalloc1(1,&bseq);
5449:     bseq[0] = *B_seq;
5450:   }
5451:   MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);
5452:   *B_seq = bseq[0];
5453:   PetscFree(bseq);
5454:   if (!rowb) {
5455:     ISDestroy(&isrowb);
5456:   } else {
5457:     *rowb = isrowb;
5458:   }
5459:   if (!colb) {
5460:     ISDestroy(&iscolb);
5461:   } else {
5462:     *colb = iscolb;
5463:   }
5464:   PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);
5465:   return(0);
5466: }

5468: /*
5469:     MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns
5470:     of the OFF-DIAGONAL portion of local A

5472:     Collective on Mat

5474:    Input Parameters:
5475: +    A,B - the matrices in mpiaij format
5476: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

5478:    Output Parameter:
5479: +    startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL)
5480: .    startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL)
5481: .    bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL)
5482: -    B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N

5484:     Developer Notes: This directly accesses information inside the VecScatter associated with the matrix-vector product
5485:      for this matrix. This is not desirable..

5487:     Level: developer

5489: */
5490: PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth)
5491: {
5492:   PetscErrorCode         ierr;
5493:   Mat_MPIAIJ             *a=(Mat_MPIAIJ*)A->data;
5494:   Mat_SeqAIJ             *b_oth;
5495:   VecScatter             ctx;
5496:   MPI_Comm               comm;
5497:   const PetscMPIInt      *rprocs,*sprocs;
5498:   const PetscInt         *srow,*rstarts,*sstarts;
5499:   PetscInt               *rowlen,*bufj,*bufJ,ncols = 0,aBn=a->B->cmap->n,row,*b_othi,*b_othj,*rvalues=NULL,*svalues=NULL,*cols,sbs,rbs;
5500:   PetscInt               i,j,k=0,l,ll,nrecvs,nsends,nrows,*rstartsj = 0,*sstartsj,len;
5501:   PetscScalar            *b_otha,*bufa,*bufA,*vals = NULL;
5502:   MPI_Request            *rwaits = NULL,*swaits = NULL;
5503:   MPI_Status             rstatus;
5504:   PetscMPIInt            jj,size,tag,rank,nsends_mpi,nrecvs_mpi;

5507:   PetscObjectGetComm((PetscObject)A,&comm);
5508:   MPI_Comm_size(comm,&size);

5510:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5511:     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);
5512:   }
5513:   PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);
5514:   MPI_Comm_rank(comm,&rank);

5516:   if (size == 1) {
5517:     startsj_s = NULL;
5518:     bufa_ptr  = NULL;
5519:     *B_oth    = NULL;
5520:     return(0);
5521:   }

5523:   ctx = a->Mvctx;
5524:   tag = ((PetscObject)ctx)->tag;

5526:   if (ctx->inuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE," Scatter ctx already in use");
5527:   VecScatterGetRemote_Private(ctx,PETSC_TRUE/*send*/,&nsends,&sstarts,&srow,&sprocs,&sbs);
5528:   /* rprocs[] must be ordered so that indices received from them are ordered in rvalues[], which is key to algorithms used in this subroutine */
5529:   VecScatterGetRemoteOrdered_Private(ctx,PETSC_FALSE/*recv*/,&nrecvs,&rstarts,NULL/*indices not needed*/,&rprocs,&rbs);
5530:   PetscMPIIntCast(nsends,&nsends_mpi);
5531:   PetscMPIIntCast(nrecvs,&nrecvs_mpi);
5532:   PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);

5534:   if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX;
5535:   if (scall == MAT_INITIAL_MATRIX) {
5536:     /* i-array */
5537:     /*---------*/
5538:     /*  post receives */
5539:     if (nrecvs) {PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);} /* rstarts can be NULL when nrecvs=0 */
5540:     for (i=0; i<nrecvs; i++) {
5541:       rowlen = rvalues + rstarts[i]*rbs;
5542:       nrows  = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */
5543:       MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5544:     }

5546:     /* pack the outgoing message */
5547:     PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);

5549:     sstartsj[0] = 0;
5550:     rstartsj[0] = 0;
5551:     len         = 0; /* total length of j or a array to be sent */
5552:     if (nsends) {
5553:       k    = sstarts[0]; /* ATTENTION: sstarts[0] and rstarts[0] are not necessarily zero */
5554:       PetscMalloc1(sbs*(sstarts[nsends]-sstarts[0]),&svalues);
5555:     }
5556:     for (i=0; i<nsends; i++) {
5557:       rowlen = svalues + (sstarts[i]-sstarts[0])*sbs;
5558:       nrows  = sstarts[i+1]-sstarts[i]; /* num of block rows */
5559:       for (j=0; j<nrows; j++) {
5560:         row = srow[k] + B->rmap->range[rank]; /* global row idx */
5561:         for (l=0; l<sbs; l++) {
5562:           MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL); /* rowlength */

5564:           rowlen[j*sbs+l] = ncols;

5566:           len += ncols;
5567:           MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);
5568:         }
5569:         k++;
5570:       }
5571:       MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);

5573:       sstartsj[i+1] = len;  /* starting point of (i+1)-th outgoing msg in bufj and bufa */
5574:     }
5575:     /* recvs and sends of i-array are completed */
5576:     i = nrecvs;
5577:     while (i--) {
5578:       MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5579:     }
5580:     if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5581:     PetscFree(svalues);

5583:     /* allocate buffers for sending j and a arrays */
5584:     PetscMalloc1(len+1,&bufj);
5585:     PetscMalloc1(len+1,&bufa);

5587:     /* create i-array of B_oth */
5588:     PetscMalloc1(aBn+2,&b_othi);

5590:     b_othi[0] = 0;
5591:     len       = 0; /* total length of j or a array to be received */
5592:     k         = 0;
5593:     for (i=0; i<nrecvs; i++) {
5594:       rowlen = rvalues + (rstarts[i]-rstarts[0])*rbs;
5595:       nrows  = (rstarts[i+1]-rstarts[i])*rbs; /* num of rows to be received */
5596:       for (j=0; j<nrows; j++) {
5597:         b_othi[k+1] = b_othi[k] + rowlen[j];
5598:         PetscIntSumError(rowlen[j],len,&len);
5599:         k++;
5600:       }
5601:       rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */
5602:     }
5603:     PetscFree(rvalues);

5605:     /* allocate space for j and a arrrays of B_oth */
5606:     PetscMalloc1(b_othi[aBn]+1,&b_othj);
5607:     PetscMalloc1(b_othi[aBn]+1,&b_otha);

5609:     /* j-array */
5610:     /*---------*/
5611:     /*  post receives of j-array */
5612:     for (i=0; i<nrecvs; i++) {
5613:       nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5614:       MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5615:     }

5617:     /* pack the outgoing message j-array */
5618:     if (nsends) k = sstarts[0];
5619:     for (i=0; i<nsends; i++) {
5620:       nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5621:       bufJ  = bufj+sstartsj[i];
5622:       for (j=0; j<nrows; j++) {
5623:         row = srow[k++] + B->rmap->range[rank];  /* global row idx */
5624:         for (ll=0; ll<sbs; ll++) {
5625:           MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5626:           for (l=0; l<ncols; l++) {
5627:             *bufJ++ = cols[l];
5628:           }
5629:           MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5630:         }
5631:       }
5632:       MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);
5633:     }

5635:     /* recvs and sends of j-array are completed */
5636:     i = nrecvs;
5637:     while (i--) {
5638:       MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5639:     }
5640:     if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5641:   } else if (scall == MAT_REUSE_MATRIX) {
5642:     sstartsj = *startsj_s;
5643:     rstartsj = *startsj_r;
5644:     bufa     = *bufa_ptr;
5645:     b_oth    = (Mat_SeqAIJ*)(*B_oth)->data;
5646:     b_otha   = b_oth->a;
5647:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container");

5649:   /* a-array */
5650:   /*---------*/
5651:   /*  post receives of a-array */
5652:   for (i=0; i<nrecvs; i++) {
5653:     nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5654:     MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);
5655:   }

5657:   /* pack the outgoing message a-array */
5658:   if (nsends) k = sstarts[0];
5659:   for (i=0; i<nsends; i++) {
5660:     nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5661:     bufA  = bufa+sstartsj[i];
5662:     for (j=0; j<nrows; j++) {
5663:       row = srow[k++] + B->rmap->range[rank];  /* global row idx */
5664:       for (ll=0; ll<sbs; ll++) {
5665:         MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5666:         for (l=0; l<ncols; l++) {
5667:           *bufA++ = vals[l];
5668:         }
5669:         MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5670:       }
5671:     }
5672:     MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);
5673:   }
5674:   /* recvs and sends of a-array are completed */
5675:   i = nrecvs;
5676:   while (i--) {
5677:     MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5678:   }
5679:   if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5680:   PetscFree2(rwaits,swaits);

5682:   if (scall == MAT_INITIAL_MATRIX) {
5683:     /* put together the new matrix */
5684:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);

5686:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5687:     /* Since these are PETSc arrays, change flags to free them as necessary. */
5688:     b_oth          = (Mat_SeqAIJ*)(*B_oth)->data;
5689:     b_oth->free_a  = PETSC_TRUE;
5690:     b_oth->free_ij = PETSC_TRUE;
5691:     b_oth->nonew   = 0;

5693:     PetscFree(bufj);
5694:     if (!startsj_s || !bufa_ptr) {
5695:       PetscFree2(sstartsj,rstartsj);
5696:       PetscFree(bufa_ptr);
5697:     } else {
5698:       *startsj_s = sstartsj;
5699:       *startsj_r = rstartsj;
5700:       *bufa_ptr  = bufa;
5701:     }
5702:   }

5704:   VecScatterRestoreRemote_Private(ctx,PETSC_TRUE,&nsends,&sstarts,&srow,&sprocs,&sbs);
5705:   VecScatterRestoreRemoteOrdered_Private(ctx,PETSC_FALSE,&nrecvs,&rstarts,NULL,&rprocs,&rbs);
5706:   PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);
5707:   return(0);
5708: }

5710: /*@C
5711:   MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication.

5713:   Not Collective

5715:   Input Parameters:
5716: . A - The matrix in mpiaij format

5718:   Output Parameter:
5719: + lvec - The local vector holding off-process values from the argument to a matrix-vector product
5720: . colmap - A map from global column index to local index into lvec
5721: - multScatter - A scatter from the argument of a matrix-vector product to lvec

5723:   Level: developer

5725: @*/
5726: #if defined(PETSC_USE_CTABLE)
5727: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter)
5728: #else
5729: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter)
5730: #endif
5731: {
5732:   Mat_MPIAIJ *a;

5739:   a = (Mat_MPIAIJ*) A->data;
5740:   if (lvec) *lvec = a->lvec;
5741:   if (colmap) *colmap = a->colmap;
5742:   if (multScatter) *multScatter = a->Mvctx;
5743:   return(0);
5744: }

5746: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*);
5747: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*);
5748: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJSELL(Mat,MatType,MatReuse,Mat*);
5749: #if defined(PETSC_HAVE_MKL_SPARSE)
5750: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJMKL(Mat,MatType,MatReuse,Mat*);
5751: #endif
5752: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIBAIJ(Mat,MatType,MatReuse,Mat*);
5753: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*);
5754: #if defined(PETSC_HAVE_ELEMENTAL)
5755: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
5756: #endif
5757: #if defined(PETSC_HAVE_HYPRE)
5758: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
5759: #endif
5760: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISELL(Mat,MatType,MatReuse,Mat*);
5761: PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*);
5762: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_IS_XAIJ(Mat);

5764: /*
5765:     Computes (B'*A')' since computing B*A directly is untenable

5767:                n                       p                          p
5768:         (              )       (              )         (                  )
5769:       m (      A       )  *  n (       B      )   =   m (         C        )
5770:         (              )       (              )         (                  )

5772: */
5773: PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C)
5774: {
5776:   Mat            At,Bt,Ct;

5779:   MatTranspose(A,MAT_INITIAL_MATRIX,&At);
5780:   MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);
5781:   MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);
5782:   MatDestroy(&At);
5783:   MatDestroy(&Bt);
5784:   MatTranspose(Ct,MAT_REUSE_MATRIX,&C);
5785:   MatDestroy(&Ct);
5786:   return(0);
5787: }

5789: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat C)
5790: {
5792:   PetscInt       m=A->rmap->n,n=B->cmap->n;

5795:   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);
5796:   MatSetSizes(C,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
5797:   MatSetBlockSizesFromMats(C,A,B);
5798:   MatSetType(C,MATMPIDENSE);
5799:   MatMPIDenseSetPreallocation(C,NULL);
5800:   MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
5801:   MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);

5803:   C->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ;
5804:   return(0);
5805: }

5807: /* ----------------------------------------------------------------*/
5808: static PetscErrorCode MatProductSetFromOptions_MPIDense_MPIAIJ_AB(Mat C)
5809: {
5810:   Mat_Product *product = C->product;
5811:   Mat         A = product->A,B=product->B;

5814:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend)
5815:     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);

5817:   C->ops->matmultsymbolic = MatMatMultSymbolic_MPIDense_MPIAIJ;
5818:   C->ops->productsymbolic = MatProductSymbolic_AB;
5819:   return(0);
5820: }

5822: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_MPIDense_MPIAIJ(Mat C)
5823: {
5825:   Mat_Product    *product = C->product;

5828:   if (product->type == MATPRODUCT_AB) {
5829:     MatProductSetFromOptions_MPIDense_MPIAIJ_AB(C);
5830:   } else SETERRQ1(PetscObjectComm((PetscObject)C),PETSC_ERR_SUP,"MatProduct type %s is not supported for MPIDense and MPIAIJ matrices",MatProductTypes[product->type]);
5831:   return(0);
5832: }
5833: /* ----------------------------------------------------------------*/

5835: /*MC
5836:    MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices.

5838:    Options Database Keys:
5839: . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions()

5841:    Level: beginner

5843:    Notes:
5844:     MatSetValues() may be called for this matrix type with a NULL argument for the numerical values,
5845:     in this case the values associated with the rows and columns one passes in are set to zero
5846:     in the matrix

5848:     MatSetOptions(,MAT_STRUCTURE_ONLY,PETSC_TRUE) may be called for this matrix type. In this no
5849:     space is allocated for the nonzero entries and any entries passed with MatSetValues() are ignored

5851: .seealso: MatCreateAIJ()
5852: M*/

5854: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B)
5855: {
5856:   Mat_MPIAIJ     *b;
5858:   PetscMPIInt    size;

5861:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);

5863:   PetscNewLog(B,&b);
5864:   B->data       = (void*)b;
5865:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
5866:   B->assembled  = PETSC_FALSE;
5867:   B->insertmode = NOT_SET_VALUES;
5868:   b->size       = size;

5870:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);

5872:   /* build cache for off array entries formed */
5873:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

5875:   b->donotstash  = PETSC_FALSE;
5876:   b->colmap      = 0;
5877:   b->garray      = 0;
5878:   b->roworiented = PETSC_TRUE;

5880:   /* stuff used for matrix vector multiply */
5881:   b->lvec  = NULL;
5882:   b->Mvctx = NULL;

5884:   /* stuff for MatGetRow() */
5885:   b->rowindices   = 0;
5886:   b->rowvalues    = 0;
5887:   b->getrowactive = PETSC_FALSE;

5889:   /* flexible pointer used in CUSP/CUSPARSE classes */
5890:   b->spptr = NULL;

5892:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);
5893:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);
5894:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);
5895:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);
5896:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);
5897:   PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_MPIAIJ);
5898:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);
5899:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);
5900:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);
5901:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijsell_C",MatConvert_MPIAIJ_MPIAIJSELL);
5902: #if defined(PETSC_HAVE_MKL_SPARSE)
5903:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijmkl_C",MatConvert_MPIAIJ_MPIAIJMKL);
5904: #endif
5905:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);
5906:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpibaij_C",MatConvert_MPIAIJ_MPIBAIJ);
5907:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);
5908: #if defined(PETSC_HAVE_ELEMENTAL)
5909:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);
5910: #endif
5911:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_XAIJ_IS);
5912:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisell_C",MatConvert_MPIAIJ_MPISELL);
5913:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);
5914:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);
5915: #if defined(PETSC_HAVE_HYPRE)
5916:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);
5917:   PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_transpose_mpiaij_mpiaij_C",MatProductSetFromOptions_Transpose_AIJ_AIJ);
5918: #endif
5919:   PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_is_mpiaij_C",MatProductSetFromOptions_IS_XAIJ);
5920:   PetscObjectComposeFunction((PetscObject)B,"MatProductSetFromOptions_mpiaij_mpiaij_C",MatProductSetFromOptions_MPIAIJ);
5921:   PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);
5922:   return(0);
5923: }

5925: /*@C
5926:      MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal"
5927:          and "off-diagonal" part of the matrix in CSR format.

5929:    Collective

5931:    Input Parameters:
5932: +  comm - MPI communicator
5933: .  m - number of local rows (Cannot be PETSC_DECIDE)
5934: .  n - This value should be the same as the local size used in creating the
5935:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
5936:        calculated if N is given) For square matrices n is almost always m.
5937: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
5938: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
5939: .   i - row indices for "diagonal" portion of matrix; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix
5940: .   j - column indices
5941: .   a - matrix values
5942: .   oi - row indices for "off-diagonal" portion of matrix; that is oi[0] = 0, oi[row] = oi[row-1] + number of elements in that row of the matrix
5943: .   oj - column indices
5944: -   oa - matrix values

5946:    Output Parameter:
5947: .   mat - the matrix

5949:    Level: advanced

5951:    Notes:
5952:        The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user
5953:        must free the arrays once the matrix has been destroyed and not before.

5955:        The i and j indices are 0 based

5957:        See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix

5959:        This sets local rows and cannot be used to set off-processor values.

5961:        Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a
5962:        legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does
5963:        not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because
5964:        the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to
5965:        keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all
5966:        communication if it is known that only local entries will be set.

5968: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
5969:           MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays()
5970: @*/
5971: 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)
5972: {
5974:   Mat_MPIAIJ     *maij;

5977:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
5978:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
5979:   if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0");
5980:   MatCreate(comm,mat);
5981:   MatSetSizes(*mat,m,n,M,N);
5982:   MatSetType(*mat,MATMPIAIJ);
5983:   maij = (Mat_MPIAIJ*) (*mat)->data;

5985:   (*mat)->preallocated = PETSC_TRUE;

5987:   PetscLayoutSetUp((*mat)->rmap);
5988:   PetscLayoutSetUp((*mat)->cmap);

5990:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);
5991:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);

5993:   MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);
5994:   MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);
5995:   MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);
5996:   MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);

5998:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
5999:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
6000:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
6001:   MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
6002:   MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
6003:   return(0);
6004: }

6006: /*
6007:     Special version for direct calls from Fortran
6008: */
6009:  #include <petsc/private/fortranimpl.h>

6011: /* Change these macros so can be used in void function */
6012: #undef CHKERRQ
6013: #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr)
6014: #undef SETERRQ2
6015: #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr)
6016: #undef SETERRQ3
6017: #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr)
6018: #undef SETERRQ
6019: #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr)

6021: #if defined(PETSC_HAVE_FORTRAN_CAPS)
6022: #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ
6023: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
6024: #define matsetvaluesmpiaij_ matsetvaluesmpiaij
6025: #else
6026: #endif
6027: PETSC_EXTERN void matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr)
6028: {
6029:   Mat            mat  = *mmat;
6030:   PetscInt       m    = *mm, n = *mn;
6031:   InsertMode     addv = *maddv;
6032:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
6033:   PetscScalar    value;

6036:   MatCheckPreallocated(mat,1);
6037:   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;

6039: #if defined(PETSC_USE_DEBUG)
6040:   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
6041: #endif
6042:   {
6043:     PetscInt  i,j,rstart  = mat->rmap->rstart,rend = mat->rmap->rend;
6044:     PetscInt  cstart      = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
6045:     PetscBool roworiented = aij->roworiented;

6047:     /* Some Variables required in the macro */
6048:     Mat        A                    = aij->A;
6049:     Mat_SeqAIJ *a                   = (Mat_SeqAIJ*)A->data;
6050:     PetscInt   *aimax               = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
6051:     MatScalar  *aa                  = a->a;
6052:     PetscBool  ignorezeroentries    = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE);
6053:     Mat        B                    = aij->B;
6054:     Mat_SeqAIJ *b                   = (Mat_SeqAIJ*)B->data;
6055:     PetscInt   *bimax               = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
6056:     MatScalar  *ba                  = b->a;
6057:     /* This variable below is only for the PETSC_HAVE_VIENNACL or PETSC_HAVE_CUDA cases, but we define it in all cases because we
6058:      * cannot use "#if defined" inside a macro. */
6059:     PETSC_UNUSED PetscBool inserted = PETSC_FALSE;

6061:     PetscInt  *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
6062:     PetscInt  nonew = a->nonew;
6063:     MatScalar *ap1,*ap2;

6066:     for (i=0; i<m; i++) {
6067:       if (im[i] < 0) continue;
6068: #if defined(PETSC_USE_DEBUG)
6069:       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);
6070: #endif
6071:       if (im[i] >= rstart && im[i] < rend) {
6072:         row      = im[i] - rstart;
6073:         lastcol1 = -1;
6074:         rp1      = aj + ai[row];
6075:         ap1      = aa + ai[row];
6076:         rmax1    = aimax[row];
6077:         nrow1    = ailen[row];
6078:         low1     = 0;
6079:         high1    = nrow1;
6080:         lastcol2 = -1;
6081:         rp2      = bj + bi[row];
6082:         ap2      = ba + bi[row];
6083:         rmax2    = bimax[row];
6084:         nrow2    = bilen[row];
6085:         low2     = 0;
6086:         high2    = nrow2;

6088:         for (j=0; j<n; j++) {
6089:           if (roworiented) value = v[i*n+j];
6090:           else value = v[i+j*m];
6091:           if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && im[i] != in[j]) continue;
6092:           if (in[j] >= cstart && in[j] < cend) {
6093:             col = in[j] - cstart;
6094:             MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
6095: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
6096:             if (A->offloadmask != PETSC_OFFLOAD_UNALLOCATED && inserted) A->offloadmask = PETSC_OFFLOAD_CPU;
6097: #endif
6098:           } else if (in[j] < 0) continue;
6099: #if defined(PETSC_USE_DEBUG)
6100:           /* extra brace on SETERRQ2() is required for --with-errorchecking=0 - due to the next 'else' clause */
6101:           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);}
6102: #endif
6103:           else {
6104:             if (mat->was_assembled) {
6105:               if (!aij->colmap) {
6106:                 MatCreateColmap_MPIAIJ_Private(mat);
6107:               }
6108: #if defined(PETSC_USE_CTABLE)
6109:               PetscTableFind(aij->colmap,in[j]+1,&col);
6110:               col--;
6111: #else
6112:               col = aij->colmap[in[j]] - 1;
6113: #endif
6114:               if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
6115:                 MatDisAssemble_MPIAIJ(mat);
6116:                 col  =  in[j];
6117:                 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
6118:                 B        = aij->B;
6119:                 b        = (Mat_SeqAIJ*)B->data;
6120:                 bimax    = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
6121:                 rp2      = bj + bi[row];
6122:                 ap2      = ba + bi[row];
6123:                 rmax2    = bimax[row];
6124:                 nrow2    = bilen[row];
6125:                 low2     = 0;
6126:                 high2    = nrow2;
6127:                 bm       = aij->B->rmap->n;
6128:                 ba       = b->a;
6129:                 inserted = PETSC_FALSE;
6130:               }
6131:             } else col = in[j];
6132:             MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
6133: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
6134:             if (B->offloadmask != PETSC_OFFLOAD_UNALLOCATED && inserted) B->offloadmask = PETSC_OFFLOAD_CPU;
6135: #endif
6136:           }
6137:         }
6138:       } else if (!aij->donotstash) {
6139:         if (roworiented) {
6140:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
6141:         } else {
6142:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
6143:         }
6144:       }
6145:     }
6146:   }
6147:   PetscFunctionReturnVoid();
6148: }