Date: 2015-10-02T22:06:40+00:00

Actual source code: mpiaij.c
petsc-3.6.2 2015-10-02
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      2: #include <../src/mat/impls/aij/mpi/mpiaij.h>   /*I "petscmat.h" I*/
      3: #include <petsc/private/vecimpl.h>
      4: #include <petsc/private/isimpl.h>
      5: #include <petscblaslapack.h>
      6: #include <petscsf.h>

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

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

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

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

     23:   Level: beginner

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

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

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

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

     40:   Level: beginner

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    231:     Only for square matrices

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

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

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

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

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

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

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

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

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

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

    427: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol)     \
    428: { \
    429:     if (col <= lastcol1)  low1 = 0;     \
    430:     else                 high1 = nrow1; \
    431:     lastcol1 = col;\
    432:     while (high1-low1 > 5) { \
    433:       t = (low1+high1)/2; \
    434:       if (rp1[t] > col) high1 = t; \
    435:       else              low1  = t; \
    436:     } \
    437:       for (_i=low1; _i<high1; _i++) { \
    438:         if (rp1[_i] > col) break; \
    439:         if (rp1[_i] == col) { \
    440:           if (addv == ADD_VALUES) ap1[_i] += value;   \
    441:           else                    ap1[_i] = value; \
    442:           goto a_noinsert; \
    443:         } \
    444:       }  \
    445:       if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
    446:       if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;}                \
    447:       if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
    448:       MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
    449:       N = nrow1++ - 1; a->nz++; high1++; \
    450:       /* shift up all the later entries in this row */ \
    451:       for (ii=N; ii>=_i; ii--) { \
    452:         rp1[ii+1] = rp1[ii]; \
    453:         ap1[ii+1] = ap1[ii]; \
    454:       } \
    455:       rp1[_i] = col;  \
    456:       ap1[_i] = value;  \
    457:       A->nonzerostate++;\
    458:       a_noinsert: ; \
    459:       ailen[row] = nrow1; \
    460: }

    463: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \
    464:   { \
    465:     if (col <= lastcol2) low2 = 0;                        \
    466:     else high2 = nrow2;                                   \
    467:     lastcol2 = col;                                       \
    468:     while (high2-low2 > 5) {                              \
    469:       t = (low2+high2)/2;                                 \
    470:       if (rp2[t] > col) high2 = t;                        \
    471:       else             low2  = t;                         \
    472:     }                                                     \
    473:     for (_i=low2; _i<high2; _i++) {                       \
    474:       if (rp2[_i] > col) break;                           \
    475:       if (rp2[_i] == col) {                               \
    476:         if (addv == ADD_VALUES) ap2[_i] += value;         \
    477:         else                    ap2[_i] = value;          \
    478:         goto b_noinsert;                                  \
    479:       }                                                   \
    480:     }                                                     \
    481:     if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
    482:     if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;}                        \
    483:     if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
    484:     MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
    485:     N = nrow2++ - 1; b->nz++; high2++;                    \
    486:     /* shift up all the later entries in this row */      \
    487:     for (ii=N; ii>=_i; ii--) {                            \
    488:       rp2[ii+1] = rp2[ii];                                \
    489:       ap2[ii+1] = ap2[ii];                                \
    490:     }                                                     \
    491:     rp2[_i] = col;                                        \
    492:     ap2[_i] = value;                                      \
    493:     B->nonzerostate++;                                    \
    494:     b_noinsert: ;                                         \
    495:     bilen[row] = nrow2;                                   \
    496:   }

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

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

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

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

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

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

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

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

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

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

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

    644:   for (i=0; i<m; i++) {
    645:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
    646:     if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1);
    647:     if (idxm[i] >= rstart && idxm[i] < rend) {
    648:       row = idxm[i] - rstart;
    649:       for (j=0; j<n; j++) {
    650:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
    651:         if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1);
    652:         if (idxn[j] >= cstart && idxn[j] < cend) {
    653:           col  = idxn[j] - cstart;
    654:           MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
    655:         } else {
    656:           if (!aij->colmap) {
    657:             MatCreateColmap_MPIAIJ_Private(mat);
    658:           }
    659: #if defined(PETSC_USE_CTABLE)
    660:           PetscTableFind(aij->colmap,idxn[j]+1,&col);
    661:           col--;
    662: #else
    663:           col = aij->colmap[idxn[j]] - 1;
    664: #endif
    665:           if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
    666:           else {
    667:             MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
    668:           }
    669:         }
    670:       }
    671:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
    672:   }
    673:   return(0);
    674: }

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

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

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

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

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

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

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

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

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

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

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

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

    762:   aij->rowvalues = 0;

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

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

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

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

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

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

    835:     VecGetArrayRead(x, &xx);
    836:     VecGetArray(b, &bb);
    837:     for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
    838:     VecRestoreArrayRead(x, &xx);
    839:     VecRestoreArray(b, &bb);
    840:   }
    841:   /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/
    842:   MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
    843:   if ((diag != 0.0) && (mat->A->rmap->N == mat->A->cmap->N)) {
    844:     MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);
    845:   } else if (diag != 0.0) {
    846:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
    847:     if (((Mat_SeqAIJ *) mat->A->data)->nonew) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
    848:     for (r = 0; r < len; ++r) {
    849:       const PetscInt row = lrows[r] + A->rmap->rstart;
    850:       MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);
    851:     }
    852:     MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
    853:     MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);
    854:   } else {
    855:     MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
    856:   }
    857:   PetscFree(lrows);

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

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

    886:   /* Create SF where leaves are input rows and roots are owned rows */
    887:   PetscMalloc1(n, &lrows);
    888:   for (r = 0; r < n; ++r) lrows[r] = -1;
    889:   PetscMalloc1(N, &rrows);
    890:   for (r = 0; r < N; ++r) {
    891:     const PetscInt idx   = rows[r];
    892:     if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N);
    893:     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
    894:       PetscLayoutFindOwner(A->rmap,idx,&p);
    895:     }
    896:     rrows[r].rank  = p;
    897:     rrows[r].index = rows[r] - owners[p];
    898:   }
    899:   PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
    900:   PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
    901:   /* Collect flags for rows to be zeroed */
    902:   PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
    903:   PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
    904:   PetscSFDestroy(&sf);
    905:   /* Compress and put in row numbers */
    906:   for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
    907:   /* zero diagonal part of matrix */
    908:   MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
    909:   /* handle off diagonal part of matrix */
    910:   MatCreateVecs(A,&xmask,NULL);
    911:   VecDuplicate(l->lvec,&lmask);
    912:   VecGetArray(xmask,&bb);
    913:   for (i=0; i<len; i++) bb[lrows[i]] = 1;
    914:   VecRestoreArray(xmask,&bb);
    915:   VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
    916:   VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
    917:   VecDestroy(&xmask);
    918:   if (x) {
    919:     VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
    920:     VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
    921:     VecGetArrayRead(l->lvec,&xx);
    922:     VecGetArray(b,&bb);
    923:   }
    924:   VecGetArray(lmask,&mask);
    925:   /* remove zeroed rows of off diagonal matrix */
    926:   ii = aij->i;
    927:   for (i=0; i<len; i++) {
    928:     PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));
    929:   }
    930:   /* loop over all elements of off process part of matrix zeroing removed columns*/
    931:   if (aij->compressedrow.use) {
    932:     m    = aij->compressedrow.nrows;
    933:     ii   = aij->compressedrow.i;
    934:     ridx = aij->compressedrow.rindex;
    935:     for (i=0; i<m; i++) {
    936:       n  = ii[i+1] - ii[i];
    937:       aj = aij->j + ii[i];
    938:       aa = aij->a + ii[i];

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

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

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

    991:   VecGetLocalSize(xx,&nt);
    992:   if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt);
    993:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    994:   (*a->A->ops->mult)(a->A,xx,yy);
    995:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    996:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
    997:   return(0);
    998: }

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

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

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

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

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

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

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

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

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

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

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

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

    1131:   if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
    1132:   if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition");
    1133:   MatGetDiagonal(a->A,v);
    1134:   return(0);
    1135: }

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

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

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

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

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

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

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

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

    1229:   /* load up the local row counts */
    1230:   PetscMalloc1(rlen+1,&row_lengths);
    1231:   for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];

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

    1251:   /* load up the local column indices */
    1252:   nzmax = nz; /* th processor needs space a largest processor needs */
    1253:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
    1254:   PetscMalloc1(nzmax+1,&column_indices);
    1255:   cnt   = 0;
    1256:   for (i=0; i<mat->rmap->n; i++) {
    1257:     for (j=B->i[i]; j<B->i[i+1]; j++) {
    1258:       if ((col = garray[B->j[j]]) > cstart) break;
    1259:       column_indices[cnt++] = col;
    1260:     }
    1261:     for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart;
    1262:     for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]];
    1263:   }
    1264:   if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);

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

    1287:   /* load up the local column values */
    1288:   PetscMalloc1(nzmax+1,&column_values);
    1289:   cnt  = 0;
    1290:   for (i=0; i<mat->rmap->n; i++) {
    1291:     for (j=B->i[i]; j<B->i[i+1]; j++) {
    1292:       if (garray[B->j[j]] > cstart) break;
    1293:       column_values[cnt++] = B->a[j];
    1294:     }
    1295:     for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k];
    1296:     for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j];
    1297:   }
    1298:   if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    1710:   MatGetInfo(B,MAT_LOCAL,info);

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    2143: PetscErrorCode MatSetUp_MPIAIJ(Mat A)
    2144: {

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

    2152: /*
    2153:    Computes the number of nonzeros per row needed for preallocation when X and Y
    2154:    have different nonzero structure.
    2155: */
    2158: PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *xltog,const PetscInt *yi,const PetscInt *yj,const PetscInt *yltog,PetscInt *nnz)
    2159: {
    2160:   PetscInt       i,j,k,nzx,nzy;

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

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

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

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

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

    2238: extern PetscErrorCode  MatConjugate_SeqAIJ(Mat);

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

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

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

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

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

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

    2283: #if defined(PETSC_HAVE_PBGL)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    2618: /* -------------------------------------------------------------------*/
    2619: static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ,
    2620:                                        MatGetRow_MPIAIJ,
    2621:                                        MatRestoreRow_MPIAIJ,
    2622:                                        MatMult_MPIAIJ,
    2623:                                 /* 4*/ MatMultAdd_MPIAIJ,
    2624:                                        MatMultTranspose_MPIAIJ,
    2625:                                        MatMultTransposeAdd_MPIAIJ,
    2626: #if defined(PETSC_HAVE_PBGL)
    2627:                                        MatSolve_MPIAIJ,
    2628: #else
    2629:                                        0,
    2630: #endif
    2631:                                        0,
    2632:                                        0,
    2633:                                 /*10*/ 0,
    2634:                                        0,
    2635:                                        0,
    2636:                                        MatSOR_MPIAIJ,
    2637:                                        MatTranspose_MPIAIJ,
    2638:                                 /*15*/ MatGetInfo_MPIAIJ,
    2639:                                        MatEqual_MPIAIJ,
    2640:                                        MatGetDiagonal_MPIAIJ,
    2641:                                        MatDiagonalScale_MPIAIJ,
    2642:                                        MatNorm_MPIAIJ,
    2643:                                 /*20*/ MatAssemblyBegin_MPIAIJ,
    2644:                                        MatAssemblyEnd_MPIAIJ,
    2645:                                        MatSetOption_MPIAIJ,
    2646:                                        MatZeroEntries_MPIAIJ,
    2647:                                 /*24*/ MatZeroRows_MPIAIJ,
    2648:                                        0,
    2649: #if defined(PETSC_HAVE_PBGL)
    2650:                                        0,
    2651: #else
    2652:                                        0,
    2653: #endif
    2654:                                        0,
    2655:                                        0,
    2656:                                 /*29*/ MatSetUp_MPIAIJ,
    2657: #if defined(PETSC_HAVE_PBGL)
    2658:                                        0,
    2659: #else
    2660:                                        0,
    2661: #endif
    2662:                                        0,
    2663:                                        0,
    2664:                                        0,
    2665:                                 /*34*/ MatDuplicate_MPIAIJ,
    2666:                                        0,
    2667:                                        0,
    2668:                                        0,
    2669:                                        0,
    2670:                                 /*39*/ MatAXPY_MPIAIJ,
    2671:                                        MatGetSubMatrices_MPIAIJ,
    2672:                                        MatIncreaseOverlap_MPIAIJ,
    2673:                                        MatGetValues_MPIAIJ,
    2674:                                        MatCopy_MPIAIJ,
    2675:                                 /*44*/ MatGetRowMax_MPIAIJ,
    2676:                                        MatScale_MPIAIJ,
    2677:                                        MatShift_MPIAIJ,
    2678:                                        MatDiagonalSet_MPIAIJ,
    2679:                                        MatZeroRowsColumns_MPIAIJ,
    2680:                                 /*49*/ MatSetRandom_MPIAIJ,
    2681:                                        0,
    2682:                                        0,
    2683:                                        0,
    2684:                                        0,
    2685:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
    2686:                                        0,
    2687:                                        MatSetUnfactored_MPIAIJ,
    2688:                                        MatPermute_MPIAIJ,
    2689:                                        0,
    2690:                                 /*59*/ MatGetSubMatrix_MPIAIJ,
    2691:                                        MatDestroy_MPIAIJ,
    2692:                                        MatView_MPIAIJ,
    2693:                                        0,
    2694:                                        MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ,
    2695:                                 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ,
    2696:                                        MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ,
    2697:                                        0,
    2698:                                        0,
    2699:                                        0,
    2700:                                 /*69*/ MatGetRowMaxAbs_MPIAIJ,
    2701:                                        MatGetRowMinAbs_MPIAIJ,
    2702:                                        0,
    2703:                                        MatSetColoring_MPIAIJ,
    2704:                                        0,
    2705:                                        MatSetValuesAdifor_MPIAIJ,
    2706:                                 /*75*/ MatFDColoringApply_AIJ,
    2707:                                        0,
    2708:                                        0,
    2709:                                        0,
    2710:                                        MatFindZeroDiagonals_MPIAIJ,
    2711:                                 /*80*/ 0,
    2712:                                        0,
    2713:                                        0,
    2714:                                 /*83*/ MatLoad_MPIAIJ,
    2715:                                        0,
    2716:                                        0,
    2717:                                        0,
    2718:                                        0,
    2719:                                        0,
    2720:                                 /*89*/ MatMatMult_MPIAIJ_MPIAIJ,
    2721:                                        MatMatMultSymbolic_MPIAIJ_MPIAIJ,
    2722:                                        MatMatMultNumeric_MPIAIJ_MPIAIJ,
    2723:                                        MatPtAP_MPIAIJ_MPIAIJ,
    2724:                                        MatPtAPSymbolic_MPIAIJ_MPIAIJ,
    2725:                                 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ,
    2726:                                        0,
    2727:                                        0,
    2728:                                        0,
    2729:                                        0,
    2730:                                 /*99*/ 0,
    2731:                                        0,
    2732:                                        0,
    2733:                                        MatConjugate_MPIAIJ,
    2734:                                        0,
    2735:                                 /*104*/MatSetValuesRow_MPIAIJ,
    2736:                                        MatRealPart_MPIAIJ,
    2737:                                        MatImaginaryPart_MPIAIJ,
    2738:                                        0,
    2739:                                        0,
    2740:                                 /*109*/0,
    2741:                                        0,
    2742:                                        MatGetRowMin_MPIAIJ,
    2743:                                        0,
    2744:                                        0,
    2745:                                 /*114*/MatGetSeqNonzeroStructure_MPIAIJ,
    2746:                                        0,
    2747:                                        MatGetGhosts_MPIAIJ,
    2748:                                        0,
    2749:                                        0,
    2750:                                 /*119*/0,
    2751:                                        0,
    2752:                                        0,
    2753:                                        0,
    2754:                                        MatGetMultiProcBlock_MPIAIJ,
    2755:                                 /*124*/MatFindNonzeroRows_MPIAIJ,
    2756:                                        MatGetColumnNorms_MPIAIJ,
    2757:                                        MatInvertBlockDiagonal_MPIAIJ,
    2758:                                        0,
    2759:                                        MatGetSubMatricesMPI_MPIAIJ,
    2760:                                 /*129*/0,
    2761:                                        MatTransposeMatMult_MPIAIJ_MPIAIJ,
    2762:                                        MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ,
    2763:                                        MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ,
    2764:                                        0,
    2765:                                 /*134*/0,
    2766:                                        0,
    2767:                                        0,
    2768:                                        0,
    2769:                                        0,
    2770:                                 /*139*/0,
    2771:                                        0,
    2772:                                        0,
    2773:                                        MatFDColoringSetUp_MPIXAIJ,
    2774:                                        MatFindOffBlockDiagonalEntries_MPIAIJ,
    2775:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ
    2776: };

    2778: /* ----------------------------------------------------------------------------------------*/

    2782: PetscErrorCode  MatStoreValues_MPIAIJ(Mat mat)
    2783: {
    2784:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

    2788:   MatStoreValues(aij->A);
    2789:   MatStoreValues(aij->B);
    2790:   return(0);
    2791: }

    2795: PetscErrorCode  MatRetrieveValues_MPIAIJ(Mat mat)
    2796: {
    2797:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;

    2801:   MatRetrieveValues(aij->A);
    2802:   MatRetrieveValues(aij->B);
    2803:   return(0);
    2804: }

    2808: PetscErrorCode  MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
    2809: {
    2810:   Mat_MPIAIJ     *b;

    2814:   PetscLayoutSetUp(B->rmap);
    2815:   PetscLayoutSetUp(B->cmap);
    2816:   b = (Mat_MPIAIJ*)B->data;

    2818:   if (!B->preallocated) {
    2819:     /* Explicitly create 2 MATSEQAIJ matrices. */
    2820:     MatCreate(PETSC_COMM_SELF,&b->A);
    2821:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
    2822:     MatSetBlockSizesFromMats(b->A,B,B);
    2823:     MatSetType(b->A,MATSEQAIJ);
    2824:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
    2825:     MatCreate(PETSC_COMM_SELF,&b->B);
    2826:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
    2827:     MatSetBlockSizesFromMats(b->B,B,B);
    2828:     MatSetType(b->B,MATSEQAIJ);
    2829:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
    2830:   }

    2832:   MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);
    2833:   MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);
    2834:   B->preallocated = PETSC_TRUE;
    2835:   return(0);
    2836: }

    2840: PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
    2841: {
    2842:   Mat            mat;
    2843:   Mat_MPIAIJ     *a,*oldmat = (Mat_MPIAIJ*)matin->data;

    2847:   *newmat = 0;
    2848:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
    2849:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
    2850:   MatSetBlockSizesFromMats(mat,matin,matin);
    2851:   MatSetType(mat,((PetscObject)matin)->type_name);
    2852:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
    2853:   a       = (Mat_MPIAIJ*)mat->data;

    2855:   mat->factortype   = matin->factortype;
    2856:   mat->assembled    = PETSC_TRUE;
    2857:   mat->insertmode   = NOT_SET_VALUES;
    2858:   mat->preallocated = PETSC_TRUE;

    2860:   a->size         = oldmat->size;
    2861:   a->rank         = oldmat->rank;
    2862:   a->donotstash   = oldmat->donotstash;
    2863:   a->roworiented  = oldmat->roworiented;
    2864:   a->rowindices   = 0;
    2865:   a->rowvalues    = 0;
    2866:   a->getrowactive = PETSC_FALSE;

    2868:   PetscLayoutReference(matin->rmap,&mat->rmap);
    2869:   PetscLayoutReference(matin->cmap,&mat->cmap);

    2871:   if (oldmat->colmap) {
    2872: #if defined(PETSC_USE_CTABLE)
    2873:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
    2874: #else
    2875:     PetscMalloc1(mat->cmap->N,&a->colmap);
    2876:     PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
    2877:     PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));
    2878: #endif
    2879:   } else a->colmap = 0;
    2880:   if (oldmat->garray) {
    2881:     PetscInt len;
    2882:     len  = oldmat->B->cmap->n;
    2883:     PetscMalloc1(len+1,&a->garray);
    2884:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
    2885:     if (len) { PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt)); }
    2886:   } else a->garray = 0;

    2888:   VecDuplicate(oldmat->lvec,&a->lvec);
    2889:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
    2890:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
    2891:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
    2892:   MatDuplicate(oldmat->A,cpvalues,&a->A);
    2893:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
    2894:   MatDuplicate(oldmat->B,cpvalues,&a->B);
    2895:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
    2896:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
    2897:   *newmat = mat;
    2898:   return(0);
    2899: }

    2905: PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer)
    2906: {
    2907:   PetscScalar    *vals,*svals;
    2908:   MPI_Comm       comm;
    2910:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
    2911:   PetscInt       i,nz,j,rstart,rend,mmax,maxnz = 0;
    2912:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols;
    2913:   PetscInt       *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols;
    2914:   PetscInt       cend,cstart,n,*rowners;
    2915:   int            fd;
    2916:   PetscInt       bs = newMat->rmap->bs;

    2919:   /* force binary viewer to load .info file if it has not yet done so */
    2920:   PetscViewerSetUp(viewer);
    2921:   PetscObjectGetComm((PetscObject)viewer,&comm);
    2922:   MPI_Comm_size(comm,&size);
    2923:   MPI_Comm_rank(comm,&rank);
    2924:   PetscViewerBinaryGetDescriptor(viewer,&fd);
    2925:   if (!rank) {
    2926:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
    2927:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
    2928:   }

    2930:   PetscOptionsBegin(comm,NULL,"Options for loading MPIAIJ matrix","Mat");
    2931:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
    2932:   PetscOptionsEnd();
    2933:   if (bs < 0) bs = 1;

    2935:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
    2936:   M    = header[1]; N = header[2];

    2938:   /* If global sizes are set, check if they are consistent with that given in the file */
    2939:   if (newMat->rmap->N >= 0 && newMat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newMat->rmap->N,M);
    2940:   if (newMat->cmap->N >=0 && newMat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newMat->cmap->N,N);

    2942:   /* determine ownership of all (block) rows */
    2943:   if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs);
    2944:   if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank));    /* PETSC_DECIDE */
    2945:   else m = newMat->rmap->n; /* Set by user */

    2947:   PetscMalloc1(size+1,&rowners);
    2948:   MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

    2950:   /* First process needs enough room for process with most rows */
    2951:   if (!rank) {
    2952:     mmax = rowners[1];
    2953:     for (i=2; i<=size; i++) {
    2954:       mmax = PetscMax(mmax, rowners[i]);
    2955:     }
    2956:   } else mmax = -1;             /* unused, but compilers complain */

    2958:   rowners[0] = 0;
    2959:   for (i=2; i<=size; i++) {
    2960:     rowners[i] += rowners[i-1];
    2961:   }
    2962:   rstart = rowners[rank];
    2963:   rend   = rowners[rank+1];

    2965:   /* distribute row lengths to all processors */
    2966:   PetscMalloc2(m,&ourlens,m,&offlens);
    2967:   if (!rank) {
    2968:     PetscBinaryRead(fd,ourlens,m,PETSC_INT);
    2969:     PetscMalloc1(mmax,&rowlengths);
    2970:     PetscCalloc1(size,&procsnz);
    2971:     for (j=0; j<m; j++) {
    2972:       procsnz[0] += ourlens[j];
    2973:     }
    2974:     for (i=1; i<size; i++) {
    2975:       PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);
    2976:       /* calculate the number of nonzeros on each processor */
    2977:       for (j=0; j<rowners[i+1]-rowners[i]; j++) {
    2978:         procsnz[i] += rowlengths[j];
    2979:       }
    2980:       MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
    2981:     }
    2982:     PetscFree(rowlengths);
    2983:   } else {
    2984:     MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);
    2985:   }

    2987:   if (!rank) {
    2988:     /* determine max buffer needed and allocate it */
    2989:     maxnz = 0;
    2990:     for (i=0; i<size; i++) {
    2991:       maxnz = PetscMax(maxnz,procsnz[i]);
    2992:     }
    2993:     PetscMalloc1(maxnz,&cols);

    2995:     /* read in my part of the matrix column indices  */
    2996:     nz   = procsnz[0];
    2997:     PetscMalloc1(nz,&mycols);
    2998:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);

    3000:     /* read in every one elses and ship off */
    3001:     for (i=1; i<size; i++) {
    3002:       nz   = procsnz[i];
    3003:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
    3004:       MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);
    3005:     }
    3006:     PetscFree(cols);
    3007:   } else {
    3008:     /* determine buffer space needed for message */
    3009:     nz = 0;
    3010:     for (i=0; i<m; i++) {
    3011:       nz += ourlens[i];
    3012:     }
    3013:     PetscMalloc1(nz,&mycols);

    3015:     /* receive message of column indices*/
    3016:     MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);
    3017:   }

    3019:   /* determine column ownership if matrix is not square */
    3020:   if (N != M) {
    3021:     if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank);
    3022:     else n = newMat->cmap->n;
    3023:     MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);
    3024:     cstart = cend - n;
    3025:   } else {
    3026:     cstart = rstart;
    3027:     cend   = rend;
    3028:     n      = cend - cstart;
    3029:   }

    3031:   /* loop over local rows, determining number of off diagonal entries */
    3032:   PetscMemzero(offlens,m*sizeof(PetscInt));
    3033:   jj   = 0;
    3034:   for (i=0; i<m; i++) {
    3035:     for (j=0; j<ourlens[i]; j++) {
    3036:       if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++;
    3037:       jj++;
    3038:     }
    3039:   }

    3041:   for (i=0; i<m; i++) {
    3042:     ourlens[i] -= offlens[i];
    3043:   }
    3044:   MatSetSizes(newMat,m,n,M,N);

    3046:   if (bs > 1) {MatSetBlockSize(newMat,bs);}

    3048:   MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);

    3050:   for (i=0; i<m; i++) {
    3051:     ourlens[i] += offlens[i];
    3052:   }

    3054:   if (!rank) {
    3055:     PetscMalloc1(maxnz+1,&vals);

    3057:     /* read in my part of the matrix numerical values  */
    3058:     nz   = procsnz[0];
    3059:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);

    3061:     /* insert into matrix */
    3062:     jj      = rstart;
    3063:     smycols = mycols;
    3064:     svals   = vals;
    3065:     for (i=0; i<m; i++) {
    3066:       MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
    3067:       smycols += ourlens[i];
    3068:       svals   += ourlens[i];
    3069:       jj++;
    3070:     }

    3072:     /* read in other processors and ship out */
    3073:     for (i=1; i<size; i++) {
    3074:       nz   = procsnz[i];
    3075:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    3076:       MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);
    3077:     }
    3078:     PetscFree(procsnz);
    3079:   } else {
    3080:     /* receive numeric values */
    3081:     PetscMalloc1(nz+1,&vals);

    3083:     /* receive message of values*/
    3084:     MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);

    3086:     /* insert into matrix */
    3087:     jj      = rstart;
    3088:     smycols = mycols;
    3089:     svals   = vals;
    3090:     for (i=0; i<m; i++) {
    3091:       MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
    3092:       smycols += ourlens[i];
    3093:       svals   += ourlens[i];
    3094:       jj++;
    3095:     }
    3096:   }
    3097:   PetscFree2(ourlens,offlens);
    3098:   PetscFree(vals);
    3099:   PetscFree(mycols);
    3100:   PetscFree(rowners);
    3101:   MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);
    3102:   MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);
    3103:   return(0);
    3104: }

    3108: /* TODO: Not scalable because of ISAllGather(). */
    3109: PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
    3110: {
    3112:   IS             iscol_local;
    3113:   PetscInt       csize;

    3116:   ISGetLocalSize(iscol,&csize);
    3117:   if (call == MAT_REUSE_MATRIX) {
    3118:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
    3119:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
    3120:   } else {
    3121:     PetscInt cbs;
    3122:     ISGetBlockSize(iscol,&cbs);
    3123:     ISAllGather(iscol,&iscol_local);
    3124:     ISSetBlockSize(iscol_local,cbs);
    3125:   }
    3126:   MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
    3127:   if (call == MAT_INITIAL_MATRIX) {
    3128:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
    3129:     ISDestroy(&iscol_local);
    3130:   }
    3131:   return(0);
    3132: }

    3134: extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*);
    3137: /*
    3138:     Not great since it makes two copies of the submatrix, first an SeqAIJ
    3139:   in local and then by concatenating the local matrices the end result.
    3140:   Writing it directly would be much like MatGetSubMatrices_MPIAIJ()

    3142:   Note: This requires a sequential iscol with all indices.
    3143: */
    3144: PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
    3145: {
    3147:   PetscMPIInt    rank,size;
    3148:   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs;
    3149:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol;
    3150:   PetscBool      allcolumns, colflag;
    3151:   Mat            M,Mreuse;
    3152:   MatScalar      *vwork,*aa;
    3153:   MPI_Comm       comm;
    3154:   Mat_SeqAIJ     *aij;

    3157:   PetscObjectGetComm((PetscObject)mat,&comm);
    3158:   MPI_Comm_rank(comm,&rank);
    3159:   MPI_Comm_size(comm,&size);

    3161:   ISIdentity(iscol,&colflag);
    3162:   ISGetLocalSize(iscol,&ncol);
    3163:   if (colflag && ncol == mat->cmap->N) {
    3164:     allcolumns = PETSC_TRUE;
    3165:   } else {
    3166:     allcolumns = PETSC_FALSE;
    3167:   }
    3168:   if (call ==  MAT_REUSE_MATRIX) {
    3169:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
    3170:     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
    3171:     MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);
    3172:   } else {
    3173:     MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);
    3174:   }

    3176:   /*
    3177:       m - number of local rows
    3178:       n - number of columns (same on all processors)
    3179:       rstart - first row in new global matrix generated
    3180:   */
    3181:   MatGetSize(Mreuse,&m,&n);
    3182:   MatGetBlockSizes(Mreuse,&bs,&cbs);
    3183:   if (call == MAT_INITIAL_MATRIX) {
    3184:     aij = (Mat_SeqAIJ*)(Mreuse)->data;
    3185:     ii  = aij->i;
    3186:     jj  = aij->j;

    3188:     /*
    3189:         Determine the number of non-zeros in the diagonal and off-diagonal
    3190:         portions of the matrix in order to do correct preallocation
    3191:     */

    3193:     /* first get start and end of "diagonal" columns */
    3194:     if (csize == PETSC_DECIDE) {
    3195:       ISGetSize(isrow,&mglobal);
    3196:       if (mglobal == n) { /* square matrix */
    3197:         nlocal = m;
    3198:       } else {
    3199:         nlocal = n/size + ((n % size) > rank);
    3200:       }
    3201:     } else {
    3202:       nlocal = csize;
    3203:     }
    3204:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
    3205:     rstart = rend - nlocal;
    3206:     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);

    3208:     /* next, compute all the lengths */
    3209:     PetscMalloc1(2*m+1,&dlens);
    3210:     olens = dlens + m;
    3211:     for (i=0; i<m; i++) {
    3212:       jend = ii[i+1] - ii[i];
    3213:       olen = 0;
    3214:       dlen = 0;
    3215:       for (j=0; j<jend; j++) {
    3216:         if (*jj < rstart || *jj >= rend) olen++;
    3217:         else dlen++;
    3218:         jj++;
    3219:       }
    3220:       olens[i] = olen;
    3221:       dlens[i] = dlen;
    3222:     }
    3223:     MatCreate(comm,&M);
    3224:     MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);
    3225:     MatSetBlockSizes(M,bs,cbs);
    3226:     MatSetType(M,((PetscObject)mat)->type_name);
    3227:     MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
    3228:     PetscFree(dlens);
    3229:   } else {
    3230:     PetscInt ml,nl;

    3232:     M    = *newmat;
    3233:     MatGetLocalSize(M,&ml,&nl);
    3234:     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
    3235:     MatZeroEntries(M);
    3236:     /*
    3237:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
    3238:        rather than the slower MatSetValues().
    3239:     */
    3240:     M->was_assembled = PETSC_TRUE;
    3241:     M->assembled     = PETSC_FALSE;
    3242:   }
    3243:   MatGetOwnershipRange(M,&rstart,&rend);
    3244:   aij  = (Mat_SeqAIJ*)(Mreuse)->data;
    3245:   ii   = aij->i;
    3246:   jj   = aij->j;
    3247:   aa   = aij->a;
    3248:   for (i=0; i<m; i++) {
    3249:     row   = rstart + i;
    3250:     nz    = ii[i+1] - ii[i];
    3251:     cwork = jj;     jj += nz;
    3252:     vwork = aa;     aa += nz;
    3253:     MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
    3254:   }

    3256:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
    3257:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
    3258:   *newmat = M;

    3260:   /* save submatrix used in processor for next request */
    3261:   if (call ==  MAT_INITIAL_MATRIX) {
    3262:     PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
    3263:     MatDestroy(&Mreuse);
    3264:   }
    3265:   return(0);
    3266: }

    3270: PetscErrorCode  MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
    3271: {
    3272:   PetscInt       m,cstart, cend,j,nnz,i,d;
    3273:   PetscInt       *d_nnz,*o_nnz,nnz_max = 0,rstart,ii;
    3274:   const PetscInt *JJ;
    3275:   PetscScalar    *values;

    3279:   if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]);

    3281:   PetscLayoutSetUp(B->rmap);
    3282:   PetscLayoutSetUp(B->cmap);
    3283:   m      = B->rmap->n;
    3284:   cstart = B->cmap->rstart;
    3285:   cend   = B->cmap->rend;
    3286:   rstart = B->rmap->rstart;

    3288:   PetscMalloc2(m,&d_nnz,m,&o_nnz);

    3290: #if defined(PETSC_USE_DEBUGGING)
    3291:   for (i=0; i<m; i++) {
    3292:     nnz = Ii[i+1]- Ii[i];
    3293:     JJ  = J + Ii[i];
    3294:     if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz);
    3295:     if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j);
    3296:     if (nnz && (JJ[nnz-1] >= B->cmap->N) SETERRRQ3(PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N);
    3297:   }
    3298: #endif

    3300:   for (i=0; i<m; i++) {
    3301:     nnz     = Ii[i+1]- Ii[i];
    3302:     JJ      = J + Ii[i];
    3303:     nnz_max = PetscMax(nnz_max,nnz);
    3304:     d       = 0;
    3305:     for (j=0; j<nnz; j++) {
    3306:       if (cstart <= JJ[j] && JJ[j] < cend) d++;
    3307:     }
    3308:     d_nnz[i] = d;
    3309:     o_nnz[i] = nnz - d;
    3310:   }
    3311:   MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
    3312:   PetscFree2(d_nnz,o_nnz);

    3314:   if (v) values = (PetscScalar*)v;
    3315:   else {
    3316:     PetscCalloc1(nnz_max+1,&values);
    3317:   }

    3319:   for (i=0; i<m; i++) {
    3320:     ii   = i + rstart;
    3321:     nnz  = Ii[i+1]- Ii[i];
    3322:     MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);
    3323:   }
    3324:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    3325:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

    3327:   if (!v) {
    3328:     PetscFree(values);
    3329:   }
    3330:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    3331:   return(0);
    3332: }

    3336: /*@
    3337:    MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format
    3338:    (the default parallel PETSc format).

    3340:    Collective on MPI_Comm

    3342:    Input Parameters:
    3343: +  B - the matrix
    3344: .  i - the indices into j for the start of each local row (starts with zero)
    3345: .  j - the column indices for each local row (starts with zero)
    3346: -  v - optional values in the matrix

    3348:    Level: developer

    3350:    Notes:
    3351:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
    3352:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
    3353:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

    3355:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

    3357:        The format which is used for the sparse matrix input, is equivalent to a
    3358:     row-major ordering.. i.e for the following matrix, the input data expected is
    3359:     as shown:

    3361:         1 0 0
    3362:         2 0 3     P0
    3363:        -------
    3364:         4 5 6     P1

    3366:      Process0 [P0]: rows_owned=[0,1]
    3367:         i =  {0,1,3}  [size = nrow+1  = 2+1]
    3368:         j =  {0,0,2}  [size = nz = 6]
    3369:         v =  {1,2,3}  [size = nz = 6]

    3371:      Process1 [P1]: rows_owned=[2]
    3372:         i =  {0,3}    [size = nrow+1  = 1+1]
    3373:         j =  {0,1,2}  [size = nz = 6]
    3374:         v =  {4,5,6}  [size = nz = 6]

    3376: .keywords: matrix, aij, compressed row, sparse, parallel

    3378: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ,
    3379:           MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays()
    3380: @*/
    3381: PetscErrorCode  MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
    3382: {

    3386:   PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));
    3387:   return(0);
    3388: }

    3392: /*@C
    3393:    MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format
    3394:    (the default parallel PETSc format).  For good matrix assembly performance
    3395:    the user should preallocate the matrix storage by setting the parameters
    3396:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    3397:    performance can be increased by more than a factor of 50.

    3399:    Collective on MPI_Comm

    3401:    Input Parameters:
    3402: +  B - the matrix
    3403: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
    3404:            (same value is used for all local rows)
    3405: .  d_nnz - array containing the number of nonzeros in the various rows of the
    3406:            DIAGONAL portion of the local submatrix (possibly different for each row)
    3407:            or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
    3408:            The size of this array is equal to the number of local rows, i.e 'm'.
    3409:            For matrices that will be factored, you must leave room for (and set)
    3410:            the diagonal entry even if it is zero.
    3411: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
    3412:            submatrix (same value is used for all local rows).
    3413: -  o_nnz - array containing the number of nonzeros in the various rows of the
    3414:            OFF-DIAGONAL portion of the local submatrix (possibly different for
    3415:            each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
    3416:            structure. The size of this array is equal to the number
    3417:            of local rows, i.e 'm'.

    3419:    If the *_nnz parameter is given then the *_nz parameter is ignored

    3421:    The AIJ format (also called the Yale sparse matrix format or
    3422:    compressed row storage (CSR)), is fully compatible with standard Fortran 77
    3423:    storage.  The stored row and column indices begin with zero.
    3424:    See Users-Manual: ch_mat for details.

    3426:    The parallel matrix is partitioned such that the first m0 rows belong to
    3427:    process 0, the next m1 rows belong to process 1, the next m2 rows belong
    3428:    to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.

    3430:    The DIAGONAL portion of the local submatrix of a processor can be defined
    3431:    as the submatrix which is obtained by extraction the part corresponding to
    3432:    the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
    3433:    first row that belongs to the processor, r2 is the last row belonging to
    3434:    the this processor, and c1-c2 is range of indices of the local part of a
    3435:    vector suitable for applying the matrix to.  This is an mxn matrix.  In the
    3436:    common case of a square matrix, the row and column ranges are the same and
    3437:    the DIAGONAL part is also square. The remaining portion of the local
    3438:    submatrix (mxN) constitute the OFF-DIAGONAL portion.

    3440:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

    3442:    You can call MatGetInfo() to get information on how effective the preallocation was;
    3443:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
    3444:    You can also run with the option -info and look for messages with the string
    3445:    malloc in them to see if additional memory allocation was needed.

    3447:    Example usage:

    3449:    Consider the following 8x8 matrix with 34 non-zero values, that is
    3450:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
    3451:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
    3452:    as follows:

    3454: .vb
    3455:             1  2  0  |  0  3  0  |  0  4
    3456:     Proc0   0  5  6  |  7  0  0  |  8  0
    3457:             9  0 10  | 11  0  0  | 12  0
    3458:     -------------------------------------
    3459:            13  0 14  | 15 16 17  |  0  0
    3460:     Proc1   0 18  0  | 19 20 21  |  0  0
    3461:             0  0  0  | 22 23  0  | 24  0
    3462:     -------------------------------------
    3463:     Proc2  25 26 27  |  0  0 28  | 29  0
    3464:            30  0  0  | 31 32 33  |  0 34
    3465: .ve

    3467:    This can be represented as a collection of submatrices as:

    3469: .vb
    3470:       A B C
    3471:       D E F
    3472:       G H I
    3473: .ve

    3475:    Where the submatrices A,B,C are owned by proc0, D,E,F are
    3476:    owned by proc1, G,H,I are owned by proc2.

    3478:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
    3479:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
    3480:    The 'M','N' parameters are 8,8, and have the same values on all procs.

    3482:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
    3483:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
    3484:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
    3485:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
    3486:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
    3487:    matrix, ans [DF] as another SeqAIJ matrix.

    3489:    When d_nz, o_nz parameters are specified, d_nz storage elements are
    3490:    allocated for every row of the local diagonal submatrix, and o_nz
    3491:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
    3492:    One way to choose d_nz and o_nz is to use the max nonzerors per local
    3493:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
    3494:    In this case, the values of d_nz,o_nz are:
    3495: .vb
    3496:      proc0 : dnz = 2, o_nz = 2
    3497:      proc1 : dnz = 3, o_nz = 2
    3498:      proc2 : dnz = 1, o_nz = 4
    3499: .ve
    3500:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
    3501:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
    3502:    for proc3. i.e we are using 12+15+10=37 storage locations to store
    3503:    34 values.

    3505:    When d_nnz, o_nnz parameters are specified, the storage is specified
    3506:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
    3507:    In the above case the values for d_nnz,o_nnz are:
    3508: .vb
    3509:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
    3510:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
    3511:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
    3512: .ve
    3513:    Here the space allocated is sum of all the above values i.e 34, and
    3514:    hence pre-allocation is perfect.

    3516:    Level: intermediate

    3518: .keywords: matrix, aij, compressed row, sparse, parallel

    3520: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(),
    3521:           MPIAIJ, MatGetInfo(), PetscSplitOwnership()
    3522: @*/
    3523: PetscErrorCode  MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
    3524: {

    3530:   PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
    3531:   return(0);
    3532: }

    3536: /*@
    3537:      MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard
    3538:          CSR format the local rows.

    3540:    Collective on MPI_Comm

    3542:    Input Parameters:
    3543: +  comm - MPI communicator
    3544: .  m - number of local rows (Cannot be PETSC_DECIDE)
    3545: .  n - This value should be the same as the local size used in creating the
    3546:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
    3547:        calculated if N is given) For square matrices n is almost always m.
    3548: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    3549: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    3550: .   i - row indices
    3551: .   j - column indices
    3552: -   a - matrix values

    3554:    Output Parameter:
    3555: .   mat - the matrix

    3557:    Level: intermediate

    3559:    Notes:
    3560:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
    3561:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
    3562:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

    3564:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

    3566:        The format which is used for the sparse matrix input, is equivalent to a
    3567:     row-major ordering.. i.e for the following matrix, the input data expected is
    3568:     as shown:

    3570:         1 0 0
    3571:         2 0 3     P0
    3572:        -------
    3573:         4 5 6     P1

    3575:      Process0 [P0]: rows_owned=[0,1]
    3576:         i =  {0,1,3}  [size = nrow+1  = 2+1]
    3577:         j =  {0,0,2}  [size = nz = 6]
    3578:         v =  {1,2,3}  [size = nz = 6]

    3580:      Process1 [P1]: rows_owned=[2]
    3581:         i =  {0,3}    [size = nrow+1  = 1+1]
    3582:         j =  {0,1,2}  [size = nz = 6]
    3583:         v =  {4,5,6}  [size = nz = 6]

    3585: .keywords: matrix, aij, compressed row, sparse, parallel

    3587: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
    3588:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
    3589: @*/
    3590: PetscErrorCode  MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
    3591: {

    3595:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
    3596:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
    3597:   MatCreate(comm,mat);
    3598:   MatSetSizes(*mat,m,n,M,N);
    3599:   /* MatSetBlockSizes(M,bs,cbs); */
    3600:   MatSetType(*mat,MATMPIAIJ);
    3601:   MatMPIAIJSetPreallocationCSR(*mat,i,j,a);
    3602:   return(0);
    3603: }

    3607: /*@C
    3608:    MatCreateAIJ - Creates a sparse parallel matrix in AIJ format
    3609:    (the default parallel PETSc format).  For good matrix assembly performance
    3610:    the user should preallocate the matrix storage by setting the parameters
    3611:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    3612:    performance can be increased by more than a factor of 50.

    3614:    Collective on MPI_Comm

    3616:    Input Parameters:
    3617: +  comm - MPI communicator
    3618: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
    3619:            This value should be the same as the local size used in creating the
    3620:            y vector for the matrix-vector product y = Ax.
    3621: .  n - This value should be the same as the local size used in creating the
    3622:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
    3623:        calculated if N is given) For square matrices n is almost always m.
    3624: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    3625: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    3626: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
    3627:            (same value is used for all local rows)
    3628: .  d_nnz - array containing the number of nonzeros in the various rows of the
    3629:            DIAGONAL portion of the local submatrix (possibly different for each row)
    3630:            or NULL, if d_nz is used to specify the nonzero structure.
    3631:            The size of this array is equal to the number of local rows, i.e 'm'.
    3632: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
    3633:            submatrix (same value is used for all local rows).
    3634: -  o_nnz - array containing the number of nonzeros in the various rows of the
    3635:            OFF-DIAGONAL portion of the local submatrix (possibly different for
    3636:            each row) or NULL, if o_nz is used to specify the nonzero
    3637:            structure. The size of this array is equal to the number
    3638:            of local rows, i.e 'm'.

    3640:    Output Parameter:
    3641: .  A - the matrix

    3643:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
    3644:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
    3645:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

    3647:    Notes:
    3648:    If the *_nnz parameter is given then the *_nz parameter is ignored

    3650:    m,n,M,N parameters specify the size of the matrix, and its partitioning across
    3651:    processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
    3652:    storage requirements for this matrix.

    3654:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one
    3655:    processor than it must be used on all processors that share the object for
    3656:    that argument.

    3658:    The user MUST specify either the local or global matrix dimensions
    3659:    (possibly both).

    3661:    The parallel matrix is partitioned across processors such that the
    3662:    first m0 rows belong to process 0, the next m1 rows belong to
    3663:    process 1, the next m2 rows belong to process 2 etc.. where
    3664:    m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
    3665:    values corresponding to [m x N] submatrix.

    3667:    The columns are logically partitioned with the n0 columns belonging
    3668:    to 0th partition, the next n1 columns belonging to the next
    3669:    partition etc.. where n0,n1,n2... are the input parameter 'n'.

    3671:    The DIAGONAL portion of the local submatrix on any given processor
    3672:    is the submatrix corresponding to the rows and columns m,n
    3673:    corresponding to the given processor. i.e diagonal matrix on
    3674:    process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
    3675:    etc. The remaining portion of the local submatrix [m x (N-n)]
    3676:    constitute the OFF-DIAGONAL portion. The example below better
    3677:    illustrates this concept.

    3679:    For a square global matrix we define each processor's diagonal portion
    3680:    to be its local rows and the corresponding columns (a square submatrix);
    3681:    each processor's off-diagonal portion encompasses the remainder of the
    3682:    local matrix (a rectangular submatrix).

    3684:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

    3686:    When calling this routine with a single process communicator, a matrix of
    3687:    type SEQAIJ is returned.  If a matrix of type MPIAIJ is desired for this
    3688:    type of communicator, use the construction mechanism:
    3689:      MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...);

    3691:    By default, this format uses inodes (identical nodes) when possible.
    3692:    We search for consecutive rows with the same nonzero structure, thereby
    3693:    reusing matrix information to achieve increased efficiency.

    3695:    Options Database Keys:
    3696: +  -mat_no_inode  - Do not use inodes
    3697: .  -mat_inode_limit <limit> - Sets inode limit (max limit=5)
    3698: -  -mat_aij_oneindex - Internally use indexing starting at 1
    3699:         rather than 0.  Note that when calling MatSetValues(),
    3700:         the user still MUST index entries starting at 0!

    3703:    Example usage:

    3705:    Consider the following 8x8 matrix with 34 non-zero values, that is
    3706:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
    3707:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
    3708:    as follows:

    3710: .vb
    3711:             1  2  0  |  0  3  0  |  0  4
    3712:     Proc0   0  5  6  |  7  0  0  |  8  0
    3713:             9  0 10  | 11  0  0  | 12  0
    3714:     -------------------------------------
    3715:            13  0 14  | 15 16 17  |  0  0
    3716:     Proc1   0 18  0  | 19 20 21  |  0  0
    3717:             0  0  0  | 22 23  0  | 24  0
    3718:     -------------------------------------
    3719:     Proc2  25 26 27  |  0  0 28  | 29  0
    3720:            30  0  0  | 31 32 33  |  0 34
    3721: .ve

    3723:    This can be represented as a collection of submatrices as:

    3725: .vb
    3726:       A B C
    3727:       D E F
    3728:       G H I
    3729: .ve

    3731:    Where the submatrices A,B,C are owned by proc0, D,E,F are
    3732:    owned by proc1, G,H,I are owned by proc2.

    3734:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
    3735:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
    3736:    The 'M','N' parameters are 8,8, and have the same values on all procs.

    3738:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
    3739:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
    3740:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
    3741:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
    3742:    part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
    3743:    matrix, ans [DF] as another SeqAIJ matrix.

    3745:    When d_nz, o_nz parameters are specified, d_nz storage elements are
    3746:    allocated for every row of the local diagonal submatrix, and o_nz
    3747:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
    3748:    One way to choose d_nz and o_nz is to use the max nonzerors per local
    3749:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
    3750:    In this case, the values of d_nz,o_nz are:
    3751: .vb
    3752:      proc0 : dnz = 2, o_nz = 2
    3753:      proc1 : dnz = 3, o_nz = 2
    3754:      proc2 : dnz = 1, o_nz = 4
    3755: .ve
    3756:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
    3757:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
    3758:    for proc3. i.e we are using 12+15+10=37 storage locations to store
    3759:    34 values.

    3761:    When d_nnz, o_nnz parameters are specified, the storage is specified
    3762:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
    3763:    In the above case the values for d_nnz,o_nnz are:
    3764: .vb
    3765:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
    3766:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
    3767:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
    3768: .ve
    3769:    Here the space allocated is sum of all the above values i.e 34, and
    3770:    hence pre-allocation is perfect.

    3772:    Level: intermediate

    3774: .keywords: matrix, aij, compressed row, sparse, parallel

    3776: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
    3777:           MPIAIJ, MatCreateMPIAIJWithArrays()
    3778: @*/
    3779: 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)
    3780: {
    3782:   PetscMPIInt    size;

    3785:   MatCreate(comm,A);
    3786:   MatSetSizes(*A,m,n,M,N);
    3787:   MPI_Comm_size(comm,&size);
    3788:   if (size > 1) {
    3789:     MatSetType(*A,MATMPIAIJ);
    3790:     MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
    3791:   } else {
    3792:     MatSetType(*A,MATSEQAIJ);
    3793:     MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
    3794:   }
    3795:   return(0);
    3796: }

    3800: PetscErrorCode  MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
    3801: {
    3802:   Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;

    3805:   if (Ad)     *Ad     = a->A;
    3806:   if (Ao)     *Ao     = a->B;
    3807:   if (colmap) *colmap = a->garray;
    3808:   return(0);
    3809: }

    3813: PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring)
    3814: {
    3816:   PetscInt       i;
    3817:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

    3820:   if (coloring->ctype == IS_COLORING_GLOBAL) {
    3821:     ISColoringValue *allcolors,*colors;
    3822:     ISColoring      ocoloring;

    3824:     /* set coloring for diagonal portion */
    3825:     MatSetColoring_SeqAIJ(a->A,coloring);

    3827:     /* set coloring for off-diagonal portion */
    3828:     ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);
    3829:     PetscMalloc1(a->B->cmap->n+1,&colors);
    3830:     for (i=0; i<a->B->cmap->n; i++) {
    3831:       colors[i] = allcolors[a->garray[i]];
    3832:     }
    3833:     PetscFree(allcolors);
    3834:     ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);
    3835:     MatSetColoring_SeqAIJ(a->B,ocoloring);
    3836:     ISColoringDestroy(&ocoloring);
    3837:   } else if (coloring->ctype == IS_COLORING_GHOSTED) {
    3838:     ISColoringValue *colors;
    3839:     PetscInt        *larray;
    3840:     ISColoring      ocoloring;

    3842:     /* set coloring for diagonal portion */
    3843:     PetscMalloc1(a->A->cmap->n+1,&larray);
    3844:     for (i=0; i<a->A->cmap->n; i++) {
    3845:       larray[i] = i + A->cmap->rstart;
    3846:     }
    3847:     ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);
    3848:     PetscMalloc1(a->A->cmap->n+1,&colors);
    3849:     for (i=0; i<a->A->cmap->n; i++) {
    3850:       colors[i] = coloring->colors[larray[i]];
    3851:     }
    3852:     PetscFree(larray);
    3853:     ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);
    3854:     MatSetColoring_SeqAIJ(a->A,ocoloring);
    3855:     ISColoringDestroy(&ocoloring);

    3857:     /* set coloring for off-diagonal portion */
    3858:     PetscMalloc1(a->B->cmap->n+1,&larray);
    3859:     ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);
    3860:     PetscMalloc1(a->B->cmap->n+1,&colors);
    3861:     for (i=0; i<a->B->cmap->n; i++) {
    3862:       colors[i] = coloring->colors[larray[i]];
    3863:     }
    3864:     PetscFree(larray);
    3865:     ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);
    3866:     MatSetColoring_SeqAIJ(a->B,ocoloring);
    3867:     ISColoringDestroy(&ocoloring);
    3868:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype);
    3869:   return(0);
    3870: }

    3874: PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues)
    3875: {
    3876:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data;

    3880:   MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);
    3881:   MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);
    3882:   return(0);
    3883: }

    3887: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
    3888: {
    3890:   PetscInt       m,N,i,rstart,nnz,Ii;
    3891:   PetscInt       *indx;
    3892:   PetscScalar    *values;

    3895:   MatGetSize(inmat,&m,&N);
    3896:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
    3897:     PetscInt       *dnz,*onz,sum,bs,cbs;

    3899:     if (n == PETSC_DECIDE) {
    3900:       PetscSplitOwnership(comm,&n,&N);
    3901:     }
    3902:     /* Check sum(n) = N */
    3903:     MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
    3904:     if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N);

    3906:     MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);
    3907:     rstart -= m;

    3909:     MatPreallocateInitialize(comm,m,n,dnz,onz);
    3910:     for (i=0; i<m; i++) {
    3911:       MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
    3912:       MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);
    3913:       MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
    3914:     }

    3916:     MatCreate(comm,outmat);
    3917:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
    3918:     MatGetBlockSizes(inmat,&bs,&cbs);
    3919:     MatSetBlockSizes(*outmat,bs,cbs);
    3920:     MatSetType(*outmat,MATMPIAIJ);
    3921:     MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);
    3922:     MatPreallocateFinalize(dnz,onz);
    3923:   }

    3925:   /* numeric phase */
    3926:   MatGetOwnershipRange(*outmat,&rstart,NULL);
    3927:   for (i=0; i<m; i++) {
    3928:     MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
    3929:     Ii   = i + rstart;
    3930:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
    3931:     MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
    3932:   }
    3933:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
    3934:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
    3935:   return(0);
    3936: }

    3940: PetscErrorCode MatFileSplit(Mat A,char *outfile)
    3941: {
    3942:   PetscErrorCode    ierr;
    3943:   PetscMPIInt       rank;
    3944:   PetscInt          m,N,i,rstart,nnz;
    3945:   size_t            len;
    3946:   const PetscInt    *indx;
    3947:   PetscViewer       out;
    3948:   char              *name;
    3949:   Mat               B;
    3950:   const PetscScalar *values;

    3953:   MatGetLocalSize(A,&m,0);
    3954:   MatGetSize(A,0,&N);
    3955:   /* Should this be the type of the diagonal block of A? */
    3956:   MatCreate(PETSC_COMM_SELF,&B);
    3957:   MatSetSizes(B,m,N,m,N);
    3958:   MatSetBlockSizesFromMats(B,A,A);
    3959:   MatSetType(B,MATSEQAIJ);
    3960:   MatSeqAIJSetPreallocation(B,0,NULL);
    3961:   MatGetOwnershipRange(A,&rstart,0);
    3962:   for (i=0; i<m; i++) {
    3963:     MatGetRow(A,i+rstart,&nnz,&indx,&values);
    3964:     MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);
    3965:     MatRestoreRow(A,i+rstart,&nnz,&indx,&values);
    3966:   }
    3967:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    3968:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

    3970:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
    3971:   PetscStrlen(outfile,&len);
    3972:   PetscMalloc1(len+5,&name);
    3973:   sprintf(name,"%s.%d",outfile,rank);
    3974:   PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);
    3975:   PetscFree(name);
    3976:   MatView(B,out);
    3977:   PetscViewerDestroy(&out);
    3978:   MatDestroy(&B);
    3979:   return(0);
    3980: }

    3982: extern PetscErrorCode MatDestroy_MPIAIJ(Mat);
    3985: PetscErrorCode  MatDestroy_MPIAIJ_SeqsToMPI(Mat A)
    3986: {
    3987:   PetscErrorCode      ierr;
    3988:   Mat_Merge_SeqsToMPI *merge;
    3989:   PetscContainer      container;

    3992:   PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);
    3993:   if (container) {
    3994:     PetscContainerGetPointer(container,(void**)&merge);
    3995:     PetscFree(merge->id_r);
    3996:     PetscFree(merge->len_s);
    3997:     PetscFree(merge->len_r);
    3998:     PetscFree(merge->bi);
    3999:     PetscFree(merge->bj);
    4000:     PetscFree(merge->buf_ri[0]);
    4001:     PetscFree(merge->buf_ri);
    4002:     PetscFree(merge->buf_rj[0]);
    4003:     PetscFree(merge->buf_rj);
    4004:     PetscFree(merge->coi);
    4005:     PetscFree(merge->coj);
    4006:     PetscFree(merge->owners_co);
    4007:     PetscLayoutDestroy(&merge->rowmap);
    4008:     PetscFree(merge);
    4009:     PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);
    4010:   }
    4011:   MatDestroy_MPIAIJ(A);
    4012:   return(0);
    4013: }

    4015: #include <../src/mat/utils/freespace.h>
    4016: #include <petscbt.h>

    4020: PetscErrorCode  MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat)
    4021: {
    4022:   PetscErrorCode      ierr;
    4023:   MPI_Comm            comm;
    4024:   Mat_SeqAIJ          *a  =(Mat_SeqAIJ*)seqmat->data;
    4025:   PetscMPIInt         size,rank,taga,*len_s;
    4026:   PetscInt            N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj;
    4027:   PetscInt            proc,m;
    4028:   PetscInt            **buf_ri,**buf_rj;
    4029:   PetscInt            k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj;
    4030:   PetscInt            nrows,**buf_ri_k,**nextrow,**nextai;
    4031:   MPI_Request         *s_waits,*r_waits;
    4032:   MPI_Status          *status;
    4033:   MatScalar           *aa=a->a;
    4034:   MatScalar           **abuf_r,*ba_i;
    4035:   Mat_Merge_SeqsToMPI *merge;
    4036:   PetscContainer      container;

    4039:   PetscObjectGetComm((PetscObject)mpimat,&comm);
    4040:   PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);

    4042:   MPI_Comm_size(comm,&size);
    4043:   MPI_Comm_rank(comm,&rank);

    4045:   PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);
    4046:   PetscContainerGetPointer(container,(void**)&merge);

    4048:   bi     = merge->bi;
    4049:   bj     = merge->bj;
    4050:   buf_ri = merge->buf_ri;
    4051:   buf_rj = merge->buf_rj;

    4053:   PetscMalloc1(size,&status);
    4054:   owners = merge->rowmap->range;
    4055:   len_s  = merge->len_s;

    4057:   /* send and recv matrix values */
    4058:   /*-----------------------------*/
    4059:   PetscObjectGetNewTag((PetscObject)mpimat,&taga);
    4060:   PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);

    4062:   PetscMalloc1(merge->nsend+1,&s_waits);
    4063:   for (proc=0,k=0; proc<size; proc++) {
    4064:     if (!len_s[proc]) continue;
    4065:     i    = owners[proc];
    4066:     MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);
    4067:     k++;
    4068:   }

    4070:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,r_waits,status);}
    4071:   if (merge->nsend) {MPI_Waitall(merge->nsend,s_waits,status);}
    4072:   PetscFree(status);

    4074:   PetscFree(s_waits);
    4075:   PetscFree(r_waits);

    4077:   /* insert mat values of mpimat */
    4078:   /*----------------------------*/
    4079:   PetscMalloc1(N,&ba_i);
    4080:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

    4082:   for (k=0; k<merge->nrecv; k++) {
    4083:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
    4084:     nrows       = *(buf_ri_k[k]);
    4085:     nextrow[k]  = buf_ri_k[k]+1;  /* next row number of k-th recved i-structure */
    4086:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
    4087:   }

    4089:   /* set values of ba */
    4090:   m = merge->rowmap->n;
    4091:   for (i=0; i<m; i++) {
    4092:     arow = owners[rank] + i;
    4093:     bj_i = bj+bi[i];  /* col indices of the i-th row of mpimat */
    4094:     bnzi = bi[i+1] - bi[i];
    4095:     PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));

    4097:     /* add local non-zero vals of this proc's seqmat into ba */
    4098:     anzi   = ai[arow+1] - ai[arow];
    4099:     aj     = a->j + ai[arow];
    4100:     aa     = a->a + ai[arow];
    4101:     nextaj = 0;
    4102:     for (j=0; nextaj<anzi; j++) {
    4103:       if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
    4104:         ba_i[j] += aa[nextaj++];
    4105:       }
    4106:     }

    4108:     /* add received vals into ba */
    4109:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
    4110:       /* i-th row */
    4111:       if (i == *nextrow[k]) {
    4112:         anzi   = *(nextai[k]+1) - *nextai[k];
    4113:         aj     = buf_rj[k] + *(nextai[k]);
    4114:         aa     = abuf_r[k] + *(nextai[k]);
    4115:         nextaj = 0;
    4116:         for (j=0; nextaj<anzi; j++) {
    4117:           if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
    4118:             ba_i[j] += aa[nextaj++];
    4119:           }
    4120:         }
    4121:         nextrow[k]++; nextai[k]++;
    4122:       }
    4123:     }
    4124:     MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);
    4125:   }
    4126:   MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);
    4127:   MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);

    4129:   PetscFree(abuf_r[0]);
    4130:   PetscFree(abuf_r);
    4131:   PetscFree(ba_i);
    4132:   PetscFree3(buf_ri_k,nextrow,nextai);
    4133:   PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);
    4134:   return(0);
    4135: }

    4137: extern PetscErrorCode  MatDestroy_MPIAIJ_SeqsToMPI(Mat);

    4141: PetscErrorCode  MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat)
    4142: {
    4143:   PetscErrorCode      ierr;
    4144:   Mat                 B_mpi;
    4145:   Mat_SeqAIJ          *a=(Mat_SeqAIJ*)seqmat->data;
    4146:   PetscMPIInt         size,rank,tagi,tagj,*len_s,*len_si,*len_ri;
    4147:   PetscInt            **buf_rj,**buf_ri,**buf_ri_k;
    4148:   PetscInt            M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j;
    4149:   PetscInt            len,proc,*dnz,*onz,bs,cbs;
    4150:   PetscInt            k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0;
    4151:   PetscInt            nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai;
    4152:   MPI_Request         *si_waits,*sj_waits,*ri_waits,*rj_waits;
    4153:   MPI_Status          *status;
    4154:   PetscFreeSpaceList  free_space=NULL,current_space=NULL;
    4155:   PetscBT             lnkbt;
    4156:   Mat_Merge_SeqsToMPI *merge;
    4157:   PetscContainer      container;

    4160:   PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);

    4162:   /* make sure it is a PETSc comm */
    4163:   PetscCommDuplicate(comm,&comm,NULL);
    4164:   MPI_Comm_size(comm,&size);
    4165:   MPI_Comm_rank(comm,&rank);

    4167:   PetscNew(&merge);
    4168:   PetscMalloc1(size,&status);

    4170:   /* determine row ownership */
    4171:   /*---------------------------------------------------------*/
    4172:   PetscLayoutCreate(comm,&merge->rowmap);
    4173:   PetscLayoutSetLocalSize(merge->rowmap,m);
    4174:   PetscLayoutSetSize(merge->rowmap,M);
    4175:   PetscLayoutSetBlockSize(merge->rowmap,1);
    4176:   PetscLayoutSetUp(merge->rowmap);
    4177:   PetscMalloc1(size,&len_si);
    4178:   PetscMalloc1(size,&merge->len_s);

    4180:   m      = merge->rowmap->n;
    4181:   owners = merge->rowmap->range;

    4183:   /* determine the number of messages to send, their lengths */
    4184:   /*---------------------------------------------------------*/
    4185:   len_s = merge->len_s;

    4187:   len          = 0; /* length of buf_si[] */
    4188:   merge->nsend = 0;
    4189:   for (proc=0; proc<size; proc++) {
    4190:     len_si[proc] = 0;
    4191:     if (proc == rank) {
    4192:       len_s[proc] = 0;
    4193:     } else {
    4194:       len_si[proc] = owners[proc+1] - owners[proc] + 1;
    4195:       len_s[proc]  = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */
    4196:     }
    4197:     if (len_s[proc]) {
    4198:       merge->nsend++;
    4199:       nrows = 0;
    4200:       for (i=owners[proc]; i<owners[proc+1]; i++) {
    4201:         if (ai[i+1] > ai[i]) nrows++;
    4202:       }
    4203:       len_si[proc] = 2*(nrows+1);
    4204:       len         += len_si[proc];
    4205:     }
    4206:   }

    4208:   /* determine the number and length of messages to receive for ij-structure */
    4209:   /*-------------------------------------------------------------------------*/
    4210:   PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);
    4211:   PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);

    4213:   /* post the Irecv of j-structure */
    4214:   /*-------------------------------*/
    4215:   PetscCommGetNewTag(comm,&tagj);
    4216:   PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);

    4218:   /* post the Isend of j-structure */
    4219:   /*--------------------------------*/
    4220:   PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);

    4222:   for (proc=0, k=0; proc<size; proc++) {
    4223:     if (!len_s[proc]) continue;
    4224:     i    = owners[proc];
    4225:     MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);
    4226:     k++;
    4227:   }

    4229:   /* receives and sends of j-structure are complete */
    4230:   /*------------------------------------------------*/
    4231:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,rj_waits,status);}
    4232:   if (merge->nsend) {MPI_Waitall(merge->nsend,sj_waits,status);}

    4234:   /* send and recv i-structure */
    4235:   /*---------------------------*/
    4236:   PetscCommGetNewTag(comm,&tagi);
    4237:   PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);

    4239:   PetscMalloc1(len+1,&buf_s);
    4240:   buf_si = buf_s;  /* points to the beginning of k-th msg to be sent */
    4241:   for (proc=0,k=0; proc<size; proc++) {
    4242:     if (!len_s[proc]) continue;
    4243:     /* form outgoing message for i-structure:
    4244:          buf_si[0]:                 nrows to be sent
    4245:                [1:nrows]:           row index (global)
    4246:                [nrows+1:2*nrows+1]: i-structure index
    4247:     */
    4248:     /*-------------------------------------------*/
    4249:     nrows       = len_si[proc]/2 - 1;
    4250:     buf_si_i    = buf_si + nrows+1;
    4251:     buf_si[0]   = nrows;
    4252:     buf_si_i[0] = 0;
    4253:     nrows       = 0;
    4254:     for (i=owners[proc]; i<owners[proc+1]; i++) {
    4255:       anzi = ai[i+1] - ai[i];
    4256:       if (anzi) {
    4257:         buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */
    4258:         buf_si[nrows+1]   = i-owners[proc]; /* local row index */
    4259:         nrows++;
    4260:       }
    4261:     }
    4262:     MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);
    4263:     k++;
    4264:     buf_si += len_si[proc];
    4265:   }

    4267:   if (merge->nrecv) {MPI_Waitall(merge->nrecv,ri_waits,status);}
    4268:   if (merge->nsend) {MPI_Waitall(merge->nsend,si_waits,status);}

    4270:   PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);
    4271:   for (i=0; i<merge->nrecv; i++) {
    4272:     PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);
    4273:   }

    4275:   PetscFree(len_si);
    4276:   PetscFree(len_ri);
    4277:   PetscFree(rj_waits);
    4278:   PetscFree2(si_waits,sj_waits);
    4279:   PetscFree(ri_waits);
    4280:   PetscFree(buf_s);
    4281:   PetscFree(status);

    4283:   /* compute a local seq matrix in each processor */
    4284:   /*----------------------------------------------*/
    4285:   /* allocate bi array and free space for accumulating nonzero column info */
    4286:   PetscMalloc1(m+1,&bi);
    4287:   bi[0] = 0;

    4289:   /* create and initialize a linked list */
    4290:   nlnk = N+1;
    4291:   PetscLLCreate(N,N,nlnk,lnk,lnkbt);

    4293:   /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */
    4294:   len  = ai[owners[rank+1]] - ai[owners[rank]];
    4295:   PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);

    4297:   current_space = free_space;

    4299:   /* determine symbolic info for each local row */
    4300:   PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);

    4302:   for (k=0; k<merge->nrecv; k++) {
    4303:     buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
    4304:     nrows       = *buf_ri_k[k];
    4305:     nextrow[k]  = buf_ri_k[k] + 1;  /* next row number of k-th recved i-structure */
    4306:     nextai[k]   = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure  */
    4307:   }

    4309:   MatPreallocateInitialize(comm,m,n,dnz,onz);
    4310:   len  = 0;
    4311:   for (i=0; i<m; i++) {
    4312:     bnzi = 0;
    4313:     /* add local non-zero cols of this proc's seqmat into lnk */
    4314:     arow  = owners[rank] + i;
    4315:     anzi  = ai[arow+1] - ai[arow];
    4316:     aj    = a->j + ai[arow];
    4317:     PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
    4318:     bnzi += nlnk;
    4319:     /* add received col data into lnk */
    4320:     for (k=0; k<merge->nrecv; k++) { /* k-th received message */
    4321:       if (i == *nextrow[k]) { /* i-th row */
    4322:         anzi  = *(nextai[k]+1) - *nextai[k];
    4323:         aj    = buf_rj[k] + *nextai[k];
    4324:         PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
    4325:         bnzi += nlnk;
    4326:         nextrow[k]++; nextai[k]++;
    4327:       }
    4328:     }
    4329:     if (len < bnzi) len = bnzi;  /* =max(bnzi) */

    4331:     /* if free space is not available, make more free space */
    4332:     if (current_space->local_remaining<bnzi) {
    4333:       PetscFreeSpaceGet(bnzi+current_space->total_array_size,&current_space);
    4334:       nspacedouble++;
    4335:     }
    4336:     /* copy data into free space, then initialize lnk */
    4337:     PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);
    4338:     MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);

    4340:     current_space->array           += bnzi;
    4341:     current_space->local_used      += bnzi;
    4342:     current_space->local_remaining -= bnzi;

    4344:     bi[i+1] = bi[i] + bnzi;
    4345:   }

    4347:   PetscFree3(buf_ri_k,nextrow,nextai);

    4349:   PetscMalloc1(bi[m]+1,&bj);
    4350:   PetscFreeSpaceContiguous(&free_space,bj);
    4351:   PetscLLDestroy(lnk,lnkbt);

    4353:   /* create symbolic parallel matrix B_mpi */
    4354:   /*---------------------------------------*/
    4355:   MatGetBlockSizes(seqmat,&bs,&cbs);
    4356:   MatCreate(comm,&B_mpi);
    4357:   if (n==PETSC_DECIDE) {
    4358:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);
    4359:   } else {
    4360:     MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
    4361:   }
    4362:   MatSetBlockSizes(B_mpi,bs,cbs);
    4363:   MatSetType(B_mpi,MATMPIAIJ);
    4364:   MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);
    4365:   MatPreallocateFinalize(dnz,onz);
    4366:   MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);

    4368:   /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */
    4369:   B_mpi->assembled    = PETSC_FALSE;
    4370:   B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI;
    4371:   merge->bi           = bi;
    4372:   merge->bj           = bj;
    4373:   merge->buf_ri       = buf_ri;
    4374:   merge->buf_rj       = buf_rj;
    4375:   merge->coi          = NULL;
    4376:   merge->coj          = NULL;
    4377:   merge->owners_co    = NULL;

    4379:   PetscCommDestroy(&comm);

    4381:   /* attach the supporting struct to B_mpi for reuse */
    4382:   PetscContainerCreate(PETSC_COMM_SELF,&container);
    4383:   PetscContainerSetPointer(container,merge);
    4384:   PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);
    4385:   PetscContainerDestroy(&container);
    4386:   *mpimat = B_mpi;

    4388:   PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);
    4389:   return(0);
    4390: }

    4394: /*@C
    4395:       MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential
    4396:                  matrices from each processor

    4398:     Collective on MPI_Comm

    4400:    Input Parameters:
    4401: +    comm - the communicators the parallel matrix will live on
    4402: .    seqmat - the input sequential matrices
    4403: .    m - number of local rows (or PETSC_DECIDE)
    4404: .    n - number of local columns (or PETSC_DECIDE)
    4405: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

    4407:    Output Parameter:
    4408: .    mpimat - the parallel matrix generated

    4410:     Level: advanced

    4412:    Notes:
    4413:      The dimensions of the sequential matrix in each processor MUST be the same.
    4414:      The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be
    4415:      destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat.
    4416: @*/
    4417: PetscErrorCode  MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat)
    4418: {
    4420:   PetscMPIInt    size;

    4423:   MPI_Comm_size(comm,&size);
    4424:   if (size == 1) {
    4425:     PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
    4426:     if (scall == MAT_INITIAL_MATRIX) {
    4427:       MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);
    4428:     } else {
    4429:       MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);
    4430:     }
    4431:     PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
    4432:     return(0);
    4433:   }
    4434:   PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
    4435:   if (scall == MAT_INITIAL_MATRIX) {
    4436:     MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);
    4437:   }
    4438:   MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);
    4439:   PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
    4440:   return(0);
    4441: }

    4445: /*@
    4446:      MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with
    4447:           mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained
    4448:           with MatGetSize()

    4450:     Not Collective

    4452:    Input Parameters:
    4453: +    A - the matrix
    4454: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

    4456:    Output Parameter:
    4457: .    A_loc - the local sequential matrix generated

    4459:     Level: developer

    4461: .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed()

    4463: @*/
    4464: PetscErrorCode  MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc)
    4465: {
    4467:   Mat_MPIAIJ     *mpimat=(Mat_MPIAIJ*)A->data;
    4468:   Mat_SeqAIJ     *mat,*a,*b;
    4469:   PetscInt       *ai,*aj,*bi,*bj,*cmap=mpimat->garray;
    4470:   MatScalar      *aa,*ba,*cam;
    4471:   PetscScalar    *ca;
    4472:   PetscInt       am=A->rmap->n,i,j,k,cstart=A->cmap->rstart;
    4473:   PetscInt       *ci,*cj,col,ncols_d,ncols_o,jo;
    4474:   PetscBool      match;
    4475:   MPI_Comm       comm;
    4476:   PetscMPIInt    size;

    4479:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
    4480:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input");
    4481:   PetscObjectGetComm((PetscObject)A,&comm);
    4482:   MPI_Comm_size(comm,&size);
    4483:   if (size == 1 && scall == MAT_REUSE_MATRIX) return(0);

    4485:   PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);
    4486:   a = (Mat_SeqAIJ*)(mpimat->A)->data;
    4487:   b = (Mat_SeqAIJ*)(mpimat->B)->data;
    4488:   ai = a->i; aj = a->j; bi = b->i; bj = b->j;
    4489:   aa = a->a; ba = b->a;
    4490:   if (scall == MAT_INITIAL_MATRIX) {
    4491:     if (size == 1) {
    4492:       MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);
    4493:       return(0);
    4494:     }

    4496:     PetscMalloc1(1+am,&ci);
    4497:     ci[0] = 0;
    4498:     for (i=0; i<am; i++) {
    4499:       ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]);
    4500:     }
    4501:     PetscMalloc1(1+ci[am],&cj);
    4502:     PetscMalloc1(1+ci[am],&ca);
    4503:     k    = 0;
    4504:     for (i=0; i<am; i++) {
    4505:       ncols_o = bi[i+1] - bi[i];
    4506:       ncols_d = ai[i+1] - ai[i];
    4507:       /* off-diagonal portion of A */
    4508:       for (jo=0; jo<ncols_o; jo++) {
    4509:         col = cmap[*bj];
    4510:         if (col >= cstart) break;
    4511:         cj[k]   = col; bj++;
    4512:         ca[k++] = *ba++;
    4513:       }
    4514:       /* diagonal portion of A */
    4515:       for (j=0; j<ncols_d; j++) {
    4516:         cj[k]   = cstart + *aj++;
    4517:         ca[k++] = *aa++;
    4518:       }
    4519:       /* off-diagonal portion of A */
    4520:       for (j=jo; j<ncols_o; j++) {
    4521:         cj[k]   = cmap[*bj++];
    4522:         ca[k++] = *ba++;
    4523:       }
    4524:     }
    4525:     /* put together the new matrix */
    4526:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);
    4527:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
    4528:     /* Since these are PETSc arrays, change flags to free them as necessary. */
    4529:     mat          = (Mat_SeqAIJ*)(*A_loc)->data;
    4530:     mat->free_a  = PETSC_TRUE;
    4531:     mat->free_ij = PETSC_TRUE;
    4532:     mat->nonew   = 0;
    4533:   } else if (scall == MAT_REUSE_MATRIX) {
    4534:     mat=(Mat_SeqAIJ*)(*A_loc)->data;
    4535:     ci = mat->i; cj = mat->j; cam = mat->a;
    4536:     for (i=0; i<am; i++) {
    4537:       /* off-diagonal portion of A */
    4538:       ncols_o = bi[i+1] - bi[i];
    4539:       for (jo=0; jo<ncols_o; jo++) {
    4540:         col = cmap[*bj];
    4541:         if (col >= cstart) break;
    4542:         *cam++ = *ba++; bj++;
    4543:       }
    4544:       /* diagonal portion of A */
    4545:       ncols_d = ai[i+1] - ai[i];
    4546:       for (j=0; j<ncols_d; j++) *cam++ = *aa++;
    4547:       /* off-diagonal portion of A */
    4548:       for (j=jo; j<ncols_o; j++) {
    4549:         *cam++ = *ba++; bj++;
    4550:       }
    4551:     }
    4552:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
    4553:   PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);
    4554:   return(0);
    4555: }

    4559: /*@C
    4560:      MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns

    4562:     Not Collective

    4564:    Input Parameters:
    4565: +    A - the matrix
    4566: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
    4567: -    row, col - index sets of rows and columns to extract (or NULL)

    4569:    Output Parameter:
    4570: .    A_loc - the local sequential matrix generated

    4572:     Level: developer

    4574: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat()

    4576: @*/
    4577: PetscErrorCode  MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
    4578: {
    4579:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
    4581:   PetscInt       i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
    4582:   IS             isrowa,iscola;
    4583:   Mat            *aloc;
    4584:   PetscBool      match;

    4587:   PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
    4588:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input");
    4589:   PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
    4590:   if (!row) {
    4591:     start = A->rmap->rstart; end = A->rmap->rend;
    4592:     ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
    4593:   } else {
    4594:     isrowa = *row;
    4595:   }
    4596:   if (!col) {
    4597:     start = A->cmap->rstart;
    4598:     cmap  = a->garray;
    4599:     nzA   = a->A->cmap->n;
    4600:     nzB   = a->B->cmap->n;
    4601:     PetscMalloc1(nzA+nzB, &idx);
    4602:     ncols = 0;
    4603:     for (i=0; i<nzB; i++) {
    4604:       if (cmap[i] < start) idx[ncols++] = cmap[i];
    4605:       else break;
    4606:     }
    4607:     imark = i;
    4608:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;
    4609:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
    4610:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
    4611:   } else {
    4612:     iscola = *col;
    4613:   }
    4614:   if (scall != MAT_INITIAL_MATRIX) {
    4615:     PetscMalloc1(1,&aloc);
    4616:     aloc[0] = *A_loc;
    4617:   }
    4618:   MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
    4619:   *A_loc = aloc[0];
    4620:   PetscFree(aloc);
    4621:   if (!row) {
    4622:     ISDestroy(&isrowa);
    4623:   }
    4624:   if (!col) {
    4625:     ISDestroy(&iscola);
    4626:   }
    4627:   PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
    4628:   return(0);
    4629: }

    4633: /*@C
    4634:     MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A

    4636:     Collective on Mat

    4638:    Input Parameters:
    4639: +    A,B - the matrices in mpiaij format
    4640: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
    4641: -    rowb, colb - index sets of rows and columns of B to extract (or NULL)

    4643:    Output Parameter:
    4644: +    rowb, colb - index sets of rows and columns of B to extract
    4645: -    B_seq - the sequential matrix generated

    4647:     Level: developer

    4649: @*/
    4650: PetscErrorCode  MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq)
    4651: {
    4652:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
    4654:   PetscInt       *idx,i,start,ncols,nzA,nzB,*cmap,imark;
    4655:   IS             isrowb,iscolb;
    4656:   Mat            *bseq=NULL;

    4659:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
    4660:     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);
    4661:   }
    4662:   PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);

    4664:   if (scall == MAT_INITIAL_MATRIX) {
    4665:     start = A->cmap->rstart;
    4666:     cmap  = a->garray;
    4667:     nzA   = a->A->cmap->n;
    4668:     nzB   = a->B->cmap->n;
    4669:     PetscMalloc1(nzA+nzB, &idx);
    4670:     ncols = 0;
    4671:     for (i=0; i<nzB; i++) {  /* row < local row index */
    4672:       if (cmap[i] < start) idx[ncols++] = cmap[i];
    4673:       else break;
    4674:     }
    4675:     imark = i;
    4676:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;  /* local rows */
    4677:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */
    4678:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);
    4679:     ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);
    4680:   } else {
    4681:     if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX");
    4682:     isrowb  = *rowb; iscolb = *colb;
    4683:     PetscMalloc1(1,&bseq);
    4684:     bseq[0] = *B_seq;
    4685:   }
    4686:   MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);
    4687:   *B_seq = bseq[0];
    4688:   PetscFree(bseq);
    4689:   if (!rowb) {
    4690:     ISDestroy(&isrowb);
    4691:   } else {
    4692:     *rowb = isrowb;
    4693:   }
    4694:   if (!colb) {
    4695:     ISDestroy(&iscolb);
    4696:   } else {
    4697:     *colb = iscolb;
    4698:   }
    4699:   PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);
    4700:   return(0);
    4701: }

    4705: /*
    4706:     MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns
    4707:     of the OFF-DIAGONAL portion of local A

    4709:     Collective on Mat

    4711:    Input Parameters:
    4712: +    A,B - the matrices in mpiaij format
    4713: -    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

    4715:    Output Parameter:
    4716: +    startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL)
    4717: .    startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL)
    4718: .    bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL)
    4719: -    B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N

    4721:     Level: developer

    4723: */
    4724: PetscErrorCode  MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth)
    4725: {
    4726:   VecScatter_MPI_General *gen_to,*gen_from;
    4727:   PetscErrorCode         ierr;
    4728:   Mat_MPIAIJ             *a=(Mat_MPIAIJ*)A->data;
    4729:   Mat_SeqAIJ             *b_oth;
    4730:   VecScatter             ctx =a->Mvctx;
    4731:   MPI_Comm               comm;
    4732:   PetscMPIInt            *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank;
    4733:   PetscInt               *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj;
    4734:   PetscScalar            *rvalues,*svalues;
    4735:   MatScalar              *b_otha,*bufa,*bufA;
    4736:   PetscInt               i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len;
    4737:   MPI_Request            *rwaits = NULL,*swaits = NULL;
    4738:   MPI_Status             *sstatus,rstatus;
    4739:   PetscMPIInt            jj,size;
    4740:   PetscInt               *cols,sbs,rbs;
    4741:   PetscScalar            *vals;

    4744:   PetscObjectGetComm((PetscObject)A,&comm);
    4745:   MPI_Comm_size(comm,&size);

    4747:   if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
    4748:     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);
    4749:   }
    4750:   PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);
    4751:   MPI_Comm_rank(comm,&rank);

    4753:   gen_to   = (VecScatter_MPI_General*)ctx->todata;
    4754:   gen_from = (VecScatter_MPI_General*)ctx->fromdata;
    4755:   rvalues  = gen_from->values; /* holds the length of receiving row */
    4756:   svalues  = gen_to->values;   /* holds the length of sending row */
    4757:   nrecvs   = gen_from->n;
    4758:   nsends   = gen_to->n;

    4760:   PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);
    4761:   srow    = gen_to->indices;    /* local row index to be sent */
    4762:   sstarts = gen_to->starts;
    4763:   sprocs  = gen_to->procs;
    4764:   sstatus = gen_to->sstatus;
    4765:   sbs     = gen_to->bs;
    4766:   rstarts = gen_from->starts;
    4767:   rprocs  = gen_from->procs;
    4768:   rbs     = gen_from->bs;

    4770:   if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX;
    4771:   if (scall == MAT_INITIAL_MATRIX) {
    4772:     /* i-array */
    4773:     /*---------*/
    4774:     /*  post receives */
    4775:     for (i=0; i<nrecvs; i++) {
    4776:       rowlen = (PetscInt*)rvalues + rstarts[i]*rbs;
    4777:       nrows  = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */
    4778:       MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
    4779:     }

    4781:     /* pack the outgoing message */
    4782:     PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);

    4784:     sstartsj[0] = 0;
    4785:     rstartsj[0] = 0;
    4786:     len         = 0; /* total length of j or a array to be sent */
    4787:     k           = 0;
    4788:     for (i=0; i<nsends; i++) {
    4789:       rowlen = (PetscInt*)svalues + sstarts[i]*sbs;
    4790:       nrows  = sstarts[i+1]-sstarts[i]; /* num of block rows */
    4791:       for (j=0; j<nrows; j++) {
    4792:         row = srow[k] + B->rmap->range[rank]; /* global row idx */
    4793:         for (l=0; l<sbs; l++) {
    4794:           MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL); /* rowlength */

    4796:           rowlen[j*sbs+l] = ncols;

    4798:           len += ncols;
    4799:           MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);
    4800:         }
    4801:         k++;
    4802:       }
    4803:       MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);

    4805:       sstartsj[i+1] = len;  /* starting point of (i+1)-th outgoing msg in bufj and bufa */
    4806:     }
    4807:     /* recvs and sends of i-array are completed */
    4808:     i = nrecvs;
    4809:     while (i--) {
    4810:       MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
    4811:     }
    4812:     if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}

    4814:     /* allocate buffers for sending j and a arrays */
    4815:     PetscMalloc1(len+1,&bufj);
    4816:     PetscMalloc1(len+1,&bufa);

    4818:     /* create i-array of B_oth */
    4819:     PetscMalloc1(aBn+2,&b_othi);

    4821:     b_othi[0] = 0;
    4822:     len       = 0; /* total length of j or a array to be received */
    4823:     k         = 0;
    4824:     for (i=0; i<nrecvs; i++) {
    4825:       rowlen = (PetscInt*)rvalues + rstarts[i]*rbs;
    4826:       nrows  = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */
    4827:       for (j=0; j<nrows; j++) {
    4828:         b_othi[k+1] = b_othi[k] + rowlen[j];
    4829:         len        += rowlen[j]; k++;
    4830:       }
    4831:       rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */
    4832:     }

    4834:     /* allocate space for j and a arrrays of B_oth */
    4835:     PetscMalloc1(b_othi[aBn]+1,&b_othj);
    4836:     PetscMalloc1(b_othi[aBn]+1,&b_otha);

    4838:     /* j-array */
    4839:     /*---------*/
    4840:     /*  post receives of j-array */
    4841:     for (i=0; i<nrecvs; i++) {
    4842:       nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
    4843:       MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
    4844:     }

    4846:     /* pack the outgoing message j-array */
    4847:     k = 0;
    4848:     for (i=0; i<nsends; i++) {
    4849:       nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
    4850:       bufJ  = bufj+sstartsj[i];
    4851:       for (j=0; j<nrows; j++) {
    4852:         row = srow[k++] + B->rmap->range[rank];  /* global row idx */
    4853:         for (ll=0; ll<sbs; ll++) {
    4854:           MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
    4855:           for (l=0; l<ncols; l++) {
    4856:             *bufJ++ = cols[l];
    4857:           }
    4858:           MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
    4859:         }
    4860:       }
    4861:       MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);
    4862:     }

    4864:     /* recvs and sends of j-array are completed */
    4865:     i = nrecvs;
    4866:     while (i--) {
    4867:       MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
    4868:     }
    4869:     if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
    4870:   } else if (scall == MAT_REUSE_MATRIX) {
    4871:     sstartsj = *startsj_s;
    4872:     rstartsj = *startsj_r;
    4873:     bufa     = *bufa_ptr;
    4874:     b_oth    = (Mat_SeqAIJ*)(*B_oth)->data;
    4875:     b_otha   = b_oth->a;
    4876:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container");

    4878:   /* a-array */
    4879:   /*---------*/
    4880:   /*  post receives of a-array */
    4881:   for (i=0; i<nrecvs; i++) {
    4882:     nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
    4883:     MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);
    4884:   }

    4886:   /* pack the outgoing message a-array */
    4887:   k = 0;
    4888:   for (i=0; i<nsends; i++) {
    4889:     nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
    4890:     bufA  = bufa+sstartsj[i];
    4891:     for (j=0; j<nrows; j++) {
    4892:       row = srow[k++] + B->rmap->range[rank];  /* global row idx */
    4893:       for (ll=0; ll<sbs; ll++) {
    4894:         MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
    4895:         for (l=0; l<ncols; l++) {
    4896:           *bufA++ = vals[l];
    4897:         }
    4898:         MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
    4899:       }
    4900:     }
    4901:     MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);
    4902:   }
    4903:   /* recvs and sends of a-array are completed */
    4904:   i = nrecvs;
    4905:   while (i--) {
    4906:     MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);
    4907:   }
    4908:   if (nsends) {MPI_Waitall(nsends,swaits,sstatus);}
    4909:   PetscFree2(rwaits,swaits);

    4911:   if (scall == MAT_INITIAL_MATRIX) {
    4912:     /* put together the new matrix */
    4913:     MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);

    4915:     /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
    4916:     /* Since these are PETSc arrays, change flags to free them as necessary. */
    4917:     b_oth          = (Mat_SeqAIJ*)(*B_oth)->data;
    4918:     b_oth->free_a  = PETSC_TRUE;
    4919:     b_oth->free_ij = PETSC_TRUE;
    4920:     b_oth->nonew   = 0;

    4922:     PetscFree(bufj);
    4923:     if (!startsj_s || !bufa_ptr) {
    4924:       PetscFree2(sstartsj,rstartsj);
    4925:       PetscFree(bufa_ptr);
    4926:     } else {
    4927:       *startsj_s = sstartsj;
    4928:       *startsj_r = rstartsj;
    4929:       *bufa_ptr  = bufa;
    4930:     }
    4931:   }
    4932:   PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);
    4933:   return(0);
    4934: }

    4938: /*@C
    4939:   MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication.

    4941:   Not Collective

    4943:   Input Parameters:
    4944: . A - The matrix in mpiaij format

    4946:   Output Parameter:
    4947: + lvec - The local vector holding off-process values from the argument to a matrix-vector product
    4948: . colmap - A map from global column index to local index into lvec
    4949: - multScatter - A scatter from the argument of a matrix-vector product to lvec

    4951:   Level: developer

    4953: @*/
    4954: #if defined(PETSC_USE_CTABLE)
    4955: PetscErrorCode  MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter)
    4956: #else
    4957: PetscErrorCode  MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter)
    4958: #endif
    4959: {
    4960:   Mat_MPIAIJ *a;

    4967:   a = (Mat_MPIAIJ*) A->data;
    4968:   if (lvec) *lvec = a->lvec;
    4969:   if (colmap) *colmap = a->colmap;
    4970:   if (multScatter) *multScatter = a->Mvctx;
    4971:   return(0);
    4972: }

    4974: PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*);
    4975: PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*);
    4976: PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*);
    4977: #if defined(PETSC_HAVE_ELEMENTAL)
    4978: PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
    4979: #endif

    4983: /*
    4984:     Computes (B'*A')' since computing B*A directly is untenable

    4986:                n                       p                          p
    4987:         (              )       (              )         (                  )
    4988:       m (      A       )  *  n (       B      )   =   m (         C        )
    4989:         (              )       (              )         (                  )

    4991: */
    4992: PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C)
    4993: {
    4995:   Mat            At,Bt,Ct;

    4998:   MatTranspose(A,MAT_INITIAL_MATRIX,&At);
    4999:   MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);
    5000:   MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);
    5001:   MatDestroy(&At);
    5002:   MatDestroy(&Bt);
    5003:   MatTranspose(Ct,MAT_REUSE_MATRIX,&C);
    5004:   MatDestroy(&Ct);
    5005:   return(0);
    5006: }

    5010: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
    5011: {
    5013:   PetscInt       m=A->rmap->n,n=B->cmap->n;
    5014:   Mat            Cmat;

    5017:   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);
    5018:   MatCreate(PetscObjectComm((PetscObject)A),&Cmat);
    5019:   MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
    5020:   MatSetBlockSizesFromMats(Cmat,A,B);
    5021:   MatSetType(Cmat,MATMPIDENSE);
    5022:   MatMPIDenseSetPreallocation(Cmat,NULL);
    5023:   MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);
    5024:   MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);

    5026:   Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ;

    5028:   *C = Cmat;
    5029:   return(0);
    5030: }

    5032: /* ----------------------------------------------------------------*/
    5035: PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
    5036: {

    5040:   if (scall == MAT_INITIAL_MATRIX) {
    5041:     PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);
    5042:     MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);
    5043:     PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);
    5044:   }
    5045:   PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);
    5046:   MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);
    5047:   PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);
    5048:   return(0);
    5049: }

    5051: /*MC
    5052:    MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices.

    5054:    Options Database Keys:
    5055: . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions()

    5057:   Level: beginner

    5059: .seealso: MatCreateAIJ()
    5060: M*/

    5064: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B)
    5065: {
    5066:   Mat_MPIAIJ     *b;
    5068:   PetscMPIInt    size;

    5071:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);

    5073:   PetscNewLog(B,&b);
    5074:   B->data       = (void*)b;
    5075:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
    5076:   B->assembled  = PETSC_FALSE;
    5077:   B->insertmode = NOT_SET_VALUES;
    5078:   b->size       = size;

    5080:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);

    5082:   /* build cache for off array entries formed */
    5083:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

    5085:   b->donotstash  = PETSC_FALSE;
    5086:   b->colmap      = 0;
    5087:   b->garray      = 0;
    5088:   b->roworiented = PETSC_TRUE;

    5090:   /* stuff used for matrix vector multiply */
    5091:   b->lvec  = NULL;
    5092:   b->Mvctx = NULL;

    5094:   /* stuff for MatGetRow() */
    5095:   b->rowindices   = 0;
    5096:   b->rowvalues    = 0;
    5097:   b->getrowactive = PETSC_FALSE;

    5099:   /* flexible pointer used in CUSP/CUSPARSE classes */
    5100:   b->spptr = NULL;

    5102:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);
    5103:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);
    5104:   PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);
    5105:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);
    5106:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);
    5107:   PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);
    5108:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);
    5109:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);
    5110:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);
    5111:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);
    5112: #if defined(PETSC_HAVE_ELEMENTAL)
    5113:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);
    5114: #endif
    5115:   PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);
    5116:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);
    5117:   PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);
    5118:   PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);
    5119:   return(0);
    5120: }

    5124: /*@C
    5125:      MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal"
    5126:          and "off-diagonal" part of the matrix in CSR format.

    5128:    Collective on MPI_Comm

    5130:    Input Parameters:
    5131: +  comm - MPI communicator
    5132: .  m - number of local rows (Cannot be PETSC_DECIDE)
    5133: .  n - This value should be the same as the local size used in creating the
    5134:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
    5135:        calculated if N is given) For square matrices n is almost always m.
    5136: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    5137: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    5138: .   i - row indices for "diagonal" portion of matrix
    5139: .   j - column indices
    5140: .   a - matrix values
    5141: .   oi - row indices for "off-diagonal" portion of matrix
    5142: .   oj - column indices
    5143: -   oa - matrix values

    5145:    Output Parameter:
    5146: .   mat - the matrix

    5148:    Level: advanced

    5150:    Notes:
    5151:        The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user
    5152:        must free the arrays once the matrix has been destroyed and not before.

    5154:        The i and j indices are 0 based

    5156:        See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix

    5158:        This sets local rows and cannot be used to set off-processor values.

    5160:        Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a
    5161:        legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does
    5162:        not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because
    5163:        the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to
    5164:        keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all
    5165:        communication if it is known that only local entries will be set.

    5167: .keywords: matrix, aij, compressed row, sparse, parallel

    5169: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
    5170:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays()
    5171: @*/
    5172: 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)
    5173: {
    5175:   Mat_MPIAIJ     *maij;

    5178:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
    5179:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
    5180:   if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0");
    5181:   MatCreate(comm,mat);
    5182:   MatSetSizes(*mat,m,n,M,N);
    5183:   MatSetType(*mat,MATMPIAIJ);
    5184:   maij = (Mat_MPIAIJ*) (*mat)->data;

    5186:   (*mat)->preallocated = PETSC_TRUE;

    5188:   PetscLayoutSetUp((*mat)->rmap);
    5189:   PetscLayoutSetUp((*mat)->cmap);

    5191:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);
    5192:   MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);

    5194:   MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);
    5195:   MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);
    5196:   MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);
    5197:   MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);

    5199:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
    5200:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
    5201:   MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    5202:   return(0);
    5203: }

    5205: /*
    5206:     Special version for direct calls from Fortran
    5207: */
    5208: #include <petsc/private/fortranimpl.h>

    5210: #if defined(PETSC_HAVE_FORTRAN_CAPS)
    5211: #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ
    5212: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
    5213: #define matsetvaluesmpiaij_ matsetvaluesmpiaij
    5214: #endif

    5216: /* Change these macros so can be used in void function */
    5217: #undef CHKERRQ
    5218: #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr)
    5219: #undef SETERRQ2
    5220: #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr)
    5221: #undef SETERRQ3
    5222: #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr)
    5223: #undef SETERRQ
    5224: #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr)

    5228: PETSC_EXTERN void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr)
    5229: {
    5230:   Mat            mat  = *mmat;
    5231:   PetscInt       m    = *mm, n = *mn;
    5232:   InsertMode     addv = *maddv;
    5233:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
    5234:   PetscScalar    value;

    5237:   MatCheckPreallocated(mat,1);
    5238:   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;

    5240: #if defined(PETSC_USE_DEBUG)
    5241:   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
    5242: #endif
    5243:   {
    5244:     PetscInt  i,j,rstart  = mat->rmap->rstart,rend = mat->rmap->rend;
    5245:     PetscInt  cstart      = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
    5246:     PetscBool roworiented = aij->roworiented;

    5248:     /* Some Variables required in the macro */
    5249:     Mat        A                 = aij->A;
    5250:     Mat_SeqAIJ *a                = (Mat_SeqAIJ*)A->data;
    5251:     PetscInt   *aimax            = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
    5252:     MatScalar  *aa               = a->a;
    5253:     PetscBool  ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE);
    5254:     Mat        B                 = aij->B;
    5255:     Mat_SeqAIJ *b                = (Mat_SeqAIJ*)B->data;
    5256:     PetscInt   *bimax            = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
    5257:     MatScalar  *ba               = b->a;

    5259:     PetscInt  *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
    5260:     PetscInt  nonew = a->nonew;
    5261:     MatScalar *ap1,*ap2;

    5264:     for (i=0; i<m; i++) {
    5265:       if (im[i] < 0) continue;
    5266: #if defined(PETSC_USE_DEBUG)
    5267:       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);
    5268: #endif
    5269:       if (im[i] >= rstart && im[i] < rend) {
    5270:         row      = im[i] - rstart;
    5271:         lastcol1 = -1;
    5272:         rp1      = aj + ai[row];
    5273:         ap1      = aa + ai[row];
    5274:         rmax1    = aimax[row];
    5275:         nrow1    = ailen[row];
    5276:         low1     = 0;
    5277:         high1    = nrow1;
    5278:         lastcol2 = -1;
    5279:         rp2      = bj + bi[row];
    5280:         ap2      = ba + bi[row];
    5281:         rmax2    = bimax[row];
    5282:         nrow2    = bilen[row];
    5283:         low2     = 0;
    5284:         high2    = nrow2;

    5286:         for (j=0; j<n; j++) {
    5287:           if (roworiented) value = v[i*n+j];
    5288:           else value = v[i+j*m];
    5289:           if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue;
    5290:           if (in[j] >= cstart && in[j] < cend) {
    5291:             col = in[j] - cstart;
    5292:             MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
    5293:           } else if (in[j] < 0) continue;
    5294: #if defined(PETSC_USE_DEBUG)
    5295:           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);
    5296: #endif
    5297:           else {
    5298:             if (mat->was_assembled) {
    5299:               if (!aij->colmap) {
    5300:                 MatCreateColmap_MPIAIJ_Private(mat);
    5301:               }
    5302: #if defined(PETSC_USE_CTABLE)
    5303:               PetscTableFind(aij->colmap,in[j]+1,&col);
    5304:               col--;
    5305: #else
    5306:               col = aij->colmap[in[j]] - 1;
    5307: #endif
    5308:               if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
    5309:                 MatDisAssemble_MPIAIJ(mat);
    5310:                 col  =  in[j];
    5311:                 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
    5312:                 B     = aij->B;
    5313:                 b     = (Mat_SeqAIJ*)B->data;
    5314:                 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
    5315:                 rp2   = bj + bi[row];
    5316:                 ap2   = ba + bi[row];
    5317:                 rmax2 = bimax[row];
    5318:                 nrow2 = bilen[row];
    5319:                 low2  = 0;
    5320:                 high2 = nrow2;
    5321:                 bm    = aij->B->rmap->n;
    5322:                 ba    = b->a;
    5323:               }
    5324:             } else col = in[j];
    5325:             MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
    5326:           }
    5327:         }
    5328:       } else if (!aij->donotstash) {
    5329:         if (roworiented) {
    5330:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
    5331:         } else {
    5332:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
    5333:         }
    5334:       }
    5335:     }
    5336:   }
    5337:   PetscFunctionReturnVoid();
    5338: }