Actual source code: mpisbaij.c
petsc-3.7.1 2016-05-15
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      2: #include <../src/mat/impls/baij/mpi/mpibaij.h>    /*I "petscmat.h" I*/
      3: #include <../src/mat/impls/sbaij/mpi/mpisbaij.h>
      4: #include <../src/mat/impls/sbaij/seq/sbaij.h>
      5: #include <petscblaslapack.h>

      7: #if defined(PETSC_HAVE_ELEMENTAL)
      8: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
      9: #endif
     12: PetscErrorCode  MatStoreValues_MPISBAIJ(Mat mat)
     13: {
     14:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

     18:   MatStoreValues(aij->A);
     19:   MatStoreValues(aij->B);
     20:   return(0);
     21: }

     25: PetscErrorCode  MatRetrieveValues_MPISBAIJ(Mat mat)
     26: {
     27:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

     31:   MatRetrieveValues(aij->A);
     32:   MatRetrieveValues(aij->B);
     33:   return(0);
     34: }

     36: #define  MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,orow,ocol)      \
     37:   { \
     38:  \
     39:     brow = row/bs;  \
     40:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
     41:     rmax = aimax[brow]; nrow = ailen[brow]; \
     42:     bcol = col/bs; \
     43:     ridx = row % bs; cidx = col % bs; \
     44:     low  = 0; high = nrow; \
     45:     while (high-low > 3) { \
     46:       t = (low+high)/2; \
     47:       if (rp[t] > bcol) high = t; \
     48:       else              low  = t; \
     49:     } \
     50:     for (_i=low; _i<high; _i++) { \
     51:       if (rp[_i] > bcol) break; \
     52:       if (rp[_i] == bcol) { \
     53:         bap = ap + bs2*_i + bs*cidx + ridx; \
     54:         if (addv == ADD_VALUES) *bap += value;  \
     55:         else                    *bap  = value;  \
     56:         goto a_noinsert; \
     57:       } \
     58:     } \
     59:     if (a->nonew == 1) goto a_noinsert; \
     60:     if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
     61:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
     62:     N = nrow++ - 1;  \
     63:     /* shift up all the later entries in this row */ \
     64:     for (ii=N; ii>=_i; ii--) { \
     65:       rp[ii+1] = rp[ii]; \
     66:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
     67:     } \
     68:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); }  \
     69:     rp[_i]                      = bcol;  \
     70:     ap[bs2*_i + bs*cidx + ridx] = value;  \
     71:     A->nonzerostate++;\
     72: a_noinsert:; \
     73:     ailen[brow] = nrow; \
     74:   }

     76: #define  MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,orow,ocol) \
     77:   { \
     78:     brow = row/bs;  \
     79:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
     80:     rmax = bimax[brow]; nrow = bilen[brow]; \
     81:     bcol = col/bs; \
     82:     ridx = row % bs; cidx = col % bs; \
     83:     low  = 0; high = nrow; \
     84:     while (high-low > 3) { \
     85:       t = (low+high)/2; \
     86:       if (rp[t] > bcol) high = t; \
     87:       else              low  = t; \
     88:     } \
     89:     for (_i=low; _i<high; _i++) { \
     90:       if (rp[_i] > bcol) break; \
     91:       if (rp[_i] == bcol) { \
     92:         bap = ap + bs2*_i + bs*cidx + ridx; \
     93:         if (addv == ADD_VALUES) *bap += value;  \
     94:         else                    *bap  = value;  \
     95:         goto b_noinsert; \
     96:       } \
     97:     } \
     98:     if (b->nonew == 1) goto b_noinsert; \
     99:     if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
    100:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
    101:     N = nrow++ - 1;  \
    102:     /* shift up all the later entries in this row */ \
    103:     for (ii=N; ii>=_i; ii--) { \
    104:       rp[ii+1] = rp[ii]; \
    105:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
    106:     } \
    107:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));}  \
    108:     rp[_i]                      = bcol;  \
    109:     ap[bs2*_i + bs*cidx + ridx] = value;  \
    110:     B->nonzerostate++;\
    111: b_noinsert:; \
    112:     bilen[brow] = nrow; \
    113:   }

    115: /* Only add/insert a(i,j) with i<=j (blocks).
    116:    Any a(i,j) with i>j input by user is ingored.
    117: */
    120: PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
    121: {
    122:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    123:   MatScalar      value;
    124:   PetscBool      roworiented = baij->roworiented;
    126:   PetscInt       i,j,row,col;
    127:   PetscInt       rstart_orig=mat->rmap->rstart;
    128:   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
    129:   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;

    131:   /* Some Variables required in the macro */
    132:   Mat          A     = baij->A;
    133:   Mat_SeqSBAIJ *a    = (Mat_SeqSBAIJ*)(A)->data;
    134:   PetscInt     *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
    135:   MatScalar    *aa   =a->a;

    137:   Mat         B     = baij->B;
    138:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
    139:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
    140:   MatScalar   *ba   =b->a;

    142:   PetscInt  *rp,ii,nrow,_i,rmax,N,brow,bcol;
    143:   PetscInt  low,high,t,ridx,cidx,bs2=a->bs2;
    144:   MatScalar *ap,*bap;

    146:   /* for stash */
    147:   PetscInt  n_loc, *in_loc = NULL;
    148:   MatScalar *v_loc = NULL;

    151:   if (!baij->donotstash) {
    152:     if (n > baij->n_loc) {
    153:       PetscFree(baij->in_loc);
    154:       PetscFree(baij->v_loc);
    155:       PetscMalloc1(n,&baij->in_loc);
    156:       PetscMalloc1(n,&baij->v_loc);

    158:       baij->n_loc = n;
    159:     }
    160:     in_loc = baij->in_loc;
    161:     v_loc  = baij->v_loc;
    162:   }

    164:   for (i=0; i<m; i++) {
    165:     if (im[i] < 0) continue;
    166: #if defined(PETSC_USE_DEBUG)
    167:     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);
    168: #endif
    169:     if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
    170:       row = im[i] - rstart_orig;              /* local row index */
    171:       for (j=0; j<n; j++) {
    172:         if (im[i]/bs > in[j]/bs) {
    173:           if (a->ignore_ltriangular) {
    174:             continue;    /* ignore lower triangular blocks */
    175:           } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
    176:         }
    177:         if (in[j] >= cstart_orig && in[j] < cend_orig) {  /* diag entry (A) */
    178:           col  = in[j] - cstart_orig;         /* local col index */
    179:           brow = row/bs; bcol = col/bs;
    180:           if (brow > bcol) continue;  /* ignore lower triangular blocks of A */
    181:           if (roworiented) value = v[i*n+j];
    182:           else             value = v[i+j*m];
    183:           MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
    184:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
    185:         } else if (in[j] < 0) continue;
    186: #if defined(PETSC_USE_DEBUG)
    187:         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);
    188: #endif
    189:         else {  /* off-diag entry (B) */
    190:           if (mat->was_assembled) {
    191:             if (!baij->colmap) {
    192:               MatCreateColmap_MPIBAIJ_Private(mat);
    193:             }
    194: #if defined(PETSC_USE_CTABLE)
    195:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
    196:             col  = col - 1;
    197: #else
    198:             col = baij->colmap[in[j]/bs] - 1;
    199: #endif
    200:             if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
    201:               MatDisAssemble_MPISBAIJ(mat);
    202:               col  =  in[j];
    203:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
    204:               B    = baij->B;
    205:               b    = (Mat_SeqBAIJ*)(B)->data;
    206:               bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
    207:               ba   = b->a;
    208:             } else col += in[j]%bs;
    209:           } else col = in[j];
    210:           if (roworiented) value = v[i*n+j];
    211:           else             value = v[i+j*m];
    212:           MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
    213:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
    214:         }
    215:       }
    216:     } else {  /* off processor entry */
    217:       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]);
    218:       if (!baij->donotstash) {
    219:         mat->assembled = PETSC_FALSE;
    220:         n_loc          = 0;
    221:         for (j=0; j<n; j++) {
    222:           if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
    223:           in_loc[n_loc] = in[j];
    224:           if (roworiented) {
    225:             v_loc[n_loc] = v[i*n+j];
    226:           } else {
    227:             v_loc[n_loc] = v[j*m+i];
    228:           }
    229:           n_loc++;
    230:         }
    231:         MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
    232:       }
    233:     }
    234:   }
    235:   return(0);
    236: }

    240: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
    241: {
    242:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
    243:   PetscErrorCode    ierr;
    244:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
    245:   PetscInt          *imax      =a->imax,*ai=a->i,*ailen=a->ilen;
    246:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
    247:   PetscBool         roworiented=a->roworiented;
    248:   const PetscScalar *value     = v;
    249:   MatScalar         *ap,*aa = a->a,*bap;

    252:   if (col < row) {
    253:     if (a->ignore_ltriangular) return(0); /* ignore lower triangular block */
    254:     else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
    255:   }
    256:   rp   = aj + ai[row];
    257:   ap   = aa + bs2*ai[row];
    258:   rmax = imax[row];
    259:   nrow = ailen[row];
    260:   value = v;
    261:   low   = 0;
    262:   high  = nrow;

    264:   while (high-low > 7) {
    265:     t = (low+high)/2;
    266:     if (rp[t] > col) high = t;
    267:     else             low  = t;
    268:   }
    269:   for (i=low; i<high; i++) {
    270:     if (rp[i] > col) break;
    271:     if (rp[i] == col) {
    272:       bap = ap +  bs2*i;
    273:       if (roworiented) {
    274:         if (is == ADD_VALUES) {
    275:           for (ii=0; ii<bs; ii++) {
    276:             for (jj=ii; jj<bs2; jj+=bs) {
    277:               bap[jj] += *value++;
    278:             }
    279:           }
    280:         } else {
    281:           for (ii=0; ii<bs; ii++) {
    282:             for (jj=ii; jj<bs2; jj+=bs) {
    283:               bap[jj] = *value++;
    284:             }
    285:           }
    286:         }
    287:       } else {
    288:         if (is == ADD_VALUES) {
    289:           for (ii=0; ii<bs; ii++) {
    290:             for (jj=0; jj<bs; jj++) {
    291:               *bap++ += *value++;
    292:             }
    293:           }
    294:         } else {
    295:           for (ii=0; ii<bs; ii++) {
    296:             for (jj=0; jj<bs; jj++) {
    297:               *bap++  = *value++;
    298:             }
    299:           }
    300:         }
    301:       }
    302:       goto noinsert2;
    303:     }
    304:   }
    305:   if (nonew == 1) goto noinsert2;
    306:   if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new block index nonzero block (%D, %D) in the matrix", orow, ocol);
    307:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
    308:   N = nrow++ - 1; high++;
    309:   /* shift up all the later entries in this row */
    310:   for (ii=N; ii>=i; ii--) {
    311:     rp[ii+1] = rp[ii];
    312:     PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
    313:   }
    314:   if (N >= i) {
    315:     PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
    316:   }
    317:   rp[i] = col;
    318:   bap   = ap +  bs2*i;
    319:   if (roworiented) {
    320:     for (ii=0; ii<bs; ii++) {
    321:       for (jj=ii; jj<bs2; jj+=bs) {
    322:         bap[jj] = *value++;
    323:       }
    324:     }
    325:   } else {
    326:     for (ii=0; ii<bs; ii++) {
    327:       for (jj=0; jj<bs; jj++) {
    328:         *bap++ = *value++;
    329:       }
    330:     }
    331:   }
    332:   noinsert2:;
    333:   ailen[row] = nrow;
    334:   return(0);
    335: }

    339: /*
    340:    This routine is exactly duplicated in mpibaij.c
    341: */
    342: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
    343: {
    344:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    345:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
    346:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
    347:   PetscErrorCode    ierr;
    348:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
    349:   PetscBool         roworiented=a->roworiented;
    350:   const PetscScalar *value     = v;
    351:   MatScalar         *ap,*aa = a->a,*bap;

    354:   rp   = aj + ai[row];
    355:   ap   = aa + bs2*ai[row];
    356:   rmax = imax[row];
    357:   nrow = ailen[row];
    358:   low  = 0;
    359:   high = nrow;
    360:   value = v;
    361:   while (high-low > 7) {
    362:     t = (low+high)/2;
    363:     if (rp[t] > col) high = t;
    364:     else             low  = t;
    365:   }
    366:   for (i=low; i<high; i++) {
    367:     if (rp[i] > col) break;
    368:     if (rp[i] == col) {
    369:       bap = ap +  bs2*i;
    370:       if (roworiented) {
    371:         if (is == ADD_VALUES) {
    372:           for (ii=0; ii<bs; ii++) {
    373:             for (jj=ii; jj<bs2; jj+=bs) {
    374:               bap[jj] += *value++;
    375:             }
    376:           }
    377:         } else {
    378:           for (ii=0; ii<bs; ii++) {
    379:             for (jj=ii; jj<bs2; jj+=bs) {
    380:               bap[jj] = *value++;
    381:             }
    382:           }
    383:         }
    384:       } else {
    385:         if (is == ADD_VALUES) {
    386:           for (ii=0; ii<bs; ii++,value+=bs) {
    387:             for (jj=0; jj<bs; jj++) {
    388:               bap[jj] += value[jj];
    389:             }
    390:             bap += bs;
    391:           }
    392:         } else {
    393:           for (ii=0; ii<bs; ii++,value+=bs) {
    394:             for (jj=0; jj<bs; jj++) {
    395:               bap[jj]  = value[jj];
    396:             }
    397:             bap += bs;
    398:           }
    399:         }
    400:       }
    401:       goto noinsert2;
    402:     }
    403:   }
    404:   if (nonew == 1) goto noinsert2;
    405:   if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new global block indexed nonzero block (%D, %D) in the matrix", orow, ocol);
    406:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
    407:   N = nrow++ - 1; high++;
    408:   /* shift up all the later entries in this row */
    409:   for (ii=N; ii>=i; ii--) {
    410:     rp[ii+1] = rp[ii];
    411:     PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
    412:   }
    413:   if (N >= i) {
    414:     PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
    415:   }
    416:   rp[i] = col;
    417:   bap   = ap +  bs2*i;
    418:   if (roworiented) {
    419:     for (ii=0; ii<bs; ii++) {
    420:       for (jj=ii; jj<bs2; jj+=bs) {
    421:         bap[jj] = *value++;
    422:       }
    423:     }
    424:   } else {
    425:     for (ii=0; ii<bs; ii++) {
    426:       for (jj=0; jj<bs; jj++) {
    427:         *bap++ = *value++;
    428:       }
    429:     }
    430:   }
    431:   noinsert2:;
    432:   ailen[row] = nrow;
    433:   return(0);
    434: }

    438: /*
    439:     This routine could be optimized by removing the need for the block copy below and passing stride information
    440:   to the above inline routines; similarly in MatSetValuesBlocked_MPIBAIJ()
    441: */
    442: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
    443: {
    444:   Mat_MPISBAIJ    *baij = (Mat_MPISBAIJ*)mat->data;
    445:   const MatScalar *value;
    446:   MatScalar       *barray     =baij->barray;
    447:   PetscBool       roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
    448:   PetscErrorCode  ierr;
    449:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
    450:   PetscInt        rend=baij->rendbs,cstart=baij->rstartbs,stepval;
    451:   PetscInt        cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2;

    454:   if (!barray) {
    455:     PetscMalloc1(bs2,&barray);
    456:     baij->barray = barray;
    457:   }

    459:   if (roworiented) {
    460:     stepval = (n-1)*bs;
    461:   } else {
    462:     stepval = (m-1)*bs;
    463:   }
    464:   for (i=0; i<m; i++) {
    465:     if (im[i] < 0) continue;
    466: #if defined(PETSC_USE_DEBUG)
    467:     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed row too large %D max %D",im[i],baij->Mbs-1);
    468: #endif
    469:     if (im[i] >= rstart && im[i] < rend) {
    470:       row = im[i] - rstart;
    471:       for (j=0; j<n; j++) {
    472:         if (im[i] > in[j]) {
    473:           if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
    474:           else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
    475:         }
    476:         /* If NumCol = 1 then a copy is not required */
    477:         if ((roworiented) && (n == 1)) {
    478:           barray = (MatScalar*) v + i*bs2;
    479:         } else if ((!roworiented) && (m == 1)) {
    480:           barray = (MatScalar*) v + j*bs2;
    481:         } else { /* Here a copy is required */
    482:           if (roworiented) {
    483:             value = v + i*(stepval+bs)*bs + j*bs;
    484:           } else {
    485:             value = v + j*(stepval+bs)*bs + i*bs;
    486:           }
    487:           for (ii=0; ii<bs; ii++,value+=stepval) {
    488:             for (jj=0; jj<bs; jj++) {
    489:               *barray++ = *value++;
    490:             }
    491:           }
    492:           barray -=bs2;
    493:         }

    495:         if (in[j] >= cstart && in[j] < cend) {
    496:           col  = in[j] - cstart;
    497:           MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
    498:         } else if (in[j] < 0) continue;
    499: #if defined(PETSC_USE_DEBUG)
    500:         else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed column too large %D max %D",in[j],baij->Nbs-1);
    501: #endif
    502:         else {
    503:           if (mat->was_assembled) {
    504:             if (!baij->colmap) {
    505:               MatCreateColmap_MPIBAIJ_Private(mat);
    506:             }

    508: #if defined(PETSC_USE_DEBUG)
    509: #if defined(PETSC_USE_CTABLE)
    510:             { PetscInt data;
    511:               PetscTableFind(baij->colmap,in[j]+1,&data);
    512:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    513:             }
    514: #else
    515:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    516: #endif
    517: #endif
    518: #if defined(PETSC_USE_CTABLE)
    519:             PetscTableFind(baij->colmap,in[j]+1,&col);
    520:             col  = (col - 1)/bs;
    521: #else
    522:             col = (baij->colmap[in[j]] - 1)/bs;
    523: #endif
    524:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
    525:               MatDisAssemble_MPISBAIJ(mat);
    526:               col  = in[j];
    527:             }
    528:           } else col = in[j];
    529:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
    530:         }
    531:       }
    532:     } else {
    533:       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process block indexed row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
    534:       if (!baij->donotstash) {
    535:         if (roworiented) {
    536:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    537:         } else {
    538:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    539:         }
    540:       }
    541:     }
    542:   }
    543:   return(0);
    544: }

    548: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
    549: {
    550:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    552:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
    553:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

    556:   for (i=0; i<m; i++) {
    557:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */
    558:     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);
    559:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
    560:       row = idxm[i] - bsrstart;
    561:       for (j=0; j<n; j++) {
    562:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */
    563:         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);
    564:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
    565:           col  = idxn[j] - bscstart;
    566:           MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
    567:         } else {
    568:           if (!baij->colmap) {
    569:             MatCreateColmap_MPIBAIJ_Private(mat);
    570:           }
    571: #if defined(PETSC_USE_CTABLE)
    572:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
    573:           data--;
    574: #else
    575:           data = baij->colmap[idxn[j]/bs]-1;
    576: #endif
    577:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
    578:           else {
    579:             col  = data + idxn[j]%bs;
    580:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
    581:           }
    582:         }
    583:       }
    584:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
    585:   }
    586:   return(0);
    587: }

    591: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
    592: {
    593:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    595:   PetscReal      sum[2],*lnorm2;

    598:   if (baij->size == 1) {
    599:      MatNorm(baij->A,type,norm);
    600:   } else {
    601:     if (type == NORM_FROBENIUS) {
    602:       PetscMalloc1(2,&lnorm2);
    603:        MatNorm(baij->A,type,lnorm2);
    604:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++;            /* squar power of norm(A) */
    605:        MatNorm(baij->B,type,lnorm2);
    606:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--;             /* squar power of norm(B) */
    607:       MPIU_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
    608:       *norm   = PetscSqrtReal(sum[0] + 2*sum[1]);
    609:       PetscFree(lnorm2);
    610:     } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
    611:       Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
    612:       Mat_SeqBAIJ  *bmat=(Mat_SeqBAIJ*)baij->B->data;
    613:       PetscReal    *rsum,*rsum2,vabs;
    614:       PetscInt     *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
    615:       PetscInt     brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs;
    616:       MatScalar    *v;

    618:       PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);
    619:       PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));
    620:       /* Amat */
    621:       v = amat->a; jj = amat->j;
    622:       for (brow=0; brow<mbs; brow++) {
    623:         grow = bs*(rstart + brow);
    624:         nz   = amat->i[brow+1] - amat->i[brow];
    625:         for (bcol=0; bcol<nz; bcol++) {
    626:           gcol = bs*(rstart + *jj); jj++;
    627:           for (col=0; col<bs; col++) {
    628:             for (row=0; row<bs; row++) {
    629:               vabs            = PetscAbsScalar(*v); v++;
    630:               rsum[gcol+col] += vabs;
    631:               /* non-diagonal block */
    632:               if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
    633:             }
    634:           }
    635:         }
    636:         PetscLogFlops(nz*bs*bs);
    637:       }
    638:       /* Bmat */
    639:       v = bmat->a; jj = bmat->j;
    640:       for (brow=0; brow<mbs; brow++) {
    641:         grow = bs*(rstart + brow);
    642:         nz = bmat->i[brow+1] - bmat->i[brow];
    643:         for (bcol=0; bcol<nz; bcol++) {
    644:           gcol = bs*garray[*jj]; jj++;
    645:           for (col=0; col<bs; col++) {
    646:             for (row=0; row<bs; row++) {
    647:               vabs            = PetscAbsScalar(*v); v++;
    648:               rsum[gcol+col] += vabs;
    649:               rsum[grow+row] += vabs;
    650:             }
    651:           }
    652:         }
    653:         PetscLogFlops(nz*bs*bs);
    654:       }
    655:       MPIU_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
    656:       *norm = 0.0;
    657:       for (col=0; col<mat->cmap->N; col++) {
    658:         if (rsum2[col] > *norm) *norm = rsum2[col];
    659:       }
    660:       PetscFree2(rsum,rsum2);
    661:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
    662:   }
    663:   return(0);
    664: }

    668: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
    669: {
    670:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    672:   PetscInt       nstash,reallocs;

    675:   if (baij->donotstash || mat->nooffprocentries) return(0);

    677:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
    678:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
    679:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
    680:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
    681:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
    682:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
    683:   return(0);
    684: }

    688: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
    689: {
    690:   Mat_MPISBAIJ   *baij=(Mat_MPISBAIJ*)mat->data;
    691:   Mat_SeqSBAIJ   *a   =(Mat_SeqSBAIJ*)baij->A->data;
    693:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
    694:   PetscInt       *row,*col;
    695:   PetscBool      other_disassembled;
    696:   PetscMPIInt    n;
    697:   PetscBool      r1,r2,r3;
    698:   MatScalar      *val;

    700:   /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */
    702:   if (!baij->donotstash &&  !mat->nooffprocentries) {
    703:     while (1) {
    704:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
    705:       if (!flg) break;

    707:       for (i=0; i<n;) {
    708:         /* Now identify the consecutive vals belonging to the same row */
    709:         for (j=i,rstart=row[j]; j<n; j++) {
    710:           if (row[j] != rstart) break;
    711:         }
    712:         if (j < n) ncols = j-i;
    713:         else       ncols = n-i;
    714:         /* Now assemble all these values with a single function call */
    715:         MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
    716:         i    = j;
    717:       }
    718:     }
    719:     MatStashScatterEnd_Private(&mat->stash);
    720:     /* Now process the block-stash. Since the values are stashed column-oriented,
    721:        set the roworiented flag to column oriented, and after MatSetValues()
    722:        restore the original flags */
    723:     r1 = baij->roworiented;
    724:     r2 = a->roworiented;
    725:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

    727:     baij->roworiented = PETSC_FALSE;
    728:     a->roworiented    = PETSC_FALSE;

    730:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */
    731:     while (1) {
    732:       MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);
    733:       if (!flg) break;

    735:       for (i=0; i<n;) {
    736:         /* Now identify the consecutive vals belonging to the same row */
    737:         for (j=i,rstart=row[j]; j<n; j++) {
    738:           if (row[j] != rstart) break;
    739:         }
    740:         if (j < n) ncols = j-i;
    741:         else       ncols = n-i;
    742:         MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
    743:         i    = j;
    744:       }
    745:     }
    746:     MatStashScatterEnd_Private(&mat->bstash);

    748:     baij->roworiented = r1;
    749:     a->roworiented    = r2;

    751:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
    752:   }

    754:   MatAssemblyBegin(baij->A,mode);
    755:   MatAssemblyEnd(baij->A,mode);

    757:   /* determine if any processor has disassembled, if so we must
    758:      also disassemble ourselfs, in order that we may reassemble. */
    759:   /*
    760:      if nonzero structure of submatrix B cannot change then we know that
    761:      no processor disassembled thus we can skip this stuff
    762:   */
    763:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
    764:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
    765:     if (mat->was_assembled && !other_disassembled) {
    766:       MatDisAssemble_MPISBAIJ(mat);
    767:     }
    768:   }

    770:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
    771:     MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
    772:   }
    773:   MatAssemblyBegin(baij->B,mode);
    774:   MatAssemblyEnd(baij->B,mode);

    776:   PetscFree2(baij->rowvalues,baij->rowindices);

    778:   baij->rowvalues = 0;

    780:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
    781:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
    782:     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
    783:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
    784:   }
    785:   return(0);
    786: }

    788: extern PetscErrorCode MatView_SeqSBAIJ(Mat,PetscViewer);
    789: extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
    790: #include <petscdraw.h>
    793: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
    794: {
    795:   Mat_MPISBAIJ      *baij = (Mat_MPISBAIJ*)mat->data;
    796:   PetscErrorCode    ierr;
    797:   PetscInt          bs   = mat->rmap->bs;
    798:   PetscMPIInt       rank = baij->rank;
    799:   PetscBool         iascii,isdraw;
    800:   PetscViewer       sviewer;
    801:   PetscViewerFormat format;

    804:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    805:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    806:   if (iascii) {
    807:     PetscViewerGetFormat(viewer,&format);
    808:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
    809:       MatInfo info;
    810:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
    811:       MatGetInfo(mat,MAT_LOCAL,&info);
    812:       PetscViewerASCIIPushSynchronized(viewer);
    813:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);
    814:       MatGetInfo(baij->A,MAT_LOCAL,&info);
    815:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
    816:       MatGetInfo(baij->B,MAT_LOCAL,&info);
    817:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
    818:       PetscViewerFlush(viewer);
    819:       PetscViewerASCIIPopSynchronized(viewer);
    820:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
    821:       VecScatterView(baij->Mvctx,viewer);
    822:       return(0);
    823:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
    824:       PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
    825:       return(0);
    826:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
    827:       return(0);
    828:     }
    829:   }

    831:   if (isdraw) {
    832:     PetscDraw draw;
    833:     PetscBool isnull;
    834:     PetscViewerDrawGetDraw(viewer,0,&draw);
    835:     PetscDrawIsNull(draw,&isnull);
    836:     if (isnull) return(0);
    837:   }

    839:   {
    840:     /* assemble the entire matrix onto first processor. */
    841:     Mat          A;
    842:     Mat_SeqSBAIJ *Aloc;
    843:     Mat_SeqBAIJ  *Bloc;
    844:     PetscInt     M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
    845:     MatScalar    *a;
    846:     const char   *matname;

    848:     /* Should this be the same type as mat? */
    849:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
    850:     if (!rank) {
    851:       MatSetSizes(A,M,N,M,N);
    852:     } else {
    853:       MatSetSizes(A,0,0,M,N);
    854:     }
    855:     MatSetType(A,MATMPISBAIJ);
    856:     MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
    857:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
    858:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

    860:     /* copy over the A part */
    861:     Aloc = (Mat_SeqSBAIJ*)baij->A->data;
    862:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
    863:     PetscMalloc1(bs,&rvals);

    865:     for (i=0; i<mbs; i++) {
    866:       rvals[0] = bs*(baij->rstartbs + i);
    867:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    868:       for (j=ai[i]; j<ai[i+1]; j++) {
    869:         col = (baij->cstartbs+aj[j])*bs;
    870:         for (k=0; k<bs; k++) {
    871:           MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
    872:           col++;
    873:           a += bs;
    874:         }
    875:       }
    876:     }
    877:     /* copy over the B part */
    878:     Bloc = (Mat_SeqBAIJ*)baij->B->data;
    879:     ai   = Bloc->i; aj = Bloc->j; a = Bloc->a;
    880:     for (i=0; i<mbs; i++) {

    882:       rvals[0] = bs*(baij->rstartbs + i);
    883:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    884:       for (j=ai[i]; j<ai[i+1]; j++) {
    885:         col = baij->garray[aj[j]]*bs;
    886:         for (k=0; k<bs; k++) {
    887:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
    888:           col++;
    889:           a += bs;
    890:         }
    891:       }
    892:     }
    893:     PetscFree(rvals);
    894:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    895:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    896:     /*
    897:        Everyone has to call to draw the matrix since the graphics waits are
    898:        synchronized across all processors that share the PetscDraw object
    899:     */
    900:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
    901:     PetscObjectGetName((PetscObject)mat,&matname);
    902:     if (!rank) {
    903:       PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,matname);
    904:       MatView_SeqSBAIJ(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
    905:     }
    906:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
    907:     PetscViewerFlush(viewer);
    908:     MatDestroy(&A);
    909:   }
    910:   return(0);
    911: }

    915: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
    916: {
    918:   PetscBool      iascii,isdraw,issocket,isbinary;

    921:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    922:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    923:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
    924:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    925:   if (iascii || isdraw || issocket || isbinary) {
    926:     MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
    927:   }
    928:   return(0);
    929: }

    933: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
    934: {
    935:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;

    939: #if defined(PETSC_USE_LOG)
    940:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
    941: #endif
    942:   MatStashDestroy_Private(&mat->stash);
    943:   MatStashDestroy_Private(&mat->bstash);
    944:   MatDestroy(&baij->A);
    945:   MatDestroy(&baij->B);
    946: #if defined(PETSC_USE_CTABLE)
    947:   PetscTableDestroy(&baij->colmap);
    948: #else
    949:   PetscFree(baij->colmap);
    950: #endif
    951:   PetscFree(baij->garray);
    952:   VecDestroy(&baij->lvec);
    953:   VecScatterDestroy(&baij->Mvctx);
    954:   VecDestroy(&baij->slvec0);
    955:   VecDestroy(&baij->slvec0b);
    956:   VecDestroy(&baij->slvec1);
    957:   VecDestroy(&baij->slvec1a);
    958:   VecDestroy(&baij->slvec1b);
    959:   VecScatterDestroy(&baij->sMvctx);
    960:   PetscFree2(baij->rowvalues,baij->rowindices);
    961:   PetscFree(baij->barray);
    962:   PetscFree(baij->hd);
    963:   VecDestroy(&baij->diag);
    964:   VecDestroy(&baij->bb1);
    965:   VecDestroy(&baij->xx1);
    966: #if defined(PETSC_USE_REAL_MAT_SINGLE)
    967:   PetscFree(baij->setvaluescopy);
    968: #endif
    969:   PetscFree(baij->in_loc);
    970:   PetscFree(baij->v_loc);
    971:   PetscFree(baij->rangebs);
    972:   PetscFree(mat->data);

    974:   PetscObjectChangeTypeName((PetscObject)mat,0);
    975:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
    976:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
    977:   PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);
    978:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);
    979:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C",NULL);
    980: #if defined(PETSC_HAVE_ELEMENTAL)
    981:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_elemental_C",NULL);
    982: #endif
    983:   return(0);
    984: }

    988: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
    989: {
    990:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
    991:   PetscErrorCode    ierr;
    992:   PetscInt          nt,mbs=a->mbs,bs=A->rmap->bs;
    993:   PetscScalar       *from;
    994:   const PetscScalar *x;

    997:   VecGetLocalSize(xx,&nt);
    998:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

    1000:   /* diagonal part */
    1001:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
    1002:   VecSet(a->slvec1b,0.0);

    1004:   /* subdiagonal part */
    1005:   (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);

    1007:   /* copy x into the vec slvec0 */
    1008:   VecGetArray(a->slvec0,&from);
    1009:   VecGetArrayRead(xx,&x);

    1011:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
    1012:   VecRestoreArray(a->slvec0,&from);
    1013:   VecRestoreArrayRead(xx,&x);

    1015:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    1016:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    1017:   /* supperdiagonal part */
    1018:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
    1019:   return(0);
    1020: }

    1024: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
    1025: {
    1026:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
    1027:   PetscErrorCode    ierr;
    1028:   PetscInt          nt,mbs=a->mbs,bs=A->rmap->bs;
    1029:   PetscScalar       *from;
    1030:   const PetscScalar *x;

    1033:   VecGetLocalSize(xx,&nt);
    1034:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

    1036:   /* diagonal part */
    1037:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
    1038:   VecSet(a->slvec1b,0.0);

    1040:   /* subdiagonal part */
    1041:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

    1043:   /* copy x into the vec slvec0 */
    1044:   VecGetArray(a->slvec0,&from);
    1045:   VecGetArrayRead(xx,&x);

    1047:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
    1048:   VecRestoreArray(a->slvec0,&from);
    1049:   VecRestoreArrayRead(xx,&x);

    1051:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    1052:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    1053:   /* supperdiagonal part */
    1054:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
    1055:   return(0);
    1056: }

    1060: PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy)
    1061: {
    1062:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
    1064:   PetscInt       nt;

    1067:   VecGetLocalSize(xx,&nt);
    1068:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");

    1070:   VecGetLocalSize(yy,&nt);
    1071:   if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");

    1073:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1074:   /* do diagonal part */
    1075:   (*a->A->ops->mult)(a->A,xx,yy);
    1076:   /* do supperdiagonal part */
    1077:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1078:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
    1079:   /* do subdiagonal part */
    1080:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
    1081:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    1082:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    1083:   return(0);
    1084: }

    1088: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
    1089: {
    1090:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
    1091:   PetscErrorCode    ierr;
    1092:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
    1093:   PetscScalar       *from,zero=0.0;
    1094:   const PetscScalar *x;

    1097:   /*
    1098:   PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n");
    1099:   PetscSynchronizedFlush(PetscObjectComm((PetscObject)A),PETSC_STDOUT);
    1100:   */
    1101:   /* diagonal part */
    1102:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
    1103:   VecSet(a->slvec1b,zero);

    1105:   /* subdiagonal part */
    1106:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

    1108:   /* copy x into the vec slvec0 */
    1109:   VecGetArray(a->slvec0,&from);
    1110:   VecGetArrayRead(xx,&x);
    1111:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
    1112:   VecRestoreArray(a->slvec0,&from);

    1114:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    1115:   VecRestoreArrayRead(xx,&x);
    1116:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

    1118:   /* supperdiagonal part */
    1119:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
    1120:   return(0);
    1121: }

    1125: PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz)
    1126: {
    1127:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1131:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1132:   /* do diagonal part */
    1133:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
    1134:   /* do supperdiagonal part */
    1135:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1136:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);

    1138:   /* do subdiagonal part */
    1139:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
    1140:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
    1141:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
    1142:   return(0);
    1143: }

    1145: /*
    1146:   This only works correctly for square matrices where the subblock A->A is the
    1147:    diagonal block
    1148: */
    1151: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
    1152: {
    1153:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1157:   /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
    1158:   MatGetDiagonal(a->A,v);
    1159:   return(0);
    1160: }

    1164: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
    1165: {
    1166:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1170:   MatScale(a->A,aa);
    1171:   MatScale(a->B,aa);
    1172:   return(0);
    1173: }

    1177: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1178: {
    1179:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
    1180:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
    1182:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
    1183:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
    1184:   PetscInt       *cmap,*idx_p,cstart = mat->rstartbs;

    1187:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
    1188:   mat->getrowactive = PETSC_TRUE;

    1190:   if (!mat->rowvalues && (idx || v)) {
    1191:     /*
    1192:         allocate enough space to hold information from the longest row.
    1193:     */
    1194:     Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
    1195:     Mat_SeqBAIJ  *Ba = (Mat_SeqBAIJ*)mat->B->data;
    1196:     PetscInt     max = 1,mbs = mat->mbs,tmp;
    1197:     for (i=0; i<mbs; i++) {
    1198:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
    1199:       if (max < tmp) max = tmp;
    1200:     }
    1201:     PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
    1202:   }

    1204:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
    1205:   lrow = row - brstart;  /* local row index */

    1207:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
    1208:   if (!v)   {pvA = 0; pvB = 0;}
    1209:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
    1210:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
    1211:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
    1212:   nztot = nzA + nzB;

    1214:   cmap = mat->garray;
    1215:   if (v  || idx) {
    1216:     if (nztot) {
    1217:       /* Sort by increasing column numbers, assuming A and B already sorted */
    1218:       PetscInt imark = -1;
    1219:       if (v) {
    1220:         *v = v_p = mat->rowvalues;
    1221:         for (i=0; i<nzB; i++) {
    1222:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
    1223:           else break;
    1224:         }
    1225:         imark = i;
    1226:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
    1227:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
    1228:       }
    1229:       if (idx) {
    1230:         *idx = idx_p = mat->rowindices;
    1231:         if (imark > -1) {
    1232:           for (i=0; i<imark; i++) {
    1233:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
    1234:           }
    1235:         } else {
    1236:           for (i=0; i<nzB; i++) {
    1237:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
    1238:             else break;
    1239:           }
    1240:           imark = i;
    1241:         }
    1242:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
    1243:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
    1244:       }
    1245:     } else {
    1246:       if (idx) *idx = 0;
    1247:       if (v)   *v   = 0;
    1248:     }
    1249:   }
    1250:   *nz  = nztot;
    1251:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
    1252:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
    1253:   return(0);
    1254: }

    1258: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1259: {
    1260:   Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;

    1263:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
    1264:   baij->getrowactive = PETSC_FALSE;
    1265:   return(0);
    1266: }

    1270: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
    1271: {
    1272:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
    1273:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

    1276:   aA->getrow_utriangular = PETSC_TRUE;
    1277:   return(0);
    1278: }
    1281: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
    1282: {
    1283:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
    1284:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

    1287:   aA->getrow_utriangular = PETSC_FALSE;
    1288:   return(0);
    1289: }

    1293: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
    1294: {
    1295:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1299:   MatRealPart(a->A);
    1300:   MatRealPart(a->B);
    1301:   return(0);
    1302: }

    1306: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
    1307: {
    1308:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1312:   MatImaginaryPart(a->A);
    1313:   MatImaginaryPart(a->B);
    1314:   return(0);
    1315: }

    1317: /* Check if isrow is a subset of iscol_local, called by MatGetSubMatrix_MPISBAIJ()
    1318:    Input: isrow       - distributed(parallel),
    1319:           iscol_local - locally owned (seq)
    1320: */
    1323: PetscErrorCode ISEqual_private(IS isrow,IS iscol_local,PetscBool  *flg)
    1324: {
    1326:   PetscInt       sz1,sz2,*a1,*a2,i,j,k,nmatch;
    1327:   const PetscInt *ptr1,*ptr2;

    1330:   ISGetLocalSize(isrow,&sz1);
    1331:   ISGetLocalSize(iscol_local,&sz2);
    1332:   if (sz1 > sz2) {
    1333:     *flg = PETSC_FALSE;
    1334:     return(0);
    1335:   }

    1337:   ISGetIndices(isrow,&ptr1);
    1338:   ISGetIndices(iscol_local,&ptr2);

    1340:   PetscMalloc1(sz1,&a1);
    1341:   PetscMalloc1(sz2,&a2);
    1342:   PetscMemcpy(a1,ptr1,sz1*sizeof(PetscInt));
    1343:   PetscMemcpy(a2,ptr2,sz2*sizeof(PetscInt));
    1344:   PetscSortInt(sz1,a1);
    1345:   PetscSortInt(sz2,a2);

    1347:   nmatch=0;
    1348:   k     = 0;
    1349:   for (i=0; i<sz1; i++){
    1350:     for (j=k; j<sz2; j++){
    1351:       if (a1[i] == a2[j]) {
    1352:         k = j; nmatch++;
    1353:         break;
    1354:       }
    1355:     }
    1356:   }
    1357:   ISRestoreIndices(isrow,&ptr1);
    1358:   ISRestoreIndices(iscol_local,&ptr2);
    1359:   PetscFree(a1);
    1360:   PetscFree(a2);
    1361:   if (nmatch < sz1) {
    1362:     *flg = PETSC_FALSE;
    1363:   } else {
    1364:     *flg = PETSC_TRUE;
    1365:   }
    1366:   return(0);
    1367: }

    1371: PetscErrorCode MatGetSubMatrix_MPISBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
    1372: {
    1374:   IS             iscol_local;
    1375:   PetscInt       csize;
    1376:   PetscBool      isequal;

    1379:   ISGetLocalSize(iscol,&csize);
    1380:   if (call == MAT_REUSE_MATRIX) {
    1381:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
    1382:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
    1383:   } else {
    1384:     ISAllGather(iscol,&iscol_local);
    1385:     ISEqual_private(isrow,iscol_local,&isequal);
    1386:     if (!isequal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"For symmetric format, iscol must equal isrow");
    1387:   }

    1389:   /* now call MatGetSubMatrix_MPIBAIJ() */
    1390:   MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
    1391:   if (call == MAT_INITIAL_MATRIX) {
    1392:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
    1393:     ISDestroy(&iscol_local);
    1394:   }
    1395:   return(0);
    1396: }

    1400: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
    1401: {
    1402:   Mat_MPISBAIJ   *l = (Mat_MPISBAIJ*)A->data;

    1406:   MatZeroEntries(l->A);
    1407:   MatZeroEntries(l->B);
    1408:   return(0);
    1409: }

    1413: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
    1414: {
    1415:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)matin->data;
    1416:   Mat            A  = a->A,B = a->B;
    1418:   PetscReal      isend[5],irecv[5];

    1421:   info->block_size = (PetscReal)matin->rmap->bs;

    1423:   MatGetInfo(A,MAT_LOCAL,info);

    1425:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
    1426:   isend[3] = info->memory;  isend[4] = info->mallocs;

    1428:   MatGetInfo(B,MAT_LOCAL,info);

    1430:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
    1431:   isend[3] += info->memory;  isend[4] += info->mallocs;
    1432:   if (flag == MAT_LOCAL) {
    1433:     info->nz_used      = isend[0];
    1434:     info->nz_allocated = isend[1];
    1435:     info->nz_unneeded  = isend[2];
    1436:     info->memory       = isend[3];
    1437:     info->mallocs      = isend[4];
    1438:   } else if (flag == MAT_GLOBAL_MAX) {
    1439:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

    1441:     info->nz_used      = irecv[0];
    1442:     info->nz_allocated = irecv[1];
    1443:     info->nz_unneeded  = irecv[2];
    1444:     info->memory       = irecv[3];
    1445:     info->mallocs      = irecv[4];
    1446:   } else if (flag == MAT_GLOBAL_SUM) {
    1447:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

    1449:     info->nz_used      = irecv[0];
    1450:     info->nz_allocated = irecv[1];
    1451:     info->nz_unneeded  = irecv[2];
    1452:     info->memory       = irecv[3];
    1453:     info->mallocs      = irecv[4];
    1454:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
    1455:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
    1456:   info->fill_ratio_needed = 0;
    1457:   info->factor_mallocs    = 0;
    1458:   return(0);
    1459: }

    1463: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
    1464: {
    1465:   Mat_MPISBAIJ   *a  = (Mat_MPISBAIJ*)A->data;
    1466:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

    1470:   switch (op) {
    1471:   case MAT_NEW_NONZERO_LOCATIONS:
    1472:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
    1473:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
    1474:   case MAT_KEEP_NONZERO_PATTERN:
    1475:   case MAT_NEW_NONZERO_LOCATION_ERR:
    1476:     MatCheckPreallocated(A,1);
    1477:     MatSetOption(a->A,op,flg);
    1478:     MatSetOption(a->B,op,flg);
    1479:     break;
    1480:   case MAT_ROW_ORIENTED:
    1481:     MatCheckPreallocated(A,1);
    1482:     a->roworiented = flg;

    1484:     MatSetOption(a->A,op,flg);
    1485:     MatSetOption(a->B,op,flg);
    1486:     break;
    1487:   case MAT_NEW_DIAGONALS:
    1488:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
    1489:     break;
    1490:   case MAT_IGNORE_OFF_PROC_ENTRIES:
    1491:     a->donotstash = flg;
    1492:     break;
    1493:   case MAT_USE_HASH_TABLE:
    1494:     a->ht_flag = flg;
    1495:     break;
    1496:   case MAT_HERMITIAN:
    1497:     MatCheckPreallocated(A,1);
    1498:     if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first");
    1499:     MatSetOption(a->A,op,flg);

    1501:     A->ops->mult = MatMult_MPISBAIJ_Hermitian;
    1502:     break;
    1503:   case MAT_SPD:
    1504:     A->spd_set = PETSC_TRUE;
    1505:     A->spd     = flg;
    1506:     if (flg) {
    1507:       A->symmetric                  = PETSC_TRUE;
    1508:       A->structurally_symmetric     = PETSC_TRUE;
    1509:       A->symmetric_set              = PETSC_TRUE;
    1510:       A->structurally_symmetric_set = PETSC_TRUE;
    1511:     }
    1512:     break;
    1513:   case MAT_SYMMETRIC:
    1514:     MatCheckPreallocated(A,1);
    1515:     MatSetOption(a->A,op,flg);
    1516:     break;
    1517:   case MAT_STRUCTURALLY_SYMMETRIC:
    1518:     MatCheckPreallocated(A,1);
    1519:     MatSetOption(a->A,op,flg);
    1520:     break;
    1521:   case MAT_SYMMETRY_ETERNAL:
    1522:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric");
    1523:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
    1524:     break;
    1525:   case MAT_IGNORE_LOWER_TRIANGULAR:
    1526:     aA->ignore_ltriangular = flg;
    1527:     break;
    1528:   case MAT_ERROR_LOWER_TRIANGULAR:
    1529:     aA->ignore_ltriangular = flg;
    1530:     break;
    1531:   case MAT_GETROW_UPPERTRIANGULAR:
    1532:     aA->getrow_utriangular = flg;
    1533:     break;
    1534:   default:
    1535:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
    1536:   }
    1537:   return(0);
    1538: }

    1542: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
    1543: {

    1547:   if (MAT_INITIAL_MATRIX || *B != A) {
    1548:     MatDuplicate(A,MAT_COPY_VALUES,B);
    1549:   }
    1550:   return(0);
    1551: }

    1555: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
    1556: {
    1557:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    1558:   Mat            a     = baij->A, b=baij->B;
    1560:   PetscInt       nv,m,n;
    1561:   PetscBool      flg;

    1564:   if (ll != rr) {
    1565:     VecEqual(ll,rr,&flg);
    1566:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n");
    1567:   }
    1568:   if (!ll) return(0);

    1570:   MatGetLocalSize(mat,&m,&n);
    1571:   if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n);

    1573:   VecGetLocalSize(rr,&nv);
    1574:   if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size");

    1576:   VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);

    1578:   /* left diagonalscale the off-diagonal part */
    1579:   (*b->ops->diagonalscale)(b,ll,NULL);

    1581:   /* scale the diagonal part */
    1582:   (*a->ops->diagonalscale)(a,ll,rr);

    1584:   /* right diagonalscale the off-diagonal part */
    1585:   VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1586:   (*b->ops->diagonalscale)(b,NULL,baij->lvec);
    1587:   return(0);
    1588: }

    1592: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
    1593: {
    1594:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1598:   MatSetUnfactored(a->A);
    1599:   return(0);
    1600: }

    1602: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);

    1606: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool  *flag)
    1607: {
    1608:   Mat_MPISBAIJ   *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
    1609:   Mat            a,b,c,d;
    1610:   PetscBool      flg;

    1614:   a = matA->A; b = matA->B;
    1615:   c = matB->A; d = matB->B;

    1617:   MatEqual(a,c,&flg);
    1618:   if (flg) {
    1619:     MatEqual(b,d,&flg);
    1620:   }
    1621:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
    1622:   return(0);
    1623: }

    1627: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
    1628: {
    1630:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
    1631:   Mat_MPISBAIJ   *b = (Mat_MPISBAIJ*)B->data;

    1634:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
    1635:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
    1636:     MatGetRowUpperTriangular(A);
    1637:     MatCopy_Basic(A,B,str);
    1638:     MatRestoreRowUpperTriangular(A);
    1639:   } else {
    1640:     MatCopy(a->A,b->A,str);
    1641:     MatCopy(a->B,b->B,str);
    1642:   }
    1643:   return(0);
    1644: }

    1648: PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
    1649: {

    1653:   MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
    1654:   return(0);
    1655: }

    1659: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
    1660: {
    1662:   Mat_MPISBAIJ   *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
    1663:   PetscBLASInt   bnz,one=1;
    1664:   Mat_SeqSBAIJ   *xa,*ya;
    1665:   Mat_SeqBAIJ    *xb,*yb;

    1668:   if (str == SAME_NONZERO_PATTERN) {
    1669:     PetscScalar alpha = a;
    1670:     xa   = (Mat_SeqSBAIJ*)xx->A->data;
    1671:     ya   = (Mat_SeqSBAIJ*)yy->A->data;
    1672:     PetscBLASIntCast(xa->nz,&bnz);
    1673:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
    1674:     xb   = (Mat_SeqBAIJ*)xx->B->data;
    1675:     yb   = (Mat_SeqBAIJ*)yy->B->data;
    1676:     PetscBLASIntCast(xb->nz,&bnz);
    1677:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
    1678:     PetscObjectStateIncrease((PetscObject)Y);
    1679:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
    1680:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
    1681:     MatAXPY_Basic(Y,a,X,str);
    1682:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
    1683:   } else {
    1684:     Mat      B;
    1685:     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
    1686:     if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
    1687:     MatGetRowUpperTriangular(X);
    1688:     MatGetRowUpperTriangular(Y);
    1689:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
    1690:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
    1691:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
    1692:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
    1693:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
    1694:     MatSetBlockSizesFromMats(B,Y,Y);
    1695:     MatSetType(B,MATMPISBAIJ);
    1696:     MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);
    1697:     MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
    1698:     MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
    1699:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
    1700:     MatHeaderReplace(Y,&B);
    1701:     PetscFree(nnz_d);
    1702:     PetscFree(nnz_o);
    1703:     MatRestoreRowUpperTriangular(X);
    1704:     MatRestoreRowUpperTriangular(Y);
    1705:   }
    1706:   return(0);
    1707: }

    1711: PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
    1712: {
    1714:   PetscInt       i;
    1715:   PetscBool      flg;

    1718:   MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B); /* B[] are sbaij matrices */
    1719:   for (i=0; i<n; i++) {
    1720:     ISEqual(irow[i],icol[i],&flg);
    1721:     if (!flg) {
    1722:       MatSeqSBAIJZeroOps_Private(*B[i]);
    1723:     }
    1724:   }
    1725:   return(0);
    1726: }

    1730: PetscErrorCode MatShift_MPISBAIJ(Mat Y,PetscScalar a)
    1731: {
    1733:   Mat_MPISBAIJ    *maij = (Mat_MPISBAIJ*)Y->data;
    1734:   Mat_SeqSBAIJ    *aij = (Mat_SeqSBAIJ*)maij->A->data;

    1737:   if (!Y->preallocated) {
    1738:     MatMPISBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
    1739:   } else if (!aij->nz) {
    1740:     PetscInt nonew = aij->nonew;
    1741:     MatSeqSBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
    1742:     aij->nonew = nonew;
    1743:   }
    1744:   MatShift_Basic(Y,a);
    1745:   return(0);
    1746: }

    1750: PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
    1751: {
    1752:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1756:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
    1757:   MatMissingDiagonal(a->A,missing,d);
    1758:   if (d) {
    1759:     PetscInt rstart;
    1760:     MatGetOwnershipRange(A,&rstart,NULL);
    1761:     *d += rstart/A->rmap->bs;

    1763:   }
    1764:   return(0);
    1765: }

    1768: /* -------------------------------------------------------------------*/
    1769: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
    1770:                                        MatGetRow_MPISBAIJ,
    1771:                                        MatRestoreRow_MPISBAIJ,
    1772:                                        MatMult_MPISBAIJ,
    1773:                                /*  4*/ MatMultAdd_MPISBAIJ,
    1774:                                        MatMult_MPISBAIJ,       /* transpose versions are same as non-transpose */
    1775:                                        MatMultAdd_MPISBAIJ,
    1776:                                        0,
    1777:                                        0,
    1778:                                        0,
    1779:                                /* 10*/ 0,
    1780:                                        0,
    1781:                                        0,
    1782:                                        MatSOR_MPISBAIJ,
    1783:                                        MatTranspose_MPISBAIJ,
    1784:                                /* 15*/ MatGetInfo_MPISBAIJ,
    1785:                                        MatEqual_MPISBAIJ,
    1786:                                        MatGetDiagonal_MPISBAIJ,
    1787:                                        MatDiagonalScale_MPISBAIJ,
    1788:                                        MatNorm_MPISBAIJ,
    1789:                                /* 20*/ MatAssemblyBegin_MPISBAIJ,
    1790:                                        MatAssemblyEnd_MPISBAIJ,
    1791:                                        MatSetOption_MPISBAIJ,
    1792:                                        MatZeroEntries_MPISBAIJ,
    1793:                                /* 24*/ 0,
    1794:                                        0,
    1795:                                        0,
    1796:                                        0,
    1797:                                        0,
    1798:                                /* 29*/ MatSetUp_MPISBAIJ,
    1799:                                        0,
    1800:                                        0,
    1801:                                        0,
    1802:                                        0,
    1803:                                /* 34*/ MatDuplicate_MPISBAIJ,
    1804:                                        0,
    1805:                                        0,
    1806:                                        0,
    1807:                                        0,
    1808:                                /* 39*/ MatAXPY_MPISBAIJ,
    1809:                                        MatGetSubMatrices_MPISBAIJ,
    1810:                                        MatIncreaseOverlap_MPISBAIJ,
    1811:                                        MatGetValues_MPISBAIJ,
    1812:                                        MatCopy_MPISBAIJ,
    1813:                                /* 44*/ 0,
    1814:                                        MatScale_MPISBAIJ,
    1815:                                        MatShift_MPISBAIJ,
    1816:                                        0,
    1817:                                        0,
    1818:                                /* 49*/ 0,
    1819:                                        0,
    1820:                                        0,
    1821:                                        0,
    1822:                                        0,
    1823:                                /* 54*/ 0,
    1824:                                        0,
    1825:                                        MatSetUnfactored_MPISBAIJ,
    1826:                                        0,
    1827:                                        MatSetValuesBlocked_MPISBAIJ,
    1828:                                /* 59*/ MatGetSubMatrix_MPISBAIJ,
    1829:                                        0,
    1830:                                        0,
    1831:                                        0,
    1832:                                        0,
    1833:                                /* 64*/ 0,
    1834:                                        0,
    1835:                                        0,
    1836:                                        0,
    1837:                                        0,
    1838:                                /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
    1839:                                        0,
    1840:                                        0,
    1841:                                        0,
    1842:                                        0,
    1843:                                /* 74*/ 0,
    1844:                                        0,
    1845:                                        0,
    1846:                                        0,
    1847:                                        0,
    1848:                                /* 79*/ 0,
    1849:                                        0,
    1850:                                        0,
    1851:                                        0,
    1852:                                        MatLoad_MPISBAIJ,
    1853:                                /* 84*/ 0,
    1854:                                        0,
    1855:                                        0,
    1856:                                        0,
    1857:                                        0,
    1858:                                /* 89*/ 0,
    1859:                                        0,
    1860:                                        0,
    1861:                                        0,
    1862:                                        0,
    1863:                                /* 94*/ 0,
    1864:                                        0,
    1865:                                        0,
    1866:                                        0,
    1867:                                        0,
    1868:                                /* 99*/ 0,
    1869:                                        0,
    1870:                                        0,
    1871:                                        0,
    1872:                                        0,
    1873:                                /*104*/ 0,
    1874:                                        MatRealPart_MPISBAIJ,
    1875:                                        MatImaginaryPart_MPISBAIJ,
    1876:                                        MatGetRowUpperTriangular_MPISBAIJ,
    1877:                                        MatRestoreRowUpperTriangular_MPISBAIJ,
    1878:                                /*109*/ 0,
    1879:                                        0,
    1880:                                        0,
    1881:                                        0,
    1882:                                        MatMissingDiagonal_MPISBAIJ,
    1883:                                /*114*/ 0,
    1884:                                        0,
    1885:                                        0,
    1886:                                        0,
    1887:                                        0,
    1888:                                /*119*/ 0,
    1889:                                        0,
    1890:                                        0,
    1891:                                        0,
    1892:                                        0,
    1893:                                /*124*/ 0,
    1894:                                        0,
    1895:                                        0,
    1896:                                        0,
    1897:                                        0,
    1898:                                /*129*/ 0,
    1899:                                        0,
    1900:                                        0,
    1901:                                        0,
    1902:                                        0,
    1903:                                /*134*/ 0,
    1904:                                        0,
    1905:                                        0,
    1906:                                        0,
    1907:                                        0,
    1908:                                /*139*/ 0,
    1909:                                        0,
    1910:                                        0,
    1911:                                        0,
    1912:                                        0,
    1913:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPISBAIJ
    1914: };

    1918: PetscErrorCode  MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
    1919: {
    1921:   *a = ((Mat_MPISBAIJ*)A->data)->A;
    1922:   return(0);
    1923: }

    1927: PetscErrorCode  MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
    1928: {
    1929:   Mat_MPISBAIJ   *b;
    1931:   PetscInt       i,mbs,Mbs;

    1934:   MatSetBlockSize(B,PetscAbs(bs));
    1935:   PetscLayoutSetUp(B->rmap);
    1936:   PetscLayoutSetUp(B->cmap);
    1937:   PetscLayoutGetBlockSize(B->rmap,&bs);

    1939:   b   = (Mat_MPISBAIJ*)B->data;
    1940:   mbs = B->rmap->n/bs;
    1941:   Mbs = B->rmap->N/bs;
    1942:   if (mbs*bs != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap->N,bs);

    1944:   B->rmap->bs = bs;
    1945:   b->bs2      = bs*bs;
    1946:   b->mbs      = mbs;
    1947:   b->Mbs      = Mbs;
    1948:   b->nbs      = B->cmap->n/bs;
    1949:   b->Nbs      = B->cmap->N/bs;

    1951:   for (i=0; i<=b->size; i++) {
    1952:     b->rangebs[i] = B->rmap->range[i]/bs;
    1953:   }
    1954:   b->rstartbs = B->rmap->rstart/bs;
    1955:   b->rendbs   = B->rmap->rend/bs;

    1957:   b->cstartbs = B->cmap->rstart/bs;
    1958:   b->cendbs   = B->cmap->rend/bs;

    1960:   if (!B->preallocated) {
    1961:     MatCreate(PETSC_COMM_SELF,&b->A);
    1962:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
    1963:     MatSetType(b->A,MATSEQSBAIJ);
    1964:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
    1965:     MatCreate(PETSC_COMM_SELF,&b->B);
    1966:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
    1967:     MatSetType(b->B,MATSEQBAIJ);
    1968:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
    1969:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
    1970:   }

    1972:   MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
    1973:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);

    1975:   B->preallocated = PETSC_TRUE;
    1976:   return(0);
    1977: }

    1981: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
    1982: {
    1983:   PetscInt       m,rstart,cstart,cend;
    1984:   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
    1985:   const PetscInt *JJ    =0;
    1986:   PetscScalar    *values=0;

    1990:   if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
    1991:   PetscLayoutSetBlockSize(B->rmap,bs);
    1992:   PetscLayoutSetBlockSize(B->cmap,bs);
    1993:   PetscLayoutSetUp(B->rmap);
    1994:   PetscLayoutSetUp(B->cmap);
    1995:   PetscLayoutGetBlockSize(B->rmap,&bs);
    1996:   m      = B->rmap->n/bs;
    1997:   rstart = B->rmap->rstart/bs;
    1998:   cstart = B->cmap->rstart/bs;
    1999:   cend   = B->cmap->rend/bs;

    2001:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
    2002:   PetscMalloc2(m,&d_nnz,m,&o_nnz);
    2003:   for (i=0; i<m; i++) {
    2004:     nz = ii[i+1] - ii[i];
    2005:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
    2006:     nz_max = PetscMax(nz_max,nz);
    2007:     JJ     = jj + ii[i];
    2008:     for (j=0; j<nz; j++) {
    2009:       if (*JJ >= cstart) break;
    2010:       JJ++;
    2011:     }
    2012:     d = 0;
    2013:     for (; j<nz; j++) {
    2014:       if (*JJ++ >= cend) break;
    2015:       d++;
    2016:     }
    2017:     d_nnz[i] = d;
    2018:     o_nnz[i] = nz - d;
    2019:   }
    2020:   MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
    2021:   PetscFree2(d_nnz,o_nnz);

    2023:   values = (PetscScalar*)V;
    2024:   if (!values) {
    2025:     PetscMalloc1(bs*bs*nz_max,&values);
    2026:     PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));
    2027:   }
    2028:   for (i=0; i<m; i++) {
    2029:     PetscInt          row    = i + rstart;
    2030:     PetscInt          ncols  = ii[i+1] - ii[i];
    2031:     const PetscInt    *icols = jj + ii[i];
    2032:     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
    2033:     MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
    2034:   }

    2036:   if (!V) { PetscFree(values); }
    2037:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    2038:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    2039:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    2040:   return(0);
    2041: }

    2043: /*MC
    2044:    MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
    2045:    based on block compressed sparse row format.  Only the upper triangular portion of the "diagonal" portion of
    2046:    the matrix is stored.

    2048:   For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
    2049:   can call MatSetOption(Mat, MAT_HERMITIAN);

    2051:    Options Database Keys:
    2052: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()

    2054:   Level: beginner

    2056: .seealso: MatCreateMPISBAIJ
    2057: M*/

    2059: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*);

    2063: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
    2064: {
    2065:   Mat_MPISBAIJ   *b;
    2067:   PetscBool      flg = PETSC_FALSE;

    2070:   PetscNewLog(B,&b);
    2071:   B->data = (void*)b;
    2072:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

    2074:   B->ops->destroy = MatDestroy_MPISBAIJ;
    2075:   B->ops->view    = MatView_MPISBAIJ;
    2076:   B->assembled    = PETSC_FALSE;
    2077:   B->insertmode   = NOT_SET_VALUES;

    2079:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
    2080:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

    2082:   /* build local table of row and column ownerships */
    2083:   PetscMalloc1(b->size+2,&b->rangebs);

    2085:   /* build cache for off array entries formed */
    2086:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

    2088:   b->donotstash  = PETSC_FALSE;
    2089:   b->colmap      = NULL;
    2090:   b->garray      = NULL;
    2091:   b->roworiented = PETSC_TRUE;

    2093:   /* stuff used in block assembly */
    2094:   b->barray = 0;

    2096:   /* stuff used for matrix vector multiply */
    2097:   b->lvec    = 0;
    2098:   b->Mvctx   = 0;
    2099:   b->slvec0  = 0;
    2100:   b->slvec0b = 0;
    2101:   b->slvec1  = 0;
    2102:   b->slvec1a = 0;
    2103:   b->slvec1b = 0;
    2104:   b->sMvctx  = 0;

    2106:   /* stuff for MatGetRow() */
    2107:   b->rowindices   = 0;
    2108:   b->rowvalues    = 0;
    2109:   b->getrowactive = PETSC_FALSE;

    2111:   /* hash table stuff */
    2112:   b->ht           = 0;
    2113:   b->hd           = 0;
    2114:   b->ht_size      = 0;
    2115:   b->ht_flag      = PETSC_FALSE;
    2116:   b->ht_fact      = 0;
    2117:   b->ht_total_ct  = 0;
    2118:   b->ht_insert_ct = 0;

    2120:   /* stuff for MatGetSubMatrices_MPIBAIJ_local() */
    2121:   b->ijonly = PETSC_FALSE;

    2123:   b->in_loc = 0;
    2124:   b->v_loc  = 0;
    2125:   b->n_loc  = 0;

    2127:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);
    2128:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);
    2129:   PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPISBAIJ);
    2130:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);
    2131:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
    2132:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpisbstrm_C",MatConvert_MPISBAIJ_MPISBSTRM);
    2133: #if defined(PETSC_HAVE_ELEMENTAL)
    2134:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_elemental_C",MatConvert_MPISBAIJ_Elemental);
    2135: #endif

    2137:   B->symmetric                  = PETSC_TRUE;
    2138:   B->structurally_symmetric     = PETSC_TRUE;
    2139:   B->symmetric_set              = PETSC_TRUE;
    2140:   B->structurally_symmetric_set = PETSC_TRUE;

    2142:   PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
    2143:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");
    2144:   PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);
    2145:   if (flg) {
    2146:     PetscReal fact = 1.39;
    2147:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
    2148:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
    2149:     if (fact <= 1.0) fact = 1.39;
    2150:     MatMPIBAIJSetHashTableFactor(B,fact);
    2151:     PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
    2152:   }
    2153:   PetscOptionsEnd();
    2154:   return(0);
    2155: }

    2157: /*MC
    2158:    MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.

    2160:    This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
    2161:    and MATMPISBAIJ otherwise.

    2163:    Options Database Keys:
    2164: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()

    2166:   Level: beginner

    2168: .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ
    2169: M*/

    2173: /*@C
    2174:    MatMPISBAIJSetPreallocation - For good matrix assembly performance
    2175:    the user should preallocate the matrix storage by setting the parameters
    2176:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    2177:    performance can be increased by more than a factor of 50.

    2179:    Collective on Mat

    2181:    Input Parameters:
    2182: +  B - the matrix
    2183: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    2184:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    2185: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
    2186:            submatrix  (same for all local rows)
    2187: .  d_nnz - array containing the number of block nonzeros in the various block rows
    2188:            in the upper triangular and diagonal part of the in diagonal portion of the local
    2189:            (possibly different for each block row) or NULL.  If you plan to factor the matrix you must leave room
    2190:            for the diagonal entry and set a value even if it is zero.
    2191: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
    2192:            submatrix (same for all local rows).
    2193: -  o_nnz - array containing the number of nonzeros in the various block rows of the
    2194:            off-diagonal portion of the local submatrix that is right of the diagonal
    2195:            (possibly different for each block row) or NULL.

    2198:    Options Database Keys:
    2199: .   -mat_no_unroll - uses code that does not unroll the loops in the
    2200:                      block calculations (much slower)
    2201: .   -mat_block_size - size of the blocks to use

    2203:    Notes:

    2205:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
    2206:    than it must be used on all processors that share the object for that argument.

    2208:    If the *_nnz parameter is given then the *_nz parameter is ignored

    2210:    Storage Information:
    2211:    For a square global matrix we define each processor's diagonal portion
    2212:    to be its local rows and the corresponding columns (a square submatrix);
    2213:    each processor's off-diagonal portion encompasses the remainder of the
    2214:    local matrix (a rectangular submatrix).

    2216:    The user can specify preallocated storage for the diagonal part of
    2217:    the local submatrix with either d_nz or d_nnz (not both).  Set
    2218:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
    2219:    memory allocation.  Likewise, specify preallocated storage for the
    2220:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

    2222:    You can call MatGetInfo() to get information on how effective the preallocation was;
    2223:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
    2224:    You can also run with the option -info and look for messages with the string
    2225:    malloc in them to see if additional memory allocation was needed.

    2227:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
    2228:    the figure below we depict these three local rows and all columns (0-11).

    2230: .vb
    2231:            0 1 2 3 4 5 6 7 8 9 10 11
    2232:           --------------------------
    2233:    row 3  |. . . d d d o o o o  o  o
    2234:    row 4  |. . . d d d o o o o  o  o
    2235:    row 5  |. . . d d d o o o o  o  o
    2236:           --------------------------
    2237: .ve

    2239:    Thus, any entries in the d locations are stored in the d (diagonal)
    2240:    submatrix, and any entries in the o locations are stored in the
    2241:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
    2242:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

    2244:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
    2245:    plus the diagonal part of the d matrix,
    2246:    and o_nz should indicate the number of block nonzeros per row in the o matrix

    2248:    In general, for PDE problems in which most nonzeros are near the diagonal,
    2249:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
    2250:    or you will get TERRIBLE performance; see the users' manual chapter on
    2251:    matrices.

    2253:    Level: intermediate

    2255: .keywords: matrix, block, aij, compressed row, sparse, parallel

    2257: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
    2258: @*/
    2259: PetscErrorCode  MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
    2260: {

    2267:   PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
    2268:   return(0);
    2269: }

    2273: /*@C
    2274:    MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
    2275:    (block compressed row).  For good matrix assembly performance
    2276:    the user should preallocate the matrix storage by setting the parameters
    2277:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    2278:    performance can be increased by more than a factor of 50.

    2280:    Collective on MPI_Comm

    2282:    Input Parameters:
    2283: +  comm - MPI communicator
    2284: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    2285:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    2286: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
    2287:            This value should be the same as the local size used in creating the
    2288:            y vector for the matrix-vector product y = Ax.
    2289: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
    2290:            This value should be the same as the local size used in creating the
    2291:            x vector for the matrix-vector product y = Ax.
    2292: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    2293: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    2294: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
    2295:            submatrix  (same for all local rows)
    2296: .  d_nnz - array containing the number of block nonzeros in the various block rows
    2297:            in the upper triangular portion of the in diagonal portion of the local
    2298:            (possibly different for each block block row) or NULL.
    2299:            If you plan to factor the matrix you must leave room for the diagonal entry and
    2300:            set its value even if it is zero.
    2301: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
    2302:            submatrix (same for all local rows).
    2303: -  o_nnz - array containing the number of nonzeros in the various block rows of the
    2304:            off-diagonal portion of the local submatrix (possibly different for
    2305:            each block row) or NULL.

    2307:    Output Parameter:
    2308: .  A - the matrix

    2310:    Options Database Keys:
    2311: .   -mat_no_unroll - uses code that does not unroll the loops in the
    2312:                      block calculations (much slower)
    2313: .   -mat_block_size - size of the blocks to use
    2314: .   -mat_mpi - use the parallel matrix data structures even on one processor
    2315:                (defaults to using SeqBAIJ format on one processor)

    2317:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
    2318:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
    2319:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

    2321:    Notes:
    2322:    The number of rows and columns must be divisible by blocksize.
    2323:    This matrix type does not support complex Hermitian operation.

    2325:    The user MUST specify either the local or global matrix dimensions
    2326:    (possibly both).

    2328:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
    2329:    than it must be used on all processors that share the object for that argument.

    2331:    If the *_nnz parameter is given then the *_nz parameter is ignored

    2333:    Storage Information:
    2334:    For a square global matrix we define each processor's diagonal portion
    2335:    to be its local rows and the corresponding columns (a square submatrix);
    2336:    each processor's off-diagonal portion encompasses the remainder of the
    2337:    local matrix (a rectangular submatrix).

    2339:    The user can specify preallocated storage for the diagonal part of
    2340:    the local submatrix with either d_nz or d_nnz (not both).  Set
    2341:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
    2342:    memory allocation.  Likewise, specify preallocated storage for the
    2343:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

    2345:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
    2346:    the figure below we depict these three local rows and all columns (0-11).

    2348: .vb
    2349:            0 1 2 3 4 5 6 7 8 9 10 11
    2350:           --------------------------
    2351:    row 3  |. . . d d d o o o o  o  o
    2352:    row 4  |. . . d d d o o o o  o  o
    2353:    row 5  |. . . d d d o o o o  o  o
    2354:           --------------------------
    2355: .ve

    2357:    Thus, any entries in the d locations are stored in the d (diagonal)
    2358:    submatrix, and any entries in the o locations are stored in the
    2359:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
    2360:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

    2362:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
    2363:    plus the diagonal part of the d matrix,
    2364:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
    2365:    In general, for PDE problems in which most nonzeros are near the diagonal,
    2366:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
    2367:    or you will get TERRIBLE performance; see the users' manual chapter on
    2368:    matrices.

    2370:    Level: intermediate

    2372: .keywords: matrix, block, aij, compressed row, sparse, parallel

    2374: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
    2375: @*/

    2377: PetscErrorCode  MatCreateSBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A)
    2378: {
    2380:   PetscMPIInt    size;

    2383:   MatCreate(comm,A);
    2384:   MatSetSizes(*A,m,n,M,N);
    2385:   MPI_Comm_size(comm,&size);
    2386:   if (size > 1) {
    2387:     MatSetType(*A,MATMPISBAIJ);
    2388:     MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
    2389:   } else {
    2390:     MatSetType(*A,MATSEQSBAIJ);
    2391:     MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
    2392:   }
    2393:   return(0);
    2394: }

    2399: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
    2400: {
    2401:   Mat            mat;
    2402:   Mat_MPISBAIJ   *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
    2404:   PetscInt       len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
    2405:   PetscScalar    *array;

    2408:   *newmat = 0;

    2410:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
    2411:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
    2412:   MatSetType(mat,((PetscObject)matin)->type_name);
    2413:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
    2414:   PetscLayoutReference(matin->rmap,&mat->rmap);
    2415:   PetscLayoutReference(matin->cmap,&mat->cmap);

    2417:   mat->factortype   = matin->factortype;
    2418:   mat->preallocated = PETSC_TRUE;
    2419:   mat->assembled    = PETSC_TRUE;
    2420:   mat->insertmode   = NOT_SET_VALUES;

    2422:   a      = (Mat_MPISBAIJ*)mat->data;
    2423:   a->bs2 = oldmat->bs2;
    2424:   a->mbs = oldmat->mbs;
    2425:   a->nbs = oldmat->nbs;
    2426:   a->Mbs = oldmat->Mbs;
    2427:   a->Nbs = oldmat->Nbs;

    2430:   a->size         = oldmat->size;
    2431:   a->rank         = oldmat->rank;
    2432:   a->donotstash   = oldmat->donotstash;
    2433:   a->roworiented  = oldmat->roworiented;
    2434:   a->rowindices   = 0;
    2435:   a->rowvalues    = 0;
    2436:   a->getrowactive = PETSC_FALSE;
    2437:   a->barray       = 0;
    2438:   a->rstartbs     = oldmat->rstartbs;
    2439:   a->rendbs       = oldmat->rendbs;
    2440:   a->cstartbs     = oldmat->cstartbs;
    2441:   a->cendbs       = oldmat->cendbs;

    2443:   /* hash table stuff */
    2444:   a->ht           = 0;
    2445:   a->hd           = 0;
    2446:   a->ht_size      = 0;
    2447:   a->ht_flag      = oldmat->ht_flag;
    2448:   a->ht_fact      = oldmat->ht_fact;
    2449:   a->ht_total_ct  = 0;
    2450:   a->ht_insert_ct = 0;

    2452:   PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));
    2453:   if (oldmat->colmap) {
    2454: #if defined(PETSC_USE_CTABLE)
    2455:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
    2456: #else
    2457:     PetscMalloc1(a->Nbs,&a->colmap);
    2458:     PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
    2459:     PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));
    2460: #endif
    2461:   } else a->colmap = 0;

    2463:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
    2464:     PetscMalloc1(len,&a->garray);
    2465:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
    2466:     PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));
    2467:   } else a->garray = 0;

    2469:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
    2470:   VecDuplicate(oldmat->lvec,&a->lvec);
    2471:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
    2472:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
    2473:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

    2475:   VecDuplicate(oldmat->slvec0,&a->slvec0);
    2476:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
    2477:   VecDuplicate(oldmat->slvec1,&a->slvec1);
    2478:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);

    2480:   VecGetLocalSize(a->slvec1,&nt);
    2481:   VecGetArray(a->slvec1,&array);
    2482:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);
    2483:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
    2484:   VecRestoreArray(a->slvec1,&array);
    2485:   VecGetArray(a->slvec0,&array);
    2486:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
    2487:   VecRestoreArray(a->slvec0,&array);
    2488:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
    2489:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
    2490:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);
    2491:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);
    2492:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);

    2494:   /*  VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
    2495:   PetscObjectReference((PetscObject)oldmat->sMvctx);
    2496:   a->sMvctx = oldmat->sMvctx;
    2497:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);

    2499:   MatDuplicate(oldmat->A,cpvalues,&a->A);
    2500:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
    2501:   MatDuplicate(oldmat->B,cpvalues,&a->B);
    2502:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
    2503:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
    2504:   *newmat = mat;
    2505:   return(0);
    2506: }

    2510: PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer)
    2511: {
    2513:   PetscInt       i,nz,j,rstart,rend;
    2514:   PetscScalar    *vals,*buf;
    2515:   MPI_Comm       comm;
    2516:   MPI_Status     status;
    2517:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs;
    2518:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens;
    2519:   PetscInt       *procsnz = 0,jj,*mycols,*ibuf;
    2520:   PetscInt       bs = newmat->rmap->bs,Mbs,mbs,extra_rows;
    2521:   PetscInt       *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount;
    2522:   PetscInt       dcount,kmax,k,nzcount,tmp;
    2523:   int            fd;

    2526:   /* force binary viewer to load .info file if it has not yet done so */
    2527:   PetscViewerSetUp(viewer);
    2528:   PetscObjectGetComm((PetscObject)viewer,&comm);
    2529:   PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");
    2530:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
    2531:   PetscOptionsEnd();
    2532:   if (bs < 0) bs = 1;

    2534:   MPI_Comm_size(comm,&size);
    2535:   MPI_Comm_rank(comm,&rank);
    2536:   PetscViewerBinaryGetDescriptor(viewer,&fd);
    2537:   if (!rank) {
    2538:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
    2539:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
    2540:     if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ");
    2541:   }

    2543:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
    2544:   M    = header[1];
    2545:   N    = header[2];

    2547:   /* If global sizes are set, check if they are consistent with that given in the file */
    2548:   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);
    2549:   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);

    2551:   if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");

    2553:   /*
    2554:      This code adds extra rows to make sure the number of rows is
    2555:      divisible by the blocksize
    2556:   */
    2557:   Mbs        = M/bs;
    2558:   extra_rows = bs - M + bs*(Mbs);
    2559:   if (extra_rows == bs) extra_rows = 0;
    2560:   else                  Mbs++;
    2561:   if (extra_rows &&!rank) {
    2562:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
    2563:   }

    2565:   /* determine ownership of all rows */
    2566:   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
    2567:     mbs = Mbs/size + ((Mbs % size) > rank);
    2568:     m   = mbs*bs;
    2569:   } else { /* User Set */
    2570:     m   = newmat->rmap->n;
    2571:     mbs = m/bs;
    2572:   }
    2573:   PetscMalloc2(size+1,&rowners,size+1,&browners);
    2574:   PetscMPIIntCast(mbs,&mmbs);
    2575:   MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);
    2576:   rowners[0] = 0;
    2577:   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
    2578:   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
    2579:   rstart = rowners[rank];
    2580:   rend   = rowners[rank+1];

    2582:   /* distribute row lengths to all processors */
    2583:   PetscMalloc1((rend-rstart)*bs,&locrowlens);
    2584:   if (!rank) {
    2585:     PetscMalloc1(M+extra_rows,&rowlengths);
    2586:     PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
    2587:     for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
    2588:     PetscMalloc1(size,&sndcounts);
    2589:     for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i];
    2590:     MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
    2591:     PetscFree(sndcounts);
    2592:   } else {
    2593:     MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
    2594:   }

    2596:   if (!rank) {   /* procs[0] */
    2597:     /* calculate the number of nonzeros on each processor */
    2598:     PetscMalloc1(size,&procsnz);
    2599:     PetscMemzero(procsnz,size*sizeof(PetscInt));
    2600:     for (i=0; i<size; i++) {
    2601:       for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) {
    2602:         procsnz[i] += rowlengths[j];
    2603:       }
    2604:     }
    2605:     PetscFree(rowlengths);

    2607:     /* determine max buffer needed and allocate it */
    2608:     maxnz = 0;
    2609:     for (i=0; i<size; i++) {
    2610:       maxnz = PetscMax(maxnz,procsnz[i]);
    2611:     }
    2612:     PetscMalloc1(maxnz,&cols);

    2614:     /* read in my part of the matrix column indices  */
    2615:     nz     = procsnz[0];
    2616:     PetscMalloc1(nz,&ibuf);
    2617:     mycols = ibuf;
    2618:     if (size == 1) nz -= extra_rows;
    2619:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);
    2620:     if (size == 1) {
    2621:       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
    2622:     }

    2624:     /* read in every ones (except the last) and ship off */
    2625:     for (i=1; i<size-1; i++) {
    2626:       nz   = procsnz[i];
    2627:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
    2628:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
    2629:     }
    2630:     /* read in the stuff for the last proc */
    2631:     if (size != 1) {
    2632:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
    2633:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
    2634:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
    2635:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
    2636:     }
    2637:     PetscFree(cols);
    2638:   } else {  /* procs[i], i>0 */
    2639:     /* determine buffer space needed for message */
    2640:     nz = 0;
    2641:     for (i=0; i<m; i++) nz += locrowlens[i];
    2642:     PetscMalloc1(nz,&ibuf);
    2643:     mycols = ibuf;
    2644:     /* receive message of column indices*/
    2645:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
    2646:     MPI_Get_count(&status,MPIU_INT,&maxnz);
    2647:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
    2648:   }

    2650:   /* loop over local rows, determining number of off diagonal entries */
    2651:   PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);
    2652:   PetscMalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);
    2653:   PetscMemzero(mask,Mbs*sizeof(PetscInt));
    2654:   PetscMemzero(masked1,Mbs*sizeof(PetscInt));
    2655:   PetscMemzero(masked2,Mbs*sizeof(PetscInt));
    2656:   rowcount = 0;
    2657:   nzcount  = 0;
    2658:   for (i=0; i<mbs; i++) {
    2659:     dcount  = 0;
    2660:     odcount = 0;
    2661:     for (j=0; j<bs; j++) {
    2662:       kmax = locrowlens[rowcount];
    2663:       for (k=0; k<kmax; k++) {
    2664:         tmp = mycols[nzcount++]/bs; /* block col. index */
    2665:         if (!mask[tmp]) {
    2666:           mask[tmp] = 1;
    2667:           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */
    2668:           else masked1[dcount++] = tmp; /* entry in diag portion */
    2669:         }
    2670:       }
    2671:       rowcount++;
    2672:     }

    2674:     dlens[i]  = dcount;  /* d_nzz[i] */
    2675:     odlens[i] = odcount; /* o_nzz[i] */

    2677:     /* zero out the mask elements we set */
    2678:     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
    2679:     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
    2680:   }
    2681:   MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
    2682:   MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);
    2683:   MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);

    2685:   if (!rank) {
    2686:     PetscMalloc1(maxnz,&buf);
    2687:     /* read in my part of the matrix numerical values  */
    2688:     nz     = procsnz[0];
    2689:     vals   = buf;
    2690:     mycols = ibuf;
    2691:     if (size == 1) nz -= extra_rows;
    2692:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    2693:     if (size == 1) {
    2694:       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
    2695:     }

    2697:     /* insert into matrix */
    2698:     jj = rstart*bs;
    2699:     for (i=0; i<m; i++) {
    2700:       MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
    2701:       mycols += locrowlens[i];
    2702:       vals   += locrowlens[i];
    2703:       jj++;
    2704:     }

    2706:     /* read in other processors (except the last one) and ship out */
    2707:     for (i=1; i<size-1; i++) {
    2708:       nz   = procsnz[i];
    2709:       vals = buf;
    2710:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    2711:       MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
    2712:     }
    2713:     /* the last proc */
    2714:     if (size != 1) {
    2715:       nz   = procsnz[i] - extra_rows;
    2716:       vals = buf;
    2717:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    2718:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
    2719:       MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
    2720:     }
    2721:     PetscFree(procsnz);

    2723:   } else {
    2724:     /* receive numeric values */
    2725:     PetscMalloc1(nz,&buf);

    2727:     /* receive message of values*/
    2728:     vals   = buf;
    2729:     mycols = ibuf;
    2730:     MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);
    2731:     MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
    2732:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");

    2734:     /* insert into matrix */
    2735:     jj = rstart*bs;
    2736:     for (i=0; i<m; i++) {
    2737:       MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
    2738:       mycols += locrowlens[i];
    2739:       vals   += locrowlens[i];
    2740:       jj++;
    2741:     }
    2742:   }

    2744:   PetscFree(locrowlens);
    2745:   PetscFree(buf);
    2746:   PetscFree(ibuf);
    2747:   PetscFree2(rowners,browners);
    2748:   PetscFree2(dlens,odlens);
    2749:   PetscFree3(mask,masked1,masked2);
    2750:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
    2751:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
    2752:   return(0);
    2753: }

    2757: /*XXXXX@
    2758:    MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

    2760:    Input Parameters:
    2761: .  mat  - the matrix
    2762: .  fact - factor

    2764:    Not Collective on Mat, each process can have a different hash factor

    2766:    Level: advanced

    2768:   Notes:
    2769:    This can also be set by the command line option: -mat_use_hash_table fact

    2771: .keywords: matrix, hashtable, factor, HT

    2773: .seealso: MatSetOption()
    2774: @XXXXX*/

    2779: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
    2780: {
    2781:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
    2782:   Mat_SeqBAIJ    *b = (Mat_SeqBAIJ*)(a->B)->data;
    2783:   PetscReal      atmp;
    2784:   PetscReal      *work,*svalues,*rvalues;
    2786:   PetscInt       i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
    2787:   PetscMPIInt    rank,size;
    2788:   PetscInt       *rowners_bs,dest,count,source;
    2789:   PetscScalar    *va;
    2790:   MatScalar      *ba;
    2791:   MPI_Status     stat;

    2794:   if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov");
    2795:   MatGetRowMaxAbs(a->A,v,NULL);
    2796:   VecGetArray(v,&va);

    2798:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
    2799:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

    2801:   bs  = A->rmap->bs;
    2802:   mbs = a->mbs;
    2803:   Mbs = a->Mbs;
    2804:   ba  = b->a;
    2805:   bi  = b->i;
    2806:   bj  = b->j;

    2808:   /* find ownerships */
    2809:   rowners_bs = A->rmap->range;

    2811:   /* each proc creates an array to be distributed */
    2812:   PetscMalloc1(bs*Mbs,&work);
    2813:   PetscMemzero(work,bs*Mbs*sizeof(PetscReal));

    2815:   /* row_max for B */
    2816:   if (rank != size-1) {
    2817:     for (i=0; i<mbs; i++) {
    2818:       ncols = bi[1] - bi[0]; bi++;
    2819:       brow  = bs*i;
    2820:       for (j=0; j<ncols; j++) {
    2821:         bcol = bs*(*bj);
    2822:         for (kcol=0; kcol<bs; kcol++) {
    2823:           col  = bcol + kcol;                /* local col index */
    2824:           col += rowners_bs[rank+1];      /* global col index */
    2825:           for (krow=0; krow<bs; krow++) {
    2826:             atmp = PetscAbsScalar(*ba); ba++;
    2827:             row  = brow + krow;   /* local row index */
    2828:             if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
    2829:             if (work[col] < atmp) work[col] = atmp;
    2830:           }
    2831:         }
    2832:         bj++;
    2833:       }
    2834:     }

    2836:     /* send values to its owners */
    2837:     for (dest=rank+1; dest<size; dest++) {
    2838:       svalues = work + rowners_bs[dest];
    2839:       count   = rowners_bs[dest+1]-rowners_bs[dest];
    2840:       MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));
    2841:     }
    2842:   }

    2844:   /* receive values */
    2845:   if (rank) {
    2846:     rvalues = work;
    2847:     count   = rowners_bs[rank+1]-rowners_bs[rank];
    2848:     for (source=0; source<rank; source++) {
    2849:       MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);
    2850:       /* process values */
    2851:       for (i=0; i<count; i++) {
    2852:         if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
    2853:       }
    2854:     }
    2855:   }

    2857:   VecRestoreArray(v,&va);
    2858:   PetscFree(work);
    2859:   return(0);
    2860: }

    2864: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    2865: {
    2866:   Mat_MPISBAIJ      *mat = (Mat_MPISBAIJ*)matin->data;
    2867:   PetscErrorCode    ierr;
    2868:   PetscInt          mbs=mat->mbs,bs=matin->rmap->bs;
    2869:   PetscScalar       *x,*ptr,*from;
    2870:   Vec               bb1;
    2871:   const PetscScalar *b;

    2874:   if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
    2875:   if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

    2877:   if (flag == SOR_APPLY_UPPER) {
    2878:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2879:     return(0);
    2880:   }

    2882:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
    2883:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    2884:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
    2885:       its--;
    2886:     }

    2888:     VecDuplicate(bb,&bb1);
    2889:     while (its--) {

    2891:       /* lower triangular part: slvec0b = - B^T*xx */
    2892:       (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);

    2894:       /* copy xx into slvec0a */
    2895:       VecGetArray(mat->slvec0,&ptr);
    2896:       VecGetArray(xx,&x);
    2897:       PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));
    2898:       VecRestoreArray(mat->slvec0,&ptr);

    2900:       VecScale(mat->slvec0,-1.0);

    2902:       /* copy bb into slvec1a */
    2903:       VecGetArray(mat->slvec1,&ptr);
    2904:       VecGetArrayRead(bb,&b);
    2905:       PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));
    2906:       VecRestoreArray(mat->slvec1,&ptr);

    2908:       /* set slvec1b = 0 */
    2909:       VecSet(mat->slvec1b,0.0);

    2911:       VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
    2912:       VecRestoreArray(xx,&x);
    2913:       VecRestoreArrayRead(bb,&b);
    2914:       VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);

    2916:       /* upper triangular part: bb1 = bb1 - B*x */
    2917:       (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);

    2919:       /* local diagonal sweep */
    2920:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
    2921:     }
    2922:     VecDestroy(&bb1);
    2923:   } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
    2924:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2925:   } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
    2926:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2927:   } else if (flag & SOR_EISENSTAT) {
    2928:     Vec               xx1;
    2929:     PetscBool         hasop;
    2930:     const PetscScalar *diag;
    2931:     PetscScalar       *sl,scale = (omega - 2.0)/omega;
    2932:     PetscInt          i,n;

    2934:     if (!mat->xx1) {
    2935:       VecDuplicate(bb,&mat->xx1);
    2936:       VecDuplicate(bb,&mat->bb1);
    2937:     }
    2938:     xx1 = mat->xx1;
    2939:     bb1 = mat->bb1;

    2941:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

    2943:     if (!mat->diag) {
    2944:       /* this is wrong for same matrix with new nonzero values */
    2945:       MatCreateVecs(matin,&mat->diag,NULL);
    2946:       MatGetDiagonal(matin,mat->diag);
    2947:     }
    2948:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);

    2950:     if (hasop) {
    2951:       MatMultDiagonalBlock(matin,xx,bb1);
    2952:       VecAYPX(mat->slvec1a,scale,bb);
    2953:     } else {
    2954:       /*
    2955:           These two lines are replaced by code that may be a bit faster for a good compiler
    2956:       VecPointwiseMult(mat->slvec1a,mat->diag,xx);
    2957:       VecAYPX(mat->slvec1a,scale,bb);
    2958:       */
    2959:       VecGetArray(mat->slvec1a,&sl);
    2960:       VecGetArrayRead(mat->diag,&diag);
    2961:       VecGetArrayRead(bb,&b);
    2962:       VecGetArray(xx,&x);
    2963:       VecGetLocalSize(xx,&n);
    2964:       if (omega == 1.0) {
    2965:         for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
    2966:         PetscLogFlops(2.0*n);
    2967:       } else {
    2968:         for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
    2969:         PetscLogFlops(3.0*n);
    2970:       }
    2971:       VecRestoreArray(mat->slvec1a,&sl);
    2972:       VecRestoreArrayRead(mat->diag,&diag);
    2973:       VecRestoreArrayRead(bb,&b);
    2974:       VecRestoreArray(xx,&x);
    2975:     }

    2977:     /* multiply off-diagonal portion of matrix */
    2978:     VecSet(mat->slvec1b,0.0);
    2979:     (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
    2980:     VecGetArray(mat->slvec0,&from);
    2981:     VecGetArray(xx,&x);
    2982:     PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
    2983:     VecRestoreArray(mat->slvec0,&from);
    2984:     VecRestoreArray(xx,&x);
    2985:     VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
    2986:     VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
    2987:     (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);

    2989:     /* local sweep */
    2990:     (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
    2991:     VecAXPY(xx,1.0,xx1);
    2992:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
    2993:   return(0);
    2994: }

    2998: PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    2999: {
    3000:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
    3002:   Vec            lvec1,bb1;

    3005:   if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
    3006:   if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

    3008:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
    3009:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    3010:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
    3011:       its--;
    3012:     }

    3014:     VecDuplicate(mat->lvec,&lvec1);
    3015:     VecDuplicate(bb,&bb1);
    3016:     while (its--) {
    3017:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

    3019:       /* lower diagonal part: bb1 = bb - B^T*xx */
    3020:       (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);
    3021:       VecScale(lvec1,-1.0);

    3023:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
    3024:       VecCopy(bb,bb1);
    3025:       VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

    3027:       /* upper diagonal part: bb1 = bb1 - B*x */
    3028:       VecScale(mat->lvec,-1.0);
    3029:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);

    3031:       VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

    3033:       /* diagonal sweep */
    3034:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
    3035:     }
    3036:     VecDestroy(&lvec1);
    3037:     VecDestroy(&bb1);
    3038:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
    3039:   return(0);
    3040: }

    3044: /*@
    3045:      MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
    3046:          CSR format the local rows.

    3048:    Collective on MPI_Comm

    3050:    Input Parameters:
    3051: +  comm - MPI communicator
    3052: .  bs - the block size, only a block size of 1 is supported
    3053: .  m - number of local rows (Cannot be PETSC_DECIDE)
    3054: .  n - This value should be the same as the local size used in creating the
    3055:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
    3056:        calculated if N is given) For square matrices n is almost always m.
    3057: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    3058: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    3059: .   i - row indices
    3060: .   j - column indices
    3061: -   a - matrix values

    3063:    Output Parameter:
    3064: .   mat - the matrix

    3066:    Level: intermediate

    3068:    Notes:
    3069:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
    3070:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
    3071:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

    3073:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

    3075: .keywords: matrix, aij, compressed row, sparse, parallel

    3077: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
    3078:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
    3079: @*/
    3080: PetscErrorCode  MatCreateMPISBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
    3081: {

    3086:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
    3087:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
    3088:   MatCreate(comm,mat);
    3089:   MatSetSizes(*mat,m,n,M,N);
    3090:   MatSetType(*mat,MATMPISBAIJ);
    3091:   MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
    3092:   return(0);
    3093: }

    3098: /*@C
    3099:    MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
    3100:    (the default parallel PETSc format).

    3102:    Collective on MPI_Comm

    3104:    Input Parameters:
    3105: +  B - the matrix
    3106: .  bs - the block size
    3107: .  i - the indices into j for the start of each local row (starts with zero)
    3108: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
    3109: -  v - optional values in the matrix

    3111:    Level: developer

    3113: .keywords: matrix, aij, compressed row, sparse, parallel

    3115: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
    3116: @*/
    3117: PetscErrorCode  MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
    3118: {

    3122:   PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
    3123:   return(0);
    3124: }

    3128: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
    3129: {
    3131:   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
    3132:   PetscInt       *indx;
    3133:   PetscScalar    *values;

    3136:   MatGetSize(inmat,&m,&N);
    3137:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
    3138:     Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)inmat->data;
    3139:     PetscInt       *dnz,*onz,sum,bs,cbs,mbs,Nbs;
    3140:     PetscInt       *bindx,rmax=a->rmax,j;
    3141:
    3142:     MatGetBlockSizes(inmat,&bs,&cbs);
    3143:     mbs = m/bs; Nbs = N/cbs;
    3144:     if (n == PETSC_DECIDE) {
    3145:       PetscSplitOwnership(comm,&n,&Nbs);
    3146:     }
    3147:     /* Check sum(n) = Nbs */
    3148:     MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
    3149:     if (sum != Nbs) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",Nbs);

    3151:     MPI_Scan(&mbs, &rstart,1,MPIU_INT,MPI_SUM,comm);
    3152:     rstart -= mbs;

    3154:     PetscMalloc1(rmax,&bindx);
    3155:     MatPreallocateInitialize(comm,mbs,n,dnz,onz);
    3156:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
    3157:     for (i=0; i<mbs; i++) {
    3158:       MatGetRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
    3159:       nnz = nnz/bs;
    3160:       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
    3161:       MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
    3162:       MatRestoreRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);
    3163:     }
    3164:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
    3165:     PetscFree(bindx);

    3167:     MatCreate(comm,outmat);
    3168:     MatSetSizes(*outmat,m,n*bs,PETSC_DETERMINE,PETSC_DETERMINE);
    3169:     MatSetBlockSizes(*outmat,bs,cbs);
    3170:     MatSetType(*outmat,MATMPISBAIJ);
    3171:     MatMPISBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
    3172:     MatPreallocateFinalize(dnz,onz);
    3173:   }
    3174:
    3175:   /* numeric phase */
    3176:   MatGetBlockSizes(inmat,&bs,&cbs);
    3177:   MatGetOwnershipRange(*outmat,&rstart,NULL);

    3179:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
    3180:   for (i=0; i<m; i++) {
    3181:     MatGetRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
    3182:     Ii   = i + rstart;
    3183:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
    3184:     MatRestoreRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
    3185:   }
    3186:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
    3187:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
    3188:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
    3189:   return(0);
    3190: }