Actual source code: mpisbaij.c

      2: #include <../src/mat/impls/baij/mpi/mpibaij.h>
      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
     10: #if defined(PETSC_HAVE_SCALAPACK)
     11: PETSC_INTERN PetscErrorCode MatConvert_SBAIJ_ScaLAPACK(Mat,MatType,MatReuse,Mat*);
     12: #endif

     14: /* This could be moved to matimpl.h */
     15: static PetscErrorCode MatPreallocateWithMats_Private(Mat B, PetscInt nm, Mat X[], PetscBool symm[], PetscBool fill)
     16: {
     17:   Mat            preallocator;
     18:   PetscInt       r,rstart,rend;
     19:   PetscInt       bs,i,m,n,M,N;
     20:   PetscBool      cong = PETSC_TRUE;

     24:   for (i = 0; i < nm; i++) {
     26:     PetscLayoutCompare(B->rmap,X[i]->rmap,&cong);
     28:   }
     30:   MatGetBlockSize(B,&bs);
     31:   MatGetSize(B,&M,&N);
     32:   MatGetLocalSize(B,&m,&n);
     33:   MatCreate(PetscObjectComm((PetscObject)B),&preallocator);
     34:   MatSetType(preallocator,MATPREALLOCATOR);
     35:   MatSetBlockSize(preallocator,bs);
     36:   MatSetSizes(preallocator,m,n,M,N);
     37:   MatSetUp(preallocator);
     38:   MatGetOwnershipRange(preallocator,&rstart,&rend);
     39:   for (r = rstart; r < rend; ++r) {
     40:     PetscInt          ncols;
     41:     const PetscInt    *row;
     42:     const PetscScalar *vals;

     44:     for (i = 0; i < nm; i++) {
     45:       MatGetRow(X[i],r,&ncols,&row,&vals);
     46:       MatSetValues(preallocator,1,&r,ncols,row,vals,INSERT_VALUES);
     47:       if (symm && symm[i]) {
     48:         MatSetValues(preallocator,ncols,row,1,&r,vals,INSERT_VALUES);
     49:       }
     50:       MatRestoreRow(X[i],r,&ncols,&row,&vals);
     51:     }
     52:   }
     53:   MatAssemblyBegin(preallocator,MAT_FINAL_ASSEMBLY);
     54:   MatAssemblyEnd(preallocator,MAT_FINAL_ASSEMBLY);
     55:   MatPreallocatorPreallocate(preallocator,fill,B);
     56:   MatDestroy(&preallocator);
     57:   return 0;
     58: }

     60: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Basic(Mat A, MatType newtype, MatReuse reuse, Mat *newmat)
     61: {
     62:   Mat            B;
     63:   PetscInt       r;

     65:   if (reuse != MAT_REUSE_MATRIX) {
     66:     PetscBool symm = PETSC_TRUE,isdense;
     67:     PetscInt  bs;

     69:     MatCreate(PetscObjectComm((PetscObject)A),&B);
     70:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
     71:     MatSetType(B,newtype);
     72:     MatGetBlockSize(A,&bs);
     73:     MatSetBlockSize(B,bs);
     74:     PetscLayoutSetUp(B->rmap);
     75:     PetscLayoutSetUp(B->cmap);
     76:     PetscObjectTypeCompareAny((PetscObject)B,&isdense,MATSEQDENSE,MATMPIDENSE,MATSEQDENSECUDA,"");
     77:     if (!isdense) {
     78:       MatGetRowUpperTriangular(A);
     79:       MatPreallocateWithMats_Private(B,1,&A,&symm,PETSC_TRUE);
     80:       MatRestoreRowUpperTriangular(A);
     81:     } else {
     82:       MatSetUp(B);
     83:     }
     84:   } else {
     85:     B    = *newmat;
     86:     MatZeroEntries(B);
     87:   }

     89:   MatGetRowUpperTriangular(A);
     90:   for (r = A->rmap->rstart; r < A->rmap->rend; r++) {
     91:     PetscInt          ncols;
     92:     const PetscInt    *row;
     93:     const PetscScalar *vals;

     95:     MatGetRow(A,r,&ncols,&row,&vals);
     96:     MatSetValues(B,1,&r,ncols,row,vals,INSERT_VALUES);
     97: #if defined(PETSC_USE_COMPLEX)
     98:     if (A->hermitian) {
     99:       PetscInt i;
    100:       for (i = 0; i < ncols; i++) {
    101:         MatSetValue(B,row[i],r,PetscConj(vals[i]),INSERT_VALUES);
    102:       }
    103:     } else {
    104:       MatSetValues(B,ncols,row,1,&r,vals,INSERT_VALUES);
    105:     }
    106: #else
    107:     MatSetValues(B,ncols,row,1,&r,vals,INSERT_VALUES);
    108: #endif
    109:     MatRestoreRow(A,r,&ncols,&row,&vals);
    110:   }
    111:   MatRestoreRowUpperTriangular(A);
    112:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    113:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

    115:   if (reuse == MAT_INPLACE_MATRIX) {
    116:     MatHeaderReplace(A,&B);
    117:   } else {
    118:     *newmat = B;
    119:   }
    120:   return 0;
    121: }

    123: PetscErrorCode  MatStoreValues_MPISBAIJ(Mat mat)
    124: {
    125:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

    127:   MatStoreValues(aij->A);
    128:   MatStoreValues(aij->B);
    129:   return 0;
    130: }

    132: PetscErrorCode  MatRetrieveValues_MPISBAIJ(Mat mat)
    133: {
    134:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

    136:   MatRetrieveValues(aij->A);
    137:   MatRetrieveValues(aij->B);
    138:   return 0;
    139: }

    141: #define  MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,orow,ocol)      \
    142:   { \
    143:     brow = row/bs;  \
    144:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
    145:     rmax = aimax[brow]; nrow = ailen[brow]; \
    146:     bcol = col/bs; \
    147:     ridx = row % bs; cidx = col % bs; \
    148:     low  = 0; high = nrow; \
    149:     while (high-low > 3) { \
    150:       t = (low+high)/2; \
    151:       if (rp[t] > bcol) high = t; \
    152:       else              low  = t; \
    153:     } \
    154:     for (_i=low; _i<high; _i++) { \
    155:       if (rp[_i] > bcol) break; \
    156:       if (rp[_i] == bcol) { \
    157:         bap = ap + bs2*_i + bs*cidx + ridx; \
    158:         if (addv == ADD_VALUES) *bap += value;  \
    159:         else                    *bap  = value;  \
    160:         goto a_noinsert; \
    161:       } \
    162:     } \
    163:     if (a->nonew == 1) goto a_noinsert; \
    165:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
    166:     N = nrow++ - 1;  \
    167:     /* shift up all the later entries in this row */ \
    168:     PetscArraymove(rp+_i+1,rp+_i,N-_i+1); \
    169:     PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1)); \
    170:     PetscArrayzero(ap+bs2*_i,bs2);  \
    171:     rp[_i]                      = bcol;  \
    172:     ap[bs2*_i + bs*cidx + ridx] = value;  \
    173:     A->nonzerostate++;\
    174: a_noinsert:; \
    175:     ailen[brow] = nrow; \
    176:   }

    178: #define  MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,orow,ocol) \
    179:   { \
    180:     brow = row/bs;  \
    181:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
    182:     rmax = bimax[brow]; nrow = bilen[brow]; \
    183:     bcol = col/bs; \
    184:     ridx = row % bs; cidx = col % bs; \
    185:     low  = 0; high = nrow; \
    186:     while (high-low > 3) { \
    187:       t = (low+high)/2; \
    188:       if (rp[t] > bcol) high = t; \
    189:       else              low  = t; \
    190:     } \
    191:     for (_i=low; _i<high; _i++) { \
    192:       if (rp[_i] > bcol) break; \
    193:       if (rp[_i] == bcol) { \
    194:         bap = ap + bs2*_i + bs*cidx + ridx; \
    195:         if (addv == ADD_VALUES) *bap += value;  \
    196:         else                    *bap  = value;  \
    197:         goto b_noinsert; \
    198:       } \
    199:     } \
    200:     if (b->nonew == 1) goto b_noinsert; \
    202:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
    203:     N = nrow++ - 1;  \
    204:     /* shift up all the later entries in this row */ \
    205:     PetscArraymove(rp+_i+1,rp+_i,N-_i+1); \
    206:     PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1)); \
    207:     PetscArrayzero(ap+bs2*_i,bs2); \
    208:     rp[_i]                      = bcol;  \
    209:     ap[bs2*_i + bs*cidx + ridx] = value;  \
    210:     B->nonzerostate++;\
    211: b_noinsert:; \
    212:     bilen[brow] = nrow; \
    213:   }

    215: /* Only add/insert a(i,j) with i<=j (blocks).
    216:    Any a(i,j) with i>j input by user is ingored or generates an error
    217: */
    218: PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
    219: {
    220:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    221:   MatScalar      value;
    222:   PetscBool      roworiented = baij->roworiented;
    223:   PetscInt       i,j,row,col;
    224:   PetscInt       rstart_orig=mat->rmap->rstart;
    225:   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
    226:   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;

    228:   /* Some Variables required in the macro */
    229:   Mat          A     = baij->A;
    230:   Mat_SeqSBAIJ *a    = (Mat_SeqSBAIJ*)(A)->data;
    231:   PetscInt     *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
    232:   MatScalar    *aa   =a->a;

    234:   Mat         B     = baij->B;
    235:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
    236:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
    237:   MatScalar   *ba   =b->a;

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

    243:   /* for stash */
    244:   PetscInt  n_loc, *in_loc = NULL;
    245:   MatScalar *v_loc = NULL;

    247:   if (!baij->donotstash) {
    248:     if (n > baij->n_loc) {
    249:       PetscFree(baij->in_loc);
    250:       PetscFree(baij->v_loc);
    251:       PetscMalloc1(n,&baij->in_loc);
    252:       PetscMalloc1(n,&baij->v_loc);

    254:       baij->n_loc = n;
    255:     }
    256:     in_loc = baij->in_loc;
    257:     v_loc  = baij->v_loc;
    258:   }

    260:   for (i=0; i<m; i++) {
    261:     if (im[i] < 0) continue;
    263:     if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
    264:       row = im[i] - rstart_orig;              /* local row index */
    265:       for (j=0; j<n; j++) {
    266:         if (im[i]/bs > in[j]/bs) {
    267:           if (a->ignore_ltriangular) {
    268:             continue;    /* ignore lower triangular blocks */
    269:           } 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)");
    270:         }
    271:         if (in[j] >= cstart_orig && in[j] < cend_orig) {  /* diag entry (A) */
    272:           col  = in[j] - cstart_orig;         /* local col index */
    273:           brow = row/bs; bcol = col/bs;
    274:           if (brow > bcol) continue;  /* ignore lower triangular blocks of A */
    275:           if (roworiented) value = v[i*n+j];
    276:           else             value = v[i+j*m];
    277:           MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
    278:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
    279:         } else if (in[j] < 0) continue;
    281:         else {  /* off-diag entry (B) */
    282:           if (mat->was_assembled) {
    283:             if (!baij->colmap) {
    284:               MatCreateColmap_MPIBAIJ_Private(mat);
    285:             }
    286: #if defined(PETSC_USE_CTABLE)
    287:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
    288:             col  = col - 1;
    289: #else
    290:             col = baij->colmap[in[j]/bs] - 1;
    291: #endif
    292:             if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
    293:               MatDisAssemble_MPISBAIJ(mat);
    294:               col  =  in[j];
    295:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
    296:               B    = baij->B;
    297:               b    = (Mat_SeqBAIJ*)(B)->data;
    298:               bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
    299:               ba   = b->a;
    300:             } else col += in[j]%bs;
    301:           } else col = in[j];
    302:           if (roworiented) value = v[i*n+j];
    303:           else             value = v[i+j*m];
    304:           MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
    305:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
    306:         }
    307:       }
    308:     } else {  /* off processor entry */
    310:       if (!baij->donotstash) {
    311:         mat->assembled = PETSC_FALSE;
    312:         n_loc          = 0;
    313:         for (j=0; j<n; j++) {
    314:           if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
    315:           in_loc[n_loc] = in[j];
    316:           if (roworiented) {
    317:             v_loc[n_loc] = v[i*n+j];
    318:           } else {
    319:             v_loc[n_loc] = v[j*m+i];
    320:           }
    321:           n_loc++;
    322:         }
    323:         MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
    324:       }
    325:     }
    326:   }
    327:   return 0;
    328: }

    330: static inline PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
    331: {
    332:   Mat_SeqSBAIJ      *a = (Mat_SeqSBAIJ*)A->data;
    333:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
    334:   PetscInt          *imax      =a->imax,*ai=a->i,*ailen=a->ilen;
    335:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
    336:   PetscBool         roworiented=a->roworiented;
    337:   const PetscScalar *value     = v;
    338:   MatScalar         *ap,*aa = a->a,*bap;

    340:   if (col < row) {
    341:     if (a->ignore_ltriangular) return 0; /* ignore lower triangular block */
    342:     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)");
    343:   }
    344:   rp   = aj + ai[row];
    345:   ap   = aa + bs2*ai[row];
    346:   rmax = imax[row];
    347:   nrow = ailen[row];
    348:   value = v;
    349:   low   = 0;
    350:   high  = nrow;

    352:   while (high-low > 7) {
    353:     t = (low+high)/2;
    354:     if (rp[t] > col) high = t;
    355:     else             low  = t;
    356:   }
    357:   for (i=low; i<high; i++) {
    358:     if (rp[i] > col) break;
    359:     if (rp[i] == col) {
    360:       bap = ap +  bs2*i;
    361:       if (roworiented) {
    362:         if (is == ADD_VALUES) {
    363:           for (ii=0; ii<bs; ii++) {
    364:             for (jj=ii; jj<bs2; jj+=bs) {
    365:               bap[jj] += *value++;
    366:             }
    367:           }
    368:         } else {
    369:           for (ii=0; ii<bs; ii++) {
    370:             for (jj=ii; jj<bs2; jj+=bs) {
    371:               bap[jj] = *value++;
    372:             }
    373:           }
    374:         }
    375:       } else {
    376:         if (is == ADD_VALUES) {
    377:           for (ii=0; ii<bs; ii++) {
    378:             for (jj=0; jj<bs; jj++) {
    379:               *bap++ += *value++;
    380:             }
    381:           }
    382:         } else {
    383:           for (ii=0; ii<bs; ii++) {
    384:             for (jj=0; jj<bs; jj++) {
    385:               *bap++  = *value++;
    386:             }
    387:           }
    388:         }
    389:       }
    390:       goto noinsert2;
    391:     }
    392:   }
    393:   if (nonew == 1) goto noinsert2;
    395:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
    396:   N = nrow++ - 1; high++;
    397:   /* shift up all the later entries in this row */
    398:   PetscArraymove(rp+i+1,rp+i,N-i+1);
    399:   PetscArraymove(ap+bs2*(i+1),ap+bs2*i,bs2*(N-i+1));
    400:   rp[i] = col;
    401:   bap   = ap +  bs2*i;
    402:   if (roworiented) {
    403:     for (ii=0; ii<bs; ii++) {
    404:       for (jj=ii; jj<bs2; jj+=bs) {
    405:         bap[jj] = *value++;
    406:       }
    407:     }
    408:   } else {
    409:     for (ii=0; ii<bs; ii++) {
    410:       for (jj=0; jj<bs; jj++) {
    411:         *bap++ = *value++;
    412:       }
    413:     }
    414:   }
    415:   noinsert2:;
    416:   ailen[row] = nrow;
    417:   return 0;
    418: }

    420: /*
    421:    This routine is exactly duplicated in mpibaij.c
    422: */
    423: static inline PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
    424: {
    425:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    426:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
    427:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
    428:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
    429:   PetscBool         roworiented=a->roworiented;
    430:   const PetscScalar *value     = v;
    431:   MatScalar         *ap,*aa = a->a,*bap;

    433:   rp   = aj + ai[row];
    434:   ap   = aa + bs2*ai[row];
    435:   rmax = imax[row];
    436:   nrow = ailen[row];
    437:   low  = 0;
    438:   high = nrow;
    439:   value = v;
    440:   while (high-low > 7) {
    441:     t = (low+high)/2;
    442:     if (rp[t] > col) high = t;
    443:     else             low  = t;
    444:   }
    445:   for (i=low; i<high; i++) {
    446:     if (rp[i] > col) break;
    447:     if (rp[i] == col) {
    448:       bap = ap +  bs2*i;
    449:       if (roworiented) {
    450:         if (is == ADD_VALUES) {
    451:           for (ii=0; ii<bs; ii++) {
    452:             for (jj=ii; jj<bs2; jj+=bs) {
    453:               bap[jj] += *value++;
    454:             }
    455:           }
    456:         } else {
    457:           for (ii=0; ii<bs; ii++) {
    458:             for (jj=ii; jj<bs2; jj+=bs) {
    459:               bap[jj] = *value++;
    460:             }
    461:           }
    462:         }
    463:       } else {
    464:         if (is == ADD_VALUES) {
    465:           for (ii=0; ii<bs; ii++,value+=bs) {
    466:             for (jj=0; jj<bs; jj++) {
    467:               bap[jj] += value[jj];
    468:             }
    469:             bap += bs;
    470:           }
    471:         } else {
    472:           for (ii=0; ii<bs; ii++,value+=bs) {
    473:             for (jj=0; jj<bs; jj++) {
    474:               bap[jj]  = value[jj];
    475:             }
    476:             bap += bs;
    477:           }
    478:         }
    479:       }
    480:       goto noinsert2;
    481:     }
    482:   }
    483:   if (nonew == 1) goto noinsert2;
    485:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
    486:   N = nrow++ - 1; high++;
    487:   /* shift up all the later entries in this row */
    488:   PetscArraymove(rp+i+1,rp+i,N-i+1);
    489:   PetscArraymove(ap+bs2*(i+1),ap+bs2*i,bs2*(N-i+1));
    490:   rp[i] = col;
    491:   bap   = ap +  bs2*i;
    492:   if (roworiented) {
    493:     for (ii=0; ii<bs; ii++) {
    494:       for (jj=ii; jj<bs2; jj+=bs) {
    495:         bap[jj] = *value++;
    496:       }
    497:     }
    498:   } else {
    499:     for (ii=0; ii<bs; ii++) {
    500:       for (jj=0; jj<bs; jj++) {
    501:         *bap++ = *value++;
    502:       }
    503:     }
    504:   }
    505:   noinsert2:;
    506:   ailen[row] = nrow;
    507:   return 0;
    508: }

    510: /*
    511:     This routine could be optimized by removing the need for the block copy below and passing stride information
    512:   to the above inline routines; similarly in MatSetValuesBlocked_MPIBAIJ()
    513: */
    514: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
    515: {
    516:   Mat_MPISBAIJ    *baij = (Mat_MPISBAIJ*)mat->data;
    517:   const MatScalar *value;
    518:   MatScalar       *barray     =baij->barray;
    519:   PetscBool       roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
    520:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
    521:   PetscInt        rend=baij->rendbs,cstart=baij->cstartbs,stepval;
    522:   PetscInt        cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;

    524:   if (!barray) {
    525:     PetscMalloc1(bs2,&barray);
    526:     baij->barray = barray;
    527:   }

    529:   if (roworiented) {
    530:     stepval = (n-1)*bs;
    531:   } else {
    532:     stepval = (m-1)*bs;
    533:   }
    534:   for (i=0; i<m; i++) {
    535:     if (im[i] < 0) continue;
    537:     if (im[i] >= rstart && im[i] < rend) {
    538:       row = im[i] - rstart;
    539:       for (j=0; j<n; j++) {
    540:         if (im[i] > in[j]) {
    541:           if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
    542:           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)");
    543:         }
    544:         /* If NumCol = 1 then a copy is not required */
    545:         if ((roworiented) && (n == 1)) {
    546:           barray = (MatScalar*) v + i*bs2;
    547:         } else if ((!roworiented) && (m == 1)) {
    548:           barray = (MatScalar*) v + j*bs2;
    549:         } else { /* Here a copy is required */
    550:           if (roworiented) {
    551:             value = v + i*(stepval+bs)*bs + j*bs;
    552:           } else {
    553:             value = v + j*(stepval+bs)*bs + i*bs;
    554:           }
    555:           for (ii=0; ii<bs; ii++,value+=stepval) {
    556:             for (jj=0; jj<bs; jj++) {
    557:               *barray++ = *value++;
    558:             }
    559:           }
    560:           barray -=bs2;
    561:         }

    563:         if (in[j] >= cstart && in[j] < cend) {
    564:           col  = in[j] - cstart;
    565:           MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
    566:         } else if (in[j] < 0) continue;
    568:         else {
    569:           if (mat->was_assembled) {
    570:             if (!baij->colmap) {
    571:               MatCreateColmap_MPIBAIJ_Private(mat);
    572:             }

    574: #if defined(PETSC_USE_DEBUG)
    575: #if defined(PETSC_USE_CTABLE)
    576:             { PetscInt data;
    577:               PetscTableFind(baij->colmap,in[j]+1,&data);
    579:             }
    580: #else
    582: #endif
    583: #endif
    584: #if defined(PETSC_USE_CTABLE)
    585:             PetscTableFind(baij->colmap,in[j]+1,&col);
    586:             col  = (col - 1)/bs;
    587: #else
    588:             col = (baij->colmap[in[j]] - 1)/bs;
    589: #endif
    590:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
    591:               MatDisAssemble_MPISBAIJ(mat);
    592:               col  = in[j];
    593:             }
    594:           } else col = in[j];
    595:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
    596:         }
    597:       }
    598:     } else {
    600:       if (!baij->donotstash) {
    601:         if (roworiented) {
    602:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    603:         } else {
    604:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    605:         }
    606:       }
    607:     }
    608:   }
    609:   return 0;
    610: }

    612: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
    613: {
    614:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    615:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
    616:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

    618:   for (i=0; i<m; i++) {
    619:     if (idxm[i] < 0) continue; /* negative row */
    621:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
    622:       row = idxm[i] - bsrstart;
    623:       for (j=0; j<n; j++) {
    624:         if (idxn[j] < 0) continue; /* negative column */
    626:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
    627:           col  = idxn[j] - bscstart;
    628:           MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
    629:         } else {
    630:           if (!baij->colmap) {
    631:             MatCreateColmap_MPIBAIJ_Private(mat);
    632:           }
    633: #if defined(PETSC_USE_CTABLE)
    634:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
    635:           data--;
    636: #else
    637:           data = baij->colmap[idxn[j]/bs]-1;
    638: #endif
    639:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
    640:           else {
    641:             col  = data + idxn[j]%bs;
    642:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
    643:           }
    644:         }
    645:       }
    646:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
    647:   }
    648:   return 0;
    649: }

    651: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
    652: {
    653:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    654:   PetscReal      sum[2],*lnorm2;

    656:   if (baij->size == 1) {
    657:     MatNorm(baij->A,type,norm);
    658:   } else {
    659:     if (type == NORM_FROBENIUS) {
    660:       PetscMalloc1(2,&lnorm2);
    661:       MatNorm(baij->A,type,lnorm2);
    662:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++;            /* squar power of norm(A) */
    663:       MatNorm(baij->B,type,lnorm2);
    664:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--;             /* squar power of norm(B) */
    665:       MPIU_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
    666:       *norm   = PetscSqrtReal(sum[0] + 2*sum[1]);
    667:       PetscFree(lnorm2);
    668:     } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
    669:       Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
    670:       Mat_SeqBAIJ  *bmat=(Mat_SeqBAIJ*)baij->B->data;
    671:       PetscReal    *rsum,*rsum2,vabs;
    672:       PetscInt     *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
    673:       PetscInt     brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs;
    674:       MatScalar    *v;

    676:       PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);
    677:       PetscArrayzero(rsum,mat->cmap->N);
    678:       /* Amat */
    679:       v = amat->a; jj = amat->j;
    680:       for (brow=0; brow<mbs; brow++) {
    681:         grow = bs*(rstart + brow);
    682:         nz   = amat->i[brow+1] - amat->i[brow];
    683:         for (bcol=0; bcol<nz; bcol++) {
    684:           gcol = bs*(rstart + *jj); jj++;
    685:           for (col=0; col<bs; col++) {
    686:             for (row=0; row<bs; row++) {
    687:               vabs            = PetscAbsScalar(*v); v++;
    688:               rsum[gcol+col] += vabs;
    689:               /* non-diagonal block */
    690:               if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
    691:             }
    692:           }
    693:         }
    694:         PetscLogFlops(nz*bs*bs);
    695:       }
    696:       /* Bmat */
    697:       v = bmat->a; jj = bmat->j;
    698:       for (brow=0; brow<mbs; brow++) {
    699:         grow = bs*(rstart + brow);
    700:         nz = bmat->i[brow+1] - bmat->i[brow];
    701:         for (bcol=0; bcol<nz; bcol++) {
    702:           gcol = bs*garray[*jj]; jj++;
    703:           for (col=0; col<bs; col++) {
    704:             for (row=0; row<bs; row++) {
    705:               vabs            = PetscAbsScalar(*v); v++;
    706:               rsum[gcol+col] += vabs;
    707:               rsum[grow+row] += vabs;
    708:             }
    709:           }
    710:         }
    711:         PetscLogFlops(nz*bs*bs);
    712:       }
    713:       MPIU_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
    714:       *norm = 0.0;
    715:       for (col=0; col<mat->cmap->N; col++) {
    716:         if (rsum2[col] > *norm) *norm = rsum2[col];
    717:       }
    718:       PetscFree2(rsum,rsum2);
    719:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
    720:   }
    721:   return 0;
    722: }

    724: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
    725: {
    726:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    727:   PetscInt       nstash,reallocs;

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

    731:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
    732:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
    733:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
    734:   PetscInfo(mat,"Stash has %" PetscInt_FMT " entries,uses %" PetscInt_FMT " mallocs.\n",nstash,reallocs);
    735:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
    736:   PetscInfo(mat,"Block-Stash has %" PetscInt_FMT " entries, uses %" PetscInt_FMT " mallocs.\n",nstash,reallocs);
    737:   return 0;
    738: }

    740: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
    741: {
    742:   Mat_MPISBAIJ   *baij=(Mat_MPISBAIJ*)mat->data;
    743:   Mat_SeqSBAIJ   *a   =(Mat_SeqSBAIJ*)baij->A->data;
    744:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
    745:   PetscInt       *row,*col;
    746:   PetscBool      other_disassembled;
    747:   PetscMPIInt    n;
    748:   PetscBool      r1,r2,r3;
    749:   MatScalar      *val;

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

    757:       for (i=0; i<n;) {
    758:         /* Now identify the consecutive vals belonging to the same row */
    759:         for (j=i,rstart=row[j]; j<n; j++) {
    760:           if (row[j] != rstart) break;
    761:         }
    762:         if (j < n) ncols = j-i;
    763:         else       ncols = n-i;
    764:         /* Now assemble all these values with a single function call */
    765:         MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
    766:         i    = j;
    767:       }
    768:     }
    769:     MatStashScatterEnd_Private(&mat->stash);
    770:     /* Now process the block-stash. Since the values are stashed column-oriented,
    771:        set the roworiented flag to column oriented, and after MatSetValues()
    772:        restore the original flags */
    773:     r1 = baij->roworiented;
    774:     r2 = a->roworiented;
    775:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

    777:     baij->roworiented = PETSC_FALSE;
    778:     a->roworiented    = PETSC_FALSE;

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

    785:       for (i=0; i<n;) {
    786:         /* Now identify the consecutive vals belonging to the same row */
    787:         for (j=i,rstart=row[j]; j<n; j++) {
    788:           if (row[j] != rstart) break;
    789:         }
    790:         if (j < n) ncols = j-i;
    791:         else       ncols = n-i;
    792:         MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
    793:         i    = j;
    794:       }
    795:     }
    796:     MatStashScatterEnd_Private(&mat->bstash);

    798:     baij->roworiented = r1;
    799:     a->roworiented    = r2;

    801:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
    802:   }

    804:   MatAssemblyBegin(baij->A,mode);
    805:   MatAssemblyEnd(baij->A,mode);

    807:   /* determine if any processor has disassembled, if so we must
    808:      also disassemble ourselves, in order that we may reassemble. */
    809:   /*
    810:      if nonzero structure of submatrix B cannot change then we know that
    811:      no processor disassembled thus we can skip this stuff
    812:   */
    813:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
    814:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
    815:     if (mat->was_assembled && !other_disassembled) {
    816:       MatDisAssemble_MPISBAIJ(mat);
    817:     }
    818:   }

    820:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
    821:     MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
    822:   }
    823:   MatAssemblyBegin(baij->B,mode);
    824:   MatAssemblyEnd(baij->B,mode);

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

    828:   baij->rowvalues = NULL;

    830:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
    831:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
    832:     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
    833:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
    834:   }
    835:   return 0;
    836: }

    838: extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
    839: #include <petscdraw.h>
    840: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
    841: {
    842:   Mat_MPISBAIJ      *baij = (Mat_MPISBAIJ*)mat->data;
    843:   PetscInt          bs   = mat->rmap->bs;
    844:   PetscMPIInt       rank = baij->rank;
    845:   PetscBool         iascii,isdraw;
    846:   PetscViewer       sviewer;
    847:   PetscViewerFormat format;

    849:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    850:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    851:   if (iascii) {
    852:     PetscViewerGetFormat(viewer,&format);
    853:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
    854:       MatInfo info;
    855:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
    856:       MatGetInfo(mat,MAT_LOCAL,&info);
    857:       PetscViewerASCIIPushSynchronized(viewer);
    858:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %" PetscInt_FMT " nz %" PetscInt_FMT " nz alloced %" PetscInt_FMT " bs %" PetscInt_FMT " mem %g\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(double)info.memory);
    859:       MatGetInfo(baij->A,MAT_LOCAL,&info);
    860:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %" PetscInt_FMT " \n",rank,(PetscInt)info.nz_used);
    861:       MatGetInfo(baij->B,MAT_LOCAL,&info);
    862:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %" PetscInt_FMT " \n",rank,(PetscInt)info.nz_used);
    863:       PetscViewerFlush(viewer);
    864:       PetscViewerASCIIPopSynchronized(viewer);
    865:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
    866:       VecScatterView(baij->Mvctx,viewer);
    867:       return 0;
    868:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
    869:       PetscViewerASCIIPrintf(viewer,"  block size is %" PetscInt_FMT "\n",bs);
    870:       return 0;
    871:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
    872:       return 0;
    873:     }
    874:   }

    876:   if (isdraw) {
    877:     PetscDraw draw;
    878:     PetscBool isnull;
    879:     PetscViewerDrawGetDraw(viewer,0,&draw);
    880:     PetscDrawIsNull(draw,&isnull);
    881:     if (isnull) return 0;
    882:   }

    884:   {
    885:     /* assemble the entire matrix onto first processor. */
    886:     Mat          A;
    887:     Mat_SeqSBAIJ *Aloc;
    888:     Mat_SeqBAIJ  *Bloc;
    889:     PetscInt     M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
    890:     MatScalar    *a;
    891:     const char   *matname;

    893:     /* Should this be the same type as mat? */
    894:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
    895:     if (rank == 0) {
    896:       MatSetSizes(A,M,N,M,N);
    897:     } else {
    898:       MatSetSizes(A,0,0,M,N);
    899:     }
    900:     MatSetType(A,MATMPISBAIJ);
    901:     MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
    902:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
    903:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

    905:     /* copy over the A part */
    906:     Aloc = (Mat_SeqSBAIJ*)baij->A->data;
    907:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
    908:     PetscMalloc1(bs,&rvals);

    910:     for (i=0; i<mbs; i++) {
    911:       rvals[0] = bs*(baij->rstartbs + i);
    912:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    913:       for (j=ai[i]; j<ai[i+1]; j++) {
    914:         col = (baij->cstartbs+aj[j])*bs;
    915:         for (k=0; k<bs; k++) {
    916:           MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
    917:           col++;
    918:           a += bs;
    919:         }
    920:       }
    921:     }
    922:     /* copy over the B part */
    923:     Bloc = (Mat_SeqBAIJ*)baij->B->data;
    924:     ai   = Bloc->i; aj = Bloc->j; a = Bloc->a;
    925:     for (i=0; i<mbs; i++) {

    927:       rvals[0] = bs*(baij->rstartbs + i);
    928:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    929:       for (j=ai[i]; j<ai[i+1]; j++) {
    930:         col = baij->garray[aj[j]]*bs;
    931:         for (k=0; k<bs; k++) {
    932:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
    933:           col++;
    934:           a += bs;
    935:         }
    936:       }
    937:     }
    938:     PetscFree(rvals);
    939:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    940:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    941:     /*
    942:        Everyone has to call to draw the matrix since the graphics waits are
    943:        synchronized across all processors that share the PetscDraw object
    944:     */
    945:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
    946:     PetscObjectGetName((PetscObject)mat,&matname);
    947:     if (rank == 0) {
    948:       PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,matname);
    949:       MatView_SeqSBAIJ(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
    950:     }
    951:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
    952:     PetscViewerFlush(viewer);
    953:     MatDestroy(&A);
    954:   }
    955:   return 0;
    956: }

    958: /* Used for both MPIBAIJ and MPISBAIJ matrices */
    959: #define MatView_MPISBAIJ_Binary MatView_MPIBAIJ_Binary

    961: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
    962: {
    963:   PetscBool      iascii,isdraw,issocket,isbinary;

    965:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    966:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    967:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
    968:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    969:   if (iascii || isdraw || issocket) {
    970:     MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
    971:   } else if (isbinary) {
    972:     MatView_MPISBAIJ_Binary(mat,viewer);
    973:   }
    974:   return 0;
    975: }

    977: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
    978: {
    979:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;

    981: #if defined(PETSC_USE_LOG)
    982:   PetscLogObjectState((PetscObject)mat,"Rows=%" PetscInt_FMT ",Cols=%" PetscInt_FMT,mat->rmap->N,mat->cmap->N);
    983: #endif
    984:   MatStashDestroy_Private(&mat->stash);
    985:   MatStashDestroy_Private(&mat->bstash);
    986:   MatDestroy(&baij->A);
    987:   MatDestroy(&baij->B);
    988: #if defined(PETSC_USE_CTABLE)
    989:   PetscTableDestroy(&baij->colmap);
    990: #else
    991:   PetscFree(baij->colmap);
    992: #endif
    993:   PetscFree(baij->garray);
    994:   VecDestroy(&baij->lvec);
    995:   VecScatterDestroy(&baij->Mvctx);
    996:   VecDestroy(&baij->slvec0);
    997:   VecDestroy(&baij->slvec0b);
    998:   VecDestroy(&baij->slvec1);
    999:   VecDestroy(&baij->slvec1a);
    1000:   VecDestroy(&baij->slvec1b);
    1001:   VecScatterDestroy(&baij->sMvctx);
    1002:   PetscFree2(baij->rowvalues,baij->rowindices);
    1003:   PetscFree(baij->barray);
    1004:   PetscFree(baij->hd);
    1005:   VecDestroy(&baij->diag);
    1006:   VecDestroy(&baij->bb1);
    1007:   VecDestroy(&baij->xx1);
    1008: #if defined(PETSC_USE_REAL_MAT_SINGLE)
    1009:   PetscFree(baij->setvaluescopy);
    1010: #endif
    1011:   PetscFree(baij->in_loc);
    1012:   PetscFree(baij->v_loc);
    1013:   PetscFree(baij->rangebs);
    1014:   PetscFree(mat->data);

    1016:   PetscObjectChangeTypeName((PetscObject)mat,NULL);
    1017:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
    1018:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
    1019:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);
    1020:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocationCSR_C",NULL);
    1021: #if defined(PETSC_HAVE_ELEMENTAL)
    1022:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_elemental_C",NULL);
    1023: #endif
    1024: #if defined(PETSC_HAVE_SCALAPACK)
    1025:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_scalapack_C",NULL);
    1026: #endif
    1027:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpiaij_C",NULL);
    1028:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpibaij_C",NULL);
    1029:   return 0;
    1030: }

    1032: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
    1033: {
    1034:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
    1035:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
    1036:   PetscScalar       *from;
    1037:   const PetscScalar *x;

    1039:   /* diagonal part */
    1040:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
    1041:   VecSet(a->slvec1b,0.0);

    1043:   /* subdiagonal part */
    1045:   (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);

    1047:   /* copy x into the vec slvec0 */
    1048:   VecGetArray(a->slvec0,&from);
    1049:   VecGetArrayRead(xx,&x);

    1051:   PetscArraycpy(from,x,bs*mbs);
    1052:   VecRestoreArray(a->slvec0,&from);
    1053:   VecRestoreArrayRead(xx,&x);

    1055:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    1056:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    1057:   /* supperdiagonal part */
    1058:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
    1059:   return 0;
    1060: }

    1062: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
    1063: {
    1064:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
    1065:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
    1066:   PetscScalar       *from;
    1067:   const PetscScalar *x;

    1069:   /* diagonal part */
    1070:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
    1071:   VecSet(a->slvec1b,0.0);

    1073:   /* subdiagonal part */
    1074:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

    1076:   /* copy x into the vec slvec0 */
    1077:   VecGetArray(a->slvec0,&from);
    1078:   VecGetArrayRead(xx,&x);

    1080:   PetscArraycpy(from,x,bs*mbs);
    1081:   VecRestoreArray(a->slvec0,&from);
    1082:   VecRestoreArrayRead(xx,&x);

    1084:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    1085:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    1086:   /* supperdiagonal part */
    1087:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
    1088:   return 0;
    1089: }

    1091: PetscErrorCode MatMultAdd_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy,Vec zz)
    1092: {
    1093:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
    1094:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
    1095:   PetscScalar       *from,zero=0.0;
    1096:   const PetscScalar *x;

    1098:   /* diagonal part */
    1099:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
    1100:   VecSet(a->slvec1b,zero);

    1102:   /* subdiagonal part */
    1104:   (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);

    1106:   /* copy x into the vec slvec0 */
    1107:   VecGetArray(a->slvec0,&from);
    1108:   VecGetArrayRead(xx,&x);
    1109:   PetscArraycpy(from,x,bs*mbs);
    1110:   VecRestoreArray(a->slvec0,&from);

    1112:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    1113:   VecRestoreArrayRead(xx,&x);
    1114:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

    1116:   /* supperdiagonal part */
    1117:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
    1118:   return 0;
    1119: }

    1121: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
    1122: {
    1123:   Mat_MPISBAIJ      *a = (Mat_MPISBAIJ*)A->data;
    1124:   PetscInt          mbs=a->mbs,bs=A->rmap->bs;
    1125:   PetscScalar       *from,zero=0.0;
    1126:   const PetscScalar *x;

    1128:   /* diagonal part */
    1129:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
    1130:   VecSet(a->slvec1b,zero);

    1132:   /* subdiagonal part */
    1133:   (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);

    1135:   /* copy x into the vec slvec0 */
    1136:   VecGetArray(a->slvec0,&from);
    1137:   VecGetArrayRead(xx,&x);
    1138:   PetscArraycpy(from,x,bs*mbs);
    1139:   VecRestoreArray(a->slvec0,&from);

    1141:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    1142:   VecRestoreArrayRead(xx,&x);
    1143:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

    1145:   /* supperdiagonal part */
    1146:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
    1147:   return 0;
    1148: }

    1150: /*
    1151:   This only works correctly for square matrices where the subblock A->A is the
    1152:    diagonal block
    1153: */
    1154: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
    1155: {
    1156:   Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;

    1159:   MatGetDiagonal(a->A,v);
    1160:   return 0;
    1161: }

    1163: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
    1164: {
    1165:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1167:   MatScale(a->A,aa);
    1168:   MatScale(a->B,aa);
    1169:   return 0;
    1170: }

    1172: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1173: {
    1174:   Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data;
    1175:   PetscScalar  *vworkA,*vworkB,**pvA,**pvB,*v_p;
    1176:   PetscInt     bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
    1177:   PetscInt     nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
    1178:   PetscInt    *cmap,*idx_p,cstart = mat->rstartbs;

    1181:   mat->getrowactive = PETSC_TRUE;

    1183:   if (!mat->rowvalues && (idx || v)) {
    1184:     /*
    1185:         allocate enough space to hold information from the longest row.
    1186:     */
    1187:     Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
    1188:     Mat_SeqBAIJ  *Ba = (Mat_SeqBAIJ*)mat->B->data;
    1189:     PetscInt     max = 1,mbs = mat->mbs,tmp;
    1190:     for (i=0; i<mbs; i++) {
    1191:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
    1192:       if (max < tmp) max = tmp;
    1193:     }
    1194:     PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
    1195:   }

    1198:   lrow = row - brstart;  /* local row index */

    1200:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
    1201:   if (!v)   {pvA = NULL; pvB = NULL;}
    1202:   if (!idx) {pcA = NULL; if (!v) pcB = NULL;}
    1203:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
    1204:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
    1205:   nztot = nzA + nzB;

    1207:   cmap = mat->garray;
    1208:   if (v  || idx) {
    1209:     if (nztot) {
    1210:       /* Sort by increasing column numbers, assuming A and B already sorted */
    1211:       PetscInt imark = -1;
    1212:       if (v) {
    1213:         *v = v_p = mat->rowvalues;
    1214:         for (i=0; i<nzB; i++) {
    1215:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
    1216:           else break;
    1217:         }
    1218:         imark = i;
    1219:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
    1220:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
    1221:       }
    1222:       if (idx) {
    1223:         *idx = idx_p = mat->rowindices;
    1224:         if (imark > -1) {
    1225:           for (i=0; i<imark; i++) {
    1226:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
    1227:           }
    1228:         } else {
    1229:           for (i=0; i<nzB; i++) {
    1230:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
    1231:             else break;
    1232:           }
    1233:           imark = i;
    1234:         }
    1235:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
    1236:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
    1237:       }
    1238:     } else {
    1239:       if (idx) *idx = NULL;
    1240:       if (v)   *v   = NULL;
    1241:     }
    1242:   }
    1243:   *nz  = nztot;
    1244:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
    1245:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
    1246:   return 0;
    1247: }

    1249: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1250: {
    1251:   Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;

    1254:   baij->getrowactive = PETSC_FALSE;
    1255:   return 0;
    1256: }

    1258: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
    1259: {
    1260:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
    1261:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

    1263:   aA->getrow_utriangular = PETSC_TRUE;
    1264:   return 0;
    1265: }
    1266: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
    1267: {
    1268:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
    1269:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

    1271:   aA->getrow_utriangular = PETSC_FALSE;
    1272:   return 0;
    1273: }

    1275: PetscErrorCode MatConjugate_MPISBAIJ(Mat mat)
    1276: {
    1277:   if (PetscDefined(USE_COMPLEX)) {
    1278:     Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)mat->data;

    1280:     MatConjugate(a->A);
    1281:     MatConjugate(a->B);
    1282:   }
    1283:   return 0;
    1284: }

    1286: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
    1287: {
    1288:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1290:   MatRealPart(a->A);
    1291:   MatRealPart(a->B);
    1292:   return 0;
    1293: }

    1295: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
    1296: {
    1297:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

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

    1304: /* Check if isrow is a subset of iscol_local, called by MatCreateSubMatrix_MPISBAIJ()
    1305:    Input: isrow       - distributed(parallel),
    1306:           iscol_local - locally owned (seq)
    1307: */
    1308: PetscErrorCode ISEqual_private(IS isrow,IS iscol_local,PetscBool  *flg)
    1309: {
    1310:   PetscInt       sz1,sz2,*a1,*a2,i,j,k,nmatch;
    1311:   const PetscInt *ptr1,*ptr2;

    1313:   ISGetLocalSize(isrow,&sz1);
    1314:   ISGetLocalSize(iscol_local,&sz2);
    1315:   if (sz1 > sz2) {
    1316:     *flg = PETSC_FALSE;
    1317:     return 0;
    1318:   }

    1320:   ISGetIndices(isrow,&ptr1);
    1321:   ISGetIndices(iscol_local,&ptr2);

    1323:   PetscMalloc1(sz1,&a1);
    1324:   PetscMalloc1(sz2,&a2);
    1325:   PetscArraycpy(a1,ptr1,sz1);
    1326:   PetscArraycpy(a2,ptr2,sz2);
    1327:   PetscSortInt(sz1,a1);
    1328:   PetscSortInt(sz2,a2);

    1330:   nmatch=0;
    1331:   k     = 0;
    1332:   for (i=0; i<sz1; i++) {
    1333:     for (j=k; j<sz2; j++) {
    1334:       if (a1[i] == a2[j]) {
    1335:         k = j; nmatch++;
    1336:         break;
    1337:       }
    1338:     }
    1339:   }
    1340:   ISRestoreIndices(isrow,&ptr1);
    1341:   ISRestoreIndices(iscol_local,&ptr2);
    1342:   PetscFree(a1);
    1343:   PetscFree(a2);
    1344:   if (nmatch < sz1) {
    1345:     *flg = PETSC_FALSE;
    1346:   } else {
    1347:     *flg = PETSC_TRUE;
    1348:   }
    1349:   return 0;
    1350: }

    1352: PetscErrorCode MatCreateSubMatrix_MPISBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
    1353: {
    1354:   IS             iscol_local;
    1355:   PetscInt       csize;
    1356:   PetscBool      isequal;

    1358:   ISGetLocalSize(iscol,&csize);
    1359:   if (call == MAT_REUSE_MATRIX) {
    1360:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
    1362:   } else {
    1363:     PetscBool issorted;

    1365:     ISAllGather(iscol,&iscol_local);
    1366:     ISEqual_private(isrow,iscol_local,&isequal);
    1367:     ISSorted(iscol_local, &issorted);
    1369:   }

    1371:   /* now call MatCreateSubMatrix_MPIBAIJ() */
    1372:   MatCreateSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
    1373:   if (call == MAT_INITIAL_MATRIX) {
    1374:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
    1375:     ISDestroy(&iscol_local);
    1376:   }
    1377:   return 0;
    1378: }

    1380: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
    1381: {
    1382:   Mat_MPISBAIJ   *l = (Mat_MPISBAIJ*)A->data;

    1384:   MatZeroEntries(l->A);
    1385:   MatZeroEntries(l->B);
    1386:   return 0;
    1387: }

    1389: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
    1390: {
    1391:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)matin->data;
    1392:   Mat            A  = a->A,B = a->B;
    1393:   PetscLogDouble isend[5],irecv[5];

    1395:   info->block_size = (PetscReal)matin->rmap->bs;

    1397:   MatGetInfo(A,MAT_LOCAL,info);

    1399:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
    1400:   isend[3] = info->memory;  isend[4] = info->mallocs;

    1402:   MatGetInfo(B,MAT_LOCAL,info);

    1404:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
    1405:   isend[3] += info->memory;  isend[4] += info->mallocs;
    1406:   if (flag == MAT_LOCAL) {
    1407:     info->nz_used      = isend[0];
    1408:     info->nz_allocated = isend[1];
    1409:     info->nz_unneeded  = isend[2];
    1410:     info->memory       = isend[3];
    1411:     info->mallocs      = isend[4];
    1412:   } else if (flag == MAT_GLOBAL_MAX) {
    1413:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_MAX,PetscObjectComm((PetscObject)matin));

    1415:     info->nz_used      = irecv[0];
    1416:     info->nz_allocated = irecv[1];
    1417:     info->nz_unneeded  = irecv[2];
    1418:     info->memory       = irecv[3];
    1419:     info->mallocs      = irecv[4];
    1420:   } else if (flag == MAT_GLOBAL_SUM) {
    1421:     MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_SUM,PetscObjectComm((PetscObject)matin));

    1423:     info->nz_used      = irecv[0];
    1424:     info->nz_allocated = irecv[1];
    1425:     info->nz_unneeded  = irecv[2];
    1426:     info->memory       = irecv[3];
    1427:     info->mallocs      = irecv[4];
    1428:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
    1429:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
    1430:   info->fill_ratio_needed = 0;
    1431:   info->factor_mallocs    = 0;
    1432:   return 0;
    1433: }

    1435: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
    1436: {
    1437:   Mat_MPISBAIJ   *a  = (Mat_MPISBAIJ*)A->data;
    1438:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

    1440:   switch (op) {
    1441:   case MAT_NEW_NONZERO_LOCATIONS:
    1442:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
    1443:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
    1444:   case MAT_KEEP_NONZERO_PATTERN:
    1445:   case MAT_SUBMAT_SINGLEIS:
    1446:   case MAT_NEW_NONZERO_LOCATION_ERR:
    1447:     MatCheckPreallocated(A,1);
    1448:     MatSetOption(a->A,op,flg);
    1449:     MatSetOption(a->B,op,flg);
    1450:     break;
    1451:   case MAT_ROW_ORIENTED:
    1452:     MatCheckPreallocated(A,1);
    1453:     a->roworiented = flg;

    1455:     MatSetOption(a->A,op,flg);
    1456:     MatSetOption(a->B,op,flg);
    1457:     break;
    1458:   case MAT_FORCE_DIAGONAL_ENTRIES:
    1459:   case MAT_SORTED_FULL:
    1460:     PetscInfo(A,"Option %s ignored\n",MatOptions[op]);
    1461:     break;
    1462:   case MAT_IGNORE_OFF_PROC_ENTRIES:
    1463:     a->donotstash = flg;
    1464:     break;
    1465:   case MAT_USE_HASH_TABLE:
    1466:     a->ht_flag = flg;
    1467:     break;
    1468:   case MAT_HERMITIAN:
    1469:     MatCheckPreallocated(A,1);
    1470:     MatSetOption(a->A,op,flg);
    1471: #if defined(PETSC_USE_COMPLEX)
    1472:     if (flg) { /* need different mat-vec ops */
    1473:       A->ops->mult             = MatMult_MPISBAIJ_Hermitian;
    1474:       A->ops->multadd          = MatMultAdd_MPISBAIJ_Hermitian;
    1475:       A->ops->multtranspose    = NULL;
    1476:       A->ops->multtransposeadd = NULL;
    1477:       A->symmetric = PETSC_FALSE;
    1478:     }
    1479: #endif
    1480:     break;
    1481:   case MAT_SPD:
    1482:   case MAT_SYMMETRIC:
    1483:     MatCheckPreallocated(A,1);
    1484:     MatSetOption(a->A,op,flg);
    1485: #if defined(PETSC_USE_COMPLEX)
    1486:     if (flg) { /* restore to use default mat-vec ops */
    1487:       A->ops->mult             = MatMult_MPISBAIJ;
    1488:       A->ops->multadd          = MatMultAdd_MPISBAIJ;
    1489:       A->ops->multtranspose    = MatMult_MPISBAIJ;
    1490:       A->ops->multtransposeadd = MatMultAdd_MPISBAIJ;
    1491:     }
    1492: #endif
    1493:     break;
    1494:   case MAT_STRUCTURALLY_SYMMETRIC:
    1495:     MatCheckPreallocated(A,1);
    1496:     MatSetOption(a->A,op,flg);
    1497:     break;
    1498:   case MAT_SYMMETRY_ETERNAL:
    1500:     PetscInfo(A,"Option %s ignored\n",MatOptions[op]);
    1501:     break;
    1502:   case MAT_IGNORE_LOWER_TRIANGULAR:
    1503:     aA->ignore_ltriangular = flg;
    1504:     break;
    1505:   case MAT_ERROR_LOWER_TRIANGULAR:
    1506:     aA->ignore_ltriangular = flg;
    1507:     break;
    1508:   case MAT_GETROW_UPPERTRIANGULAR:
    1509:     aA->getrow_utriangular = flg;
    1510:     break;
    1511:   default:
    1512:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
    1513:   }
    1514:   return 0;
    1515: }

    1517: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
    1518: {
    1519:   if (reuse == MAT_INITIAL_MATRIX) {
    1520:     MatDuplicate(A,MAT_COPY_VALUES,B);
    1521:   }  else if (reuse == MAT_REUSE_MATRIX) {
    1522:     MatCopy(A,*B,SAME_NONZERO_PATTERN);
    1523:   }
    1524:   return 0;
    1525: }

    1527: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
    1528: {
    1529:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    1530:   Mat            a     = baij->A, b=baij->B;
    1531:   PetscInt       nv,m,n;
    1532:   PetscBool      flg;

    1534:   if (ll != rr) {
    1535:     VecEqual(ll,rr,&flg);
    1537:   }
    1538:   if (!ll) return 0;

    1540:   MatGetLocalSize(mat,&m,&n);

    1543:   VecGetLocalSize(rr,&nv);

    1546:   VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);

    1548:   /* left diagonalscale the off-diagonal part */
    1549:   (*b->ops->diagonalscale)(b,ll,NULL);

    1551:   /* scale the diagonal part */
    1552:   (*a->ops->diagonalscale)(a,ll,rr);

    1554:   /* right diagonalscale the off-diagonal part */
    1555:   VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1556:   (*b->ops->diagonalscale)(b,NULL,baij->lvec);
    1557:   return 0;
    1558: }

    1560: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
    1561: {
    1562:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1564:   MatSetUnfactored(a->A);
    1565:   return 0;
    1566: }

    1568: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);

    1570: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool  *flag)
    1571: {
    1572:   Mat_MPISBAIJ   *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
    1573:   Mat            a,b,c,d;
    1574:   PetscBool      flg;

    1576:   a = matA->A; b = matA->B;
    1577:   c = matB->A; d = matB->B;

    1579:   MatEqual(a,c,&flg);
    1580:   if (flg) {
    1581:     MatEqual(b,d,&flg);
    1582:   }
    1583:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
    1584:   return 0;
    1585: }

    1587: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
    1588: {
    1589:   PetscBool      isbaij;

    1591:   PetscObjectTypeCompareAny((PetscObject)B,&isbaij,MATSEQSBAIJ,MATMPISBAIJ,"");
    1593:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
    1594:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
    1595:     MatGetRowUpperTriangular(A);
    1596:     MatCopy_Basic(A,B,str);
    1597:     MatRestoreRowUpperTriangular(A);
    1598:   } else {
    1599:     Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
    1600:     Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data;

    1602:     MatCopy(a->A,b->A,str);
    1603:     MatCopy(a->B,b->B,str);
    1604:   }
    1605:   PetscObjectStateIncrease((PetscObject)B);
    1606:   return 0;
    1607: }

    1609: PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
    1610: {
    1611:   MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,NULL,PETSC_DEFAULT,NULL);
    1612:   return 0;
    1613: }

    1615: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
    1616: {
    1617:   Mat_MPISBAIJ   *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
    1618:   PetscBLASInt   bnz,one=1;
    1619:   Mat_SeqSBAIJ   *xa,*ya;
    1620:   Mat_SeqBAIJ    *xb,*yb;

    1622:   if (str == SAME_NONZERO_PATTERN) {
    1623:     PetscScalar alpha = a;
    1624:     xa   = (Mat_SeqSBAIJ*)xx->A->data;
    1625:     ya   = (Mat_SeqSBAIJ*)yy->A->data;
    1626:     PetscBLASIntCast(xa->nz,&bnz);
    1627:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
    1628:     xb   = (Mat_SeqBAIJ*)xx->B->data;
    1629:     yb   = (Mat_SeqBAIJ*)yy->B->data;
    1630:     PetscBLASIntCast(xb->nz,&bnz);
    1631:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
    1632:     PetscObjectStateIncrease((PetscObject)Y);
    1633:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
    1634:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
    1635:     MatAXPY_Basic(Y,a,X,str);
    1636:     MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
    1637:   } else {
    1638:     Mat      B;
    1639:     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
    1641:     MatGetRowUpperTriangular(X);
    1642:     MatGetRowUpperTriangular(Y);
    1643:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
    1644:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
    1645:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
    1646:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
    1647:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
    1648:     MatSetBlockSizesFromMats(B,Y,Y);
    1649:     MatSetType(B,MATMPISBAIJ);
    1650:     MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);
    1651:     MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
    1652:     MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
    1653:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
    1654:     MatHeaderMerge(Y,&B);
    1655:     PetscFree(nnz_d);
    1656:     PetscFree(nnz_o);
    1657:     MatRestoreRowUpperTriangular(X);
    1658:     MatRestoreRowUpperTriangular(Y);
    1659:   }
    1660:   return 0;
    1661: }

    1663: PetscErrorCode MatCreateSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
    1664: {
    1665:   PetscInt       i;
    1666:   PetscBool      flg;

    1668:   MatCreateSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B); /* B[] are sbaij matrices */
    1669:   for (i=0; i<n; i++) {
    1670:     ISEqual(irow[i],icol[i],&flg);
    1671:     if (!flg) {
    1672:       MatSeqSBAIJZeroOps_Private(*B[i]);
    1673:     }
    1674:   }
    1675:   return 0;
    1676: }

    1678: PetscErrorCode MatShift_MPISBAIJ(Mat Y,PetscScalar a)
    1679: {
    1680:   Mat_MPISBAIJ    *maij = (Mat_MPISBAIJ*)Y->data;
    1681:   Mat_SeqSBAIJ    *aij = (Mat_SeqSBAIJ*)maij->A->data;

    1683:   if (!Y->preallocated) {
    1684:     MatMPISBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
    1685:   } else if (!aij->nz) {
    1686:     PetscInt nonew = aij->nonew;
    1687:     MatSeqSBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
    1688:     aij->nonew = nonew;
    1689:   }
    1690:   MatShift_Basic(Y,a);
    1691:   return 0;
    1692: }

    1694: PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
    1695: {
    1696:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1699:   MatMissingDiagonal(a->A,missing,d);
    1700:   if (d) {
    1701:     PetscInt rstart;
    1702:     MatGetOwnershipRange(A,&rstart,NULL);
    1703:     *d += rstart/A->rmap->bs;

    1705:   }
    1706:   return 0;
    1707: }

    1709: PetscErrorCode  MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
    1710: {
    1711:   *a = ((Mat_MPISBAIJ*)A->data)->A;
    1712:   return 0;
    1713: }

    1715: /* -------------------------------------------------------------------*/
    1716: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
    1717:                                        MatGetRow_MPISBAIJ,
    1718:                                        MatRestoreRow_MPISBAIJ,
    1719:                                        MatMult_MPISBAIJ,
    1720:                                /*  4*/ MatMultAdd_MPISBAIJ,
    1721:                                        MatMult_MPISBAIJ,       /* transpose versions are same as non-transpose */
    1722:                                        MatMultAdd_MPISBAIJ,
    1723:                                        NULL,
    1724:                                        NULL,
    1725:                                        NULL,
    1726:                                /* 10*/ NULL,
    1727:                                        NULL,
    1728:                                        NULL,
    1729:                                        MatSOR_MPISBAIJ,
    1730:                                        MatTranspose_MPISBAIJ,
    1731:                                /* 15*/ MatGetInfo_MPISBAIJ,
    1732:                                        MatEqual_MPISBAIJ,
    1733:                                        MatGetDiagonal_MPISBAIJ,
    1734:                                        MatDiagonalScale_MPISBAIJ,
    1735:                                        MatNorm_MPISBAIJ,
    1736:                                /* 20*/ MatAssemblyBegin_MPISBAIJ,
    1737:                                        MatAssemblyEnd_MPISBAIJ,
    1738:                                        MatSetOption_MPISBAIJ,
    1739:                                        MatZeroEntries_MPISBAIJ,
    1740:                                /* 24*/ NULL,
    1741:                                        NULL,
    1742:                                        NULL,
    1743:                                        NULL,
    1744:                                        NULL,
    1745:                                /* 29*/ MatSetUp_MPISBAIJ,
    1746:                                        NULL,
    1747:                                        NULL,
    1748:                                        MatGetDiagonalBlock_MPISBAIJ,
    1749:                                        NULL,
    1750:                                /* 34*/ MatDuplicate_MPISBAIJ,
    1751:                                        NULL,
    1752:                                        NULL,
    1753:                                        NULL,
    1754:                                        NULL,
    1755:                                /* 39*/ MatAXPY_MPISBAIJ,
    1756:                                        MatCreateSubMatrices_MPISBAIJ,
    1757:                                        MatIncreaseOverlap_MPISBAIJ,
    1758:                                        MatGetValues_MPISBAIJ,
    1759:                                        MatCopy_MPISBAIJ,
    1760:                                /* 44*/ NULL,
    1761:                                        MatScale_MPISBAIJ,
    1762:                                        MatShift_MPISBAIJ,
    1763:                                        NULL,
    1764:                                        NULL,
    1765:                                /* 49*/ NULL,
    1766:                                        NULL,
    1767:                                        NULL,
    1768:                                        NULL,
    1769:                                        NULL,
    1770:                                /* 54*/ NULL,
    1771:                                        NULL,
    1772:                                        MatSetUnfactored_MPISBAIJ,
    1773:                                        NULL,
    1774:                                        MatSetValuesBlocked_MPISBAIJ,
    1775:                                /* 59*/ MatCreateSubMatrix_MPISBAIJ,
    1776:                                        NULL,
    1777:                                        NULL,
    1778:                                        NULL,
    1779:                                        NULL,
    1780:                                /* 64*/ NULL,
    1781:                                        NULL,
    1782:                                        NULL,
    1783:                                        NULL,
    1784:                                        NULL,
    1785:                                /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
    1786:                                        NULL,
    1787:                                        MatConvert_MPISBAIJ_Basic,
    1788:                                        NULL,
    1789:                                        NULL,
    1790:                                /* 74*/ NULL,
    1791:                                        NULL,
    1792:                                        NULL,
    1793:                                        NULL,
    1794:                                        NULL,
    1795:                                /* 79*/ NULL,
    1796:                                        NULL,
    1797:                                        NULL,
    1798:                                        NULL,
    1799:                                        MatLoad_MPISBAIJ,
    1800:                                /* 84*/ NULL,
    1801:                                        NULL,
    1802:                                        NULL,
    1803:                                        NULL,
    1804:                                        NULL,
    1805:                                /* 89*/ NULL,
    1806:                                        NULL,
    1807:                                        NULL,
    1808:                                        NULL,
    1809:                                        NULL,
    1810:                                /* 94*/ NULL,
    1811:                                        NULL,
    1812:                                        NULL,
    1813:                                        NULL,
    1814:                                        NULL,
    1815:                                /* 99*/ NULL,
    1816:                                        NULL,
    1817:                                        NULL,
    1818:                                        MatConjugate_MPISBAIJ,
    1819:                                        NULL,
    1820:                                /*104*/ NULL,
    1821:                                        MatRealPart_MPISBAIJ,
    1822:                                        MatImaginaryPart_MPISBAIJ,
    1823:                                        MatGetRowUpperTriangular_MPISBAIJ,
    1824:                                        MatRestoreRowUpperTriangular_MPISBAIJ,
    1825:                                /*109*/ NULL,
    1826:                                        NULL,
    1827:                                        NULL,
    1828:                                        NULL,
    1829:                                        MatMissingDiagonal_MPISBAIJ,
    1830:                                /*114*/ NULL,
    1831:                                        NULL,
    1832:                                        NULL,
    1833:                                        NULL,
    1834:                                        NULL,
    1835:                                /*119*/ NULL,
    1836:                                        NULL,
    1837:                                        NULL,
    1838:                                        NULL,
    1839:                                        NULL,
    1840:                                /*124*/ NULL,
    1841:                                        NULL,
    1842:                                        NULL,
    1843:                                        NULL,
    1844:                                        NULL,
    1845:                                /*129*/ NULL,
    1846:                                        NULL,
    1847:                                        NULL,
    1848:                                        NULL,
    1849:                                        NULL,
    1850:                                /*134*/ NULL,
    1851:                                        NULL,
    1852:                                        NULL,
    1853:                                        NULL,
    1854:                                        NULL,
    1855:                                /*139*/ MatSetBlockSizes_Default,
    1856:                                        NULL,
    1857:                                        NULL,
    1858:                                        NULL,
    1859:                                        NULL,
    1860:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPISBAIJ,
    1861:                                        NULL,
    1862:                                        NULL,
    1863:                                        NULL
    1864: };

    1866: PetscErrorCode  MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
    1867: {
    1868:   Mat_MPISBAIJ   *b = (Mat_MPISBAIJ*)B->data;
    1869:   PetscInt       i,mbs,Mbs;
    1870:   PetscMPIInt    size;

    1872:   MatSetBlockSize(B,PetscAbs(bs));
    1873:   PetscLayoutSetUp(B->rmap);
    1874:   PetscLayoutSetUp(B->cmap);
    1875:   PetscLayoutGetBlockSize(B->rmap,&bs);

    1879:   mbs = B->rmap->n/bs;
    1880:   Mbs = B->rmap->N/bs;

    1883:   B->rmap->bs = bs;
    1884:   b->bs2      = bs*bs;
    1885:   b->mbs      = mbs;
    1886:   b->Mbs      = Mbs;
    1887:   b->nbs      = B->cmap->n/bs;
    1888:   b->Nbs      = B->cmap->N/bs;

    1890:   for (i=0; i<=b->size; i++) {
    1891:     b->rangebs[i] = B->rmap->range[i]/bs;
    1892:   }
    1893:   b->rstartbs = B->rmap->rstart/bs;
    1894:   b->rendbs   = B->rmap->rend/bs;

    1896:   b->cstartbs = B->cmap->rstart/bs;
    1897:   b->cendbs   = B->cmap->rend/bs;

    1899: #if defined(PETSC_USE_CTABLE)
    1900:   PetscTableDestroy(&b->colmap);
    1901: #else
    1902:   PetscFree(b->colmap);
    1903: #endif
    1904:   PetscFree(b->garray);
    1905:   VecDestroy(&b->lvec);
    1906:   VecScatterDestroy(&b->Mvctx);
    1907:   VecDestroy(&b->slvec0);
    1908:   VecDestroy(&b->slvec0b);
    1909:   VecDestroy(&b->slvec1);
    1910:   VecDestroy(&b->slvec1a);
    1911:   VecDestroy(&b->slvec1b);
    1912:   VecScatterDestroy(&b->sMvctx);

    1914:   /* Because the B will have been resized we simply destroy it and create a new one each time */
    1915:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
    1916:   MatDestroy(&b->B);
    1917:   MatCreate(PETSC_COMM_SELF,&b->B);
    1918:   MatSetSizes(b->B,B->rmap->n,size > 1 ? B->cmap->N : 0,B->rmap->n,size > 1 ? B->cmap->N : 0);
    1919:   MatSetType(b->B,MATSEQBAIJ);
    1920:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

    1922:   if (!B->preallocated) {
    1923:     MatCreate(PETSC_COMM_SELF,&b->A);
    1924:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
    1925:     MatSetType(b->A,MATSEQSBAIJ);
    1926:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
    1927:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
    1928:   }

    1930:   MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
    1931:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);

    1933:   B->preallocated  = PETSC_TRUE;
    1934:   B->was_assembled = PETSC_FALSE;
    1935:   B->assembled     = PETSC_FALSE;
    1936:   return 0;
    1937: }

    1939: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
    1940: {
    1941:   PetscInt       m,rstart,cend;
    1942:   PetscInt       i,j,d,nz,bd, nz_max=0,*d_nnz=NULL,*o_nnz=NULL;
    1943:   const PetscInt *JJ    =NULL;
    1944:   PetscScalar    *values=NULL;
    1945:   PetscBool      roworiented = ((Mat_MPISBAIJ*)B->data)->roworiented;
    1946:   PetscBool      nooffprocentries;

    1949:   PetscLayoutSetBlockSize(B->rmap,bs);
    1950:   PetscLayoutSetBlockSize(B->cmap,bs);
    1951:   PetscLayoutSetUp(B->rmap);
    1952:   PetscLayoutSetUp(B->cmap);
    1953:   PetscLayoutGetBlockSize(B->rmap,&bs);
    1954:   m      = B->rmap->n/bs;
    1955:   rstart = B->rmap->rstart/bs;
    1956:   cend   = B->cmap->rend/bs;

    1959:   PetscMalloc2(m,&d_nnz,m,&o_nnz);
    1960:   for (i=0; i<m; i++) {
    1961:     nz = ii[i+1] - ii[i];
    1963:     /* count the ones on the diagonal and above, split into diagonal and off diagonal portions. */
    1964:     JJ     = jj + ii[i];
    1965:     bd     = 0;
    1966:     for (j=0; j<nz; j++) {
    1967:       if (*JJ >= i + rstart) break;
    1968:       JJ++;
    1969:       bd++;
    1970:     }
    1971:     d  = 0;
    1972:     for (; j<nz; j++) {
    1973:       if (*JJ++ >= cend) break;
    1974:       d++;
    1975:     }
    1976:     d_nnz[i] = d;
    1977:     o_nnz[i] = nz - d - bd;
    1978:     nz       = nz - bd;
    1979:     nz_max = PetscMax(nz_max,nz);
    1980:   }
    1981:   MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
    1982:   MatSetOption(B,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);
    1983:   PetscFree2(d_nnz,o_nnz);

    1985:   values = (PetscScalar*)V;
    1986:   if (!values) {
    1987:     PetscCalloc1(bs*bs*nz_max,&values);
    1988:   }
    1989:   for (i=0; i<m; i++) {
    1990:     PetscInt          row    = i + rstart;
    1991:     PetscInt          ncols  = ii[i+1] - ii[i];
    1992:     const PetscInt    *icols = jj + ii[i];
    1993:     if (bs == 1 || !roworiented) {         /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */
    1994:       const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
    1995:       MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
    1996:     } else {                    /* block ordering does not match so we can only insert one block at a time. */
    1997:       PetscInt j;
    1998:       for (j=0; j<ncols; j++) {
    1999:         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
    2000:         MatSetValuesBlocked_MPISBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);
    2001:       }
    2002:     }
    2003:   }

    2005:   if (!V) PetscFree(values);
    2006:   nooffprocentries    = B->nooffprocentries;
    2007:   B->nooffprocentries = PETSC_TRUE;
    2008:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    2009:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    2010:   B->nooffprocentries = nooffprocentries;

    2012:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    2013:   return 0;
    2014: }

    2016: /*MC
    2017:    MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
    2018:    based on block compressed sparse row format.  Only the upper triangular portion of the "diagonal" portion of
    2019:    the matrix is stored.

    2021:    For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
    2022:    can call MatSetOption(Mat, MAT_HERMITIAN);

    2024:    Options Database Keys:
    2025: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()

    2027:    Notes:
    2028:      The number of rows in the matrix must be less than or equal to the number of columns. Similarly the number of rows in the
    2029:      diagonal portion of the matrix of each process has to less than or equal the number of columns.

    2031:    Level: beginner

    2033: .seealso: MatCreateBAIJ(), MATSEQSBAIJ, MatType
    2034: M*/

    2036: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
    2037: {
    2038:   Mat_MPISBAIJ   *b;
    2040:   PetscBool      flg = PETSC_FALSE;

    2042:   PetscNewLog(B,&b);
    2043:   B->data = (void*)b;
    2044:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

    2046:   B->ops->destroy = MatDestroy_MPISBAIJ;
    2047:   B->ops->view    = MatView_MPISBAIJ;
    2048:   B->assembled    = PETSC_FALSE;
    2049:   B->insertmode   = NOT_SET_VALUES;

    2051:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
    2052:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

    2054:   /* build local table of row and column ownerships */
    2055:   PetscMalloc1(b->size+2,&b->rangebs);

    2057:   /* build cache for off array entries formed */
    2058:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

    2060:   b->donotstash  = PETSC_FALSE;
    2061:   b->colmap      = NULL;
    2062:   b->garray      = NULL;
    2063:   b->roworiented = PETSC_TRUE;

    2065:   /* stuff used in block assembly */
    2066:   b->barray = NULL;

    2068:   /* stuff used for matrix vector multiply */
    2069:   b->lvec    = NULL;
    2070:   b->Mvctx   = NULL;
    2071:   b->slvec0  = NULL;
    2072:   b->slvec0b = NULL;
    2073:   b->slvec1  = NULL;
    2074:   b->slvec1a = NULL;
    2075:   b->slvec1b = NULL;
    2076:   b->sMvctx  = NULL;

    2078:   /* stuff for MatGetRow() */
    2079:   b->rowindices   = NULL;
    2080:   b->rowvalues    = NULL;
    2081:   b->getrowactive = PETSC_FALSE;

    2083:   /* hash table stuff */
    2084:   b->ht           = NULL;
    2085:   b->hd           = NULL;
    2086:   b->ht_size      = 0;
    2087:   b->ht_flag      = PETSC_FALSE;
    2088:   b->ht_fact      = 0;
    2089:   b->ht_total_ct  = 0;
    2090:   b->ht_insert_ct = 0;

    2092:   /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
    2093:   b->ijonly = PETSC_FALSE;

    2095:   b->in_loc = NULL;
    2096:   b->v_loc  = NULL;
    2097:   b->n_loc  = 0;

    2099:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);
    2100:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);
    2101:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);
    2102:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
    2103: #if defined(PETSC_HAVE_ELEMENTAL)
    2104:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_elemental_C",MatConvert_MPISBAIJ_Elemental);
    2105: #endif
    2106: #if defined(PETSC_HAVE_SCALAPACK)
    2107:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_scalapack_C",MatConvert_SBAIJ_ScaLAPACK);
    2108: #endif
    2109:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpiaij_C",MatConvert_MPISBAIJ_Basic);
    2110:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpibaij_C",MatConvert_MPISBAIJ_Basic);

    2112:   B->symmetric                  = PETSC_TRUE;
    2113:   B->structurally_symmetric     = PETSC_TRUE;
    2114:   B->symmetric_set              = PETSC_TRUE;
    2115:   B->structurally_symmetric_set = PETSC_TRUE;
    2116:   B->symmetric_eternal          = PETSC_TRUE;
    2117: #if defined(PETSC_USE_COMPLEX)
    2118:   B->hermitian                  = PETSC_FALSE;
    2119:   B->hermitian_set              = PETSC_FALSE;
    2120: #else
    2121:   B->hermitian                  = PETSC_TRUE;
    2122:   B->hermitian_set              = PETSC_TRUE;
    2123: #endif

    2125:   PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
    2126:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");
    2127:   PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);
    2128:   if (flg) {
    2129:     PetscReal fact = 1.39;
    2130:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
    2131:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
    2132:     if (fact <= 1.0) fact = 1.39;
    2133:     MatMPIBAIJSetHashTableFactor(B,fact);
    2134:     PetscInfo(B,"Hash table Factor used %5.2g\n",(double)fact);
    2135:   }
    2136:   PetscOptionsEnd();
    2137:   return 0;
    2138: }

    2140: /*MC
    2141:    MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.

    2143:    This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
    2144:    and MATMPISBAIJ otherwise.

    2146:    Options Database Keys:
    2147: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()

    2149:   Level: beginner

    2151: .seealso: MatCreateSBAIJ, MATSEQSBAIJ, MATMPISBAIJ
    2152: M*/

    2154: /*@C
    2155:    MatMPISBAIJSetPreallocation - For good matrix assembly performance
    2156:    the user should preallocate the matrix storage by setting the parameters
    2157:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    2158:    performance can be increased by more than a factor of 50.

    2160:    Collective on Mat

    2162:    Input Parameters:
    2163: +  B - the matrix
    2164: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    2165:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    2166: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
    2167:            submatrix  (same for all local rows)
    2168: .  d_nnz - array containing the number of block nonzeros in the various block rows
    2169:            in the upper triangular and diagonal part of the in diagonal portion of the local
    2170:            (possibly different for each block row) or NULL.  If you plan to factor the matrix you must leave room
    2171:            for the diagonal entry and set a value even if it is zero.
    2172: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
    2173:            submatrix (same for all local rows).
    2174: -  o_nnz - array containing the number of nonzeros in the various block rows of the
    2175:            off-diagonal portion of the local submatrix that is right of the diagonal
    2176:            (possibly different for each block row) or NULL.

    2178:    Options Database Keys:
    2179: +   -mat_no_unroll - uses code that does not unroll the loops in the
    2180:                      block calculations (much slower)
    2181: -   -mat_block_size - size of the blocks to use

    2183:    Notes:

    2185:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
    2186:    than it must be used on all processors that share the object for that argument.

    2188:    If the *_nnz parameter is given then the *_nz parameter is ignored

    2190:    Storage Information:
    2191:    For a square global matrix we define each processor's diagonal portion
    2192:    to be its local rows and the corresponding columns (a square submatrix);
    2193:    each processor's off-diagonal portion encompasses the remainder of the
    2194:    local matrix (a rectangular submatrix).

    2196:    The user can specify preallocated storage for the diagonal part of
    2197:    the local submatrix with either d_nz or d_nnz (not both).  Set
    2198:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
    2199:    memory allocation.  Likewise, specify preallocated storage for the
    2200:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

    2202:    You can call MatGetInfo() to get information on how effective the preallocation was;
    2203:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
    2204:    You can also run with the option -info and look for messages with the string
    2205:    malloc in them to see if additional memory allocation was needed.

    2207:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
    2208:    the figure below we depict these three local rows and all columns (0-11).

    2210: .vb
    2211:            0 1 2 3 4 5 6 7 8 9 10 11
    2212:           --------------------------
    2213:    row 3  |. . . d d d o o o o  o  o
    2214:    row 4  |. . . d d d o o o o  o  o
    2215:    row 5  |. . . d d d o o o o  o  o
    2216:           --------------------------
    2217: .ve

    2219:    Thus, any entries in the d locations are stored in the d (diagonal)
    2220:    submatrix, and any entries in the o locations are stored in the
    2221:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
    2222:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

    2224:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
    2225:    plus the diagonal part of the d matrix,
    2226:    and o_nz should indicate the number of block nonzeros per row in the o matrix

    2228:    In general, for PDE problems in which most nonzeros are near the diagonal,
    2229:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
    2230:    or you will get TERRIBLE performance; see the users' manual chapter on
    2231:    matrices.

    2233:    Level: intermediate

    2235: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
    2236: @*/
    2237: PetscErrorCode  MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
    2238: {
    2242:   PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
    2243:   return 0;
    2244: }

    2246: /*@C
    2247:    MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
    2248:    (block compressed row).  For good matrix assembly performance
    2249:    the user should preallocate the matrix storage by setting the parameters
    2250:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    2251:    performance can be increased by more than a factor of 50.

    2253:    Collective

    2255:    Input Parameters:
    2256: +  comm - MPI communicator
    2257: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    2258:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    2259: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
    2260:            This value should be the same as the local size used in creating the
    2261:            y vector for the matrix-vector product y = Ax.
    2262: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
    2263:            This value should be the same as the local size used in creating the
    2264:            x vector for the matrix-vector product y = Ax.
    2265: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    2266: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    2267: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
    2268:            submatrix  (same for all local rows)
    2269: .  d_nnz - array containing the number of block nonzeros in the various block rows
    2270:            in the upper triangular portion of the in diagonal portion of the local
    2271:            (possibly different for each block block row) or NULL.
    2272:            If you plan to factor the matrix you must leave room for the diagonal entry and
    2273:            set its value even if it is zero.
    2274: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
    2275:            submatrix (same for all local rows).
    2276: -  o_nnz - array containing the number of nonzeros in the various block rows of the
    2277:            off-diagonal portion of the local submatrix (possibly different for
    2278:            each block row) or NULL.

    2280:    Output Parameter:
    2281: .  A - the matrix

    2283:    Options Database Keys:
    2284: +   -mat_no_unroll - uses code that does not unroll the loops in the
    2285:                      block calculations (much slower)
    2286: .   -mat_block_size - size of the blocks to use
    2287: -   -mat_mpi - use the parallel matrix data structures even on one processor
    2288:                (defaults to using SeqBAIJ format on one processor)

    2290:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
    2291:    MatXXXXSetPreallocation() paradigm instead of this routine directly.
    2292:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

    2294:    Notes:
    2295:    The number of rows and columns must be divisible by blocksize.
    2296:    This matrix type does not support complex Hermitian operation.

    2298:    The user MUST specify either the local or global matrix dimensions
    2299:    (possibly both).

    2301:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
    2302:    than it must be used on all processors that share the object for that argument.

    2304:    If the *_nnz parameter is given then the *_nz parameter is ignored

    2306:    Storage Information:
    2307:    For a square global matrix we define each processor's diagonal portion
    2308:    to be its local rows and the corresponding columns (a square submatrix);
    2309:    each processor's off-diagonal portion encompasses the remainder of the
    2310:    local matrix (a rectangular submatrix).

    2312:    The user can specify preallocated storage for the diagonal part of
    2313:    the local submatrix with either d_nz or d_nnz (not both).  Set
    2314:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
    2315:    memory allocation.  Likewise, specify preallocated storage for the
    2316:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

    2318:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
    2319:    the figure below we depict these three local rows and all columns (0-11).

    2321: .vb
    2322:            0 1 2 3 4 5 6 7 8 9 10 11
    2323:           --------------------------
    2324:    row 3  |. . . d d d o o o o  o  o
    2325:    row 4  |. . . d d d o o o o  o  o
    2326:    row 5  |. . . d d d o o o o  o  o
    2327:           --------------------------
    2328: .ve

    2330:    Thus, any entries in the d locations are stored in the d (diagonal)
    2331:    submatrix, and any entries in the o locations are stored in the
    2332:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
    2333:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

    2335:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
    2336:    plus the diagonal part of the d matrix,
    2337:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
    2338:    In general, for PDE problems in which most nonzeros are near the diagonal,
    2339:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
    2340:    or you will get TERRIBLE performance; see the users' manual chapter on
    2341:    matrices.

    2343:    Level: intermediate

    2345: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
    2346: @*/

    2348: 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)
    2349: {
    2350:   PetscMPIInt    size;

    2352:   MatCreate(comm,A);
    2353:   MatSetSizes(*A,m,n,M,N);
    2354:   MPI_Comm_size(comm,&size);
    2355:   if (size > 1) {
    2356:     MatSetType(*A,MATMPISBAIJ);
    2357:     MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
    2358:   } else {
    2359:     MatSetType(*A,MATSEQSBAIJ);
    2360:     MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
    2361:   }
    2362:   return 0;
    2363: }

    2365: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
    2366: {
    2367:   Mat            mat;
    2368:   Mat_MPISBAIJ   *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
    2369:   PetscInt       len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
    2370:   PetscScalar    *array;

    2372:   *newmat = NULL;

    2374:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
    2375:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
    2376:   MatSetType(mat,((PetscObject)matin)->type_name);
    2377:   PetscLayoutReference(matin->rmap,&mat->rmap);
    2378:   PetscLayoutReference(matin->cmap,&mat->cmap);

    2380:   mat->factortype   = matin->factortype;
    2381:   mat->preallocated = PETSC_TRUE;
    2382:   mat->assembled    = PETSC_TRUE;
    2383:   mat->insertmode   = NOT_SET_VALUES;

    2385:   a      = (Mat_MPISBAIJ*)mat->data;
    2386:   a->bs2 = oldmat->bs2;
    2387:   a->mbs = oldmat->mbs;
    2388:   a->nbs = oldmat->nbs;
    2389:   a->Mbs = oldmat->Mbs;
    2390:   a->Nbs = oldmat->Nbs;

    2392:   a->size         = oldmat->size;
    2393:   a->rank         = oldmat->rank;
    2394:   a->donotstash   = oldmat->donotstash;
    2395:   a->roworiented  = oldmat->roworiented;
    2396:   a->rowindices   = NULL;
    2397:   a->rowvalues    = NULL;
    2398:   a->getrowactive = PETSC_FALSE;
    2399:   a->barray       = NULL;
    2400:   a->rstartbs     = oldmat->rstartbs;
    2401:   a->rendbs       = oldmat->rendbs;
    2402:   a->cstartbs     = oldmat->cstartbs;
    2403:   a->cendbs       = oldmat->cendbs;

    2405:   /* hash table stuff */
    2406:   a->ht           = NULL;
    2407:   a->hd           = NULL;
    2408:   a->ht_size      = 0;
    2409:   a->ht_flag      = oldmat->ht_flag;
    2410:   a->ht_fact      = oldmat->ht_fact;
    2411:   a->ht_total_ct  = 0;
    2412:   a->ht_insert_ct = 0;

    2414:   PetscArraycpy(a->rangebs,oldmat->rangebs,a->size+2);
    2415:   if (oldmat->colmap) {
    2416: #if defined(PETSC_USE_CTABLE)
    2417:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
    2418: #else
    2419:     PetscMalloc1(a->Nbs,&a->colmap);
    2420:     PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
    2421:     PetscArraycpy(a->colmap,oldmat->colmap,a->Nbs);
    2422: #endif
    2423:   } else a->colmap = NULL;

    2425:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
    2426:     PetscMalloc1(len,&a->garray);
    2427:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
    2428:     PetscArraycpy(a->garray,oldmat->garray,len);
    2429:   } else a->garray = NULL;

    2431:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
    2432:   VecDuplicate(oldmat->lvec,&a->lvec);
    2433:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
    2434:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
    2435:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

    2437:   VecDuplicate(oldmat->slvec0,&a->slvec0);
    2438:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
    2439:   VecDuplicate(oldmat->slvec1,&a->slvec1);
    2440:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);

    2442:   VecGetLocalSize(a->slvec1,&nt);
    2443:   VecGetArray(a->slvec1,&array);
    2444:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);
    2445:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
    2446:   VecRestoreArray(a->slvec1,&array);
    2447:   VecGetArray(a->slvec0,&array);
    2448:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
    2449:   VecRestoreArray(a->slvec0,&array);
    2450:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
    2451:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
    2452:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);
    2453:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);
    2454:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);

    2456:   /* VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
    2457:   PetscObjectReference((PetscObject)oldmat->sMvctx);
    2458:   a->sMvctx = oldmat->sMvctx;
    2459:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);

    2461:   MatDuplicate(oldmat->A,cpvalues,&a->A);
    2462:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
    2463:   MatDuplicate(oldmat->B,cpvalues,&a->B);
    2464:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
    2465:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
    2466:   *newmat = mat;
    2467:   return 0;
    2468: }

    2470: /* Used for both MPIBAIJ and MPISBAIJ matrices */
    2471: #define MatLoad_MPISBAIJ_Binary MatLoad_MPIBAIJ_Binary

    2473: PetscErrorCode MatLoad_MPISBAIJ(Mat mat,PetscViewer viewer)
    2474: {
    2475:   PetscBool      isbinary;

    2477:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    2479:   MatLoad_MPISBAIJ_Binary(mat,viewer);
    2480:   return 0;
    2481: }

    2483: /*XXXXX@
    2484:    MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

    2486:    Input Parameters:
    2487: .  mat  - the matrix
    2488: .  fact - factor

    2490:    Not Collective on Mat, each process can have a different hash factor

    2492:    Level: advanced

    2494:   Notes:
    2495:    This can also be set by the command line option: -mat_use_hash_table fact

    2497: .seealso: MatSetOption()
    2498: @XXXXX*/

    2500: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
    2501: {
    2502:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
    2503:   Mat_SeqBAIJ    *b = (Mat_SeqBAIJ*)(a->B)->data;
    2504:   PetscReal      atmp;
    2505:   PetscReal      *work,*svalues,*rvalues;
    2506:   PetscInt       i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
    2507:   PetscMPIInt    rank,size;
    2508:   PetscInt       *rowners_bs,dest,count,source;
    2509:   PetscScalar    *va;
    2510:   MatScalar      *ba;
    2511:   MPI_Status     stat;

    2514:   MatGetRowMaxAbs(a->A,v,NULL);
    2515:   VecGetArray(v,&va);

    2517:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
    2518:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

    2520:   bs  = A->rmap->bs;
    2521:   mbs = a->mbs;
    2522:   Mbs = a->Mbs;
    2523:   ba  = b->a;
    2524:   bi  = b->i;
    2525:   bj  = b->j;

    2527:   /* find ownerships */
    2528:   rowners_bs = A->rmap->range;

    2530:   /* each proc creates an array to be distributed */
    2531:   PetscCalloc1(bs*Mbs,&work);

    2533:   /* row_max for B */
    2534:   if (rank != size-1) {
    2535:     for (i=0; i<mbs; i++) {
    2536:       ncols = bi[1] - bi[0]; bi++;
    2537:       brow  = bs*i;
    2538:       for (j=0; j<ncols; j++) {
    2539:         bcol = bs*(*bj);
    2540:         for (kcol=0; kcol<bs; kcol++) {
    2541:           col  = bcol + kcol;                /* local col index */
    2542:           col += rowners_bs[rank+1];      /* global col index */
    2543:           for (krow=0; krow<bs; krow++) {
    2544:             atmp = PetscAbsScalar(*ba); ba++;
    2545:             row  = brow + krow;   /* local row index */
    2546:             if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
    2547:             if (work[col] < atmp) work[col] = atmp;
    2548:           }
    2549:         }
    2550:         bj++;
    2551:       }
    2552:     }

    2554:     /* send values to its owners */
    2555:     for (dest=rank+1; dest<size; dest++) {
    2556:       svalues = work + rowners_bs[dest];
    2557:       count   = rowners_bs[dest+1]-rowners_bs[dest];
    2558:       MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));
    2559:     }
    2560:   }

    2562:   /* receive values */
    2563:   if (rank) {
    2564:     rvalues = work;
    2565:     count   = rowners_bs[rank+1]-rowners_bs[rank];
    2566:     for (source=0; source<rank; source++) {
    2567:       MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);
    2568:       /* process values */
    2569:       for (i=0; i<count; i++) {
    2570:         if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
    2571:       }
    2572:     }
    2573:   }

    2575:   VecRestoreArray(v,&va);
    2576:   PetscFree(work);
    2577:   return 0;
    2578: }

    2580: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    2581: {
    2582:   Mat_MPISBAIJ      *mat = (Mat_MPISBAIJ*)matin->data;
    2583:   PetscInt          mbs=mat->mbs,bs=matin->rmap->bs;
    2584:   PetscScalar       *x,*ptr,*from;
    2585:   Vec               bb1;
    2586:   const PetscScalar *b;

    2591:   if (flag == SOR_APPLY_UPPER) {
    2592:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2593:     return 0;
    2594:   }

    2596:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
    2597:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    2598:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
    2599:       its--;
    2600:     }

    2602:     VecDuplicate(bb,&bb1);
    2603:     while (its--) {

    2605:       /* lower triangular part: slvec0b = - B^T*xx */
    2606:       (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);

    2608:       /* copy xx into slvec0a */
    2609:       VecGetArray(mat->slvec0,&ptr);
    2610:       VecGetArray(xx,&x);
    2611:       PetscArraycpy(ptr,x,bs*mbs);
    2612:       VecRestoreArray(mat->slvec0,&ptr);

    2614:       VecScale(mat->slvec0,-1.0);

    2616:       /* copy bb into slvec1a */
    2617:       VecGetArray(mat->slvec1,&ptr);
    2618:       VecGetArrayRead(bb,&b);
    2619:       PetscArraycpy(ptr,b,bs*mbs);
    2620:       VecRestoreArray(mat->slvec1,&ptr);

    2622:       /* set slvec1b = 0 */
    2623:       VecSet(mat->slvec1b,0.0);

    2625:       VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
    2626:       VecRestoreArray(xx,&x);
    2627:       VecRestoreArrayRead(bb,&b);
    2628:       VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);

    2630:       /* upper triangular part: bb1 = bb1 - B*x */
    2631:       (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);

    2633:       /* local diagonal sweep */
    2634:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
    2635:     }
    2636:     VecDestroy(&bb1);
    2637:   } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
    2638:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2639:   } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
    2640:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2641:   } else if (flag & SOR_EISENSTAT) {
    2642:     Vec               xx1;
    2643:     PetscBool         hasop;
    2644:     const PetscScalar *diag;
    2645:     PetscScalar       *sl,scale = (omega - 2.0)/omega;
    2646:     PetscInt          i,n;

    2648:     if (!mat->xx1) {
    2649:       VecDuplicate(bb,&mat->xx1);
    2650:       VecDuplicate(bb,&mat->bb1);
    2651:     }
    2652:     xx1 = mat->xx1;
    2653:     bb1 = mat->bb1;

    2655:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

    2657:     if (!mat->diag) {
    2658:       /* this is wrong for same matrix with new nonzero values */
    2659:       MatCreateVecs(matin,&mat->diag,NULL);
    2660:       MatGetDiagonal(matin,mat->diag);
    2661:     }
    2662:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);

    2664:     if (hasop) {
    2665:       MatMultDiagonalBlock(matin,xx,bb1);
    2666:       VecAYPX(mat->slvec1a,scale,bb);
    2667:     } else {
    2668:       /*
    2669:           These two lines are replaced by code that may be a bit faster for a good compiler
    2670:       VecPointwiseMult(mat->slvec1a,mat->diag,xx);
    2671:       VecAYPX(mat->slvec1a,scale,bb);
    2672:       */
    2673:       VecGetArray(mat->slvec1a,&sl);
    2674:       VecGetArrayRead(mat->diag,&diag);
    2675:       VecGetArrayRead(bb,&b);
    2676:       VecGetArray(xx,&x);
    2677:       VecGetLocalSize(xx,&n);
    2678:       if (omega == 1.0) {
    2679:         for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
    2680:         PetscLogFlops(2.0*n);
    2681:       } else {
    2682:         for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
    2683:         PetscLogFlops(3.0*n);
    2684:       }
    2685:       VecRestoreArray(mat->slvec1a,&sl);
    2686:       VecRestoreArrayRead(mat->diag,&diag);
    2687:       VecRestoreArrayRead(bb,&b);
    2688:       VecRestoreArray(xx,&x);
    2689:     }

    2691:     /* multiply off-diagonal portion of matrix */
    2692:     VecSet(mat->slvec1b,0.0);
    2693:     (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
    2694:     VecGetArray(mat->slvec0,&from);
    2695:     VecGetArray(xx,&x);
    2696:     PetscArraycpy(from,x,bs*mbs);
    2697:     VecRestoreArray(mat->slvec0,&from);
    2698:     VecRestoreArray(xx,&x);
    2699:     VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
    2700:     VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
    2701:     (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);

    2703:     /* local sweep */
    2704:     (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
    2705:     VecAXPY(xx,1.0,xx1);
    2706:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
    2707:   return 0;
    2708: }

    2710: /*@
    2711:      MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
    2712:          CSR format the local rows.

    2714:    Collective

    2716:    Input Parameters:
    2717: +  comm - MPI communicator
    2718: .  bs - the block size, only a block size of 1 is supported
    2719: .  m - number of local rows (Cannot be PETSC_DECIDE)
    2720: .  n - This value should be the same as the local size used in creating the
    2721:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
    2722:        calculated if N is given) For square matrices n is almost always m.
    2723: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    2724: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    2725: .   i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of block elements in that row block row of the matrix
    2726: .   j - column indices
    2727: -   a - matrix values

    2729:    Output Parameter:
    2730: .   mat - the matrix

    2732:    Level: intermediate

    2734:    Notes:
    2735:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
    2736:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
    2737:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

    2739:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

    2741: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
    2742:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
    2743: @*/
    2744: 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)
    2745: {
    2748:   MatCreate(comm,mat);
    2749:   MatSetSizes(*mat,m,n,M,N);
    2750:   MatSetType(*mat,MATMPISBAIJ);
    2751:   MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
    2752:   return 0;
    2753: }

    2755: /*@C
    2756:    MatMPISBAIJSetPreallocationCSR - Creates a sparse parallel matrix in SBAIJ format using the given nonzero structure and (optional) numerical values

    2758:    Collective

    2760:    Input Parameters:
    2761: +  B - the matrix
    2762: .  bs - the block size
    2763: .  i - the indices into j for the start of each local row (starts with zero)
    2764: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
    2765: -  v - optional values in the matrix

    2767:    Level: advanced

    2769:    Notes:
    2770:    Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
    2771:    and usually the numerical values as well

    2773:    Any entries below the diagonal are ignored

    2775: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
    2776: @*/
    2777: PetscErrorCode  MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
    2778: {
    2779:   PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
    2780:   return 0;
    2781: }

    2783: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
    2784: {
    2786:   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
    2787:   PetscInt       *indx;
    2788:   PetscScalar    *values;

    2790:   MatGetSize(inmat,&m,&N);
    2791:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
    2792:     Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)inmat->data;
    2793:     PetscInt       *dnz,*onz,mbs,Nbs,nbs;
    2794:     PetscInt       *bindx,rmax=a->rmax,j;
    2795:     PetscMPIInt    rank,size;

    2797:     MatGetBlockSizes(inmat,&bs,&cbs);
    2798:     mbs = m/bs; Nbs = N/cbs;
    2799:     if (n == PETSC_DECIDE) {
    2800:       PetscSplitOwnershipBlock(comm,cbs,&n,&N);
    2801:     }
    2802:     nbs = n/cbs;

    2804:     PetscMalloc1(rmax,&bindx);
    2805:     MatPreallocateInitialize(comm,mbs,nbs,dnz,onz); /* inline function, output __end and __rstart are used below */

    2807:     MPI_Comm_rank(comm,&rank);
    2808:     MPI_Comm_rank(comm,&size);
    2809:     if (rank == size-1) {
    2810:       /* Check sum(nbs) = Nbs */
    2812:     }

    2814:     rstart = __rstart; /* block rstart of *outmat; see inline function MatPreallocateInitialize */
    2815:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
    2816:     for (i=0; i<mbs; i++) {
    2817:       MatGetRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
    2818:       nnz  = nnz/bs;
    2819:       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
    2820:       MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
    2821:       MatRestoreRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);
    2822:     }
    2823:     MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
    2824:     PetscFree(bindx);

    2826:     MatCreate(comm,outmat);
    2827:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
    2828:     MatSetBlockSizes(*outmat,bs,cbs);
    2829:     MatSetType(*outmat,MATSBAIJ);
    2830:     MatSeqSBAIJSetPreallocation(*outmat,bs,0,dnz);
    2831:     MatMPISBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
    2832:     MatPreallocateFinalize(dnz,onz);
    2833:   }

    2835:   /* numeric phase */
    2836:   MatGetBlockSizes(inmat,&bs,&cbs);
    2837:   MatGetOwnershipRange(*outmat,&rstart,NULL);

    2839:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
    2840:   for (i=0; i<m; i++) {
    2841:     MatGetRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
    2842:     Ii   = i + rstart;
    2843:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
    2844:     MatRestoreRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
    2845:   }
    2846:   MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
    2847:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
    2848:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
    2849:   return 0;
    2850: }