Actual source code: mpibaij.c
petsc-3.10.5 2019-03-28
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      2:  #include <../src/mat/impls/baij/mpi/mpibaij.h>

      4:  #include <petscblaslapack.h>
      5:  #include <petscsf.h>

      7: #if defined(PETSC_HAVE_HYPRE)
      8: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
      9: #endif

     11: PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[])
     12: {
     13:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
     15:   PetscInt       i,*idxb = 0;
     16:   PetscScalar    *va,*vb;
     17:   Vec            vtmp;

     20:   MatGetRowMaxAbs(a->A,v,idx);
     21:   VecGetArray(v,&va);
     22:   if (idx) {
     23:     for (i=0; i<A->rmap->n; i++) {
     24:       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
     25:     }
     26:   }

     28:   VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
     29:   if (idx) {PetscMalloc1(A->rmap->n,&idxb);}
     30:   MatGetRowMaxAbs(a->B,vtmp,idxb);
     31:   VecGetArray(vtmp,&vb);

     33:   for (i=0; i<A->rmap->n; i++) {
     34:     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
     35:       va[i] = vb[i];
     36:       if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs);
     37:     }
     38:   }

     40:   VecRestoreArray(v,&va);
     41:   VecRestoreArray(vtmp,&vb);
     42:   PetscFree(idxb);
     43:   VecDestroy(&vtmp);
     44:   return(0);
     45: }

     47: PetscErrorCode  MatStoreValues_MPIBAIJ(Mat mat)
     48: {
     49:   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)mat->data;

     53:   MatStoreValues(aij->A);
     54:   MatStoreValues(aij->B);
     55:   return(0);
     56: }

     58: PetscErrorCode  MatRetrieveValues_MPIBAIJ(Mat mat)
     59: {
     60:   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)mat->data;

     64:   MatRetrieveValues(aij->A);
     65:   MatRetrieveValues(aij->B);
     66:   return(0);
     67: }

     69: /*
     70:      Local utility routine that creates a mapping from the global column
     71:    number to the local number in the off-diagonal part of the local
     72:    storage of the matrix.  This is done in a non scalable way since the
     73:    length of colmap equals the global matrix length.
     74: */
     75: PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat)
     76: {
     77:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
     78:   Mat_SeqBAIJ    *B    = (Mat_SeqBAIJ*)baij->B->data;
     80:   PetscInt       nbs = B->nbs,i,bs=mat->rmap->bs;

     83: #if defined(PETSC_USE_CTABLE)
     84:   PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);
     85:   for (i=0; i<nbs; i++) {
     86:     PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);
     87:   }
     88: #else
     89:   PetscMalloc1(baij->Nbs+1,&baij->colmap);
     90:   PetscLogObjectMemory((PetscObject)mat,baij->Nbs*sizeof(PetscInt));
     91:   PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));
     92:   for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1;
     93: #endif
     94:   return(0);
     95: }

     97: #define  MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,orow,ocol)       \
     98:   { \
     99:  \
    100:     brow = row/bs;  \
    101:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
    102:     rmax = aimax[brow]; nrow = ailen[brow]; \
    103:     bcol = col/bs; \
    104:     ridx = row % bs; cidx = col % bs; \
    105:     low  = 0; high = nrow; \
    106:     while (high-low > 3) { \
    107:       t = (low+high)/2; \
    108:       if (rp[t] > bcol) high = t; \
    109:       else              low  = t; \
    110:     } \
    111:     for (_i=low; _i<high; _i++) { \
    112:       if (rp[_i] > bcol) break; \
    113:       if (rp[_i] == bcol) { \
    114:         bap = ap +  bs2*_i + bs*cidx + ridx; \
    115:         if (addv == ADD_VALUES) *bap += value;  \
    116:         else                    *bap  = value;  \
    117:         goto a_noinsert; \
    118:       } \
    119:     } \
    120:     if (a->nonew == 1) goto a_noinsert; \
    121:     if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
    122:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
    123:     N = nrow++ - 1;  \
    124:     /* shift up all the later entries in this row */ \
    125:     for (ii=N; ii>=_i; ii--) { \
    126:       rp[ii+1] = rp[ii]; \
    127:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
    128:     } \
    129:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); }  \
    130:     rp[_i]                      = bcol;  \
    131:     ap[bs2*_i + bs*cidx + ridx] = value;  \
    132: a_noinsert:; \
    133:     ailen[brow] = nrow; \
    134:   }

    136: #define  MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,orow,ocol)       \
    137:   { \
    138:     brow = row/bs;  \
    139:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
    140:     rmax = bimax[brow]; nrow = bilen[brow]; \
    141:     bcol = col/bs; \
    142:     ridx = row % bs; cidx = col % bs; \
    143:     low  = 0; high = nrow; \
    144:     while (high-low > 3) { \
    145:       t = (low+high)/2; \
    146:       if (rp[t] > bcol) high = t; \
    147:       else              low  = t; \
    148:     } \
    149:     for (_i=low; _i<high; _i++) { \
    150:       if (rp[_i] > bcol) break; \
    151:       if (rp[_i] == bcol) { \
    152:         bap = ap +  bs2*_i + bs*cidx + ridx; \
    153:         if (addv == ADD_VALUES) *bap += value;  \
    154:         else                    *bap  = value;  \
    155:         goto b_noinsert; \
    156:       } \
    157:     } \
    158:     if (b->nonew == 1) goto b_noinsert; \
    159:     if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column  (%D, %D) into matrix", orow, ocol); \
    160:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
    161:     N = nrow++ - 1;  \
    162:     /* shift up all the later entries in this row */ \
    163:     for (ii=N; ii>=_i; ii--) { \
    164:       rp[ii+1] = rp[ii]; \
    165:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
    166:     } \
    167:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));}  \
    168:     rp[_i]                      = bcol;  \
    169:     ap[bs2*_i + bs*cidx + ridx] = value;  \
    170: b_noinsert:; \
    171:     bilen[brow] = nrow; \
    172:   }

    174: PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
    175: {
    176:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
    177:   MatScalar      value;
    178:   PetscBool      roworiented = baij->roworiented;
    180:   PetscInt       i,j,row,col;
    181:   PetscInt       rstart_orig=mat->rmap->rstart;
    182:   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
    183:   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;

    185:   /* Some Variables required in the macro */
    186:   Mat         A     = baij->A;
    187:   Mat_SeqBAIJ *a    = (Mat_SeqBAIJ*)(A)->data;
    188:   PetscInt    *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
    189:   MatScalar   *aa   =a->a;

    191:   Mat         B     = baij->B;
    192:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
    193:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
    194:   MatScalar   *ba   =b->a;

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

    201:   for (i=0; i<m; i++) {
    202:     if (im[i] < 0) continue;
    203: #if defined(PETSC_USE_DEBUG)
    204:     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
    205: #endif
    206:     if (im[i] >= rstart_orig && im[i] < rend_orig) {
    207:       row = im[i] - rstart_orig;
    208:       for (j=0; j<n; j++) {
    209:         if (in[j] >= cstart_orig && in[j] < cend_orig) {
    210:           col = in[j] - cstart_orig;
    211:           if (roworiented) value = v[i*n+j];
    212:           else             value = v[i+j*m];
    213:           MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
    214:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
    215:         } else if (in[j] < 0) continue;
    216: #if defined(PETSC_USE_DEBUG)
    217:         else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);
    218: #endif
    219:         else {
    220:           if (mat->was_assembled) {
    221:             if (!baij->colmap) {
    222:               MatCreateColmap_MPIBAIJ_Private(mat);
    223:             }
    224: #if defined(PETSC_USE_CTABLE)
    225:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
    226:             col  = col - 1;
    227: #else
    228:             col = baij->colmap[in[j]/bs] - 1;
    229: #endif
    230:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
    231:               MatDisAssemble_MPIBAIJ(mat);
    232:               col  =  in[j];
    233:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
    234:               B    = baij->B;
    235:               b    = (Mat_SeqBAIJ*)(B)->data;
    236:               bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
    237:               ba   =b->a;
    238:             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]);
    239:             else col += in[j]%bs;
    240:           } else col = in[j];
    241:           if (roworiented) value = v[i*n+j];
    242:           else             value = v[i+j*m];
    243:           MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
    244:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
    245:         }
    246:       }
    247:     } else {
    248:       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
    249:       if (!baij->donotstash) {
    250:         mat->assembled = PETSC_FALSE;
    251:         if (roworiented) {
    252:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);
    253:         } else {
    254:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);
    255:         }
    256:       }
    257:     }
    258:   }
    259:   return(0);
    260: }

    262: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
    263: {
    264:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    265:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
    266:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
    267:   PetscErrorCode    ierr;
    268:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
    269:   PetscBool         roworiented=a->roworiented;
    270:   const PetscScalar *value     = v;
    271:   MatScalar         *ap,*aa = a->a,*bap;

    274:   rp   = aj + ai[row];
    275:   ap   = aa + bs2*ai[row];
    276:   rmax = imax[row];
    277:   nrow = ailen[row];
    278:   value = v;
    279:   low = 0;
    280:   high = nrow;
    281:   while (high-low > 7) {
    282:     t = (low+high)/2;
    283:     if (rp[t] > col) high = t;
    284:     else             low  = t;
    285:   }
    286:   for (i=low; i<high; i++) {
    287:     if (rp[i] > col) break;
    288:     if (rp[i] == col) {
    289:       bap = ap +  bs2*i;
    290:       if (roworiented) {
    291:         if (is == ADD_VALUES) {
    292:           for (ii=0; ii<bs; ii++) {
    293:             for (jj=ii; jj<bs2; jj+=bs) {
    294:               bap[jj] += *value++;
    295:             }
    296:           }
    297:         } else {
    298:           for (ii=0; ii<bs; ii++) {
    299:             for (jj=ii; jj<bs2; jj+=bs) {
    300:               bap[jj] = *value++;
    301:             }
    302:           }
    303:         }
    304:       } else {
    305:         if (is == ADD_VALUES) {
    306:           for (ii=0; ii<bs; ii++,value+=bs) {
    307:             for (jj=0; jj<bs; jj++) {
    308:               bap[jj] += value[jj];
    309:             }
    310:             bap += bs;
    311:           }
    312:         } else {
    313:           for (ii=0; ii<bs; ii++,value+=bs) {
    314:             for (jj=0; jj<bs; jj++) {
    315:               bap[jj]  = value[jj];
    316:             }
    317:             bap += bs;
    318:           }
    319:         }
    320:       }
    321:       goto noinsert2;
    322:     }
    323:   }
    324:   if (nonew == 1) goto noinsert2;
    325:   if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new global block indexed nonzero block (%D, %D) in the matrix", orow, ocol);
    326:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
    327:   N = nrow++ - 1; high++;
    328:   /* shift up all the later entries in this row */
    329:   for (ii=N; ii>=i; ii--) {
    330:     rp[ii+1] = rp[ii];
    331:     PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
    332:   }
    333:   if (N >= i) {
    334:     PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
    335:   }
    336:   rp[i] = col;
    337:   bap   = ap +  bs2*i;
    338:   if (roworiented) {
    339:     for (ii=0; ii<bs; ii++) {
    340:       for (jj=ii; jj<bs2; jj+=bs) {
    341:         bap[jj] = *value++;
    342:       }
    343:     }
    344:   } else {
    345:     for (ii=0; ii<bs; ii++) {
    346:       for (jj=0; jj<bs; jj++) {
    347:         *bap++ = *value++;
    348:       }
    349:     }
    350:   }
    351:   noinsert2:;
    352:   ailen[row] = nrow;
    353:   return(0);
    354: }

    356: /*
    357:     This routine should be optimized so that the block copy at ** Here a copy is required ** below is not needed
    358:     by passing additional stride information into the MatSetValuesBlocked_SeqBAIJ_Inlined() routine
    359: */
    360: PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
    361: {
    362:   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
    363:   const PetscScalar *value;
    364:   MatScalar         *barray     = baij->barray;
    365:   PetscBool         roworiented = baij->roworiented;
    366:   PetscErrorCode    ierr;
    367:   PetscInt          i,j,ii,jj,row,col,rstart=baij->rstartbs;
    368:   PetscInt          rend=baij->rendbs,cstart=baij->cstartbs,stepval;
    369:   PetscInt          cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;

    372:   if (!barray) {
    373:     PetscMalloc1(bs2,&barray);
    374:     baij->barray = barray;
    375:   }

    377:   if (roworiented) stepval = (n-1)*bs;
    378:   else stepval = (m-1)*bs;

    380:   for (i=0; i<m; i++) {
    381:     if (im[i] < 0) continue;
    382: #if defined(PETSC_USE_DEBUG)
    383:     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed row too large %D max %D",im[i],baij->Mbs-1);
    384: #endif
    385:     if (im[i] >= rstart && im[i] < rend) {
    386:       row = im[i] - rstart;
    387:       for (j=0; j<n; j++) {
    388:         /* If NumCol = 1 then a copy is not required */
    389:         if ((roworiented) && (n == 1)) {
    390:           barray = (MatScalar*)v + i*bs2;
    391:         } else if ((!roworiented) && (m == 1)) {
    392:           barray = (MatScalar*)v + j*bs2;
    393:         } else { /* Here a copy is required */
    394:           if (roworiented) {
    395:             value = v + (i*(stepval+bs) + j)*bs;
    396:           } else {
    397:             value = v + (j*(stepval+bs) + i)*bs;
    398:           }
    399:           for (ii=0; ii<bs; ii++,value+=bs+stepval) {
    400:             for (jj=0; jj<bs; jj++) barray[jj] = value[jj];
    401:             barray += bs;
    402:           }
    403:           barray -= bs2;
    404:         }

    406:         if (in[j] >= cstart && in[j] < cend) {
    407:           col  = in[j] - cstart;
    408:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
    409:         } else if (in[j] < 0) continue;
    410: #if defined(PETSC_USE_DEBUG)
    411:         else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed column too large %D max %D",in[j],baij->Nbs-1);
    412: #endif
    413:         else {
    414:           if (mat->was_assembled) {
    415:             if (!baij->colmap) {
    416:               MatCreateColmap_MPIBAIJ_Private(mat);
    417:             }

    419: #if defined(PETSC_USE_DEBUG)
    420: #if defined(PETSC_USE_CTABLE)
    421:             { PetscInt data;
    422:               PetscTableFind(baij->colmap,in[j]+1,&data);
    423:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    424:             }
    425: #else
    426:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    427: #endif
    428: #endif
    429: #if defined(PETSC_USE_CTABLE)
    430:             PetscTableFind(baij->colmap,in[j]+1,&col);
    431:             col  = (col - 1)/bs;
    432: #else
    433:             col = (baij->colmap[in[j]] - 1)/bs;
    434: #endif
    435:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
    436:               MatDisAssemble_MPIBAIJ(mat);
    437:               col  =  in[j];
    438:             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new blocked indexed nonzero block (%D, %D) into matrix",im[i],in[j]);
    439:           } else col = in[j];
    440:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
    441:         }
    442:       }
    443:     } else {
    444:       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process block indexed row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
    445:       if (!baij->donotstash) {
    446:         if (roworiented) {
    447:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    448:         } else {
    449:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    450:         }
    451:       }
    452:     }
    453:   }
    454:   return(0);
    455: }

    457: #define HASH_KEY 0.6180339887
    458: #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp)))
    459: /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
    460: /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
    461: PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
    462: {
    463:   Mat_MPIBAIJ    *baij       = (Mat_MPIBAIJ*)mat->data;
    464:   PetscBool      roworiented = baij->roworiented;
    466:   PetscInt       i,j,row,col;
    467:   PetscInt       rstart_orig=mat->rmap->rstart;
    468:   PetscInt       rend_orig  =mat->rmap->rend,Nbs=baij->Nbs;
    469:   PetscInt       h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx;
    470:   PetscReal      tmp;
    471:   MatScalar      **HD = baij->hd,value;
    472: #if defined(PETSC_USE_DEBUG)
    473:   PetscInt       total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
    474: #endif

    477:   for (i=0; i<m; i++) {
    478: #if defined(PETSC_USE_DEBUG)
    479:     if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row");
    480:     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
    481: #endif
    482:     row = im[i];
    483:     if (row >= rstart_orig && row < rend_orig) {
    484:       for (j=0; j<n; j++) {
    485:         col = in[j];
    486:         if (roworiented) value = v[i*n+j];
    487:         else             value = v[i+j*m];
    488:         /* Look up PetscInto the Hash Table */
    489:         key = (row/bs)*Nbs+(col/bs)+1;
    490:         h1  = HASH(size,key,tmp);

    493:         idx = h1;
    494: #if defined(PETSC_USE_DEBUG)
    495:         insert_ct++;
    496:         total_ct++;
    497:         if (HT[idx] != key) {
    498:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
    499:           if (idx == size) {
    500:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
    501:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
    502:           }
    503:         }
    504: #else
    505:         if (HT[idx] != key) {
    506:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
    507:           if (idx == size) {
    508:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
    509:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
    510:           }
    511:         }
    512: #endif
    513:         /* A HASH table entry is found, so insert the values at the correct address */
    514:         if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value;
    515:         else                    *(HD[idx]+ (col % bs)*bs + (row % bs))  = value;
    516:       }
    517:     } else if (!baij->donotstash) {
    518:       if (roworiented) {
    519:         MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);
    520:       } else {
    521:         MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);
    522:       }
    523:     }
    524:   }
    525: #if defined(PETSC_USE_DEBUG)
    526:   baij->ht_total_ct  += total_ct;
    527:   baij->ht_insert_ct += insert_ct;
    528: #endif
    529:   return(0);
    530: }

    532: PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
    533: {
    534:   Mat_MPIBAIJ       *baij       = (Mat_MPIBAIJ*)mat->data;
    535:   PetscBool         roworiented = baij->roworiented;
    536:   PetscErrorCode    ierr;
    537:   PetscInt          i,j,ii,jj,row,col;
    538:   PetscInt          rstart=baij->rstartbs;
    539:   PetscInt          rend  =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2;
    540:   PetscInt          h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs;
    541:   PetscReal         tmp;
    542:   MatScalar         **HD = baij->hd,*baij_a;
    543:   const PetscScalar *v_t,*value;
    544: #if defined(PETSC_USE_DEBUG)
    545:   PetscInt          total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
    546: #endif

    549:   if (roworiented) stepval = (n-1)*bs;
    550:   else stepval = (m-1)*bs;

    552:   for (i=0; i<m; i++) {
    553: #if defined(PETSC_USE_DEBUG)
    554:     if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]);
    555:     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],baij->Mbs-1);
    556: #endif
    557:     row = im[i];
    558:     v_t = v + i*nbs2;
    559:     if (row >= rstart && row < rend) {
    560:       for (j=0; j<n; j++) {
    561:         col = in[j];

    563:         /* Look up into the Hash Table */
    564:         key = row*Nbs+col+1;
    565:         h1  = HASH(size,key,tmp);

    567:         idx = h1;
    568: #if defined(PETSC_USE_DEBUG)
    569:         total_ct++;
    570:         insert_ct++;
    571:         if (HT[idx] != key) {
    572:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
    573:           if (idx == size) {
    574:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
    575:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
    576:           }
    577:         }
    578: #else
    579:         if (HT[idx] != key) {
    580:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
    581:           if (idx == size) {
    582:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
    583:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
    584:           }
    585:         }
    586: #endif
    587:         baij_a = HD[idx];
    588:         if (roworiented) {
    589:           /*value = v + i*(stepval+bs)*bs + j*bs;*/
    590:           /* value = v + (i*(stepval+bs)+j)*bs; */
    591:           value = v_t;
    592:           v_t  += bs;
    593:           if (addv == ADD_VALUES) {
    594:             for (ii=0; ii<bs; ii++,value+=stepval) {
    595:               for (jj=ii; jj<bs2; jj+=bs) {
    596:                 baij_a[jj] += *value++;
    597:               }
    598:             }
    599:           } else {
    600:             for (ii=0; ii<bs; ii++,value+=stepval) {
    601:               for (jj=ii; jj<bs2; jj+=bs) {
    602:                 baij_a[jj] = *value++;
    603:               }
    604:             }
    605:           }
    606:         } else {
    607:           value = v + j*(stepval+bs)*bs + i*bs;
    608:           if (addv == ADD_VALUES) {
    609:             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
    610:               for (jj=0; jj<bs; jj++) {
    611:                 baij_a[jj] += *value++;
    612:               }
    613:             }
    614:           } else {
    615:             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
    616:               for (jj=0; jj<bs; jj++) {
    617:                 baij_a[jj] = *value++;
    618:               }
    619:             }
    620:           }
    621:         }
    622:       }
    623:     } else {
    624:       if (!baij->donotstash) {
    625:         if (roworiented) {
    626:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    627:         } else {
    628:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    629:         }
    630:       }
    631:     }
    632:   }
    633: #if defined(PETSC_USE_DEBUG)
    634:   baij->ht_total_ct  += total_ct;
    635:   baij->ht_insert_ct += insert_ct;
    636: #endif
    637:   return(0);
    638: }

    640: PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
    641: {
    642:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
    644:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
    645:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

    648:   for (i=0; i<m; i++) {
    649:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
    650:     if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1);
    651:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
    652:       row = idxm[i] - bsrstart;
    653:       for (j=0; j<n; j++) {
    654:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
    655:         if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1);
    656:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
    657:           col  = idxn[j] - bscstart;
    658:           MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
    659:         } else {
    660:           if (!baij->colmap) {
    661:             MatCreateColmap_MPIBAIJ_Private(mat);
    662:           }
    663: #if defined(PETSC_USE_CTABLE)
    664:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
    665:           data--;
    666: #else
    667:           data = baij->colmap[idxn[j]/bs]-1;
    668: #endif
    669:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
    670:           else {
    671:             col  = data + idxn[j]%bs;
    672:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
    673:           }
    674:         }
    675:       }
    676:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
    677:   }
    678:   return(0);
    679: }

    681: PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm)
    682: {
    683:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
    684:   Mat_SeqBAIJ    *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data;
    686:   PetscInt       i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col;
    687:   PetscReal      sum = 0.0;
    688:   MatScalar      *v;

    691:   if (baij->size == 1) {
    692:      MatNorm(baij->A,type,nrm);
    693:   } else {
    694:     if (type == NORM_FROBENIUS) {
    695:       v  = amat->a;
    696:       nz = amat->nz*bs2;
    697:       for (i=0; i<nz; i++) {
    698:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
    699:       }
    700:       v  = bmat->a;
    701:       nz = bmat->nz*bs2;
    702:       for (i=0; i<nz; i++) {
    703:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
    704:       }
    705:       MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
    706:       *nrm = PetscSqrtReal(*nrm);
    707:     } else if (type == NORM_1) { /* max column sum */
    708:       PetscReal *tmp,*tmp2;
    709:       PetscInt  *jj,*garray=baij->garray,cstart=baij->rstartbs;
    710:       PetscMalloc2(mat->cmap->N,&tmp,mat->cmap->N,&tmp2);
    711:       PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));
    712:       v    = amat->a; jj = amat->j;
    713:       for (i=0; i<amat->nz; i++) {
    714:         for (j=0; j<bs; j++) {
    715:           col = bs*(cstart + *jj) + j; /* column index */
    716:           for (row=0; row<bs; row++) {
    717:             tmp[col] += PetscAbsScalar(*v);  v++;
    718:           }
    719:         }
    720:         jj++;
    721:       }
    722:       v = bmat->a; jj = bmat->j;
    723:       for (i=0; i<bmat->nz; i++) {
    724:         for (j=0; j<bs; j++) {
    725:           col = bs*garray[*jj] + j;
    726:           for (row=0; row<bs; row++) {
    727:             tmp[col] += PetscAbsScalar(*v); v++;
    728:           }
    729:         }
    730:         jj++;
    731:       }
    732:       MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
    733:       *nrm = 0.0;
    734:       for (j=0; j<mat->cmap->N; j++) {
    735:         if (tmp2[j] > *nrm) *nrm = tmp2[j];
    736:       }
    737:       PetscFree2(tmp,tmp2);
    738:     } else if (type == NORM_INFINITY) { /* max row sum */
    739:       PetscReal *sums;
    740:       PetscMalloc1(bs,&sums);
    741:       sum  = 0.0;
    742:       for (j=0; j<amat->mbs; j++) {
    743:         for (row=0; row<bs; row++) sums[row] = 0.0;
    744:         v  = amat->a + bs2*amat->i[j];
    745:         nz = amat->i[j+1]-amat->i[j];
    746:         for (i=0; i<nz; i++) {
    747:           for (col=0; col<bs; col++) {
    748:             for (row=0; row<bs; row++) {
    749:               sums[row] += PetscAbsScalar(*v); v++;
    750:             }
    751:           }
    752:         }
    753:         v  = bmat->a + bs2*bmat->i[j];
    754:         nz = bmat->i[j+1]-bmat->i[j];
    755:         for (i=0; i<nz; i++) {
    756:           for (col=0; col<bs; col++) {
    757:             for (row=0; row<bs; row++) {
    758:               sums[row] += PetscAbsScalar(*v); v++;
    759:             }
    760:           }
    761:         }
    762:         for (row=0; row<bs; row++) {
    763:           if (sums[row] > sum) sum = sums[row];
    764:         }
    765:       }
    766:       MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
    767:       PetscFree(sums);
    768:     } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet");
    769:   }
    770:   return(0);
    771: }

    773: /*
    774:   Creates the hash table, and sets the table
    775:   This table is created only once.
    776:   If new entried need to be added to the matrix
    777:   then the hash table has to be destroyed and
    778:   recreated.
    779: */
    780: PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor)
    781: {
    782:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
    783:   Mat            A     = baij->A,B=baij->B;
    784:   Mat_SeqBAIJ    *a    = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data;
    785:   PetscInt       i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
    787:   PetscInt       ht_size,bs2=baij->bs2,rstart=baij->rstartbs;
    788:   PetscInt       cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs;
    789:   PetscInt       *HT,key;
    790:   MatScalar      **HD;
    791:   PetscReal      tmp;
    792: #if defined(PETSC_USE_INFO)
    793:   PetscInt ct=0,max=0;
    794: #endif

    797:   if (baij->ht) return(0);

    799:   baij->ht_size = (PetscInt)(factor*nz);
    800:   ht_size       = baij->ht_size;

    802:   /* Allocate Memory for Hash Table */
    803:   PetscCalloc2(ht_size,&baij->hd,ht_size,&baij->ht);
    804:   HD   = baij->hd;
    805:   HT   = baij->ht;

    807:   /* Loop Over A */
    808:   for (i=0; i<a->mbs; i++) {
    809:     for (j=ai[i]; j<ai[i+1]; j++) {
    810:       row = i+rstart;
    811:       col = aj[j]+cstart;

    813:       key = row*Nbs + col + 1;
    814:       h1  = HASH(ht_size,key,tmp);
    815:       for (k=0; k<ht_size; k++) {
    816:         if (!HT[(h1+k)%ht_size]) {
    817:           HT[(h1+k)%ht_size] = key;
    818:           HD[(h1+k)%ht_size] = a->a + j*bs2;
    819:           break;
    820: #if defined(PETSC_USE_INFO)
    821:         } else {
    822:           ct++;
    823: #endif
    824:         }
    825:       }
    826: #if defined(PETSC_USE_INFO)
    827:       if (k> max) max = k;
    828: #endif
    829:     }
    830:   }
    831:   /* Loop Over B */
    832:   for (i=0; i<b->mbs; i++) {
    833:     for (j=bi[i]; j<bi[i+1]; j++) {
    834:       row = i+rstart;
    835:       col = garray[bj[j]];
    836:       key = row*Nbs + col + 1;
    837:       h1  = HASH(ht_size,key,tmp);
    838:       for (k=0; k<ht_size; k++) {
    839:         if (!HT[(h1+k)%ht_size]) {
    840:           HT[(h1+k)%ht_size] = key;
    841:           HD[(h1+k)%ht_size] = b->a + j*bs2;
    842:           break;
    843: #if defined(PETSC_USE_INFO)
    844:         } else {
    845:           ct++;
    846: #endif
    847:         }
    848:       }
    849: #if defined(PETSC_USE_INFO)
    850:       if (k> max) max = k;
    851: #endif
    852:     }
    853:   }

    855:   /* Print Summary */
    856: #if defined(PETSC_USE_INFO)
    857:   for (i=0,j=0; i<ht_size; i++) {
    858:     if (HT[i]) j++;
    859:   }
    860:   PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);
    861: #endif
    862:   return(0);
    863: }

    865: PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode)
    866: {
    867:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
    869:   PetscInt       nstash,reallocs;

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

    874:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
    875:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
    876:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
    877:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
    878:   MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);
    879:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
    880:   return(0);
    881: }

    883: PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode)
    884: {
    885:   Mat_MPIBAIJ    *baij=(Mat_MPIBAIJ*)mat->data;
    886:   Mat_SeqBAIJ    *a   =(Mat_SeqBAIJ*)baij->A->data;
    888:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
    889:   PetscInt       *row,*col;
    890:   PetscBool      r1,r2,r3,other_disassembled;
    891:   MatScalar      *val;
    892:   PetscMPIInt    n;

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

    901:       for (i=0; i<n;) {
    902:         /* Now identify the consecutive vals belonging to the same row */
    903:         for (j=i,rstart=row[j]; j<n; j++) {
    904:           if (row[j] != rstart) break;
    905:         }
    906:         if (j < n) ncols = j-i;
    907:         else       ncols = n-i;
    908:         /* Now assemble all these values with a single function call */
    909:         MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
    910:         i    = j;
    911:       }
    912:     }
    913:     MatStashScatterEnd_Private(&mat->stash);
    914:     /* Now process the block-stash. Since the values are stashed column-oriented,
    915:        set the roworiented flag to column oriented, and after MatSetValues()
    916:        restore the original flags */
    917:     r1 = baij->roworiented;
    918:     r2 = a->roworiented;
    919:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

    921:     baij->roworiented = PETSC_FALSE;
    922:     a->roworiented    = PETSC_FALSE;

    924:     (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */
    925:     while (1) {
    926:       MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);
    927:       if (!flg) break;

    929:       for (i=0; i<n;) {
    930:         /* Now identify the consecutive vals belonging to the same row */
    931:         for (j=i,rstart=row[j]; j<n; j++) {
    932:           if (row[j] != rstart) break;
    933:         }
    934:         if (j < n) ncols = j-i;
    935:         else       ncols = n-i;
    936:         MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
    937:         i    = j;
    938:       }
    939:     }
    940:     MatStashScatterEnd_Private(&mat->bstash);

    942:     baij->roworiented = r1;
    943:     a->roworiented    = r2;

    945:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */
    946:   }

    948:   MatAssemblyBegin(baij->A,mode);
    949:   MatAssemblyEnd(baij->A,mode);

    951:   /* determine if any processor has disassembled, if so we must
    952:      also disassemble ourselfs, in order that we may reassemble. */
    953:   /*
    954:      if nonzero structure of submatrix B cannot change then we know that
    955:      no processor disassembled thus we can skip this stuff
    956:   */
    957:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
    958:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
    959:     if (mat->was_assembled && !other_disassembled) {
    960:       MatDisAssemble_MPIBAIJ(mat);
    961:     }
    962:   }

    964:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
    965:     MatSetUpMultiply_MPIBAIJ(mat);
    966:   }
    967:   MatAssemblyBegin(baij->B,mode);
    968:   MatAssemblyEnd(baij->B,mode);

    970: #if defined(PETSC_USE_INFO)
    971:   if (baij->ht && mode== MAT_FINAL_ASSEMBLY) {
    972:     PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",(double)((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);

    974:     baij->ht_total_ct  = 0;
    975:     baij->ht_insert_ct = 0;
    976:   }
    977: #endif
    978:   if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) {
    979:     MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);

    981:     mat->ops->setvalues        = MatSetValues_MPIBAIJ_HT;
    982:     mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT;
    983:   }

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

    987:   baij->rowvalues = 0;

    989:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
    990:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
    991:     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
    992:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
    993:   }
    994:   return(0);
    995: }

    997: extern PetscErrorCode MatView_SeqBAIJ(Mat,PetscViewer);
    998:  #include <petscdraw.h>
    999: static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
    1000: {
    1001:   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
    1002:   PetscErrorCode    ierr;
    1003:   PetscMPIInt       rank = baij->rank;
    1004:   PetscInt          bs   = mat->rmap->bs;
    1005:   PetscBool         iascii,isdraw;
    1006:   PetscViewer       sviewer;
    1007:   PetscViewerFormat format;

    1010:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    1011:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    1012:   if (iascii) {
    1013:     PetscViewerGetFormat(viewer,&format);
    1014:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
    1015:       MatInfo info;
    1016:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
    1017:       MatGetInfo(mat,MAT_LOCAL,&info);
    1018:       PetscViewerASCIIPushSynchronized(viewer);
    1019:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %g\n",
    1020:                                                 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(double)info.memory);
    1021:       MatGetInfo(baij->A,MAT_LOCAL,&info);
    1022:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
    1023:       MatGetInfo(baij->B,MAT_LOCAL,&info);
    1024:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
    1025:       PetscViewerFlush(viewer);
    1026:       PetscViewerASCIIPopSynchronized(viewer);
    1027:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
    1028:       VecScatterView(baij->Mvctx,viewer);
    1029:       return(0);
    1030:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
    1031:       PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
    1032:       return(0);
    1033:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
    1034:       return(0);
    1035:     }
    1036:   }

    1038:   if (isdraw) {
    1039:     PetscDraw draw;
    1040:     PetscBool isnull;
    1041:     PetscViewerDrawGetDraw(viewer,0,&draw);
    1042:     PetscDrawIsNull(draw,&isnull);
    1043:     if (isnull) return(0);
    1044:   }

    1046:   {
    1047:     /* assemble the entire matrix onto first processor. */
    1048:     Mat         A;
    1049:     Mat_SeqBAIJ *Aloc;
    1050:     PetscInt    M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
    1051:     MatScalar   *a;
    1052:     const char  *matname;

    1054:     /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */
    1055:     /* Perhaps this should be the type of mat? */
    1056:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
    1057:     if (!rank) {
    1058:       MatSetSizes(A,M,N,M,N);
    1059:     } else {
    1060:       MatSetSizes(A,0,0,M,N);
    1061:     }
    1062:     MatSetType(A,MATMPIBAIJ);
    1063:     MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
    1064:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
    1065:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

    1067:     /* copy over the A part */
    1068:     Aloc = (Mat_SeqBAIJ*)baij->A->data;
    1069:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
    1070:     PetscMalloc1(bs,&rvals);

    1072:     for (i=0; i<mbs; i++) {
    1073:       rvals[0] = bs*(baij->rstartbs + i);
    1074:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    1075:       for (j=ai[i]; j<ai[i+1]; j++) {
    1076:         col = (baij->cstartbs+aj[j])*bs;
    1077:         for (k=0; k<bs; k++) {
    1078:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
    1079:           col++; a += bs;
    1080:         }
    1081:       }
    1082:     }
    1083:     /* copy over the B part */
    1084:     Aloc = (Mat_SeqBAIJ*)baij->B->data;
    1085:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
    1086:     for (i=0; i<mbs; i++) {
    1087:       rvals[0] = bs*(baij->rstartbs + i);
    1088:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    1089:       for (j=ai[i]; j<ai[i+1]; j++) {
    1090:         col = baij->garray[aj[j]]*bs;
    1091:         for (k=0; k<bs; k++) {
    1092:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
    1093:           col++; a += bs;
    1094:         }
    1095:       }
    1096:     }
    1097:     PetscFree(rvals);
    1098:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    1099:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    1100:     /*
    1101:        Everyone has to call to draw the matrix since the graphics waits are
    1102:        synchronized across all processors that share the PetscDraw object
    1103:     */
    1104:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
    1105:     PetscObjectGetName((PetscObject)mat,&matname);
    1106:     if (!rank) {
    1107:       PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,matname);
    1108:       MatView_SeqBAIJ(((Mat_MPIBAIJ*)(A->data))->A,sviewer);
    1109:     }
    1110:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
    1111:     PetscViewerFlush(viewer);
    1112:     MatDestroy(&A);
    1113:   }
    1114:   return(0);
    1115: }

    1117: static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer)
    1118: {
    1119:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)mat->data;
    1120:   Mat_SeqBAIJ    *A = (Mat_SeqBAIJ*)a->A->data;
    1121:   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)a->B->data;
    1123:   PetscInt       i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen;
    1124:   PetscInt       *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll;
    1125:   int            fd;
    1126:   PetscScalar    *column_values;
    1127:   FILE           *file;
    1128:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
    1129:   PetscInt       message_count,flowcontrolcount;

    1132:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
    1133:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
    1134:   nz   = bs2*(A->nz + B->nz);
    1135:   rlen = mat->rmap->n;
    1136:   PetscViewerBinaryGetDescriptor(viewer,&fd);
    1137:   if (!rank) {
    1138:     header[0] = MAT_FILE_CLASSID;
    1139:     header[1] = mat->rmap->N;
    1140:     header[2] = mat->cmap->N;

    1142:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
    1143:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
    1144:     /* get largest number of rows any processor has */
    1145:     range = mat->rmap->range;
    1146:     for (i=1; i<size; i++) {
    1147:       rlen = PetscMax(rlen,range[i+1] - range[i]);
    1148:     }
    1149:   } else {
    1150:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
    1151:   }

    1153:   PetscMalloc1(rlen/bs,&crow_lens);
    1154:   /* compute lengths of each row  */
    1155:   for (i=0; i<a->mbs; i++) {
    1156:     crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
    1157:   }
    1158:   /* store the row lengths to the file */
    1159:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
    1160:   if (!rank) {
    1161:     MPI_Status status;
    1162:     PetscMalloc1(rlen,&row_lens);
    1163:     rlen = (range[1] - range[0])/bs;
    1164:     for (i=0; i<rlen; i++) {
    1165:       for (j=0; j<bs; j++) {
    1166:         row_lens[i*bs+j] = bs*crow_lens[i];
    1167:       }
    1168:     }
    1169:     PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
    1170:     for (i=1; i<size; i++) {
    1171:       rlen = (range[i+1] - range[i])/bs;
    1172:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
    1173:       MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
    1174:       for (k=0; k<rlen; k++) {
    1175:         for (j=0; j<bs; j++) {
    1176:           row_lens[k*bs+j] = bs*crow_lens[k];
    1177:         }
    1178:       }
    1179:       PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
    1180:     }
    1181:     PetscViewerFlowControlEndMaster(viewer,&message_count);
    1182:     PetscFree(row_lens);
    1183:   } else {
    1184:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
    1185:     MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
    1186:     PetscViewerFlowControlEndWorker(viewer,&message_count);
    1187:   }
    1188:   PetscFree(crow_lens);

    1190:   /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the
    1191:      information needed to make it for each row from a block row. This does require more communication but still not more than
    1192:      the communication needed for the nonzero values  */
    1193:   nzmax = nz; /*  space a largest processor needs */
    1194:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
    1195:   PetscMalloc1(nzmax,&column_indices);
    1196:   cnt   = 0;
    1197:   for (i=0; i<a->mbs; i++) {
    1198:     pcnt = cnt;
    1199:     for (j=B->i[i]; j<B->i[i+1]; j++) {
    1200:       if ((col = garray[B->j[j]]) > cstart) break;
    1201:       for (l=0; l<bs; l++) {
    1202:         column_indices[cnt++] = bs*col+l;
    1203:       }
    1204:     }
    1205:     for (k=A->i[i]; k<A->i[i+1]; k++) {
    1206:       for (l=0; l<bs; l++) {
    1207:         column_indices[cnt++] = bs*(A->j[k] + cstart)+l;
    1208:       }
    1209:     }
    1210:     for (; j<B->i[i+1]; j++) {
    1211:       for (l=0; l<bs; l++) {
    1212:         column_indices[cnt++] = bs*garray[B->j[j]]+l;
    1213:       }
    1214:     }
    1215:     len = cnt - pcnt;
    1216:     for (k=1; k<bs; k++) {
    1217:       PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));
    1218:       cnt += len;
    1219:     }
    1220:   }
    1221:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

    1223:   /* store the columns to the file */
    1224:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
    1225:   if (!rank) {
    1226:     MPI_Status status;
    1227:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
    1228:     for (i=1; i<size; i++) {
    1229:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
    1230:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
    1231:       MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
    1232:       PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);
    1233:     }
    1234:     PetscViewerFlowControlEndMaster(viewer,&message_count);
    1235:   } else {
    1236:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
    1237:     MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
    1238:     MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
    1239:     PetscViewerFlowControlEndWorker(viewer,&message_count);
    1240:   }
    1241:   PetscFree(column_indices);

    1243:   /* load up the numerical values */
    1244:   PetscMalloc1(nzmax,&column_values);
    1245:   cnt  = 0;
    1246:   for (i=0; i<a->mbs; i++) {
    1247:     rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]);
    1248:     for (j=B->i[i]; j<B->i[i+1]; j++) {
    1249:       if (garray[B->j[j]] > cstart) break;
    1250:       for (l=0; l<bs; l++) {
    1251:         for (ll=0; ll<bs; ll++) {
    1252:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
    1253:         }
    1254:       }
    1255:       cnt += bs;
    1256:     }
    1257:     for (k=A->i[i]; k<A->i[i+1]; k++) {
    1258:       for (l=0; l<bs; l++) {
    1259:         for (ll=0; ll<bs; ll++) {
    1260:           column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll];
    1261:         }
    1262:       }
    1263:       cnt += bs;
    1264:     }
    1265:     for (; j<B->i[i+1]; j++) {
    1266:       for (l=0; l<bs; l++) {
    1267:         for (ll=0; ll<bs; ll++) {
    1268:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
    1269:         }
    1270:       }
    1271:       cnt += bs;
    1272:     }
    1273:     cnt += (bs-1)*rlen;
    1274:   }
    1275:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

    1277:   /* store the column values to the file */
    1278:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
    1279:   if (!rank) {
    1280:     MPI_Status status;
    1281:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
    1282:     for (i=1; i<size; i++) {
    1283:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
    1284:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
    1285:       MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);
    1286:       PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);
    1287:     }
    1288:     PetscViewerFlowControlEndMaster(viewer,&message_count);
    1289:   } else {
    1290:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
    1291:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
    1292:     MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
    1293:     PetscViewerFlowControlEndWorker(viewer,&message_count);
    1294:   }
    1295:   PetscFree(column_values);

    1297:   PetscViewerBinaryGetInfoPointer(viewer,&file);
    1298:   if (file) {
    1299:     fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs);
    1300:   }
    1301:   return(0);
    1302: }

    1304: PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer)
    1305: {
    1307:   PetscBool      iascii,isdraw,issocket,isbinary;

    1310:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    1311:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    1312:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
    1313:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    1314:   if (iascii || isdraw || issocket) {
    1315:     MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);
    1316:   } else if (isbinary) {
    1317:     MatView_MPIBAIJ_Binary(mat,viewer);
    1318:   }
    1319:   return(0);
    1320: }

    1322: PetscErrorCode MatDestroy_MPIBAIJ(Mat mat)
    1323: {
    1324:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;

    1328: #if defined(PETSC_USE_LOG)
    1329:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
    1330: #endif
    1331:   MatStashDestroy_Private(&mat->stash);
    1332:   MatStashDestroy_Private(&mat->bstash);
    1333:   MatDestroy(&baij->A);
    1334:   MatDestroy(&baij->B);
    1335: #if defined(PETSC_USE_CTABLE)
    1336:   PetscTableDestroy(&baij->colmap);
    1337: #else
    1338:   PetscFree(baij->colmap);
    1339: #endif
    1340:   PetscFree(baij->garray);
    1341:   VecDestroy(&baij->lvec);
    1342:   VecScatterDestroy(&baij->Mvctx);
    1343:   PetscFree2(baij->rowvalues,baij->rowindices);
    1344:   PetscFree(baij->barray);
    1345:   PetscFree2(baij->hd,baij->ht);
    1346:   PetscFree(baij->rangebs);
    1347:   PetscFree(mat->data);

    1349:   PetscObjectChangeTypeName((PetscObject)mat,0);
    1350:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
    1351:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
    1352:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);
    1353:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);
    1354:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
    1355:   PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);
    1356:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);
    1357:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);
    1358: #if defined(PETSC_HAVE_HYPRE)
    1359:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_hypre_C",NULL);
    1360: #endif
    1361:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_is_C",NULL);
    1362:   PetscObjectComposeFunction((PetscObject)mat,"MatPtAP_is_mpibaij_C",NULL);
    1363:   return(0);
    1364: }

    1366: PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy)
    1367: {
    1368:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
    1370:   PetscInt       nt;

    1373:   VecGetLocalSize(xx,&nt);
    1374:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
    1375:   VecGetLocalSize(yy,&nt);
    1376:   if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");
    1377:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1378:   (*a->A->ops->mult)(a->A,xx,yy);
    1379:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1380:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
    1381:   return(0);
    1382: }

    1384: PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
    1385: {
    1386:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    1390:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1391:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
    1392:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1393:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
    1394:   return(0);
    1395: }

    1397: PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy)
    1398: {
    1399:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
    1401:   PetscBool      merged;

    1404:   VecScatterGetMerged(a->Mvctx,&merged);
    1405:   /* do nondiagonal part */
    1406:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
    1407:   if (!merged) {
    1408:     /* send it on its way */
    1409:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    1410:     /* do local part */
    1411:     (*a->A->ops->multtranspose)(a->A,xx,yy);
    1412:     /* receive remote parts: note this assumes the values are not actually */
    1413:     /* inserted in yy until the next line */
    1414:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    1415:   } else {
    1416:     /* do local part */
    1417:     (*a->A->ops->multtranspose)(a->A,xx,yy);
    1418:     /* send it on its way */
    1419:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    1420:     /* values actually were received in the Begin() but we need to call this nop */
    1421:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    1422:   }
    1423:   return(0);
    1424: }

    1426: PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
    1427: {
    1428:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    1432:   /* do nondiagonal part */
    1433:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
    1434:   /* send it on its way */
    1435:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
    1436:   /* do local part */
    1437:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
    1438:   /* receive remote parts: note this assumes the values are not actually */
    1439:   /* inserted in yy until the next line, which is true for my implementation*/
    1440:   /* but is not perhaps always true. */
    1441:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
    1442:   return(0);
    1443: }

    1445: /*
    1446:   This only works correctly for square matrices where the subblock A->A is the
    1447:    diagonal block
    1448: */
    1449: PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v)
    1450: {
    1451:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    1455:   if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
    1456:   MatGetDiagonal(a->A,v);
    1457:   return(0);
    1458: }

    1460: PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa)
    1461: {
    1462:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    1466:   MatScale(a->A,aa);
    1467:   MatScale(a->B,aa);
    1468:   return(0);
    1469: }

    1471: PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1472: {
    1473:   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
    1474:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
    1476:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
    1477:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
    1478:   PetscInt       *cmap,*idx_p,cstart = mat->cstartbs;

    1481:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
    1482:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
    1483:   mat->getrowactive = PETSC_TRUE;

    1485:   if (!mat->rowvalues && (idx || v)) {
    1486:     /*
    1487:         allocate enough space to hold information from the longest row.
    1488:     */
    1489:     Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data;
    1490:     PetscInt    max = 1,mbs = mat->mbs,tmp;
    1491:     for (i=0; i<mbs; i++) {
    1492:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
    1493:       if (max < tmp) max = tmp;
    1494:     }
    1495:     PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
    1496:   }
    1497:   lrow = row - brstart;

    1499:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
    1500:   if (!v)   {pvA = 0; pvB = 0;}
    1501:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
    1502:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
    1503:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
    1504:   nztot = nzA + nzB;

    1506:   cmap = mat->garray;
    1507:   if (v  || idx) {
    1508:     if (nztot) {
    1509:       /* Sort by increasing column numbers, assuming A and B already sorted */
    1510:       PetscInt imark = -1;
    1511:       if (v) {
    1512:         *v = v_p = mat->rowvalues;
    1513:         for (i=0; i<nzB; i++) {
    1514:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
    1515:           else break;
    1516:         }
    1517:         imark = i;
    1518:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
    1519:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
    1520:       }
    1521:       if (idx) {
    1522:         *idx = idx_p = mat->rowindices;
    1523:         if (imark > -1) {
    1524:           for (i=0; i<imark; i++) {
    1525:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
    1526:           }
    1527:         } else {
    1528:           for (i=0; i<nzB; i++) {
    1529:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
    1530:             else break;
    1531:           }
    1532:           imark = i;
    1533:         }
    1534:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
    1535:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
    1536:       }
    1537:     } else {
    1538:       if (idx) *idx = 0;
    1539:       if (v)   *v   = 0;
    1540:     }
    1541:   }
    1542:   *nz  = nztot;
    1543:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
    1544:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
    1545:   return(0);
    1546: }

    1548: PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1549: {
    1550:   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;

    1553:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called");
    1554:   baij->getrowactive = PETSC_FALSE;
    1555:   return(0);
    1556: }

    1558: PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A)
    1559: {
    1560:   Mat_MPIBAIJ    *l = (Mat_MPIBAIJ*)A->data;

    1564:   MatZeroEntries(l->A);
    1565:   MatZeroEntries(l->B);
    1566:   return(0);
    1567: }

    1569: PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
    1570: {
    1571:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)matin->data;
    1572:   Mat            A  = a->A,B = a->B;
    1574:   PetscReal      isend[5],irecv[5];

    1577:   info->block_size = (PetscReal)matin->rmap->bs;

    1579:   MatGetInfo(A,MAT_LOCAL,info);

    1581:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
    1582:   isend[3] = info->memory;  isend[4] = info->mallocs;

    1584:   MatGetInfo(B,MAT_LOCAL,info);

    1586:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
    1587:   isend[3] += info->memory;  isend[4] += info->mallocs;

    1589:   if (flag == MAT_LOCAL) {
    1590:     info->nz_used      = isend[0];
    1591:     info->nz_allocated = isend[1];
    1592:     info->nz_unneeded  = isend[2];
    1593:     info->memory       = isend[3];
    1594:     info->mallocs      = isend[4];
    1595:   } else if (flag == MAT_GLOBAL_MAX) {
    1596:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

    1598:     info->nz_used      = irecv[0];
    1599:     info->nz_allocated = irecv[1];
    1600:     info->nz_unneeded  = irecv[2];
    1601:     info->memory       = irecv[3];
    1602:     info->mallocs      = irecv[4];
    1603:   } else if (flag == MAT_GLOBAL_SUM) {
    1604:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

    1606:     info->nz_used      = irecv[0];
    1607:     info->nz_allocated = irecv[1];
    1608:     info->nz_unneeded  = irecv[2];
    1609:     info->memory       = irecv[3];
    1610:     info->mallocs      = irecv[4];
    1611:   } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
    1612:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
    1613:   info->fill_ratio_needed = 0;
    1614:   info->factor_mallocs    = 0;
    1615:   return(0);
    1616: }

    1618: PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg)
    1619: {
    1620:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    1624:   switch (op) {
    1625:   case MAT_NEW_NONZERO_LOCATIONS:
    1626:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
    1627:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
    1628:   case MAT_KEEP_NONZERO_PATTERN:
    1629:   case MAT_NEW_NONZERO_LOCATION_ERR:
    1630:     MatCheckPreallocated(A,1);
    1631:     MatSetOption(a->A,op,flg);
    1632:     MatSetOption(a->B,op,flg);
    1633:     break;
    1634:   case MAT_ROW_ORIENTED:
    1635:     MatCheckPreallocated(A,1);
    1636:     a->roworiented = flg;

    1638:     MatSetOption(a->A,op,flg);
    1639:     MatSetOption(a->B,op,flg);
    1640:     break;
    1641:   case MAT_NEW_DIAGONALS:
    1642:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
    1643:     break;
    1644:   case MAT_IGNORE_OFF_PROC_ENTRIES:
    1645:     a->donotstash = flg;
    1646:     break;
    1647:   case MAT_USE_HASH_TABLE:
    1648:     a->ht_flag = flg;
    1649:     a->ht_fact = 1.39;
    1650:     break;
    1651:   case MAT_SYMMETRIC:
    1652:   case MAT_STRUCTURALLY_SYMMETRIC:
    1653:   case MAT_HERMITIAN:
    1654:   case MAT_SUBMAT_SINGLEIS:
    1655:   case MAT_SYMMETRY_ETERNAL:
    1656:     MatCheckPreallocated(A,1);
    1657:     MatSetOption(a->A,op,flg);
    1658:     break;
    1659:   default:
    1660:     SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op);
    1661:   }
    1662:   return(0);
    1663: }

    1665: PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout)
    1666: {
    1667:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)A->data;
    1668:   Mat_SeqBAIJ    *Aloc;
    1669:   Mat            B;
    1671:   PetscInt       M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col;
    1672:   PetscInt       bs=A->rmap->bs,mbs=baij->mbs;
    1673:   MatScalar      *a;

    1676:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) {
    1677:     MatCreate(PetscObjectComm((PetscObject)A),&B);
    1678:     MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
    1679:     MatSetType(B,((PetscObject)A)->type_name);
    1680:     /* Do not know preallocation information, but must set block size */
    1681:     MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);
    1682:   } else {
    1683:     B = *matout;
    1684:   }

    1686:   /* copy over the A part */
    1687:   Aloc = (Mat_SeqBAIJ*)baij->A->data;
    1688:   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
    1689:   PetscMalloc1(bs,&rvals);

    1691:   for (i=0; i<mbs; i++) {
    1692:     rvals[0] = bs*(baij->rstartbs + i);
    1693:     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    1694:     for (j=ai[i]; j<ai[i+1]; j++) {
    1695:       col = (baij->cstartbs+aj[j])*bs;
    1696:       for (k=0; k<bs; k++) {
    1697:         MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);

    1699:         col++; a += bs;
    1700:       }
    1701:     }
    1702:   }
    1703:   /* copy over the B part */
    1704:   Aloc = (Mat_SeqBAIJ*)baij->B->data;
    1705:   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
    1706:   for (i=0; i<mbs; i++) {
    1707:     rvals[0] = bs*(baij->rstartbs + i);
    1708:     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    1709:     for (j=ai[i]; j<ai[i+1]; j++) {
    1710:       col = baij->garray[aj[j]]*bs;
    1711:       for (k=0; k<bs; k++) {
    1712:         MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);
    1713:         col++;
    1714:         a += bs;
    1715:       }
    1716:     }
    1717:   }
    1718:   PetscFree(rvals);
    1719:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    1720:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

    1722:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) *matout = B;
    1723:   else {
    1724:     MatHeaderMerge(A,&B);
    1725:   }
    1726:   return(0);
    1727: }

    1729: PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr)
    1730: {
    1731:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
    1732:   Mat            a     = baij->A,b = baij->B;
    1734:   PetscInt       s1,s2,s3;

    1737:   MatGetLocalSize(mat,&s2,&s3);
    1738:   if (rr) {
    1739:     VecGetLocalSize(rr,&s1);
    1740:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
    1741:     /* Overlap communication with computation. */
    1742:     VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1743:   }
    1744:   if (ll) {
    1745:     VecGetLocalSize(ll,&s1);
    1746:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
    1747:     (*b->ops->diagonalscale)(b,ll,NULL);
    1748:   }
    1749:   /* scale  the diagonal block */
    1750:   (*a->ops->diagonalscale)(a,ll,rr);

    1752:   if (rr) {
    1753:     /* Do a scatter end and then right scale the off-diagonal block */
    1754:     VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1755:     (*b->ops->diagonalscale)(b,NULL,baij->lvec);
    1756:   }
    1757:   return(0);
    1758: }

    1760: PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
    1761: {
    1762:   Mat_MPIBAIJ   *l      = (Mat_MPIBAIJ *) A->data;
    1763:   PetscInt      *lrows;
    1764:   PetscInt       r, len;
    1765:   PetscBool      cong;

    1769:   /* get locally owned rows */
    1770:   MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);
    1771:   /* fix right hand side if needed */
    1772:   if (x && b) {
    1773:     const PetscScalar *xx;
    1774:     PetscScalar       *bb;

    1776:     VecGetArrayRead(x,&xx);
    1777:     VecGetArray(b,&bb);
    1778:     for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
    1779:     VecRestoreArrayRead(x,&xx);
    1780:     VecRestoreArray(b,&bb);
    1781:   }

    1783:   /* actually zap the local rows */
    1784:   /*
    1785:         Zero the required rows. If the "diagonal block" of the matrix
    1786:      is square and the user wishes to set the diagonal we use separate
    1787:      code so that MatSetValues() is not called for each diagonal allocating
    1788:      new memory, thus calling lots of mallocs and slowing things down.

    1790:   */
    1791:   /* must zero l->B before l->A because the (diag) case below may put values into l->B*/
    1792:   MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,NULL,NULL);
    1793:   MatHasCongruentLayouts(A,&cong);
    1794:   if ((diag != 0.0) && cong) {
    1795:     MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,NULL,NULL);
    1796:   } else if (diag != 0.0) {
    1797:     MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);
    1798:     if (((Mat_SeqBAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\
    1799:        MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
    1800:     for (r = 0; r < len; ++r) {
    1801:       const PetscInt row = lrows[r] + A->rmap->rstart;
    1802:       MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);
    1803:     }
    1804:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    1805:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    1806:   } else {
    1807:     MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,NULL,NULL);
    1808:   }
    1809:   PetscFree(lrows);

    1811:   /* only change matrix nonzero state if pattern was allowed to be changed */
    1812:   if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) {
    1813:     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
    1814:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
    1815:   }
    1816:   return(0);
    1817: }

    1819: PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
    1820: {
    1821:   Mat_MPIBAIJ       *l = (Mat_MPIBAIJ*)A->data;
    1822:   PetscErrorCode    ierr;
    1823:   PetscMPIInt       n = A->rmap->n;
    1824:   PetscInt          i,j,k,r,p = 0,len = 0,row,col,count;
    1825:   PetscInt          *lrows,*owners = A->rmap->range;
    1826:   PetscSFNode       *rrows;
    1827:   PetscSF           sf;
    1828:   const PetscScalar *xx;
    1829:   PetscScalar       *bb,*mask;
    1830:   Vec               xmask,lmask;
    1831:   Mat_SeqBAIJ       *baij = (Mat_SeqBAIJ*)l->B->data;
    1832:   PetscInt           bs = A->rmap->bs, bs2 = baij->bs2;
    1833:   PetscScalar       *aa;

    1836:   /* Create SF where leaves are input rows and roots are owned rows */
    1837:   PetscMalloc1(n, &lrows);
    1838:   for (r = 0; r < n; ++r) lrows[r] = -1;
    1839:   PetscMalloc1(N, &rrows);
    1840:   for (r = 0; r < N; ++r) {
    1841:     const PetscInt idx   = rows[r];
    1842:     if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N);
    1843:     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
    1844:       PetscLayoutFindOwner(A->rmap,idx,&p);
    1845:     }
    1846:     rrows[r].rank  = p;
    1847:     rrows[r].index = rows[r] - owners[p];
    1848:   }
    1849:   PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
    1850:   PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
    1851:   /* Collect flags for rows to be zeroed */
    1852:   PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
    1853:   PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
    1854:   PetscSFDestroy(&sf);
    1855:   /* Compress and put in row numbers */
    1856:   for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
    1857:   /* zero diagonal part of matrix */
    1858:   MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
    1859:   /* handle off diagonal part of matrix */
    1860:   MatCreateVecs(A,&xmask,NULL);
    1861:   VecDuplicate(l->lvec,&lmask);
    1862:   VecGetArray(xmask,&bb);
    1863:   for (i=0; i<len; i++) bb[lrows[i]] = 1;
    1864:   VecRestoreArray(xmask,&bb);
    1865:   VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
    1866:   VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
    1867:   VecDestroy(&xmask);
    1868:   if (x) {
    1869:     VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1870:     VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1871:     VecGetArrayRead(l->lvec,&xx);
    1872:     VecGetArray(b,&bb);
    1873:   }
    1874:   VecGetArray(lmask,&mask);
    1875:   /* remove zeroed rows of off diagonal matrix */
    1876:   for (i = 0; i < len; ++i) {
    1877:     row   = lrows[i];
    1878:     count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
    1879:     aa    = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
    1880:     for (k = 0; k < count; ++k) {
    1881:       aa[0] = 0.0;
    1882:       aa   += bs;
    1883:     }
    1884:   }
    1885:   /* loop over all elements of off process part of matrix zeroing removed columns*/
    1886:   for (i = 0; i < l->B->rmap->N; ++i) {
    1887:     row = i/bs;
    1888:     for (j = baij->i[row]; j < baij->i[row+1]; ++j) {
    1889:       for (k = 0; k < bs; ++k) {
    1890:         col = bs*baij->j[j] + k;
    1891:         if (PetscAbsScalar(mask[col])) {
    1892:           aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k;
    1893:           if (x) bb[i] -= aa[0]*xx[col];
    1894:           aa[0] = 0.0;
    1895:         }
    1896:       }
    1897:     }
    1898:   }
    1899:   if (x) {
    1900:     VecRestoreArray(b,&bb);
    1901:     VecRestoreArrayRead(l->lvec,&xx);
    1902:   }
    1903:   VecRestoreArray(lmask,&mask);
    1904:   VecDestroy(&lmask);
    1905:   PetscFree(lrows);

    1907:   /* only change matrix nonzero state if pattern was allowed to be changed */
    1908:   if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) {
    1909:     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
    1910:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
    1911:   }
    1912:   return(0);
    1913: }

    1915: PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A)
    1916: {
    1917:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    1921:   MatSetUnfactored(a->A);
    1922:   return(0);
    1923: }

    1925: static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*);

    1927: PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool  *flag)
    1928: {
    1929:   Mat_MPIBAIJ    *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data;
    1930:   Mat            a,b,c,d;
    1931:   PetscBool      flg;

    1935:   a = matA->A; b = matA->B;
    1936:   c = matB->A; d = matB->B;

    1938:   MatEqual(a,c,&flg);
    1939:   if (flg) {
    1940:     MatEqual(b,d,&flg);
    1941:   }
    1942:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
    1943:   return(0);
    1944: }

    1946: PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str)
    1947: {
    1949:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
    1950:   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;

    1953:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
    1954:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
    1955:     MatCopy_Basic(A,B,str);
    1956:   } else {
    1957:     MatCopy(a->A,b->A,str);
    1958:     MatCopy(a->B,b->B,str);
    1959:   }
    1960:   PetscObjectStateIncrease((PetscObject)B);
    1961:   return(0);
    1962: }

    1964: PetscErrorCode MatSetUp_MPIBAIJ(Mat A)
    1965: {

    1969:   MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
    1970:   return(0);
    1971: }

    1973: PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
    1974: {
    1976:   PetscInt       bs = Y->rmap->bs,m = Y->rmap->N/bs;
    1977:   Mat_SeqBAIJ    *x = (Mat_SeqBAIJ*)X->data;
    1978:   Mat_SeqBAIJ    *y = (Mat_SeqBAIJ*)Y->data;

    1981:   MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
    1982:   return(0);
    1983: }

    1985: PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
    1986: {
    1988:   Mat_MPIBAIJ    *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data;
    1989:   PetscBLASInt   bnz,one=1;
    1990:   Mat_SeqBAIJ    *x,*y;
    1991:   PetscInt       bs2 = Y->rmap->bs*Y->rmap->bs;

    1994:   if (str == SAME_NONZERO_PATTERN) {
    1995:     PetscScalar alpha = a;
    1996:     x    = (Mat_SeqBAIJ*)xx->A->data;
    1997:     y    = (Mat_SeqBAIJ*)yy->A->data;
    1998:     PetscBLASIntCast(x->nz*bs2,&bnz);
    1999:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
    2000:     x    = (Mat_SeqBAIJ*)xx->B->data;
    2001:     y    = (Mat_SeqBAIJ*)yy->B->data;
    2002:     PetscBLASIntCast(x->nz*bs2,&bnz);
    2003:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
    2004:     PetscObjectStateIncrease((PetscObject)Y);
    2005:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
    2006:     MatAXPY_Basic(Y,a,X,str);
    2007:   } else {
    2008:     Mat      B;
    2009:     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
    2010:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
    2011:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
    2012:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
    2013:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
    2014:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
    2015:     MatSetBlockSizesFromMats(B,Y,Y);
    2016:     MatSetType(B,MATMPIBAIJ);
    2017:     MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);
    2018:     MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
    2019:     MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
    2020:     /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */
    2021:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
    2022:     MatHeaderReplace(Y,&B);
    2023:     PetscFree(nnz_d);
    2024:     PetscFree(nnz_o);
    2025:   }
    2026:   return(0);
    2027: }

    2029: PetscErrorCode MatRealPart_MPIBAIJ(Mat A)
    2030: {
    2031:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    2035:   MatRealPart(a->A);
    2036:   MatRealPart(a->B);
    2037:   return(0);
    2038: }

    2040: PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A)
    2041: {
    2042:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    2046:   MatImaginaryPart(a->A);
    2047:   MatImaginaryPart(a->B);
    2048:   return(0);
    2049: }

    2051: PetscErrorCode MatCreateSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
    2052: {
    2054:   IS             iscol_local;
    2055:   PetscInt       csize;

    2058:   ISGetLocalSize(iscol,&csize);
    2059:   if (call == MAT_REUSE_MATRIX) {
    2060:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
    2061:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
    2062:   } else {
    2063:     ISAllGather(iscol,&iscol_local);
    2064:   }
    2065:   MatCreateSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
    2066:   if (call == MAT_INITIAL_MATRIX) {
    2067:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
    2068:     ISDestroy(&iscol_local);
    2069:   }
    2070:   return(0);
    2071: }

    2073: /*
    2074:   Not great since it makes two copies of the submatrix, first an SeqBAIJ
    2075:   in local and then by concatenating the local matrices the end result.
    2076:   Writing it directly would be much like MatCreateSubMatrices_MPIBAIJ().
    2077:   This routine is used for BAIJ and SBAIJ matrices (unfortunate dependency).
    2078: */
    2079: PetscErrorCode MatCreateSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
    2080: {
    2082:   PetscMPIInt    rank,size;
    2083:   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs;
    2084:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
    2085:   Mat            M,Mreuse;
    2086:   MatScalar      *vwork,*aa;
    2087:   MPI_Comm       comm;
    2088:   IS             isrow_new, iscol_new;
    2089:   Mat_SeqBAIJ    *aij;

    2092:   PetscObjectGetComm((PetscObject)mat,&comm);
    2093:   MPI_Comm_rank(comm,&rank);
    2094:   MPI_Comm_size(comm,&size);
    2095:   /* The compression and expansion should be avoided. Doesn't point
    2096:      out errors, might change the indices, hence buggey */
    2097:   ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);
    2098:   ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);

    2100:   if (call ==  MAT_REUSE_MATRIX) {
    2101:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
    2102:     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
    2103:     MatCreateSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&Mreuse);
    2104:   } else {
    2105:     MatCreateSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&Mreuse);
    2106:   }
    2107:   ISDestroy(&isrow_new);
    2108:   ISDestroy(&iscol_new);
    2109:   /*
    2110:       m - number of local rows
    2111:       n - number of columns (same on all processors)
    2112:       rstart - first row in new global matrix generated
    2113:   */
    2114:   MatGetBlockSize(mat,&bs);
    2115:   MatGetSize(Mreuse,&m,&n);
    2116:   m    = m/bs;
    2117:   n    = n/bs;

    2119:   if (call == MAT_INITIAL_MATRIX) {
    2120:     aij = (Mat_SeqBAIJ*)(Mreuse)->data;
    2121:     ii  = aij->i;
    2122:     jj  = aij->j;

    2124:     /*
    2125:         Determine the number of non-zeros in the diagonal and off-diagonal
    2126:         portions of the matrix in order to do correct preallocation
    2127:     */

    2129:     /* first get start and end of "diagonal" columns */
    2130:     if (csize == PETSC_DECIDE) {
    2131:       ISGetSize(isrow,&mglobal);
    2132:       if (mglobal == n*bs) { /* square matrix */
    2133:         nlocal = m;
    2134:       } else {
    2135:         nlocal = n/size + ((n % size) > rank);
    2136:       }
    2137:     } else {
    2138:       nlocal = csize/bs;
    2139:     }
    2140:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
    2141:     rstart = rend - nlocal;
    2142:     if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n);

    2144:     /* next, compute all the lengths */
    2145:     PetscMalloc2(m+1,&dlens,m+1,&olens);
    2146:     for (i=0; i<m; i++) {
    2147:       jend = ii[i+1] - ii[i];
    2148:       olen = 0;
    2149:       dlen = 0;
    2150:       for (j=0; j<jend; j++) {
    2151:         if (*jj < rstart || *jj >= rend) olen++;
    2152:         else dlen++;
    2153:         jj++;
    2154:       }
    2155:       olens[i] = olen;
    2156:       dlens[i] = dlen;
    2157:     }
    2158:     MatCreate(comm,&M);
    2159:     MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);
    2160:     MatSetType(M,((PetscObject)mat)->type_name);
    2161:     MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);
    2162:     MatMPISBAIJSetPreallocation(M,bs,0,dlens,0,olens);
    2163:     PetscFree2(dlens,olens);
    2164:   } else {
    2165:     PetscInt ml,nl;

    2167:     M    = *newmat;
    2168:     MatGetLocalSize(M,&ml,&nl);
    2169:     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
    2170:     MatZeroEntries(M);
    2171:     /*
    2172:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
    2173:        rather than the slower MatSetValues().
    2174:     */
    2175:     M->was_assembled = PETSC_TRUE;
    2176:     M->assembled     = PETSC_FALSE;
    2177:   }
    2178:   MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);
    2179:   MatGetOwnershipRange(M,&rstart,&rend);
    2180:   aij  = (Mat_SeqBAIJ*)(Mreuse)->data;
    2181:   ii   = aij->i;
    2182:   jj   = aij->j;
    2183:   aa   = aij->a;
    2184:   for (i=0; i<m; i++) {
    2185:     row   = rstart/bs + i;
    2186:     nz    = ii[i+1] - ii[i];
    2187:     cwork = jj;     jj += nz;
    2188:     vwork = aa;     aa += nz*bs*bs;
    2189:     MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
    2190:   }

    2192:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
    2193:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
    2194:   *newmat = M;

    2196:   /* save submatrix used in processor for next request */
    2197:   if (call ==  MAT_INITIAL_MATRIX) {
    2198:     PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
    2199:     PetscObjectDereference((PetscObject)Mreuse);
    2200:   }
    2201:   return(0);
    2202: }

    2204: PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B)
    2205: {
    2206:   MPI_Comm       comm,pcomm;
    2207:   PetscInt       clocal_size,nrows;
    2208:   const PetscInt *rows;
    2209:   PetscMPIInt    size;
    2210:   IS             crowp,lcolp;

    2214:   PetscObjectGetComm((PetscObject)A,&comm);
    2215:   /* make a collective version of 'rowp' */
    2216:   PetscObjectGetComm((PetscObject)rowp,&pcomm);
    2217:   if (pcomm==comm) {
    2218:     crowp = rowp;
    2219:   } else {
    2220:     ISGetSize(rowp,&nrows);
    2221:     ISGetIndices(rowp,&rows);
    2222:     ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);
    2223:     ISRestoreIndices(rowp,&rows);
    2224:   }
    2225:   ISSetPermutation(crowp);
    2226:   /* make a local version of 'colp' */
    2227:   PetscObjectGetComm((PetscObject)colp,&pcomm);
    2228:   MPI_Comm_size(pcomm,&size);
    2229:   if (size==1) {
    2230:     lcolp = colp;
    2231:   } else {
    2232:     ISAllGather(colp,&lcolp);
    2233:   }
    2234:   ISSetPermutation(lcolp);
    2235:   /* now we just get the submatrix */
    2236:   MatGetLocalSize(A,NULL,&clocal_size);
    2237:   MatCreateSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);
    2238:   /* clean up */
    2239:   if (pcomm!=comm) {
    2240:     ISDestroy(&crowp);
    2241:   }
    2242:   if (size>1) {
    2243:     ISDestroy(&lcolp);
    2244:   }
    2245:   return(0);
    2246: }

    2248: PetscErrorCode  MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
    2249: {
    2250:   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data;
    2251:   Mat_SeqBAIJ *B    = (Mat_SeqBAIJ*)baij->B->data;

    2254:   if (nghosts) *nghosts = B->nbs;
    2255:   if (ghosts) *ghosts = baij->garray;
    2256:   return(0);
    2257: }

    2259: PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat)
    2260: {
    2261:   Mat            B;
    2262:   Mat_MPIBAIJ    *a  = (Mat_MPIBAIJ*)A->data;
    2263:   Mat_SeqBAIJ    *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data;
    2264:   Mat_SeqAIJ     *b;
    2266:   PetscMPIInt    size,rank,*recvcounts = 0,*displs = 0;
    2267:   PetscInt       sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs;
    2268:   PetscInt       m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf;

    2271:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
    2272:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

    2274:   /* ----------------------------------------------------------------
    2275:      Tell every processor the number of nonzeros per row
    2276:   */
    2277:   PetscMalloc1(A->rmap->N/bs,&lens);
    2278:   for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) {
    2279:     lens[i] = ad->i[i-A->rmap->rstart/bs+1] - ad->i[i-A->rmap->rstart/bs] + bd->i[i-A->rmap->rstart/bs+1] - bd->i[i-A->rmap->rstart/bs];
    2280:   }
    2281:   PetscMalloc1(2*size,&recvcounts);
    2282:   displs    = recvcounts + size;
    2283:   for (i=0; i<size; i++) {
    2284:     recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs;
    2285:     displs[i]     = A->rmap->range[i]/bs;
    2286:   }
    2287: #if defined(PETSC_HAVE_MPI_IN_PLACE)
    2288:   MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
    2289: #else
    2290:   sendcount = A->rmap->rend/bs - A->rmap->rstart/bs;
    2291:   MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
    2292: #endif
    2293:   /* ---------------------------------------------------------------
    2294:      Create the sequential matrix of the same type as the local block diagonal
    2295:   */
    2296:   MatCreate(PETSC_COMM_SELF,&B);
    2297:   MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);
    2298:   MatSetType(B,MATSEQAIJ);
    2299:   MatSeqAIJSetPreallocation(B,0,lens);
    2300:   b    = (Mat_SeqAIJ*)B->data;

    2302:   /*--------------------------------------------------------------------
    2303:     Copy my part of matrix column indices over
    2304:   */
    2305:   sendcount  = ad->nz + bd->nz;
    2306:   jsendbuf   = b->j + b->i[rstarts[rank]/bs];
    2307:   a_jsendbuf = ad->j;
    2308:   b_jsendbuf = bd->j;
    2309:   n          = A->rmap->rend/bs - A->rmap->rstart/bs;
    2310:   cnt        = 0;
    2311:   for (i=0; i<n; i++) {

    2313:     /* put in lower diagonal portion */
    2314:     m = bd->i[i+1] - bd->i[i];
    2315:     while (m > 0) {
    2316:       /* is it above diagonal (in bd (compressed) numbering) */
    2317:       if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break;
    2318:       jsendbuf[cnt++] = garray[*b_jsendbuf++];
    2319:       m--;
    2320:     }

    2322:     /* put in diagonal portion */
    2323:     for (j=ad->i[i]; j<ad->i[i+1]; j++) {
    2324:       jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++;
    2325:     }

    2327:     /* put in upper diagonal portion */
    2328:     while (m-- > 0) {
    2329:       jsendbuf[cnt++] = garray[*b_jsendbuf++];
    2330:     }
    2331:   }
    2332:   if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt);

    2334:   /*--------------------------------------------------------------------
    2335:     Gather all column indices to all processors
    2336:   */
    2337:   for (i=0; i<size; i++) {
    2338:     recvcounts[i] = 0;
    2339:     for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) {
    2340:       recvcounts[i] += lens[j];
    2341:     }
    2342:   }
    2343:   displs[0] = 0;
    2344:   for (i=1; i<size; i++) {
    2345:     displs[i] = displs[i-1] + recvcounts[i-1];
    2346:   }
    2347: #if defined(PETSC_HAVE_MPI_IN_PLACE)
    2348:   MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
    2349: #else
    2350:   MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
    2351: #endif
    2352:   /*--------------------------------------------------------------------
    2353:     Assemble the matrix into useable form (note numerical values not yet set)
    2354:   */
    2355:   /* set the b->ilen (length of each row) values */
    2356:   PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));
    2357:   /* set the b->i indices */
    2358:   b->i[0] = 0;
    2359:   for (i=1; i<=A->rmap->N/bs; i++) {
    2360:     b->i[i] = b->i[i-1] + lens[i-1];
    2361:   }
    2362:   PetscFree(lens);
    2363:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    2364:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    2365:   PetscFree(recvcounts);

    2367:   if (A->symmetric) {
    2368:     MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);
    2369:   } else if (A->hermitian) {
    2370:     MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);
    2371:   } else if (A->structurally_symmetric) {
    2372:     MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);
    2373:   }
    2374:   *newmat = B;
    2375:   return(0);
    2376: }

    2378: PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    2379: {
    2380:   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
    2382:   Vec            bb1 = 0;

    2385:   if (flag == SOR_APPLY_UPPER) {
    2386:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2387:     return(0);
    2388:   }

    2390:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) {
    2391:     VecDuplicate(bb,&bb1);
    2392:   }

    2394:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
    2395:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    2396:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2397:       its--;
    2398:     }

    2400:     while (its--) {
    2401:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
    2402:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

    2404:       /* update rhs: bb1 = bb - B*x */
    2405:       VecScale(mat->lvec,-1.0);
    2406:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

    2408:       /* local sweep */
    2409:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
    2410:     }
    2411:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
    2412:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    2413:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2414:       its--;
    2415:     }
    2416:     while (its--) {
    2417:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
    2418:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

    2420:       /* update rhs: bb1 = bb - B*x */
    2421:       VecScale(mat->lvec,-1.0);
    2422:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

    2424:       /* local sweep */
    2425:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
    2426:     }
    2427:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
    2428:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    2429:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2430:       its--;
    2431:     }
    2432:     while (its--) {
    2433:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
    2434:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

    2436:       /* update rhs: bb1 = bb - B*x */
    2437:       VecScale(mat->lvec,-1.0);
    2438:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

    2440:       /* local sweep */
    2441:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
    2442:     }
    2443:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported");

    2445:   VecDestroy(&bb1);
    2446:   return(0);
    2447: }

    2449: PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms)
    2450: {
    2452:   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)A->data;
    2453:   PetscInt       N,i,*garray = aij->garray;
    2454:   PetscInt       ib,jb,bs = A->rmap->bs;
    2455:   Mat_SeqBAIJ    *a_aij = (Mat_SeqBAIJ*) aij->A->data;
    2456:   MatScalar      *a_val = a_aij->a;
    2457:   Mat_SeqBAIJ    *b_aij = (Mat_SeqBAIJ*) aij->B->data;
    2458:   MatScalar      *b_val = b_aij->a;
    2459:   PetscReal      *work;

    2462:   MatGetSize(A,NULL,&N);
    2463:   PetscCalloc1(N,&work);
    2464:   if (type == NORM_2) {
    2465:     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
    2466:       for (jb=0; jb<bs; jb++) {
    2467:         for (ib=0; ib<bs; ib++) {
    2468:           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val);
    2469:           a_val++;
    2470:         }
    2471:       }
    2472:     }
    2473:     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
    2474:       for (jb=0; jb<bs; jb++) {
    2475:         for (ib=0; ib<bs; ib++) {
    2476:           work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val);
    2477:           b_val++;
    2478:         }
    2479:       }
    2480:     }
    2481:   } else if (type == NORM_1) {
    2482:     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
    2483:       for (jb=0; jb<bs; jb++) {
    2484:         for (ib=0; ib<bs; ib++) {
    2485:           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val);
    2486:           a_val++;
    2487:         }
    2488:       }
    2489:     }
    2490:     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
    2491:       for (jb=0; jb<bs; jb++) {
    2492:        for (ib=0; ib<bs; ib++) {
    2493:           work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val);
    2494:           b_val++;
    2495:         }
    2496:       }
    2497:     }
    2498:   } else if (type == NORM_INFINITY) {
    2499:     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
    2500:       for (jb=0; jb<bs; jb++) {
    2501:         for (ib=0; ib<bs; ib++) {
    2502:           int col = A->cmap->rstart + a_aij->j[i] * bs + jb;
    2503:           work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]);
    2504:           a_val++;
    2505:         }
    2506:       }
    2507:     }
    2508:     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
    2509:       for (jb=0; jb<bs; jb++) {
    2510:         for (ib=0; ib<bs; ib++) {
    2511:           int col = garray[b_aij->j[i]] * bs + jb;
    2512:           work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]);
    2513:           b_val++;
    2514:         }
    2515:       }
    2516:     }
    2517:   } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
    2518:   if (type == NORM_INFINITY) {
    2519:     MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
    2520:   } else {
    2521:     MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
    2522:   }
    2523:   PetscFree(work);
    2524:   if (type == NORM_2) {
    2525:     for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]);
    2526:   }
    2527:   return(0);
    2528: }

    2530: PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values)
    2531: {
    2532:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*) A->data;

    2536:   MatInvertBlockDiagonal(a->A,values);
    2537:   A->factorerrortype             = a->A->factorerrortype;
    2538:   A->factorerror_zeropivot_value = a->A->factorerror_zeropivot_value;
    2539:   A->factorerror_zeropivot_row   = a->A->factorerror_zeropivot_row;
    2540:   return(0);
    2541: }

    2543: PetscErrorCode MatShift_MPIBAIJ(Mat Y,PetscScalar a)
    2544: {
    2546:   Mat_MPIBAIJ    *maij = (Mat_MPIBAIJ*)Y->data;
    2547:   Mat_SeqBAIJ    *aij = (Mat_SeqBAIJ*)maij->A->data;

    2550:   if (!Y->preallocated) {
    2551:     MatMPIBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
    2552:   } else if (!aij->nz) {
    2553:     PetscInt nonew = aij->nonew;
    2554:     MatSeqBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
    2555:     aij->nonew = nonew;
    2556:   }
    2557:   MatShift_Basic(Y,a);
    2558:   return(0);
    2559: }

    2561: PetscErrorCode MatMissingDiagonal_MPIBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
    2562: {
    2563:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    2567:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
    2568:   MatMissingDiagonal(a->A,missing,d);
    2569:   if (d) {
    2570:     PetscInt rstart;
    2571:     MatGetOwnershipRange(A,&rstart,NULL);
    2572:     *d += rstart/A->rmap->bs;

    2574:   }
    2575:   return(0);
    2576: }

    2578: PetscErrorCode  MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a)
    2579: {
    2581:   *a = ((Mat_MPIBAIJ*)A->data)->A;
    2582:   return(0);
    2583: }

    2585: /* -------------------------------------------------------------------*/
    2586: static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ,
    2587:                                        MatGetRow_MPIBAIJ,
    2588:                                        MatRestoreRow_MPIBAIJ,
    2589:                                        MatMult_MPIBAIJ,
    2590:                                 /* 4*/ MatMultAdd_MPIBAIJ,
    2591:                                        MatMultTranspose_MPIBAIJ,
    2592:                                        MatMultTransposeAdd_MPIBAIJ,
    2593:                                        0,
    2594:                                        0,
    2595:                                        0,
    2596:                                 /*10*/ 0,
    2597:                                        0,
    2598:                                        0,
    2599:                                        MatSOR_MPIBAIJ,
    2600:                                        MatTranspose_MPIBAIJ,
    2601:                                 /*15*/ MatGetInfo_MPIBAIJ,
    2602:                                        MatEqual_MPIBAIJ,
    2603:                                        MatGetDiagonal_MPIBAIJ,
    2604:                                        MatDiagonalScale_MPIBAIJ,
    2605:                                        MatNorm_MPIBAIJ,
    2606:                                 /*20*/ MatAssemblyBegin_MPIBAIJ,
    2607:                                        MatAssemblyEnd_MPIBAIJ,
    2608:                                        MatSetOption_MPIBAIJ,
    2609:                                        MatZeroEntries_MPIBAIJ,
    2610:                                 /*24*/ MatZeroRows_MPIBAIJ,
    2611:                                        0,
    2612:                                        0,
    2613:                                        0,
    2614:                                        0,
    2615:                                 /*29*/ MatSetUp_MPIBAIJ,
    2616:                                        0,
    2617:                                        0,
    2618:                                        MatGetDiagonalBlock_MPIBAIJ,
    2619:                                        0,
    2620:                                 /*34*/ MatDuplicate_MPIBAIJ,
    2621:                                        0,
    2622:                                        0,
    2623:                                        0,
    2624:                                        0,
    2625:                                 /*39*/ MatAXPY_MPIBAIJ,
    2626:                                        MatCreateSubMatrices_MPIBAIJ,
    2627:                                        MatIncreaseOverlap_MPIBAIJ,
    2628:                                        MatGetValues_MPIBAIJ,
    2629:                                        MatCopy_MPIBAIJ,
    2630:                                 /*44*/ 0,
    2631:                                        MatScale_MPIBAIJ,
    2632:                                        MatShift_MPIBAIJ,
    2633:                                        0,
    2634:                                        MatZeroRowsColumns_MPIBAIJ,
    2635:                                 /*49*/ 0,
    2636:                                        0,
    2637:                                        0,
    2638:                                        0,
    2639:                                        0,
    2640:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
    2641:                                        0,
    2642:                                        MatSetUnfactored_MPIBAIJ,
    2643:                                        MatPermute_MPIBAIJ,
    2644:                                        MatSetValuesBlocked_MPIBAIJ,
    2645:                                 /*59*/ MatCreateSubMatrix_MPIBAIJ,
    2646:                                        MatDestroy_MPIBAIJ,
    2647:                                        MatView_MPIBAIJ,
    2648:                                        0,
    2649:                                        0,
    2650:                                 /*64*/ 0,
    2651:                                        0,
    2652:                                        0,
    2653:                                        0,
    2654:                                        0,
    2655:                                 /*69*/ MatGetRowMaxAbs_MPIBAIJ,
    2656:                                        0,
    2657:                                        0,
    2658:                                        0,
    2659:                                        0,
    2660:                                 /*74*/ 0,
    2661:                                        MatFDColoringApply_BAIJ,
    2662:                                        0,
    2663:                                        0,
    2664:                                        0,
    2665:                                 /*79*/ 0,
    2666:                                        0,
    2667:                                        0,
    2668:                                        0,
    2669:                                        MatLoad_MPIBAIJ,
    2670:                                 /*84*/ 0,
    2671:                                        0,
    2672:                                        0,
    2673:                                        0,
    2674:                                        0,
    2675:                                 /*89*/ 0,
    2676:                                        0,
    2677:                                        0,
    2678:                                        0,
    2679:                                        0,
    2680:                                 /*94*/ 0,
    2681:                                        0,
    2682:                                        0,
    2683:                                        0,
    2684:                                        0,
    2685:                                 /*99*/ 0,
    2686:                                        0,
    2687:                                        0,
    2688:                                        0,
    2689:                                        0,
    2690:                                 /*104*/0,
    2691:                                        MatRealPart_MPIBAIJ,
    2692:                                        MatImaginaryPart_MPIBAIJ,
    2693:                                        0,
    2694:                                        0,
    2695:                                 /*109*/0,
    2696:                                        0,
    2697:                                        0,
    2698:                                        0,
    2699:                                        MatMissingDiagonal_MPIBAIJ,
    2700:                                 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ,
    2701:                                        0,
    2702:                                        MatGetGhosts_MPIBAIJ,
    2703:                                        0,
    2704:                                        0,
    2705:                                 /*119*/0,
    2706:                                        0,
    2707:                                        0,
    2708:                                        0,
    2709:                                        MatGetMultiProcBlock_MPIBAIJ,
    2710:                                 /*124*/0,
    2711:                                        MatGetColumnNorms_MPIBAIJ,
    2712:                                        MatInvertBlockDiagonal_MPIBAIJ,
    2713:                                        0,
    2714:                                        0,
    2715:                                /*129*/ 0,
    2716:                                        0,
    2717:                                        0,
    2718:                                        0,
    2719:                                        0,
    2720:                                /*134*/ 0,
    2721:                                        0,
    2722:                                        0,
    2723:                                        0,
    2724:                                        0,
    2725:                                /*139*/ MatSetBlockSizes_Default,
    2726:                                        0,
    2727:                                        0,
    2728:                                        MatFDColoringSetUp_MPIXAIJ,
    2729:                                        0,
    2730:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIBAIJ
    2731: };

    2734: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*);
    2735: PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*);

    2737: PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
    2738: {
    2739:   PetscInt       m,rstart,cstart,cend;
    2740:   PetscInt       i,j,dlen,olen,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
    2741:   const PetscInt *JJ    =0;
    2742:   PetscScalar    *values=0;
    2743:   PetscBool      roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented;

    2747:   PetscLayoutSetBlockSize(B->rmap,bs);
    2748:   PetscLayoutSetBlockSize(B->cmap,bs);
    2749:   PetscLayoutSetUp(B->rmap);
    2750:   PetscLayoutSetUp(B->cmap);
    2751:   PetscLayoutGetBlockSize(B->rmap,&bs);
    2752:   m      = B->rmap->n/bs;
    2753:   rstart = B->rmap->rstart/bs;
    2754:   cstart = B->cmap->rstart/bs;
    2755:   cend   = B->cmap->rend/bs;

    2757:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
    2758:   PetscMalloc2(m,&d_nnz,m,&o_nnz);
    2759:   for (i=0; i<m; i++) {
    2760:     nz = ii[i+1] - ii[i];
    2761:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
    2762:     nz_max = PetscMax(nz_max,nz);
    2763:     dlen   = 0;
    2764:     olen   = 0;
    2765:     JJ     = jj + ii[i];
    2766:     for (j=0; j<nz; j++) {
    2767:       if (*JJ < cstart || *JJ >= cend) olen++;
    2768:       else dlen++;
    2769:       JJ++;
    2770:     }
    2771:     d_nnz[i] = dlen;
    2772:     o_nnz[i] = olen;
    2773:   }
    2774:   MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
    2775:   PetscFree2(d_nnz,o_nnz);

    2777:   values = (PetscScalar*)V;
    2778:   if (!values) {
    2779:     PetscCalloc1(bs*bs*nz_max,&values);
    2780:   }
    2781:   for (i=0; i<m; i++) {
    2782:     PetscInt          row    = i + rstart;
    2783:     PetscInt          ncols  = ii[i+1] - ii[i];
    2784:     const PetscInt    *icols = jj + ii[i];
    2785:     if (!roworiented) {         /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */
    2786:       const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
    2787:       MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
    2788:     } else {                    /* block ordering does not match so we can only insert one block at a time. */
    2789:       PetscInt j;
    2790:       for (j=0; j<ncols; j++) {
    2791:         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
    2792:         MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);
    2793:       }
    2794:     }
    2795:   }

    2797:   if (!V) { PetscFree(values); }
    2798:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    2799:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    2800:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    2801:   return(0);
    2802: }

    2804: /*@C
    2805:    MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
    2806:    (the default parallel PETSc format).

    2808:    Collective on MPI_Comm

    2810:    Input Parameters:
    2811: +  B - the matrix
    2812: .  bs - the block size
    2813: .  i - the indices into j for the start of each local row (starts with zero)
    2814: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
    2815: -  v - optional values in the matrix

    2817:    Level: developer

    2819:    Notes:
    2820:     The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED.  For example, C programs
    2821:    may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is
    2822:    over rows within a block and the last index is over columns within a block row.  Fortran programs will likely set
    2823:    MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
    2824:    block column and the second index is over columns within a block.

    2826: .keywords: matrix, aij, compressed row, sparse, parallel

    2828: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ
    2829: @*/
    2830: PetscErrorCode  MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
    2831: {

    2838:   PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
    2839:   return(0);
    2840: }

    2842: PetscErrorCode  MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
    2843: {
    2844:   Mat_MPIBAIJ    *b;
    2846:   PetscInt       i;

    2849:   MatSetBlockSize(B,PetscAbs(bs));
    2850:   PetscLayoutSetUp(B->rmap);
    2851:   PetscLayoutSetUp(B->cmap);
    2852:   PetscLayoutGetBlockSize(B->rmap,&bs);

    2854:   if (d_nnz) {
    2855:     for (i=0; i<B->rmap->n/bs; i++) {
    2856:       if (d_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]);
    2857:     }
    2858:   }
    2859:   if (o_nnz) {
    2860:     for (i=0; i<B->rmap->n/bs; i++) {
    2861:       if (o_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]);
    2862:     }
    2863:   }

    2865:   b      = (Mat_MPIBAIJ*)B->data;
    2866:   b->bs2 = bs*bs;
    2867:   b->mbs = B->rmap->n/bs;
    2868:   b->nbs = B->cmap->n/bs;
    2869:   b->Mbs = B->rmap->N/bs;
    2870:   b->Nbs = B->cmap->N/bs;

    2872:   for (i=0; i<=b->size; i++) {
    2873:     b->rangebs[i] = B->rmap->range[i]/bs;
    2874:   }
    2875:   b->rstartbs = B->rmap->rstart/bs;
    2876:   b->rendbs   = B->rmap->rend/bs;
    2877:   b->cstartbs = B->cmap->rstart/bs;
    2878:   b->cendbs   = B->cmap->rend/bs;

    2880: #if defined(PETSC_USE_CTABLE)
    2881:   PetscTableDestroy(&b->colmap);
    2882: #else
    2883:   PetscFree(b->colmap);
    2884: #endif
    2885:   PetscFree(b->garray);
    2886:   VecDestroy(&b->lvec);
    2887:   VecScatterDestroy(&b->Mvctx);

    2889:   /* Because the B will have been resized we simply destroy it and create a new one each time */
    2890:   MatDestroy(&b->B);
    2891:   MatCreate(PETSC_COMM_SELF,&b->B);
    2892:   MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
    2893:   MatSetType(b->B,MATSEQBAIJ);
    2894:   PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);

    2896:   if (!B->preallocated) {
    2897:     MatCreate(PETSC_COMM_SELF,&b->A);
    2898:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
    2899:     MatSetType(b->A,MATSEQBAIJ);
    2900:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
    2901:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
    2902:   }

    2904:   MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
    2905:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);
    2906:   B->preallocated  = PETSC_TRUE;
    2907:   B->was_assembled = PETSC_FALSE;
    2908:   B->assembled     = PETSC_FALSE;
    2909:   return(0);
    2910: }

    2912: extern PetscErrorCode  MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec);
    2913: extern PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal);

    2915: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj)
    2916: {
    2917:   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;
    2919:   Mat_SeqBAIJ    *d  = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data;
    2920:   PetscInt       M   = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs;
    2921:   const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray;

    2924:   PetscMalloc1(M+1,&ii);
    2925:   ii[0] = 0;
    2926:   for (i=0; i<M; i++) {
    2927:     if ((id[i+1] - id[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,id[i],id[i+1]);
    2928:     if ((io[i+1] - io[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,io[i],io[i+1]);
    2929:     ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i];
    2930:     /* remove one from count of matrix has diagonal */
    2931:     for (j=id[i]; j<id[i+1]; j++) {
    2932:       if (jd[j] == i) {ii[i+1]--;break;}
    2933:     }
    2934:   }
    2935:   PetscMalloc1(ii[M],&jj);
    2936:   cnt  = 0;
    2937:   for (i=0; i<M; i++) {
    2938:     for (j=io[i]; j<io[i+1]; j++) {
    2939:       if (garray[jo[j]] > rstart) break;
    2940:       jj[cnt++] = garray[jo[j]];
    2941:     }
    2942:     for (k=id[i]; k<id[i+1]; k++) {
    2943:       if (jd[k] != i) {
    2944:         jj[cnt++] = rstart + jd[k];
    2945:       }
    2946:     }
    2947:     for (; j<io[i+1]; j++) {
    2948:       jj[cnt++] = garray[jo[j]];
    2949:     }
    2950:   }
    2951:   MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);
    2952:   return(0);
    2953: }

    2955:  #include <../src/mat/impls/aij/mpi/mpiaij.h>

    2957: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*);

    2959: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
    2960: {
    2962:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
    2963:   Mat            B;
    2964:   Mat_MPIAIJ     *b;

    2967:   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");

    2969:   if (reuse == MAT_REUSE_MATRIX) {
    2970:     B = *newmat;
    2971:   } else {
    2972:     MatCreate(PetscObjectComm((PetscObject)A),&B);
    2973:     MatSetType(B,MATMPIAIJ);
    2974:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    2975:     MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);
    2976:     MatSeqAIJSetPreallocation(B,0,NULL);
    2977:     MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);
    2978:   }
    2979:   b = (Mat_MPIAIJ*) B->data;

    2981:   if (reuse == MAT_REUSE_MATRIX) {
    2982:     MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_REUSE_MATRIX, &b->A);
    2983:     MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_REUSE_MATRIX, &b->B);
    2984:   } else {
    2985:     MatDestroy(&b->A);
    2986:     MatDestroy(&b->B);
    2987:     MatDisAssemble_MPIBAIJ(A);
    2988:     MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);
    2989:     MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);
    2990:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    2991:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    2992:   }
    2993:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    2994:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

    2996:   if (reuse == MAT_INPLACE_MATRIX) {
    2997:     MatHeaderReplace(A,&B);
    2998:   } else {
    2999:    *newmat = B;
    3000:   }
    3001:   return(0);
    3002: }

    3004: /*MC
    3005:    MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices.

    3007:    Options Database Keys:
    3008: + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions()
    3009: . -mat_block_size <bs> - set the blocksize used to store the matrix
    3010: - -mat_use_hash_table <fact>

    3012:   Level: beginner

    3014: .seealso: MatCreateMPIBAIJ
    3015: M*/

    3017: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*);
    3018: PETSC_INTERN PetscErrorCode MatPtAP_IS_XAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);

    3020: PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B)
    3021: {
    3022:   Mat_MPIBAIJ    *b;
    3024:   PetscBool      flg = PETSC_FALSE;

    3027:   PetscNewLog(B,&b);
    3028:   B->data = (void*)b;

    3030:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
    3031:   B->assembled = PETSC_FALSE;

    3033:   B->insertmode = NOT_SET_VALUES;
    3034:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
    3035:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

    3037:   /* build local table of row and column ownerships */
    3038:   PetscMalloc1(b->size+1,&b->rangebs);

    3040:   /* build cache for off array entries formed */
    3041:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

    3043:   b->donotstash  = PETSC_FALSE;
    3044:   b->colmap      = NULL;
    3045:   b->garray      = NULL;
    3046:   b->roworiented = PETSC_TRUE;

    3048:   /* stuff used in block assembly */
    3049:   b->barray = 0;

    3051:   /* stuff used for matrix vector multiply */
    3052:   b->lvec  = 0;
    3053:   b->Mvctx = 0;

    3055:   /* stuff for MatGetRow() */
    3056:   b->rowindices   = 0;
    3057:   b->rowvalues    = 0;
    3058:   b->getrowactive = PETSC_FALSE;

    3060:   /* hash table stuff */
    3061:   b->ht           = 0;
    3062:   b->hd           = 0;
    3063:   b->ht_size      = 0;
    3064:   b->ht_flag      = PETSC_FALSE;
    3065:   b->ht_fact      = 0;
    3066:   b->ht_total_ct  = 0;
    3067:   b->ht_insert_ct = 0;

    3069:   /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
    3070:   b->ijonly = PETSC_FALSE;

    3073:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);
    3074:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);
    3075:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);
    3076: #if defined(PETSC_HAVE_HYPRE)
    3077:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_hypre_C",MatConvert_AIJ_HYPRE);
    3078: #endif
    3079:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);
    3080:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);
    3081:   PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);
    3082:   PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);
    3083:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);
    3084:   PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);
    3085:   PetscObjectComposeFunction((PetscObject)B,"MatPtAP_is_mpibaij_C",MatPtAP_IS_XAIJ);
    3086:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_is_C",MatConvert_XAIJ_IS);
    3087:   PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);

    3089:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");
    3090:   PetscOptionsName("-mat_use_hash_table","Use hash table to save time in constructing matrix","MatSetOption",&flg);
    3091:   if (flg) {
    3092:     PetscReal fact = 1.39;
    3093:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
    3094:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
    3095:     if (fact <= 1.0) fact = 1.39;
    3096:     MatMPIBAIJSetHashTableFactor(B,fact);
    3097:     PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
    3098:   }
    3099:   PetscOptionsEnd();
    3100:   return(0);
    3101: }

    3103: /*MC
    3104:    MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices.

    3106:    This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator,
    3107:    and MATMPIBAIJ otherwise.

    3109:    Options Database Keys:
    3110: . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions()

    3112:   Level: beginner

    3114: .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
    3115: M*/

    3117: /*@C
    3118:    MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format
    3119:    (block compressed row).  For good matrix assembly performance
    3120:    the user should preallocate the matrix storage by setting the parameters
    3121:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    3122:    performance can be increased by more than a factor of 50.

    3124:    Collective on Mat

    3126:    Input Parameters:
    3127: +  B - the matrix
    3128: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    3129:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    3130: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
    3131:            submatrix  (same for all local rows)
    3132: .  d_nnz - array containing the number of block nonzeros in the various block rows
    3133:            of the in diagonal portion of the local (possibly different for each block
    3134:            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry and
    3135:            set it even if it is zero.
    3136: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
    3137:            submatrix (same for all local rows).
    3138: -  o_nnz - array containing the number of nonzeros in the various block rows of the
    3139:            off-diagonal portion of the local submatrix (possibly different for
    3140:            each block row) or NULL.

    3142:    If the *_nnz parameter is given then the *_nz parameter is ignored

    3144:    Options Database Keys:
    3145: +   -mat_block_size - size of the blocks to use
    3146: -   -mat_use_hash_table <fact>

    3148:    Notes:
    3149:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
    3150:    than it must be used on all processors that share the object for that argument.

    3152:    Storage Information:
    3153:    For a square global matrix we define each processor's diagonal portion
    3154:    to be its local rows and the corresponding columns (a square submatrix);
    3155:    each processor's off-diagonal portion encompasses the remainder of the
    3156:    local matrix (a rectangular submatrix).

    3158:    The user can specify preallocated storage for the diagonal part of
    3159:    the local submatrix with either d_nz or d_nnz (not both).  Set
    3160:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
    3161:    memory allocation.  Likewise, specify preallocated storage for the
    3162:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

    3164:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
    3165:    the figure below we depict these three local rows and all columns (0-11).

    3167: .vb
    3168:            0 1 2 3 4 5 6 7 8 9 10 11
    3169:           --------------------------
    3170:    row 3  |o o o d d d o o o o  o  o
    3171:    row 4  |o o o d d d o o o o  o  o
    3172:    row 5  |o o o d d d o o o o  o  o
    3173:           --------------------------
    3174: .ve

    3176:    Thus, any entries in the d locations are stored in the d (diagonal)
    3177:    submatrix, and any entries in the o locations are stored in the
    3178:    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
    3179:    stored simply in the MATSEQBAIJ format for compressed row storage.

    3181:    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
    3182:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
    3183:    In general, for PDE problems in which most nonzeros are near the diagonal,
    3184:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
    3185:    or you will get TERRIBLE performance; see the users' manual chapter on
    3186:    matrices.

    3188:    You can call MatGetInfo() to get information on how effective the preallocation was;
    3189:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
    3190:    You can also run with the option -info and look for messages with the string
    3191:    malloc in them to see if additional memory allocation was needed.

    3193:    Level: intermediate

    3195: .keywords: matrix, block, aij, compressed row, sparse, parallel

    3197: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership()
    3198: @*/
    3199: PetscErrorCode  MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
    3200: {

    3207:   PetscTryMethod(B,"MatMPIBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
    3208:   return(0);
    3209: }

    3211: /*@C
    3212:    MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format
    3213:    (block compressed row).  For good matrix assembly performance
    3214:    the user should preallocate the matrix storage by setting the parameters
    3215:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    3216:    performance can be increased by more than a factor of 50.

    3218:    Collective on MPI_Comm

    3220:    Input Parameters:
    3221: +  comm - MPI communicator
    3222: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    3223:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    3224: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
    3225:            This value should be the same as the local size used in creating the
    3226:            y vector for the matrix-vector product y = Ax.
    3227: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
    3228:            This value should be the same as the local size used in creating the
    3229:            x vector for the matrix-vector product y = Ax.
    3230: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    3231: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    3232: .  d_nz  - number of nonzero blocks per block row in diagonal portion of local
    3233:            submatrix  (same for all local rows)
    3234: .  d_nnz - array containing the number of nonzero blocks in the various block rows
    3235:            of the in diagonal portion of the local (possibly different for each block
    3236:            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry
    3237:            and set it even if it is zero.
    3238: .  o_nz  - number of nonzero blocks per block row in the off-diagonal portion of local
    3239:            submatrix (same for all local rows).
    3240: -  o_nnz - array containing the number of nonzero blocks in the various block rows of the
    3241:            off-diagonal portion of the local submatrix (possibly different for
    3242:            each block row) or NULL.

    3244:    Output Parameter:
    3245: .  A - the matrix

    3247:    Options Database Keys:
    3248: +   -mat_block_size - size of the blocks to use
    3249: -   -mat_use_hash_table <fact>

    3251:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
    3252:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
    3253:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

    3255:    Notes:
    3256:    If the *_nnz parameter is given then the *_nz parameter is ignored

    3258:    A nonzero block is any block that as 1 or more nonzeros in it

    3260:    The user MUST specify either the local or global matrix dimensions
    3261:    (possibly both).

    3263:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
    3264:    than it must be used on all processors that share the object for that argument.

    3266:    Storage Information:
    3267:    For a square global matrix we define each processor's diagonal portion
    3268:    to be its local rows and the corresponding columns (a square submatrix);
    3269:    each processor's off-diagonal portion encompasses the remainder of the
    3270:    local matrix (a rectangular submatrix).

    3272:    The user can specify preallocated storage for the diagonal part of
    3273:    the local submatrix with either d_nz or d_nnz (not both).  Set
    3274:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
    3275:    memory allocation.  Likewise, specify preallocated storage for the
    3276:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

    3278:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
    3279:    the figure below we depict these three local rows and all columns (0-11).

    3281: .vb
    3282:            0 1 2 3 4 5 6 7 8 9 10 11
    3283:           --------------------------
    3284:    row 3  |o o o d d d o o o o  o  o
    3285:    row 4  |o o o d d d o o o o  o  o
    3286:    row 5  |o o o d d d o o o o  o  o
    3287:           --------------------------
    3288: .ve

    3290:    Thus, any entries in the d locations are stored in the d (diagonal)
    3291:    submatrix, and any entries in the o locations are stored in the
    3292:    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
    3293:    stored simply in the MATSEQBAIJ format for compressed row storage.

    3295:    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
    3296:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
    3297:    In general, for PDE problems in which most nonzeros are near the diagonal,
    3298:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
    3299:    or you will get TERRIBLE performance; see the users' manual chapter on
    3300:    matrices.

    3302:    Level: intermediate

    3304: .keywords: matrix, block, aij, compressed row, sparse, parallel

    3306: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
    3307: @*/
    3308: PetscErrorCode  MatCreateBAIJ(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)
    3309: {
    3311:   PetscMPIInt    size;

    3314:   MatCreate(comm,A);
    3315:   MatSetSizes(*A,m,n,M,N);
    3316:   MPI_Comm_size(comm,&size);
    3317:   if (size > 1) {
    3318:     MatSetType(*A,MATMPIBAIJ);
    3319:     MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
    3320:   } else {
    3321:     MatSetType(*A,MATSEQBAIJ);
    3322:     MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
    3323:   }
    3324:   return(0);
    3325: }

    3327: static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
    3328: {
    3329:   Mat            mat;
    3330:   Mat_MPIBAIJ    *a,*oldmat = (Mat_MPIBAIJ*)matin->data;
    3332:   PetscInt       len=0;

    3335:   *newmat = 0;
    3336:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
    3337:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
    3338:   MatSetType(mat,((PetscObject)matin)->type_name);
    3339:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));

    3341:   mat->factortype   = matin->factortype;
    3342:   mat->preallocated = PETSC_TRUE;
    3343:   mat->assembled    = PETSC_TRUE;
    3344:   mat->insertmode   = NOT_SET_VALUES;

    3346:   a             = (Mat_MPIBAIJ*)mat->data;
    3347:   mat->rmap->bs = matin->rmap->bs;
    3348:   a->bs2        = oldmat->bs2;
    3349:   a->mbs        = oldmat->mbs;
    3350:   a->nbs        = oldmat->nbs;
    3351:   a->Mbs        = oldmat->Mbs;
    3352:   a->Nbs        = oldmat->Nbs;

    3354:   PetscLayoutReference(matin->rmap,&mat->rmap);
    3355:   PetscLayoutReference(matin->cmap,&mat->cmap);

    3357:   a->size         = oldmat->size;
    3358:   a->rank         = oldmat->rank;
    3359:   a->donotstash   = oldmat->donotstash;
    3360:   a->roworiented  = oldmat->roworiented;
    3361:   a->rowindices   = 0;
    3362:   a->rowvalues    = 0;
    3363:   a->getrowactive = PETSC_FALSE;
    3364:   a->barray       = 0;
    3365:   a->rstartbs     = oldmat->rstartbs;
    3366:   a->rendbs       = oldmat->rendbs;
    3367:   a->cstartbs     = oldmat->cstartbs;
    3368:   a->cendbs       = oldmat->cendbs;

    3370:   /* hash table stuff */
    3371:   a->ht           = 0;
    3372:   a->hd           = 0;
    3373:   a->ht_size      = 0;
    3374:   a->ht_flag      = oldmat->ht_flag;
    3375:   a->ht_fact      = oldmat->ht_fact;
    3376:   a->ht_total_ct  = 0;
    3377:   a->ht_insert_ct = 0;

    3379:   PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));
    3380:   if (oldmat->colmap) {
    3381: #if defined(PETSC_USE_CTABLE)
    3382:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
    3383: #else
    3384:     PetscMalloc1(a->Nbs,&a->colmap);
    3385:     PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
    3386:     PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));
    3387: #endif
    3388:   } else a->colmap = 0;

    3390:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
    3391:     PetscMalloc1(len,&a->garray);
    3392:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
    3393:     PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));
    3394:   } else a->garray = 0;

    3396:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
    3397:   VecDuplicate(oldmat->lvec,&a->lvec);
    3398:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
    3399:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
    3400:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

    3402:   MatDuplicate(oldmat->A,cpvalues,&a->A);
    3403:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
    3404:   MatDuplicate(oldmat->B,cpvalues,&a->B);
    3405:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
    3406:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
    3407:   *newmat = mat;
    3408:   return(0);
    3409: }

    3411: PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer)
    3412: {
    3414:   int            fd;
    3415:   PetscInt       i,nz,j,rstart,rend;
    3416:   PetscScalar    *vals,*buf;
    3417:   MPI_Comm       comm;
    3418:   MPI_Status     status;
    3419:   PetscMPIInt    rank,size,maxnz;
    3420:   PetscInt       header[4],*rowlengths = 0,M,N,m,*rowners,*cols;
    3421:   PetscInt       *locrowlens = NULL,*procsnz = NULL,*browners = NULL;
    3422:   PetscInt       jj,*mycols,*ibuf,bs = newmat->rmap->bs,Mbs,mbs,extra_rows,mmax;
    3423:   PetscMPIInt    tag    = ((PetscObject)viewer)->tag;
    3424:   PetscInt       *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount;
    3425:   PetscInt       dcount,kmax,k,nzcount,tmp,mend;

    3428:   /* force binary viewer to load .info file if it has not yet done so */
    3429:   PetscViewerSetUp(viewer);
    3430:   PetscObjectGetComm((PetscObject)viewer,&comm);
    3431:   PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");
    3432:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
    3433:   PetscOptionsEnd();
    3434:   if (bs < 0) bs = 1;

    3436:   MPI_Comm_size(comm,&size);
    3437:   MPI_Comm_rank(comm,&rank);
    3438:   PetscViewerBinaryGetDescriptor(viewer,&fd);
    3439:   if (!rank) {
    3440:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
    3441:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
    3442:     if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newmat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk, cannot load as MPIAIJ");
    3443:   }
    3444:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
    3445:   M    = header[1]; N = header[2];

    3447:   /* If global sizes are set, check if they are consistent with that given in the file */
    3448:   if (newmat->rmap->N >= 0 && newmat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newmat->rmap->N,M);
    3449:   if (newmat->cmap->N >= 0 && newmat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newmat->cmap->N,N);

    3451:   if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices");

    3453:   /*
    3454:      This code adds extra rows to make sure the number of rows is
    3455:      divisible by the blocksize
    3456:   */
    3457:   Mbs        = M/bs;
    3458:   extra_rows = bs - M + bs*Mbs;
    3459:   if (extra_rows == bs) extra_rows = 0;
    3460:   else                  Mbs++;
    3461:   if (extra_rows && !rank) {
    3462:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
    3463:   }

    3465:   /* determine ownership of all rows */
    3466:   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
    3467:     mbs = Mbs/size + ((Mbs % size) > rank);
    3468:     m   = mbs*bs;
    3469:   } else { /* User set */
    3470:     m   = newmat->rmap->n;
    3471:     mbs = m/bs;
    3472:   }
    3473:   PetscMalloc2(size+1,&rowners,size+1,&browners);
    3474:   MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

    3476:   /* process 0 needs enough room for process with most rows */
    3477:   if (!rank) {
    3478:     mmax = rowners[1];
    3479:     for (i=2; i<=size; i++) {
    3480:       mmax = PetscMax(mmax,rowners[i]);
    3481:     }
    3482:     mmax*=bs;
    3483:   } else mmax = -1;             /* unused, but compiler warns anyway */

    3485:   rowners[0] = 0;
    3486:   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
    3487:   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
    3488:   rstart = rowners[rank];
    3489:   rend   = rowners[rank+1];

    3491:   /* distribute row lengths to all processors */
    3492:   PetscMalloc1(m,&locrowlens);
    3493:   if (!rank) {
    3494:     mend = m;
    3495:     if (size == 1) mend = mend - extra_rows;
    3496:     PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);
    3497:     for (j=mend; j<m; j++) locrowlens[j] = 1;
    3498:     PetscMalloc1(mmax,&rowlengths);
    3499:     PetscCalloc1(size,&procsnz);
    3500:     for (j=0; j<m; j++) {
    3501:       procsnz[0] += locrowlens[j];
    3502:     }
    3503:     for (i=1; i<size; i++) {
    3504:       mend = browners[i+1] - browners[i];
    3505:       if (i == size-1) mend = mend - extra_rows;
    3506:       PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);
    3507:       for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1;
    3508:       /* calculate the number of nonzeros on each processor */
    3509:       for (j=0; j<browners[i+1]-browners[i]; j++) {
    3510:         procsnz[i] += rowlengths[j];
    3511:       }
    3512:       MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);
    3513:     }
    3514:     PetscFree(rowlengths);
    3515:   } else {
    3516:     MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);
    3517:   }

    3519:   if (!rank) {
    3520:     /* determine max buffer needed and allocate it */
    3521:     maxnz = procsnz[0];
    3522:     for (i=1; i<size; i++) {
    3523:       maxnz = PetscMax(maxnz,procsnz[i]);
    3524:     }
    3525:     PetscMalloc1(maxnz,&cols);

    3527:     /* read in my part of the matrix column indices  */
    3528:     nz     = procsnz[0];
    3529:     PetscMalloc1(nz+1,&ibuf);
    3530:     mycols = ibuf;
    3531:     if (size == 1) nz -= extra_rows;
    3532:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);
    3533:     if (size == 1) {
    3534:       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
    3535:     }

    3537:     /* read in every ones (except the last) and ship off */
    3538:     for (i=1; i<size-1; i++) {
    3539:       nz   = procsnz[i];
    3540:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
    3541:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
    3542:     }
    3543:     /* read in the stuff for the last proc */
    3544:     if (size != 1) {
    3545:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
    3546:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
    3547:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
    3548:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
    3549:     }
    3550:     PetscFree(cols);
    3551:   } else {
    3552:     /* determine buffer space needed for message */
    3553:     nz = 0;
    3554:     for (i=0; i<m; i++) {
    3555:       nz += locrowlens[i];
    3556:     }
    3557:     PetscMalloc1(nz+1,&ibuf);
    3558:     mycols = ibuf;
    3559:     /* receive message of column indices*/
    3560:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
    3561:     MPI_Get_count(&status,MPIU_INT,&maxnz);
    3562:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
    3563:   }

    3565:   /* loop over local rows, determining number of off diagonal entries */
    3566:   PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);
    3567:   PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);
    3568:   rowcount = 0; nzcount = 0;
    3569:   for (i=0; i<mbs; i++) {
    3570:     dcount  = 0;
    3571:     odcount = 0;
    3572:     for (j=0; j<bs; j++) {
    3573:       kmax = locrowlens[rowcount];
    3574:       for (k=0; k<kmax; k++) {
    3575:         tmp = mycols[nzcount++]/bs;
    3576:         if (!mask[tmp]) {
    3577:           mask[tmp] = 1;
    3578:           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp;
    3579:           else masked1[dcount++] = tmp;
    3580:         }
    3581:       }
    3582:       rowcount++;
    3583:     }

    3585:     dlens[i]  = dcount;
    3586:     odlens[i] = odcount;

    3588:     /* zero out the mask elements we set */
    3589:     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
    3590:     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
    3591:   }

    3593:   MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
    3594:   MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);

    3596:   if (!rank) {
    3597:     PetscMalloc1(maxnz+1,&buf);
    3598:     /* read in my part of the matrix numerical values  */
    3599:     nz     = procsnz[0];
    3600:     vals   = buf;
    3601:     mycols = ibuf;
    3602:     if (size == 1) nz -= extra_rows;
    3603:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    3604:     if (size == 1) {
    3605:       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
    3606:     }

    3608:     /* insert into matrix */
    3609:     jj = rstart*bs;
    3610:     for (i=0; i<m; i++) {
    3611:       MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
    3612:       mycols += locrowlens[i];
    3613:       vals   += locrowlens[i];
    3614:       jj++;
    3615:     }
    3616:     /* read in other processors (except the last one) and ship out */
    3617:     for (i=1; i<size-1; i++) {
    3618:       nz   = procsnz[i];
    3619:       vals = buf;
    3620:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    3621:       MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
    3622:     }
    3623:     /* the last proc */
    3624:     if (size != 1) {
    3625:       nz   = procsnz[i] - extra_rows;
    3626:       vals = buf;
    3627:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    3628:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
    3629:       MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
    3630:     }
    3631:     PetscFree(procsnz);
    3632:   } else {
    3633:     /* receive numeric values */
    3634:     PetscMalloc1(nz+1,&buf);

    3636:     /* receive message of values*/
    3637:     vals   = buf;
    3638:     mycols = ibuf;
    3639:     MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);

    3641:     /* insert into matrix */
    3642:     jj = rstart*bs;
    3643:     for (i=0; i<m; i++) {
    3644:       MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
    3645:       mycols += locrowlens[i];
    3646:       vals   += locrowlens[i];
    3647:       jj++;
    3648:     }
    3649:   }
    3650:   PetscFree(locrowlens);
    3651:   PetscFree(buf);
    3652:   PetscFree(ibuf);
    3653:   PetscFree2(rowners,browners);
    3654:   PetscFree2(dlens,odlens);
    3655:   PetscFree3(mask,masked1,masked2);
    3656:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
    3657:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
    3658:   return(0);
    3659: }

    3661: /*@
    3662:    MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

    3664:    Input Parameters:
    3665: .  mat  - the matrix
    3666: .  fact - factor

    3668:    Not Collective, each process can use a different factor

    3670:    Level: advanced

    3672:   Notes:
    3673:    This can also be set by the command line option: -mat_use_hash_table <fact>

    3675: .keywords: matrix, hashtable, factor, HT

    3677: .seealso: MatSetOption()
    3678: @*/
    3679: PetscErrorCode  MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact)
    3680: {

    3684:   PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));
    3685:   return(0);
    3686: }

    3688: PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact)
    3689: {
    3690:   Mat_MPIBAIJ *baij;

    3693:   baij          = (Mat_MPIBAIJ*)mat->data;
    3694:   baij->ht_fact = fact;
    3695:   return(0);
    3696: }

    3698: PetscErrorCode  MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
    3699: {
    3700:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
    3701:   PetscBool      flg;

    3705:   PetscObjectTypeCompare((PetscObject)A,MATMPIBAIJ,&flg);
    3706:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIBAIJ matrix as input");
    3707:   if (Ad)     *Ad     = a->A;
    3708:   if (Ao)     *Ao     = a->B;
    3709:   if (colmap) *colmap = a->garray;
    3710:   return(0);
    3711: }

    3713: /*
    3714:     Special version for direct calls from Fortran (to eliminate two function call overheads
    3715: */
    3716: #if defined(PETSC_HAVE_FORTRAN_CAPS)
    3717: #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED
    3718: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
    3719: #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked
    3720: #endif

    3722: /*@C
    3723:   MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked()

    3725:   Collective on Mat

    3727:   Input Parameters:
    3728: + mat - the matrix
    3729: . min - number of input rows
    3730: . im - input rows
    3731: . nin - number of input columns
    3732: . in - input columns
    3733: . v - numerical values input
    3734: - addvin - INSERT_VALUES or ADD_VALUES

    3736:   Notes:
    3737:     This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse.

    3739:   Level: advanced

    3741: .seealso:   MatSetValuesBlocked()
    3742: @*/
    3743: PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin)
    3744: {
    3745:   /* convert input arguments to C version */
    3746:   Mat        mat  = *matin;
    3747:   PetscInt   m    = *min, n = *nin;
    3748:   InsertMode addv = *addvin;

    3750:   Mat_MPIBAIJ     *baij = (Mat_MPIBAIJ*)mat->data;
    3751:   const MatScalar *value;
    3752:   MatScalar       *barray     = baij->barray;
    3753:   PetscBool       roworiented = baij->roworiented;
    3754:   PetscErrorCode  ierr;
    3755:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
    3756:   PetscInt        rend=baij->rendbs,cstart=baij->cstartbs,stepval;
    3757:   PetscInt        cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;

    3760:   /* tasks normally handled by MatSetValuesBlocked() */
    3761:   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
    3762: #if defined(PETSC_USE_DEBUG)
    3763:   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
    3764:   if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
    3765: #endif
    3766:   if (mat->assembled) {
    3767:     mat->was_assembled = PETSC_TRUE;
    3768:     mat->assembled     = PETSC_FALSE;
    3769:   }
    3770:   PetscLogEventBegin(MAT_SetValues,mat,0,0,0);

    3773:   if (!barray) {
    3774:     PetscMalloc1(bs2,&barray);
    3775:     baij->barray = barray;
    3776:   }

    3778:   if (roworiented) stepval = (n-1)*bs;
    3779:   else stepval = (m-1)*bs;

    3781:   for (i=0; i<m; i++) {
    3782:     if (im[i] < 0) continue;
    3783: #if defined(PETSC_USE_DEBUG)
    3784:     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1);
    3785: #endif
    3786:     if (im[i] >= rstart && im[i] < rend) {
    3787:       row = im[i] - rstart;
    3788:       for (j=0; j<n; j++) {
    3789:         /* If NumCol = 1 then a copy is not required */
    3790:         if ((roworiented) && (n == 1)) {
    3791:           barray = (MatScalar*)v + i*bs2;
    3792:         } else if ((!roworiented) && (m == 1)) {
    3793:           barray = (MatScalar*)v + j*bs2;
    3794:         } else { /* Here a copy is required */
    3795:           if (roworiented) {
    3796:             value = v + i*(stepval+bs)*bs + j*bs;
    3797:           } else {
    3798:             value = v + j*(stepval+bs)*bs + i*bs;
    3799:           }
    3800:           for (ii=0; ii<bs; ii++,value+=stepval) {
    3801:             for (jj=0; jj<bs; jj++) {
    3802:               *barray++ = *value++;
    3803:             }
    3804:           }
    3805:           barray -=bs2;
    3806:         }

    3808:         if (in[j] >= cstart && in[j] < cend) {
    3809:           col  = in[j] - cstart;
    3810:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
    3811:         } else if (in[j] < 0) continue;
    3812: #if defined(PETSC_USE_DEBUG)
    3813:         else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);
    3814: #endif
    3815:         else {
    3816:           if (mat->was_assembled) {
    3817:             if (!baij->colmap) {
    3818:               MatCreateColmap_MPIBAIJ_Private(mat);
    3819:             }

    3821: #if defined(PETSC_USE_DEBUG)
    3822: #if defined(PETSC_USE_CTABLE)
    3823:             { PetscInt data;
    3824:               PetscTableFind(baij->colmap,in[j]+1,&data);
    3825:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    3826:             }
    3827: #else
    3828:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    3829: #endif
    3830: #endif
    3831: #if defined(PETSC_USE_CTABLE)
    3832:             PetscTableFind(baij->colmap,in[j]+1,&col);
    3833:             col  = (col - 1)/bs;
    3834: #else
    3835:             col = (baij->colmap[in[j]] - 1)/bs;
    3836: #endif
    3837:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
    3838:               MatDisAssemble_MPIBAIJ(mat);
    3839:               col  =  in[j];
    3840:             }
    3841:           } else col = in[j];
    3842:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
    3843:         }
    3844:       }
    3845:     } else {
    3846:       if (!baij->donotstash) {
    3847:         if (roworiented) {
    3848:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    3849:         } else {
    3850:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    3851:         }
    3852:       }
    3853:     }
    3854:   }

    3856:   /* task normally handled by MatSetValuesBlocked() */
    3857:   PetscLogEventEnd(MAT_SetValues,mat,0,0,0);
    3858:   return(0);
    3859: }

    3861: /*@
    3862:      MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard
    3863:          CSR format the local rows.

    3865:    Collective on MPI_Comm

    3867:    Input Parameters:
    3868: +  comm - MPI communicator
    3869: .  bs - the block size, only a block size of 1 is supported
    3870: .  m - number of local rows (Cannot be PETSC_DECIDE)
    3871: .  n - This value should be the same as the local size used in creating the
    3872:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
    3873:        calculated if N is given) For square matrices n is almost always m.
    3874: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    3875: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    3876: .   i - row indices
    3877: .   j - column indices
    3878: -   a - matrix values

    3880:    Output Parameter:
    3881: .   mat - the matrix

    3883:    Level: intermediate

    3885:    Notes:
    3886:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
    3887:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
    3888:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

    3890:      The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is
    3891:      the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first
    3892:      block, followed by the second column of the first block etc etc.  That is, the blocks are contiguous in memory
    3893:      with column-major ordering within blocks.

    3895:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

    3897: .keywords: matrix, aij, compressed row, sparse, parallel

    3899: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
    3900:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
    3901: @*/
    3902: PetscErrorCode  MatCreateMPIBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
    3903: {

    3907:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
    3908:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
    3909:   MatCreate(comm,mat);
    3910:   MatSetSizes(*mat,m,n,M,N);
    3911:   MatSetType(*mat,MATMPIBAIJ);
    3912:   MatSetBlockSize(*mat,bs);
    3913:   MatSetUp(*mat);
    3914:   MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);
    3915:   MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);
    3916:   MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);
    3917:   return(0);
    3918: }

    3920: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
    3921: {
    3923:   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
    3924:   PetscInt       *indx;
    3925:   PetscScalar    *values;

    3928:   MatGetSize(inmat,&m,&N);
    3929:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
    3930:     Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)inmat->data;
    3931:     PetscInt       *dnz,*onz,mbs,Nbs,nbs;
    3932:     PetscInt       *bindx,rmax=a->rmax,j;
    3933:     PetscMPIInt    rank,size;

    3935:     MatGetBlockSizes(inmat,&bs,&cbs);
    3936:     mbs = m/bs; Nbs = N/cbs;
    3937:     if (n == PETSC_DECIDE) {
    3938:       nbs  = n;
    3939:       PetscSplitOwnership(comm,&nbs,&Nbs);
    3940:       n    = nbs*cbs;
    3941:     } else {
    3942:       nbs = n/cbs;
    3943:     }

    3945:     PetscMalloc1(rmax,&bindx);
    3946:     MatPreallocateInitialize(comm,mbs,nbs,dnz,onz); /* inline function, output __end and __rstart are used below */

    3948:     MPI_Comm_rank(comm,&rank);
    3949:     MPI_Comm_rank(comm,&size);
    3950:     if (rank == size-1) {
    3951:       /* Check sum(nbs) = Nbs */
    3952:       if (__end != Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local block columns %D != global block columns %D",__end,Nbs);
    3953:     }

    3955:     rstart = __rstart; /* block rstart of *outmat; see inline function MatPreallocateInitialize */
    3956:     for (i=0; i<mbs; i++) {
    3957:       MatGetRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
    3958:       nnz = nnz/bs;
    3959:       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
    3960:       MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
    3961:       MatRestoreRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);
    3962:     }
    3963:     PetscFree(bindx);

    3965:     MatCreate(comm,outmat);
    3966:     MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
    3967:     MatSetBlockSizes(*outmat,bs,cbs);
    3968:     MatSetType(*outmat,MATBAIJ);
    3969:     MatSeqBAIJSetPreallocation(*outmat,bs,0,dnz);
    3970:     MatMPIBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
    3971:     MatPreallocateFinalize(dnz,onz);
    3972:   }

    3974:   /* numeric phase */
    3975:   MatGetBlockSizes(inmat,&bs,&cbs);
    3976:   MatGetOwnershipRange(*outmat,&rstart,NULL);

    3978:   for (i=0; i<m; i++) {
    3979:     MatGetRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);
    3980:     Ii   = i + rstart;
    3981:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
    3982:     MatRestoreRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);
    3983:   }
    3984:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
    3985:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
    3986:   return(0);
    3987: }