Date: 2016-07-24T16:55:27+00:00

Actual source code: mpibaij.c
petsc-3.7.3 2016-07-24
Report Typos and Errors

      2: #include <../src/mat/impls/baij/mpi/mpibaij.h>   /*I  "petscmat.h"  I*/

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

      9: PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[])
     10: {
     11:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
     13:   PetscInt       i,*idxb = 0;
     14:   PetscScalar    *va,*vb;
     15:   Vec            vtmp;

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

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

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

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

     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: }

     60: PetscErrorCode  MatRetrieveValues_MPIBAIJ(Mat mat)
     61: {
     62:   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)mat->data;

     66:   MatRetrieveValues(aij->A);
     67:   MatRetrieveValues(aij->B);
     68:   return(0);
     69: }

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

     87: #if defined(PETSC_USE_CTABLE)
     88:   PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);
     89:   for (i=0; i<nbs; i++) {
     90:     PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);
     91:   }
     92: #else
     93:   PetscMalloc1(baij->Nbs+1,&baij->colmap);
     94:   PetscLogObjectMemory((PetscObject)mat,baij->Nbs*sizeof(PetscInt));
     95:   PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));
     96:   for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1;
     97: #endif
     98:   return(0);
     99: }

    101: #define  MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,orow,ocol)       \
    102:   { \
    103:  \
    104:     brow = row/bs;  \
    105:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
    106:     rmax = aimax[brow]; nrow = ailen[brow]; \
    107:     bcol = col/bs; \
    108:     ridx = row % bs; cidx = col % bs; \
    109:     low  = 0; high = nrow; \
    110:     while (high-low > 3) { \
    111:       t = (low+high)/2; \
    112:       if (rp[t] > bcol) high = t; \
    113:       else              low  = t; \
    114:     } \
    115:     for (_i=low; _i<high; _i++) { \
    116:       if (rp[_i] > bcol) break; \
    117:       if (rp[_i] == bcol) { \
    118:         bap = ap +  bs2*_i + bs*cidx + ridx; \
    119:         if (addv == ADD_VALUES) *bap += value;  \
    120:         else                    *bap  = value;  \
    121:         goto a_noinsert; \
    122:       } \
    123:     } \
    124:     if (a->nonew == 1) goto a_noinsert; \
    125:     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); \
    126:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
    127:     N = nrow++ - 1;  \
    128:     /* shift up all the later entries in this row */ \
    129:     for (ii=N; ii>=_i; ii--) { \
    130:       rp[ii+1] = rp[ii]; \
    131:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
    132:     } \
    133:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); }  \
    134:     rp[_i]                      = bcol;  \
    135:     ap[bs2*_i + bs*cidx + ridx] = value;  \
    136: a_noinsert:; \
    137:     ailen[brow] = nrow; \
    138:   }

    140: #define  MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,orow,ocol)       \
    141:   { \
    142:     brow = row/bs;  \
    143:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
    144:     rmax = bimax[brow]; nrow = bilen[brow]; \
    145:     bcol = col/bs; \
    146:     ridx = row % bs; cidx = col % bs; \
    147:     low  = 0; high = nrow; \
    148:     while (high-low > 3) { \
    149:       t = (low+high)/2; \
    150:       if (rp[t] > bcol) high = t; \
    151:       else              low  = t; \
    152:     } \
    153:     for (_i=low; _i<high; _i++) { \
    154:       if (rp[_i] > bcol) break; \
    155:       if (rp[_i] == bcol) { \
    156:         bap = ap +  bs2*_i + bs*cidx + ridx; \
    157:         if (addv == ADD_VALUES) *bap += value;  \
    158:         else                    *bap  = value;  \
    159:         goto b_noinsert; \
    160:       } \
    161:     } \
    162:     if (b->nonew == 1) goto b_noinsert; \
    163:     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); \
    164:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
    165:     N = nrow++ - 1;  \
    166:     /* shift up all the later entries in this row */ \
    167:     for (ii=N; ii>=_i; ii--) { \
    168:       rp[ii+1] = rp[ii]; \
    169:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
    170:     } \
    171:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));}  \
    172:     rp[_i]                      = bcol;  \
    173:     ap[bs2*_i + bs*cidx + ridx] = value;  \
    174: b_noinsert:; \
    175:     bilen[brow] = nrow; \
    176:   }

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

    191:   /* Some Variables required in the macro */
    192:   Mat         A     = baij->A;
    193:   Mat_SeqBAIJ *a    = (Mat_SeqBAIJ*)(A)->data;
    194:   PetscInt    *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
    195:   MatScalar   *aa   =a->a;

    197:   Mat         B     = baij->B;
    198:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
    199:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
    200:   MatScalar   *ba   =b->a;

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

    207:   for (i=0; i<m; i++) {
    208:     if (im[i] < 0) continue;
    209: #if defined(PETSC_USE_DEBUG)
    210:     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);
    211: #endif
    212:     if (im[i] >= rstart_orig && im[i] < rend_orig) {
    213:       row = im[i] - rstart_orig;
    214:       for (j=0; j<n; j++) {
    215:         if (in[j] >= cstart_orig && in[j] < cend_orig) {
    216:           col = in[j] - cstart_orig;
    217:           if (roworiented) value = v[i*n+j];
    218:           else             value = v[i+j*m];
    219:           MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
    220:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
    221:         } else if (in[j] < 0) continue;
    222: #if defined(PETSC_USE_DEBUG)
    223:         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);
    224: #endif
    225:         else {
    226:           if (mat->was_assembled) {
    227:             if (!baij->colmap) {
    228:               MatCreateColmap_MPIBAIJ_Private(mat);
    229:             }
    230: #if defined(PETSC_USE_CTABLE)
    231:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
    232:             col  = col - 1;
    233: #else
    234:             col = baij->colmap[in[j]/bs] - 1;
    235: #endif
    236:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
    237:               MatDisAssemble_MPIBAIJ(mat);
    238:               col  =  in[j];
    239:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
    240:               B    = baij->B;
    241:               b    = (Mat_SeqBAIJ*)(B)->data;
    242:               bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
    243:               ba   =b->a;
    244:             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]);
    245:             else col += in[j]%bs;
    246:           } else col = in[j];
    247:           if (roworiented) value = v[i*n+j];
    248:           else             value = v[i+j*m];
    249:           MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
    250:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
    251:         }
    252:       }
    253:     } else {
    254:       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]);
    255:       if (!baij->donotstash) {
    256:         mat->assembled = PETSC_FALSE;
    257:         if (roworiented) {
    258:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);
    259:         } else {
    260:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);
    261:         }
    262:       }
    263:     }
    264:   }
    265:   return(0);
    266: }

    270: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
    271: {
    272:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
    273:   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
    274:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
    275:   PetscErrorCode    ierr;
    276:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
    277:   PetscBool         roworiented=a->roworiented;
    278:   const PetscScalar *value     = v;
    279:   MatScalar         *ap,*aa = a->a,*bap;

    282:   rp   = aj + ai[row];
    283:   ap   = aa + bs2*ai[row];
    284:   rmax = imax[row];
    285:   nrow = ailen[row];
    286:   value = v;
    287:   low = 0;
    288:   high = nrow;
    289:   while (high-low > 7) {
    290:     t = (low+high)/2;
    291:     if (rp[t] > col) high = t;
    292:     else             low  = t;
    293:   }
    294:   for (i=low; i<high; i++) {
    295:     if (rp[i] > col) break;
    296:     if (rp[i] == col) {
    297:       bap = ap +  bs2*i;
    298:       if (roworiented) {
    299:         if (is == ADD_VALUES) {
    300:           for (ii=0; ii<bs; ii++) {
    301:             for (jj=ii; jj<bs2; jj+=bs) {
    302:               bap[jj] += *value++;
    303:             }
    304:           }
    305:         } else {
    306:           for (ii=0; ii<bs; ii++) {
    307:             for (jj=ii; jj<bs2; jj+=bs) {
    308:               bap[jj] = *value++;
    309:             }
    310:           }
    311:         }
    312:       } else {
    313:         if (is == ADD_VALUES) {
    314:           for (ii=0; ii<bs; ii++,value+=bs) {
    315:             for (jj=0; jj<bs; jj++) {
    316:               bap[jj] += value[jj];
    317:             }
    318:             bap += bs;
    319:           }
    320:         } else {
    321:           for (ii=0; ii<bs; ii++,value+=bs) {
    322:             for (jj=0; jj<bs; jj++) {
    323:               bap[jj]  = value[jj];
    324:             }
    325:             bap += bs;
    326:           }
    327:         }
    328:       }
    329:       goto noinsert2;
    330:     }
    331:   }
    332:   if (nonew == 1) goto noinsert2;
    333:   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);
    334:   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
    335:   N = nrow++ - 1; high++;
    336:   /* shift up all the later entries in this row */
    337:   for (ii=N; ii>=i; ii--) {
    338:     rp[ii+1] = rp[ii];
    339:     PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
    340:   }
    341:   if (N >= i) {
    342:     PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
    343:   }
    344:   rp[i] = col;
    345:   bap   = ap +  bs2*i;
    346:   if (roworiented) {
    347:     for (ii=0; ii<bs; ii++) {
    348:       for (jj=ii; jj<bs2; jj+=bs) {
    349:         bap[jj] = *value++;
    350:       }
    351:     }
    352:   } else {
    353:     for (ii=0; ii<bs; ii++) {
    354:       for (jj=0; jj<bs; jj++) {
    355:         *bap++ = *value++;
    356:       }
    357:     }
    358:   }
    359:   noinsert2:;
    360:   ailen[row] = nrow;
    361:   return(0);
    362: }

    366: /*
    367:     This routine should be optimized so that the block copy at ** Here a copy is required ** below is not needed
    368:     by passing additional stride information into the MatSetValuesBlocked_SeqBAIJ_Inlined() routine
    369: */
    370: PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
    371: {
    372:   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
    373:   const PetscScalar *value;
    374:   MatScalar         *barray     = baij->barray;
    375:   PetscBool         roworiented = baij->roworiented;
    376:   PetscErrorCode    ierr;
    377:   PetscInt          i,j,ii,jj,row,col,rstart=baij->rstartbs;
    378:   PetscInt          rend=baij->rendbs,cstart=baij->cstartbs,stepval;
    379:   PetscInt          cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;

    382:   if (!barray) {
    383:     PetscMalloc1(bs2,&barray);
    384:     baij->barray = barray;
    385:   }

    387:   if (roworiented) stepval = (n-1)*bs;
    388:   else stepval = (m-1)*bs;

    390:   for (i=0; i<m; i++) {
    391:     if (im[i] < 0) continue;
    392: #if defined(PETSC_USE_DEBUG)
    393:     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);
    394: #endif
    395:     if (im[i] >= rstart && im[i] < rend) {
    396:       row = im[i] - rstart;
    397:       for (j=0; j<n; j++) {
    398:         /* If NumCol = 1 then a copy is not required */
    399:         if ((roworiented) && (n == 1)) {
    400:           barray = (MatScalar*)v + i*bs2;
    401:         } else if ((!roworiented) && (m == 1)) {
    402:           barray = (MatScalar*)v + j*bs2;
    403:         } else { /* Here a copy is required */
    404:           if (roworiented) {
    405:             value = v + (i*(stepval+bs) + j)*bs;
    406:           } else {
    407:             value = v + (j*(stepval+bs) + i)*bs;
    408:           }
    409:           for (ii=0; ii<bs; ii++,value+=bs+stepval) {
    410:             for (jj=0; jj<bs; jj++) barray[jj] = value[jj];
    411:             barray += bs;
    412:           }
    413:           barray -= bs2;
    414:         }

    416:         if (in[j] >= cstart && in[j] < cend) {
    417:           col  = in[j] - cstart;
    418:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
    419:         } else if (in[j] < 0) continue;
    420: #if defined(PETSC_USE_DEBUG)
    421:         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);
    422: #endif
    423:         else {
    424:           if (mat->was_assembled) {
    425:             if (!baij->colmap) {
    426:               MatCreateColmap_MPIBAIJ_Private(mat);
    427:             }

    429: #if defined(PETSC_USE_DEBUG)
    430: #if defined(PETSC_USE_CTABLE)
    431:             { PetscInt data;
    432:               PetscTableFind(baij->colmap,in[j]+1,&data);
    433:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    434:             }
    435: #else
    436:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    437: #endif
    438: #endif
    439: #if defined(PETSC_USE_CTABLE)
    440:             PetscTableFind(baij->colmap,in[j]+1,&col);
    441:             col  = (col - 1)/bs;
    442: #else
    443:             col = (baij->colmap[in[j]] - 1)/bs;
    444: #endif
    445:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
    446:               MatDisAssemble_MPIBAIJ(mat);
    447:               col  =  in[j];
    448:             } 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]);
    449:           } else col = in[j];
    450:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
    451:         }
    452:       }
    453:     } else {
    454:       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]);
    455:       if (!baij->donotstash) {
    456:         if (roworiented) {
    457:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    458:         } else {
    459:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    460:         }
    461:       }
    462:     }
    463:   }
    464:   return(0);
    465: }

    467: #define HASH_KEY 0.6180339887
    468: #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp)))
    469: /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
    470: /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
    473: PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
    474: {
    475:   Mat_MPIBAIJ    *baij       = (Mat_MPIBAIJ*)mat->data;
    476:   PetscBool      roworiented = baij->roworiented;
    478:   PetscInt       i,j,row,col;
    479:   PetscInt       rstart_orig=mat->rmap->rstart;
    480:   PetscInt       rend_orig  =mat->rmap->rend,Nbs=baij->Nbs;
    481:   PetscInt       h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx;
    482:   PetscReal      tmp;
    483:   MatScalar      **HD = baij->hd,value;
    484: #if defined(PETSC_USE_DEBUG)
    485:   PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
    486: #endif

    489:   for (i=0; i<m; i++) {
    490: #if defined(PETSC_USE_DEBUG)
    491:     if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row");
    492:     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);
    493: #endif
    494:     row = im[i];
    495:     if (row >= rstart_orig && row < rend_orig) {
    496:       for (j=0; j<n; j++) {
    497:         col = in[j];
    498:         if (roworiented) value = v[i*n+j];
    499:         else             value = v[i+j*m];
    500:         /* Look up PetscInto the Hash Table */
    501:         key = (row/bs)*Nbs+(col/bs)+1;
    502:         h1  = HASH(size,key,tmp);

    505:         idx = h1;
    506: #if defined(PETSC_USE_DEBUG)
    507:         insert_ct++;
    508:         total_ct++;
    509:         if (HT[idx] != key) {
    510:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
    511:           if (idx == size) {
    512:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
    513:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
    514:           }
    515:         }
    516: #else
    517:         if (HT[idx] != key) {
    518:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
    519:           if (idx == size) {
    520:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
    521:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
    522:           }
    523:         }
    524: #endif
    525:         /* A HASH table entry is found, so insert the values at the correct address */
    526:         if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value;
    527:         else                    *(HD[idx]+ (col % bs)*bs + (row % bs))  = value;
    528:       }
    529:     } else if (!baij->donotstash) {
    530:       if (roworiented) {
    531:         MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);
    532:       } else {
    533:         MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);
    534:       }
    535:     }
    536:   }
    537: #if defined(PETSC_USE_DEBUG)
    538:   baij->ht_total_ct  = total_ct;
    539:   baij->ht_insert_ct = insert_ct;
    540: #endif
    541:   return(0);
    542: }

    546: PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
    547: {
    548:   Mat_MPIBAIJ       *baij       = (Mat_MPIBAIJ*)mat->data;
    549:   PetscBool         roworiented = baij->roworiented;
    550:   PetscErrorCode    ierr;
    551:   PetscInt          i,j,ii,jj,row,col;
    552:   PetscInt          rstart=baij->rstartbs;
    553:   PetscInt          rend  =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2;
    554:   PetscInt          h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs;
    555:   PetscReal         tmp;
    556:   MatScalar         **HD = baij->hd,*baij_a;
    557:   const PetscScalar *v_t,*value;
    558: #if defined(PETSC_USE_DEBUG)
    559:   PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
    560: #endif

    563:   if (roworiented) stepval = (n-1)*bs;
    564:   else stepval = (m-1)*bs;

    566:   for (i=0; i<m; i++) {
    567: #if defined(PETSC_USE_DEBUG)
    568:     if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]);
    569:     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);
    570: #endif
    571:     row = im[i];
    572:     v_t = v + i*nbs2;
    573:     if (row >= rstart && row < rend) {
    574:       for (j=0; j<n; j++) {
    575:         col = in[j];

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

    581:         idx = h1;
    582: #if defined(PETSC_USE_DEBUG)
    583:         total_ct++;
    584:         insert_ct++;
    585:         if (HT[idx] != key) {
    586:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
    587:           if (idx == size) {
    588:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
    589:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
    590:           }
    591:         }
    592: #else
    593:         if (HT[idx] != key) {
    594:           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
    595:           if (idx == size) {
    596:             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
    597:             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
    598:           }
    599:         }
    600: #endif
    601:         baij_a = HD[idx];
    602:         if (roworiented) {
    603:           /*value = v + i*(stepval+bs)*bs + j*bs;*/
    604:           /* value = v + (i*(stepval+bs)+j)*bs; */
    605:           value = v_t;
    606:           v_t  += bs;
    607:           if (addv == ADD_VALUES) {
    608:             for (ii=0; ii<bs; ii++,value+=stepval) {
    609:               for (jj=ii; jj<bs2; jj+=bs) {
    610:                 baij_a[jj] += *value++;
    611:               }
    612:             }
    613:           } else {
    614:             for (ii=0; ii<bs; ii++,value+=stepval) {
    615:               for (jj=ii; jj<bs2; jj+=bs) {
    616:                 baij_a[jj] = *value++;
    617:               }
    618:             }
    619:           }
    620:         } else {
    621:           value = v + j*(stepval+bs)*bs + i*bs;
    622:           if (addv == ADD_VALUES) {
    623:             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
    624:               for (jj=0; jj<bs; jj++) {
    625:                 baij_a[jj] += *value++;
    626:               }
    627:             }
    628:           } else {
    629:             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
    630:               for (jj=0; jj<bs; jj++) {
    631:                 baij_a[jj] = *value++;
    632:               }
    633:             }
    634:           }
    635:         }
    636:       }
    637:     } else {
    638:       if (!baij->donotstash) {
    639:         if (roworiented) {
    640:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    641:         } else {
    642:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    643:         }
    644:       }
    645:     }
    646:   }
    647: #if defined(PETSC_USE_DEBUG)
    648:   baij->ht_total_ct  = total_ct;
    649:   baij->ht_insert_ct = insert_ct;
    650: #endif
    651:   return(0);
    652: }

    656: PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
    657: {
    658:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
    660:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
    661:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

    664:   for (i=0; i<m; i++) {
    665:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
    666:     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);
    667:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
    668:       row = idxm[i] - bsrstart;
    669:       for (j=0; j<n; j++) {
    670:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
    671:         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);
    672:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
    673:           col  = idxn[j] - bscstart;
    674:           MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
    675:         } else {
    676:           if (!baij->colmap) {
    677:             MatCreateColmap_MPIBAIJ_Private(mat);
    678:           }
    679: #if defined(PETSC_USE_CTABLE)
    680:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
    681:           data--;
    682: #else
    683:           data = baij->colmap[idxn[j]/bs]-1;
    684: #endif
    685:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
    686:           else {
    687:             col  = data + idxn[j]%bs;
    688:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
    689:           }
    690:         }
    691:       }
    692:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
    693:   }
    694:   return(0);
    695: }

    699: PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm)
    700: {
    701:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
    702:   Mat_SeqBAIJ    *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data;
    704:   PetscInt       i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col;
    705:   PetscReal      sum = 0.0;
    706:   MatScalar      *v;

    709:   if (baij->size == 1) {
    710:      MatNorm(baij->A,type,nrm);
    711:   } else {
    712:     if (type == NORM_FROBENIUS) {
    713:       v  = amat->a;
    714:       nz = amat->nz*bs2;
    715:       for (i=0; i<nz; i++) {
    716:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
    717:       }
    718:       v  = bmat->a;
    719:       nz = bmat->nz*bs2;
    720:       for (i=0; i<nz; i++) {
    721:         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
    722:       }
    723:       MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
    724:       *nrm = PetscSqrtReal(*nrm);
    725:     } else if (type == NORM_1) { /* max column sum */
    726:       PetscReal *tmp,*tmp2;
    727:       PetscInt  *jj,*garray=baij->garray,cstart=baij->rstartbs;
    728:       PetscMalloc2(mat->cmap->N,&tmp,mat->cmap->N,&tmp2);
    729:       PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));
    730:       v    = amat->a; jj = amat->j;
    731:       for (i=0; i<amat->nz; i++) {
    732:         for (j=0; j<bs; j++) {
    733:           col = bs*(cstart + *jj) + j; /* column index */
    734:           for (row=0; row<bs; row++) {
    735:             tmp[col] += PetscAbsScalar(*v);  v++;
    736:           }
    737:         }
    738:         jj++;
    739:       }
    740:       v = bmat->a; jj = bmat->j;
    741:       for (i=0; i<bmat->nz; i++) {
    742:         for (j=0; j<bs; j++) {
    743:           col = bs*garray[*jj] + j;
    744:           for (row=0; row<bs; row++) {
    745:             tmp[col] += PetscAbsScalar(*v); v++;
    746:           }
    747:         }
    748:         jj++;
    749:       }
    750:       MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
    751:       *nrm = 0.0;
    752:       for (j=0; j<mat->cmap->N; j++) {
    753:         if (tmp2[j] > *nrm) *nrm = tmp2[j];
    754:       }
    755:       PetscFree2(tmp,tmp2);
    756:     } else if (type == NORM_INFINITY) { /* max row sum */
    757:       PetscReal *sums;
    758:       PetscMalloc1(bs,&sums);
    759:       sum  = 0.0;
    760:       for (j=0; j<amat->mbs; j++) {
    761:         for (row=0; row<bs; row++) sums[row] = 0.0;
    762:         v  = amat->a + bs2*amat->i[j];
    763:         nz = amat->i[j+1]-amat->i[j];
    764:         for (i=0; i<nz; i++) {
    765:           for (col=0; col<bs; col++) {
    766:             for (row=0; row<bs; row++) {
    767:               sums[row] += PetscAbsScalar(*v); v++;
    768:             }
    769:           }
    770:         }
    771:         v  = bmat->a + bs2*bmat->i[j];
    772:         nz = bmat->i[j+1]-bmat->i[j];
    773:         for (i=0; i<nz; i++) {
    774:           for (col=0; col<bs; col++) {
    775:             for (row=0; row<bs; row++) {
    776:               sums[row] += PetscAbsScalar(*v); v++;
    777:             }
    778:           }
    779:         }
    780:         for (row=0; row<bs; row++) {
    781:           if (sums[row] > sum) sum = sums[row];
    782:         }
    783:       }
    784:       MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
    785:       PetscFree(sums);
    786:     } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet");
    787:   }
    788:   return(0);
    789: }

    791: /*
    792:   Creates the hash table, and sets the table
    793:   This table is created only once.
    794:   If new entried need to be added to the matrix
    795:   then the hash table has to be destroyed and
    796:   recreated.
    797: */
    800: PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor)
    801: {
    802:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
    803:   Mat            A     = baij->A,B=baij->B;
    804:   Mat_SeqBAIJ    *a    = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data;
    805:   PetscInt       i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
    807:   PetscInt       ht_size,bs2=baij->bs2,rstart=baij->rstartbs;
    808:   PetscInt       cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs;
    809:   PetscInt       *HT,key;
    810:   MatScalar      **HD;
    811:   PetscReal      tmp;
    812: #if defined(PETSC_USE_INFO)
    813:   PetscInt ct=0,max=0;
    814: #endif

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

    819:   baij->ht_size = (PetscInt)(factor*nz);
    820:   ht_size       = baij->ht_size;

    822:   /* Allocate Memory for Hash Table */
    823:   PetscCalloc2(ht_size,&baij->hd,ht_size,&baij->ht);
    824:   HD   = baij->hd;
    825:   HT   = baij->ht;

    827:   /* Loop Over A */
    828:   for (i=0; i<a->mbs; i++) {
    829:     for (j=ai[i]; j<ai[i+1]; j++) {
    830:       row = i+rstart;
    831:       col = aj[j]+cstart;

    833:       key = row*Nbs + col + 1;
    834:       h1  = HASH(ht_size,key,tmp);
    835:       for (k=0; k<ht_size; k++) {
    836:         if (!HT[(h1+k)%ht_size]) {
    837:           HT[(h1+k)%ht_size] = key;
    838:           HD[(h1+k)%ht_size] = a->a + j*bs2;
    839:           break;
    840: #if defined(PETSC_USE_INFO)
    841:         } else {
    842:           ct++;
    843: #endif
    844:         }
    845:       }
    846: #if defined(PETSC_USE_INFO)
    847:       if (k> max) max = k;
    848: #endif
    849:     }
    850:   }
    851:   /* Loop Over B */
    852:   for (i=0; i<b->mbs; i++) {
    853:     for (j=bi[i]; j<bi[i+1]; j++) {
    854:       row = i+rstart;
    855:       col = garray[bj[j]];
    856:       key = row*Nbs + col + 1;
    857:       h1  = HASH(ht_size,key,tmp);
    858:       for (k=0; k<ht_size; k++) {
    859:         if (!HT[(h1+k)%ht_size]) {
    860:           HT[(h1+k)%ht_size] = key;
    861:           HD[(h1+k)%ht_size] = b->a + j*bs2;
    862:           break;
    863: #if defined(PETSC_USE_INFO)
    864:         } else {
    865:           ct++;
    866: #endif
    867:         }
    868:       }
    869: #if defined(PETSC_USE_INFO)
    870:       if (k> max) max = k;
    871: #endif
    872:     }
    873:   }

    875:   /* Print Summary */
    876: #if defined(PETSC_USE_INFO)
    877:   for (i=0,j=0; i<ht_size; i++) {
    878:     if (HT[i]) j++;
    879:   }
    880:   PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);
    881: #endif
    882:   return(0);
    883: }

    887: PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode)
    888: {
    889:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
    891:   PetscInt       nstash,reallocs;

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

    896:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
    897:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
    898:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
    899:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
    900:   MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);
    901:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
    902:   return(0);
    903: }

    907: PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode)
    908: {
    909:   Mat_MPIBAIJ    *baij=(Mat_MPIBAIJ*)mat->data;
    910:   Mat_SeqBAIJ    *a   =(Mat_SeqBAIJ*)baij->A->data;
    912:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
    913:   PetscInt       *row,*col;
    914:   PetscBool      r1,r2,r3,other_disassembled;
    915:   MatScalar      *val;
    916:   PetscMPIInt    n;

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

    925:       for (i=0; i<n;) {
    926:         /* Now identify the consecutive vals belonging to the same row */
    927:         for (j=i,rstart=row[j]; j<n; j++) {
    928:           if (row[j] != rstart) break;
    929:         }
    930:         if (j < n) ncols = j-i;
    931:         else       ncols = n-i;
    932:         /* Now assemble all these values with a single function call */
    933:         MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
    934:         i    = j;
    935:       }
    936:     }
    937:     MatStashScatterEnd_Private(&mat->stash);
    938:     /* Now process the block-stash. Since the values are stashed column-oriented,
    939:        set the roworiented flag to column oriented, and after MatSetValues()
    940:        restore the original flags */
    941:     r1 = baij->roworiented;
    942:     r2 = a->roworiented;
    943:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

    945:     baij->roworiented = PETSC_FALSE;
    946:     a->roworiented    = PETSC_FALSE;

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

    953:       for (i=0; i<n;) {
    954:         /* Now identify the consecutive vals belonging to the same row */
    955:         for (j=i,rstart=row[j]; j<n; j++) {
    956:           if (row[j] != rstart) break;
    957:         }
    958:         if (j < n) ncols = j-i;
    959:         else       ncols = n-i;
    960:         MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
    961:         i    = j;
    962:       }
    963:     }
    964:     MatStashScatterEnd_Private(&mat->bstash);

    966:     baij->roworiented = r1;
    967:     a->roworiented    = r2;

    969:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */
    970:   }

    972:   MatAssemblyBegin(baij->A,mode);
    973:   MatAssemblyEnd(baij->A,mode);

    975:   /* determine if any processor has disassembled, if so we must
    976:      also disassemble ourselfs, in order that we may reassemble. */
    977:   /*
    978:      if nonzero structure of submatrix B cannot change then we know that
    979:      no processor disassembled thus we can skip this stuff
    980:   */
    981:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
    982:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
    983:     if (mat->was_assembled && !other_disassembled) {
    984:       MatDisAssemble_MPIBAIJ(mat);
    985:     }
    986:   }

    988:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
    989:     MatSetUpMultiply_MPIBAIJ(mat);
    990:   }
    991:   MatAssemblyBegin(baij->B,mode);
    992:   MatAssemblyEnd(baij->B,mode);

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

    998:     baij->ht_total_ct  = 0;
    999:     baij->ht_insert_ct = 0;
    1000:   }
    1001: #endif
    1002:   if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) {
    1003:     MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);

    1005:     mat->ops->setvalues        = MatSetValues_MPIBAIJ_HT;
    1006:     mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT;
    1007:   }

    1009:   PetscFree2(baij->rowvalues,baij->rowindices);

    1011:   baij->rowvalues = 0;

    1013:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
    1014:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
    1015:     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
    1016:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
    1017:   }
    1018:   return(0);
    1019: }

    1021: extern PetscErrorCode MatView_SeqBAIJ(Mat,PetscViewer);
    1022: #include <petscdraw.h>
    1025: static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
    1026: {
    1027:   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
    1028:   PetscErrorCode    ierr;
    1029:   PetscMPIInt       rank = baij->rank;
    1030:   PetscInt          bs   = mat->rmap->bs;
    1031:   PetscBool         iascii,isdraw;
    1032:   PetscViewer       sviewer;
    1033:   PetscViewerFormat format;

    1036:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    1037:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    1038:   if (iascii) {
    1039:     PetscViewerGetFormat(viewer,&format);
    1040:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
    1041:       MatInfo info;
    1042:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
    1043:       MatGetInfo(mat,MAT_LOCAL,&info);
    1044:       PetscViewerASCIIPushSynchronized(viewer);
    1045:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",
    1046:                                                 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);
    1047:       MatGetInfo(baij->A,MAT_LOCAL,&info);
    1048:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
    1049:       MatGetInfo(baij->B,MAT_LOCAL,&info);
    1050:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
    1051:       PetscViewerFlush(viewer);
    1052:       PetscViewerASCIIPopSynchronized(viewer);
    1053:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
    1054:       VecScatterView(baij->Mvctx,viewer);
    1055:       return(0);
    1056:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
    1057:       PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
    1058:       return(0);
    1059:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
    1060:       return(0);
    1061:     }
    1062:   }

    1064:   if (isdraw) {
    1065:     PetscDraw draw;
    1066:     PetscBool isnull;
    1067:     PetscViewerDrawGetDraw(viewer,0,&draw);
    1068:     PetscDrawIsNull(draw,&isnull);
    1069:     if (isnull) return(0);
    1070:   }

    1072:   {
    1073:     /* assemble the entire matrix onto first processor. */
    1074:     Mat         A;
    1075:     Mat_SeqBAIJ *Aloc;
    1076:     PetscInt    M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
    1077:     MatScalar   *a;
    1078:     const char  *matname;

    1080:     /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */
    1081:     /* Perhaps this should be the type of mat? */
    1082:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
    1083:     if (!rank) {
    1084:       MatSetSizes(A,M,N,M,N);
    1085:     } else {
    1086:       MatSetSizes(A,0,0,M,N);
    1087:     }
    1088:     MatSetType(A,MATMPIBAIJ);
    1089:     MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
    1090:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
    1091:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

    1093:     /* copy over the A part */
    1094:     Aloc = (Mat_SeqBAIJ*)baij->A->data;
    1095:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
    1096:     PetscMalloc1(bs,&rvals);

    1098:     for (i=0; i<mbs; i++) {
    1099:       rvals[0] = bs*(baij->rstartbs + i);
    1100:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    1101:       for (j=ai[i]; j<ai[i+1]; j++) {
    1102:         col = (baij->cstartbs+aj[j])*bs;
    1103:         for (k=0; k<bs; k++) {
    1104:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
    1105:           col++; a += bs;
    1106:         }
    1107:       }
    1108:     }
    1109:     /* copy over the B part */
    1110:     Aloc = (Mat_SeqBAIJ*)baij->B->data;
    1111:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
    1112:     for (i=0; i<mbs; i++) {
    1113:       rvals[0] = bs*(baij->rstartbs + i);
    1114:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    1115:       for (j=ai[i]; j<ai[i+1]; j++) {
    1116:         col = baij->garray[aj[j]]*bs;
    1117:         for (k=0; k<bs; k++) {
    1118:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
    1119:           col++; a += bs;
    1120:         }
    1121:       }
    1122:     }
    1123:     PetscFree(rvals);
    1124:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    1125:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    1126:     /*
    1127:        Everyone has to call to draw the matrix since the graphics waits are
    1128:        synchronized across all processors that share the PetscDraw object
    1129:     */
    1130:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
    1131:     PetscObjectGetName((PetscObject)mat,&matname);
    1132:     if (!rank) {
    1133:       PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,matname);
    1134:       MatView_SeqBAIJ(((Mat_MPIBAIJ*)(A->data))->A,sviewer);
    1135:     }
    1136:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
    1137:     PetscViewerFlush(viewer);
    1138:     MatDestroy(&A);
    1139:   }
    1140:   return(0);
    1141: }

    1145: static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer)
    1146: {
    1147:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)mat->data;
    1148:   Mat_SeqBAIJ    *A = (Mat_SeqBAIJ*)a->A->data;
    1149:   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)a->B->data;
    1151:   PetscInt       i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen;
    1152:   PetscInt       *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll;
    1153:   int            fd;
    1154:   PetscScalar    *column_values;
    1155:   FILE           *file;
    1156:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
    1157:   PetscInt       message_count,flowcontrolcount;

    1160:   MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
    1161:   MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
    1162:   nz   = bs2*(A->nz + B->nz);
    1163:   rlen = mat->rmap->n;
    1164:   PetscViewerBinaryGetDescriptor(viewer,&fd);
    1165:   if (!rank) {
    1166:     header[0] = MAT_FILE_CLASSID;
    1167:     header[1] = mat->rmap->N;
    1168:     header[2] = mat->cmap->N;

    1170:     MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
    1171:     PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
    1172:     /* get largest number of rows any processor has */
    1173:     range = mat->rmap->range;
    1174:     for (i=1; i<size; i++) {
    1175:       rlen = PetscMax(rlen,range[i+1] - range[i]);
    1176:     }
    1177:   } else {
    1178:     MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
    1179:   }

    1181:   PetscMalloc1(rlen/bs,&crow_lens);
    1182:   /* compute lengths of each row  */
    1183:   for (i=0; i<a->mbs; i++) {
    1184:     crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
    1185:   }
    1186:   /* store the row lengths to the file */
    1187:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
    1188:   if (!rank) {
    1189:     MPI_Status status;
    1190:     PetscMalloc1(rlen,&row_lens);
    1191:     rlen = (range[1] - range[0])/bs;
    1192:     for (i=0; i<rlen; i++) {
    1193:       for (j=0; j<bs; j++) {
    1194:         row_lens[i*bs+j] = bs*crow_lens[i];
    1195:       }
    1196:     }
    1197:     PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
    1198:     for (i=1; i<size; i++) {
    1199:       rlen = (range[i+1] - range[i])/bs;
    1200:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
    1201:       MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
    1202:       for (k=0; k<rlen; k++) {
    1203:         for (j=0; j<bs; j++) {
    1204:           row_lens[k*bs+j] = bs*crow_lens[k];
    1205:         }
    1206:       }
    1207:       PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
    1208:     }
    1209:     PetscViewerFlowControlEndMaster(viewer,&message_count);
    1210:     PetscFree(row_lens);
    1211:   } else {
    1212:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
    1213:     MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
    1214:     PetscViewerFlowControlEndWorker(viewer,&message_count);
    1215:   }
    1216:   PetscFree(crow_lens);

    1218:   /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the
    1219:      information needed to make it for each row from a block row. This does require more communication but still not more than
    1220:      the communication needed for the nonzero values  */
    1221:   nzmax = nz; /*  space a largest processor needs */
    1222:   MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
    1223:   PetscMalloc1(nzmax,&column_indices);
    1224:   cnt   = 0;
    1225:   for (i=0; i<a->mbs; i++) {
    1226:     pcnt = cnt;
    1227:     for (j=B->i[i]; j<B->i[i+1]; j++) {
    1228:       if ((col = garray[B->j[j]]) > cstart) break;
    1229:       for (l=0; l<bs; l++) {
    1230:         column_indices[cnt++] = bs*col+l;
    1231:       }
    1232:     }
    1233:     for (k=A->i[i]; k<A->i[i+1]; k++) {
    1234:       for (l=0; l<bs; l++) {
    1235:         column_indices[cnt++] = bs*(A->j[k] + cstart)+l;
    1236:       }
    1237:     }
    1238:     for (; j<B->i[i+1]; j++) {
    1239:       for (l=0; l<bs; l++) {
    1240:         column_indices[cnt++] = bs*garray[B->j[j]]+l;
    1241:       }
    1242:     }
    1243:     len = cnt - pcnt;
    1244:     for (k=1; k<bs; k++) {
    1245:       PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));
    1246:       cnt += len;
    1247:     }
    1248:   }
    1249:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

    1251:   /* store the columns to the file */
    1252:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
    1253:   if (!rank) {
    1254:     MPI_Status status;
    1255:     PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
    1256:     for (i=1; i<size; i++) {
    1257:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
    1258:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
    1259:       MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
    1260:       PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);
    1261:     }
    1262:     PetscViewerFlowControlEndMaster(viewer,&message_count);
    1263:   } else {
    1264:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
    1265:     MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
    1266:     MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
    1267:     PetscViewerFlowControlEndWorker(viewer,&message_count);
    1268:   }
    1269:   PetscFree(column_indices);

    1271:   /* load up the numerical values */
    1272:   PetscMalloc1(nzmax,&column_values);
    1273:   cnt  = 0;
    1274:   for (i=0; i<a->mbs; i++) {
    1275:     rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]);
    1276:     for (j=B->i[i]; j<B->i[i+1]; j++) {
    1277:       if (garray[B->j[j]] > cstart) break;
    1278:       for (l=0; l<bs; l++) {
    1279:         for (ll=0; ll<bs; ll++) {
    1280:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
    1281:         }
    1282:       }
    1283:       cnt += bs;
    1284:     }
    1285:     for (k=A->i[i]; k<A->i[i+1]; k++) {
    1286:       for (l=0; l<bs; l++) {
    1287:         for (ll=0; ll<bs; ll++) {
    1288:           column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll];
    1289:         }
    1290:       }
    1291:       cnt += bs;
    1292:     }
    1293:     for (; j<B->i[i+1]; j++) {
    1294:       for (l=0; l<bs; l++) {
    1295:         for (ll=0; ll<bs; ll++) {
    1296:           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
    1297:         }
    1298:       }
    1299:       cnt += bs;
    1300:     }
    1301:     cnt += (bs-1)*rlen;
    1302:   }
    1303:   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);

    1305:   /* store the column values to the file */
    1306:   PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
    1307:   if (!rank) {
    1308:     MPI_Status status;
    1309:     PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
    1310:     for (i=1; i<size; i++) {
    1311:       PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
    1312:       MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
    1313:       MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);
    1314:       PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);
    1315:     }
    1316:     PetscViewerFlowControlEndMaster(viewer,&message_count);
    1317:   } else {
    1318:     PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
    1319:     MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
    1320:     MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
    1321:     PetscViewerFlowControlEndWorker(viewer,&message_count);
    1322:   }
    1323:   PetscFree(column_values);

    1325:   PetscViewerBinaryGetInfoPointer(viewer,&file);
    1326:   if (file) {
    1327:     fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs);
    1328:   }
    1329:   return(0);
    1330: }

    1334: PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer)
    1335: {
    1337:   PetscBool      iascii,isdraw,issocket,isbinary;

    1340:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    1341:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    1342:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
    1343:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    1344:   if (iascii || isdraw || issocket) {
    1345:     MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);
    1346:   } else if (isbinary) {
    1347:     MatView_MPIBAIJ_Binary(mat,viewer);
    1348:   }
    1349:   return(0);
    1350: }

    1354: PetscErrorCode MatDestroy_MPIBAIJ(Mat mat)
    1355: {
    1356:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;

    1360: #if defined(PETSC_USE_LOG)
    1361:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
    1362: #endif
    1363:   MatStashDestroy_Private(&mat->stash);
    1364:   MatStashDestroy_Private(&mat->bstash);
    1365:   MatDestroy(&baij->A);
    1366:   MatDestroy(&baij->B);
    1367: #if defined(PETSC_USE_CTABLE)
    1368:   PetscTableDestroy(&baij->colmap);
    1369: #else
    1370:   PetscFree(baij->colmap);
    1371: #endif
    1372:   PetscFree(baij->garray);
    1373:   VecDestroy(&baij->lvec);
    1374:   VecScatterDestroy(&baij->Mvctx);
    1375:   PetscFree2(baij->rowvalues,baij->rowindices);
    1376:   PetscFree(baij->barray);
    1377:   PetscFree2(baij->hd,baij->ht);
    1378:   PetscFree(baij->rangebs);
    1379:   PetscFree(mat->data);

    1381:   PetscObjectChangeTypeName((PetscObject)mat,0);
    1382:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
    1383:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
    1384:   PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);
    1385:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);
    1386:   PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);
    1387:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
    1388:   PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);
    1389:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);
    1390:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);
    1391:   return(0);
    1392: }

    1396: PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy)
    1397: {
    1398:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
    1400:   PetscInt       nt;

    1403:   VecGetLocalSize(xx,&nt);
    1404:   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
    1405:   VecGetLocalSize(yy,&nt);
    1406:   if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");
    1407:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1408:   (*a->A->ops->mult)(a->A,xx,yy);
    1409:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1410:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
    1411:   return(0);
    1412: }

    1416: PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
    1417: {
    1418:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    1422:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1423:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
    1424:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1425:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
    1426:   return(0);
    1427: }

    1431: PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy)
    1432: {
    1433:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
    1435:   PetscBool      merged;

    1438:   VecScatterGetMerged(a->Mvctx,&merged);
    1439:   /* do nondiagonal part */
    1440:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
    1441:   if (!merged) {
    1442:     /* send it on its way */
    1443:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    1444:     /* do local part */
    1445:     (*a->A->ops->multtranspose)(a->A,xx,yy);
    1446:     /* receive remote parts: note this assumes the values are not actually */
    1447:     /* inserted in yy until the next line */
    1448:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    1449:   } else {
    1450:     /* do local part */
    1451:     (*a->A->ops->multtranspose)(a->A,xx,yy);
    1452:     /* send it on its way */
    1453:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    1454:     /* values actually were received in the Begin() but we need to call this nop */
    1455:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    1456:   }
    1457:   return(0);
    1458: }

    1462: PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
    1463: {
    1464:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    1468:   /* do nondiagonal part */
    1469:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
    1470:   /* send it on its way */
    1471:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
    1472:   /* do local part */
    1473:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
    1474:   /* receive remote parts: note this assumes the values are not actually */
    1475:   /* inserted in yy until the next line, which is true for my implementation*/
    1476:   /* but is not perhaps always true. */
    1477:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
    1478:   return(0);
    1479: }

    1481: /*
    1482:   This only works correctly for square matrices where the subblock A->A is the
    1483:    diagonal block
    1484: */
    1487: PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v)
    1488: {
    1489:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    1493:   if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
    1494:   MatGetDiagonal(a->A,v);
    1495:   return(0);
    1496: }

    1500: PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa)
    1501: {
    1502:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    1506:   MatScale(a->A,aa);
    1507:   MatScale(a->B,aa);
    1508:   return(0);
    1509: }

    1513: PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1514: {
    1515:   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
    1516:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
    1518:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
    1519:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
    1520:   PetscInt       *cmap,*idx_p,cstart = mat->cstartbs;

    1523:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
    1524:   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
    1525:   mat->getrowactive = PETSC_TRUE;

    1527:   if (!mat->rowvalues && (idx || v)) {
    1528:     /*
    1529:         allocate enough space to hold information from the longest row.
    1530:     */
    1531:     Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data;
    1532:     PetscInt    max = 1,mbs = mat->mbs,tmp;
    1533:     for (i=0; i<mbs; i++) {
    1534:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
    1535:       if (max < tmp) max = tmp;
    1536:     }
    1537:     PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
    1538:   }
    1539:   lrow = row - brstart;

    1541:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
    1542:   if (!v)   {pvA = 0; pvB = 0;}
    1543:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
    1544:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
    1545:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
    1546:   nztot = nzA + nzB;

    1548:   cmap = mat->garray;
    1549:   if (v  || idx) {
    1550:     if (nztot) {
    1551:       /* Sort by increasing column numbers, assuming A and B already sorted */
    1552:       PetscInt imark = -1;
    1553:       if (v) {
    1554:         *v = v_p = mat->rowvalues;
    1555:         for (i=0; i<nzB; i++) {
    1556:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
    1557:           else break;
    1558:         }
    1559:         imark = i;
    1560:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
    1561:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
    1562:       }
    1563:       if (idx) {
    1564:         *idx = idx_p = mat->rowindices;
    1565:         if (imark > -1) {
    1566:           for (i=0; i<imark; i++) {
    1567:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
    1568:           }
    1569:         } else {
    1570:           for (i=0; i<nzB; i++) {
    1571:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
    1572:             else break;
    1573:           }
    1574:           imark = i;
    1575:         }
    1576:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
    1577:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
    1578:       }
    1579:     } else {
    1580:       if (idx) *idx = 0;
    1581:       if (v)   *v   = 0;
    1582:     }
    1583:   }
    1584:   *nz  = nztot;
    1585:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
    1586:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
    1587:   return(0);
    1588: }

    1592: PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1593: {
    1594:   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;

    1597:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called");
    1598:   baij->getrowactive = PETSC_FALSE;
    1599:   return(0);
    1600: }

    1604: PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A)
    1605: {
    1606:   Mat_MPIBAIJ    *l = (Mat_MPIBAIJ*)A->data;

    1610:   MatZeroEntries(l->A);
    1611:   MatZeroEntries(l->B);
    1612:   return(0);
    1613: }

    1617: PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
    1618: {
    1619:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)matin->data;
    1620:   Mat            A  = a->A,B = a->B;
    1622:   PetscReal      isend[5],irecv[5];

    1625:   info->block_size = (PetscReal)matin->rmap->bs;

    1627:   MatGetInfo(A,MAT_LOCAL,info);

    1629:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
    1630:   isend[3] = info->memory;  isend[4] = info->mallocs;

    1632:   MatGetInfo(B,MAT_LOCAL,info);

    1634:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
    1635:   isend[3] += info->memory;  isend[4] += info->mallocs;

    1637:   if (flag == MAT_LOCAL) {
    1638:     info->nz_used      = isend[0];
    1639:     info->nz_allocated = isend[1];
    1640:     info->nz_unneeded  = isend[2];
    1641:     info->memory       = isend[3];
    1642:     info->mallocs      = isend[4];
    1643:   } else if (flag == MAT_GLOBAL_MAX) {
    1644:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

    1646:     info->nz_used      = irecv[0];
    1647:     info->nz_allocated = irecv[1];
    1648:     info->nz_unneeded  = irecv[2];
    1649:     info->memory       = irecv[3];
    1650:     info->mallocs      = irecv[4];
    1651:   } else if (flag == MAT_GLOBAL_SUM) {
    1652:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

    1654:     info->nz_used      = irecv[0];
    1655:     info->nz_allocated = irecv[1];
    1656:     info->nz_unneeded  = irecv[2];
    1657:     info->memory       = irecv[3];
    1658:     info->mallocs      = irecv[4];
    1659:   } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
    1660:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
    1661:   info->fill_ratio_needed = 0;
    1662:   info->factor_mallocs    = 0;
    1663:   return(0);
    1664: }

    1668: PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg)
    1669: {
    1670:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    1674:   switch (op) {
    1675:   case MAT_NEW_NONZERO_LOCATIONS:
    1676:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
    1677:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
    1678:   case MAT_KEEP_NONZERO_PATTERN:
    1679:   case MAT_NEW_NONZERO_LOCATION_ERR:
    1680:     MatCheckPreallocated(A,1);
    1681:     MatSetOption(a->A,op,flg);
    1682:     MatSetOption(a->B,op,flg);
    1683:     break;
    1684:   case MAT_ROW_ORIENTED:
    1685:     MatCheckPreallocated(A,1);
    1686:     a->roworiented = flg;

    1688:     MatSetOption(a->A,op,flg);
    1689:     MatSetOption(a->B,op,flg);
    1690:     break;
    1691:   case MAT_NEW_DIAGONALS:
    1692:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
    1693:     break;
    1694:   case MAT_IGNORE_OFF_PROC_ENTRIES:
    1695:     a->donotstash = flg;
    1696:     break;
    1697:   case MAT_USE_HASH_TABLE:
    1698:     a->ht_flag = flg;
    1699:     break;
    1700:   case MAT_SYMMETRIC:
    1701:   case MAT_STRUCTURALLY_SYMMETRIC:
    1702:   case MAT_HERMITIAN:
    1703:   case MAT_SYMMETRY_ETERNAL:
    1704:     MatCheckPreallocated(A,1);
    1705:     MatSetOption(a->A,op,flg);
    1706:     break;
    1707:   default:
    1708:     SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op);
    1709:   }
    1710:   return(0);
    1711: }

    1715: PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout)
    1716: {
    1717:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)A->data;
    1718:   Mat_SeqBAIJ    *Aloc;
    1719:   Mat            B;
    1721:   PetscInt       M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col;
    1722:   PetscInt       bs=A->rmap->bs,mbs=baij->mbs;
    1723:   MatScalar      *a;

    1726:   if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");
    1727:   if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
    1728:     MatCreate(PetscObjectComm((PetscObject)A),&B);
    1729:     MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
    1730:     MatSetType(B,((PetscObject)A)->type_name);
    1731:     /* Do not know preallocation information, but must set block size */
    1732:     MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);
    1733:   } else {
    1734:     B = *matout;
    1735:   }

    1737:   /* copy over the A part */
    1738:   Aloc = (Mat_SeqBAIJ*)baij->A->data;
    1739:   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
    1740:   PetscMalloc1(bs,&rvals);

    1742:   for (i=0; i<mbs; i++) {
    1743:     rvals[0] = bs*(baij->rstartbs + i);
    1744:     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    1745:     for (j=ai[i]; j<ai[i+1]; j++) {
    1746:       col = (baij->cstartbs+aj[j])*bs;
    1747:       for (k=0; k<bs; k++) {
    1748:         MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);

    1750:         col++; a += bs;
    1751:       }
    1752:     }
    1753:   }
    1754:   /* copy over the B part */
    1755:   Aloc = (Mat_SeqBAIJ*)baij->B->data;
    1756:   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
    1757:   for (i=0; i<mbs; i++) {
    1758:     rvals[0] = bs*(baij->rstartbs + i);
    1759:     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    1760:     for (j=ai[i]; j<ai[i+1]; j++) {
    1761:       col = baij->garray[aj[j]]*bs;
    1762:       for (k=0; k<bs; k++) {
    1763:         MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);
    1764:         col++;
    1765:         a += bs;
    1766:       }
    1767:     }
    1768:   }
    1769:   PetscFree(rvals);
    1770:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    1771:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

    1773:   if (reuse == MAT_INITIAL_MATRIX || *matout != A) *matout = B;
    1774:   else {
    1775:     MatHeaderMerge(A,&B);
    1776:   }
    1777:   return(0);
    1778: }

    1782: PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr)
    1783: {
    1784:   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
    1785:   Mat            a     = baij->A,b = baij->B;
    1787:   PetscInt       s1,s2,s3;

    1790:   MatGetLocalSize(mat,&s2,&s3);
    1791:   if (rr) {
    1792:     VecGetLocalSize(rr,&s1);
    1793:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
    1794:     /* Overlap communication with computation. */
    1795:     VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1796:   }
    1797:   if (ll) {
    1798:     VecGetLocalSize(ll,&s1);
    1799:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
    1800:     (*b->ops->diagonalscale)(b,ll,NULL);
    1801:   }
    1802:   /* scale  the diagonal block */
    1803:   (*a->ops->diagonalscale)(a,ll,rr);

    1805:   if (rr) {
    1806:     /* Do a scatter end and then right scale the off-diagonal block */
    1807:     VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1808:     (*b->ops->diagonalscale)(b,NULL,baij->lvec);
    1809:   }
    1810:   return(0);
    1811: }

    1815: PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
    1816: {
    1817:   Mat_MPIBAIJ   *l      = (Mat_MPIBAIJ *) A->data;
    1818:   PetscInt      *owners = A->rmap->range;
    1819:   PetscInt       n      = A->rmap->n;
    1820:   PetscSF        sf;
    1821:   PetscInt      *lrows;
    1822:   PetscSFNode   *rrows;
    1823:   PetscInt       r, p = 0, len = 0;

    1827:   /* Create SF where leaves are input rows and roots are owned rows */
    1828:   PetscMalloc1(n, &lrows);
    1829:   for (r = 0; r < n; ++r) lrows[r] = -1;
    1830:   if (!A->nooffproczerorows) {PetscMalloc1(N, &rrows);}
    1831:   for (r = 0; r < N; ++r) {
    1832:     const PetscInt idx   = rows[r];
    1833:     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);
    1834:     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
    1835:       PetscLayoutFindOwner(A->rmap,idx,&p);
    1836:     }
    1837:     if (A->nooffproczerorows) {
    1838:       if (p != l->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,l->rank);
    1839:       lrows[len++] = idx - owners[p];
    1840:     } else {
    1841:       rrows[r].rank = p;
    1842:       rrows[r].index = rows[r] - owners[p];
    1843:     }
    1844:   }
    1845:   if (!A->nooffproczerorows) {
    1846:     PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
    1847:     PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
    1848:     /* Collect flags for rows to be zeroed */
    1849:     PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
    1850:     PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
    1851:     PetscSFDestroy(&sf);
    1852:     /* Compress and put in row numbers */
    1853:     for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
    1854:   }
    1855:   /* fix right hand side if needed */
    1856:   if (x && b) {
    1857:     const PetscScalar *xx;
    1858:     PetscScalar       *bb;

    1860:     VecGetArrayRead(x,&xx);
    1861:     VecGetArray(b,&bb);
    1862:     for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
    1863:     VecRestoreArrayRead(x,&xx);
    1864:     VecRestoreArray(b,&bb);
    1865:   }

    1867:   /* actually zap the local rows */
    1868:   /*
    1869:         Zero the required rows. If the "diagonal block" of the matrix
    1870:      is square and the user wishes to set the diagonal we use separate
    1871:      code so that MatSetValues() is not called for each diagonal allocating
    1872:      new memory, thus calling lots of mallocs and slowing things down.

    1874:   */
    1875:   /* must zero l->B before l->A because the (diag) case below may put values into l->B*/
    1876:   MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,NULL,NULL);
    1877:   if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) {
    1878:     MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,NULL,NULL);
    1879:   } else if (diag != 0.0) {
    1880:     MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);
    1881:     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\
    1882:        MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
    1883:     for (r = 0; r < len; ++r) {
    1884:       const PetscInt row = lrows[r] + A->rmap->rstart;
    1885:       MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);
    1886:     }
    1887:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    1888:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    1889:   } else {
    1890:     MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,NULL,NULL);
    1891:   }
    1892:   PetscFree(lrows);

    1894:   /* only change matrix nonzero state if pattern was allowed to be changed */
    1895:   if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) {
    1896:     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
    1897:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
    1898:   }
    1899:   return(0);
    1900: }

    1904: PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
    1905: {
    1906:   Mat_MPIBAIJ       *l = (Mat_MPIBAIJ*)A->data;
    1907:   PetscErrorCode    ierr;
    1908:   PetscMPIInt       n = A->rmap->n;
    1909:   PetscInt          i,j,k,r,p = 0,len = 0,row,col,count;
    1910:   PetscInt          *lrows,*owners = A->rmap->range;
    1911:   PetscSFNode       *rrows;
    1912:   PetscSF           sf;
    1913:   const PetscScalar *xx;
    1914:   PetscScalar       *bb,*mask;
    1915:   Vec               xmask,lmask;
    1916:   Mat_SeqBAIJ       *baij = (Mat_SeqBAIJ*)l->B->data;
    1917:   PetscInt           bs = A->rmap->bs, bs2 = baij->bs2;
    1918:   PetscScalar       *aa;

    1921:   /* Create SF where leaves are input rows and roots are owned rows */
    1922:   PetscMalloc1(n, &lrows);
    1923:   for (r = 0; r < n; ++r) lrows[r] = -1;
    1924:   PetscMalloc1(N, &rrows);
    1925:   for (r = 0; r < N; ++r) {
    1926:     const PetscInt idx   = rows[r];
    1927:     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);
    1928:     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
    1929:       PetscLayoutFindOwner(A->rmap,idx,&p);
    1930:     }
    1931:     rrows[r].rank  = p;
    1932:     rrows[r].index = rows[r] - owners[p];
    1933:   }
    1934:   PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
    1935:   PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
    1936:   /* Collect flags for rows to be zeroed */
    1937:   PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
    1938:   PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
    1939:   PetscSFDestroy(&sf);
    1940:   /* Compress and put in row numbers */
    1941:   for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
    1942:   /* zero diagonal part of matrix */
    1943:   MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
    1944:   /* handle off diagonal part of matrix */
    1945:   MatCreateVecs(A,&xmask,NULL);
    1946:   VecDuplicate(l->lvec,&lmask);
    1947:   VecGetArray(xmask,&bb);
    1948:   for (i=0; i<len; i++) bb[lrows[i]] = 1;
    1949:   VecRestoreArray(xmask,&bb);
    1950:   VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
    1951:   VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
    1952:   VecDestroy(&xmask);
    1953:   if (x) {
    1954:     VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1955:     VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1956:     VecGetArrayRead(l->lvec,&xx);
    1957:     VecGetArray(b,&bb);
    1958:   }
    1959:   VecGetArray(lmask,&mask);
    1960:   /* remove zeroed rows of off diagonal matrix */
    1961:   for (i = 0; i < len; ++i) {
    1962:     row   = lrows[i];
    1963:     count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
    1964:     aa    = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
    1965:     for (k = 0; k < count; ++k) {
    1966:       aa[0] = 0.0;
    1967:       aa   += bs;
    1968:     }
    1969:   }
    1970:   /* loop over all elements of off process part of matrix zeroing removed columns*/
    1971:   for (i = 0; i < l->B->rmap->N; ++i) {
    1972:     row = i/bs;
    1973:     for (j = baij->i[row]; j < baij->i[row+1]; ++j) {
    1974:       for (k = 0; k < bs; ++k) {
    1975:         col = bs*baij->j[j] + k;
    1976:         if (PetscAbsScalar(mask[col])) {
    1977:           aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k;
    1978:           if (x) bb[i] -= aa[0]*xx[col];
    1979:           aa[0] = 0.0;
    1980:         }
    1981:       }
    1982:     }
    1983:   }
    1984:   if (x) {
    1985:     VecRestoreArray(b,&bb);
    1986:     VecRestoreArrayRead(l->lvec,&xx);
    1987:   }
    1988:   VecRestoreArray(lmask,&mask);
    1989:   VecDestroy(&lmask);
    1990:   PetscFree(lrows);

    1992:   /* only change matrix nonzero state if pattern was allowed to be changed */
    1993:   if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) {
    1994:     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
    1995:     MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
    1996:   }
    1997:   return(0);
    1998: }

    2002: PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A)
    2003: {
    2004:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    2008:   MatSetUnfactored(a->A);
    2009:   return(0);
    2010: }

    2012: static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*);

    2016: PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool  *flag)
    2017: {
    2018:   Mat_MPIBAIJ    *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data;
    2019:   Mat            a,b,c,d;
    2020:   PetscBool      flg;

    2024:   a = matA->A; b = matA->B;
    2025:   c = matB->A; d = matB->B;

    2027:   MatEqual(a,c,&flg);
    2028:   if (flg) {
    2029:     MatEqual(b,d,&flg);
    2030:   }
    2031:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
    2032:   return(0);
    2033: }

    2037: PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str)
    2038: {
    2040:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
    2041:   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;

    2044:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
    2045:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
    2046:     MatCopy_Basic(A,B,str);
    2047:   } else {
    2048:     MatCopy(a->A,b->A,str);
    2049:     MatCopy(a->B,b->B,str);
    2050:   }
    2051:   return(0);
    2052: }

    2056: PetscErrorCode MatSetUp_MPIBAIJ(Mat A)
    2057: {

    2061:   MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
    2062:   return(0);
    2063: }

    2067: PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
    2068: {
    2070:   PetscInt       bs = Y->rmap->bs,m = Y->rmap->N/bs;
    2071:   Mat_SeqBAIJ    *x = (Mat_SeqBAIJ*)X->data;
    2072:   Mat_SeqBAIJ    *y = (Mat_SeqBAIJ*)Y->data;

    2075:   MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
    2076:   return(0);
    2077: }

    2081: PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
    2082: {
    2084:   Mat_MPIBAIJ    *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data;
    2085:   PetscBLASInt   bnz,one=1;
    2086:   Mat_SeqBAIJ    *x,*y;

    2089:   if (str == SAME_NONZERO_PATTERN) {
    2090:     PetscScalar alpha = a;
    2091:     x    = (Mat_SeqBAIJ*)xx->A->data;
    2092:     y    = (Mat_SeqBAIJ*)yy->A->data;
    2093:     PetscBLASIntCast(x->nz,&bnz);
    2094:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
    2095:     x    = (Mat_SeqBAIJ*)xx->B->data;
    2096:     y    = (Mat_SeqBAIJ*)yy->B->data;
    2097:     PetscBLASIntCast(x->nz,&bnz);
    2098:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
    2099:     PetscObjectStateIncrease((PetscObject)Y);
    2100:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
    2101:     MatAXPY_Basic(Y,a,X,str);
    2102:   } else {
    2103:     Mat      B;
    2104:     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
    2105:     PetscMalloc1(yy->A->rmap->N,&nnz_d);
    2106:     PetscMalloc1(yy->B->rmap->N,&nnz_o);
    2107:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
    2108:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
    2109:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
    2110:     MatSetBlockSizesFromMats(B,Y,Y);
    2111:     MatSetType(B,MATMPIBAIJ);
    2112:     MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);
    2113:     MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
    2114:     MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
    2115:     /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */
    2116:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
    2117:     MatHeaderReplace(Y,&B);
    2118:     PetscFree(nnz_d);
    2119:     PetscFree(nnz_o);
    2120:   }
    2121:   return(0);
    2122: }

    2126: PetscErrorCode MatRealPart_MPIBAIJ(Mat A)
    2127: {
    2128:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    2132:   MatRealPart(a->A);
    2133:   MatRealPart(a->B);
    2134:   return(0);
    2135: }

    2139: PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A)
    2140: {
    2141:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    2145:   MatImaginaryPart(a->A);
    2146:   MatImaginaryPart(a->B);
    2147:   return(0);
    2148: }

    2152: PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
    2153: {
    2155:   IS             iscol_local;
    2156:   PetscInt       csize;

    2159:   ISGetLocalSize(iscol,&csize);
    2160:   if (call == MAT_REUSE_MATRIX) {
    2161:     PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
    2162:     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
    2163:   } else {
    2164:     ISAllGather(iscol,&iscol_local);
    2165:   }
    2166:   MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
    2167:   if (call == MAT_INITIAL_MATRIX) {
    2168:     PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
    2169:     ISDestroy(&iscol_local);
    2170:   }
    2171:   return(0);
    2172: }
    2173: extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*);
    2176: /*
    2177:   Not great since it makes two copies of the submatrix, first an SeqBAIJ
    2178:   in local and then by concatenating the local matrices the end result.
    2179:   Writing it directly would be much like MatGetSubMatrices_MPIBAIJ().
    2180:   This routine is used for BAIJ and SBAIJ matrices (unfortunate dependency).
    2181: */
    2182: PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
    2183: {
    2185:   PetscMPIInt    rank,size;
    2186:   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs;
    2187:   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow;
    2188:   Mat            M,Mreuse;
    2189:   MatScalar      *vwork,*aa;
    2190:   MPI_Comm       comm;
    2191:   IS             isrow_new, iscol_new;
    2192:   PetscBool      idflag,allrows, allcols;
    2193:   Mat_SeqBAIJ    *aij;

    2196:   PetscObjectGetComm((PetscObject)mat,&comm);
    2197:   MPI_Comm_rank(comm,&rank);
    2198:   MPI_Comm_size(comm,&size);
    2199:   /* The compression and expansion should be avoided. Doesn't point
    2200:      out errors, might change the indices, hence buggey */
    2201:   ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);
    2202:   ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);

    2204:   /* Check for special case: each processor gets entire matrix columns */
    2205:   ISIdentity(iscol,&idflag);
    2206:   ISGetLocalSize(iscol,&ncol);
    2207:   if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE;
    2208:   else allcols = PETSC_FALSE;

    2210:   ISIdentity(isrow,&idflag);
    2211:   ISGetLocalSize(isrow,&nrow);
    2212:   if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE;
    2213:   else allrows = PETSC_FALSE;

    2215:   if (call ==  MAT_REUSE_MATRIX) {
    2216:     PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
    2217:     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
    2218:     MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);
    2219:   } else {
    2220:     MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);
    2221:   }
    2222:   ISDestroy(&isrow_new);
    2223:   ISDestroy(&iscol_new);
    2224:   /*
    2225:       m - number of local rows
    2226:       n - number of columns (same on all processors)
    2227:       rstart - first row in new global matrix generated
    2228:   */
    2229:   MatGetBlockSize(mat,&bs);
    2230:   MatGetSize(Mreuse,&m,&n);
    2231:   m    = m/bs;
    2232:   n    = n/bs;

    2234:   if (call == MAT_INITIAL_MATRIX) {
    2235:     aij = (Mat_SeqBAIJ*)(Mreuse)->data;
    2236:     ii  = aij->i;
    2237:     jj  = aij->j;

    2239:     /*
    2240:         Determine the number of non-zeros in the diagonal and off-diagonal
    2241:         portions of the matrix in order to do correct preallocation
    2242:     */

    2244:     /* first get start and end of "diagonal" columns */
    2245:     if (csize == PETSC_DECIDE) {
    2246:       ISGetSize(isrow,&mglobal);
    2247:       if (mglobal == n*bs) { /* square matrix */
    2248:         nlocal = m;
    2249:       } else {
    2250:         nlocal = n/size + ((n % size) > rank);
    2251:       }
    2252:     } else {
    2253:       nlocal = csize/bs;
    2254:     }
    2255:     MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
    2256:     rstart = rend - nlocal;
    2257:     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);

    2259:     /* next, compute all the lengths */
    2260:     PetscMalloc2(m+1,&dlens,m+1,&olens);
    2261:     for (i=0; i<m; i++) {
    2262:       jend = ii[i+1] - ii[i];
    2263:       olen = 0;
    2264:       dlen = 0;
    2265:       for (j=0; j<jend; j++) {
    2266:         if (*jj < rstart || *jj >= rend) olen++;
    2267:         else dlen++;
    2268:         jj++;
    2269:       }
    2270:       olens[i] = olen;
    2271:       dlens[i] = dlen;
    2272:     }
    2273:     MatCreate(comm,&M);
    2274:     MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);
    2275:     MatSetType(M,((PetscObject)mat)->type_name);
    2276:     MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);
    2277:     MatMPISBAIJSetPreallocation(M,bs,0,dlens,0,olens);
    2278:     PetscFree2(dlens,olens);
    2279:   } else {
    2280:     PetscInt ml,nl;

    2282:     M    = *newmat;
    2283:     MatGetLocalSize(M,&ml,&nl);
    2284:     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
    2285:     MatZeroEntries(M);
    2286:     /*
    2287:          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
    2288:        rather than the slower MatSetValues().
    2289:     */
    2290:     M->was_assembled = PETSC_TRUE;
    2291:     M->assembled     = PETSC_FALSE;
    2292:   }
    2293:   MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);
    2294:   MatGetOwnershipRange(M,&rstart,&rend);
    2295:   aij  = (Mat_SeqBAIJ*)(Mreuse)->data;
    2296:   ii   = aij->i;
    2297:   jj   = aij->j;
    2298:   aa   = aij->a;
    2299:   for (i=0; i<m; i++) {
    2300:     row   = rstart/bs + i;
    2301:     nz    = ii[i+1] - ii[i];
    2302:     cwork = jj;     jj += nz;
    2303:     vwork = aa;     aa += nz*bs*bs;
    2304:     MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
    2305:   }

    2307:   MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
    2308:   MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
    2309:   *newmat = M;

    2311:   /* save submatrix used in processor for next request */
    2312:   if (call ==  MAT_INITIAL_MATRIX) {
    2313:     PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
    2314:     PetscObjectDereference((PetscObject)Mreuse);
    2315:   }
    2316:   return(0);
    2317: }

    2321: PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B)
    2322: {
    2323:   MPI_Comm       comm,pcomm;
    2324:   PetscInt       clocal_size,nrows;
    2325:   const PetscInt *rows;
    2326:   PetscMPIInt    size;
    2327:   IS             crowp,lcolp;

    2331:   PetscObjectGetComm((PetscObject)A,&comm);
    2332:   /* make a collective version of 'rowp' */
    2333:   PetscObjectGetComm((PetscObject)rowp,&pcomm);
    2334:   if (pcomm==comm) {
    2335:     crowp = rowp;
    2336:   } else {
    2337:     ISGetSize(rowp,&nrows);
    2338:     ISGetIndices(rowp,&rows);
    2339:     ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);
    2340:     ISRestoreIndices(rowp,&rows);
    2341:   }
    2342:   ISSetPermutation(crowp);
    2343:   /* make a local version of 'colp' */
    2344:   PetscObjectGetComm((PetscObject)colp,&pcomm);
    2345:   MPI_Comm_size(pcomm,&size);
    2346:   if (size==1) {
    2347:     lcolp = colp;
    2348:   } else {
    2349:     ISAllGather(colp,&lcolp);
    2350:   }
    2351:   ISSetPermutation(lcolp);
    2352:   /* now we just get the submatrix */
    2353:   MatGetLocalSize(A,NULL,&clocal_size);
    2354:   MatGetSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);
    2355:   /* clean up */
    2356:   if (pcomm!=comm) {
    2357:     ISDestroy(&crowp);
    2358:   }
    2359:   if (size>1) {
    2360:     ISDestroy(&lcolp);
    2361:   }
    2362:   return(0);
    2363: }

    2367: PetscErrorCode  MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
    2368: {
    2369:   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data;
    2370:   Mat_SeqBAIJ *B    = (Mat_SeqBAIJ*)baij->B->data;

    2373:   if (nghosts) *nghosts = B->nbs;
    2374:   if (ghosts) *ghosts = baij->garray;
    2375:   return(0);
    2376: }

    2380: PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat)
    2381: {
    2382:   Mat            B;
    2383:   Mat_MPIBAIJ    *a  = (Mat_MPIBAIJ*)A->data;
    2384:   Mat_SeqBAIJ    *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data;
    2385:   Mat_SeqAIJ     *b;
    2387:   PetscMPIInt    size,rank,*recvcounts = 0,*displs = 0;
    2388:   PetscInt       sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs;
    2389:   PetscInt       m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf;

    2392:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
    2393:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

    2395:   /* ----------------------------------------------------------------
    2396:      Tell every processor the number of nonzeros per row
    2397:   */
    2398:   PetscMalloc1(A->rmap->N/bs,&lens);
    2399:   for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) {
    2400:     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];
    2401:   }
    2402:   PetscMalloc1(2*size,&recvcounts);
    2403:   displs    = recvcounts + size;
    2404:   for (i=0; i<size; i++) {
    2405:     recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs;
    2406:     displs[i]     = A->rmap->range[i]/bs;
    2407:   }
    2408: #if defined(PETSC_HAVE_MPI_IN_PLACE)
    2409:   MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
    2410: #else
    2411:   sendcount = A->rmap->rend/bs - A->rmap->rstart/bs;
    2412:   MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
    2413: #endif
    2414:   /* ---------------------------------------------------------------
    2415:      Create the sequential matrix of the same type as the local block diagonal
    2416:   */
    2417:   MatCreate(PETSC_COMM_SELF,&B);
    2418:   MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);
    2419:   MatSetType(B,MATSEQAIJ);
    2420:   MatSeqAIJSetPreallocation(B,0,lens);
    2421:   b    = (Mat_SeqAIJ*)B->data;

    2423:   /*--------------------------------------------------------------------
    2424:     Copy my part of matrix column indices over
    2425:   */
    2426:   sendcount  = ad->nz + bd->nz;
    2427:   jsendbuf   = b->j + b->i[rstarts[rank]/bs];
    2428:   a_jsendbuf = ad->j;
    2429:   b_jsendbuf = bd->j;
    2430:   n          = A->rmap->rend/bs - A->rmap->rstart/bs;
    2431:   cnt        = 0;
    2432:   for (i=0; i<n; i++) {

    2434:     /* put in lower diagonal portion */
    2435:     m = bd->i[i+1] - bd->i[i];
    2436:     while (m > 0) {
    2437:       /* is it above diagonal (in bd (compressed) numbering) */
    2438:       if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break;
    2439:       jsendbuf[cnt++] = garray[*b_jsendbuf++];
    2440:       m--;
    2441:     }

    2443:     /* put in diagonal portion */
    2444:     for (j=ad->i[i]; j<ad->i[i+1]; j++) {
    2445:       jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++;
    2446:     }

    2448:     /* put in upper diagonal portion */
    2449:     while (m-- > 0) {
    2450:       jsendbuf[cnt++] = garray[*b_jsendbuf++];
    2451:     }
    2452:   }
    2453:   if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt);

    2455:   /*--------------------------------------------------------------------
    2456:     Gather all column indices to all processors
    2457:   */
    2458:   for (i=0; i<size; i++) {
    2459:     recvcounts[i] = 0;
    2460:     for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) {
    2461:       recvcounts[i] += lens[j];
    2462:     }
    2463:   }
    2464:   displs[0] = 0;
    2465:   for (i=1; i<size; i++) {
    2466:     displs[i] = displs[i-1] + recvcounts[i-1];
    2467:   }
    2468: #if defined(PETSC_HAVE_MPI_IN_PLACE)
    2469:   MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
    2470: #else
    2471:   MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));
    2472: #endif
    2473:   /*--------------------------------------------------------------------
    2474:     Assemble the matrix into useable form (note numerical values not yet set)
    2475:   */
    2476:   /* set the b->ilen (length of each row) values */
    2477:   PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));
    2478:   /* set the b->i indices */
    2479:   b->i[0] = 0;
    2480:   for (i=1; i<=A->rmap->N/bs; i++) {
    2481:     b->i[i] = b->i[i-1] + lens[i-1];
    2482:   }
    2483:   PetscFree(lens);
    2484:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    2485:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    2486:   PetscFree(recvcounts);

    2488:   if (A->symmetric) {
    2489:     MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);
    2490:   } else if (A->hermitian) {
    2491:     MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);
    2492:   } else if (A->structurally_symmetric) {
    2493:     MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);
    2494:   }
    2495:   *newmat = B;
    2496:   return(0);
    2497: }

    2501: PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    2502: {
    2503:   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
    2505:   Vec            bb1 = 0;

    2508:   if (flag == SOR_APPLY_UPPER) {
    2509:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2510:     return(0);
    2511:   }

    2513:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) {
    2514:     VecDuplicate(bb,&bb1);
    2515:   }

    2517:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
    2518:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    2519:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2520:       its--;
    2521:     }

    2523:     while (its--) {
    2524:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
    2525:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

    2527:       /* update rhs: bb1 = bb - B*x */
    2528:       VecScale(mat->lvec,-1.0);
    2529:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

    2531:       /* local sweep */
    2532:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
    2533:     }
    2534:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
    2535:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    2536:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2537:       its--;
    2538:     }
    2539:     while (its--) {
    2540:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
    2541:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

    2543:       /* update rhs: bb1 = bb - B*x */
    2544:       VecScale(mat->lvec,-1.0);
    2545:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

    2547:       /* local sweep */
    2548:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
    2549:     }
    2550:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
    2551:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    2552:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2553:       its--;
    2554:     }
    2555:     while (its--) {
    2556:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
    2557:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

    2559:       /* update rhs: bb1 = bb - B*x */
    2560:       VecScale(mat->lvec,-1.0);
    2561:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

    2563:       /* local sweep */
    2564:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
    2565:     }
    2566:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported");

    2568:   VecDestroy(&bb1);
    2569:   return(0);
    2570: }

    2574: PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms)
    2575: {
    2577:   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)A->data;
    2578:   PetscInt       N,i,*garray = aij->garray;
    2579:   PetscInt       ib,jb,bs = A->rmap->bs;
    2580:   Mat_SeqBAIJ    *a_aij = (Mat_SeqBAIJ*) aij->A->data;
    2581:   MatScalar      *a_val = a_aij->a;
    2582:   Mat_SeqBAIJ    *b_aij = (Mat_SeqBAIJ*) aij->B->data;
    2583:   MatScalar      *b_val = b_aij->a;
    2584:   PetscReal      *work;

    2587:   MatGetSize(A,NULL,&N);
    2588:   PetscCalloc1(N,&work);
    2589:   if (type == NORM_2) {
    2590:     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
    2591:       for (jb=0; jb<bs; jb++) {
    2592:         for (ib=0; ib<bs; ib++) {
    2593:           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val);
    2594:           a_val++;
    2595:         }
    2596:       }
    2597:     }
    2598:     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
    2599:       for (jb=0; jb<bs; jb++) {
    2600:         for (ib=0; ib<bs; ib++) {
    2601:           work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val);
    2602:           b_val++;
    2603:         }
    2604:       }
    2605:     }
    2606:   } else if (type == NORM_1) {
    2607:     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
    2608:       for (jb=0; jb<bs; jb++) {
    2609:         for (ib=0; ib<bs; ib++) {
    2610:           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val);
    2611:           a_val++;
    2612:         }
    2613:       }
    2614:     }
    2615:     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
    2616:       for (jb=0; jb<bs; jb++) {
    2617:        for (ib=0; ib<bs; ib++) {
    2618:           work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val);
    2619:           b_val++;
    2620:         }
    2621:       }
    2622:     }
    2623:   } else if (type == NORM_INFINITY) {
    2624:     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
    2625:       for (jb=0; jb<bs; jb++) {
    2626:         for (ib=0; ib<bs; ib++) {
    2627:           int col = A->cmap->rstart + a_aij->j[i] * bs + jb;
    2628:           work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]);
    2629:           a_val++;
    2630:         }
    2631:       }
    2632:     }
    2633:     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
    2634:       for (jb=0; jb<bs; jb++) {
    2635:         for (ib=0; ib<bs; ib++) {
    2636:           int col = garray[b_aij->j[i]] * bs + jb;
    2637:           work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]);
    2638:           b_val++;
    2639:         }
    2640:       }
    2641:     }
    2642:   } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
    2643:   if (type == NORM_INFINITY) {
    2644:     MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
    2645:   } else {
    2646:     MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
    2647:   }
    2648:   PetscFree(work);
    2649:   if (type == NORM_2) {
    2650:     for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]);
    2651:   }
    2652:   return(0);
    2653: }

    2657: PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values)
    2658: {
    2659:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*) A->data;

    2663:   MatInvertBlockDiagonal(a->A,values);
    2664:   A->errortype = a->A->errortype;
    2665:   return(0);
    2666: }

    2670: PetscErrorCode MatShift_MPIBAIJ(Mat Y,PetscScalar a)
    2671: {
    2673:   Mat_MPIBAIJ    *maij = (Mat_MPIBAIJ*)Y->data;
    2674:   Mat_SeqBAIJ    *aij = (Mat_SeqBAIJ*)maij->A->data;

    2677:   if (!Y->preallocated) {
    2678:     MatMPIBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
    2679:   } else if (!aij->nz) {
    2680:     PetscInt nonew = aij->nonew;
    2681:     MatSeqBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
    2682:     aij->nonew = nonew;
    2683:   }
    2684:   MatShift_Basic(Y,a);
    2685:   return(0);
    2686: }

    2690: PetscErrorCode MatMissingDiagonal_MPIBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
    2691: {
    2692:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;

    2696:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
    2697:   MatMissingDiagonal(a->A,missing,d);
    2698:   if (d) {
    2699:     PetscInt rstart;
    2700:     MatGetOwnershipRange(A,&rstart,NULL);
    2701:     *d += rstart/A->rmap->bs;

    2703:   }
    2704:   return(0);
    2705: }

    2707: /* -------------------------------------------------------------------*/
    2708: static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ,
    2709:                                        MatGetRow_MPIBAIJ,
    2710:                                        MatRestoreRow_MPIBAIJ,
    2711:                                        MatMult_MPIBAIJ,
    2712:                                 /* 4*/ MatMultAdd_MPIBAIJ,
    2713:                                        MatMultTranspose_MPIBAIJ,
    2714:                                        MatMultTransposeAdd_MPIBAIJ,
    2715:                                        0,
    2716:                                        0,
    2717:                                        0,
    2718:                                 /*10*/ 0,
    2719:                                        0,
    2720:                                        0,
    2721:                                        MatSOR_MPIBAIJ,
    2722:                                        MatTranspose_MPIBAIJ,
    2723:                                 /*15*/ MatGetInfo_MPIBAIJ,
    2724:                                        MatEqual_MPIBAIJ,
    2725:                                        MatGetDiagonal_MPIBAIJ,
    2726:                                        MatDiagonalScale_MPIBAIJ,
    2727:                                        MatNorm_MPIBAIJ,
    2728:                                 /*20*/ MatAssemblyBegin_MPIBAIJ,
    2729:                                        MatAssemblyEnd_MPIBAIJ,
    2730:                                        MatSetOption_MPIBAIJ,
    2731:                                        MatZeroEntries_MPIBAIJ,
    2732:                                 /*24*/ MatZeroRows_MPIBAIJ,
    2733:                                        0,
    2734:                                        0,
    2735:                                        0,
    2736:                                        0,
    2737:                                 /*29*/ MatSetUp_MPIBAIJ,
    2738:                                        0,
    2739:                                        0,
    2740:                                        0,
    2741:                                        0,
    2742:                                 /*34*/ MatDuplicate_MPIBAIJ,
    2743:                                        0,
    2744:                                        0,
    2745:                                        0,
    2746:                                        0,
    2747:                                 /*39*/ MatAXPY_MPIBAIJ,
    2748:                                        MatGetSubMatrices_MPIBAIJ,
    2749:                                        MatIncreaseOverlap_MPIBAIJ,
    2750:                                        MatGetValues_MPIBAIJ,
    2751:                                        MatCopy_MPIBAIJ,
    2752:                                 /*44*/ 0,
    2753:                                        MatScale_MPIBAIJ,
    2754:                                        MatShift_MPIBAIJ,
    2755:                                        0,
    2756:                                        MatZeroRowsColumns_MPIBAIJ,
    2757:                                 /*49*/ 0,
    2758:                                        0,
    2759:                                        0,
    2760:                                        0,
    2761:                                        0,
    2762:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
    2763:                                        0,
    2764:                                        MatSetUnfactored_MPIBAIJ,
    2765:                                        MatPermute_MPIBAIJ,
    2766:                                        MatSetValuesBlocked_MPIBAIJ,
    2767:                                 /*59*/ MatGetSubMatrix_MPIBAIJ,
    2768:                                        MatDestroy_MPIBAIJ,
    2769:                                        MatView_MPIBAIJ,
    2770:                                        0,
    2771:                                        0,
    2772:                                 /*64*/ 0,
    2773:                                        0,
    2774:                                        0,
    2775:                                        0,
    2776:                                        0,
    2777:                                 /*69*/ MatGetRowMaxAbs_MPIBAIJ,
    2778:                                        0,
    2779:                                        0,
    2780:                                        0,
    2781:                                        0,
    2782:                                 /*74*/ 0,
    2783:                                        MatFDColoringApply_BAIJ,
    2784:                                        0,
    2785:                                        0,
    2786:                                        0,
    2787:                                 /*79*/ 0,
    2788:                                        0,
    2789:                                        0,
    2790:                                        0,
    2791:                                        MatLoad_MPIBAIJ,
    2792:                                 /*84*/ 0,
    2793:                                        0,
    2794:                                        0,
    2795:                                        0,
    2796:                                        0,
    2797:                                 /*89*/ 0,
    2798:                                        0,
    2799:                                        0,
    2800:                                        0,
    2801:                                        0,
    2802:                                 /*94*/ 0,
    2803:                                        0,
    2804:                                        0,
    2805:                                        0,
    2806:                                        0,
    2807:                                 /*99*/ 0,
    2808:                                        0,
    2809:                                        0,
    2810:                                        0,
    2811:                                        0,
    2812:                                 /*104*/0,
    2813:                                        MatRealPart_MPIBAIJ,
    2814:                                        MatImaginaryPart_MPIBAIJ,
    2815:                                        0,
    2816:                                        0,
    2817:                                 /*109*/0,
    2818:                                        0,
    2819:                                        0,
    2820:                                        0,
    2821:                                        MatMissingDiagonal_MPIBAIJ,
    2822:                                 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ,
    2823:                                        0,
    2824:                                        MatGetGhosts_MPIBAIJ,
    2825:                                        0,
    2826:                                        0,
    2827:                                 /*119*/0,
    2828:                                        0,
    2829:                                        0,
    2830:                                        0,
    2831:                                        MatGetMultiProcBlock_MPIBAIJ,
    2832:                                 /*124*/0,
    2833:                                        MatGetColumnNorms_MPIBAIJ,
    2834:                                        MatInvertBlockDiagonal_MPIBAIJ,
    2835:                                        0,
    2836:                                        0,
    2837:                                /*129*/ 0,
    2838:                                        0,
    2839:                                        0,
    2840:                                        0,
    2841:                                        0,
    2842:                                /*134*/ 0,
    2843:                                        0,
    2844:                                        0,
    2845:                                        0,
    2846:                                        0,
    2847:                                /*139*/ 0,
    2848:                                        0,
    2849:                                        0,
    2850:                                        MatFDColoringSetUp_MPIXAIJ,
    2851:                                        0,
    2852:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIBAIJ
    2853: };

    2857: PetscErrorCode  MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a)
    2858: {
    2860:   *a = ((Mat_MPIBAIJ*)A->data)->A;
    2861:   return(0);
    2862: }

    2864: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*);

    2868: PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
    2869: {
    2870:   PetscInt       m,rstart,cstart,cend;
    2871:   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
    2872:   const PetscInt *JJ    =0;
    2873:   PetscScalar    *values=0;
    2874:   PetscBool      roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented;

    2878:   PetscLayoutSetBlockSize(B->rmap,bs);
    2879:   PetscLayoutSetBlockSize(B->cmap,bs);
    2880:   PetscLayoutSetUp(B->rmap);
    2881:   PetscLayoutSetUp(B->cmap);
    2882:   PetscLayoutGetBlockSize(B->rmap,&bs);
    2883:   m      = B->rmap->n/bs;
    2884:   rstart = B->rmap->rstart/bs;
    2885:   cstart = B->cmap->rstart/bs;
    2886:   cend   = B->cmap->rend/bs;

    2888:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
    2889:   PetscMalloc2(m,&d_nnz,m,&o_nnz);
    2890:   for (i=0; i<m; i++) {
    2891:     nz = ii[i+1] - ii[i];
    2892:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
    2893:     nz_max = PetscMax(nz_max,nz);
    2894:     JJ     = jj + ii[i];
    2895:     for (j=0; j<nz; j++) {
    2896:       if (*JJ >= cstart) break;
    2897:       JJ++;
    2898:     }
    2899:     d = 0;
    2900:     for (; j<nz; j++) {
    2901:       if (*JJ++ >= cend) break;
    2902:       d++;
    2903:     }
    2904:     d_nnz[i] = d;
    2905:     o_nnz[i] = nz - d;
    2906:   }
    2907:   MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
    2908:   PetscFree2(d_nnz,o_nnz);

    2910:   values = (PetscScalar*)V;
    2911:   if (!values) {
    2912:     PetscMalloc1(bs*bs*nz_max,&values);
    2913:     PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));
    2914:   }
    2915:   for (i=0; i<m; i++) {
    2916:     PetscInt          row    = i + rstart;
    2917:     PetscInt          ncols  = ii[i+1] - ii[i];
    2918:     const PetscInt    *icols = jj + ii[i];
    2919:     if (!roworiented) {         /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */
    2920:       const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
    2921:       MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
    2922:     } else {                    /* block ordering does not match so we can only insert one block at a time. */
    2923:       PetscInt j;
    2924:       for (j=0; j<ncols; j++) {
    2925:         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
    2926:         MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);
    2927:       }
    2928:     }
    2929:   }

    2931:   if (!V) { PetscFree(values); }
    2932:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    2933:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    2934:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    2935:   return(0);
    2936: }

    2940: /*@C
    2941:    MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
    2942:    (the default parallel PETSc format).

    2944:    Collective on MPI_Comm

    2946:    Input Parameters:
    2947: +  B - the matrix
    2948: .  bs - the block size
    2949: .  i - the indices into j for the start of each local row (starts with zero)
    2950: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
    2951: -  v - optional values in the matrix

    2953:    Level: developer

    2955:    Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED.  For example, C programs
    2956:    may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is
    2957:    over rows within a block and the last index is over columns within a block row.  Fortran programs will likely set
    2958:    MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
    2959:    block column and the second index is over columns within a block.

    2961: .keywords: matrix, aij, compressed row, sparse, parallel

    2963: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ
    2964: @*/
    2965: PetscErrorCode  MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
    2966: {

    2973:   PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
    2974:   return(0);
    2975: }

    2979: PetscErrorCode  MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
    2980: {
    2981:   Mat_MPIBAIJ    *b;
    2983:   PetscInt       i;

    2986:   MatSetBlockSize(B,PetscAbs(bs));
    2987:   PetscLayoutSetUp(B->rmap);
    2988:   PetscLayoutSetUp(B->cmap);
    2989:   PetscLayoutGetBlockSize(B->rmap,&bs);

    2991:   if (d_nnz) {
    2992:     for (i=0; i<B->rmap->n/bs; i++) {
    2993:       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]);
    2994:     }
    2995:   }
    2996:   if (o_nnz) {
    2997:     for (i=0; i<B->rmap->n/bs; i++) {
    2998:       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]);
    2999:     }
    3000:   }

    3002:   b      = (Mat_MPIBAIJ*)B->data;
    3003:   b->bs2 = bs*bs;
    3004:   b->mbs = B->rmap->n/bs;
    3005:   b->nbs = B->cmap->n/bs;
    3006:   b->Mbs = B->rmap->N/bs;
    3007:   b->Nbs = B->cmap->N/bs;

    3009:   for (i=0; i<=b->size; i++) {
    3010:     b->rangebs[i] = B->rmap->range[i]/bs;
    3011:   }
    3012:   b->rstartbs = B->rmap->rstart/bs;
    3013:   b->rendbs   = B->rmap->rend/bs;
    3014:   b->cstartbs = B->cmap->rstart/bs;
    3015:   b->cendbs   = B->cmap->rend/bs;

    3017:   if (!B->preallocated) {
    3018:     MatCreate(PETSC_COMM_SELF,&b->A);
    3019:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
    3020:     MatSetType(b->A,MATSEQBAIJ);
    3021:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
    3022:     MatCreate(PETSC_COMM_SELF,&b->B);
    3023:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
    3024:     MatSetType(b->B,MATSEQBAIJ);
    3025:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
    3026:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
    3027:   }

    3029:   MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
    3030:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);
    3031:   B->preallocated = PETSC_TRUE;
    3032:   return(0);
    3033: }

    3035: extern PetscErrorCode  MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec);
    3036: extern PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal);

    3040: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj)
    3041: {
    3042:   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;
    3044:   Mat_SeqBAIJ    *d  = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data;
    3045:   PetscInt       M   = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs;
    3046:   const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray;

    3049:   PetscMalloc1(M+1,&ii);
    3050:   ii[0] = 0;
    3051:   for (i=0; i<M; i++) {
    3052:     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]);
    3053:     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]);
    3054:     ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i];
    3055:     /* remove one from count of matrix has diagonal */
    3056:     for (j=id[i]; j<id[i+1]; j++) {
    3057:       if (jd[j] == i) {ii[i+1]--;break;}
    3058:     }
    3059:   }
    3060:   PetscMalloc1(ii[M],&jj);
    3061:   cnt  = 0;
    3062:   for (i=0; i<M; i++) {
    3063:     for (j=io[i]; j<io[i+1]; j++) {
    3064:       if (garray[jo[j]] > rstart) break;
    3065:       jj[cnt++] = garray[jo[j]];
    3066:     }
    3067:     for (k=id[i]; k<id[i+1]; k++) {
    3068:       if (jd[k] != i) {
    3069:         jj[cnt++] = rstart + jd[k];
    3070:       }
    3071:     }
    3072:     for (; j<io[i+1]; j++) {
    3073:       jj[cnt++] = garray[jo[j]];
    3074:     }
    3075:   }
    3076:   MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);
    3077:   return(0);
    3078: }

    3080: #include <../src/mat/impls/aij/mpi/mpiaij.h>

    3082: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*);

    3086: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
    3087: {
    3089:   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
    3090:   Mat            B;
    3091:   Mat_MPIAIJ     *b;

    3094:   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");

    3096:   MatCreate(PetscObjectComm((PetscObject)A),&B);
    3097:   MatSetType(B,MATMPIAIJ);
    3098:   MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    3099:   MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);
    3100:   MatSeqAIJSetPreallocation(B,0,NULL);
    3101:   MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);
    3102:   b    = (Mat_MPIAIJ*) B->data;

    3104:   MatDestroy(&b->A);
    3105:   MatDestroy(&b->B);
    3106:   MatDisAssemble_MPIBAIJ(A);
    3107:   MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);
    3108:   MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);
    3109:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    3110:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    3111:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    3112:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    3113:   if (reuse == MAT_INPLACE_MATRIX) {
    3114:     MatHeaderReplace(A,&B);
    3115:   } else {
    3116:    *newmat = B;
    3117:   }
    3118:   return(0);
    3119: }

    3121: /*MC
    3122:    MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices.

    3124:    Options Database Keys:
    3125: + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions()
    3126: . -mat_block_size <bs> - set the blocksize used to store the matrix
    3127: - -mat_use_hash_table <fact>

    3129:   Level: beginner

    3131: .seealso: MatCreateMPIBAIJ
    3132: M*/

    3134: PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*);

    3138: PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B)
    3139: {
    3140:   Mat_MPIBAIJ    *b;
    3142:   PetscBool      flg = PETSC_FALSE;

    3145:   PetscNewLog(B,&b);
    3146:   B->data = (void*)b;

    3148:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
    3149:   B->assembled = PETSC_FALSE;

    3151:   B->insertmode = NOT_SET_VALUES;
    3152:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
    3153:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

    3155:   /* build local table of row and column ownerships */
    3156:   PetscMalloc1(b->size+1,&b->rangebs);

    3158:   /* build cache for off array entries formed */
    3159:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

    3161:   b->donotstash  = PETSC_FALSE;
    3162:   b->colmap      = NULL;
    3163:   b->garray      = NULL;
    3164:   b->roworiented = PETSC_TRUE;

    3166:   /* stuff used in block assembly */
    3167:   b->barray = 0;

    3169:   /* stuff used for matrix vector multiply */
    3170:   b->lvec  = 0;
    3171:   b->Mvctx = 0;

    3173:   /* stuff for MatGetRow() */
    3174:   b->rowindices   = 0;
    3175:   b->rowvalues    = 0;
    3176:   b->getrowactive = PETSC_FALSE;

    3178:   /* hash table stuff */
    3179:   b->ht           = 0;
    3180:   b->hd           = 0;
    3181:   b->ht_size      = 0;
    3182:   b->ht_flag      = PETSC_FALSE;
    3183:   b->ht_fact      = 0;
    3184:   b->ht_total_ct  = 0;
    3185:   b->ht_insert_ct = 0;

    3187:   /* stuff for MatGetSubMatrices_MPIBAIJ_local() */
    3188:   b->ijonly = PETSC_FALSE;

    3191:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);
    3192:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);
    3193:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);
    3194:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);
    3195:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);
    3196:   PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);
    3197:   PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);
    3198:   PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);
    3199:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);
    3200:   PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);
    3201:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);
    3202:   PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);

    3204:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");
    3205:   PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);
    3206:   if (flg) {
    3207:     PetscReal fact = 1.39;
    3208:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
    3209:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
    3210:     if (fact <= 1.0) fact = 1.39;
    3211:     MatMPIBAIJSetHashTableFactor(B,fact);
    3212:     PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
    3213:   }
    3214:   PetscOptionsEnd();
    3215:   return(0);
    3216: }

    3218: /*MC
    3219:    MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices.

    3221:    This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator,
    3222:    and MATMPIBAIJ otherwise.

    3224:    Options Database Keys:
    3225: . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions()

    3227:   Level: beginner

    3229: .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
    3230: M*/

    3234: /*@C
    3235:    MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format
    3236:    (block compressed row).  For good matrix assembly performance
    3237:    the user should preallocate the matrix storage by setting the parameters
    3238:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    3239:    performance can be increased by more than a factor of 50.

    3241:    Collective on Mat

    3243:    Input Parameters:
    3244: +  B - the matrix
    3245: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    3246:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    3247: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
    3248:            submatrix  (same for all local rows)
    3249: .  d_nnz - array containing the number of block nonzeros in the various block rows
    3250:            of the in diagonal portion of the local (possibly different for each block
    3251:            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry and
    3252:            set it even if it is zero.
    3253: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
    3254:            submatrix (same for all local rows).
    3255: -  o_nnz - array containing the number of nonzeros in the various block rows of the
    3256:            off-diagonal portion of the local submatrix (possibly different for
    3257:            each block row) or NULL.

    3259:    If the *_nnz parameter is given then the *_nz parameter is ignored

    3261:    Options Database Keys:
    3262: +   -mat_block_size - size of the blocks to use
    3263: -   -mat_use_hash_table <fact>

    3265:    Notes:
    3266:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
    3267:    than it must be used on all processors that share the object for that argument.

    3269:    Storage Information:
    3270:    For a square global matrix we define each processor's diagonal portion
    3271:    to be its local rows and the corresponding columns (a square submatrix);
    3272:    each processor's off-diagonal portion encompasses the remainder of the
    3273:    local matrix (a rectangular submatrix).

    3275:    The user can specify preallocated storage for the diagonal part of
    3276:    the local submatrix with either d_nz or d_nnz (not both).  Set
    3277:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
    3278:    memory allocation.  Likewise, specify preallocated storage for the
    3279:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

    3281:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
    3282:    the figure below we depict these three local rows and all columns (0-11).

    3284: .vb
    3285:            0 1 2 3 4 5 6 7 8 9 10 11
    3286:           --------------------------
    3287:    row 3  |o o o d d d o o o o  o  o
    3288:    row 4  |o o o d d d o o o o  o  o
    3289:    row 5  |o o o d d d o o o o  o  o
    3290:           --------------------------
    3291: .ve

    3293:    Thus, any entries in the d locations are stored in the d (diagonal)
    3294:    submatrix, and any entries in the o locations are stored in the
    3295:    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
    3296:    stored simply in the MATSEQBAIJ format for compressed row storage.

    3298:    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
    3299:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
    3300:    In general, for PDE problems in which most nonzeros are near the diagonal,
    3301:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
    3302:    or you will get TERRIBLE performance; see the users' manual chapter on
    3303:    matrices.

    3305:    You can call MatGetInfo() to get information on how effective the preallocation was;
    3306:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
    3307:    You can also run with the option -info and look for messages with the string
    3308:    malloc in them to see if additional memory allocation was needed.

    3310:    Level: intermediate

    3312: .keywords: matrix, block, aij, compressed row, sparse, parallel

    3314: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership()
    3315: @*/
    3316: PetscErrorCode  MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
    3317: {

    3324:   PetscTryMethod(B,"MatMPIBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
    3325:   return(0);
    3326: }

    3330: /*@C
    3331:    MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format
    3332:    (block compressed row).  For good matrix assembly performance
    3333:    the user should preallocate the matrix storage by setting the parameters
    3334:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    3335:    performance can be increased by more than a factor of 50.

    3337:    Collective on MPI_Comm

    3339:    Input Parameters:
    3340: +  comm - MPI communicator
    3341: .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
    3342:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
    3343: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
    3344:            This value should be the same as the local size used in creating the
    3345:            y vector for the matrix-vector product y = Ax.
    3346: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
    3347:            This value should be the same as the local size used in creating the
    3348:            x vector for the matrix-vector product y = Ax.
    3349: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    3350: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    3351: .  d_nz  - number of nonzero blocks per block row in diagonal portion of local
    3352:            submatrix  (same for all local rows)
    3353: .  d_nnz - array containing the number of nonzero blocks in the various block rows
    3354:            of the in diagonal portion of the local (possibly different for each block
    3355:            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry
    3356:            and set it even if it is zero.
    3357: .  o_nz  - number of nonzero blocks per block row in the off-diagonal portion of local
    3358:            submatrix (same for all local rows).
    3359: -  o_nnz - array containing the number of nonzero blocks in the various block rows of the
    3360:            off-diagonal portion of the local submatrix (possibly different for
    3361:            each block row) or NULL.

    3363:    Output Parameter:
    3364: .  A - the matrix

    3366:    Options Database Keys:
    3367: +   -mat_block_size - size of the blocks to use
    3368: -   -mat_use_hash_table <fact>

    3370:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
    3371:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
    3372:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

    3374:    Notes:
    3375:    If the *_nnz parameter is given then the *_nz parameter is ignored

    3377:    A nonzero block is any block that as 1 or more nonzeros in it

    3379:    The user MUST specify either the local or global matrix dimensions
    3380:    (possibly both).

    3382:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
    3383:    than it must be used on all processors that share the object for that argument.

    3385:    Storage Information:
    3386:    For a square global matrix we define each processor's diagonal portion
    3387:    to be its local rows and the corresponding columns (a square submatrix);
    3388:    each processor's off-diagonal portion encompasses the remainder of the
    3389:    local matrix (a rectangular submatrix).

    3391:    The user can specify preallocated storage for the diagonal part of
    3392:    the local submatrix with either d_nz or d_nnz (not both).  Set
    3393:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
    3394:    memory allocation.  Likewise, specify preallocated storage for the
    3395:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

    3397:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
    3398:    the figure below we depict these three local rows and all columns (0-11).

    3400: .vb
    3401:            0 1 2 3 4 5 6 7 8 9 10 11
    3402:           --------------------------
    3403:    row 3  |o o o d d d o o o o  o  o
    3404:    row 4  |o o o d d d o o o o  o  o
    3405:    row 5  |o o o d d d o o o o  o  o
    3406:           --------------------------
    3407: .ve

    3409:    Thus, any entries in the d locations are stored in the d (diagonal)
    3410:    submatrix, and any entries in the o locations are stored in the
    3411:    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
    3412:    stored simply in the MATSEQBAIJ format for compressed row storage.

    3414:    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
    3415:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
    3416:    In general, for PDE problems in which most nonzeros are near the diagonal,
    3417:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
    3418:    or you will get TERRIBLE performance; see the users' manual chapter on
    3419:    matrices.

    3421:    Level: intermediate

    3423: .keywords: matrix, block, aij, compressed row, sparse, parallel

    3425: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
    3426: @*/
    3427: 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)
    3428: {
    3430:   PetscMPIInt    size;

    3433:   MatCreate(comm,A);
    3434:   MatSetSizes(*A,m,n,M,N);
    3435:   MPI_Comm_size(comm,&size);
    3436:   if (size > 1) {
    3437:     MatSetType(*A,MATMPIBAIJ);
    3438:     MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
    3439:   } else {
    3440:     MatSetType(*A,MATSEQBAIJ);
    3441:     MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
    3442:   }
    3443:   return(0);
    3444: }

    3448: static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
    3449: {
    3450:   Mat            mat;
    3451:   Mat_MPIBAIJ    *a,*oldmat = (Mat_MPIBAIJ*)matin->data;
    3453:   PetscInt       len=0;

    3456:   *newmat = 0;
    3457:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
    3458:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
    3459:   MatSetType(mat,((PetscObject)matin)->type_name);
    3460:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));

    3462:   mat->factortype   = matin->factortype;
    3463:   mat->preallocated = PETSC_TRUE;
    3464:   mat->assembled    = PETSC_TRUE;
    3465:   mat->insertmode   = NOT_SET_VALUES;

    3467:   a             = (Mat_MPIBAIJ*)mat->data;
    3468:   mat->rmap->bs = matin->rmap->bs;
    3469:   a->bs2        = oldmat->bs2;
    3470:   a->mbs        = oldmat->mbs;
    3471:   a->nbs        = oldmat->nbs;
    3472:   a->Mbs        = oldmat->Mbs;
    3473:   a->Nbs        = oldmat->Nbs;

    3475:   PetscLayoutReference(matin->rmap,&mat->rmap);
    3476:   PetscLayoutReference(matin->cmap,&mat->cmap);

    3478:   a->size         = oldmat->size;
    3479:   a->rank         = oldmat->rank;
    3480:   a->donotstash   = oldmat->donotstash;
    3481:   a->roworiented  = oldmat->roworiented;
    3482:   a->rowindices   = 0;
    3483:   a->rowvalues    = 0;
    3484:   a->getrowactive = PETSC_FALSE;
    3485:   a->barray       = 0;
    3486:   a->rstartbs     = oldmat->rstartbs;
    3487:   a->rendbs       = oldmat->rendbs;
    3488:   a->cstartbs     = oldmat->cstartbs;
    3489:   a->cendbs       = oldmat->cendbs;

    3491:   /* hash table stuff */
    3492:   a->ht           = 0;
    3493:   a->hd           = 0;
    3494:   a->ht_size      = 0;
    3495:   a->ht_flag      = oldmat->ht_flag;
    3496:   a->ht_fact      = oldmat->ht_fact;
    3497:   a->ht_total_ct  = 0;
    3498:   a->ht_insert_ct = 0;

    3500:   PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));
    3501:   if (oldmat->colmap) {
    3502: #if defined(PETSC_USE_CTABLE)
    3503:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
    3504: #else
    3505:     PetscMalloc1(a->Nbs,&a->colmap);
    3506:     PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
    3507:     PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));
    3508: #endif
    3509:   } else a->colmap = 0;

    3511:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
    3512:     PetscMalloc1(len,&a->garray);
    3513:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
    3514:     PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));
    3515:   } else a->garray = 0;

    3517:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
    3518:   VecDuplicate(oldmat->lvec,&a->lvec);
    3519:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
    3520:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
    3521:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);

    3523:   MatDuplicate(oldmat->A,cpvalues,&a->A);
    3524:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
    3525:   MatDuplicate(oldmat->B,cpvalues,&a->B);
    3526:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
    3527:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
    3528:   *newmat = mat;
    3529:   return(0);
    3530: }

    3534: PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer)
    3535: {
    3537:   int            fd;
    3538:   PetscInt       i,nz,j,rstart,rend;
    3539:   PetscScalar    *vals,*buf;
    3540:   MPI_Comm       comm;
    3541:   MPI_Status     status;
    3542:   PetscMPIInt    rank,size,maxnz;
    3543:   PetscInt       header[4],*rowlengths = 0,M,N,m,*rowners,*cols;
    3544:   PetscInt       *locrowlens = NULL,*procsnz = NULL,*browners = NULL;
    3545:   PetscInt       jj,*mycols,*ibuf,bs = newmat->rmap->bs,Mbs,mbs,extra_rows,mmax;
    3546:   PetscMPIInt    tag    = ((PetscObject)viewer)->tag;
    3547:   PetscInt       *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount;
    3548:   PetscInt       dcount,kmax,k,nzcount,tmp,mend;

    3551:   /* force binary viewer to load .info file if it has not yet done so */
    3552:   PetscViewerSetUp(viewer);
    3553:   PetscObjectGetComm((PetscObject)viewer,&comm);
    3554:   PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");
    3555:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
    3556:   PetscOptionsEnd();
    3557:   if (bs < 0) bs = 1;

    3559:   MPI_Comm_size(comm,&size);
    3560:   MPI_Comm_rank(comm,&rank);
    3561:   PetscViewerBinaryGetDescriptor(viewer,&fd);
    3562:   if (!rank) {
    3563:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
    3564:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
    3565:     if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newmat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk, cannot load as MPIAIJ");
    3566:   }
    3567:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
    3568:   M    = header[1]; N = header[2];

    3570:   /* If global sizes are set, check if they are consistent with that given in the file */
    3571:   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);
    3572:   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);

    3574:   if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices");

    3576:   /*
    3577:      This code adds extra rows to make sure the number of rows is
    3578:      divisible by the blocksize
    3579:   */
    3580:   Mbs        = M/bs;
    3581:   extra_rows = bs - M + bs*Mbs;
    3582:   if (extra_rows == bs) extra_rows = 0;
    3583:   else                  Mbs++;
    3584:   if (extra_rows && !rank) {
    3585:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
    3586:   }

    3588:   /* determine ownership of all rows */
    3589:   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
    3590:     mbs = Mbs/size + ((Mbs % size) > rank);
    3591:     m   = mbs*bs;
    3592:   } else { /* User set */
    3593:     m   = newmat->rmap->n;
    3594:     mbs = m/bs;
    3595:   }
    3596:   PetscMalloc2(size+1,&rowners,size+1,&browners);
    3597:   MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);

    3599:   /* process 0 needs enough room for process with most rows */
    3600:   if (!rank) {
    3601:     mmax = rowners[1];
    3602:     for (i=2; i<=size; i++) {
    3603:       mmax = PetscMax(mmax,rowners[i]);
    3604:     }
    3605:     mmax*=bs;
    3606:   } else mmax = -1;             /* unused, but compiler warns anyway */

    3608:   rowners[0] = 0;
    3609:   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
    3610:   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
    3611:   rstart = rowners[rank];
    3612:   rend   = rowners[rank+1];

    3614:   /* distribute row lengths to all processors */
    3615:   PetscMalloc1(m,&locrowlens);
    3616:   if (!rank) {
    3617:     mend = m;
    3618:     if (size == 1) mend = mend - extra_rows;
    3619:     PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);
    3620:     for (j=mend; j<m; j++) locrowlens[j] = 1;
    3621:     PetscMalloc1(mmax,&rowlengths);
    3622:     PetscCalloc1(size,&procsnz);
    3623:     for (j=0; j<m; j++) {
    3624:       procsnz[0] += locrowlens[j];
    3625:     }
    3626:     for (i=1; i<size; i++) {
    3627:       mend = browners[i+1] - browners[i];
    3628:       if (i == size-1) mend = mend - extra_rows;
    3629:       PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);
    3630:       for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1;
    3631:       /* calculate the number of nonzeros on each processor */
    3632:       for (j=0; j<browners[i+1]-browners[i]; j++) {
    3633:         procsnz[i] += rowlengths[j];
    3634:       }
    3635:       MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);
    3636:     }
    3637:     PetscFree(rowlengths);
    3638:   } else {
    3639:     MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);
    3640:   }

    3642:   if (!rank) {
    3643:     /* determine max buffer needed and allocate it */
    3644:     maxnz = procsnz[0];
    3645:     for (i=1; i<size; i++) {
    3646:       maxnz = PetscMax(maxnz,procsnz[i]);
    3647:     }
    3648:     PetscMalloc1(maxnz,&cols);

    3650:     /* read in my part of the matrix column indices  */
    3651:     nz     = procsnz[0];
    3652:     PetscMalloc1(nz+1,&ibuf);
    3653:     mycols = ibuf;
    3654:     if (size == 1) nz -= extra_rows;
    3655:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);
    3656:     if (size == 1) {
    3657:       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
    3658:     }

    3660:     /* read in every ones (except the last) and ship off */
    3661:     for (i=1; i<size-1; i++) {
    3662:       nz   = procsnz[i];
    3663:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
    3664:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
    3665:     }
    3666:     /* read in the stuff for the last proc */
    3667:     if (size != 1) {
    3668:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
    3669:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
    3670:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
    3671:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
    3672:     }
    3673:     PetscFree(cols);
    3674:   } else {
    3675:     /* determine buffer space needed for message */
    3676:     nz = 0;
    3677:     for (i=0; i<m; i++) {
    3678:       nz += locrowlens[i];
    3679:     }
    3680:     PetscMalloc1(nz+1,&ibuf);
    3681:     mycols = ibuf;
    3682:     /* receive message of column indices*/
    3683:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
    3684:     MPI_Get_count(&status,MPIU_INT,&maxnz);
    3685:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
    3686:   }

    3688:   /* loop over local rows, determining number of off diagonal entries */
    3689:   PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);
    3690:   PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);
    3691:   rowcount = 0; nzcount = 0;
    3692:   for (i=0; i<mbs; i++) {
    3693:     dcount  = 0;
    3694:     odcount = 0;
    3695:     for (j=0; j<bs; j++) {
    3696:       kmax = locrowlens[rowcount];
    3697:       for (k=0; k<kmax; k++) {
    3698:         tmp = mycols[nzcount++]/bs;
    3699:         if (!mask[tmp]) {
    3700:           mask[tmp] = 1;
    3701:           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp;
    3702:           else masked1[dcount++] = tmp;
    3703:         }
    3704:       }
    3705:       rowcount++;
    3706:     }

    3708:     dlens[i]  = dcount;
    3709:     odlens[i] = odcount;

    3711:     /* zero out the mask elements we set */
    3712:     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
    3713:     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
    3714:   }

    3716:   MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
    3717:   MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);

    3719:   if (!rank) {
    3720:     PetscMalloc1(maxnz+1,&buf);
    3721:     /* read in my part of the matrix numerical values  */
    3722:     nz     = procsnz[0];
    3723:     vals   = buf;
    3724:     mycols = ibuf;
    3725:     if (size == 1) nz -= extra_rows;
    3726:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    3727:     if (size == 1) {
    3728:       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
    3729:     }

    3731:     /* insert into matrix */
    3732:     jj = rstart*bs;
    3733:     for (i=0; i<m; i++) {
    3734:       MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
    3735:       mycols += locrowlens[i];
    3736:       vals   += locrowlens[i];
    3737:       jj++;
    3738:     }
    3739:     /* read in other processors (except the last one) and ship out */
    3740:     for (i=1; i<size-1; i++) {
    3741:       nz   = procsnz[i];
    3742:       vals = buf;
    3743:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    3744:       MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
    3745:     }
    3746:     /* the last proc */
    3747:     if (size != 1) {
    3748:       nz   = procsnz[i] - extra_rows;
    3749:       vals = buf;
    3750:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    3751:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
    3752:       MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
    3753:     }
    3754:     PetscFree(procsnz);
    3755:   } else {
    3756:     /* receive numeric values */
    3757:     PetscMalloc1(nz+1,&buf);

    3759:     /* receive message of values*/
    3760:     vals   = buf;
    3761:     mycols = ibuf;
    3762:     MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);

    3764:     /* insert into matrix */
    3765:     jj = rstart*bs;
    3766:     for (i=0; i<m; i++) {
    3767:       MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
    3768:       mycols += locrowlens[i];
    3769:       vals   += locrowlens[i];
    3770:       jj++;
    3771:     }
    3772:   }
    3773:   PetscFree(locrowlens);
    3774:   PetscFree(buf);
    3775:   PetscFree(ibuf);
    3776:   PetscFree2(rowners,browners);
    3777:   PetscFree2(dlens,odlens);
    3778:   PetscFree3(mask,masked1,masked2);
    3779:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
    3780:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
    3781:   return(0);
    3782: }

    3786: /*@
    3787:    MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

    3789:    Input Parameters:
    3790: .  mat  - the matrix
    3791: .  fact - factor

    3793:    Not Collective, each process can use a different factor

    3795:    Level: advanced

    3797:   Notes:
    3798:    This can also be set by the command line option: -mat_use_hash_table <fact>

    3800: .keywords: matrix, hashtable, factor, HT

    3802: .seealso: MatSetOption()
    3803: @*/
    3804: PetscErrorCode  MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact)
    3805: {

    3809:   PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));
    3810:   return(0);
    3811: }

    3815: PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact)
    3816: {
    3817:   Mat_MPIBAIJ *baij;

    3820:   baij          = (Mat_MPIBAIJ*)mat->data;
    3821:   baij->ht_fact = fact;
    3822:   return(0);
    3823: }

    3827: PetscErrorCode  MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
    3828: {
    3829:   Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data;

    3832:   if (Ad)     *Ad     = a->A;
    3833:   if (Ao)     *Ao     = a->B;
    3834:   if (colmap) *colmap = a->garray;
    3835:   return(0);
    3836: }

    3838: /*
    3839:     Special version for direct calls from Fortran (to eliminate two function call overheads
    3840: */
    3841: #if defined(PETSC_HAVE_FORTRAN_CAPS)
    3842: #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED
    3843: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
    3844: #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked
    3845: #endif

    3849: /*@C
    3850:   MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked()

    3852:   Collective on Mat

    3854:   Input Parameters:
    3855: + mat - the matrix
    3856: . min - number of input rows
    3857: . im - input rows
    3858: . nin - number of input columns
    3859: . in - input columns
    3860: . v - numerical values input
    3861: - addvin - INSERT_VALUES or ADD_VALUES

    3863:   Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse.

    3865:   Level: advanced

    3867: .seealso:   MatSetValuesBlocked()
    3868: @*/
    3869: PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin)
    3870: {
    3871:   /* convert input arguments to C version */
    3872:   Mat        mat  = *matin;
    3873:   PetscInt   m    = *min, n = *nin;
    3874:   InsertMode addv = *addvin;

    3876:   Mat_MPIBAIJ     *baij = (Mat_MPIBAIJ*)mat->data;
    3877:   const MatScalar *value;
    3878:   MatScalar       *barray     = baij->barray;
    3879:   PetscBool       roworiented = baij->roworiented;
    3880:   PetscErrorCode  ierr;
    3881:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
    3882:   PetscInt        rend=baij->rendbs,cstart=baij->cstartbs,stepval;
    3883:   PetscInt        cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;

    3886:   /* tasks normally handled by MatSetValuesBlocked() */
    3887:   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
    3888: #if defined(PETSC_USE_DEBUG)
    3889:   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
    3890:   if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
    3891: #endif
    3892:   if (mat->assembled) {
    3893:     mat->was_assembled = PETSC_TRUE;
    3894:     mat->assembled     = PETSC_FALSE;
    3895:   }
    3896:   PetscLogEventBegin(MAT_SetValues,mat,0,0,0);

    3899:   if (!barray) {
    3900:     PetscMalloc1(bs2,&barray);
    3901:     baij->barray = barray;
    3902:   }

    3904:   if (roworiented) stepval = (n-1)*bs;
    3905:   else stepval = (m-1)*bs;

    3907:   for (i=0; i<m; i++) {
    3908:     if (im[i] < 0) continue;
    3909: #if defined(PETSC_USE_DEBUG)
    3910:     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);
    3911: #endif
    3912:     if (im[i] >= rstart && im[i] < rend) {
    3913:       row = im[i] - rstart;
    3914:       for (j=0; j<n; j++) {
    3915:         /* If NumCol = 1 then a copy is not required */
    3916:         if ((roworiented) && (n == 1)) {
    3917:           barray = (MatScalar*)v + i*bs2;
    3918:         } else if ((!roworiented) && (m == 1)) {
    3919:           barray = (MatScalar*)v + j*bs2;
    3920:         } else { /* Here a copy is required */
    3921:           if (roworiented) {
    3922:             value = v + i*(stepval+bs)*bs + j*bs;
    3923:           } else {
    3924:             value = v + j*(stepval+bs)*bs + i*bs;
    3925:           }
    3926:           for (ii=0; ii<bs; ii++,value+=stepval) {
    3927:             for (jj=0; jj<bs; jj++) {
    3928:               *barray++ = *value++;
    3929:             }
    3930:           }
    3931:           barray -=bs2;
    3932:         }

    3934:         if (in[j] >= cstart && in[j] < cend) {
    3935:           col  = in[j] - cstart;
    3936:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
    3937:         } else if (in[j] < 0) continue;
    3938: #if defined(PETSC_USE_DEBUG)
    3939:         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);
    3940: #endif
    3941:         else {
    3942:           if (mat->was_assembled) {
    3943:             if (!baij->colmap) {
    3944:               MatCreateColmap_MPIBAIJ_Private(mat);
    3945:             }

    3947: #if defined(PETSC_USE_DEBUG)
    3948: #if defined(PETSC_USE_CTABLE)
    3949:             { PetscInt data;
    3950:               PetscTableFind(baij->colmap,in[j]+1,&data);
    3951:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    3952:             }
    3953: #else
    3954:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    3955: #endif
    3956: #endif
    3957: #if defined(PETSC_USE_CTABLE)
    3958:             PetscTableFind(baij->colmap,in[j]+1,&col);
    3959:             col  = (col - 1)/bs;
    3960: #else
    3961:             col = (baij->colmap[in[j]] - 1)/bs;
    3962: #endif
    3963:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
    3964:               MatDisAssemble_MPIBAIJ(mat);
    3965:               col  =  in[j];
    3966:             }
    3967:           } else col = in[j];
    3968:           MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
    3969:         }
    3970:       }
    3971:     } else {
    3972:       if (!baij->donotstash) {
    3973:         if (roworiented) {
    3974:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    3975:         } else {
    3976:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    3977:         }
    3978:       }
    3979:     }
    3980:   }

    3982:   /* task normally handled by MatSetValuesBlocked() */
    3983:   PetscLogEventEnd(MAT_SetValues,mat,0,0,0);
    3984:   return(0);
    3985: }

    3989: /*@
    3990:      MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard
    3991:          CSR format the local rows.

    3993:    Collective on MPI_Comm

    3995:    Input Parameters:
    3996: +  comm - MPI communicator
    3997: .  bs - the block size, only a block size of 1 is supported
    3998: .  m - number of local rows (Cannot be PETSC_DECIDE)
    3999: .  n - This value should be the same as the local size used in creating the
    4000:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
    4001:        calculated if N is given) For square matrices n is almost always m.
    4002: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    4003: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    4004: .   i - row indices
    4005: .   j - column indices
    4006: -   a - matrix values

    4008:    Output Parameter:
    4009: .   mat - the matrix

    4011:    Level: intermediate

    4013:    Notes:
    4014:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
    4015:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
    4016:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

    4018:      The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is
    4019:      the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first
    4020:      block, followed by the second column of the first block etc etc.  That is, the blocks are contiguous in memory
    4021:      with column-major ordering within blocks.

    4023:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

    4025: .keywords: matrix, aij, compressed row, sparse, parallel

    4027: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
    4028:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
    4029: @*/
    4030: 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)
    4031: {

    4035:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
    4036:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
    4037:   MatCreate(comm,mat);
    4038:   MatSetSizes(*mat,m,n,M,N);
    4039:   MatSetType(*mat,MATMPISBAIJ);
    4040:   MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);
    4041:   MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);
    4042:   MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);
    4043:   return(0);
    4044: }

    4048: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
    4049: {
    4051:   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
    4052:   PetscInt       *indx;
    4053:   PetscScalar    *values;

    4056:   MatGetSize(inmat,&m,&N);
    4057:   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
    4058:     Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)inmat->data;
    4059:     PetscInt       *dnz,*onz,sum,mbs,Nbs;
    4060:     PetscInt       *bindx,rmax=a->rmax,j;
    4061:
    4062:     MatGetBlockSizes(inmat,&bs,&cbs);
    4063:     mbs = m/bs; Nbs = N/cbs;
    4064:     if (n == PETSC_DECIDE) {
    4065:       PetscSplitOwnership(comm,&n,&Nbs);
    4066:     }
    4067:     /* Check sum(n) = Nbs */
    4068:     MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
    4069:     if (sum != Nbs) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",Nbs);

    4071:     MPI_Scan(&mbs, &rstart,1,MPIU_INT,MPI_SUM,comm);
    4072:     rstart -= mbs;

    4074:     PetscMalloc1(rmax,&bindx);
    4075:     MatPreallocateInitialize(comm,mbs,n,dnz,onz);
    4076:     for (i=0; i<mbs; i++) {
    4077:       MatGetRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
    4078:       nnz = nnz/bs;
    4079:       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
    4080:       MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
    4081:       MatRestoreRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);
    4082:     }
    4083:     PetscFree(bindx);

    4085:     MatCreate(comm,outmat);
    4086:     MatSetSizes(*outmat,m,n*bs,PETSC_DETERMINE,PETSC_DETERMINE);
    4087:     MatSetBlockSizes(*outmat,bs,cbs);
    4088:     MatSetType(*outmat,MATMPIBAIJ);
    4089:     MatMPIBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
    4090:     MatPreallocateFinalize(dnz,onz);
    4091:   }
    4092:
    4093:   /* numeric phase */
    4094:   MatGetBlockSizes(inmat,&bs,&cbs);
    4095:   MatGetOwnershipRange(*outmat,&rstart,NULL);

    4097:   for (i=0; i<m; i++) {
    4098:     MatGetRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);
    4099:     Ii   = i + rstart;
    4100:     MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
    4101:     MatRestoreRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);
    4102:   }
    4103:   MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
    4104:   MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
    4105:   return(0);
    4106: }