Date: 2013-07-02T14:43:34+00:00

Actual source code: mpisbaij.c
petsc-3.4.2 2013-07-02

      2: #include <../src/mat/impls/baij/mpi/mpibaij.h>    /*I "petscmat.h" I*/
      3: #include <../src/mat/impls/sbaij/mpi/mpisbaij.h>
      4: #include <../src/mat/impls/sbaij/seq/sbaij.h>
      5: #include <petscblaslapack.h>

      7: extern PetscErrorCode MatSetUpMultiply_MPISBAIJ(Mat);
      8: extern PetscErrorCode MatSetUpMultiply_MPISBAIJ_2comm(Mat);
      9: extern PetscErrorCode MatDisAssemble_MPISBAIJ(Mat);
     10: extern PetscErrorCode MatIncreaseOverlap_MPISBAIJ(Mat,PetscInt,IS[],PetscInt);
     11: extern PetscErrorCode MatGetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []);
     12: extern PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []);
     13: extern PetscErrorCode MatSetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt [],PetscInt,const PetscInt [],const PetscScalar [],InsertMode);
     14: extern PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
     15: extern PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
     16: extern PetscErrorCode MatGetRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
     17: extern PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
     18: extern PetscErrorCode MatZeroRows_SeqSBAIJ(Mat,IS,PetscScalar*,Vec,Vec);
     19: extern PetscErrorCode MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar*,Vec,Vec);
     20: extern PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat,Vec,PetscInt[]);
     21: extern PetscErrorCode MatSOR_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec);

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

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

     38: PetscErrorCode  MatRetrieveValues_MPISBAIJ(Mat mat)
     39: {
     40:   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;

     44:   MatRetrieveValues(aij->A);
     45:   MatRetrieveValues(aij->B);
     46:   return(0);
     47: }

     49: #define  MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \
     50:   { \
     51:  \
     52:     brow = row/bs;  \
     53:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
     54:     rmax = aimax[brow]; nrow = ailen[brow]; \
     55:     bcol = col/bs; \
     56:     ridx = row % bs; cidx = col % bs; \
     57:     low  = 0; high = nrow; \
     58:     while (high-low > 3) { \
     59:       t = (low+high)/2; \
     60:       if (rp[t] > bcol) high = t; \
     61:       else              low  = t; \
     62:     } \
     63:     for (_i=low; _i<high; _i++) { \
     64:       if (rp[_i] > bcol) break; \
     65:       if (rp[_i] == bcol) { \
     66:         bap = ap + bs2*_i + bs*cidx + ridx; \
     67:         if (addv == ADD_VALUES) *bap += value;  \
     68:         else                    *bap  = value;  \
     69:         goto a_noinsert; \
     70:       } \
     71:     } \
     72:     if (a->nonew == 1) goto a_noinsert; \
     73:     if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
     74:     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
     75:     N = nrow++ - 1;  \
     76:     /* shift up all the later entries in this row */ \
     77:     for (ii=N; ii>=_i; ii--) { \
     78:       rp[ii+1] = rp[ii]; \
     79:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
     80:     } \
     81:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); }  \
     82:     rp[_i]                      = bcol;  \
     83:     ap[bs2*_i + bs*cidx + ridx] = value;  \
     84: a_noinsert:; \
     85:     ailen[brow] = nrow; \
     86:   }

     88: #define  MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \
     89:   { \
     90:     brow = row/bs;  \
     91:     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
     92:     rmax = bimax[brow]; nrow = bilen[brow]; \
     93:     bcol = col/bs; \
     94:     ridx = row % bs; cidx = col % bs; \
     95:     low  = 0; high = nrow; \
     96:     while (high-low > 3) { \
     97:       t = (low+high)/2; \
     98:       if (rp[t] > bcol) high = t; \
     99:       else              low  = t; \
    100:     } \
    101:     for (_i=low; _i<high; _i++) { \
    102:       if (rp[_i] > bcol) break; \
    103:       if (rp[_i] == bcol) { \
    104:         bap = ap + bs2*_i + bs*cidx + ridx; \
    105:         if (addv == ADD_VALUES) *bap += value;  \
    106:         else                    *bap  = value;  \
    107:         goto b_noinsert; \
    108:       } \
    109:     } \
    110:     if (b->nonew == 1) goto b_noinsert; \
    111:     if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
    112:     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
    113:     N = nrow++ - 1;  \
    114:     /* shift up all the later entries in this row */ \
    115:     for (ii=N; ii>=_i; ii--) { \
    116:       rp[ii+1] = rp[ii]; \
    117:       PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
    118:     } \
    119:     if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));}  \
    120:     rp[_i]                      = bcol;  \
    121:     ap[bs2*_i + bs*cidx + ridx] = value;  \
    122: b_noinsert:; \
    123:     bilen[brow] = nrow; \
    124:   }

    126: /* Only add/insert a(i,j) with i<=j (blocks).
    127:    Any a(i,j) with i>j input by user is ingored.
    128: */
    131: PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
    132: {
    133:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    134:   MatScalar      value;
    135:   PetscBool      roworiented = baij->roworiented;
    137:   PetscInt       i,j,row,col;
    138:   PetscInt       rstart_orig=mat->rmap->rstart;
    139:   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
    140:   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;

    142:   /* Some Variables required in the macro */
    143:   Mat          A     = baij->A;
    144:   Mat_SeqSBAIJ *a    = (Mat_SeqSBAIJ*)(A)->data;
    145:   PetscInt     *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
    146:   MatScalar    *aa   =a->a;

    148:   Mat         B     = baij->B;
    149:   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
    150:   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
    151:   MatScalar   *ba   =b->a;

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

    157:   /* for stash */
    158:   PetscInt  n_loc, *in_loc = NULL;
    159:   MatScalar *v_loc = NULL;

    163:   if (!baij->donotstash) {
    164:     if (n > baij->n_loc) {
    165:       PetscFree(baij->in_loc);
    166:       PetscFree(baij->v_loc);
    167:       PetscMalloc(n*sizeof(PetscInt),&baij->in_loc);
    168:       PetscMalloc(n*sizeof(MatScalar),&baij->v_loc);

    170:       baij->n_loc = n;
    171:     }
    172:     in_loc = baij->in_loc;
    173:     v_loc  = baij->v_loc;
    174:   }

    176:   for (i=0; i<m; i++) {
    177:     if (im[i] < 0) continue;
    178: #if defined(PETSC_USE_DEBUG)
    179:     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);
    180: #endif
    181:     if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
    182:       row = im[i] - rstart_orig;              /* local row index */
    183:       for (j=0; j<n; j++) {
    184:         if (im[i]/bs > in[j]/bs) {
    185:           if (a->ignore_ltriangular) {
    186:             continue;    /* ignore lower triangular blocks */
    187:           } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
    188:         }
    189:         if (in[j] >= cstart_orig && in[j] < cend_orig) {  /* diag entry (A) */
    190:           col  = in[j] - cstart_orig;         /* local col index */
    191:           brow = row/bs; bcol = col/bs;
    192:           if (brow > bcol) continue;  /* ignore lower triangular blocks of A */
    193:           if (roworiented) value = v[i*n+j];
    194:           else             value = v[i+j*m];
    195:           MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv);
    196:           /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
    197:         } else if (in[j] < 0) continue;
    198: #if defined(PETSC_USE_DEBUG)
    199:         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);
    200: #endif
    201:         else {  /* off-diag entry (B) */
    202:           if (mat->was_assembled) {
    203:             if (!baij->colmap) {
    204:               MatCreateColmap_MPIBAIJ_Private(mat);
    205:             }
    206: #if defined(PETSC_USE_CTABLE)
    207:             PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
    208:             col  = col - 1;
    209: #else
    210:             col = baij->colmap[in[j]/bs] - 1;
    211: #endif
    212:             if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
    213:               MatDisAssemble_MPISBAIJ(mat);
    214:               col  =  in[j];
    215:               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
    216:               B    = baij->B;
    217:               b    = (Mat_SeqBAIJ*)(B)->data;
    218:               bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
    219:               ba   = b->a;
    220:             } else col += in[j]%bs;
    221:           } else col = in[j];
    222:           if (roworiented) value = v[i*n+j];
    223:           else             value = v[i+j*m];
    224:           MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv);
    225:           /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
    226:         }
    227:       }
    228:     } else {  /* off processor entry */
    229:       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]);
    230:       if (!baij->donotstash) {
    231:         mat->assembled = PETSC_FALSE;
    232:         n_loc          = 0;
    233:         for (j=0; j<n; j++) {
    234:           if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
    235:           in_loc[n_loc] = in[j];
    236:           if (roworiented) {
    237:             v_loc[n_loc] = v[i*n+j];
    238:           } else {
    239:             v_loc[n_loc] = v[j*m+i];
    240:           }
    241:           n_loc++;
    242:         }
    243:         MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
    244:       }
    245:     }
    246:   }
    247:   return(0);
    248: }

    252: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
    253: {
    254:   Mat_MPISBAIJ    *baij = (Mat_MPISBAIJ*)mat->data;
    255:   const MatScalar *value;
    256:   MatScalar       *barray     =baij->barray;
    257:   PetscBool       roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
    258:   PetscErrorCode  ierr;
    259:   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
    260:   PetscInt        rend=baij->rendbs,cstart=baij->rstartbs,stepval;
    261:   PetscInt        cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2;

    264:   if (!barray) {
    265:     PetscMalloc(bs2*sizeof(MatScalar),&barray);
    266:     baij->barray = barray;
    267:   }

    269:   if (roworiented) {
    270:     stepval = (n-1)*bs;
    271:   } else {
    272:     stepval = (m-1)*bs;
    273:   }
    274:   for (i=0; i<m; i++) {
    275:     if (im[i] < 0) continue;
    276: #if defined(PETSC_USE_DEBUG)
    277:     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);
    278: #endif
    279:     if (im[i] >= rstart && im[i] < rend) {
    280:       row = im[i] - rstart;
    281:       for (j=0; j<n; j++) {
    282:         if (im[i] > in[j]) {
    283:           if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
    284:           else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
    285:         }
    286:         /* If NumCol = 1 then a copy is not required */
    287:         if ((roworiented) && (n == 1)) {
    288:           barray = (MatScalar*) v + i*bs2;
    289:         } else if ((!roworiented) && (m == 1)) {
    290:           barray = (MatScalar*) v + j*bs2;
    291:         } else { /* Here a copy is required */
    292:           if (roworiented) {
    293:             value = v + i*(stepval+bs)*bs + j*bs;
    294:           } else {
    295:             value = v + j*(stepval+bs)*bs + i*bs;
    296:           }
    297:           for (ii=0; ii<bs; ii++,value+=stepval) {
    298:             for (jj=0; jj<bs; jj++) {
    299:               *barray++ = *value++;
    300:             }
    301:           }
    302:           barray -=bs2;
    303:         }

    305:         if (in[j] >= cstart && in[j] < cend) {
    306:           col  = in[j] - cstart;
    307:           MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);
    308:         } else if (in[j] < 0) continue;
    309: #if defined(PETSC_USE_DEBUG)
    310:         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);
    311: #endif
    312:         else {
    313:           if (mat->was_assembled) {
    314:             if (!baij->colmap) {
    315:               MatCreateColmap_MPIBAIJ_Private(mat);
    316:             }

    318: #if defined(PETSC_USE_DEBUG)
    319: #if defined(PETSC_USE_CTABLE)
    320:             { PetscInt data;
    321:               PetscTableFind(baij->colmap,in[j]+1,&data);
    322:               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    323:             }
    324: #else
    325:             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
    326: #endif
    327: #endif
    328: #if defined(PETSC_USE_CTABLE)
    329:             PetscTableFind(baij->colmap,in[j]+1,&col);
    330:             col  = (col - 1)/bs;
    331: #else
    332:             col = (baij->colmap[in[j]] - 1)/bs;
    333: #endif
    334:             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
    335:               MatDisAssemble_MPISBAIJ(mat);
    336:               col  = in[j];
    337:             }
    338:           } else col = in[j];
    339:           MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);
    340:         }
    341:       }
    342:     } else {
    343:       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]);
    344:       if (!baij->donotstash) {
    345:         if (roworiented) {
    346:           MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    347:         } else {
    348:           MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
    349:         }
    350:       }
    351:     }
    352:   }
    353:   return(0);
    354: }

    358: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
    359: {
    360:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    362:   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
    363:   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;

    366:   for (i=0; i<m; i++) {
    367:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */
    368:     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);
    369:     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
    370:       row = idxm[i] - bsrstart;
    371:       for (j=0; j<n; j++) {
    372:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */
    373:         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);
    374:         if (idxn[j] >= bscstart && idxn[j] < bscend) {
    375:           col  = idxn[j] - bscstart;
    376:           MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
    377:         } else {
    378:           if (!baij->colmap) {
    379:             MatCreateColmap_MPIBAIJ_Private(mat);
    380:           }
    381: #if defined(PETSC_USE_CTABLE)
    382:           PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
    383:           data--;
    384: #else
    385:           data = baij->colmap[idxn[j]/bs]-1;
    386: #endif
    387:           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
    388:           else {
    389:             col  = data + idxn[j]%bs;
    390:             MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
    391:           }
    392:         }
    393:       }
    394:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
    395:   }
    396:   return(0);
    397: }

    401: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
    402: {
    403:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    405:   PetscReal      sum[2],*lnorm2;

    408:   if (baij->size == 1) {
    409:      MatNorm(baij->A,type,norm);
    410:   } else {
    411:     if (type == NORM_FROBENIUS) {
    412:       PetscMalloc(2*sizeof(PetscReal),&lnorm2);
    413:        MatNorm(baij->A,type,lnorm2);
    414:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++;            /* squar power of norm(A) */
    415:        MatNorm(baij->B,type,lnorm2);
    416:       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--;             /* squar power of norm(B) */
    417:       MPI_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
    418:       *norm   = PetscSqrtReal(sum[0] + 2*sum[1]);
    419:       PetscFree(lnorm2);
    420:     } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
    421:       Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
    422:       Mat_SeqBAIJ  *bmat=(Mat_SeqBAIJ*)baij->B->data;
    423:       PetscReal    *rsum,*rsum2,vabs;
    424:       PetscInt     *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
    425:       PetscInt     brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs;
    426:       MatScalar    *v;

    428:       PetscMalloc2(mat->cmap->N,PetscReal,&rsum,mat->cmap->N,PetscReal,&rsum2);
    429:       PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));
    430:       /* Amat */
    431:       v = amat->a; jj = amat->j;
    432:       for (brow=0; brow<mbs; brow++) {
    433:         grow = bs*(rstart + brow);
    434:         nz   = amat->i[brow+1] - amat->i[brow];
    435:         for (bcol=0; bcol<nz; bcol++) {
    436:           gcol = bs*(rstart + *jj); jj++;
    437:           for (col=0; col<bs; col++) {
    438:             for (row=0; row<bs; row++) {
    439:               vabs            = PetscAbsScalar(*v); v++;
    440:               rsum[gcol+col] += vabs;
    441:               /* non-diagonal block */
    442:               if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
    443:             }
    444:           }
    445:         }
    446:       }
    447:       /* Bmat */
    448:       v = bmat->a; jj = bmat->j;
    449:       for (brow=0; brow<mbs; brow++) {
    450:         grow = bs*(rstart + brow);
    451:         nz = bmat->i[brow+1] - bmat->i[brow];
    452:         for (bcol=0; bcol<nz; bcol++) {
    453:           gcol = bs*garray[*jj]; jj++;
    454:           for (col=0; col<bs; col++) {
    455:             for (row=0; row<bs; row++) {
    456:               vabs            = PetscAbsScalar(*v); v++;
    457:               rsum[gcol+col] += vabs;
    458:               rsum[grow+row] += vabs;
    459:             }
    460:           }
    461:         }
    462:       }
    463:       MPI_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
    464:       *norm = 0.0;
    465:       for (col=0; col<mat->cmap->N; col++) {
    466:         if (rsum2[col] > *norm) *norm = rsum2[col];
    467:       }
    468:       PetscFree2(rsum,rsum2);
    469:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
    470:   }
    471:   return(0);
    472: }

    476: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
    477: {
    478:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    480:   PetscInt       nstash,reallocs;
    481:   InsertMode     addv;

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

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

    491:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
    492:   MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
    493:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
    494:   PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
    495:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
    496:   PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
    497:   return(0);
    498: }

    502: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
    503: {
    504:   Mat_MPISBAIJ   *baij=(Mat_MPISBAIJ*)mat->data;
    505:   Mat_SeqSBAIJ   *a   =(Mat_SeqSBAIJ*)baij->A->data;
    507:   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
    508:   PetscInt       *row,*col;
    509:   PetscBool      other_disassembled;
    510:   PetscMPIInt    n;
    511:   PetscBool      r1,r2,r3;
    512:   MatScalar      *val;
    513:   InsertMode     addv = mat->insertmode;

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

    522:       for (i=0; i<n;) {
    523:         /* Now identify the consecutive vals belonging to the same row */
    524:         for (j=i,rstart=row[j]; j<n; j++) {
    525:           if (row[j] != rstart) break;
    526:         }
    527:         if (j < n) ncols = j-i;
    528:         else       ncols = n-i;
    529:         /* Now assemble all these values with a single function call */
    530:         MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);
    531:         i    = j;
    532:       }
    533:     }
    534:     MatStashScatterEnd_Private(&mat->stash);
    535:     /* Now process the block-stash. Since the values are stashed column-oriented,
    536:        set the roworiented flag to column oriented, and after MatSetValues()
    537:        restore the original flags */
    538:     r1 = baij->roworiented;
    539:     r2 = a->roworiented;
    540:     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;

    542:     baij->roworiented = PETSC_FALSE;
    543:     a->roworiented    = PETSC_FALSE;

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

    550:       for (i=0; i<n;) {
    551:         /* Now identify the consecutive vals belonging to the same row */
    552:         for (j=i,rstart=row[j]; j<n; j++) {
    553:           if (row[j] != rstart) break;
    554:         }
    555:         if (j < n) ncols = j-i;
    556:         else       ncols = n-i;
    557:         MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);
    558:         i    = j;
    559:       }
    560:     }
    561:     MatStashScatterEnd_Private(&mat->bstash);

    563:     baij->roworiented = r1;
    564:     a->roworiented    = r2;

    566:     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
    567:   }

    569:   MatAssemblyBegin(baij->A,mode);
    570:   MatAssemblyEnd(baij->A,mode);

    572:   /* determine if any processor has disassembled, if so we must
    573:      also disassemble ourselfs, in order that we may reassemble. */
    574:   /*
    575:      if nonzero structure of submatrix B cannot change then we know that
    576:      no processor disassembled thus we can skip this stuff
    577:   */
    578:   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
    579:     MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
    580:     if (mat->was_assembled && !other_disassembled) {
    581:       MatDisAssemble_MPISBAIJ(mat);
    582:     }
    583:   }

    585:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
    586:     MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
    587:   }
    588:   MatSetOption(baij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_TRUE);
    589:   MatAssemblyBegin(baij->B,mode);
    590:   MatAssemblyEnd(baij->B,mode);

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

    594:   baij->rowvalues = 0;
    595:   return(0);
    596: }

    598: extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
    599: #include <petscdraw.h>
    602: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
    603: {
    604:   Mat_MPISBAIJ      *baij = (Mat_MPISBAIJ*)mat->data;
    605:   PetscErrorCode    ierr;
    606:   PetscInt          bs   = mat->rmap->bs;
    607:   PetscMPIInt       size = baij->size,rank = baij->rank;
    608:   PetscBool         iascii,isdraw;
    609:   PetscViewer       sviewer;
    610:   PetscViewerFormat format;

    613:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    614:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    615:   if (iascii) {
    616:     PetscViewerGetFormat(viewer,&format);
    617:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
    618:       MatInfo info;
    619:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
    620:       MatGetInfo(mat,MAT_LOCAL,&info);
    621:       PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);
    622:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);
    623:       MatGetInfo(baij->A,MAT_LOCAL,&info);
    624:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
    625:       MatGetInfo(baij->B,MAT_LOCAL,&info);
    626:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
    627:       PetscViewerFlush(viewer);
    628:       PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);
    629:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
    630:       VecScatterView(baij->Mvctx,viewer);
    631:       return(0);
    632:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
    633:       PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
    634:       return(0);
    635:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
    636:       return(0);
    637:     }
    638:   }

    640:   if (isdraw) {
    641:     PetscDraw draw;
    642:     PetscBool isnull;
    643:     PetscViewerDrawGetDraw(viewer,0,&draw);
    644:     PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
    645:   }

    647:   if (size == 1) {
    648:     PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);
    649:     MatView(baij->A,viewer);
    650:   } else {
    651:     /* assemble the entire matrix onto first processor. */
    652:     Mat          A;
    653:     Mat_SeqSBAIJ *Aloc;
    654:     Mat_SeqBAIJ  *Bloc;
    655:     PetscInt     M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
    656:     MatScalar    *a;

    658:     /* Should this be the same type as mat? */
    659:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
    660:     if (!rank) {
    661:       MatSetSizes(A,M,N,M,N);
    662:     } else {
    663:       MatSetSizes(A,0,0,M,N);
    664:     }
    665:     MatSetType(A,MATMPISBAIJ);
    666:     MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
    667:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
    668:     PetscLogObjectParent(mat,A);

    670:     /* copy over the A part */
    671:     Aloc = (Mat_SeqSBAIJ*)baij->A->data;
    672:     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
    673:     PetscMalloc(bs*sizeof(PetscInt),&rvals);

    675:     for (i=0; i<mbs; i++) {
    676:       rvals[0] = bs*(baij->rstartbs + i);
    677:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    678:       for (j=ai[i]; j<ai[i+1]; j++) {
    679:         col = (baij->cstartbs+aj[j])*bs;
    680:         for (k=0; k<bs; k++) {
    681:           MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
    682:           col++;
    683:           a += bs;
    684:         }
    685:       }
    686:     }
    687:     /* copy over the B part */
    688:     Bloc = (Mat_SeqBAIJ*)baij->B->data;
    689:     ai   = Bloc->i; aj = Bloc->j; a = Bloc->a;
    690:     for (i=0; i<mbs; i++) {

    692:       rvals[0] = bs*(baij->rstartbs + i);
    693:       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
    694:       for (j=ai[i]; j<ai[i+1]; j++) {
    695:         col = baij->garray[aj[j]]*bs;
    696:         for (k=0; k<bs; k++) {
    697:           MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
    698:           col++;
    699:           a += bs;
    700:         }
    701:       }
    702:     }
    703:     PetscFree(rvals);
    704:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    705:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    706:     /*
    707:        Everyone has to call to draw the matrix since the graphics waits are
    708:        synchronized across all processors that share the PetscDraw object
    709:     */
    710:     PetscViewerGetSingleton(viewer,&sviewer);
    711:     if (!rank) {
    712:       PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,((PetscObject)mat)->name);
    713:       /* Set the type name to MATMPISBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqSBAIJ_ASCII()*/
    714:       PetscStrcpy(((PetscObject)((Mat_MPISBAIJ*)(A->data))->A)->type_name,MATMPISBAIJ);
    715:       MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
    716:     }
    717:     PetscViewerRestoreSingleton(viewer,&sviewer);
    718:     MatDestroy(&A);
    719:   }
    720:   return(0);
    721: }

    725: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
    726: {
    728:   PetscBool      iascii,isdraw,issocket,isbinary;

    731:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    732:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    733:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
    734:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    735:   if (iascii || isdraw || issocket || isbinary) {
    736:     MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
    737:   }
    738:   return(0);
    739: }

    743: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
    744: {
    745:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;

    749: #if defined(PETSC_USE_LOG)
    750:   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
    751: #endif
    752:   MatStashDestroy_Private(&mat->stash);
    753:   MatStashDestroy_Private(&mat->bstash);
    754:   MatDestroy(&baij->A);
    755:   MatDestroy(&baij->B);
    756: #if defined(PETSC_USE_CTABLE)
    757:   PetscTableDestroy(&baij->colmap);
    758: #else
    759:   PetscFree(baij->colmap);
    760: #endif
    761:   PetscFree(baij->garray);
    762:   VecDestroy(&baij->lvec);
    763:   VecScatterDestroy(&baij->Mvctx);
    764:   VecDestroy(&baij->slvec0);
    765:   VecDestroy(&baij->slvec0b);
    766:   VecDestroy(&baij->slvec1);
    767:   VecDestroy(&baij->slvec1a);
    768:   VecDestroy(&baij->slvec1b);
    769:   VecScatterDestroy(&baij->sMvctx);
    770:   PetscFree2(baij->rowvalues,baij->rowindices);
    771:   PetscFree(baij->barray);
    772:   PetscFree(baij->hd);
    773:   VecDestroy(&baij->diag);
    774:   VecDestroy(&baij->bb1);
    775:   VecDestroy(&baij->xx1);
    776: #if defined(PETSC_USE_REAL_MAT_SINGLE)
    777:   PetscFree(baij->setvaluescopy);
    778: #endif
    779:   PetscFree(baij->in_loc);
    780:   PetscFree(baij->v_loc);
    781:   PetscFree(baij->rangebs);
    782:   PetscFree(mat->data);

    784:   PetscObjectChangeTypeName((PetscObject)mat,0);
    785:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
    786:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
    787:   PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);
    788:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);
    789:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C",NULL);
    790:   return(0);
    791: }

    795: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
    796: {
    797:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
    799:   PetscInt       nt,mbs=a->mbs,bs=A->rmap->bs;
    800:   PetscScalar    *x,*from;

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

    806:   /* diagonal part */
    807:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
    808:   VecSet(a->slvec1b,0.0);

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

    813:   /* copy x into the vec slvec0 */
    814:   VecGetArray(a->slvec0,&from);
    815:   VecGetArray(xx,&x);

    817:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
    818:   VecRestoreArray(a->slvec0,&from);
    819:   VecRestoreArray(xx,&x);

    821:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    822:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    823:   /* supperdiagonal part */
    824:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
    825:   return(0);
    826: }

    830: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
    831: {
    832:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
    834:   PetscInt       nt,mbs=a->mbs,bs=A->rmap->bs;
    835:   PetscScalar    *x,*from;

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

    841:   /* diagonal part */
    842:   (*a->A->ops->mult)(a->A,xx,a->slvec1a);
    843:   VecSet(a->slvec1b,0.0);

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

    848:   /* copy x into the vec slvec0 */
    849:   VecGetArray(a->slvec0,&from);
    850:   VecGetArray(xx,&x);

    852:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
    853:   VecRestoreArray(a->slvec0,&from);
    854:   VecRestoreArray(xx,&x);

    856:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    857:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    858:   /* supperdiagonal part */
    859:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
    860:   return(0);
    861: }

    865: PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy)
    866: {
    867:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
    869:   PetscInt       nt;

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

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

    878:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    879:   /* do diagonal part */
    880:   (*a->A->ops->mult)(a->A,xx,yy);
    881:   /* do supperdiagonal part */
    882:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    883:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
    884:   /* do subdiagonal part */
    885:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
    886:   VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    887:   VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    888:   return(0);
    889: }

    893: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
    894: {
    895:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
    897:   PetscInt       mbs=a->mbs,bs=A->rmap->bs;
    898:   PetscScalar    *x,*from,zero=0.0;

    901:   /*
    902:   PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n");
    903:   PetscSynchronizedFlush(PetscObjectComm((PetscObject)A));
    904:   */
    905:   /* diagonal part */
    906:   (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
    907:   VecSet(a->slvec1b,zero);

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

    912:   /* copy x into the vec slvec0 */
    913:   VecGetArray(a->slvec0,&from);
    914:   VecGetArray(xx,&x);
    915:   PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
    916:   VecRestoreArray(a->slvec0,&from);

    918:   VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
    919:   VecRestoreArray(xx,&x);
    920:   VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);

    922:   /* supperdiagonal part */
    923:   (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
    924:   return(0);
    925: }

    929: PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz)
    930: {
    931:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    935:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    936:   /* do diagonal part */
    937:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
    938:   /* do supperdiagonal part */
    939:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    940:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);

    942:   /* do subdiagonal part */
    943:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
    944:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
    945:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
    946:   return(0);
    947: }

    949: /*
    950:   This only works correctly for square matrices where the subblock A->A is the
    951:    diagonal block
    952: */
    955: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
    956: {
    957:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    961:   /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
    962:   MatGetDiagonal(a->A,v);
    963:   return(0);
    964: }

    968: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
    969: {
    970:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    974:   MatScale(a->A,aa);
    975:   MatScale(a->B,aa);
    976:   return(0);
    977: }

    981: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    982: {
    983:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
    984:   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
    986:   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
    987:   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
    988:   PetscInt       *cmap,*idx_p,cstart = mat->rstartbs;

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

    994:   if (!mat->rowvalues && (idx || v)) {
    995:     /*
    996:         allocate enough space to hold information from the longest row.
    997:     */
    998:     Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
    999:     Mat_SeqBAIJ  *Ba = (Mat_SeqBAIJ*)mat->B->data;
    1000:     PetscInt     max = 1,mbs = mat->mbs,tmp;
    1001:     for (i=0; i<mbs; i++) {
    1002:       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
    1003:       if (max < tmp) max = tmp;
    1004:     }
    1005:     PetscMalloc2(max*bs2,PetscScalar,&mat->rowvalues,max*bs2,PetscInt,&mat->rowindices);
    1006:   }

    1008:   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
    1009:   lrow = row - brstart;  /* local row index */

    1011:   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
    1012:   if (!v)   {pvA = 0; pvB = 0;}
    1013:   if (!idx) {pcA = 0; if (!v) pcB = 0;}
    1014:   (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
    1015:   (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
    1016:   nztot = nzA + nzB;

    1018:   cmap = mat->garray;
    1019:   if (v  || idx) {
    1020:     if (nztot) {
    1021:       /* Sort by increasing column numbers, assuming A and B already sorted */
    1022:       PetscInt imark = -1;
    1023:       if (v) {
    1024:         *v = v_p = mat->rowvalues;
    1025:         for (i=0; i<nzB; i++) {
    1026:           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
    1027:           else break;
    1028:         }
    1029:         imark = i;
    1030:         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
    1031:         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
    1032:       }
    1033:       if (idx) {
    1034:         *idx = idx_p = mat->rowindices;
    1035:         if (imark > -1) {
    1036:           for (i=0; i<imark; i++) {
    1037:             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
    1038:           }
    1039:         } else {
    1040:           for (i=0; i<nzB; i++) {
    1041:             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
    1042:             else break;
    1043:           }
    1044:           imark = i;
    1045:         }
    1046:         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
    1047:         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
    1048:       }
    1049:     } else {
    1050:       if (idx) *idx = 0;
    1051:       if (v)   *v   = 0;
    1052:     }
    1053:   }
    1054:   *nz  = nztot;
    1055:   (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
    1056:   (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
    1057:   return(0);
    1058: }

    1062: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
    1063: {
    1064:   Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;

    1067:   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
    1068:   baij->getrowactive = PETSC_FALSE;
    1069:   return(0);
    1070: }

    1074: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
    1075: {
    1076:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
    1077:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

    1080:   aA->getrow_utriangular = PETSC_TRUE;
    1081:   return(0);
    1082: }
    1085: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
    1086: {
    1087:   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
    1088:   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;

    1091:   aA->getrow_utriangular = PETSC_FALSE;
    1092:   return(0);
    1093: }

    1097: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
    1098: {
    1099:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1103:   MatRealPart(a->A);
    1104:   MatRealPart(a->B);
    1105:   return(0);
    1106: }

    1110: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
    1111: {
    1112:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1116:   MatImaginaryPart(a->A);
    1117:   MatImaginaryPart(a->B);
    1118:   return(0);
    1119: }

    1123: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
    1124: {
    1125:   Mat_MPISBAIJ   *l = (Mat_MPISBAIJ*)A->data;

    1129:   MatZeroEntries(l->A);
    1130:   MatZeroEntries(l->B);
    1131:   return(0);
    1132: }

    1136: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
    1137: {
    1138:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)matin->data;
    1139:   Mat            A  = a->A,B = a->B;
    1141:   PetscReal      isend[5],irecv[5];

    1144:   info->block_size = (PetscReal)matin->rmap->bs;

    1146:   MatGetInfo(A,MAT_LOCAL,info);

    1148:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
    1149:   isend[3] = info->memory;  isend[4] = info->mallocs;

    1151:   MatGetInfo(B,MAT_LOCAL,info);

    1153:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
    1154:   isend[3] += info->memory;  isend[4] += info->mallocs;
    1155:   if (flag == MAT_LOCAL) {
    1156:     info->nz_used      = isend[0];
    1157:     info->nz_allocated = isend[1];
    1158:     info->nz_unneeded  = isend[2];
    1159:     info->memory       = isend[3];
    1160:     info->mallocs      = isend[4];
    1161:   } else if (flag == MAT_GLOBAL_MAX) {
    1162:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

    1164:     info->nz_used      = irecv[0];
    1165:     info->nz_allocated = irecv[1];
    1166:     info->nz_unneeded  = irecv[2];
    1167:     info->memory       = irecv[3];
    1168:     info->mallocs      = irecv[4];
    1169:   } else if (flag == MAT_GLOBAL_SUM) {
    1170:     MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

    1172:     info->nz_used      = irecv[0];
    1173:     info->nz_allocated = irecv[1];
    1174:     info->nz_unneeded  = irecv[2];
    1175:     info->memory       = irecv[3];
    1176:     info->mallocs      = irecv[4];
    1177:   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
    1178:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
    1179:   info->fill_ratio_needed = 0;
    1180:   info->factor_mallocs    = 0;
    1181:   return(0);
    1182: }

    1186: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
    1187: {
    1188:   Mat_MPISBAIJ   *a  = (Mat_MPISBAIJ*)A->data;
    1189:   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;

    1193:   switch (op) {
    1194:   case MAT_NEW_NONZERO_LOCATIONS:
    1195:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
    1196:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
    1197:   case MAT_KEEP_NONZERO_PATTERN:
    1198:   case MAT_NEW_NONZERO_LOCATION_ERR:
    1199:     MatSetOption(a->A,op,flg);
    1200:     MatSetOption(a->B,op,flg);
    1201:     break;
    1202:   case MAT_ROW_ORIENTED:
    1203:     a->roworiented = flg;

    1205:     MatSetOption(a->A,op,flg);
    1206:     MatSetOption(a->B,op,flg);
    1207:     break;
    1208:   case MAT_NEW_DIAGONALS:
    1209:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
    1210:     break;
    1211:   case MAT_IGNORE_OFF_PROC_ENTRIES:
    1212:     a->donotstash = flg;
    1213:     break;
    1214:   case MAT_USE_HASH_TABLE:
    1215:     a->ht_flag = flg;
    1216:     break;
    1217:   case MAT_HERMITIAN:
    1218:     if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first");
    1219:     MatSetOption(a->A,op,flg);

    1221:     A->ops->mult = MatMult_MPISBAIJ_Hermitian;
    1222:     break;
    1223:   case MAT_SPD:
    1224:     A->spd_set = PETSC_TRUE;
    1225:     A->spd     = flg;
    1226:     if (flg) {
    1227:       A->symmetric                  = PETSC_TRUE;
    1228:       A->structurally_symmetric     = PETSC_TRUE;
    1229:       A->symmetric_set              = PETSC_TRUE;
    1230:       A->structurally_symmetric_set = PETSC_TRUE;
    1231:     }
    1232:     break;
    1233:   case MAT_SYMMETRIC:
    1234:     MatSetOption(a->A,op,flg);
    1235:     break;
    1236:   case MAT_STRUCTURALLY_SYMMETRIC:
    1237:     MatSetOption(a->A,op,flg);
    1238:     break;
    1239:   case MAT_SYMMETRY_ETERNAL:
    1240:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric");
    1241:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
    1242:     break;
    1243:   case MAT_IGNORE_LOWER_TRIANGULAR:
    1244:     aA->ignore_ltriangular = flg;
    1245:     break;
    1246:   case MAT_ERROR_LOWER_TRIANGULAR:
    1247:     aA->ignore_ltriangular = flg;
    1248:     break;
    1249:   case MAT_GETROW_UPPERTRIANGULAR:
    1250:     aA->getrow_utriangular = flg;
    1251:     break;
    1252:   default:
    1253:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
    1254:   }
    1255:   return(0);
    1256: }

    1260: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
    1261: {

    1265:   if (MAT_INITIAL_MATRIX || *B != A) {
    1266:     MatDuplicate(A,MAT_COPY_VALUES,B);
    1267:   }
    1268:   return(0);
    1269: }

    1273: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
    1274: {
    1275:   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
    1276:   Mat            a     = baij->A, b=baij->B;
    1278:   PetscInt       nv,m,n;
    1279:   PetscBool      flg;

    1282:   if (ll != rr) {
    1283:     VecEqual(ll,rr,&flg);
    1284:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n");
    1285:   }
    1286:   if (!ll) return(0);

    1288:   MatGetLocalSize(mat,&m,&n);
    1289:   if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n);

    1291:   VecGetLocalSize(rr,&nv);
    1292:   if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size");

    1294:   VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);

    1296:   /* left diagonalscale the off-diagonal part */
    1297:   (*b->ops->diagonalscale)(b,ll,NULL);

    1299:   /* scale the diagonal part */
    1300:   (*a->ops->diagonalscale)(a,ll,rr);

    1302:   /* right diagonalscale the off-diagonal part */
    1303:   VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1304:   (*b->ops->diagonalscale)(b,NULL,baij->lvec);
    1305:   return(0);
    1306: }

    1310: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
    1311: {
    1312:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;

    1316:   MatSetUnfactored(a->A);
    1317:   return(0);
    1318: }

    1320: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);

    1324: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool  *flag)
    1325: {
    1326:   Mat_MPISBAIJ   *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
    1327:   Mat            a,b,c,d;
    1328:   PetscBool      flg;

    1332:   a = matA->A; b = matA->B;
    1333:   c = matB->A; d = matB->B;

    1335:   MatEqual(a,c,&flg);
    1336:   if (flg) {
    1337:     MatEqual(b,d,&flg);
    1338:   }
    1339:   MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
    1340:   return(0);
    1341: }

    1345: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
    1346: {
    1348:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
    1349:   Mat_MPISBAIJ   *b = (Mat_MPISBAIJ*)B->data;

    1352:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
    1353:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
    1354:     MatGetRowUpperTriangular(A);
    1355:     MatCopy_Basic(A,B,str);
    1356:     MatRestoreRowUpperTriangular(A);
    1357:   } else {
    1358:     MatCopy(a->A,b->A,str);
    1359:     MatCopy(a->B,b->B,str);
    1360:   }
    1361:   return(0);
    1362: }

    1366: PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
    1367: {

    1371:   MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
    1372:   return(0);
    1373: }

    1377: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
    1378: {
    1380:   Mat_MPISBAIJ   *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
    1381:   PetscBLASInt   bnz,one=1;
    1382:   Mat_SeqSBAIJ   *xa,*ya;
    1383:   Mat_SeqBAIJ    *xb,*yb;

    1386:   if (str == SAME_NONZERO_PATTERN) {
    1387:     PetscScalar alpha = a;
    1388:     xa   = (Mat_SeqSBAIJ*)xx->A->data;
    1389:     ya   = (Mat_SeqSBAIJ*)yy->A->data;
    1390:     PetscBLASIntCast(xa->nz,&bnz);
    1391:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
    1392:     xb   = (Mat_SeqBAIJ*)xx->B->data;
    1393:     yb   = (Mat_SeqBAIJ*)yy->B->data;
    1394:     PetscBLASIntCast(xb->nz,&bnz);
    1395:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
    1396:   } else {
    1397:     MatGetRowUpperTriangular(X);
    1398:     MatAXPY_Basic(Y,a,X,str);
    1399:     MatRestoreRowUpperTriangular(X);
    1400:   }
    1401:   return(0);
    1402: }

    1406: PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
    1407: {
    1409:   PetscInt       i;
    1410:   PetscBool      flg;

    1413:   for (i=0; i<n; i++) {
    1414:     ISEqual(irow[i],icol[i],&flg);
    1415:     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices");
    1416:   }
    1417:   MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);
    1418:   return(0);
    1419: }

    1422: /* -------------------------------------------------------------------*/
    1423: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
    1424:                                        MatGetRow_MPISBAIJ,
    1425:                                        MatRestoreRow_MPISBAIJ,
    1426:                                        MatMult_MPISBAIJ,
    1427:                                /*  4*/ MatMultAdd_MPISBAIJ,
    1428:                                        MatMult_MPISBAIJ,       /* transpose versions are same as non-transpose */
    1429:                                        MatMultAdd_MPISBAIJ,
    1430:                                        0,
    1431:                                        0,
    1432:                                        0,
    1433:                                /* 10*/ 0,
    1434:                                        0,
    1435:                                        0,
    1436:                                        MatSOR_MPISBAIJ,
    1437:                                        MatTranspose_MPISBAIJ,
    1438:                                /* 15*/ MatGetInfo_MPISBAIJ,
    1439:                                        MatEqual_MPISBAIJ,
    1440:                                        MatGetDiagonal_MPISBAIJ,
    1441:                                        MatDiagonalScale_MPISBAIJ,
    1442:                                        MatNorm_MPISBAIJ,
    1443:                                /* 20*/ MatAssemblyBegin_MPISBAIJ,
    1444:                                        MatAssemblyEnd_MPISBAIJ,
    1445:                                        MatSetOption_MPISBAIJ,
    1446:                                        MatZeroEntries_MPISBAIJ,
    1447:                                /* 24*/ 0,
    1448:                                        0,
    1449:                                        0,
    1450:                                        0,
    1451:                                        0,
    1452:                                /* 29*/ MatSetUp_MPISBAIJ,
    1453:                                        0,
    1454:                                        0,
    1455:                                        0,
    1456:                                        0,
    1457:                                /* 34*/ MatDuplicate_MPISBAIJ,
    1458:                                        0,
    1459:                                        0,
    1460:                                        0,
    1461:                                        0,
    1462:                                /* 39*/ MatAXPY_MPISBAIJ,
    1463:                                        MatGetSubMatrices_MPISBAIJ,
    1464:                                        MatIncreaseOverlap_MPISBAIJ,
    1465:                                        MatGetValues_MPISBAIJ,
    1466:                                        MatCopy_MPISBAIJ,
    1467:                                /* 44*/ 0,
    1468:                                        MatScale_MPISBAIJ,
    1469:                                        0,
    1470:                                        0,
    1471:                                        0,
    1472:                                /* 49*/ 0,
    1473:                                        0,
    1474:                                        0,
    1475:                                        0,
    1476:                                        0,
    1477:                                /* 54*/ 0,
    1478:                                        0,
    1479:                                        MatSetUnfactored_MPISBAIJ,
    1480:                                        0,
    1481:                                        MatSetValuesBlocked_MPISBAIJ,
    1482:                                /* 59*/ 0,
    1483:                                        0,
    1484:                                        0,
    1485:                                        0,
    1486:                                        0,
    1487:                                /* 64*/ 0,
    1488:                                        0,
    1489:                                        0,
    1490:                                        0,
    1491:                                        0,
    1492:                                /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
    1493:                                        0,
    1494:                                        0,
    1495:                                        0,
    1496:                                        0,
    1497:                                /* 74*/ 0,
    1498:                                        0,
    1499:                                        0,
    1500:                                        0,
    1501:                                        0,
    1502:                                /* 79*/ 0,
    1503:                                        0,
    1504:                                        0,
    1505:                                        0,
    1506:                                        MatLoad_MPISBAIJ,
    1507:                                /* 84*/ 0,
    1508:                                        0,
    1509:                                        0,
    1510:                                        0,
    1511:                                        0,
    1512:                                /* 89*/ 0,
    1513:                                        0,
    1514:                                        0,
    1515:                                        0,
    1516:                                        0,
    1517:                                /* 94*/ 0,
    1518:                                        0,
    1519:                                        0,
    1520:                                        0,
    1521:                                        0,
    1522:                                /* 99*/ 0,
    1523:                                        0,
    1524:                                        0,
    1525:                                        0,
    1526:                                        0,
    1527:                                /*104*/ 0,
    1528:                                        MatRealPart_MPISBAIJ,
    1529:                                        MatImaginaryPart_MPISBAIJ,
    1530:                                        MatGetRowUpperTriangular_MPISBAIJ,
    1531:                                        MatRestoreRowUpperTriangular_MPISBAIJ,
    1532:                                /*109*/ 0,
    1533:                                        0,
    1534:                                        0,
    1535:                                        0,
    1536:                                        0,
    1537:                                /*114*/ 0,
    1538:                                        0,
    1539:                                        0,
    1540:                                        0,
    1541:                                        0,
    1542:                                /*119*/ 0,
    1543:                                        0,
    1544:                                        0,
    1545:                                        0,
    1546:                                        0,
    1547:                                /*124*/ 0,
    1548:                                        0,
    1549:                                        0,
    1550:                                        0,
    1551:                                        0,
    1552:                                /*129*/ 0,
    1553:                                        0,
    1554:                                        0,
    1555:                                        0,
    1556:                                        0,
    1557:                                /*134*/ 0,
    1558:                                        0,
    1559:                                        0,
    1560:                                        0,
    1561:                                        0,
    1562:                                /*139*/ 0,
    1563:                                        0
    1564: };

    1569: PetscErrorCode  MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
    1570: {
    1572:   *a = ((Mat_MPISBAIJ*)A->data)->A;
    1573:   return(0);
    1574: }

    1578: PetscErrorCode  MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
    1579: {
    1580:   Mat_MPISBAIJ   *b;
    1582:   PetscInt       i,mbs,Mbs;

    1585:   PetscLayoutSetBlockSize(B->rmap,bs);
    1586:   PetscLayoutSetBlockSize(B->cmap,bs);
    1587:   PetscLayoutSetUp(B->rmap);
    1588:   PetscLayoutSetUp(B->cmap);
    1589:   PetscLayoutGetBlockSize(B->rmap,&bs);

    1591:   b   = (Mat_MPISBAIJ*)B->data;
    1592:   mbs = B->rmap->n/bs;
    1593:   Mbs = B->rmap->N/bs;
    1594:   if (mbs*bs != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap->N,bs);

    1596:   B->rmap->bs = bs;
    1597:   b->bs2      = bs*bs;
    1598:   b->mbs      = mbs;
    1599:   b->nbs      = mbs;
    1600:   b->Mbs      = Mbs;
    1601:   b->Nbs      = Mbs;

    1603:   for (i=0; i<=b->size; i++) {
    1604:     b->rangebs[i] = B->rmap->range[i]/bs;
    1605:   }
    1606:   b->rstartbs = B->rmap->rstart/bs;
    1607:   b->rendbs   = B->rmap->rend/bs;

    1609:   b->cstartbs = B->cmap->rstart/bs;
    1610:   b->cendbs   = B->cmap->rend/bs;

    1612:   if (!B->preallocated) {
    1613:     MatCreate(PETSC_COMM_SELF,&b->A);
    1614:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
    1615:     MatSetType(b->A,MATSEQSBAIJ);
    1616:     PetscLogObjectParent(B,b->A);
    1617:     MatCreate(PETSC_COMM_SELF,&b->B);
    1618:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
    1619:     MatSetType(b->B,MATSEQBAIJ);
    1620:     PetscLogObjectParent(B,b->B);
    1621:     MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
    1622:   }

    1624:   MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
    1625:   MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);

    1627:   B->preallocated = PETSC_TRUE;
    1628:   return(0);
    1629: }

    1633: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
    1634: {
    1635:   PetscInt       m,rstart,cstart,cend;
    1636:   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
    1637:   const PetscInt *JJ    =0;
    1638:   PetscScalar    *values=0;

    1642:   if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
    1643:   PetscLayoutSetBlockSize(B->rmap,bs);
    1644:   PetscLayoutSetBlockSize(B->cmap,bs);
    1645:   PetscLayoutSetUp(B->rmap);
    1646:   PetscLayoutSetUp(B->cmap);
    1647:   PetscLayoutGetBlockSize(B->rmap,&bs);
    1648:   m      = B->rmap->n/bs;
    1649:   rstart = B->rmap->rstart/bs;
    1650:   cstart = B->cmap->rstart/bs;
    1651:   cend   = B->cmap->rend/bs;

    1653:   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
    1654:   PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);
    1655:   for (i=0; i<m; i++) {
    1656:     nz = ii[i+1] - ii[i];
    1657:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
    1658:     nz_max = PetscMax(nz_max,nz);
    1659:     JJ     = jj + ii[i];
    1660:     for (j=0; j<nz; j++) {
    1661:       if (*JJ >= cstart) break;
    1662:       JJ++;
    1663:     }
    1664:     d = 0;
    1665:     for (; j<nz; j++) {
    1666:       if (*JJ++ >= cend) break;
    1667:       d++;
    1668:     }
    1669:     d_nnz[i] = d;
    1670:     o_nnz[i] = nz - d;
    1671:   }
    1672:   MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
    1673:   PetscFree2(d_nnz,o_nnz);

    1675:   values = (PetscScalar*)V;
    1676:   if (!values) {
    1677:     PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);
    1678:     PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));
    1679:   }
    1680:   for (i=0; i<m; i++) {
    1681:     PetscInt          row    = i + rstart;
    1682:     PetscInt          ncols  = ii[i+1] - ii[i];
    1683:     const PetscInt    *icols = jj + ii[i];
    1684:     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
    1685:     MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
    1686:   }

    1688:   if (!V) { PetscFree(values); }
    1689:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    1690:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    1691:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
    1692:   return(0);
    1693: }

    1695: #if defined(PETSC_HAVE_MUMPS)
    1696: PETSC_EXTERN PetscErrorCode MatGetFactor_sbaij_mumps(Mat,MatFactorType,Mat*);
    1697: #endif
    1698: #if defined(PETSC_HAVE_PASTIX)
    1699: PETSC_EXTERN PetscErrorCode MatGetFactor_mpisbaij_pastix(Mat,MatFactorType,Mat*);
    1700: #endif

    1702: /*MC
    1703:    MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
    1704:    based on block compressed sparse row format.  Only the upper triangular portion of the "diagonal" portion of
    1705:    the matrix is stored.

    1707:   For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
    1708:   can call MatSetOption(Mat, MAT_HERMITIAN);

    1710:    Options Database Keys:
    1711: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()

    1713:   Level: beginner

    1715: .seealso: MatCreateMPISBAIJ
    1716: M*/

    1718: PETSC_EXTERN PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*);

    1722: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
    1723: {
    1724:   Mat_MPISBAIJ   *b;
    1726:   PetscBool      flg;

    1729:   PetscNewLog(B,Mat_MPISBAIJ,&b);
    1730:   B->data = (void*)b;
    1731:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

    1733:   B->ops->destroy = MatDestroy_MPISBAIJ;
    1734:   B->ops->view    = MatView_MPISBAIJ;
    1735:   B->assembled    = PETSC_FALSE;
    1736:   B->insertmode   = NOT_SET_VALUES;

    1738:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
    1739:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);

    1741:   /* build local table of row and column ownerships */
    1742:   PetscMalloc((b->size+2)*sizeof(PetscInt),&b->rangebs);

    1744:   /* build cache for off array entries formed */
    1745:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

    1747:   b->donotstash  = PETSC_FALSE;
    1748:   b->colmap      = NULL;
    1749:   b->garray      = NULL;
    1750:   b->roworiented = PETSC_TRUE;

    1752:   /* stuff used in block assembly */
    1753:   b->barray = 0;

    1755:   /* stuff used for matrix vector multiply */
    1756:   b->lvec    = 0;
    1757:   b->Mvctx   = 0;
    1758:   b->slvec0  = 0;
    1759:   b->slvec0b = 0;
    1760:   b->slvec1  = 0;
    1761:   b->slvec1a = 0;
    1762:   b->slvec1b = 0;
    1763:   b->sMvctx  = 0;

    1765:   /* stuff for MatGetRow() */
    1766:   b->rowindices   = 0;
    1767:   b->rowvalues    = 0;
    1768:   b->getrowactive = PETSC_FALSE;

    1770:   /* hash table stuff */
    1771:   b->ht           = 0;
    1772:   b->hd           = 0;
    1773:   b->ht_size      = 0;
    1774:   b->ht_flag      = PETSC_FALSE;
    1775:   b->ht_fact      = 0;
    1776:   b->ht_total_ct  = 0;
    1777:   b->ht_insert_ct = 0;

    1779:   /* stuff for MatGetSubMatrices_MPIBAIJ_local() */
    1780:   b->ijonly = PETSC_FALSE;

    1782:   b->in_loc = 0;
    1783:   b->v_loc  = 0;
    1784:   b->n_loc  = 0;
    1785:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");
    1786:   PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);
    1787:   if (flg) {
    1788:     PetscReal fact = 1.39;
    1789:     MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
    1790:     PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
    1791:     if (fact <= 1.0) fact = 1.39;
    1792:     MatMPIBAIJSetHashTableFactor(B,fact);
    1793:     PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
    1794:   }
    1795:   PetscOptionsEnd();

    1797: #if defined(PETSC_HAVE_PASTIX)
    1798:   PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpisbaij_pastix);
    1799: #endif
    1800: #if defined(PETSC_HAVE_MUMPS)
    1801:   PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_sbaij_mumps);
    1802: #endif
    1803:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);
    1804:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);
    1805:   PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPISBAIJ);
    1806:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);
    1807:   PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
    1808:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpisbstrm_C",MatConvert_MPISBAIJ_MPISBSTRM);

    1810:   B->symmetric                  = PETSC_TRUE;
    1811:   B->structurally_symmetric     = PETSC_TRUE;
    1812:   B->symmetric_set              = PETSC_TRUE;
    1813:   B->structurally_symmetric_set = PETSC_TRUE;

    1815:   PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
    1816:   return(0);
    1817: }

    1819: /*MC
    1820:    MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.

    1822:    This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
    1823:    and MATMPISBAIJ otherwise.

    1825:    Options Database Keys:
    1826: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()

    1828:   Level: beginner

    1830: .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ
    1831: M*/

    1835: /*@C
    1836:    MatMPISBAIJSetPreallocation - For good matrix assembly performance
    1837:    the user should preallocate the matrix storage by setting the parameters
    1838:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    1839:    performance can be increased by more than a factor of 50.

    1841:    Collective on Mat

    1843:    Input Parameters:
    1844: +  A - the matrix
    1845: .  bs   - size of blockk
    1846: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
    1847:            submatrix  (same for all local rows)
    1848: .  d_nnz - array containing the number of block nonzeros in the various block rows
    1849:            in the upper triangular and diagonal part of the in diagonal portion of the local
    1850:            (possibly different for each block row) or NULL.  If you plan to factor the matrix you must leave room
    1851:            for the diagonal entry and set a value even if it is zero.
    1852: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
    1853:            submatrix (same for all local rows).
    1854: -  o_nnz - array containing the number of nonzeros in the various block rows of the
    1855:            off-diagonal portion of the local submatrix that is right of the diagonal
    1856:            (possibly different for each block row) or NULL.

    1859:    Options Database Keys:
    1860: .   -mat_no_unroll - uses code that does not unroll the loops in the
    1861:                      block calculations (much slower)
    1862: .   -mat_block_size - size of the blocks to use

    1864:    Notes:

    1866:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
    1867:    than it must be used on all processors that share the object for that argument.

    1869:    If the *_nnz parameter is given then the *_nz parameter is ignored

    1871:    Storage Information:
    1872:    For a square global matrix we define each processor's diagonal portion
    1873:    to be its local rows and the corresponding columns (a square submatrix);
    1874:    each processor's off-diagonal portion encompasses the remainder of the
    1875:    local matrix (a rectangular submatrix).

    1877:    The user can specify preallocated storage for the diagonal part of
    1878:    the local submatrix with either d_nz or d_nnz (not both).  Set
    1879:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
    1880:    memory allocation.  Likewise, specify preallocated storage for the
    1881:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

    1883:    You can call MatGetInfo() to get information on how effective the preallocation was;
    1884:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
    1885:    You can also run with the option -info and look for messages with the string
    1886:    malloc in them to see if additional memory allocation was needed.

    1888:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
    1889:    the figure below we depict these three local rows and all columns (0-11).

    1891: .vb
    1892:            0 1 2 3 4 5 6 7 8 9 10 11
    1893:           --------------------------
    1894:    row 3  |. . . d d d o o o o  o  o
    1895:    row 4  |. . . d d d o o o o  o  o
    1896:    row 5  |. . . d d d o o o o  o  o
    1897:           --------------------------
    1898: .ve

    1900:    Thus, any entries in the d locations are stored in the d (diagonal)
    1901:    submatrix, and any entries in the o locations are stored in the
    1902:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
    1903:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

    1905:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
    1906:    plus the diagonal part of the d matrix,
    1907:    and o_nz should indicate the number of block nonzeros per row in the o matrix

    1909:    In general, for PDE problems in which most nonzeros are near the diagonal,
    1910:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
    1911:    or you will get TERRIBLE performance; see the users' manual chapter on
    1912:    matrices.

    1914:    Level: intermediate

    1916: .keywords: matrix, block, aij, compressed row, sparse, parallel

    1918: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
    1919: @*/
    1920: PetscErrorCode  MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
    1921: {

    1928:   PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
    1929:   return(0);
    1930: }

    1934: /*@C
    1935:    MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
    1936:    (block compressed row).  For good matrix assembly performance
    1937:    the user should preallocate the matrix storage by setting the parameters
    1938:    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
    1939:    performance can be increased by more than a factor of 50.

    1941:    Collective on MPI_Comm

    1943:    Input Parameters:
    1944: +  comm - MPI communicator
    1945: .  bs   - size of blockk
    1946: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
    1947:            This value should be the same as the local size used in creating the
    1948:            y vector for the matrix-vector product y = Ax.
    1949: .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
    1950:            This value should be the same as the local size used in creating the
    1951:            x vector for the matrix-vector product y = Ax.
    1952: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    1953: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    1954: .  d_nz  - number of block nonzeros per block row in diagonal portion of local
    1955:            submatrix  (same for all local rows)
    1956: .  d_nnz - array containing the number of block nonzeros in the various block rows
    1957:            in the upper triangular portion of the in diagonal portion of the local
    1958:            (possibly different for each block block row) or NULL.
    1959:            If you plan to factor the matrix you must leave room for the diagonal entry and
    1960:            set its value even if it is zero.
    1961: .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
    1962:            submatrix (same for all local rows).
    1963: -  o_nnz - array containing the number of nonzeros in the various block rows of the
    1964:            off-diagonal portion of the local submatrix (possibly different for
    1965:            each block row) or NULL.

    1967:    Output Parameter:
    1968: .  A - the matrix

    1970:    Options Database Keys:
    1971: .   -mat_no_unroll - uses code that does not unroll the loops in the
    1972:                      block calculations (much slower)
    1973: .   -mat_block_size - size of the blocks to use
    1974: .   -mat_mpi - use the parallel matrix data structures even on one processor
    1975:                (defaults to using SeqBAIJ format on one processor)

    1977:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
    1978:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
    1979:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

    1981:    Notes:
    1982:    The number of rows and columns must be divisible by blocksize.
    1983:    This matrix type does not support complex Hermitian operation.

    1985:    The user MUST specify either the local or global matrix dimensions
    1986:    (possibly both).

    1988:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
    1989:    than it must be used on all processors that share the object for that argument.

    1991:    If the *_nnz parameter is given then the *_nz parameter is ignored

    1993:    Storage Information:
    1994:    For a square global matrix we define each processor's diagonal portion
    1995:    to be its local rows and the corresponding columns (a square submatrix);
    1996:    each processor's off-diagonal portion encompasses the remainder of the
    1997:    local matrix (a rectangular submatrix).

    1999:    The user can specify preallocated storage for the diagonal part of
    2000:    the local submatrix with either d_nz or d_nnz (not both).  Set
    2001:    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
    2002:    memory allocation.  Likewise, specify preallocated storage for the
    2003:    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).

    2005:    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
    2006:    the figure below we depict these three local rows and all columns (0-11).

    2008: .vb
    2009:            0 1 2 3 4 5 6 7 8 9 10 11
    2010:           --------------------------
    2011:    row 3  |. . . d d d o o o o  o  o
    2012:    row 4  |. . . d d d o o o o  o  o
    2013:    row 5  |. . . d d d o o o o  o  o
    2014:           --------------------------
    2015: .ve

    2017:    Thus, any entries in the d locations are stored in the d (diagonal)
    2018:    submatrix, and any entries in the o locations are stored in the
    2019:    o (off-diagonal) submatrix.  Note that the d matrix is stored in
    2020:    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.

    2022:    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
    2023:    plus the diagonal part of the d matrix,
    2024:    and o_nz should indicate the number of block nonzeros per row in the o matrix.
    2025:    In general, for PDE problems in which most nonzeros are near the diagonal,
    2026:    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
    2027:    or you will get TERRIBLE performance; see the users' manual chapter on
    2028:    matrices.

    2030:    Level: intermediate

    2032: .keywords: matrix, block, aij, compressed row, sparse, parallel

    2034: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
    2035: @*/

    2037: PetscErrorCode  MatCreateSBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A)
    2038: {
    2040:   PetscMPIInt    size;

    2043:   MatCreate(comm,A);
    2044:   MatSetSizes(*A,m,n,M,N);
    2045:   MPI_Comm_size(comm,&size);
    2046:   if (size > 1) {
    2047:     MatSetType(*A,MATMPISBAIJ);
    2048:     MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
    2049:   } else {
    2050:     MatSetType(*A,MATSEQSBAIJ);
    2051:     MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
    2052:   }
    2053:   return(0);
    2054: }

    2059: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
    2060: {
    2061:   Mat            mat;
    2062:   Mat_MPISBAIJ   *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
    2064:   PetscInt       len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
    2065:   PetscScalar    *array;

    2068:   *newmat = 0;

    2070:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
    2071:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
    2072:   MatSetType(mat,((PetscObject)matin)->type_name);
    2073:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
    2074:   PetscLayoutReference(matin->rmap,&mat->rmap);
    2075:   PetscLayoutReference(matin->cmap,&mat->cmap);

    2077:   mat->factortype   = matin->factortype;
    2078:   mat->preallocated = PETSC_TRUE;
    2079:   mat->assembled    = PETSC_TRUE;
    2080:   mat->insertmode   = NOT_SET_VALUES;

    2082:   a      = (Mat_MPISBAIJ*)mat->data;
    2083:   a->bs2 = oldmat->bs2;
    2084:   a->mbs = oldmat->mbs;
    2085:   a->nbs = oldmat->nbs;
    2086:   a->Mbs = oldmat->Mbs;
    2087:   a->Nbs = oldmat->Nbs;

    2090:   a->size         = oldmat->size;
    2091:   a->rank         = oldmat->rank;
    2092:   a->donotstash   = oldmat->donotstash;
    2093:   a->roworiented  = oldmat->roworiented;
    2094:   a->rowindices   = 0;
    2095:   a->rowvalues    = 0;
    2096:   a->getrowactive = PETSC_FALSE;
    2097:   a->barray       = 0;
    2098:   a->rstartbs     = oldmat->rstartbs;
    2099:   a->rendbs       = oldmat->rendbs;
    2100:   a->cstartbs     = oldmat->cstartbs;
    2101:   a->cendbs       = oldmat->cendbs;

    2103:   /* hash table stuff */
    2104:   a->ht           = 0;
    2105:   a->hd           = 0;
    2106:   a->ht_size      = 0;
    2107:   a->ht_flag      = oldmat->ht_flag;
    2108:   a->ht_fact      = oldmat->ht_fact;
    2109:   a->ht_total_ct  = 0;
    2110:   a->ht_insert_ct = 0;

    2112:   PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));
    2113:   if (oldmat->colmap) {
    2114: #if defined(PETSC_USE_CTABLE)
    2115:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
    2116: #else
    2117:     PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);
    2118:     PetscLogObjectMemory(mat,(a->Nbs)*sizeof(PetscInt));
    2119:     PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));
    2120: #endif
    2121:   } else a->colmap = 0;

    2123:   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
    2124:     PetscMalloc(len*sizeof(PetscInt),&a->garray);
    2125:     PetscLogObjectMemory(mat,len*sizeof(PetscInt));
    2126:     PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));
    2127:   } else a->garray = 0;

    2129:   MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
    2130:   VecDuplicate(oldmat->lvec,&a->lvec);
    2131:   PetscLogObjectParent(mat,a->lvec);
    2132:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
    2133:   PetscLogObjectParent(mat,a->Mvctx);

    2135:    VecDuplicate(oldmat->slvec0,&a->slvec0);
    2136:   PetscLogObjectParent(mat,a->slvec0);
    2137:    VecDuplicate(oldmat->slvec1,&a->slvec1);
    2138:   PetscLogObjectParent(mat,a->slvec1);

    2140:   VecGetLocalSize(a->slvec1,&nt);
    2141:   VecGetArray(a->slvec1,&array);
    2142:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);
    2143:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
    2144:   VecRestoreArray(a->slvec1,&array);
    2145:   VecGetArray(a->slvec0,&array);
    2146:   VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
    2147:   VecRestoreArray(a->slvec0,&array);
    2148:   PetscLogObjectParent(mat,a->slvec0);
    2149:   PetscLogObjectParent(mat,a->slvec1);
    2150:   PetscLogObjectParent(mat,a->slvec0b);
    2151:   PetscLogObjectParent(mat,a->slvec1a);
    2152:   PetscLogObjectParent(mat,a->slvec1b);

    2154:   /*  VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
    2155:   PetscObjectReference((PetscObject)oldmat->sMvctx);
    2156:   a->sMvctx = oldmat->sMvctx;
    2157:   PetscLogObjectParent(mat,a->sMvctx);

    2159:    MatDuplicate(oldmat->A,cpvalues,&a->A);
    2160:   PetscLogObjectParent(mat,a->A);
    2161:    MatDuplicate(oldmat->B,cpvalues,&a->B);
    2162:   PetscLogObjectParent(mat,a->B);
    2163:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
    2164:   *newmat = mat;
    2165:   return(0);
    2166: }

    2170: PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer)
    2171: {
    2173:   PetscInt       i,nz,j,rstart,rend;
    2174:   PetscScalar    *vals,*buf;
    2175:   MPI_Comm       comm;
    2176:   MPI_Status     status;
    2177:   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs;
    2178:   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens;
    2179:   PetscInt       *procsnz = 0,jj,*mycols,*ibuf;
    2180:   PetscInt       bs       =1,Mbs,mbs,extra_rows;
    2181:   PetscInt       *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount;
    2182:   PetscInt       dcount,kmax,k,nzcount,tmp,sizesset=1,grows,gcols;
    2183:   int            fd;

    2186:   PetscObjectGetComm((PetscObject)viewer,&comm);
    2187:   PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");
    2188:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
    2189:   PetscOptionsEnd();

    2191:   MPI_Comm_size(comm,&size);
    2192:   MPI_Comm_rank(comm,&rank);
    2193:   if (!rank) {
    2194:     PetscViewerBinaryGetDescriptor(viewer,&fd);
    2195:     PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
    2196:     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
    2197:     if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ");
    2198:   }

    2200:   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0;

    2202:   MPI_Bcast(header+1,3,MPIU_INT,0,comm);
    2203:   M    = header[1];
    2204:   N    = header[2];

    2206:   /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */
    2207:   if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M;
    2208:   if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N;

    2210:   /* If global sizes are set, check if they are consistent with that given in the file */
    2211:   if (sizesset) {
    2212:     MatGetSize(newmat,&grows,&gcols);
    2213:   }
    2214:   if (sizesset && newmat->rmap->N != grows) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%d) and input matrix has (%d)",M,grows);
    2215:   if (sizesset && newmat->cmap->N != gcols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%d) and input matrix has (%d)",N,gcols);

    2217:   if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");

    2219:   /*
    2220:      This code adds extra rows to make sure the number of rows is
    2221:      divisible by the blocksize
    2222:   */
    2223:   Mbs        = M/bs;
    2224:   extra_rows = bs - M + bs*(Mbs);
    2225:   if (extra_rows == bs) extra_rows = 0;
    2226:   else                  Mbs++;
    2227:   if (extra_rows &&!rank) {
    2228:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
    2229:   }

    2231:   /* determine ownership of all rows */
    2232:   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
    2233:     mbs = Mbs/size + ((Mbs % size) > rank);
    2234:     m   = mbs*bs;
    2235:   } else { /* User Set */
    2236:     m   = newmat->rmap->n;
    2237:     mbs = m/bs;
    2238:   }
    2239:   PetscMalloc2(size+1,PetscMPIInt,&rowners,size+1,PetscMPIInt,&browners);
    2240:   PetscMPIIntCast(mbs,&mmbs);
    2241:   MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);
    2242:   rowners[0] = 0;
    2243:   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
    2244:   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
    2245:   rstart = rowners[rank];
    2246:   rend   = rowners[rank+1];

    2248:   /* distribute row lengths to all processors */
    2249:   PetscMalloc((rend-rstart)*bs*sizeof(PetscInt),&locrowlens);
    2250:   if (!rank) {
    2251:     PetscMalloc((M+extra_rows)*sizeof(PetscInt),&rowlengths);
    2252:     PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
    2253:     for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
    2254:     PetscMalloc(size*sizeof(PetscMPIInt),&sndcounts);
    2255:     for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i];
    2256:     MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
    2257:     PetscFree(sndcounts);
    2258:   } else {
    2259:     MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
    2260:   }

    2262:   if (!rank) {   /* procs[0] */
    2263:     /* calculate the number of nonzeros on each processor */
    2264:     PetscMalloc(size*sizeof(PetscInt),&procsnz);
    2265:     PetscMemzero(procsnz,size*sizeof(PetscInt));
    2266:     for (i=0; i<size; i++) {
    2267:       for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) {
    2268:         procsnz[i] += rowlengths[j];
    2269:       }
    2270:     }
    2271:     PetscFree(rowlengths);

    2273:     /* determine max buffer needed and allocate it */
    2274:     maxnz = 0;
    2275:     for (i=0; i<size; i++) {
    2276:       maxnz = PetscMax(maxnz,procsnz[i]);
    2277:     }
    2278:     PetscMalloc(maxnz*sizeof(PetscInt),&cols);

    2280:     /* read in my part of the matrix column indices  */
    2281:     nz     = procsnz[0];
    2282:     PetscMalloc(nz*sizeof(PetscInt),&ibuf);
    2283:     mycols = ibuf;
    2284:     if (size == 1) nz -= extra_rows;
    2285:     PetscBinaryRead(fd,mycols,nz,PETSC_INT);
    2286:     if (size == 1) {
    2287:       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
    2288:     }

    2290:     /* read in every ones (except the last) and ship off */
    2291:     for (i=1; i<size-1; i++) {
    2292:       nz   = procsnz[i];
    2293:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
    2294:       MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
    2295:     }
    2296:     /* read in the stuff for the last proc */
    2297:     if (size != 1) {
    2298:       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
    2299:       PetscBinaryRead(fd,cols,nz,PETSC_INT);
    2300:       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
    2301:       MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
    2302:     }
    2303:     PetscFree(cols);
    2304:   } else {  /* procs[i], i>0 */
    2305:     /* determine buffer space needed for message */
    2306:     nz = 0;
    2307:     for (i=0; i<m; i++) nz += locrowlens[i];
    2308:     PetscMalloc(nz*sizeof(PetscInt),&ibuf);
    2309:     mycols = ibuf;
    2310:     /* receive message of column indices*/
    2311:     MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
    2312:     MPI_Get_count(&status,MPIU_INT,&maxnz);
    2313:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
    2314:   }

    2316:   /* loop over local rows, determining number of off diagonal entries */
    2317:   PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);
    2318:   PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);
    2319:   PetscMemzero(mask,Mbs*sizeof(PetscInt));
    2320:   PetscMemzero(masked1,Mbs*sizeof(PetscInt));
    2321:   PetscMemzero(masked2,Mbs*sizeof(PetscInt));
    2322:   rowcount = 0;
    2323:   nzcount  = 0;
    2324:   for (i=0; i<mbs; i++) {
    2325:     dcount  = 0;
    2326:     odcount = 0;
    2327:     for (j=0; j<bs; j++) {
    2328:       kmax = locrowlens[rowcount];
    2329:       for (k=0; k<kmax; k++) {
    2330:         tmp = mycols[nzcount++]/bs; /* block col. index */
    2331:         if (!mask[tmp]) {
    2332:           mask[tmp] = 1;
    2333:           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */
    2334:           else masked1[dcount++] = tmp; /* entry in diag portion */
    2335:         }
    2336:       }
    2337:       rowcount++;
    2338:     }

    2340:     dlens[i]  = dcount;  /* d_nzz[i] */
    2341:     odlens[i] = odcount; /* o_nzz[i] */

    2343:     /* zero out the mask elements we set */
    2344:     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
    2345:     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
    2346:   }
    2347:   if (!sizesset) {
    2348:     MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
    2349:   }
    2350:   MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);
    2351:   MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);

    2353:   if (!rank) {
    2354:     PetscMalloc(maxnz*sizeof(PetscScalar),&buf);
    2355:     /* read in my part of the matrix numerical values  */
    2356:     nz     = procsnz[0];
    2357:     vals   = buf;
    2358:     mycols = ibuf;
    2359:     if (size == 1) nz -= extra_rows;
    2360:     PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    2361:     if (size == 1) {
    2362:       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
    2363:     }

    2365:     /* insert into matrix */
    2366:     jj = rstart*bs;
    2367:     for (i=0; i<m; i++) {
    2368:       MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
    2369:       mycols += locrowlens[i];
    2370:       vals   += locrowlens[i];
    2371:       jj++;
    2372:     }

    2374:     /* read in other processors (except the last one) and ship out */
    2375:     for (i=1; i<size-1; i++) {
    2376:       nz   = procsnz[i];
    2377:       vals = buf;
    2378:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    2379:       MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
    2380:     }
    2381:     /* the last proc */
    2382:     if (size != 1) {
    2383:       nz   = procsnz[i] - extra_rows;
    2384:       vals = buf;
    2385:       PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
    2386:       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
    2387:       MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
    2388:     }
    2389:     PetscFree(procsnz);

    2391:   } else {
    2392:     /* receive numeric values */
    2393:     PetscMalloc(nz*sizeof(PetscScalar),&buf);

    2395:     /* receive message of values*/
    2396:     vals   = buf;
    2397:     mycols = ibuf;
    2398:     MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);
    2399:     MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
    2400:     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");

    2402:     /* insert into matrix */
    2403:     jj = rstart*bs;
    2404:     for (i=0; i<m; i++) {
    2405:       MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
    2406:       mycols += locrowlens[i];
    2407:       vals   += locrowlens[i];
    2408:       jj++;
    2409:     }
    2410:   }

    2412:   PetscFree(locrowlens);
    2413:   PetscFree(buf);
    2414:   PetscFree(ibuf);
    2415:   PetscFree2(rowners,browners);
    2416:   PetscFree2(dlens,odlens);
    2417:   PetscFree3(mask,masked1,masked2);
    2418:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
    2419:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
    2420:   return(0);
    2421: }

    2425: /*XXXXX@
    2426:    MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

    2428:    Input Parameters:
    2429: .  mat  - the matrix
    2430: .  fact - factor

    2432:    Not Collective on Mat, each process can have a different hash factor

    2434:    Level: advanced

    2436:   Notes:
    2437:    This can also be set by the command line option: -mat_use_hash_table fact

    2439: .keywords: matrix, hashtable, factor, HT

    2441: .seealso: MatSetOption()
    2442: @XXXXX*/

    2447: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
    2448: {
    2449:   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
    2450:   Mat_SeqBAIJ    *b = (Mat_SeqBAIJ*)(a->B)->data;
    2451:   PetscReal      atmp;
    2452:   PetscReal      *work,*svalues,*rvalues;
    2454:   PetscInt       i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
    2455:   PetscMPIInt    rank,size;
    2456:   PetscInt       *rowners_bs,dest,count,source;
    2457:   PetscScalar    *va;
    2458:   MatScalar      *ba;
    2459:   MPI_Status     stat;

    2462:   if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov");
    2463:   MatGetRowMaxAbs(a->A,v,NULL);
    2464:   VecGetArray(v,&va);

    2466:   MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
    2467:   MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);

    2469:   bs  = A->rmap->bs;
    2470:   mbs = a->mbs;
    2471:   Mbs = a->Mbs;
    2472:   ba  = b->a;
    2473:   bi  = b->i;
    2474:   bj  = b->j;

    2476:   /* find ownerships */
    2477:   rowners_bs = A->rmap->range;

    2479:   /* each proc creates an array to be distributed */
    2480:   PetscMalloc(bs*Mbs*sizeof(PetscReal),&work);
    2481:   PetscMemzero(work,bs*Mbs*sizeof(PetscReal));

    2483:   /* row_max for B */
    2484:   if (rank != size-1) {
    2485:     for (i=0; i<mbs; i++) {
    2486:       ncols = bi[1] - bi[0]; bi++;
    2487:       brow  = bs*i;
    2488:       for (j=0; j<ncols; j++) {
    2489:         bcol = bs*(*bj);
    2490:         for (kcol=0; kcol<bs; kcol++) {
    2491:           col  = bcol + kcol;                /* local col index */
    2492:           col += rowners_bs[rank+1];      /* global col index */
    2493:           for (krow=0; krow<bs; krow++) {
    2494:             atmp = PetscAbsScalar(*ba); ba++;
    2495:             row  = brow + krow;   /* local row index */
    2496:             if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
    2497:             if (work[col] < atmp) work[col] = atmp;
    2498:           }
    2499:         }
    2500:         bj++;
    2501:       }
    2502:     }

    2504:     /* send values to its owners */
    2505:     for (dest=rank+1; dest<size; dest++) {
    2506:       svalues = work + rowners_bs[dest];
    2507:       count   = rowners_bs[dest+1]-rowners_bs[dest];
    2508:       MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));
    2509:     }
    2510:   }

    2512:   /* receive values */
    2513:   if (rank) {
    2514:     rvalues = work;
    2515:     count   = rowners_bs[rank+1]-rowners_bs[rank];
    2516:     for (source=0; source<rank; source++) {
    2517:       MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);
    2518:       /* process values */
    2519:       for (i=0; i<count; i++) {
    2520:         if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
    2521:       }
    2522:     }
    2523:   }

    2525:   VecRestoreArray(v,&va);
    2526:   PetscFree(work);
    2527:   return(0);
    2528: }

    2532: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    2533: {
    2534:   Mat_MPISBAIJ      *mat = (Mat_MPISBAIJ*)matin->data;
    2535:   PetscErrorCode    ierr;
    2536:   PetscInt          mbs=mat->mbs,bs=matin->rmap->bs;
    2537:   PetscScalar       *x,*ptr,*from;
    2538:   Vec               bb1;
    2539:   const PetscScalar *b;

    2542:   if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
    2543:   if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

    2545:   if (flag == SOR_APPLY_UPPER) {
    2546:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2547:     return(0);
    2548:   }

    2550:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
    2551:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    2552:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
    2553:       its--;
    2554:     }

    2556:     VecDuplicate(bb,&bb1);
    2557:     while (its--) {

    2559:       /* lower triangular part: slvec0b = - B^T*xx */
    2560:       (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);

    2562:       /* copy xx into slvec0a */
    2563:       VecGetArray(mat->slvec0,&ptr);
    2564:       VecGetArray(xx,&x);
    2565:       PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));
    2566:       VecRestoreArray(mat->slvec0,&ptr);

    2568:       VecScale(mat->slvec0,-1.0);

    2570:       /* copy bb into slvec1a */
    2571:       VecGetArray(mat->slvec1,&ptr);
    2572:       VecGetArrayRead(bb,&b);
    2573:       PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));
    2574:       VecRestoreArray(mat->slvec1,&ptr);

    2576:       /* set slvec1b = 0 */
    2577:       VecSet(mat->slvec1b,0.0);

    2579:       VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
    2580:       VecRestoreArray(xx,&x);
    2581:       VecRestoreArrayRead(bb,&b);
    2582:       VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);

    2584:       /* upper triangular part: bb1 = bb1 - B*x */
    2585:       (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);

    2587:       /* local diagonal sweep */
    2588:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
    2589:     }
    2590:     VecDestroy(&bb1);
    2591:   } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
    2592:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2593:   } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
    2594:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    2595:   } else if (flag & SOR_EISENSTAT) {
    2596:     Vec               xx1;
    2597:     PetscBool         hasop;
    2598:     const PetscScalar *diag;
    2599:     PetscScalar       *sl,scale = (omega - 2.0)/omega;
    2600:     PetscInt          i,n;

    2602:     if (!mat->xx1) {
    2603:       VecDuplicate(bb,&mat->xx1);
    2604:       VecDuplicate(bb,&mat->bb1);
    2605:     }
    2606:     xx1 = mat->xx1;
    2607:     bb1 = mat->bb1;

    2609:     (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);

    2611:     if (!mat->diag) {
    2612:       /* this is wrong for same matrix with new nonzero values */
    2613:       MatGetVecs(matin,&mat->diag,NULL);
    2614:       MatGetDiagonal(matin,mat->diag);
    2615:     }
    2616:     MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);

    2618:     if (hasop) {
    2619:       MatMultDiagonalBlock(matin,xx,bb1);
    2620:       VecAYPX(mat->slvec1a,scale,bb);
    2621:     } else {
    2622:       /*
    2623:           These two lines are replaced by code that may be a bit faster for a good compiler
    2624:       VecPointwiseMult(mat->slvec1a,mat->diag,xx);
    2625:       VecAYPX(mat->slvec1a,scale,bb);
    2626:       */
    2627:       VecGetArray(mat->slvec1a,&sl);
    2628:       VecGetArrayRead(mat->diag,&diag);
    2629:       VecGetArrayRead(bb,&b);
    2630:       VecGetArray(xx,&x);
    2631:       VecGetLocalSize(xx,&n);
    2632:       if (omega == 1.0) {
    2633:         for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
    2634:         PetscLogFlops(2.0*n);
    2635:       } else {
    2636:         for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
    2637:         PetscLogFlops(3.0*n);
    2638:       }
    2639:       VecRestoreArray(mat->slvec1a,&sl);
    2640:       VecRestoreArrayRead(mat->diag,&diag);
    2641:       VecRestoreArrayRead(bb,&b);
    2642:       VecRestoreArray(xx,&x);
    2643:     }

    2645:     /* multiply off-diagonal portion of matrix */
    2646:     VecSet(mat->slvec1b,0.0);
    2647:     (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
    2648:     VecGetArray(mat->slvec0,&from);
    2649:     VecGetArray(xx,&x);
    2650:     PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
    2651:     VecRestoreArray(mat->slvec0,&from);
    2652:     VecRestoreArray(xx,&x);
    2653:     VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
    2654:     VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
    2655:     (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);

    2657:     /* local sweep */
    2658:     (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
    2659:     VecAXPY(xx,1.0,xx1);
    2660:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
    2661:   return(0);
    2662: }

    2666: PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    2667: {
    2668:   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
    2670:   Vec            lvec1,bb1;

    2673:   if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
    2674:   if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");

    2676:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
    2677:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    2678:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
    2679:       its--;
    2680:     }

    2682:     VecDuplicate(mat->lvec,&lvec1);
    2683:     VecDuplicate(bb,&bb1);
    2684:     while (its--) {
    2685:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

    2687:       /* lower diagonal part: bb1 = bb - B^T*xx */
    2688:       (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);
    2689:       VecScale(lvec1,-1.0);

    2691:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
    2692:       VecCopy(bb,bb1);
    2693:       VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

    2695:       /* upper diagonal part: bb1 = bb1 - B*x */
    2696:       VecScale(mat->lvec,-1.0);
    2697:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);

    2699:       VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);

    2701:       /* diagonal sweep */
    2702:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
    2703:     }
    2704:     VecDestroy(&lvec1);
    2705:     VecDestroy(&bb1);
    2706:   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
    2707:   return(0);
    2708: }

    2712: /*@
    2713:      MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
    2714:          CSR format the local rows.

    2716:    Collective on MPI_Comm

    2718:    Input Parameters:
    2719: +  comm - MPI communicator
    2720: .  bs - the block size, only a block size of 1 is supported
    2721: .  m - number of local rows (Cannot be PETSC_DECIDE)
    2722: .  n - This value should be the same as the local size used in creating the
    2723:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
    2724:        calculated if N is given) For square matrices n is almost always m.
    2725: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    2726: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    2727: .   i - row indices
    2728: .   j - column indices
    2729: -   a - matrix values

    2731:    Output Parameter:
    2732: .   mat - the matrix

    2734:    Level: intermediate

    2736:    Notes:
    2737:        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
    2738:      thus you CANNOT change the matrix entries by changing the values of a[] after you have
    2739:      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.

    2741:        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.

    2743: .keywords: matrix, aij, compressed row, sparse, parallel

    2745: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
    2746:           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
    2747: @*/
    2748: PetscErrorCode  MatCreateMPISBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
    2749: {

    2754:   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
    2755:   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
    2756:   MatCreate(comm,mat);
    2757:   MatSetSizes(*mat,m,n,M,N);
    2758:   MatSetType(*mat,MATMPISBAIJ);
    2759:   MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
    2760:   return(0);
    2761: }

    2766: /*@C
    2767:    MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
    2768:    (the default parallel PETSc format).

    2770:    Collective on MPI_Comm

    2772:    Input Parameters:
    2773: +  A - the matrix
    2774: .  bs - the block size
    2775: .  i - the indices into j for the start of each local row (starts with zero)
    2776: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
    2777: -  v - optional values in the matrix

    2779:    Level: developer

    2781: .keywords: matrix, aij, compressed row, sparse, parallel

    2783: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
    2784: @*/
    2785: PetscErrorCode  MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
    2786: {

    2790:   PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
    2791:   return(0);
    2792: }