xref: /petsc/src/mat/impls/baij/mpi/mpibaij.c (revision e18c124a844f8a09db1af4148adb1e1cdba562d7)

#ifdef PETSC_RCS_HEADER
static char vcid[] = "$Id: mpibaij.c,v 1.139 1998/12/17 22:10:47 bsmith Exp bsmith $";
#endif

#include "src/mat/impls/baij/mpi/mpibaij.h"   /*I  "mat.h"  I*/
#include "src/vec/vecimpl.h"

extern int MatSetUpMultiply_MPIBAIJ(Mat);
extern int DisAssemble_MPIBAIJ(Mat);
extern int MatIncreaseOverlap_MPIBAIJ(Mat,int,IS *,int);
extern int MatGetSubMatrices_MPIBAIJ(Mat,int,IS *,IS *,MatGetSubMatrixCall,Mat **);
extern int MatGetValues_SeqBAIJ(Mat,int,int *,int,int *,Scalar *);

/*
     Local utility routine that creates a mapping from the global column
   number to the local number in the off-diagonal part of the local
   storage of the matrix.  This is done in a non scable way since the
   length of colmap equals the global matrix length.
*/
#undef __FUNC__
#define __FUNC__ "CreateColmap_MPIBAIJ_Private"
static int CreateColmap_MPIBAIJ_Private(Mat mat)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;
  Mat_SeqBAIJ *B = (Mat_SeqBAIJ*) baij->B->data;
  int         nbs = B->nbs,i,bs=B->bs;;

  PetscFunctionBegin;
  baij->colmap = (int *) PetscMalloc((baij->Nbs+1)*sizeof(int));CHKPTRQ(baij->colmap);
  PLogObjectMemory(mat,baij->Nbs*sizeof(int));
  PetscMemzero(baij->colmap,baij->Nbs*sizeof(int));
  for ( i=0; i<nbs; i++ ) baij->colmap[baij->garray[i]] = i*bs+1;
  PetscFunctionReturn(0);
}

#define CHUNKSIZE  10

#define  MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \
{ \
 \
    brow = row/bs;  \
    rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
    rmax = aimax[brow]; nrow = ailen[brow]; \
      bcol = col/bs; \
      ridx = row % bs; cidx = col % bs; \
      low = 0; high = nrow; \
      while (high-low > 3) { \
        t = (low+high)/2; \
        if (rp[t] > bcol) high = t; \
        else              low  = t; \
      } \
      for ( _i=low; _i<high; _i++ ) { \
        if (rp[_i] > bcol) break; \
        if (rp[_i] == bcol) { \
          bap  = ap +  bs2*_i + bs*cidx + ridx; \
          if (addv == ADD_VALUES) *bap += value;  \
          else                    *bap  = value;  \
          goto a_noinsert; \
        } \
      } \
      if (a->nonew == 1) goto a_noinsert; \
      else if (a->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero into matrix"); \
      if (nrow >= rmax) { \
        /* there is no extra room in row, therefore enlarge */ \
        int    new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \
        Scalar *new_a; \
 \
        if (a->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero in the matrix"); \
 \
        /* malloc new storage space */ \
        len     = new_nz*(sizeof(int)+bs2*sizeof(Scalar))+(a->mbs+1)*sizeof(int); \
        new_a   = (Scalar *) PetscMalloc( len ); CHKPTRQ(new_a); \
        new_j   = (int *) (new_a + bs2*new_nz); \
        new_i   = new_j + new_nz; \
 \
        /* copy over old data into new slots */ \
        for ( ii=0; ii<brow+1; ii++ ) {new_i[ii] = ai[ii];} \
        for ( ii=brow+1; ii<a->mbs+1; ii++ ) {new_i[ii] = ai[ii]+CHUNKSIZE;} \
        PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int)); \
        len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \
        PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow, \
                                                           len*sizeof(int)); \
        PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(Scalar)); \
        PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(Scalar)); \
        PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \
                    aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(Scalar));  \
        /* free up old matrix storage */ \
        PetscFree(a->a);  \
        if (!a->singlemalloc) {PetscFree(a->i);PetscFree(a->j);} \
        aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j;  \
        a->singlemalloc = 1; \
 \
        rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
        rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \
        PLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(Scalar))); \
        a->maxnz += bs2*CHUNKSIZE; \
        a->reallocs++; \
        a->nz++; \
      } \
      N = nrow++ - 1;  \
      /* shift up all the later entries in this row */ \
      for ( ii=N; ii>=_i; ii-- ) { \
        rp[ii+1] = rp[ii]; \
        PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(Scalar)); \
      } \
      if (N>=_i) PetscMemzero(ap+bs2*_i,bs2*sizeof(Scalar));  \
      rp[_i]                      = bcol;  \
      ap[bs2*_i + bs*cidx + ridx] = value;  \
      a_noinsert:; \
    ailen[brow] = nrow; \
}

#define  MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \
{ \
 \
    brow = row/bs;  \
    rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
    rmax = bimax[brow]; nrow = bilen[brow]; \
      bcol = col/bs; \
      ridx = row % bs; cidx = col % bs; \
      low = 0; high = nrow; \
      while (high-low > 3) { \
        t = (low+high)/2; \
        if (rp[t] > bcol) high = t; \
        else              low  = t; \
      } \
      for ( _i=low; _i<high; _i++ ) { \
        if (rp[_i] > bcol) break; \
        if (rp[_i] == bcol) { \
          bap  = ap +  bs2*_i + bs*cidx + ridx; \
          if (addv == ADD_VALUES) *bap += value;  \
          else                    *bap  = value;  \
          goto b_noinsert; \
        } \
      } \
      if (b->nonew == 1) goto b_noinsert; \
      else if (b->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero into matrix"); \
      if (nrow >= rmax) { \
        /* there is no extra room in row, therefore enlarge */ \
        int    new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \
        Scalar *new_a; \
 \
        if (b->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero in the matrix"); \
 \
        /* malloc new storage space */ \
        len     = new_nz*(sizeof(int)+bs2*sizeof(Scalar))+(b->mbs+1)*sizeof(int); \
        new_a   = (Scalar *) PetscMalloc( len ); CHKPTRQ(new_a); \
        new_j   = (int *) (new_a + bs2*new_nz); \
        new_i   = new_j + new_nz; \
 \
        /* copy over old data into new slots */ \
        for ( ii=0; ii<brow+1; ii++ ) {new_i[ii] = bi[ii];} \
        for ( ii=brow+1; ii<b->mbs+1; ii++ ) {new_i[ii] = bi[ii]+CHUNKSIZE;} \
        PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(int)); \
        len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \
        PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow, \
                                                           len*sizeof(int)); \
        PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(Scalar)); \
        PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(Scalar)); \
        PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \
                    ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(Scalar));  \
        /* free up old matrix storage */ \
        PetscFree(b->a);  \
        if (!b->singlemalloc) {PetscFree(b->i);PetscFree(b->j);} \
        ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j;  \
        b->singlemalloc = 1; \
 \
        rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
        rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \
        PLogObjectMemory(B,CHUNKSIZE*(sizeof(int) + bs2*sizeof(Scalar))); \
        b->maxnz += bs2*CHUNKSIZE; \
        b->reallocs++; \
        b->nz++; \
      } \
      N = nrow++ - 1;  \
      /* shift up all the later entries in this row */ \
      for ( ii=N; ii>=_i; ii-- ) { \
        rp[ii+1] = rp[ii]; \
        PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(Scalar)); \
      } \
      if (N>=_i) PetscMemzero(ap+bs2*_i,bs2*sizeof(Scalar));  \
      rp[_i]                      = bcol;  \
      ap[bs2*_i + bs*cidx + ridx] = value;  \
      b_noinsert:; \
    bilen[brow] = nrow; \
}

#undef __FUNC__
#define __FUNC__ "MatSetValues_MPIBAIJ"
int MatSetValues_MPIBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;
  Scalar      value;
  int         ierr,i,j,row,col;
  int         roworiented = baij->roworiented,rstart_orig=baij->rstart_bs ;
  int         rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs;
  int         cend_orig=baij->cend_bs,bs=baij->bs;

  /* Some Variables required in the macro */
  Mat         A = baij->A;
  Mat_SeqBAIJ *a = (Mat_SeqBAIJ *) (A)->data;
  int         *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
  Scalar      *aa=a->a;

  Mat         B = baij->B;
  Mat_SeqBAIJ *b = (Mat_SeqBAIJ *) (B)->data;
  int         *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
  Scalar      *ba=b->a;

  int         *rp,ii,nrow,_i,rmax,N,brow,bcol;
  int         low,high,t,ridx,cidx,bs2=a->bs2;
  Scalar      *ap,*bap;

  PetscFunctionBegin;
  for ( i=0; i<m; i++ ) {
#if defined(USE_PETSC_BOPT_g)
    if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row");
    if (im[i] >= baij->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large");
#endif
    if (im[i] >= rstart_orig && im[i] < rend_orig) {
      row = im[i] - rstart_orig;
      for ( j=0; j<n; j++ ) {
        if (in[j] >= cstart_orig && in[j] < cend_orig){
          col = in[j] - cstart_orig;
          if (roworiented) value = v[i*n+j]; else value = v[i+j*m];
          MatSetValues_SeqBAIJ_A_Private(row,col,value,addv);
          /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */
        }
#if defined(USE_PETSC_BOPT_g)
        else if (in[j] < 0) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative column");}
        else if (in[j] >= baij->N) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Col too large");}
#endif
        else {
          if (mat->was_assembled) {
            if (!baij->colmap) {
              ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
            }
            col = baij->colmap[in[j]/bs] - 1 + in[j]%bs;
            if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
              ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr);
              col =  in[j];
              /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
              B = baij->B;
              b = (Mat_SeqBAIJ *) (B)->data;
              bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
              ba=b->a;
            }
          } else col = in[j];
          if (roworiented) value = v[i*n+j]; else value = v[i+j*m];
          MatSetValues_SeqBAIJ_B_Private(row,col,value,addv);
          /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */
        }
      }
    } else {
      if (roworiented && !baij->donotstash) {
        ierr = StashValues_Private(&baij->stash,im[i],n,in,v+i*n,addv);CHKERRQ(ierr);
      } else {
        if (!baij->donotstash) {
          row = im[i];
	  for ( j=0; j<n; j++ ) {
	    ierr = StashValues_Private(&baij->stash,row,1,in+j,v+i+j*m,addv);CHKERRQ(ierr);
          }
        }
      }
    }
  }
  PetscFunctionReturn(0);
}

extern int MatSetValuesBlocked_SeqBAIJ(Mat,int,int*,int,int*,Scalar*,InsertMode);
#undef __FUNC__
#define __FUNC__ "MatSetValuesBlocked_MPIBAIJ"
int MatSetValuesBlocked_MPIBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;
  Scalar      *value,*barray=baij->barray;
  int         ierr,i,j,ii,jj,row,col,k,l;
  int         roworiented = baij->roworiented,rstart=baij->rstart ;
  int         rend=baij->rend,cstart=baij->cstart,stepval;
  int         cend=baij->cend,bs=baij->bs,bs2=baij->bs2;

  if(!barray) {
    baij->barray = barray = (Scalar*) PetscMalloc(bs2*sizeof(Scalar)); CHKPTRQ(barray);
  }

  if (roworiented) {
    stepval = (n-1)*bs;
  } else {
    stepval = (m-1)*bs;
  }
  for ( i=0; i<m; i++ ) {
#if defined(USE_PETSC_BOPT_g)
    if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row");
    if (im[i] >= baij->Mbs) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large");
#endif
    if (im[i] >= rstart && im[i] < rend) {
      row = im[i] - rstart;
      for ( j=0; j<n; j++ ) {
        /* If NumCol = 1 then a copy is not required */
        if ((roworiented) && (n == 1)) {
          barray = v + i*bs2;
        } else if((!roworiented) && (m == 1)) {
          barray = v + j*bs2;
        } else { /* Here a copy is required */
          if (roworiented) {
            value = v + i*(stepval+bs)*bs + j*bs;
          } else {
            value = v + j*(stepval+bs)*bs + i*bs;
          }
          for ( ii=0; ii<bs; ii++,value+=stepval ) {
            for (jj=0; jj<bs; jj++ ) {
              *barray++  = *value++;
            }
          }
          barray -=bs2;
        }

        if (in[j] >= cstart && in[j] < cend){
          col  = in[j] - cstart;
          ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
        }
#if defined(USE_PETSC_BOPT_g)
        else if (in[j] < 0) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative column");}
        else if (in[j] >= baij->Nbs) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Column too large");}
#endif
        else {
          if (mat->was_assembled) {
            if (!baij->colmap) {
              ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
            }

#if defined(USE_PETSC_BOPT_g)
            if ((baij->colmap[in[j]] - 1) % bs) {SETERRQ(PETSC_ERR_PLIB,0,"Incorrect colmap");}
#endif
            col = (baij->colmap[in[j]] - 1)/bs;
            if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
              ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr);
              col =  in[j];
            }
          }
          else col = in[j];
          ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
        }
      }
    } else {
      if (!baij->donotstash) {
        if (roworiented ) {
          row   = im[i]*bs;
          value = v + i*(stepval+bs)*bs;
          for ( j=0; j<bs; j++,row++ ) {
            for ( k=0; k<n; k++ ) {
              for ( col=in[k]*bs,l=0; l<bs; l++,col++) {
                ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr);
              }
            }
          }
        } else {
          for ( j=0; j<n; j++ ) {
            value = v + j*(stepval+bs)*bs + i*bs;
            col   = in[j]*bs;
            for ( k=0; k<bs; k++,col++,value+=stepval) {
              for ( row = im[i]*bs,l=0; l<bs; l++,row++) {
                ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr);
              }
            }
          }
        }
      }
    }
  }
  PetscFunctionReturn(0);
}
#define HASH_KEY 0.6180339887
/* #define HASH1(size,key) ((int)((size)*fmod(((key)*HASH_KEY),1))) */
#define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(int)((size)*(tmp-(int)tmp)))
/* #define HASH(size,key,tmp) ((int)((size)*fmod(((key)*HASH_KEY),1))) */
#undef __FUNC__
#define __FUNC__ "MatSetValues_MPIBAIJ_HT"
int MatSetValues_MPIBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;
  int         ierr,i,j,row,col;
  int         roworiented = baij->roworiented,rstart_orig=baij->rstart_bs ;
  int         rend_orig=baij->rend_bs,Nbs=baij->Nbs;
  int         h1,key,size=baij->ht_size,bs=baij->bs,*HT=baij->ht,idx;
  double      tmp;
  Scalar      ** HD = baij->hd,value;
#if defined(USE_PETSC_BOPT_g)
  int         total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
#endif

  PetscFunctionBegin;

  for ( i=0; i<m; i++ ) {
#if defined(USE_PETSC_BOPT_g)
    if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row");
    if (im[i] >= baij->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large");
#endif
      row = im[i];
    if (row >= rstart_orig && row < rend_orig) {
      for ( j=0; j<n; j++ ) {
        col = in[j];
        if (roworiented) value = v[i*n+j]; else value = v[i+j*m];
        /* Look up into the Hash Table */
        key = (row/bs)*Nbs+(col/bs)+1;
        h1  = HASH(size,key,tmp);


        idx = h1;
#if defined(USE_PETSC_BOPT_g)
        insert_ct++;
        total_ct++;
        if (HT[idx] != key) {
          for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++);
          if (idx == size) {
            for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++);
            if (idx == h1) {
              SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table");
            }
          }
        }
#else
        if (HT[idx] != key) {
          for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++);
          if (idx == size) {
            for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++);
            if (idx == h1) {
              SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table");
            }
          }
        }
#endif
        /* A HASH table entry is found, so insert the values at the correct address */
        if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value;
        else                    *(HD[idx]+ (col % bs)*bs + (row % bs))  = value;
      }
    } else {
      if (roworiented && !baij->donotstash) {
        ierr = StashValues_Private(&baij->stash,im[i],n,in,v+i*n,addv);CHKERRQ(ierr);
      } else {
        if (!baij->donotstash) {
          row = im[i];
	  for ( j=0; j<n; j++ ) {
	    ierr = StashValues_Private(&baij->stash,row,1,in+j,v+i+j*m,addv);CHKERRQ(ierr);
          }
        }
      }
    }
  }
#if defined(USE_PETSC_BOPT_g)
  baij->ht_total_ct = total_ct;
  baij->ht_insert_ct = insert_ct;
#endif
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatSetValuesBlocked_MPIBAIJ_HT"
int MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;
  int         ierr,i,j,ii,jj,row,col,k,l;
  int         roworiented = baij->roworiented,rstart=baij->rstart ;
  int         rend=baij->rend,stepval,bs=baij->bs,bs2=baij->bs2;
  int         h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs;
  double      tmp;
  Scalar      ** HD = baij->hd,*value,*v_t,*baij_a;
#if defined(USE_PETSC_BOPT_g)
  int         total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
#endif

  PetscFunctionBegin;

  if (roworiented) {
    stepval = (n-1)*bs;
  } else {
    stepval = (m-1)*bs;
  }
  for ( i=0; i<m; i++ ) {
#if defined(USE_PETSC_BOPT_g)
    if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row");
    if (im[i] >= baij->Mbs) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large");
#endif
    row   = im[i];
    v_t   = v + i*bs2;
    if (row >= rstart && row < rend) {
      for ( j=0; j<n; j++ ) {
        col = in[j];

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

        idx = h1;
#if defined(USE_PETSC_BOPT_g)
        total_ct++;
        insert_ct++;
       if (HT[idx] != key) {
          for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++);
          if (idx == size) {
            for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++);
            if (idx == h1) {
              SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table");
            }
          }
        }
#else
        if (HT[idx] != key) {
          for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++);
          if (idx == size) {
            for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++);
            if (idx == h1) {
              SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table");
            }
          }
        }
#endif
        baij_a = HD[idx];
        if (roworiented) {
          /*value = v + i*(stepval+bs)*bs + j*bs;*/
          /* value = v + (i*(stepval+bs)+j)*bs; */
          value = v_t;
          v_t  += bs;
          if (addv == ADD_VALUES) {
            for ( ii=0; ii<bs; ii++,value+=stepval) {
              for ( jj=ii; jj<bs2; jj+=bs ) {
                baij_a[jj]  += *value++;
              }
            }
          } else {
            for ( ii=0; ii<bs; ii++,value+=stepval) {
              for ( jj=ii; jj<bs2; jj+=bs ) {
                baij_a[jj]  = *value++;
              }
            }
          }
        } else {
          value = v + j*(stepval+bs)*bs + i*bs;
          if (addv == ADD_VALUES) {
            for ( ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs ) {
              for ( jj=0; jj<bs; jj++ ) {
                baij_a[jj]  += *value++;
              }
            }
          } else {
            for ( ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs ) {
              for ( jj=0; jj<bs; jj++ ) {
                baij_a[jj]  = *value++;
              }
            }
          }
        }
      }
    } else {
      if (!baij->donotstash) {
        if (roworiented ) {
          row   = im[i]*bs;
          value = v + i*(stepval+bs)*bs;
          for ( j=0; j<bs; j++,row++ ) {
            for ( k=0; k<n; k++ ) {
              for ( col=in[k]*bs,l=0; l<bs; l++,col++) {
                ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr);
              }
            }
          }
        } else {
          for ( j=0; j<n; j++ ) {
            value = v + j*(stepval+bs)*bs + i*bs;
            col   = in[j]*bs;
            for ( k=0; k<bs; k++,col++,value+=stepval) {
              for ( row = im[i]*bs,l=0; l<bs; l++,row++) {
                ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr);
              }
            }
          }
        }
      }
    }
  }
#if defined(USE_PETSC_BOPT_g)
  baij->ht_total_ct = total_ct;
  baij->ht_insert_ct = insert_ct;
#endif
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatGetValues_MPIBAIJ"
int MatGetValues_MPIBAIJ(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;
  int        bs=baij->bs,ierr,i,j, bsrstart = baij->rstart*bs, bsrend = baij->rend*bs;
  int        bscstart = baij->cstart*bs, bscend = baij->cend*bs,row,col;

  PetscFunctionBegin;
  for ( i=0; i<m; i++ ) {
    if (idxm[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row");
    if (idxm[i] >= baij->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large");
    if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
      row = idxm[i] - bsrstart;
      for ( j=0; j<n; j++ ) {
        if (idxn[j] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative column");
        if (idxn[j] >= baij->N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Column too large");
        if (idxn[j] >= bscstart && idxn[j] < bscend){
          col = idxn[j] - bscstart;
          ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j); CHKERRQ(ierr);
        } else {
          if (!baij->colmap) {
            ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
          }
          if((baij->colmap[idxn[j]/bs]-1 < 0) ||
             (baij->garray[(baij->colmap[idxn[j]/bs]-1)/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
          else {
            col  = (baij->colmap[idxn[j]/bs]-1) + idxn[j]%bs;
            ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j); CHKERRQ(ierr);
          }
        }
      }
    } else {
      SETERRQ(PETSC_ERR_SUP,0,"Only local values currently supported");
    }
  }
 PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatNorm_MPIBAIJ"
int MatNorm_MPIBAIJ(Mat mat,NormType type,double *norm)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;
  Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*) baij->A->data, *bmat = (Mat_SeqBAIJ*) baij->B->data;
  int        ierr, i,bs2=baij->bs2;
  double     sum = 0.0;
  Scalar     *v;

  PetscFunctionBegin;
  if (baij->size == 1) {
    ierr =  MatNorm(baij->A,type,norm); CHKERRQ(ierr);
  } else {
    if (type == NORM_FROBENIUS) {
      v = amat->a;
      for (i=0; i<amat->nz*bs2; i++ ) {
#if defined(USE_PETSC_COMPLEX)
        sum += PetscReal(PetscConj(*v)*(*v)); v++;
#else
        sum += (*v)*(*v); v++;
#endif
      }
      v = bmat->a;
      for (i=0; i<bmat->nz*bs2; i++ ) {
#if defined(USE_PETSC_COMPLEX)
        sum += PetscReal(PetscConj(*v)*(*v)); v++;
#else
        sum += (*v)*(*v); v++;
#endif
      }
      ierr = MPI_Allreduce(&sum,norm,1,MPI_DOUBLE,MPI_SUM,mat->comm);CHKERRQ(ierr);
      *norm = sqrt(*norm);
    } else {
      SETERRQ(PETSC_ERR_SUP,0,"No support for this norm yet");
    }
  }
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatAssemblyBegin_MPIBAIJ"
int MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;
  MPI_Comm    comm = mat->comm;
  int         size = baij->size, *owners = baij->rowners,bs=baij->bs;
  int         rank = baij->rank,tag = mat->tag, *owner,*starts,count,ierr;
  MPI_Request *send_waits,*recv_waits;
  int         *nprocs,i,j,idx,*procs,nsends,nreceives,nmax,*work;
  InsertMode  addv;
  Scalar      *rvalues,*svalues;

  PetscFunctionBegin;
  if (baij->donotstash) {
    baij->svalues    = 0; baij->rvalues    = 0;
    baij->nsends     = 0; baij->nrecvs     = 0;
    baij->send_waits = 0; baij->recv_waits = 0;
    baij->rmax       = 0;
    PetscFunctionReturn(0);
  }

  /* make sure all processors are either in INSERTMODE or ADDMODE */
  ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,comm);CHKERRQ(ierr);
  if (addv == (ADD_VALUES|INSERT_VALUES)) {
    SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Some processors inserted others added");
  }
  mat->insertmode = addv; /* in case this processor had no cache */

  /*  first count number of contributors to each processor */
  nprocs = (int *) PetscMalloc( 2*size*sizeof(int) ); CHKPTRQ(nprocs);
  PetscMemzero(nprocs,2*size*sizeof(int)); procs = nprocs + size;
  owner = (int *) PetscMalloc( (baij->stash.n+1)*sizeof(int) ); CHKPTRQ(owner);
  for ( i=0; i<baij->stash.n; i++ ) {
    idx = baij->stash.idx[i];
    for ( j=0; j<size; j++ ) {
      if (idx >= owners[j]*bs && idx < owners[j+1]*bs) {
        nprocs[j]++; procs[j] = 1; owner[i] = j; break;
      }
    }
  }
  nsends = 0;  for ( i=0; i<size; i++ ) { nsends += procs[i];}

  /* inform other processors of number of messages and max length*/
  work      = (int *) PetscMalloc( size*sizeof(int) ); CHKPTRQ(work);
  ierr      = MPI_Allreduce(procs, work,size,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr);
  nreceives = work[rank];
  ierr      = MPI_Allreduce( nprocs, work,size,MPI_INT,MPI_MAX,comm);CHKERRQ(ierr);
  nmax      = work[rank];
  PetscFree(work);

  /* post receives:
       1) each message will consist of ordered pairs
     (global index,value) we store the global index as a double
     to simplify the message passing.
       2) since we don't know how long each individual message is we
     allocate the largest needed buffer for each receive. Potentially
     this is a lot of wasted space.


       This could be done better.
  */
  rvalues    = (Scalar *) PetscMalloc(3*(nreceives+1)*(nmax+1)*sizeof(Scalar));CHKPTRQ(rvalues);
  recv_waits = (MPI_Request *) PetscMalloc((nreceives+1)*sizeof(MPI_Request));CHKPTRQ(recv_waits);
  for ( i=0; i<nreceives; i++ ) {
    ierr = MPI_Irecv(rvalues+3*nmax*i,3*nmax,MPIU_SCALAR,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr);
  }

  /* do sends:
      1) starts[i] gives the starting index in svalues for stuff going to
         the ith processor
  */
  svalues    = (Scalar *) PetscMalloc(3*(baij->stash.n+1)*sizeof(Scalar));CHKPTRQ(svalues);
  send_waits = (MPI_Request *) PetscMalloc((nsends+1)*sizeof(MPI_Request));CHKPTRQ(send_waits);
  starts     = (int *) PetscMalloc( size*sizeof(int) ); CHKPTRQ(starts);
  starts[0] = 0;
  for ( i=1; i<size; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];}
  for ( i=0; i<baij->stash.n; i++ ) {
    svalues[3*starts[owner[i]]]       = (Scalar)  baij->stash.idx[i];
    svalues[3*starts[owner[i]]+1]     = (Scalar)  baij->stash.idy[i];
    svalues[3*(starts[owner[i]]++)+2] =  baij->stash.array[i];
  }
  PetscFree(owner);
  starts[0] = 0;
  for ( i=1; i<size; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];}
  count = 0;
  for ( i=0; i<size; i++ ) {
    if (procs[i]) {
      ierr = MPI_Isend(svalues+3*starts[i],3*nprocs[i],MPIU_SCALAR,i,tag,comm,send_waits+count++);CHKERRQ(ierr);
    }
  }
  PetscFree(starts); PetscFree(nprocs);

  /* Free cache space */
  PLogInfo(baij->A,"MatAssemblyBegin_MPIBAIJ:Number of off-processor values %d\n",baij->stash.n);
  ierr = StashDestroy_Private(&baij->stash); CHKERRQ(ierr);

  baij->svalues    = svalues;    baij->rvalues    = rvalues;
  baij->nsends     = nsends;     baij->nrecvs     = nreceives;
  baij->send_waits = send_waits; baij->recv_waits = recv_waits;
  baij->rmax       = nmax;

  PetscFunctionReturn(0);
}

/*
  Creates the hash table, and sets the table
  This table is created only once.
  If new entried need to be added to the matrix
  then the hash table has to be destroyed and
  recreated.
*/
#undef __FUNC__
#define __FUNC__ "MatCreateHashTable_MPIBAIJ_Private"
int MatCreateHashTable_MPIBAIJ_Private(Mat mat,double factor)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;
  Mat         A = baij->A, B=baij->B;
  Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data, *b=(Mat_SeqBAIJ *)B->data;
  int         i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
  int         size,bs2=baij->bs2,rstart=baij->rstart;
  int         cstart=baij->cstart,*garray=baij->garray,row,col,Nbs=baij->Nbs;
  int         *HT,key;
  Scalar      **HD;
  double      tmp;
#if defined(USE_PETSC_BOPT_g)
  int         ct=0,max=0;
#endif

  PetscFunctionBegin;
  baij->ht_size=(int)(factor*nz);
  size = baij->ht_size;

  if (baij->ht) {
    PetscFunctionReturn(0);
  }

  /* Allocate Memory for Hash Table */
  baij->hd = (Scalar**)PetscMalloc((size)*(sizeof(int)+sizeof(Scalar*))+1); CHKPTRQ(baij->hd);
  baij->ht = (int*)(baij->hd + size);
  HD = baij->hd;
  HT = baij->ht;


  PetscMemzero(HD,size*(sizeof(int)+sizeof(Scalar*)));


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

      key = row*Nbs + col + 1;
      h1  = HASH(size,key,tmp);
      for ( k=0; k<size; k++ ){
        if (HT[(h1+k)%size] == 0.0) {
          HT[(h1+k)%size] = key;
          HD[(h1+k)%size] = a->a + j*bs2;
          break;
#if defined(USE_PETSC_BOPT_g)
        } else {
          ct++;
#endif
        }
      }
#if defined(USE_PETSC_BOPT_g)
      if (k> max) max = k;
#endif
    }
  }
  /* Loop Over B */
  for ( i=0; i<b->mbs; i++ ) {
    for ( j=bi[i]; j<bi[i+1]; j++ ) {
      row = i+rstart;
      col = garray[bj[j]];
      key = row*Nbs + col + 1;
      h1  = HASH(size,key,tmp);
      for ( k=0; k<size; k++ ){
        if (HT[(h1+k)%size] == 0.0) {
          HT[(h1+k)%size] = key;
          HD[(h1+k)%size] = b->a + j*bs2;
          break;
#if defined(USE_PETSC_BOPT_g)
        } else {
          ct++;
#endif
        }
      }
#if defined(USE_PETSC_BOPT_g)
      if (k> max) max = k;
#endif
    }
  }

  /* Print Summary */
#if defined(USE_PETSC_BOPT_g)
  for ( i=0,j=0; i<size; i++)
    if (HT[i]) {j++;}
  PLogInfo(0,"MatCreateHashTable_MPIBAIJ_Private: Average Search = %5.2f,max search = %d\n",
           (j== 0)? 0.0:((double)(ct+j))/j,max);
#endif
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatAssemblyEnd_MPIBAIJ"
int MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;
  MPI_Status  *send_status,recv_status;
  int         imdex,nrecvs = baij->nrecvs, count = nrecvs, i, n, ierr;
  int         bs=baij->bs,row,col,other_disassembled;
  Scalar      *values,val;
  InsertMode  addv = mat->insertmode;

  PetscFunctionBegin;
  /*  wait on receives */
  while (count) {
    ierr = MPI_Waitany(nrecvs,baij->recv_waits,&imdex,&recv_status);CHKERRQ(ierr);
    /* unpack receives into our local space */
    values = baij->rvalues + 3*imdex*baij->rmax;
    ierr = MPI_Get_count(&recv_status,MPIU_SCALAR,&n);CHKERRQ(ierr);
    n = n/3;
    for ( i=0; i<n; i++ ) {
      row = (int) PetscReal(values[3*i]) - baij->rstart*bs;
      col = (int) PetscReal(values[3*i+1]);
      val = values[3*i+2];
      if (col >= baij->cstart*bs && col < baij->cend*bs) {
        col -= baij->cstart*bs;
        ierr = MatSetValues(baij->A,1,&row,1,&col,&val,addv); CHKERRQ(ierr)
      } else {
        if (mat->was_assembled) {
          if (!baij->colmap) {
            ierr = CreateColmap_MPIBAIJ_Private(mat); CHKERRQ(ierr);
          }
          col = (baij->colmap[col/bs]) - 1 + col%bs;
          if (col < 0  && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
            ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr);
            col = (int) PetscReal(values[3*i+1]);
          }
        }
        ierr = MatSetValues(baij->B,1,&row,1,&col,&val,addv); CHKERRQ(ierr)
      }
    }
    count--;
  }
  if (baij->recv_waits) PetscFree(baij->recv_waits);
  if (baij->rvalues)    PetscFree(baij->rvalues);

  /* wait on sends */
  if (baij->nsends) {
    send_status = (MPI_Status *) PetscMalloc(baij->nsends*sizeof(MPI_Status));CHKPTRQ(send_status);
    ierr        = MPI_Waitall(baij->nsends,baij->send_waits,send_status);CHKERRQ(ierr);
    PetscFree(send_status);
  }
  if (baij->send_waits) PetscFree(baij->send_waits);
  if (baij->svalues)    PetscFree(baij->svalues);

  ierr = MatAssemblyBegin(baij->A,mode); CHKERRQ(ierr);
  ierr = MatAssemblyEnd(baij->A,mode); CHKERRQ(ierr);

  /* determine if any processor has disassembled, if so we must
     also disassemble ourselfs, in order that we may reassemble. */
  /*
     if nonzero structure of submatrix B cannot change then we know that
     no processor disassembled thus we can skip this stuff
  */
  if (!((Mat_SeqBAIJ*) baij->B->data)->nonew)  {
    ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr);
    if (mat->was_assembled && !other_disassembled) {
      ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr);
    }
  }

  if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
    ierr = MatSetUpMultiply_MPIBAIJ(mat); CHKERRQ(ierr);
  }
  ierr = MatAssemblyBegin(baij->B,mode); CHKERRQ(ierr);
  ierr = MatAssemblyEnd(baij->B,mode); CHKERRQ(ierr);

#if defined(USE_PETSC_BOPT_g)
  if (baij->ht && mode== MAT_FINAL_ASSEMBLY) {
    PLogInfo(0,"MatAssemblyEnd_MPIBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",
             ((double)baij->ht_total_ct)/baij->ht_insert_ct);
    baij->ht_total_ct  = 0;
    baij->ht_insert_ct = 0;
  }
#endif
  if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) {
    ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact); CHKERRQ(ierr);
    mat->ops->setvalues        = MatSetValues_MPIBAIJ_HT;
    mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT;
  }

  if (baij->rowvalues) {PetscFree(baij->rowvalues); baij->rowvalues = 0;}
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatView_MPIBAIJ_Binary"
static int MatView_MPIBAIJ_Binary(Mat mat,Viewer viewer)
{
  Mat_MPIBAIJ  *baij = (Mat_MPIBAIJ *) mat->data;
  int          ierr;

  PetscFunctionBegin;
  if (baij->size == 1) {
    ierr = MatView(baij->A,viewer); CHKERRQ(ierr);
  } else SETERRQ(PETSC_ERR_SUP,0,"Only uniprocessor output supported");
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatView_MPIBAIJ_ASCIIorDraworMatlab"
static int MatView_MPIBAIJ_ASCIIorDraworMatlab(Mat mat,Viewer viewer)
{
  Mat_MPIBAIJ  *baij = (Mat_MPIBAIJ *) mat->data;
  int          ierr, format,bs = baij->bs, size = baij->size, rank = baij->rank;
  FILE         *fd;
  ViewerType   vtype;

  PetscFunctionBegin;
  ierr = ViewerGetType(viewer,&vtype); CHKERRQ(ierr);
  if (PetscTypeCompare(vtype,ASCII_VIEWER)) {
    ierr = ViewerGetFormat(viewer,&format);
    if (format == VIEWER_FORMAT_ASCII_INFO_LONG) {
      MatInfo info;
      MPI_Comm_rank(mat->comm,&rank);
      ierr = ViewerASCIIGetPointer(viewer,&fd); CHKERRQ(ierr);
      ierr = MatGetInfo(mat,MAT_LOCAL,&info);
      PetscSequentialPhaseBegin(mat->comm,1);
      fprintf(fd,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n",
              rank,baij->m,(int)info.nz_used*bs,(int)info.nz_allocated*bs,
              baij->bs,(int)info.memory);
      ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);
      fprintf(fd,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);
      ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);
      fprintf(fd,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);
      fflush(fd);
      PetscSequentialPhaseEnd(mat->comm,1);
      ierr = VecScatterView(baij->Mvctx,viewer); CHKERRQ(ierr);
      PetscFunctionReturn(0);
    } else if (format == VIEWER_FORMAT_ASCII_INFO) {
      PetscPrintf(mat->comm,"  block size is %d\n",bs);
      PetscFunctionReturn(0);
    }
  }

  if (PetscTypeCompare(vtype,DRAW_VIEWER)) {
    Draw       draw;
    PetscTruth isnull;
    ierr = ViewerDrawGetDraw(viewer,0,&draw); CHKERRQ(ierr);
    ierr = DrawIsNull(draw,&isnull); CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0);
  }

  if (size == 1) {
    ierr = MatView(baij->A,viewer); CHKERRQ(ierr);
  } else {
    /* assemble the entire matrix onto first processor. */
    Mat         A;
    Mat_SeqBAIJ *Aloc;
    int         M = baij->M, N = baij->N,*ai,*aj,col,i,j,k,*rvals;
    int         mbs = baij->mbs;
    Scalar      *a;

    if (!rank) {
      ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr);
    } else {
      ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr);
    }
    PLogObjectParent(mat,A);

    /* copy over the A part */
    Aloc = (Mat_SeqBAIJ*) baij->A->data;
    ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
    rvals = (int *) PetscMalloc(bs*sizeof(int)); CHKPTRQ(rvals);

    for ( i=0; i<mbs; i++ ) {
      rvals[0] = bs*(baij->rstart + i);
      for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; }
      for ( j=ai[i]; j<ai[i+1]; j++ ) {
        col = (baij->cstart+aj[j])*bs;
        for (k=0; k<bs; k++ ) {
          ierr = MatSetValues(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr);
          col++; a += bs;
        }
      }
    }
    /* copy over the B part */
    Aloc = (Mat_SeqBAIJ*) baij->B->data;
    ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
    for ( i=0; i<mbs; i++ ) {
      rvals[0] = bs*(baij->rstart + i);
      for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; }
      for ( j=ai[i]; j<ai[i+1]; j++ ) {
        col = baij->garray[aj[j]]*bs;
        for (k=0; k<bs; k++ ) {
          ierr = MatSetValues(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr);
          col++; a += bs;
        }
      }
    }
    PetscFree(rvals);
    ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr);
    ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr);
    /*
       Everyone has to call to draw the matrix since the graphics waits are
       synchronized across all processors that share the Draw object
    */
    if (!rank || PetscTypeCompare(vtype,DRAW_VIEWER)) {
      ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,viewer); CHKERRQ(ierr);
    }
    ierr = MatDestroy(A); CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}



#undef __FUNC__
#define __FUNC__ "MatView_MPIBAIJ"
int MatView_MPIBAIJ(Mat mat,Viewer viewer)
{
  int         ierr;
  ViewerType  vtype;

  PetscFunctionBegin;
  ierr = ViewerGetType(viewer,&vtype); CHKERRQ(ierr);
  if (PetscTypeCompare(vtype,ASCII_VIEWER) || PetscTypeCompare(vtype,DRAW_VIEWER) ||
      PetscTypeCompare(vtype,MATLAB_VIEWER)) {
    ierr = MatView_MPIBAIJ_ASCIIorDraworMatlab(mat,viewer); CHKERRQ(ierr);
  } else if (PetscTypeCompare(vtype,BINARY_VIEWER)) {
    ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr);
  } else {
    SETERRQ(1,1,"Viewer type not supported by PETSc object");
  }
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatDestroy_MPIBAIJ"
int MatDestroy_MPIBAIJ(Mat mat)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;
  int         ierr;

  PetscFunctionBegin;
  if (--mat->refct > 0) PetscFunctionReturn(0);

  if (mat->mapping) {
    ierr = ISLocalToGlobalMappingDestroy(mat->mapping); CHKERRQ(ierr);
  }
  if (mat->bmapping) {
    ierr = ISLocalToGlobalMappingDestroy(mat->bmapping); CHKERRQ(ierr);
  }
  if (mat->rmap) {
    ierr = MapDestroy(mat->rmap);CHKERRQ(ierr);
  }
  if (mat->cmap) {
    ierr = MapDestroy(mat->cmap);CHKERRQ(ierr);
  }
#if defined(USE_PETSC_LOG)
  PLogObjectState((PetscObject)mat,"Rows=%d, Cols=%d",baij->M,baij->N);
#endif

  ierr = StashDestroy_Private(&baij->stash); CHKERRQ(ierr);
  PetscFree(baij->rowners);
  ierr = MatDestroy(baij->A); CHKERRQ(ierr);
  ierr = MatDestroy(baij->B); CHKERRQ(ierr);
  if (baij->colmap) PetscFree(baij->colmap);
  if (baij->garray) PetscFree(baij->garray);
  if (baij->lvec)   VecDestroy(baij->lvec);
  if (baij->Mvctx)  VecScatterDestroy(baij->Mvctx);
  if (baij->rowvalues) PetscFree(baij->rowvalues);
  if (baij->barray) PetscFree(baij->barray);
  if (baij->hd) PetscFree(baij->hd);
  PetscFree(baij);
  PLogObjectDestroy(mat);
  PetscHeaderDestroy(mat);
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatMult_MPIBAIJ"
int MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy)
{
  Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data;
  int         ierr, nt;

  PetscFunctionBegin;
  ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr);
  if (nt != a->n) {
    SETERRQ(PETSC_ERR_ARG_SIZ,0,"Incompatible partition of A and xx");
  }
  ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr);
  if (nt != a->m) {
    SETERRQ(PETSC_ERR_ARG_SIZ,0,"Incompatible parition of A and yy");
  }
  ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr);
  ierr = (*a->A->ops->mult)(a->A,xx,yy); CHKERRQ(ierr);
  ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr);
  ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy); CHKERRQ(ierr);
  ierr = VecScatterPostRecvs(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatMultAdd_MPIBAIJ"
int MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
{
  Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data;
  int        ierr;

  PetscFunctionBegin;
  ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr);
  ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz); CHKERRQ(ierr);
  ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr);
  ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz); CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatMultTrans_MPIBAIJ"
int MatMultTrans_MPIBAIJ(Mat A,Vec xx,Vec yy)
{
  Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data;
  int         ierr;

  PetscFunctionBegin;
  /* do nondiagonal part */
  ierr = (*a->B->ops->multtrans)(a->B,xx,a->lvec); CHKERRQ(ierr);
  /* send it on its way */
  ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr);
  /* do local part */
  ierr = (*a->A->ops->multtrans)(a->A,xx,yy); CHKERRQ(ierr);
  /* receive remote parts: note this assumes the values are not actually */
  /* inserted in yy until the next line, which is true for my implementation*/
  /* but is not perhaps always true. */
  ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatMultTransAdd_MPIBAIJ"
int MatMultTransAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
{
  Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data;
  int         ierr;

  PetscFunctionBegin;
  /* do nondiagonal part */
  ierr = (*a->B->ops->multtrans)(a->B,xx,a->lvec); CHKERRQ(ierr);
  /* send it on its way */
  ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx); CHKERRQ(ierr);
  /* do local part */
  ierr = (*a->A->ops->multtransadd)(a->A,xx,yy,zz); CHKERRQ(ierr);
  /* receive remote parts: note this assumes the values are not actually */
  /* inserted in yy until the next line, which is true for my implementation*/
  /* but is not perhaps always true. */
  ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx); CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*
  This only works correctly for square matrices where the subblock A->A is the
   diagonal block
*/
#undef __FUNC__
#define __FUNC__ "MatGetDiagonal_MPIBAIJ"
int MatGetDiagonal_MPIBAIJ(Mat A,Vec v)
{
  Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data;
  int         ierr;

  PetscFunctionBegin;
  if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,0,"Supports only square matrix where A->A is diag block");
  ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatScale_MPIBAIJ"
int MatScale_MPIBAIJ(Scalar *aa,Mat A)
{
  Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data;
  int         ierr;

  PetscFunctionBegin;
  ierr = MatScale(aa,a->A); CHKERRQ(ierr);
  ierr = MatScale(aa,a->B); CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatGetSize_MPIBAIJ"
int MatGetSize_MPIBAIJ(Mat matin,int *m,int *n)
{
  Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data;

  PetscFunctionBegin;
  if (m) *m = mat->M;
  if (n) *n = mat->N;
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatGetLocalSize_MPIBAIJ"
int MatGetLocalSize_MPIBAIJ(Mat matin,int *m,int *n)
{
  Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data;

  PetscFunctionBegin;
  *m = mat->m; *n = mat->n;
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatGetOwnershipRange_MPIBAIJ"
int MatGetOwnershipRange_MPIBAIJ(Mat matin,int *m,int *n)
{
  Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data;

  PetscFunctionBegin;
  *m = mat->rstart*mat->bs; *n = mat->rend*mat->bs;
  PetscFunctionReturn(0);
}

extern int MatGetRow_SeqBAIJ(Mat,int,int*,int**,Scalar**);
extern int MatRestoreRow_SeqBAIJ(Mat,int,int*,int**,Scalar**);

#undef __FUNC__
#define __FUNC__ "MatGetRow_MPIBAIJ"
int MatGetRow_MPIBAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v)
{
  Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data;
  Scalar     *vworkA, *vworkB, **pvA, **pvB,*v_p;
  int        bs = mat->bs, bs2 = mat->bs2, i, ierr, *cworkA, *cworkB, **pcA, **pcB;
  int        nztot, nzA, nzB, lrow, brstart = mat->rstart*bs, brend = mat->rend*bs;
  int        *cmap, *idx_p,cstart = mat->cstart;

  PetscFunctionBegin;
  if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Already active");
  mat->getrowactive = PETSC_TRUE;

  if (!mat->rowvalues && (idx || v)) {
    /*
        allocate enough space to hold information from the longest row.
    */
    Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ *) mat->A->data,*Ba = (Mat_SeqBAIJ *) mat->B->data;
    int     max = 1,mbs = mat->mbs,tmp;
    for ( i=0; i<mbs; i++ ) {
      tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
      if (max < tmp) { max = tmp; }
    }
    mat->rowvalues = (Scalar *) PetscMalloc( max*bs2*(sizeof(int)+sizeof(Scalar)));
    CHKPTRQ(mat->rowvalues);
    mat->rowindices = (int *) (mat->rowvalues + max*bs2);
  }

  if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,0,"Only local rows")
  lrow = row - brstart;

  pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
  if (!v)   {pvA = 0; pvB = 0;}
  if (!idx) {pcA = 0; if (!v) pcB = 0;}
  ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA); CHKERRQ(ierr);
  ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB); CHKERRQ(ierr);
  nztot = nzA + nzB;

  cmap  = mat->garray;
  if (v  || idx) {
    if (nztot) {
      /* Sort by increasing column numbers, assuming A and B already sorted */
      int imark = -1;
      if (v) {
        *v = v_p = mat->rowvalues;
        for ( i=0; i<nzB; i++ ) {
          if (cmap[cworkB[i]/bs] < cstart)   v_p[i] = vworkB[i];
          else break;
        }
        imark = i;
        for ( i=0; i<nzA; i++ )     v_p[imark+i] = vworkA[i];
        for ( i=imark; i<nzB; i++ ) v_p[nzA+i]   = vworkB[i];
      }
      if (idx) {
        *idx = idx_p = mat->rowindices;
        if (imark > -1) {
          for ( i=0; i<imark; i++ ) {
            idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
          }
        } else {
          for ( i=0; i<nzB; i++ ) {
            if (cmap[cworkB[i]/bs] < cstart)
              idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
            else break;
          }
          imark = i;
        }
        for ( i=0; i<nzA; i++ )     idx_p[imark+i] = cstart*bs + cworkA[i];
        for ( i=imark; i<nzB; i++ ) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
      }
    } else {
      if (idx) *idx = 0;
      if (v)   *v   = 0;
    }
  }
  *nz = nztot;
  ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA); CHKERRQ(ierr);
  ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB); CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatRestoreRow_MPIBAIJ"
int MatRestoreRow_MPIBAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;

  PetscFunctionBegin;
  if (baij->getrowactive == PETSC_FALSE) {
    SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"MatGetRow not called");
  }
  baij->getrowactive = PETSC_FALSE;
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatGetBlockSize_MPIBAIJ"
int MatGetBlockSize_MPIBAIJ(Mat mat,int *bs)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data;

  PetscFunctionBegin;
  *bs = baij->bs;
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatZeroEntries_MPIBAIJ"
int MatZeroEntries_MPIBAIJ(Mat A)
{
  Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data;
  int         ierr;

  PetscFunctionBegin;
  ierr = MatZeroEntries(l->A); CHKERRQ(ierr);
  ierr = MatZeroEntries(l->B); CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatGetInfo_MPIBAIJ"
int MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
{
  Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) matin->data;
  Mat         A = a->A, B = a->B;
  int         ierr;
  double      isend[5], irecv[5];

  PetscFunctionBegin;
  info->block_size     = (double)a->bs;
  ierr = MatGetInfo(A,MAT_LOCAL,info); CHKERRQ(ierr);
  isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
  isend[3] = info->memory;  isend[4] = info->mallocs;
  ierr = MatGetInfo(B,MAT_LOCAL,info); CHKERRQ(ierr);
  isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
  isend[3] += info->memory;  isend[4] += info->mallocs;
  if (flag == MAT_LOCAL) {
    info->nz_used      = isend[0];
    info->nz_allocated = isend[1];
    info->nz_unneeded  = isend[2];
    info->memory       = isend[3];
    info->mallocs      = isend[4];
  } else if (flag == MAT_GLOBAL_MAX) {
    ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_MAX,matin->comm);CHKERRQ(ierr);
    info->nz_used      = irecv[0];
    info->nz_allocated = irecv[1];
    info->nz_unneeded  = irecv[2];
    info->memory       = irecv[3];
    info->mallocs      = irecv[4];
  } else if (flag == MAT_GLOBAL_SUM) {
    ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_SUM,matin->comm);CHKERRQ(ierr);
    info->nz_used      = irecv[0];
    info->nz_allocated = irecv[1];
    info->nz_unneeded  = irecv[2];
    info->memory       = irecv[3];
    info->mallocs      = irecv[4];
  }
  info->rows_global       = (double)a->M;
  info->columns_global    = (double)a->N;
  info->rows_local        = (double)a->m;
  info->columns_local     = (double)a->N;
  info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
  info->fill_ratio_needed = 0;
  info->factor_mallocs    = 0;
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatSetOption_MPIBAIJ"
int MatSetOption_MPIBAIJ(Mat A,MatOption op)
{
  Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data;

  PetscFunctionBegin;
  if (op == MAT_NO_NEW_NONZERO_LOCATIONS ||
      op == MAT_YES_NEW_NONZERO_LOCATIONS ||
      op == MAT_COLUMNS_UNSORTED ||
      op == MAT_COLUMNS_SORTED ||
      op == MAT_NEW_NONZERO_ALLOCATION_ERROR ||
      op == MAT_NEW_NONZERO_LOCATION_ERROR) {
        MatSetOption(a->A,op);
        MatSetOption(a->B,op);
  } else if (op == MAT_ROW_ORIENTED) {
        a->roworiented = 1;
        MatSetOption(a->A,op);
        MatSetOption(a->B,op);
  } else if (op == MAT_ROWS_SORTED ||
             op == MAT_ROWS_UNSORTED ||
             op == MAT_SYMMETRIC ||
             op == MAT_STRUCTURALLY_SYMMETRIC ||
             op == MAT_YES_NEW_DIAGONALS ||
             op == MAT_USE_HASH_TABLE)
    PLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n");
  else if (op == MAT_COLUMN_ORIENTED) {
    a->roworiented = 0;
    MatSetOption(a->A,op);
    MatSetOption(a->B,op);
  } else if (op == MAT_IGNORE_OFF_PROC_ENTRIES) {
    a->donotstash = 1;
  } else if (op == MAT_NO_NEW_DIAGONALS) {
    SETERRQ(PETSC_ERR_SUP,0,"MAT_NO_NEW_DIAGONALS");
  } else if (op == MAT_USE_HASH_TABLE) {
    a->ht_flag = 1;
  } else {
    SETERRQ(PETSC_ERR_SUP,0,"unknown option");
  }
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatTranspose_MPIBAIJ("
int MatTranspose_MPIBAIJ(Mat A,Mat *matout)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) A->data;
  Mat_SeqBAIJ *Aloc;
  Mat        B;
  int        ierr,M=baij->M,N=baij->N,*ai,*aj,i,*rvals,j,k,col;
  int        bs=baij->bs,mbs=baij->mbs;
  Scalar     *a;

  PetscFunctionBegin;
  if (matout == PETSC_NULL && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Square matrix only for in-place");
  ierr = MatCreateMPIBAIJ(A->comm,baij->bs,PETSC_DECIDE,PETSC_DECIDE,N,M,0,PETSC_NULL,0,PETSC_NULL,&B);
  CHKERRQ(ierr);

  /* copy over the A part */
  Aloc = (Mat_SeqBAIJ*) baij->A->data;
  ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
  rvals = (int *) PetscMalloc(bs*sizeof(int)); CHKPTRQ(rvals);

  for ( i=0; i<mbs; i++ ) {
    rvals[0] = bs*(baij->rstart + i);
    for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; }
    for ( j=ai[i]; j<ai[i+1]; j++ ) {
      col = (baij->cstart+aj[j])*bs;
      for (k=0; k<bs; k++ ) {
        ierr = MatSetValues(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr);
        col++; a += bs;
      }
    }
  }
  /* copy over the B part */
  Aloc = (Mat_SeqBAIJ*) baij->B->data;
  ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
  for ( i=0; i<mbs; i++ ) {
    rvals[0] = bs*(baij->rstart + i);
    for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; }
    for ( j=ai[i]; j<ai[i+1]; j++ ) {
      col = baij->garray[aj[j]]*bs;
      for (k=0; k<bs; k++ ) {
        ierr = MatSetValues(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr);
        col++; a += bs;
      }
    }
  }
  PetscFree(rvals);
  ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr);
  ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr);

  if (matout != PETSC_NULL) {
    *matout = B;
  } else {
    PetscOps *Abops;
    MatOps   Aops;

    /* This isn't really an in-place transpose .... but free data structures from baij */
    PetscFree(baij->rowners);
    ierr = MatDestroy(baij->A); CHKERRQ(ierr);
    ierr = MatDestroy(baij->B); CHKERRQ(ierr);
    if (baij->colmap) PetscFree(baij->colmap);
    if (baij->garray) PetscFree(baij->garray);
    if (baij->lvec) VecDestroy(baij->lvec);
    if (baij->Mvctx) VecScatterDestroy(baij->Mvctx);
    PetscFree(baij);

    /*
       This is horrible, horrible code. We need to keep the
      A pointers for the bops and ops but copy everything
      else from C.
    */
    Abops = A->bops;
    Aops  = A->ops;
    PetscMemcpy(A,B,sizeof(struct _p_Mat));
    A->bops = Abops;
    A->ops  = Aops;

    PetscHeaderDestroy(B);
  }
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatDiagonalScale_MPIBAIJ"
int MatDiagonalScale_MPIBAIJ(Mat A,Vec ll,Vec rr)
{
  Mat a = ((Mat_MPIBAIJ *) A->data)->A;
  Mat b = ((Mat_MPIBAIJ *) A->data)->B;
  int ierr,s1,s2,s3;

  PetscFunctionBegin;
  if (ll)  {
    ierr = VecGetLocalSize(ll,&s1); CHKERRQ(ierr);
    ierr = MatGetLocalSize(A,&s2,&s3); CHKERRQ(ierr);
    if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,0,"non-conforming local sizes");
    ierr = MatDiagonalScale(a,ll,0); CHKERRQ(ierr);
    ierr = MatDiagonalScale(b,ll,0); CHKERRQ(ierr);
  }
  if (rr) SETERRQ(PETSC_ERR_SUP,0,"not supported for right vector");
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatZeroRows_MPIBAIJ"
int MatZeroRows_MPIBAIJ(Mat A,IS is,Scalar *diag)
{
  Mat_MPIBAIJ    *l = (Mat_MPIBAIJ *) A->data;
  int            i,ierr,N, *rows,*owners = l->rowners,size = l->size;
  int            *procs,*nprocs,j,found,idx,nsends,*work,row;
  int            nmax,*svalues,*starts,*owner,nrecvs,rank = l->rank;
  int            *rvalues,tag = A->tag,count,base,slen,n,*source;
  int            *lens,imdex,*lrows,*values,bs=l->bs,rstart_bs=l->rstart_bs;
  MPI_Comm       comm = A->comm;
  MPI_Request    *send_waits,*recv_waits;
  MPI_Status     recv_status,*send_status;
  IS             istmp;
  PetscTruth     localdiag;

  PetscFunctionBegin;
  ierr = ISGetSize(is,&N); CHKERRQ(ierr);
  ierr = ISGetIndices(is,&rows); CHKERRQ(ierr);

  /*  first count number of contributors to each processor */
  nprocs = (int *) PetscMalloc( 2*size*sizeof(int) ); CHKPTRQ(nprocs);
  PetscMemzero(nprocs,2*size*sizeof(int)); procs = nprocs + size;
  owner = (int *) PetscMalloc((N+1)*sizeof(int)); CHKPTRQ(owner); /* see note*/
  for ( i=0; i<N; i++ ) {
    idx = rows[i];
    found = 0;
    for ( j=0; j<size; j++ ) {
      if (idx >= owners[j]*bs && idx < owners[j+1]*bs) {
        nprocs[j]++; procs[j] = 1; owner[i] = j; found = 1; break;
      }
    }
    if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Index out of range");
  }
  nsends = 0;  for ( i=0; i<size; i++ ) { nsends += procs[i];}

  /* inform other processors of number of messages and max length*/
  work   = (int *) PetscMalloc( size*sizeof(int) ); CHKPTRQ(work);
  ierr   = MPI_Allreduce( procs, work,size,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr);
  nrecvs = work[rank];
  ierr   = MPI_Allreduce( nprocs, work,size,MPI_INT,MPI_MAX,comm);CHKERRQ(ierr);
  nmax   = work[rank];
  PetscFree(work);

  /* post receives:   */
  rvalues = (int *) PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int)); CHKPTRQ(rvalues);
  recv_waits = (MPI_Request *) PetscMalloc((nrecvs+1)*sizeof(MPI_Request));CHKPTRQ(recv_waits);
  for ( i=0; i<nrecvs; i++ ) {
    ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPI_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr);
  }

  /* do sends:
     1) starts[i] gives the starting index in svalues for stuff going to
     the ith processor
  */
  svalues = (int *) PetscMalloc( (N+1)*sizeof(int) ); CHKPTRQ(svalues);
  send_waits = (MPI_Request *) PetscMalloc( (nsends+1)*sizeof(MPI_Request));CHKPTRQ(send_waits);
  starts = (int *) PetscMalloc( (size+1)*sizeof(int) ); CHKPTRQ(starts);
  starts[0] = 0;
  for ( i=1; i<size; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];}
  for ( i=0; i<N; i++ ) {
    svalues[starts[owner[i]]++] = rows[i];
  }
  ISRestoreIndices(is,&rows);

  starts[0] = 0;
  for ( i=1; i<size+1; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];}
  count = 0;
  for ( i=0; i<size; i++ ) {
    if (procs[i]) {
      ierr = MPI_Isend(svalues+starts[i],nprocs[i],MPI_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr);
    }
  }
  PetscFree(starts);

  base = owners[rank]*bs;

  /*  wait on receives */
  lens   = (int *) PetscMalloc( 2*(nrecvs+1)*sizeof(int) ); CHKPTRQ(lens);
  source = lens + nrecvs;
  count  = nrecvs; slen = 0;
  while (count) {
    ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr);
    /* unpack receives into our local space */
    ierr = MPI_Get_count(&recv_status,MPI_INT,&n);CHKERRQ(ierr);
    source[imdex]  = recv_status.MPI_SOURCE;
    lens[imdex]  = n;
    slen += n;
    count--;
  }
  PetscFree(recv_waits);

  /* move the data into the send scatter */
  lrows = (int *) PetscMalloc( (slen+1)*sizeof(int) ); CHKPTRQ(lrows);
  count = 0;
  for ( i=0; i<nrecvs; i++ ) {
    values = rvalues + i*nmax;
    for ( j=0; j<lens[i]; j++ ) {
      lrows[count++] = values[j] - base;
    }
  }
  PetscFree(rvalues); PetscFree(lens);
  PetscFree(owner); PetscFree(nprocs);

  /* actually zap the local rows */
  ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr);
  PLogObjectParent(A,istmp);

  /*
        Zero the required rows. If the "diagonal block" of the matrix
     is square and the user wishes to set the diagonal we use seperate
     code so that MatSetValues() is not called for each diagonal allocating
     new memory, thus calling lots of mallocs and slowing things down.

       Contributed by: Mathew Knepley
  */
  localdiag = PETSC_FALSE;
  if (diag && (l->A->M == l->A->N)) {
    localdiag = PETSC_TRUE;
    ierr      = MatZeroRows(l->A,istmp,diag); CHKERRQ(ierr);
  } else {
    ierr = MatZeroRows(l->A,istmp,0); CHKERRQ(ierr);
  }
  ierr = MatZeroRows(l->B,istmp,0); CHKERRQ(ierr);
  ierr = ISDestroy(istmp); CHKERRQ(ierr);

  if (diag && (localdiag == PETSC_FALSE)) {
    for ( i = 0; i < slen; i++ ) {
      row = lrows[i] + rstart_bs;
      ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES); CHKERRQ(ierr);
    }
    ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr);
    ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr);
  }
  PetscFree(lrows);

  /* wait on sends */
  if (nsends) {
    send_status = (MPI_Status *) PetscMalloc(nsends*sizeof(MPI_Status));CHKPTRQ(send_status);
    ierr        = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr);
    PetscFree(send_status);
  }
  PetscFree(send_waits); PetscFree(svalues);

  PetscFunctionReturn(0);
}

extern int MatPrintHelp_SeqBAIJ(Mat);
#undef __FUNC__
#define __FUNC__ "MatPrintHelp_MPIBAIJ"
int MatPrintHelp_MPIBAIJ(Mat A)
{
  Mat_MPIBAIJ *a   = (Mat_MPIBAIJ*) A->data;
  MPI_Comm    comm = A->comm;
  static int  called = 0;
  int         ierr;

  PetscFunctionBegin;
  if (!a->rank) {
    ierr = MatPrintHelp_SeqBAIJ(a->A);CHKERRQ(ierr);
  }
  if (called) {PetscFunctionReturn(0);} else called = 1;
  (*PetscHelpPrintf)(comm," Options for MATMPIBAIJ matrix format (the defaults):\n");
  (*PetscHelpPrintf)(comm,"  -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatSetUnfactored_MPIBAIJ"
int MatSetUnfactored_MPIBAIJ(Mat A)
{
  Mat_MPIBAIJ *a   = (Mat_MPIBAIJ*) A->data;
  int         ierr;

  PetscFunctionBegin;
  ierr = MatSetUnfactored(a->A); CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

static int MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat *);

/* -------------------------------------------------------------------*/
static struct _MatOps MatOps_Values = {
  MatSetValues_MPIBAIJ,
  MatGetRow_MPIBAIJ,
  MatRestoreRow_MPIBAIJ,
  MatMult_MPIBAIJ,
  MatMultAdd_MPIBAIJ,
  MatMultTrans_MPIBAIJ,
  MatMultTransAdd_MPIBAIJ,
  0,
  0,
  0,
  0,
  0,
  0,
  0,
  MatTranspose_MPIBAIJ,
  MatGetInfo_MPIBAIJ,
  0,
  MatGetDiagonal_MPIBAIJ,
  MatDiagonalScale_MPIBAIJ,
  MatNorm_MPIBAIJ,
  MatAssemblyBegin_MPIBAIJ,
  MatAssemblyEnd_MPIBAIJ,
  0,
  MatSetOption_MPIBAIJ,
  MatZeroEntries_MPIBAIJ,
  MatZeroRows_MPIBAIJ,
  0,
  0,
  0,
  0,
  MatGetSize_MPIBAIJ,
  MatGetLocalSize_MPIBAIJ,
  MatGetOwnershipRange_MPIBAIJ,
  0,
  0,
  0,
  0,
  MatDuplicate_MPIBAIJ,
  0,
  0,
  0,
  0,
  0,
  MatGetSubMatrices_MPIBAIJ,
  MatIncreaseOverlap_MPIBAIJ,
  MatGetValues_MPIBAIJ,
  0,
  MatPrintHelp_MPIBAIJ,
  MatScale_MPIBAIJ,
  0,
  0,
  0,
  MatGetBlockSize_MPIBAIJ,
  0,
  0,
  0,
  0,
  0,
  0,
  MatSetUnfactored_MPIBAIJ,
  0,
  MatSetValuesBlocked_MPIBAIJ,
  0,
  0,
  0,
  MatGetMaps_Petsc};

#include "pc.h"
EXTERN_C_BEGIN
extern int PCSetUp_BJacobi_BAIJ(PC);
EXTERN_C_END

#undef __FUNC__
#define __FUNC__ "MatCreateMPIBAIJ"
/*@C
   MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format
   (block compressed row).  For good matrix assembly performance
   the user should preallocate the matrix storage by setting the parameters
   d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
   performance can be increased by more than a factor of 50.

   Collective on MPI_Comm

   Input Parameters:
+  comm - MPI communicator
.  bs   - size of blockk
.  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
           This value should be the same as the local size used in creating the
           y vector for the matrix-vector product y = Ax.
.  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
           This value should be the same as the local size used in creating the
           x vector for the matrix-vector product y = Ax.
.  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
.  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
.  d_nz  - number of block nonzeros per block row in diagonal portion of local
           submatrix  (same for all local rows)
.  d_nzz - array containing the number of block nonzeros in the various block rows
           of the in diagonal portion of the local (possibly different for each block
           row) or PETSC_NULL.  You must leave room for the diagonal entry even if it is zero.
.  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
           submatrix (same for all local rows).
-  o_nzz - array containing the number of nonzeros in the various block rows of the
           off-diagonal portion of the local submatrix (possibly different for
           each block row) or PETSC_NULL.

   Output Parameter:
.  A - the matrix

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

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

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

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

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

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

.vb
           0 1 2 3 4 5 6 7 8 9 10 11
          -------------------
   row 3  |  o o o d d d o o o o o o
   row 4  |  o o o d d d o o o o o o
   row 5  |  o o o d d d o o o o o o
          -------------------
.ve

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

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

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

.seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIAIJ()
@*/
int MatCreateMPIBAIJ(MPI_Comm comm,int bs,int m,int n,int M,int N,
                    int d_nz,int *d_nnz,int o_nz,int *o_nnz,Mat *A)
{
  Mat          B;
  Mat_MPIBAIJ  *b;
  int          ierr, i,sum[2],work[2],mbs,nbs,Mbs=PETSC_DECIDE,Nbs=PETSC_DECIDE,size,flg;
  int          flag1 = 0,flag2 = 0;

  PetscFunctionBegin;
  if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Invalid block size specified, must be positive");

  MPI_Comm_size(comm,&size);
  ierr = OptionsHasName(PETSC_NULL,"-mat_mpibaij",&flag1); CHKERRQ(ierr);
  ierr = OptionsHasName(PETSC_NULL,"-mat_mpi",&flag2); CHKERRQ(ierr);
  if (!flag1 && !flag2 && size == 1) {
    if (M == PETSC_DECIDE) M = m;
    if (N == PETSC_DECIDE) N = n;
    ierr = MatCreateSeqBAIJ(comm,bs,M,N,d_nz,d_nnz,A); CHKERRQ(ierr);
    PetscFunctionReturn(0);
  }

  *A = 0;
  PetscHeaderCreate(B,_p_Mat,struct _MatOps,MAT_COOKIE,MATMPIBAIJ,"Mat",comm,MatDestroy,MatView);
  PLogObjectCreate(B);
  B->data       = (void *) (b = PetscNew(Mat_MPIBAIJ)); CHKPTRQ(b);
  PetscMemzero(b,sizeof(Mat_MPIBAIJ));
  PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

  B->ops->destroy    = MatDestroy_MPIBAIJ;
  B->ops->view       = MatView_MPIBAIJ;
  B->mapping    = 0;
  B->factor     = 0;
  B->assembled  = PETSC_FALSE;

  B->insertmode = NOT_SET_VALUES;
  MPI_Comm_rank(comm,&b->rank);
  MPI_Comm_size(comm,&b->size);

  if ( m == PETSC_DECIDE && (d_nnz != PETSC_NULL || o_nnz != PETSC_NULL)) {
    SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Cannot have PETSC_DECIDE rows but set d_nnz or o_nnz");
  }
  if ( M == PETSC_DECIDE && m == PETSC_DECIDE) {
    SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"either M or m should be specified");
  }
  if ( N == PETSC_DECIDE && n == PETSC_DECIDE) {
    SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"either N or n should be specified");
  }
  if ( M != PETSC_DECIDE && m != PETSC_DECIDE) M = PETSC_DECIDE;
  if ( N != PETSC_DECIDE && n != PETSC_DECIDE) N = PETSC_DECIDE;

  if (M == PETSC_DECIDE || N == PETSC_DECIDE) {
    work[0] = m; work[1] = n;
    mbs = m/bs; nbs = n/bs;
    ierr = MPI_Allreduce( work, sum,2,MPI_INT,MPI_SUM,comm );CHKERRQ(ierr);
    if (M == PETSC_DECIDE) {M = sum[0]; Mbs = M/bs;}
    if (N == PETSC_DECIDE) {N = sum[1]; Nbs = N/bs;}
  }
  if (m == PETSC_DECIDE) {
    Mbs = M/bs;
    if (Mbs*bs != M) SETERRQ(PETSC_ERR_ARG_SIZ,0,"No of global rows must be divisible by blocksize");
    mbs = Mbs/b->size + ((Mbs % b->size) > b->rank);
    m   = mbs*bs;
  }
  if (n == PETSC_DECIDE) {
    Nbs = N/bs;
    if (Nbs*bs != N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"No of global cols must be divisible by blocksize");
    nbs = Nbs/b->size + ((Nbs % b->size) > b->rank);
    n   = nbs*bs;
  }
  if (mbs*bs != m || nbs*bs != n) {
    SETERRQ(PETSC_ERR_ARG_SIZ,0,"No of local rows, cols must be divisible by blocksize");
  }

  b->m = m; B->m = m;
  b->n = n; B->n = n;
  b->N = N; B->N = N;
  b->M = M; B->M = M;
  b->bs  = bs;
  b->bs2 = bs*bs;
  b->mbs = mbs;
  b->nbs = nbs;
  b->Mbs = Mbs;
  b->Nbs = Nbs;

  /* the information in the maps duplicates the information computed below, eventually
     we should remove the duplicate information that is not contained in the maps */
  ierr = MapCreateMPI(comm,m,M,&B->rmap);CHKERRQ(ierr);
  ierr = MapCreateMPI(comm,n,N,&B->cmap);CHKERRQ(ierr);

  /* build local table of row and column ownerships */
  b->rowners = (int *) PetscMalloc(2*(b->size+2)*sizeof(int)); CHKPTRQ(b->rowners);
  PLogObjectMemory(B,2*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIBAIJ));
  b->cowners = b->rowners + b->size + 2;
  ierr = MPI_Allgather(&mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,comm);CHKERRQ(ierr);
  b->rowners[0] = 0;
  for ( i=2; i<=b->size; i++ ) {
    b->rowners[i] += b->rowners[i-1];
  }
  b->rstart    = b->rowners[b->rank];
  b->rend      = b->rowners[b->rank+1];
  b->rstart_bs = b->rstart * bs;
  b->rend_bs   = b->rend * bs;

  ierr = MPI_Allgather(&nbs,1,MPI_INT,b->cowners+1,1,MPI_INT,comm);CHKERRQ(ierr);
  b->cowners[0] = 0;
  for ( i=2; i<=b->size; i++ ) {
    b->cowners[i] += b->cowners[i-1];
  }
  b->cstart    = b->cowners[b->rank];
  b->cend      = b->cowners[b->rank+1];
  b->cstart_bs = b->cstart * bs;
  b->cend_bs   = b->cend * bs;


  if (d_nz == PETSC_DEFAULT) d_nz = 5;
  ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,m,n,d_nz,d_nnz,&b->A); CHKERRQ(ierr);
  PLogObjectParent(B,b->A);
  if (o_nz == PETSC_DEFAULT) o_nz = 0;
  ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,m,N,o_nz,o_nnz,&b->B); CHKERRQ(ierr);
  PLogObjectParent(B,b->B);

  /* build cache for off array entries formed */
  ierr = StashBuild_Private(&b->stash); CHKERRQ(ierr);
  b->donotstash  = 0;
  b->colmap      = 0;
  b->garray      = 0;
  b->roworiented = 1;

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

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

  /* stuff for MatGetRow() */
  b->rowindices   = 0;
  b->rowvalues    = 0;
  b->getrowactive = PETSC_FALSE;

  /* hash table stuff */
  b->ht           = 0;
  b->hd           = 0;
  b->ht_size      = 0;
  b->ht_flag      = 0;
  b->ht_fact      = 0;
  b->ht_total_ct  = 0;
  b->ht_insert_ct = 0;

  *A = B;
  ierr = OptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg); CHKERRQ(ierr);
  if (flg) {
    double fact = 1.39;
    ierr = MatSetOption(B,MAT_USE_HASH_TABLE); CHKERRQ(ierr);
    ierr = OptionsGetDouble(PETSC_NULL,"-mat_use_hash_table",&fact,&flg); CHKERRQ(ierr);
    if (fact <= 1.0) fact = 1.39;
    ierr = MatMPIBAIJSetHashTableFactor(B,fact); CHKERRQ(ierr);
    PLogInfo(0,"MatCreateMPIBAIJ:Hash table Factor used %5.2f\n",fact);
  }
  ierr = PetscObjectComposeFunction((PetscObject)B,"PCSetUp_BJacobi_C",
                                     "PCSetUp_BJacobi_BAIJ",
                                     (void*)PCSetUp_BJacobi_BAIJ);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__
#define __FUNC__ "MatDuplicate_MPIBAIJ"
static int MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
{
  Mat         mat;
  Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ *) matin->data;
  int         ierr, len=0, flg;

  PetscFunctionBegin;
  *newmat       = 0;
  PetscHeaderCreate(mat,_p_Mat,struct _MatOps,MAT_COOKIE,MATMPIBAIJ,"Mat",matin->comm,MatDestroy,MatView);
  PLogObjectCreate(mat);
  mat->data       = (void *) (a = PetscNew(Mat_MPIBAIJ)); CHKPTRQ(a);
  PetscMemcpy(mat->ops,&MatOps_Values,sizeof(struct _MatOps));
  mat->ops->destroy    = MatDestroy_MPIBAIJ;
  mat->ops->view       = MatView_MPIBAIJ;
  mat->factor          = matin->factor;
  mat->assembled       = PETSC_TRUE;

  a->m = mat->m   = oldmat->m;
  a->n = mat->n   = oldmat->n;
  a->M = mat->M   = oldmat->M;
  a->N = mat->N   = oldmat->N;

  a->bs  = oldmat->bs;
  a->bs2 = oldmat->bs2;
  a->mbs = oldmat->mbs;
  a->nbs = oldmat->nbs;
  a->Mbs = oldmat->Mbs;
  a->Nbs = oldmat->Nbs;

  a->rstart       = oldmat->rstart;
  a->rend         = oldmat->rend;
  a->cstart       = oldmat->cstart;
  a->cend         = oldmat->cend;
  a->size         = oldmat->size;
  a->rank         = oldmat->rank;
  mat->insertmode = NOT_SET_VALUES;
  a->rowvalues    = 0;
  a->getrowactive = PETSC_FALSE;
  a->barray       = 0;

  /* hash table stuff */
  a->ht           = 0;
  a->hd           = 0;
  a->ht_size      = 0;
  a->ht_flag      = oldmat->ht_flag;
  a->ht_fact      = oldmat->ht_fact;
  a->ht_total_ct  = 0;
  a->ht_insert_ct = 0;


  a->rowners = (int *) PetscMalloc(2*(a->size+2)*sizeof(int)); CHKPTRQ(a->rowners);
  PLogObjectMemory(mat,2*(a->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIBAIJ));
  a->cowners = a->rowners + a->size + 2;
  PetscMemcpy(a->rowners,oldmat->rowners,2*(a->size+2)*sizeof(int));
  ierr = StashInitialize_Private(&a->stash); CHKERRQ(ierr);
  if (oldmat->colmap) {
    a->colmap = (int *) PetscMalloc((a->Nbs)*sizeof(int));CHKPTRQ(a->colmap);
    PLogObjectMemory(mat,(a->Nbs)*sizeof(int));
    PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));
  } else a->colmap = 0;
  if (oldmat->garray && (len = ((Mat_SeqBAIJ *) (oldmat->B->data))->nbs)) {
    a->garray = (int *) PetscMalloc(len*sizeof(int)); CHKPTRQ(a->garray);
    PLogObjectMemory(mat,len*sizeof(int));
    PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));
  } else a->garray = 0;

  ierr =  VecDuplicate(oldmat->lvec,&a->lvec); CHKERRQ(ierr);
  PLogObjectParent(mat,a->lvec);
  ierr =  VecScatterCopy(oldmat->Mvctx,&a->Mvctx); CHKERRQ(ierr);

  PLogObjectParent(mat,a->Mvctx);
  ierr =  MatDuplicate(oldmat->A,cpvalues,&a->A); CHKERRQ(ierr);
  PLogObjectParent(mat,a->A);
  ierr =  MatDuplicate(oldmat->B,cpvalues,&a->B); CHKERRQ(ierr);
  PLogObjectParent(mat,a->B);
  ierr = OptionsHasName(PETSC_NULL,"-help",&flg); CHKERRQ(ierr);
  ierr = FListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr);
  if (flg) {
    ierr = MatPrintHelp(mat); CHKERRQ(ierr);
  }
  *newmat = mat;
  PetscFunctionReturn(0);
}

#include "sys.h"

#undef __FUNC__
#define __FUNC__ "MatLoad_MPIBAIJ"
int MatLoad_MPIBAIJ(Viewer viewer,MatType type,Mat *newmat)
{
  Mat          A;
  int          i, nz, ierr, j,rstart, rend, fd;
  Scalar       *vals,*buf;
  MPI_Comm     comm = ((PetscObject)viewer)->comm;
  MPI_Status   status;
  int          header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols;
  int          *locrowlens,*sndcounts = 0,*procsnz = 0, jj,*mycols,*ibuf;
  int          flg,tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows;
  int          *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount;
  int          dcount,kmax,k,nzcount,tmp;

  PetscFunctionBegin;
  ierr = OptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,&flg);CHKERRQ(ierr);

  MPI_Comm_size(comm,&size); MPI_Comm_rank(comm,&rank);
  if (!rank) {
    ierr = ViewerBinaryGetDescriptor(viewer,&fd); CHKERRQ(ierr);
    ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT); CHKERRQ(ierr);
    if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,0,"not matrix object");
    if (header[3] < 0) {
      SETERRQ(PETSC_ERR_FILE_UNEXPECTED,1,"Matrix stored in special format, cannot load as MPIBAIJ");
    }
  }

  ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr);
  M = header[1]; N = header[2];

  if (M != N) SETERRQ(PETSC_ERR_SUP,0,"Can only do square matrices");

  /*
     This code adds extra rows to make sure the number of rows is
     divisible by the blocksize
  */
  Mbs        = M/bs;
  extra_rows = bs - M + bs*(Mbs);
  if (extra_rows == bs) extra_rows = 0;
  else                  Mbs++;
  if (extra_rows &&!rank) {
    PLogInfo(0,"MatLoad_MPIBAIJ:Padding loaded matrix to match blocksize\n");
  }

  /* determine ownership of all rows */
  mbs = Mbs/size + ((Mbs % size) > rank);
  m   = mbs * bs;
  rowners = (int *) PetscMalloc(2*(size+2)*sizeof(int)); CHKPTRQ(rowners);
  browners = rowners + size + 1;
  ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr);
  rowners[0] = 0;
  for ( i=2; i<=size; i++ ) rowners[i] += rowners[i-1];
  for ( i=0; i<=size;  i++ ) browners[i] = rowners[i]*bs;
  rstart = rowners[rank];
  rend   = rowners[rank+1];

  /* distribute row lengths to all processors */
  locrowlens = (int*) PetscMalloc( (rend-rstart)*bs*sizeof(int) ); CHKPTRQ(locrowlens);
  if (!rank) {
    rowlengths = (int*) PetscMalloc( (M+extra_rows)*sizeof(int) ); CHKPTRQ(rowlengths);
    ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT); CHKERRQ(ierr);
    for ( i=0; i<extra_rows; i++ ) rowlengths[M+i] = 1;
    sndcounts = (int*) PetscMalloc( size*sizeof(int) ); CHKPTRQ(sndcounts);
    for ( i=0; i<size; i++ ) sndcounts[i] = browners[i+1] - browners[i];
    ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr);
    PetscFree(sndcounts);
  } else {
    ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT, 0,comm);CHKERRQ(ierr);
  }

  if (!rank) {
    /* calculate the number of nonzeros on each processor */
    procsnz = (int*) PetscMalloc( size*sizeof(int) ); CHKPTRQ(procsnz);
    PetscMemzero(procsnz,size*sizeof(int));
    for ( i=0; i<size; i++ ) {
      for ( j=rowners[i]*bs; j< rowners[i+1]*bs; j++ ) {
        procsnz[i] += rowlengths[j];
      }
    }
    PetscFree(rowlengths);

    /* determine max buffer needed and allocate it */
    maxnz = 0;
    for ( i=0; i<size; i++ ) {
      maxnz = PetscMax(maxnz,procsnz[i]);
    }
    cols = (int *) PetscMalloc( maxnz*sizeof(int) ); CHKPTRQ(cols);

    /* read in my part of the matrix column indices  */
    nz = procsnz[0];
    ibuf = (int *) PetscMalloc( nz*sizeof(int) ); CHKPTRQ(ibuf);
    mycols = ibuf;
    if (size == 1)  nz -= extra_rows;
    ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT); CHKERRQ(ierr);
    if (size == 1)  for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; }

    /* read in every ones (except the last) and ship off */
    for ( i=1; i<size-1; i++ ) {
      nz   = procsnz[i];
      ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT); CHKERRQ(ierr);
      ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr);
    }
    /* read in the stuff for the last proc */
    if ( size != 1 ) {
      nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
      ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT); CHKERRQ(ierr);
      for ( i=0; i<extra_rows; i++ ) cols[nz+i] = M+i;
      ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr);
    }
    PetscFree(cols);
  } else {
    /* determine buffer space needed for message */
    nz = 0;
    for ( i=0; i<m; i++ ) {
      nz += locrowlens[i];
    }
    ibuf   = (int*) PetscMalloc( nz*sizeof(int) ); CHKPTRQ(ibuf);
    mycols = ibuf;
    /* receive message of column indices*/
    ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr);
    ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr);
    if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,0,"something is wrong with file");
  }

  /* loop over local rows, determining number of off diagonal entries */
  dlens  = (int *) PetscMalloc( 2*(rend-rstart+1)*sizeof(int) ); CHKPTRQ(dlens);
  odlens = dlens + (rend-rstart);
  mask   = (int *) PetscMalloc( 3*Mbs*sizeof(int) ); CHKPTRQ(mask);
  PetscMemzero(mask,3*Mbs*sizeof(int));
  masked1 = mask    + Mbs;
  masked2 = masked1 + Mbs;
  rowcount = 0; nzcount = 0;
  for ( i=0; i<mbs; i++ ) {
    dcount  = 0;
    odcount = 0;
    for ( j=0; j<bs; j++ ) {
      kmax = locrowlens[rowcount];
      for ( k=0; k<kmax; k++ ) {
        tmp = mycols[nzcount++]/bs;
        if (!mask[tmp]) {
          mask[tmp] = 1;
          if (tmp < rstart || tmp >= rend ) masked2[odcount++] = tmp;
          else masked1[dcount++] = tmp;
        }
      }
      rowcount++;
    }

    dlens[i]  = dcount;
    odlens[i] = odcount;

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

  /* create our matrix */
  ierr = MatCreateMPIBAIJ(comm,bs,m,PETSC_DECIDE,M+extra_rows,N+extra_rows,0,dlens,0,odlens,newmat);
         CHKERRQ(ierr);
  A = *newmat;
  MatSetOption(A,MAT_COLUMNS_SORTED);

  if (!rank) {
    buf = (Scalar *) PetscMalloc( maxnz*sizeof(Scalar) ); CHKPTRQ(buf);
    /* read in my part of the matrix numerical values  */
    nz = procsnz[0];
    vals = buf;
    mycols = ibuf;
    if (size == 1)  nz -= extra_rows;
    ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR); CHKERRQ(ierr);
    if (size == 1)  for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; }

    /* insert into matrix */
    jj      = rstart*bs;
    for ( i=0; i<m; i++ ) {
      ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr);
      mycols += locrowlens[i];
      vals   += locrowlens[i];
      jj++;
    }
    /* read in other processors (except the last one) and ship out */
    for ( i=1; i<size-1; i++ ) {
      nz   = procsnz[i];
      vals = buf;
      ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR); CHKERRQ(ierr);
      ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr);
    }
    /* the last proc */
    if ( size != 1 ){
      nz   = procsnz[i] - extra_rows;
      vals = buf;
      ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR); CHKERRQ(ierr);
      for ( i=0; i<extra_rows; i++ ) vals[nz+i] = 1.0;
      ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr);
    }
    PetscFree(procsnz);
  } else {
    /* receive numeric values */
    buf = (Scalar*) PetscMalloc( nz*sizeof(Scalar) ); CHKPTRQ(buf);

    /* receive message of values*/
    vals   = buf;
    mycols = ibuf;
    ierr   = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr);
    ierr   = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr);
    if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,0,"something is wrong with file");

    /* insert into matrix */
    jj      = rstart*bs;
    for ( i=0; i<m; i++ ) {
      ierr    = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr);
      mycols += locrowlens[i];
      vals   += locrowlens[i];
      jj++;
    }
  }
  PetscFree(locrowlens);
  PetscFree(buf);
  PetscFree(ibuf);
  PetscFree(rowners);
  PetscFree(dlens);
  PetscFree(mask);
  ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr);
  ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr);
  PetscFunctionReturn(0);
}



#undef __FUNC__
#define __FUNC__ "MatMPIBAIJSetHashTableFactor"
/*@
   MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.

   Input Parameters:
.  mat  - the matrix
.  fact - factor

   Collective on Mat

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

.keywords: matrix, hashtable, factor, HT

.seealso: MatSetOption()
@*/
int MatMPIBAIJSetHashTableFactor(Mat mat,double fact)
{
  Mat_MPIBAIJ *baij;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (mat->type != MATMPIBAIJ) {
      SETERRQ(PETSC_ERR_ARG_WRONG,1,"Incorrect matrix type. Use MPIBAIJ only.");
  }
  baij = (Mat_MPIBAIJ*) mat->data;
  baij->ht_fact = fact;
  PetscFunctionReturn(0);
}