xref: /petsc/src/mat/impls/baij/mpi/mpibaij.c (revision 552e946dff8b2ae7436438151a141131988ba1d9)

/*$Id: mpibaij.c,v 1.234 2001/09/25 22:56:49 balay Exp $*/

#include "src/mat/impls/baij/mpi/mpibaij.h"   /*I  "petscmat.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 *,MatReuse,Mat **);
EXTERN int MatGetValues_SeqBAIJ(Mat,int,int *,int,int *,PetscScalar *);
EXTERN int MatSetValues_SeqBAIJ(Mat,int,int *,int,int *,PetscScalar *,InsertMode);
EXTERN int MatSetValuesBlocked_SeqBAIJ(Mat,int,int*,int,int*,PetscScalar*,InsertMode);
EXTERN int MatGetRow_SeqBAIJ(Mat,int,int*,int**,PetscScalar**);
EXTERN int MatRestoreRow_SeqBAIJ(Mat,int,int*,int**,PetscScalar**);
EXTERN int MatPrintHelp_SeqBAIJ(Mat);
EXTERN int MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar*);

/*  UGLY, ugly, ugly
   When MatScalar == PetscScalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does
   not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and
   inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ()
   converts the entries into single precision and then calls ..._MatScalar() to put them
   into the single precision data structures.
*/
#if defined(PETSC_USE_MAT_SINGLE)
EXTERN int MatSetValuesBlocked_SeqBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode);
EXTERN int MatSetValues_MPIBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode);
EXTERN int MatSetValuesBlocked_MPIBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode);
EXTERN int MatSetValues_MPIBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode);
EXTERN int MatSetValuesBlocked_MPIBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode);
#else
#define MatSetValuesBlocked_SeqBAIJ_MatScalar      MatSetValuesBlocked_SeqBAIJ
#define MatSetValues_MPIBAIJ_MatScalar             MatSetValues_MPIBAIJ
#define MatSetValuesBlocked_MPIBAIJ_MatScalar      MatSetValuesBlocked_MPIBAIJ
#define MatSetValues_MPIBAIJ_HT_MatScalar          MatSetValues_MPIBAIJ_HT
#define MatSetValuesBlocked_MPIBAIJ_HT_MatScalar   MatSetValuesBlocked_MPIBAIJ_HT
#endif

#undef __FUNCT__
#define __FUNCT__ "MatGetRowMax_MPIBAIJ"
int MatGetRowMax_MPIBAIJ(Mat A,Vec v)
{
  Mat_MPIBAIJ  *a = (Mat_MPIBAIJ*)A->data;
  int          ierr,i;
  PetscScalar  *va,*vb;
  Vec          vtmp;

  PetscFunctionBegin;

  ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr);
  ierr = VecGetArray(v,&va);CHKERRQ(ierr);

  ierr = VecCreateSeq(PETSC_COMM_SELF,A->m,&vtmp);CHKERRQ(ierr);
  ierr = MatGetRowMax(a->B,vtmp);CHKERRQ(ierr);
  ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr);

  for (i=0; i<A->m; i++){
    if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) va[i] = vb[i];
  }

  ierr = VecRestoreArray(v,&va);CHKERRQ(ierr);
  ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr);
  ierr = VecDestroy(vtmp);CHKERRQ(ierr);

  PetscFunctionReturn(0);
}

EXTERN_C_BEGIN
#undef __FUNCT__
#define __FUNCT__ "MatStoreValues_MPIBAIJ"
int MatStoreValues_MPIBAIJ(Mat mat)
{
  Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data;
  int         ierr;

  PetscFunctionBegin;
  ierr = MatStoreValues(aij->A);CHKERRQ(ierr);
  ierr = MatStoreValues(aij->B);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}
EXTERN_C_END

EXTERN_C_BEGIN
#undef __FUNCT__
#define __FUNCT__ "MatRetrieveValues_MPIBAIJ"
int MatRetrieveValues_MPIBAIJ(Mat mat)
{
  Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data;
  int         ierr;

  PetscFunctionBegin;
  ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr);
  ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}
EXTERN_C_END

/*
     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 __FUNCT__
#define __FUNCT__ "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,ierr;

  PetscFunctionBegin;
#if defined (PETSC_USE_CTABLE)
  ierr = PetscTableCreate(baij->nbs,&baij->colmap);CHKERRQ(ierr);
  for (i=0; i<nbs; i++){
    ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1);CHKERRQ(ierr);
  }
#else
  ierr = PetscMalloc((baij->Nbs+1)*sizeof(int),&baij->colmap);CHKERRQ(ierr);
  PetscLogObjectMemory(mat,baij->Nbs*sizeof(int));
  ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(int));CHKERRQ(ierr);
  for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1;
#endif
  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,"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; \
        MatScalar *new_a; \
 \
        if (a->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \
 \
        /* malloc new storage space */ \
        len     = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(int); \
        ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \
        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;} \
        ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \
        len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \
        ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \
        ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \
        ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(PetscScalar));CHKERRQ(ierr); \
        ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \
                    aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr);  \
        /* free up old matrix storage */ \
        ierr = PetscFree(a->a);CHKERRQ(ierr);  \
        if (!a->singlemalloc) { \
          ierr = PetscFree(a->i);CHKERRQ(ierr); \
          ierr = PetscFree(a->j);CHKERRQ(ierr);\
        } \
        aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j;  \
        a->singlemalloc = PETSC_TRUE; \
 \
        rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
        rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \
        PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \
        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]; \
        ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \
      } \
      if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); }  \
      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,"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; \
        MatScalar *new_a; \
 \
        if (b->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \
 \
        /* malloc new storage space */ \
        len     = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(b->mbs+1)*sizeof(int); \
        ierr    = PetscMalloc(len,&new_a);CHKERRQ(ierr); \
        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;} \
        ierr = PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \
        len  = (new_nz - CHUNKSIZE - bi[brow] - nrow); \
        ierr = PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \
        ierr = PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \
        ierr = PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); \
        ierr = PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \
                    ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr);  \
        /* free up old matrix storage */ \
        ierr = PetscFree(b->a);CHKERRQ(ierr);  \
        if (!b->singlemalloc) { \
          ierr = PetscFree(b->i);CHKERRQ(ierr); \
          ierr = PetscFree(b->j);CHKERRQ(ierr); \
        } \
        ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j;  \
        b->singlemalloc = PETSC_TRUE; \
 \
        rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
        rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \
        PetscLogObjectMemory(B,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \
        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]; \
        ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \
      } \
      if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);}  \
      rp[_i]                      = bcol;  \
      ap[bs2*_i + bs*cidx + ridx] = value;  \
      b_noinsert:; \
    bilen[brow] = nrow; \
}

#if defined(PETSC_USE_MAT_SINGLE)
#undef __FUNCT__
#define __FUNCT__ "MatSetValues_MPIBAIJ"
int MatSetValues_MPIBAIJ(Mat mat,int m,int *im,int n,int *in,PetscScalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data;
  int         ierr,i,N = m*n;
  MatScalar   *vsingle;

  PetscFunctionBegin;
  if (N > b->setvalueslen) {
    if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);}
    ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr);
    b->setvalueslen  = N;
  }
  vsingle = b->setvaluescopy;

  for (i=0; i<N; i++) {
    vsingle[i] = v[i];
  }
  ierr = MatSetValues_MPIBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ"
int MatSetValuesBlocked_MPIBAIJ(Mat mat,int m,int *im,int n,int *in,PetscScalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data;
  int         ierr,i,N = m*n*b->bs2;
  MatScalar   *vsingle;

  PetscFunctionBegin;
  if (N > b->setvalueslen) {
    if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);}
    ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr);
    b->setvalueslen  = N;
  }
  vsingle = b->setvaluescopy;
  for (i=0; i<N; i++) {
    vsingle[i] = v[i];
  }
  ierr = MatSetValuesBlocked_MPIBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatSetValues_MPIBAIJ_HT"
int MatSetValues_MPIBAIJ_HT(Mat mat,int m,int *im,int n,int *in,PetscScalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data;
  int         ierr,i,N = m*n;
  MatScalar   *vsingle;

  PetscFunctionBegin;
  if (N > b->setvalueslen) {
    if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);}
    ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr);
    b->setvalueslen  = N;
  }
  vsingle = b->setvaluescopy;
  for (i=0; i<N; i++) {
    vsingle[i] = v[i];
  }
  ierr = MatSetValues_MPIBAIJ_HT_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT"
int MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,int m,int *im,int n,int *in,PetscScalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data;
  int         ierr,i,N = m*n*b->bs2;
  MatScalar   *vsingle;

  PetscFunctionBegin;
  if (N > b->setvalueslen) {
    if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);}
    ierr = PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);CHKERRQ(ierr);
    b->setvalueslen  = N;
  }
  vsingle = b->setvaluescopy;
  for (i=0; i<N; i++) {
    vsingle[i] = v[i];
  }
  ierr = MatSetValuesBlocked_MPIBAIJ_HT_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}
#endif

#undef __FUNCT__
#define __FUNCT__ "MatSetValues_MPIBAIJ"
int MatSetValues_MPIBAIJ_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;
  MatScalar   value;
  PetscTruth  roworiented = baij->roworiented;
  int         ierr,i,j,row,col;
  int         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;
  MatScalar   *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;
  MatScalar   *ba=b->a;

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

  PetscFunctionBegin;
  for (i=0; i<m; i++) {
    if (im[i] < 0) continue;
#if defined(PETSC_USE_BOPT_g)
    if (im[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"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); */
        } else if (in[j] < 0) continue;
#if defined(PETSC_USE_BOPT_g)
        else if (in[j] >= mat->N) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large");}
#endif
        else {
          if (mat->was_assembled) {
            if (!baij->colmap) {
              ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
            }
#if defined (PETSC_USE_CTABLE)
            ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr);
            col  = col - 1;
#else
            col = baij->colmap[in[j]/bs] - 1;
#endif
            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]%bs;
          } 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 (!baij->donotstash) {
        if (roworiented) {
          ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr);
        } else {
          ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr);
        }
      }
    }
  }
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_MatScalar"
int MatSetValuesBlocked_MPIBAIJ_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;
  MatScalar   *value,*barray=baij->barray;
  PetscTruth  roworiented = baij->roworiented;
  int         ierr,i,j,ii,jj,row,col,rstart=baij->rstart;
  int         rend=baij->rend,cstart=baij->cstart,stepval;
  int         cend=baij->cend,bs=baij->bs,bs2=baij->bs2;

  PetscFunctionBegin;
  if(!barray) {
    ierr         = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr);
    baij->barray = barray;
  }

  if (roworiented) {
    stepval = (n-1)*bs;
  } else {
    stepval = (m-1)*bs;
  }
  for (i=0; i<m; i++) {
    if (im[i] < 0) continue;
#if defined(PETSC_USE_BOPT_g)
    if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %d max %d",im[i],baij->Mbs);
#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_MatScalar(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
        }
        else if (in[j] < 0) continue;
#if defined(PETSC_USE_BOPT_g)
        else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %d max %d",in[j],baij->Nbs);}
#endif
        else {
          if (mat->was_assembled) {
            if (!baij->colmap) {
              ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
            }

#if defined(PETSC_USE_BOPT_g)
#if defined (PETSC_USE_CTABLE)
            { int data;
              ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr);
              if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap");
            }
#else
            if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap");
#endif
#endif
#if defined (PETSC_USE_CTABLE)
	    ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr);
            col  = (col - 1)/bs;
#else
            col = (baij->colmap[in[j]] - 1)/bs;
#endif
            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_MatScalar(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
        }
      }
    } else {
      if (!baij->donotstash) {
        if (roworiented) {
          ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
        } else {
          ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
        }
      }
    }
  }
  PetscFunctionReturn(0);
}

#define HASH_KEY 0.6180339887
#define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(int)((size)*(tmp-(int)tmp)))
/* #define HASH(size,key) ((int)((size)*fmod(((key)*HASH_KEY),1))) */
/* #define HASH(size,key,tmp) ((int)((size)*fmod(((key)*HASH_KEY),1))) */
#undef __FUNCT__
#define __FUNCT__ "MatSetValues_MPIBAIJ_HT_MatScalar"
int MatSetValues_MPIBAIJ_HT_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;
  PetscTruth  roworiented = baij->roworiented;
  int         ierr,i,j,row,col;
  int         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;
  PetscReal   tmp;
  MatScalar   **HD = baij->hd,value;
#if defined(PETSC_USE_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(PETSC_USE_BOPT_g)
    if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row");
    if (im[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"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(PETSC_USE_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,"(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,"(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 (!baij->donotstash) {
        if (roworiented) {
          ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr);
        } else {
          ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr);
        }
      }
    }
  }
#if defined(PETSC_USE_BOPT_g)
  baij->ht_total_ct = total_ct;
  baij->ht_insert_ct = insert_ct;
#endif
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT_MatScalar"
int MatSetValuesBlocked_MPIBAIJ_HT_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;
  PetscTruth  roworiented = baij->roworiented;
  int         ierr,i,j,ii,jj,row,col;
  int         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;
  PetscReal   tmp;
  MatScalar   **HD = baij->hd,*baij_a;
  MatScalar   *v_t,*value;
#if defined(PETSC_USE_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(PETSC_USE_BOPT_g)
    if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row");
    if (im[i] >= baij->Mbs) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"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(PETSC_USE_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,"(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,"(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) {
          ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
        } else {
          ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
        }
      }
    }
  }
#if defined(PETSC_USE_BOPT_g)
  baij->ht_total_ct = total_ct;
  baij->ht_insert_ct = insert_ct;
#endif
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatGetValues_MPIBAIJ"
int MatGetValues_MPIBAIJ(Mat mat,int m,int *idxm,int n,int *idxn,PetscScalar *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,data;

  PetscFunctionBegin;
  for (i=0; i<m; i++) {
    if (idxm[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row");
    if (idxm[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"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,"Negative column");
        if (idxn[j] >= mat->N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"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 defined (PETSC_USE_CTABLE)
          ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr);
          data --;
#else
          data = baij->colmap[idxn[j]/bs]-1;
#endif
          if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
          else {
            col  = data + idxn[j]%bs;
            ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr);
          }
        }
      }
    } else {
      SETERRQ(PETSC_ERR_SUP,"Only local values currently supported");
    }
  }
 PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatNorm_MPIBAIJ"
int MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *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;
  PetscReal  sum = 0.0;
  MatScalar  *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(PETSC_USE_COMPLEX)
        sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
#else
        sum += (*v)*(*v); v++;
#endif
      }
      v = bmat->a;
      for (i=0; i<bmat->nz*bs2; i++) {
#if defined(PETSC_USE_COMPLEX)
        sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
#else
        sum += (*v)*(*v); v++;
#endif
      }
      ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr);
      *norm = sqrt(*norm);
    } else {
      SETERRQ(PETSC_ERR_SUP,"No support for this norm yet");
    }
  }
  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 __FUNCT__
#define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private"
int MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal 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,ierr;
  int         cstart=baij->cstart,*garray=baij->garray,row,col,Nbs=baij->Nbs;
  int         *HT,key;
  MatScalar   **HD;
  PetscReal   tmp;
#if defined(PETSC_USE_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 */
  ierr     = PetscMalloc((size)*(sizeof(int)+sizeof(MatScalar*))+1,&baij->hd);CHKERRQ(ierr);
  baij->ht = (int*)(baij->hd + size);
  HD       = baij->hd;
  HT       = baij->ht;


  ierr = PetscMemzero(HD,size*(sizeof(int)+sizeof(PetscScalar*)));CHKERRQ(ierr);


  /* 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(PETSC_USE_BOPT_g)
        } else {
          ct++;
#endif
        }
      }
#if defined(PETSC_USE_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(PETSC_USE_BOPT_g)
        } else {
          ct++;
#endif
        }
      }
#if defined(PETSC_USE_BOPT_g)
      if (k> max) max = k;
#endif
    }
  }

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

#undef __FUNCT__
#define __FUNCT__ "MatAssemblyBegin_MPIBAIJ"
int MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;
  int         ierr,nstash,reallocs;
  InsertMode  addv;

  PetscFunctionBegin;
  if (baij->donotstash) {
    PetscFunctionReturn(0);
  }

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

  ierr = MatStashScatterBegin_Private(&mat->stash,baij->rowners_bs);CHKERRQ(ierr);
  ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rowners);CHKERRQ(ierr);
  ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr);
  PetscLogInfo(0,"MatAssemblyBegin_MPIBAIJ:Stash has %d entries,uses %d mallocs.\n",nstash,reallocs);
  ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr);
  PetscLogInfo(0,"MatAssemblyBegin_MPIBAIJ:Block-Stash has %d entries, uses %d mallocs.\n",nstash,reallocs);
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatAssemblyEnd_MPIBAIJ"
int MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode)
{
  Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data;
  Mat_SeqBAIJ *a=(Mat_SeqBAIJ*)baij->A->data,*b=(Mat_SeqBAIJ*)baij->B->data;
  int         i,j,rstart,ncols,n,ierr,flg,bs2=baij->bs2;
  int         *row,*col,other_disassembled;
  PetscTruth  r1,r2,r3;
  MatScalar   *val;
  InsertMode  addv = mat->insertmode;

  PetscFunctionBegin;
  if (!baij->donotstash) {
    while (1) {
      ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr);
      if (!flg) break;

      for (i=0; i<n;) {
        /* Now identify the consecutive vals belonging to the same row */
        for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; }
        if (j < n) ncols = j-i;
        else       ncols = n-i;
        /* Now assemble all these values with a single function call */
        ierr = MatSetValues_MPIBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr);
        i = j;
      }
    }
    ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr);
    /* Now process the block-stash. Since the values are stashed column-oriented,
       set the roworiented flag to column oriented, and after MatSetValues()
       restore the original flags */
    r1 = baij->roworiented;
    r2 = a->roworiented;
    r3 = b->roworiented;
    baij->roworiented = PETSC_FALSE;
    a->roworiented    = PETSC_FALSE;
    b->roworiented    = PETSC_FALSE;
    while (1) {
      ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr);
      if (!flg) break;

      for (i=0; i<n;) {
        /* Now identify the consecutive vals belonging to the same row */
        for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; }
        if (j < n) ncols = j-i;
        else       ncols = n-i;
        ierr = MatSetValuesBlocked_MPIBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr);
        i = j;
      }
    }
    ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr);
    baij->roworiented = r1;
    a->roworiented    = r2;
    b->roworiented    = r3;
  }

  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(PETSC_USE_BOPT_g)
  if (baij->ht && mode== MAT_FINAL_ASSEMBLY) {
    PetscLogInfo(0,"MatAssemblyEnd_MPIBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)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) {
    ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);
    baij->rowvalues = 0;
  }
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket"
static int MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
{
  Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
  int               ierr,bs = baij->bs,size = baij->size,rank = baij->rank;
  PetscTruth        isascii,isdraw;
  PetscViewer       sviewer;
  PetscViewerFormat format;

  PetscFunctionBegin;
  ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr);
  ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr);
  if (isascii) {
    ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
    if (format == PETSC_VIEWER_ASCII_INFO_LONG) {
      MatInfo info;
      ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr);
      ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr);
      ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n",
              rank,mat->m,(int)info.nz_used*bs,(int)info.nz_allocated*bs,
              baij->bs,(int)info.memory);CHKERRQ(ierr);
      ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr);
      ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr);
      ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr);
      ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr);
      ierr = PetscViewerFlush(viewer);CHKERRQ(ierr);
      ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr);
      PetscFunctionReturn(0);
    } else if (format == PETSC_VIEWER_ASCII_INFO) {
      ierr = PetscViewerASCIIPrintf(viewer,"  block size is %d\n",bs);CHKERRQ(ierr);
      PetscFunctionReturn(0);
    }
  }

  if (isdraw) {
    PetscDraw       draw;
    PetscTruth isnull;
    ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr);
    ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0);
  }

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

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

    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_MPIBAIJ_MatScalar(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_MPIBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr);
          col++; a += bs;
        }
      }
    }
    ierr = PetscFree(rvals);CHKERRQ(ierr);
    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 PetscDraw object
    */
    ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr);
    if (!rank) {
      ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr);
      ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr);
    }
    ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr);
    ierr = MatDestroy(A);CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatView_MPIBAIJ"
int MatView_MPIBAIJ(Mat mat,PetscViewer viewer)
{
  int        ierr;
  PetscTruth isascii,isdraw,issocket,isbinary;

  PetscFunctionBegin;
  ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr);
  ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr);
  ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr);
  ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr);
  if (isascii || isdraw || issocket || isbinary) {
    ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr);
  } else {
    SETERRQ1(1,"Viewer type %s not supported by MPIBAIJ matrices",((PetscObject)viewer)->type_name);
  }
  PetscFunctionReturn(0);
}

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

  PetscFunctionBegin;
#if defined(PETSC_USE_LOG)
  PetscLogObjectState((PetscObject)mat,"Rows=%d,Cols=%d",mat->M,mat->N);
#endif
  ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr);
  ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr);
  ierr = PetscFree(baij->rowners);CHKERRQ(ierr);
  ierr = MatDestroy(baij->A);CHKERRQ(ierr);
  ierr = MatDestroy(baij->B);CHKERRQ(ierr);
#if defined (PETSC_USE_CTABLE)
  if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);}
#else
  if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);}
#endif
  if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);}
  if (baij->lvec)   {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);}
  if (baij->Mvctx)  {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);}
  if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);}
  if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);}
  if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);}
#if defined(PETSC_USE_MAT_SINGLE)
  if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);}
#endif
  ierr = PetscFree(baij);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "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,"Incompatible partition of A and xx");
  }
  ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr);
  if (nt != A->m) {
    SETERRQ(PETSC_ERR_ARG_SIZ,"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 __FUNCT__
#define __FUNCT__ "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 __FUNCT__
#define __FUNCT__ "MatMultTranspose_MPIBAIJ"
int MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy)
{
  Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data;
  int         ierr;

  PetscFunctionBegin;
  /* do nondiagonal part */
  ierr = (*a->B->ops->multtranspose)(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->multtranspose)(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 __FUNCT__
#define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ"
int MatMultTransposeAdd_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->multtranspose)(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->multtransposeadd)(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 __FUNCT__
#define __FUNCT__ "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,"Supports only square matrix where A->A is diag block");
  ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatScale_MPIBAIJ"
int MatScale_MPIBAIJ(PetscScalar *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 __FUNCT__
#define __FUNCT__ "MatGetRow_MPIBAIJ"
int MatGetRow_MPIBAIJ(Mat matin,int row,int *nz,int **idx,PetscScalar **v)
{
  Mat_MPIBAIJ  *mat = (Mat_MPIBAIJ*)matin->data;
  PetscScalar  *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,"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; }
    }
    ierr = PetscMalloc(max*bs2*(sizeof(int)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr);
    mat->rowindices = (int*)(mat->rowvalues + max*bs2);
  }

  if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"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 __FUNCT__
#define __FUNCT__ "MatRestoreRow_MPIBAIJ"
int MatRestoreRow_MPIBAIJ(Mat mat,int row,int *nz,int **idx,PetscScalar **v)
{
  Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;

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

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

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

#undef __FUNCT__
#define __FUNCT__ "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 __FUNCT__
#define __FUNCT__ "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;
  PetscReal   isend[5],irecv[5];

  PetscFunctionBegin;
  info->block_size     = (PetscReal)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,MPIU_REAL,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,MPIU_REAL,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];
  } else {
    SETERRQ1(1,"Unknown MatInfoType argument %d",flag);
  }
  info->rows_global       = (PetscReal)A->M;
  info->columns_global    = (PetscReal)A->N;
  info->rows_local        = (PetscReal)A->m;
  info->columns_local     = (PetscReal)A->N;
  info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
  info->fill_ratio_needed = 0;
  info->factor_mallocs    = 0;
  PetscFunctionReturn(0);
}

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

  PetscFunctionBegin;
  switch (op) {
  case MAT_NO_NEW_NONZERO_LOCATIONS:
  case MAT_YES_NEW_NONZERO_LOCATIONS:
  case MAT_COLUMNS_UNSORTED:
  case MAT_COLUMNS_SORTED:
  case MAT_NEW_NONZERO_ALLOCATION_ERR:
  case MAT_KEEP_ZEROED_ROWS:
  case MAT_NEW_NONZERO_LOCATION_ERR:
    ierr = MatSetOption(a->A,op);CHKERRQ(ierr);
    ierr = MatSetOption(a->B,op);CHKERRQ(ierr);
    break;
  case MAT_ROW_ORIENTED:
    a->roworiented = PETSC_TRUE;
    ierr = MatSetOption(a->A,op);CHKERRQ(ierr);
    ierr = MatSetOption(a->B,op);CHKERRQ(ierr);
    break;
  case MAT_ROWS_SORTED:
  case MAT_ROWS_UNSORTED:
  case MAT_YES_NEW_DIAGONALS:
  case MAT_USE_SINGLE_PRECISION_SOLVES:
    PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n");
    break;
  case MAT_COLUMN_ORIENTED:
    a->roworiented = PETSC_FALSE;
    ierr = MatSetOption(a->A,op);CHKERRQ(ierr);
    ierr = MatSetOption(a->B,op);CHKERRQ(ierr);
    break;
  case MAT_IGNORE_OFF_PROC_ENTRIES:
    a->donotstash = PETSC_TRUE;
    break;
  case MAT_NO_NEW_DIAGONALS:
    SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS");
    break;
  case MAT_USE_HASH_TABLE:
    a->ht_flag = PETSC_TRUE;
    break;
  default:
    SETERRQ(PETSC_ERR_SUP,"unknown option");
    break;
  }
  PetscFunctionReturn(0);
}

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

  PetscFunctionBegin;
  if (!matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");
  ierr = MatCreateMPIBAIJ(A->comm,baij->bs,A->n,A->m,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;
  ierr = PetscMalloc(bs*sizeof(int),&rvals);CHKERRQ(ierr);

  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_MPIBAIJ_MatScalar(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_MPIBAIJ_MatScalar(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr);
        col++; a += bs;
      }
    }
  }
  ierr = PetscFree(rvals);CHKERRQ(ierr);
  ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);

  if (matout) {
    *matout = B;
  } else {
    ierr = MatHeaderCopy(A,B);CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}

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

  PetscFunctionBegin;
  ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr);
  if (rr) {
    ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr);
    if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
    /* Overlap communication with computation. */
    ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr);
  }
  if (ll) {
    ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr);
    if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
    ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr);
  }
  /* scale  the diagonal block */
  ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr);

  if (rr) {
    /* Do a scatter end and then right scale the off-diagonal block */
    ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr);
    ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr);
  }

  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatZeroRows_MPIBAIJ"
int MatZeroRows_MPIBAIJ(Mat A,IS is,PetscScalar *diag)
{
  Mat_MPIBAIJ    *l = (Mat_MPIBAIJ*)A->data;
  int            i,ierr,N,*rows,*owners = l->rowners,size = l->size;
  int            *procs,*nprocs,j,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     found;

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

  /*  first count number of contributors to each processor */
  ierr  = PetscMalloc(2*size*sizeof(int),&nprocs);CHKERRQ(ierr);
  ierr  = PetscMemzero(nprocs,2*size*sizeof(int));CHKERRQ(ierr);
  procs = nprocs + size;
  ierr  = PetscMalloc((N+1)*sizeof(int),&owner);CHKERRQ(ierr); /* see note*/
  for (i=0; i<N; i++) {
    idx   = rows[i];
    found = PETSC_FALSE;
    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 = PETSC_TRUE; break;
      }
    }
    if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"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*/
  ierr   = PetscMalloc(2*size*sizeof(int),&work);CHKERRQ(ierr);
  ierr   = MPI_Allreduce(nprocs,work,2*size,MPI_INT,PetscMaxSum_Op,comm);CHKERRQ(ierr);
  nmax   = work[rank];
  nrecvs = work[size+rank];
  ierr   = PetscFree(work);CHKERRQ(ierr);

  /* post receives:   */
  ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int),&rvalues);CHKERRQ(ierr);
  ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr);
  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
  */
  ierr = PetscMalloc((N+1)*sizeof(int),&svalues);CHKERRQ(ierr);
  ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr);
  ierr = PetscMalloc((size+1)*sizeof(int),&starts);CHKERRQ(ierr);
  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];
  }
  ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr);

  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);
    }
  }
  ierr = PetscFree(starts);CHKERRQ(ierr);

  base = owners[rank]*bs;

  /*  wait on receives */
  ierr   = PetscMalloc(2*(nrecvs+1)*sizeof(int),&lens);CHKERRQ(ierr);
  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--;
  }
  ierr = PetscFree(recv_waits);CHKERRQ(ierr);

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

  /* actually zap the local rows */
  ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr);
  PetscLogObjectParent(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
  */
  /* must zero l->B before l->A because the (diag) case below may put values into l->B*/
  ierr = MatZeroRows_SeqBAIJ(l->B,istmp,0);CHKERRQ(ierr);
  if (diag && (l->A->M == l->A->N)) {
    ierr = MatZeroRows_SeqBAIJ(l->A,istmp,diag);CHKERRQ(ierr);
  } else if (diag) {
    ierr = MatZeroRows_SeqBAIJ(l->A,istmp,0);CHKERRQ(ierr);
    if (((Mat_SeqBAIJ*)l->A->data)->nonew) {
      SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\
MAT_NO_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
    }
    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);
  } else {
    ierr = MatZeroRows_SeqBAIJ(l->A,istmp,0);CHKERRQ(ierr);
  }

  ierr = ISDestroy(istmp);CHKERRQ(ierr);
  ierr = PetscFree(lrows);CHKERRQ(ierr);

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

  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "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;
  ierr = (*PetscHelpPrintf)(comm," Options for MATMPIBAIJ matrix format (the defaults):\n");CHKERRQ(ierr);
  ierr = (*PetscHelpPrintf)(comm,"  -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "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 *);

#undef __FUNCT__
#define __FUNCT__ "MatEqual_MPIBAIJ"
int MatEqual_MPIBAIJ(Mat A,Mat B,PetscTruth *flag)
{
  Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data;
  Mat         a,b,c,d;
  PetscTruth  flg;
  int         ierr;

  PetscFunctionBegin;
  ierr = PetscTypeCompare((PetscObject)B,MATMPIBAIJ,&flg);CHKERRQ(ierr);
  if (!flg) SETERRQ(PETSC_ERR_ARG_INCOMP,"Matrices must be same type");
  a = matA->A; b = matA->B;
  c = matB->A; d = matB->B;

  ierr = MatEqual(a,c,&flg);CHKERRQ(ierr);
  if (flg == PETSC_TRUE) {
    ierr = MatEqual(b,d,&flg);CHKERRQ(ierr);
  }
  ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}


#undef __FUNCT__
#define __FUNCT__ "MatSetUpPreallocation_MPIBAIJ"
int MatSetUpPreallocation_MPIBAIJ(Mat A)
{
  int        ierr;

  PetscFunctionBegin;
  ierr =  MatMPIBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/* -------------------------------------------------------------------*/
static struct _MatOps MatOps_Values = {
  MatSetValues_MPIBAIJ,
  MatGetRow_MPIBAIJ,
  MatRestoreRow_MPIBAIJ,
  MatMult_MPIBAIJ,
  MatMultAdd_MPIBAIJ,
  MatMultTranspose_MPIBAIJ,
  MatMultTransposeAdd_MPIBAIJ,
  0,
  0,
  0,
  0,
  0,
  0,
  0,
  MatTranspose_MPIBAIJ,
  MatGetInfo_MPIBAIJ,
  MatEqual_MPIBAIJ,
  MatGetDiagonal_MPIBAIJ,
  MatDiagonalScale_MPIBAIJ,
  MatNorm_MPIBAIJ,
  MatAssemblyBegin_MPIBAIJ,
  MatAssemblyEnd_MPIBAIJ,
  0,
  MatSetOption_MPIBAIJ,
  MatZeroEntries_MPIBAIJ,
  MatZeroRows_MPIBAIJ,
  0,
  0,
  0,
  0,
  MatSetUpPreallocation_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,
  MatDestroy_MPIBAIJ,
  MatView_MPIBAIJ,
  MatGetPetscMaps_Petsc,
  0,
  0,
  0,
  0,
  0,
  0,
  MatGetRowMax_MPIBAIJ};


EXTERN_C_BEGIN
#undef __FUNCT__
#define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ"
int MatGetDiagonalBlock_MPIBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a)
{
  PetscFunctionBegin;
  *a      = ((Mat_MPIBAIJ *)A->data)->A;
  *iscopy = PETSC_FALSE;
  PetscFunctionReturn(0);
}
EXTERN_C_END

EXTERN_C_BEGIN
#undef __FUNCT__
#define __FUNCT__ "MatCreate_MPIBAIJ"
int MatCreate_MPIBAIJ(Mat B)
{
  Mat_MPIBAIJ  *b;
  int          ierr;
  PetscTruth   flg;

  PetscFunctionBegin;

  ierr = PetscNew(Mat_MPIBAIJ,&b);CHKERRQ(ierr);
  B->data = (void*)b;

  ierr    = PetscMemzero(b,sizeof(Mat_MPIBAIJ));CHKERRQ(ierr);
  ierr    = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr);
  B->mapping    = 0;
  B->factor     = 0;
  B->assembled  = PETSC_FALSE;

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

  /* build local table of row and column ownerships */
  ierr          = PetscMalloc(3*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr);
  PetscLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIBAIJ));
  b->cowners    = b->rowners + b->size + 2;
  b->rowners_bs = b->cowners + b->size + 2;

  /* build cache for off array entries formed */
  ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr);
  b->donotstash  = PETSC_FALSE;
  b->colmap      = PETSC_NULL;
  b->garray      = PETSC_NULL;
  b->roworiented = PETSC_TRUE;

#if defined(PETSC_USE_MAT_SINGLE)
  /* stuff for MatSetValues_XXX in single precision */
  b->setvalueslen     = 0;
  b->setvaluescopy    = PETSC_NULL;
#endif

  /* 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      = PETSC_FALSE;
  b->ht_fact      = 0;
  b->ht_total_ct  = 0;
  b->ht_insert_ct = 0;

  ierr = PetscOptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg);CHKERRQ(ierr);
  if (flg) {
    PetscReal fact = 1.39;
    ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr);
    ierr = PetscOptionsGetReal(PETSC_NULL,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr);
    if (fact <= 1.0) fact = 1.39;
    ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr);
    PetscLogInfo(0,"MatCreateMPIBAIJ:Hash table Factor used %5.2f\n",fact);
  }
  ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C",
                                     "MatStoreValues_MPIBAIJ",
                                     MatStoreValues_MPIBAIJ);CHKERRQ(ierr);
  ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C",
                                     "MatRetrieveValues_MPIBAIJ",
                                     MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr);
  ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C",
                                     "MatGetDiagonalBlock_MPIBAIJ",
                                     MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}
EXTERN_C_END

#undef __FUNCT__
#define __FUNCT__ "MatMPIBAIJSetPreallocation"
/*@C
   MatMPIBAIJSetPreallocation - 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 Mat

   Input Parameters:
+  A - the matrix
.  bs   - size of blockk
.  d_nz  - number of block nonzeros per block row in diagonal portion of local
           submatrix  (same for all local rows)
.  d_nnz - 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_nnz - 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:


   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

   Notes:
   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.

   Level: intermediate

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

.seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ()
@*/
int MatMPIBAIJSetPreallocation(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz)
{
  Mat_MPIBAIJ  *b;
  int          ierr,i;
  PetscTruth   flg2;

  PetscFunctionBegin;
  ierr = PetscTypeCompare((PetscObject)B,MATMPIBAIJ,&flg2);CHKERRQ(ierr);
  if (!flg2) PetscFunctionReturn(0);

  B->preallocated = PETSC_TRUE;
  ierr = PetscOptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr);

  if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive");
  if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5;
  if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2;
  if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz);
  if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz);
  if (d_nnz) {
  for (i=0; i<B->m/bs; i++) {
      if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %d value %d",i,d_nnz[i]);
    }
  }
  if (o_nnz) {
    for (i=0; i<B->m/bs; i++) {
      if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %d value %d",i,o_nnz[i]);
    }
  }

  ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr);
  ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr);
  ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr);
  ierr = PetscMapCreateMPI(B->comm,B->n,B->N,&B->cmap);CHKERRQ(ierr);

  b = (Mat_MPIBAIJ*)B->data;
  b->bs  = bs;
  b->bs2 = bs*bs;
  b->mbs = B->m/bs;
  b->nbs = B->n/bs;
  b->Mbs = B->M/bs;
  b->Nbs = B->N/bs;

  ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->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];

  ierr = MPI_Allgather(&b->nbs,1,MPI_INT,b->cowners+1,1,MPI_INT,B->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];

  for (i=0; i<=b->size; i++) {
    b->rowners_bs[i] = b->rowners[i]*bs;
  }
  b->rstart_bs = b->rstart*bs;
  b->rend_bs   = b->rend*bs;
  b->cstart_bs = b->cstart*bs;
  b->cend_bs   = b->cend*bs;

  ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->n,d_nz,d_nnz,&b->A);CHKERRQ(ierr);
  PetscLogObjectParent(B,b->A);
  ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->N,o_nz,o_nnz,&b->B);CHKERRQ(ierr);
  PetscLogObjectParent(B,b->B);
  ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr);

  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "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 nonzero blocks per block row in diagonal portion of local
           submatrix  (same for all local rows)
.  d_nnz - array containing the number of nonzero blocks 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 nonzero blocks per block row in the off-diagonal portion of local
           submatrix (same for all local rows).
-  o_nnz - array containing the number of nonzero blocks 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

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

   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.

   Level: intermediate

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

.seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIBAIJ()
@*/
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)
{
  int ierr,size;

  PetscFunctionBegin;
  ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr);
  ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
  if (size > 1) {
    ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr);
    ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr);
  } else {
    ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr);
    ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "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;

  PetscFunctionBegin;
  *newmat       = 0;
  ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr);
  ierr = MatSetType(mat,MATMPIBAIJ);CHKERRQ(ierr);
  mat->preallocated = PETSC_TRUE;
  mat->assembled    = PETSC_TRUE;
  a      = (Mat_MPIBAIJ*)mat->data;
  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;
  a->donotstash   = oldmat->donotstash;
  a->roworiented  = oldmat->roworiented;
  a->rowindices   = 0;
  a->rowvalues    = 0;
  a->getrowactive = PETSC_FALSE;
  a->barray       = 0;
  a->rstart_bs    = oldmat->rstart_bs;
  a->rend_bs      = oldmat->rend_bs;
  a->cstart_bs    = oldmat->cstart_bs;
  a->cend_bs      = oldmat->cend_bs;

  /* 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;

  ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr);
  ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr);
  ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr);
  if (oldmat->colmap) {
#if defined (PETSC_USE_CTABLE)
  ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr);
#else
  ierr = PetscMalloc((a->Nbs)*sizeof(int),&a->colmap);CHKERRQ(ierr);
  PetscLogObjectMemory(mat,(a->Nbs)*sizeof(int));
  ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr);
#endif
  } else a->colmap = 0;
  if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
    ierr = PetscMalloc(len*sizeof(int),&a->garray);CHKERRQ(ierr);
    PetscLogObjectMemory(mat,len*sizeof(int));
    ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr);
  } else a->garray = 0;

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

  PetscLogObjectParent(mat,a->Mvctx);
  ierr =  MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr);
  PetscLogObjectParent(mat,a->A);
  ierr =  MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr);
  PetscLogObjectParent(mat,a->B);
  ierr = PetscFListDuplicate(matin->qlist,&mat->qlist);CHKERRQ(ierr);
  *newmat = mat;
  PetscFunctionReturn(0);
}

#include "petscsys.h"

EXTERN_C_BEGIN
#undef __FUNCT__
#define __FUNCT__ "MatLoad_MPIBAIJ"
int MatLoad_MPIBAIJ(PetscViewer viewer,MatType type,Mat *newmat)
{
  Mat          A;
  int          i,nz,ierr,j,rstart,rend,fd;
  PetscScalar  *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          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 = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr);

  ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
  ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr);
  if (!rank) {
    ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr);
    ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr);
    if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
    if (header[3] < 0) {
      SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"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,"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) {
    PetscLogInfo(0,"MatLoad_MPIBAIJ:Padding loaded matrix to match blocksize\n");
  }

  /* determine ownership of all rows */
  mbs        = Mbs/size + ((Mbs % size) > rank);
  m          = mbs*bs;
  ierr       = PetscMalloc(2*(size+2)*sizeof(int),&rowners);CHKERRQ(ierr);
  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 */
  ierr = PetscMalloc((rend-rstart)*bs*sizeof(int),&locrowlens);CHKERRQ(ierr);
  if (!rank) {
    ierr = PetscMalloc((M+extra_rows)*sizeof(int),&rowlengths);CHKERRQ(ierr);
    ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr);
    for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
    ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr);
    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);
    ierr = PetscFree(sndcounts);CHKERRQ(ierr);
  } 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 */
    ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr);
    ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr);
    for (i=0; i<size; i++) {
      for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) {
        procsnz[i] += rowlengths[j];
      }
    }
    ierr = PetscFree(rowlengths);CHKERRQ(ierr);

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

    /* read in my part of the matrix column indices  */
    nz     = procsnz[0];
    ierr   = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr);
    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);
    }
    ierr = PetscFree(cols);CHKERRQ(ierr);
  } else {
    /* determine buffer space needed for message */
    nz = 0;
    for (i=0; i<m; i++) {
      nz += locrowlens[i];
    }
    ierr   = PetscMalloc(nz*sizeof(int),&ibuf);CHKERRQ(ierr);
    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,"something is wrong with file");
  }

  /* loop over local rows, determining number of off diagonal entries */
  ierr     = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&dlens);CHKERRQ(ierr);
  odlens   = dlens + (rend-rstart);
  ierr     = PetscMalloc(3*Mbs*sizeof(int),&mask);CHKERRQ(ierr);
  ierr     = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr);
  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,m,M+extra_rows,N+extra_rows,0,dlens,0,odlens,newmat);CHKERRQ(ierr);
  A = *newmat;
  MatSetOption(A,MAT_COLUMNS_SORTED);

  if (!rank) {
    ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&buf);CHKERRQ(ierr);
    /* 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);
    }
    ierr = PetscFree(procsnz);CHKERRQ(ierr);
  } else {
    /* receive numeric values */
    ierr = PetscMalloc(nz*sizeof(PetscScalar),&buf);CHKERRQ(ierr);

    /* 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,"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++;
    }
  }
  ierr = PetscFree(locrowlens);CHKERRQ(ierr);
  ierr = PetscFree(buf);CHKERRQ(ierr);
  ierr = PetscFree(ibuf);CHKERRQ(ierr);
  ierr = PetscFree(rowners);CHKERRQ(ierr);
  ierr = PetscFree(dlens);CHKERRQ(ierr);
  ierr = PetscFree(mask);CHKERRQ(ierr);
  ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}
EXTERN_C_END

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

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

   Collective on Mat

   Level: advanced

  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,PetscReal fact)
{
  Mat_MPIBAIJ *baij;
  int         ierr;
  PetscTruth  flg;

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

#undef __FUNCT__
#define __FUNCT__ "MatMPIBAIJGetSeqBAIJ"
int MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,int **colmap)
{
  Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
  PetscFunctionBegin;
  *Ad     = a->A;
  *Ao     = a->B;
  *colmap = a->garray;
  PetscFunctionReturn(0);
}