aij/seq/matmatmult.c

/*$Id: matmatmult.c,v 1.15 2001/09/07 20:04:44 buschelm Exp $*/
/*
  Defines matrix-matrix product routines for pairs of SeqAIJ matrices
          C = A * B
          C = P * A * P^T
*/

#include "src/mat/impls/aij/seq/aij.h"
#include "src/mat/utils/freespace.h"

static int logkey_matmatmult            = 0;
static int logkey_matmatmult_symbolic   = 0;
static int logkey_matmatmult_numeric    = 0;

static int logkey_matapplypapt          = 0;
static int logkey_matapplypapt_symbolic = 0;
static int logkey_matapplypapt_numeric  = 0;

/*
     MatMatMult_Symbolic_SeqAIJ_SeqAIJ - Forms the symbolic product of two SeqAIJ matrices
           C = A * B;

     Note: C is assumed to be uncreated.
           If this is not the case, Destroy C before calling this routine.
*/
#ifdef USE_INTSORT
/*
This roution is modified by the one below for better performance.
The changes are:
   -- PetscSortInt() is replace by a linked list
   -- malloc larger Initial FreeSpace
*/
#undef __FUNCT__
#define __FUNCT__ "MatMatMult_Symbolic_SeqAIJ_SeqAIJ"
int MatMatMult_Symbolic_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat *C)
{
  int            ierr;
  FreeSpaceList  free_space=PETSC_NULL,current_space=PETSC_NULL;
  Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data,*c;
  int            aishift=a->indexshift,bishift=b->indexshift;
  int            *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*bjj;
  int            *ci,*cj,*denserow,*sparserow;
  int            an=A->N,am=A->M,bn=B->N,bm=B->M;
  int            i,j,k,anzi,brow,bnzj,cnzi;
  MatScalar      *ca;

  PetscFunctionBegin;
  /* some error checking which could be moved into interface layer */
  if (aishift || bishift) SETERRQ(PETSC_ERR_SUP,"Shifted matrix indices are not supported.");
  if (an!=bm) SETERRQ2(PETSC_ERR_ARG_SIZ,"Matrix dimensions are incompatible, %d != %d",an,bm);

  /* Set up timers */
  if (!logkey_matmatmult_symbolic) {
    ierr = PetscLogEventRegister(&logkey_matmatmult_symbolic,"MatMatMult_Symbolic",MAT_COOKIE);CHKERRQ(ierr);
  }
  ierr = PetscLogEventBegin(logkey_matmatmult_symbolic,A,B,0,0);CHKERRQ(ierr);

  /* Set up */
  /* Allocate ci array, arrays for fill computation and */
  /* free space for accumulating nonzero column info */
  ierr = PetscMalloc(((am+1)+1)*sizeof(int),&ci);CHKERRQ(ierr);
  ci[0] = 0;

  ierr = PetscMalloc((2*bn+1)*sizeof(int),&denserow);CHKERRQ(ierr);
  ierr = PetscMemzero(denserow,(2*bn+1)*sizeof(int));CHKERRQ(ierr);
  sparserow = denserow + bn;

  /* Initial FreeSpace size is nnz(B)=bi[bm] */
  ierr          = GetMoreSpace(bi[bm],&free_space);CHKERRQ(ierr);
  current_space = free_space;

  /* Determine symbolic info for each row of the product: */
  for (i=0;i<am;i++) {
    anzi = ai[i+1] - ai[i];
    cnzi = 0;
    for (j=0;j<anzi;j++) {
      brow = *aj++;
      bnzj = bi[brow+1] - bi[brow];
      bjj  = bj + bi[brow];
      for (k=0;k<bnzj;k++) {
        /* If column is not marked, mark it in compressed and uncompressed locations. */
        /* For simplicity, leave uncompressed row unsorted until finished with row, */
        /* and increment nonzero count for this row. */
        if (!denserow[bjj[k]]) {
          denserow[bjj[k]]  = -1;
          sparserow[cnzi++] = bjj[k];
        }
      }
    }

    /* sort sparserow */
    ierr = PetscSortInt(cnzi,sparserow);CHKERRQ(ierr);

    /* If free space is not available, make more free space */
    /* Double the amount of total space in the list */
    if (current_space->local_remaining<cnzi) {
      ierr = GetMoreSpace(current_space->total_array_size,&current_space);CHKERRQ(ierr);
    }

    /* Copy data into free space, and zero out denserow */
    ierr = PetscMemcpy(current_space->array,sparserow,cnzi*sizeof(int));CHKERRQ(ierr);
    current_space->array           += cnzi;
    current_space->local_used      += cnzi;
    current_space->local_remaining -= cnzi;
    for (j=0;j<cnzi;j++) {
      denserow[sparserow[j]] = 0;
    }
    ci[i+1] = ci[i] + cnzi;
  }

  /* Column indices are in the list of free space */
  /* Allocate space for cj, initialize cj, and */
  /* destroy list of free space and other temporary array(s) */
  ierr = PetscMalloc((ci[am]+1)*sizeof(int),&cj);CHKERRQ(ierr);
  ierr = MakeSpaceContiguous(&free_space,cj);CHKERRQ(ierr);
  ierr = PetscFree(denserow);CHKERRQ(ierr);

  /* Allocate space for ca */
  ierr = PetscMalloc((ci[am]+1)*sizeof(MatScalar),&ca);CHKERRQ(ierr);
  ierr = PetscMemzero(ca,(ci[am]+1)*sizeof(MatScalar));CHKERRQ(ierr);

  /* put together the new matrix */
  ierr = MatCreateSeqAIJWithArrays(A->comm,am,bn,ci,cj,ca,C);CHKERRQ(ierr);

  /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
  /* These are PETSc arrays, so change flags so arrays can be deleted by PETSc */
  c = (Mat_SeqAIJ *)((*C)->data);
  c->freedata = PETSC_TRUE;
  c->nonew    = 0;

  ierr = PetscLogEventEnd(logkey_matmatmult_symbolic,A,B,0,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}
#endif /*  USE_INTSORT */

#undef __FUNCT__
#define __FUNCT__ "MatMatMult_Symbolic_SeqAIJ_SeqAIJ"
int MatMatMult_Symbolic_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat *C)
{
  int            ierr;
  FreeSpaceList  free_space=PETSC_NULL,current_space=PETSC_NULL;
  Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data,*c;
  int            aishift=a->indexshift,bishift=b->indexshift;
  int            *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*bjj;
  int            *ci,*cj,*lnk,idx0,idx,bcol;
  int            an=A->N,am=A->M,bn=B->N,bm=B->M;
  int            i,j,k,anzi,brow,bnzj,cnzi;
  MatScalar      *ca;

  PetscFunctionBegin;
  /* some error checking which could be moved into interface layer */
  if (aishift || bishift) SETERRQ(PETSC_ERR_SUP,"Shifted matrix indices are not supported.");
  if (an!=bm) SETERRQ2(PETSC_ERR_ARG_SIZ,"Matrix dimensions are incompatible, %d != %d",an,bm);

  /* Set up timers */
  if (!logkey_matmatmult_symbolic) {
    ierr = PetscLogEventRegister(&logkey_matmatmult_symbolic,"MatMatMult_Symbolic",MAT_COOKIE);CHKERRQ(ierr);
  }
  ierr = PetscLogEventBegin(logkey_matmatmult_symbolic,A,B,0,0);CHKERRQ(ierr);

  /* Set up */
  /* Allocate ci array, arrays for fill computation and */
  /* free space for accumulating nonzero column info */
  ierr = PetscMalloc(((am+1)+1)*sizeof(int),&ci);CHKERRQ(ierr);
  ci[0] = 0;

  ierr = PetscMalloc((bn+1)*sizeof(int),&lnk);CHKERRQ(ierr);
  for (i=0; i<bn; i++) lnk[i] = -1;

  /* Initial FreeSpace size is nnz(B)=4*bi[bm] */
  ierr = GetMoreSpace(4*bi[bm],&free_space);CHKERRQ(ierr);
  current_space = free_space;

  /* Determine symbolic info for each row of the product: */
  for (i=0;i<am;i++) {
    anzi = ai[i+1] - ai[i];
    cnzi = 0;
    lnk[bn] = bn;
    for (j=0;j<anzi;j++) {
      brow = *aj++;
      bnzj = bi[brow+1] - bi[brow];
      bjj  = bj + bi[brow];
      idx  = bn;
      for (k=0;k<bnzj;k++) {
        bcol = bjj[k];
        if (lnk[bcol] == -1) { /* new col */
          if (k>0) idx = bjj[k-1];
          do {
            idx0 = idx;
            idx  = lnk[idx0];
          } while (bcol > idx);
          lnk[idx0] = bcol;
          lnk[bcol] = idx;
          cnzi++;
        }
      }
    }

    /* If free space is not available, make more free space */
    /* Double the amount of total space in the list */
    if (current_space->local_remaining<cnzi) {
      printf("...%d -th row, double space ...\n",i);
      ierr = GetMoreSpace(current_space->total_array_size,&current_space);CHKERRQ(ierr);
    }

    /* Copy data into free space, and zero out denserow and lnk */
    idx = bn;
    for (j=0; j<cnzi; j++){
      idx0 = idx;
      idx  = lnk[idx0];
      *current_space->array++ = idx;
      lnk[idx0] = -1;
    }
    lnk[idx] = -1;

    current_space->local_used      += cnzi;
    current_space->local_remaining -= cnzi;

    ci[i+1] = ci[i] + cnzi;
  }

  /* Column indices are in the list of free space */
  /* Allocate space for cj, initialize cj, and */
  /* destroy list of free space and other temporary array(s) */
  ierr = PetscMalloc((ci[am]+1)*sizeof(int),&cj);CHKERRQ(ierr);
  ierr = MakeSpaceContiguous(&free_space,cj);CHKERRQ(ierr);
  ierr = PetscFree(lnk);CHKERRQ(ierr);

  /* Allocate space for ca */
  ierr = PetscMalloc((ci[am]+1)*sizeof(MatScalar),&ca);CHKERRQ(ierr);
  ierr = PetscMemzero(ca,(ci[am]+1)*sizeof(MatScalar));CHKERRQ(ierr);

  /* put together the new matrix */
  ierr = MatCreateSeqAIJWithArrays(A->comm,am,bn,ci,cj,ca,C);CHKERRQ(ierr);

  /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
  /* These are PETSc arrays, so change flags so arrays can be deleted by PETSc */
  c = (Mat_SeqAIJ *)((*C)->data);
  c->freedata = PETSC_TRUE;
  c->nonew    = 0;

  ierr = PetscLogEventEnd(logkey_matmatmult_symbolic,A,B,0,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*
     MatMatMult_Numeric_SeqAIJ_SeqAIJ - Forms the numeric product of two SeqAIJ matrices
           C=A*B;
     Note: C must have been created by calling MatMatMult_Symbolic_SeqAIJ_SeqAIJ.
*/
#undef __FUNCT__
#define __FUNCT__ "MatMatMult_Numeric_SeqAIJ_SeqAIJ"
int MatMatMult_Numeric_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat C)
{
  int        ierr,flops=0;
  Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data;
  Mat_SeqAIJ *b = (Mat_SeqAIJ *)B->data;
  Mat_SeqAIJ *c = (Mat_SeqAIJ *)C->data;
  int        aishift=a->indexshift,bishift=b->indexshift,cishift=c->indexshift;
  int        *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*bjj,*ci=c->i,*cj=c->j;
  int        an=A->N,am=A->M,bn=B->N,bm=B->M,cn=C->N,cm=C->M;
  int        i,j,k,anzi,bnzi,cnzi,brow;
  MatScalar  *aa=a->a,*ba=b->a,*baj,*ca=c->a,*temp;

  PetscFunctionBegin;

  /* This error checking should be unnecessary if the symbolic was performed */
  if (aishift || bishift || cishift) SETERRQ(PETSC_ERR_SUP,"Shifted matrix indices are not supported.");
  if (am!=cm) SETERRQ2(PETSC_ERR_ARG_SIZ,"Matrix dimensions are incompatible, %d != %d",am,cm);
  if (an!=bm) SETERRQ2(PETSC_ERR_ARG_SIZ,"Matrix dimensions are incompatible, %d != %d",an,bm);
  if (bn!=cn) SETERRQ2(PETSC_ERR_ARG_SIZ,"Matrix dimensions are incompatible, %d != %d",bn,cn);

  /* Set up timers */
  if (!logkey_matmatmult_numeric) {
    ierr = PetscLogEventRegister(&logkey_matmatmult_numeric,"MatMatMult_Numeric",MAT_COOKIE);CHKERRQ(ierr);
  }
  ierr = PetscLogEventBegin(logkey_matmatmult_numeric,A,B,C,0);CHKERRQ(ierr);

  /* Allocate temp accumulation space to avoid searching for nonzero columns in C */
  ierr = PetscMalloc((cn+1)*sizeof(MatScalar),&temp);CHKERRQ(ierr);
  ierr = PetscMemzero(temp,cn*sizeof(MatScalar));CHKERRQ(ierr);
  /* Traverse A row-wise. */
  /* Build the ith row in C by summing over nonzero columns in A, */
  /* the rows of B corresponding to nonzeros of A. */
  for (i=0;i<am;i++) {
    anzi = ai[i+1] - ai[i];
    for (j=0;j<anzi;j++) {
      brow = *aj++;
      bnzi = bi[brow+1] - bi[brow];
      bjj  = bj + bi[brow];
      baj  = ba + bi[brow];
      for (k=0;k<bnzi;k++) {
        temp[bjj[k]] += (*aa)*baj[k];
      }
      flops += 2*bnzi;
      aa++;
    }
    /* Store row back into C, and re-zero temp */
    cnzi = ci[i+1] - ci[i];
    for (j=0;j<cnzi;j++) {
      ca[j] = temp[cj[j]];
      temp[cj[j]] = 0.0;
    }
    ca += cnzi;
    cj += cnzi;
  }
  ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);

  /* Free temp */
  ierr = PetscFree(temp);CHKERRQ(ierr);
  ierr = PetscLogFlops(flops);CHKERRQ(ierr);
  ierr = PetscLogEventEnd(logkey_matmatmult_numeric,A,B,C,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatMatMult_SeqAIJ_SeqAIJ"
int MatMatMult_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat *C) {
  int ierr;

  PetscFunctionBegin;
  if (!logkey_matmatmult) {
    ierr = PetscLogEventRegister(&logkey_matmatmult,"MatMatMult",MAT_COOKIE);CHKERRQ(ierr);
  }
  ierr = PetscLogEventBegin(logkey_matmatmult,A,B,0,0);CHKERRQ(ierr);
  ierr = MatMatMult_Symbolic_SeqAIJ_SeqAIJ(A,B,C);CHKERRQ(ierr);
  ierr = MatMatMult_Numeric_SeqAIJ_SeqAIJ(A,B,*C);CHKERRQ(ierr);
  ierr = PetscLogEventEnd(logkey_matmatmult,A,B,0,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}


/*
     MatApplyPAPt_Symbolic_SeqAIJ_SeqAIJ - Forms the symbolic product of two SeqAIJ matrices
           C = P * A * P^T;

     Note: C is assumed to be uncreated.
           If this is not the case, Destroy C before calling this routine.
*/
#undef __FUNCT__
#define __FUNCT__ "MatApplyPAPt_Symbolic_SeqAIJ_SeqAIJ"
int MatApplyPAPt_Symbolic_SeqAIJ_SeqAIJ(Mat A,Mat P,Mat *C) {
  /* Note: This code is virtually identical to that of MatApplyPtAP_SeqAIJ_Symbolic */
  /*        and MatMatMult_SeqAIJ_SeqAIJ_Symbolic.  Perhaps they could be merged nicely. */
  int            ierr;
  FreeSpaceList  free_space=PETSC_NULL,current_space=PETSC_NULL;
  Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data,*p=(Mat_SeqAIJ*)P->data,*c;
  int            aishift=a->indexshift,pishift=p->indexshift;
  int            *ai=a->i,*aj=a->j,*ajj,*pi=p->i,*pj=p->j,*pti,*ptj,*ptjj;
  int            *ci,*cj,*paj,*padenserow,*pasparserow,*denserow,*sparserow;
  int            an=A->N,am=A->M,pn=P->N,pm=P->M;
  int            i,j,k,pnzi,arow,anzj,panzi,ptrow,ptnzj,cnzi;
  MatScalar      *ca;

  PetscFunctionBegin;

  /* some error checking which could be moved into interface layer */
  if (aishift || pishift) SETERRQ(PETSC_ERR_SUP,"Shifted matrix indices are not supported.");
  if (pn!=am) SETERRQ2(PETSC_ERR_ARG_SIZ,"Matrix dimensions are incompatible, %d != %d",pn,am);
  if (am!=an) SETERRQ2(PETSC_ERR_ARG_SIZ,"Matrix 'A' must be square, %d != %d",am, an);

  /* Set up timers */
  if (!logkey_matapplypapt_symbolic) {
    ierr = PetscLogEventRegister(&logkey_matapplypapt_symbolic,"MatApplyPAPt_Symbolic",MAT_COOKIE);CHKERRQ(ierr);
  }
  ierr = PetscLogEventBegin(logkey_matapplypapt_symbolic,A,P,0,0);CHKERRQ(ierr);

  /* Create ij structure of P^T */
  ierr = MatGetSymbolicTranspose_SeqAIJ(P,&pti,&ptj);CHKERRQ(ierr);

  /* Allocate ci array, arrays for fill computation and */
  /* free space for accumulating nonzero column info */
  ierr = PetscMalloc(((pm+1)*1)*sizeof(int),&ci);CHKERRQ(ierr);
  ci[0] = 0;

  ierr = PetscMalloc((2*an+2*pm+1)*sizeof(int),&padenserow);CHKERRQ(ierr);
  ierr = PetscMemzero(padenserow,(2*an+2*pm+1)*sizeof(int));CHKERRQ(ierr);
  pasparserow  = padenserow  + an;
  denserow     = pasparserow + an;
  sparserow    = denserow    + pm;

  /* Set initial free space to be nnz(A) scaled by aspect ratio of Pt. */
  /* This should be reasonable if sparsity of PAPt is similar to that of A. */
  ierr          = GetMoreSpace((ai[am]/pn)*pm,&free_space);
  current_space = free_space;

  /* Determine fill for each row of C: */
  for (i=0;i<pm;i++) {
    pnzi  = pi[i+1] - pi[i];
    panzi = 0;
    /* Get symbolic sparse row of PA: */
    for (j=0;j<pnzi;j++) {
      arow = *pj++;
      anzj = ai[arow+1] - ai[arow];
      ajj  = aj + ai[arow];
      for (k=0;k<anzj;k++) {
        if (!padenserow[ajj[k]]) {
          padenserow[ajj[k]]   = -1;
          pasparserow[panzi++] = ajj[k];
        }
      }
    }
    /* Using symbolic row of PA, determine symbolic row of C: */
    paj    = pasparserow;
    cnzi   = 0;
    for (j=0;j<panzi;j++) {
      ptrow = *paj++;
      ptnzj = pti[ptrow+1] - pti[ptrow];
      ptjj  = ptj + pti[ptrow];
      for (k=0;k<ptnzj;k++) {
        if (!denserow[ptjj[k]]) {
          denserow[ptjj[k]] = -1;
          sparserow[cnzi++] = ptjj[k];
        }
      }
    }

    /* sort sparse representation */
    ierr = PetscSortInt(cnzi,sparserow);CHKERRQ(ierr);

    /* If free space is not available, make more free space */
    /* Double the amount of total space in the list */
    if (current_space->local_remaining<cnzi) {
      ierr = GetMoreSpace(current_space->total_array_size,&current_space);CHKERRQ(ierr);
    }

    /* Copy data into free space, and zero out dense row */
    ierr = PetscMemcpy(current_space->array,sparserow,cnzi*sizeof(int));CHKERRQ(ierr);
    current_space->array           += cnzi;
    current_space->local_used      += cnzi;
    current_space->local_remaining -= cnzi;

    for (j=0;j<panzi;j++) {
      padenserow[pasparserow[j]] = 0;
    }
    for (j=0;j<cnzi;j++) {
      denserow[sparserow[j]] = 0;
    }
    ci[i+1] = ci[i] + cnzi;
  }
  /* column indices are in the list of free space */
  /* Allocate space for cj, initialize cj, and */
  /* destroy list of free space and other temporary array(s) */
  ierr = PetscMalloc((ci[pm]+1)*sizeof(int),&cj);CHKERRQ(ierr);
  ierr = MakeSpaceContiguous(&free_space,cj);CHKERRQ(ierr);
  ierr = PetscFree(padenserow);CHKERRQ(ierr);

  /* Allocate space for ca */
  ierr = PetscMalloc((ci[pm]+1)*sizeof(MatScalar),&ca);CHKERRQ(ierr);
  ierr = PetscMemzero(ca,(ci[pm]+1)*sizeof(MatScalar));CHKERRQ(ierr);

  /* put together the new matrix */
  ierr = MatCreateSeqAIJWithArrays(A->comm,pm,pm,ci,cj,ca,C);CHKERRQ(ierr);

  /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
  /* Since these are PETSc arrays, change flags to free them as necessary. */
  c = (Mat_SeqAIJ *)((*C)->data);
  c->freedata = PETSC_TRUE;
  c->nonew    = 0;

  /* Clean up. */
  ierr = MatRestoreSymbolicTranspose_SeqAIJ(P,&pti,&ptj);CHKERRQ(ierr);

  ierr = PetscLogEventEnd(logkey_matapplypapt_symbolic,A,P,0,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/*
     MatApplyPAPt_Numeric_SeqAIJ - Forms the numeric product of two SeqAIJ matrices
           C = P * A * P^T;
     Note: C must have been created by calling MatApplyPAPt_Symbolic_SeqAIJ.
*/
#undef __FUNCT__
#define __FUNCT__ "MatApplyPAPt_Numeric_SeqAIJ_SeqAIJ"
int MatApplyPAPt_Numeric_SeqAIJ_SeqAIJ(Mat A,Mat P,Mat C) {
  int        ierr,flops=0;
  Mat_SeqAIJ *a  = (Mat_SeqAIJ *) A->data;
  Mat_SeqAIJ *p  = (Mat_SeqAIJ *) P->data;
  Mat_SeqAIJ *c  = (Mat_SeqAIJ *) C->data;
  int        aishift=a->indexshift,pishift=p->indexshift,cishift=c->indexshift;
  int        *ai=a->i,*aj=a->j,*ajj,*pi=p->i,*pj=p->j,*pjj=p->j,*paj,*pajdense,*ptj;
  int        *ci=c->i,*cj=c->j;
  int        an=A->N,am=A->M,pn=P->N,pm=P->M,cn=C->N,cm=C->M;
  int        i,j,k,k1,k2,pnzi,anzj,panzj,arow,ptcol,ptnzj,cnzi;
  MatScalar  *aa=a->a,*pa=p->a,*pta=p->a,*ptaj,*paa,*aaj,*ca=c->a,sum;

  PetscFunctionBegin;

  /* This error checking should be unnecessary if the symbolic was performed */
  if (aishift || pishift || cishift) SETERRQ(PETSC_ERR_SUP,"Shifted matrix indices are not supported.");
  if (pm!=cm) SETERRQ2(PETSC_ERR_ARG_SIZ,"Matrix dimensions are incompatible, %d != %d",pm,cm);
  if (pn!=am) SETERRQ2(PETSC_ERR_ARG_SIZ,"Matrix dimensions are incompatible, %d != %d",pn,am);
  if (am!=an) SETERRQ2(PETSC_ERR_ARG_SIZ,"Matrix 'A' must be square, %d != %d",am, an);
  if (pm!=cn) SETERRQ2(PETSC_ERR_ARG_SIZ,"Matrix dimensions are incompatible, %d != %d",pm, cn);

  /* Set up timers */
  if (!logkey_matapplypapt_numeric) {
    ierr = PetscLogEventRegister(&logkey_matapplypapt_numeric,"MatApplyPAPt_Numeric",MAT_COOKIE);CHKERRQ(ierr);
  }
  ierr = PetscLogEventBegin(logkey_matapplypapt_numeric,A,P,C,0);CHKERRQ(ierr);

  ierr = PetscMalloc(an*(sizeof(MatScalar)+2*sizeof(int)),&paa);CHKERRQ(ierr);
  ierr = PetscMemzero(paa,an*(sizeof(MatScalar)+2*sizeof(int)));CHKERRQ(ierr);
  ierr = PetscMemzero(ca,ci[cm]*sizeof(MatScalar));CHKERRQ(ierr);

  paj      = (int *)(paa + an);
  pajdense = paj + an;

  for (i=0;i<pm;i++) {
    /* Form sparse row of P*A */
    pnzi  = pi[i+1] - pi[i];
    panzj = 0;
    for (j=0;j<pnzi;j++) {
      arow = *pj++;
      anzj = ai[arow+1] - ai[arow];
      ajj  = aj + ai[arow];
      aaj  = aa + ai[arow];
      for (k=0;k<anzj;k++) {
        if (!pajdense[ajj[k]]) {
          pajdense[ajj[k]] = -1;
          paj[panzj++]     = ajj[k];
        }
        paa[ajj[k]] += (*pa)*aaj[k];
      }
      flops += 2*anzj;
      pa++;
    }

    /* Sort the j index array for quick sparse axpy. */
    ierr = PetscSortInt(panzj,paj);CHKERRQ(ierr);

    /* Compute P*A*P^T using sparse inner products. */
    /* Take advantage of pre-computed (i,j) of C for locations of non-zeros. */
    cnzi = ci[i+1] - ci[i];
    for (j=0;j<cnzi;j++) {
      /* Form sparse inner product of current row of P*A with (*cj++) col of P^T. */
      ptcol = *cj++;
      ptnzj = pi[ptcol+1] - pi[ptcol];
      ptj   = pjj + pi[ptcol];
      ptaj  = pta + pi[ptcol];
      sum   = 0.;
      k1    = 0;
      k2    = 0;
      while ((k1<panzj) && (k2<ptnzj)) {
        if (paj[k1]==ptj[k2]) {
          sum += paa[paj[k1++]]*ptaj[k2++];
        } else if (paj[k1] < ptj[k2]) {
          k1++;
        } else /* if (paj[k1] > ptj[k2]) */ {
          k2++;
        }
      }
      *ca++ = sum;
    }

    /* Zero the current row info for P*A */
    for (j=0;j<panzj;j++) {
      paa[paj[j]]      = 0.;
      pajdense[paj[j]] = 0;
    }
  }

  ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = PetscLogFlops(flops);CHKERRQ(ierr);
  ierr = PetscLogEventEnd(logkey_matapplypapt_numeric,A,P,C,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatApplyPAPt_SeqAIJ_SeqAIJ"
int MatApplyPAPt_SeqAIJ_SeqAIJ(Mat A,Mat P,Mat *C) {
  int ierr;

  PetscFunctionBegin;
  if (!logkey_matapplypapt) {
    ierr = PetscLogEventRegister(&logkey_matapplypapt,"MatApplyPAPt",MAT_COOKIE);CHKERRQ(ierr);
  }
  ierr = PetscLogEventBegin(logkey_matapplypapt,A,P,0,0);CHKERRQ(ierr);
  ierr = MatApplyPAPt_Symbolic_SeqAIJ_SeqAIJ(A,P,C);CHKERRQ(ierr);
  ierr = MatApplyPAPt_Numeric_SeqAIJ_SeqAIJ(A,P,*C);CHKERRQ(ierr);
  ierr = PetscLogEventEnd(logkey_matapplypapt,A,P,0,0);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}