seq/superlu/superlu.c

/*
        Provides an interface to the SuperLU 3.0 sparse solver
*/

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

EXTERN_C_BEGIN
#if defined(PETSC_USE_COMPLEX)
#include "zsp_defs.h"
#else
#include "dsp_defs.h"
#endif
#include "util.h"
EXTERN_C_END

typedef struct {
  SuperMatrix       A,L,U,B,X;
  superlu_options_t options;
  int               *perm_c; /* column permutation vector */
  int               *perm_r; /* row permutations from partial pivoting */
  int               *etree;
  double            *R, *C;
  char              equed[1];
  int               lwork;
  void              *work;
  double            rpg, rcond;
  mem_usage_t       mem_usage;
  MatStructure      flg;

  /* A few function pointers for inheritance */
  int (*MatDuplicate)(Mat,MatDuplicateOption,Mat*);
  int (*MatView)(Mat,PetscViewer);
  int (*MatAssemblyEnd)(Mat,MatAssemblyType);
  int (*MatLUFactorSymbolic)(Mat,IS,IS,MatFactorInfo*,Mat*);
  int (*MatDestroy)(Mat);

  /* Flag to clean up (non-global) SuperLU objects during Destroy */
  PetscTruth CleanUpSuperLU;
} Mat_SuperLU;


EXTERN int MatFactorInfo_SuperLU(Mat,PetscViewer);
EXTERN int MatLUFactorSymbolic_SuperLU(Mat,IS,IS,MatFactorInfo*,Mat*);

EXTERN_C_BEGIN
EXTERN int MatConvert_SuperLU_SeqAIJ(Mat,const MatType,Mat*);
EXTERN int MatConvert_SeqAIJ_SuperLU(Mat,const MatType,Mat*);
EXTERN_C_END

#undef __FUNCT__
#define __FUNCT__ "MatDestroy_SuperLU"
int MatDestroy_SuperLU(Mat A)
{
  int         ierr;
  Mat_SuperLU *lu = (Mat_SuperLU*)A->spptr;

  PetscFunctionBegin;
  if (lu->CleanUpSuperLU) { /* Free the SuperLU datastructures */
    Destroy_SuperMatrix_Store(&lu->A);
    Destroy_SuperMatrix_Store(&lu->B);
    Destroy_SuperMatrix_Store(&lu->X);

    ierr = PetscFree(lu->etree);CHKERRQ(ierr);
    ierr = PetscFree(lu->perm_r);CHKERRQ(ierr);
    ierr = PetscFree(lu->perm_c);CHKERRQ(ierr);
    ierr = PetscFree(lu->R);CHKERRQ(ierr);
    ierr = PetscFree(lu->C);CHKERRQ(ierr);
    if ( lu->lwork >= 0 ) {
      Destroy_SuperNode_Matrix(&lu->L);
      Destroy_CompCol_Matrix(&lu->U);
    }
  }
  ierr = MatConvert_SuperLU_SeqAIJ(A,MATSEQAIJ,&A);CHKERRQ(ierr);
  ierr = (*A->ops->destroy)(A);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatView_SuperLU"
int MatView_SuperLU(Mat A,PetscViewer viewer)
{
  int               ierr;
  PetscTruth        iascii;
  PetscViewerFormat format;
  Mat_SuperLU       *lu=(Mat_SuperLU*)(A->spptr);

  PetscFunctionBegin;
  ierr = (*lu->MatView)(A,viewer);CHKERRQ(ierr);

  ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr);
  if (iascii) {
    ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
    if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
      ierr = MatFactorInfo_SuperLU(A,viewer);CHKERRQ(ierr);
    }
  }
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatAssemblyEnd_SuperLU"
int MatAssemblyEnd_SuperLU(Mat A,MatAssemblyType mode) {
  int         ierr;
  Mat_SuperLU *lu=(Mat_SuperLU*)(A->spptr);

  PetscFunctionBegin;
  ierr = (*lu->MatAssemblyEnd)(A,mode);CHKERRQ(ierr);

  lu->MatLUFactorSymbolic  = A->ops->lufactorsymbolic;
  A->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU;
  PetscFunctionReturn(0);
}

/* This function was written for SuperLU 2.0 by Matthew Knepley. Not tested for SuperLU 3.0! */
#ifdef SuperLU2
#include "src/mat/impls/dense/seq/dense.h"
#undef __FUNCT__
#define __FUNCT__ "MatCreateNull_SuperLU"
int MatCreateNull_SuperLU(Mat A,Mat *nullMat)
{
  Mat_SuperLU   *lu = (Mat_SuperLU*)A->spptr;
  int           numRows = A->m,numCols = A->n;
  SCformat      *Lstore;
  int           numNullCols,size;
  SuperLUStat_t stat;
#if defined(PETSC_USE_COMPLEX)
  doublecomplex *nullVals,*workVals;
#else
  PetscScalar   *nullVals,*workVals;
#endif
  int           row,newRow,col,newCol,block,b,ierr;

  PetscFunctionBegin;
  if (!A->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Unfactored matrix");
  numNullCols = numCols - numRows;
  if (numNullCols < 0) SETERRQ(PETSC_ERR_ARG_WRONG,"Function only applies to underdetermined problems");
  /* Create the null matrix using MATSEQDENSE explicitly */
  ierr = MatCreate(A->comm,numRows,numNullCols,numRows,numNullCols,nullMat);CHKERRQ(ierr);
  ierr = MatSetType(*nullMat,MATSEQDENSE);CHKERRQ(ierr);
  ierr = MatSeqDenseSetPreallocation(*nullMat,PETSC_NULL);CHKERRQ(ierr);
  if (!numNullCols) {
    ierr = MatAssemblyBegin(*nullMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
    ierr = MatAssemblyEnd(*nullMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
    PetscFunctionReturn(0);
  }
#if defined(PETSC_USE_COMPLEX)
  nullVals = (doublecomplex*)((Mat_SeqDense*)(*nullMat)->data)->v;
#else
  nullVals = ((Mat_SeqDense*)(*nullMat)->data)->v;
#endif
  /* Copy in the columns */
  Lstore = (SCformat*)lu->L.Store;
  for(block = 0; block <= Lstore->nsuper; block++) {
    newRow = Lstore->sup_to_col[block];
    size   = Lstore->sup_to_col[block+1] - Lstore->sup_to_col[block];
    for(col = Lstore->rowind_colptr[newRow]; col < Lstore->rowind_colptr[newRow+1]; col++) {
      newCol = Lstore->rowind[col];
      if (newCol >= numRows) {
        for(b = 0; b < size; b++)
#if defined(PETSC_USE_COMPLEX)
          nullVals[(newCol-numRows)*numRows+newRow+b] = ((doublecomplex*)Lstore->nzval)[Lstore->nzval_colptr[newRow+b]+col];
#else
          nullVals[(newCol-numRows)*numRows+newRow+b] = ((double*)Lstore->nzval)[Lstore->nzval_colptr[newRow+b]+col];
#endif
      }
    }
  }
  /* Permute rhs to form P^T_c B */
  ierr = PetscMalloc(numRows*sizeof(double),&workVals);CHKERRQ(ierr);
  for(b = 0; b < numNullCols; b++) {
    for(row = 0; row < numRows; row++) workVals[lu->perm_c[row]] = nullVals[b*numRows+row];
    for(row = 0; row < numRows; row++) nullVals[b*numRows+row]   = workVals[row];
  }
  /* Backward solve the upper triangle A x = b */
  for(b = 0; b < numNullCols; b++) {
#if defined(PETSC_USE_COMPLEX)
    sp_ztrsv("L","T","U",&lu->L,&lu->U,&nullVals[b*numRows],&stat,&ierr);
#else
    sp_dtrsv("L","T","U",&lu->L,&lu->U,&nullVals[b*numRows],&stat,&ierr);
#endif
    if (ierr < 0)
      SETERRQ1(PETSC_ERR_ARG_WRONG,"The argument %d was invalid",-ierr);
  }
  ierr = PetscFree(workVals);CHKERRQ(ierr);

  ierr = MatAssemblyBegin(*nullMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = MatAssemblyEnd(*nullMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}
#endif

#undef __FUNCT__
#define __FUNCT__ "MatSolve_SuperLU"
int MatSolve_SuperLU(Mat A,Vec b,Vec x)
{
  Mat_SuperLU   *lu = (Mat_SuperLU*)A->spptr;
  PetscScalar   *barray,*xarray;
  int           ierr,info,i;
  SuperLUStat_t stat;
  double        ferr,berr;

  PetscFunctionBegin;
  if ( lu->lwork == -1 ) {
    PetscFunctionReturn(0);
  }
  lu->B.ncol = 1;   /* Set the number of right-hand side */
  ierr = VecGetArray(b,&barray);CHKERRQ(ierr);
  ierr = VecGetArray(x,&xarray);CHKERRQ(ierr);

#if defined(PETSC_USE_COMPLEX)
  ((DNformat*)lu->B.Store)->nzval = (doublecomplex*)barray;
  ((DNformat*)lu->X.Store)->nzval = (doublecomplex*)xarray;
#else
  ((DNformat*)lu->B.Store)->nzval = barray;
  ((DNformat*)lu->X.Store)->nzval = xarray;
#endif

  /* Initialize the statistics variables. */
  StatInit(&stat);

  lu->options.Fact  = FACTORED; /* Indicate the factored form of A is supplied. */
  lu->options.Trans = TRANS;
#if defined(PETSC_USE_COMPLEX)
  zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
           &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
           &lu->mem_usage, &stat, &info);
#else
  dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
           &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
           &lu->mem_usage, &stat, &info);
#endif
  ierr = VecRestoreArray(b,&barray);CHKERRQ(ierr);
  ierr = VecRestoreArray(x,&xarray);CHKERRQ(ierr);

  if ( !info || info == lu->A.ncol+1 ) {
    if ( lu->options.IterRefine ) {
      ierr = PetscPrintf(PETSC_COMM_SELF,"Iterative Refinement:\n");
      ierr = PetscPrintf(PETSC_COMM_SELF,"  %8s%8s%16s%16s\n", "rhs", "Steps", "FERR", "BERR");
      for (i = 0; i < 1; ++i)
        ierr = PetscPrintf(PETSC_COMM_SELF,"  %8d%8d%16e%16e\n", i+1, stat.RefineSteps, ferr, berr);
    }
  } else if ( info > 0 ){
    if ( lu->lwork == -1 ) {
      ierr = PetscPrintf(PETSC_COMM_SELF,"  ** Estimated memory: %d bytes\n", info - lu->A.ncol);
    } else {
      ierr = PetscPrintf(PETSC_COMM_SELF,"  Warning: gssvx() returns info %d\n",info);
    }
  } else if (info < 0){
    SETERRQ2(1, "info = %d, the %d-th argument in gssvx() had an illegal value", info,-info);
  }

  if ( lu->options.PrintStat ) {
    ierr = PetscPrintf(PETSC_COMM_SELF,"MatSolve__SuperLU():\n");
    StatPrint(&stat);
  }
  StatFree(&stat);
  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatLUFactorNumeric_SuperLU"
int MatLUFactorNumeric_SuperLU(Mat A,Mat *F)
{
  Mat_SeqAIJ    *aa = (Mat_SeqAIJ*)(A)->data;
  Mat_SuperLU   *lu = (Mat_SuperLU*)(*F)->spptr;
  int           ierr,info;
  SuperLUStat_t stat;
  double        ferr, berr;
  NCformat      *Ustore;
  SCformat      *Lstore;

  PetscFunctionBegin;
  if (lu->flg == SAME_NONZERO_PATTERN){ /* successing numerical factorization */
    lu->options.Fact = SamePattern;
    /* Ref: ~SuperLU_3.0/EXAMPLE/dlinsolx2.c */
    Destroy_SuperMatrix_Store(&lu->A);
    if ( lu->lwork >= 0 ) {
      Destroy_SuperNode_Matrix(&lu->L);
      Destroy_CompCol_Matrix(&lu->U);
      lu->options.Fact = SamePattern;
    }
  }

  /* Create the SuperMatrix for lu->A=A^T:
       Since SuperLU likes column-oriented matrices,we pass it the transpose,
       and then solve A^T X = B in MatSolve(). */
#if defined(PETSC_USE_COMPLEX)
  zCreate_CompCol_Matrix(&lu->A,A->n,A->m,aa->nz,(doublecomplex*)aa->a,aa->j,aa->i,
                           SLU_NC,SLU_Z,SLU_GE);
#else
  dCreate_CompCol_Matrix(&lu->A,A->n,A->m,aa->nz,aa->a,aa->j,aa->i,
                           SLU_NC,SLU_D,SLU_GE);
#endif

  /* Initialize the statistics variables. */
  StatInit(&stat);

  /* Numerical factorization */
  lu->B.ncol = 0;  /* Indicate not to solve the system */
#if defined(PETSC_USE_COMPLEX)
   zgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
           &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
           &lu->mem_usage, &stat, &info);
#else
  dgssvx(&lu->options, &lu->A, lu->perm_c, lu->perm_r, lu->etree, lu->equed, lu->R, lu->C,
           &lu->L, &lu->U, lu->work, lu->lwork, &lu->B, &lu->X, &lu->rpg, &lu->rcond, &ferr, &berr,
           &lu->mem_usage, &stat, &info);
#endif
  if ( !info || info == lu->A.ncol+1 ) {
    if ( lu->options.PivotGrowth )
      ierr = PetscPrintf(PETSC_COMM_SELF,"  Recip. pivot growth = %e\n", lu->rpg);
    if ( lu->options.ConditionNumber )
      ierr = PetscPrintf(PETSC_COMM_SELF,"  Recip. condition number = %e\n", lu->rcond);
  } else if ( info > 0 ){
    if ( lu->lwork == -1 ) {
      ierr = PetscPrintf(PETSC_COMM_SELF,"  ** Estimated memory: %d bytes\n", info - lu->A.ncol);
    } else {
      ierr = PetscPrintf(PETSC_COMM_SELF,"  Warning: gssvx() returns info %d\n",info);
    }
  } else { /* info < 0 */
    SETERRQ2(1, "info = %d, the %d-th argument in gssvx() had an illegal value", info,-info);
  }

  if ( lu->options.PrintStat ) {
    ierr = PetscPrintf(PETSC_COMM_SELF,"MatLUFactorNumeric_SuperLU():\n");
    StatPrint(&stat);
    Lstore = (SCformat *) lu->L.Store;
    Ustore = (NCformat *) lu->U.Store;
    ierr = PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in factor L = %d\n", Lstore->nnz);
    ierr = PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in factor U = %d\n", Ustore->nnz);
    ierr = PetscPrintf(PETSC_COMM_SELF,"  No of nonzeros in L+U = %d\n", Lstore->nnz + Ustore->nnz - lu->A.ncol);
    ierr = PetscPrintf(PETSC_COMM_SELF,"  L\\U MB %.3f\ttotal MB needed %.3f\texpansions %d\n",
	       lu->mem_usage.for_lu/1e6, lu->mem_usage.total_needed/1e6,
	       lu->mem_usage.expansions);
  }
  StatFree(&stat);

  lu->flg = SAME_NONZERO_PATTERN;
  PetscFunctionReturn(0);
}

/*
   Note the r permutation is ignored
*/
#undef __FUNCT__
#define __FUNCT__ "MatLUFactorSymbolic_SuperLU"
int MatLUFactorSymbolic_SuperLU(Mat A,IS r,IS c,MatFactorInfo *info,Mat *F)
{
  Mat          B;
  Mat_SuperLU  *lu;
  int          ierr,m=A->m,n=A->n,indx;
  PetscTruth   flg;
  const char   *colperm[]={"NATURAL","MMD_ATA","MMD_AT_PLUS_A","COLAMD"}; /* MY_PERMC - not supported by the petsc interface yet */
  const char   *iterrefine[]={"NOREFINE", "SINGLE", "DOUBLE", "EXTRA"};
  const char   *rowperm[]={"NOROWPERM", "LargeDiag"}; /* MY_PERMC - not supported by the petsc interface yet */

  PetscFunctionBegin;

  ierr = MatCreate(A->comm,A->m,A->n,PETSC_DETERMINE,PETSC_DETERMINE,&B);CHKERRQ(ierr);
  ierr = MatSetType(B,A->type_name);CHKERRQ(ierr);
  ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr);

  B->ops->lufactornumeric = MatLUFactorNumeric_SuperLU;
  B->ops->solve           = MatSolve_SuperLU;
  B->factor               = FACTOR_LU;
  B->assembled            = PETSC_TRUE;  /* required by -ksp_view */

  lu = (Mat_SuperLU*)(B->spptr);

  /* Set SuperLU options */
    /* the default values for options argument:
	options.Fact = DOFACT;
        options.Equil = YES;
    	options.ColPerm = COLAMD;
	options.DiagPivotThresh = 1.0;
    	options.Trans = NOTRANS;
    	options.IterRefine = NOREFINE;
    	options.SymmetricMode = NO;
    	options.PivotGrowth = NO;
    	options.ConditionNumber = NO;
    	options.PrintStat = YES;
    */
  set_default_options(&lu->options);
  /* equilibration causes error in solve(), thus not supported here. See dgssvx.c for possible reason. */
  lu->options.Equil = NO;
  lu->options.PrintStat = NO;
  lu->lwork = 0;   /* allocate space internally by system malloc */

  ierr = PetscOptionsBegin(A->comm,A->prefix,"SuperLU Options","Mat");CHKERRQ(ierr);
  /*
  ierr = PetscOptionsLogical("-mat_superlu_equil","Equil","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr);
  if (flg) lu->options.Equil = YES; -- not supported by the interface !!!
  */
  ierr = PetscOptionsEList("-mat_superlu_colperm","ColPerm","None",colperm,4,colperm[3],&indx,&flg);CHKERRQ(ierr);
  if (flg) {lu->options.ColPerm = (colperm_t)indx;}
  ierr = PetscOptionsEList("-mat_superlu_iterrefine","IterRefine","None",iterrefine,4,iterrefine[0],&indx,&flg);CHKERRQ(ierr);
  if (flg) { lu->options.IterRefine = (IterRefine_t)indx;}
  ierr = PetscOptionsLogical("-mat_superlu_symmetricmode","SymmetricMode","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr);
  if (flg) lu->options.SymmetricMode = YES;
  ierr = PetscOptionsReal("-mat_superlu_diagpivotthresh","DiagPivotThresh","None",lu->options.DiagPivotThresh,&lu->options.DiagPivotThresh,PETSC_NULL);CHKERRQ(ierr);
  ierr = PetscOptionsLogical("-mat_superlu_pivotgrowth","PivotGrowth","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr);
  if (flg) lu->options.PivotGrowth = YES;
  ierr = PetscOptionsLogical("-mat_superlu_conditionnumber","ConditionNumber","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr);
  if (flg) lu->options.ConditionNumber = YES;
  ierr = PetscOptionsEList("-mat_superlu_rowperm","rowperm","None",rowperm,2,rowperm[0],&indx,&flg);CHKERRQ(ierr);
  if (flg) {lu->options.RowPerm = (rowperm_t)indx;}
  ierr = PetscOptionsLogical("-mat_superlu_replacetinypivot","ReplaceTinyPivot","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr);
  if (flg) lu->options.ReplaceTinyPivot = YES;
  ierr = PetscOptionsLogical("-mat_superlu_printstat","PrintStat","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr);
  if (flg) lu->options.PrintStat = YES;
  ierr = PetscOptionsInt("-mat_superlu_lwork","size of work array in bytes used by factorization","None",lu->lwork,&lu->lwork,PETSC_NULL);CHKERRQ(ierr);
  if (lu->lwork > 0 ){
    ierr = PetscMalloc(lu->lwork,&lu->work);CHKERRQ(ierr);
  } else if (lu->lwork != 0 && lu->lwork != -1){
    ierr = PetscPrintf(PETSC_COMM_SELF,"   Warning: lwork %d is not supported by SUPERLU. The default lwork=0 is used.\n",lu->lwork);
    lu->lwork = 0;
  }
  PetscOptionsEnd();

#ifdef SUPERLU2
  ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatCreateNull","MatCreateNull_SuperLU",
                                    (void(*)(void))MatCreateNull_SuperLU);CHKERRQ(ierr);
#endif

  /* Allocate spaces (notice sizes are for the transpose) */
  ierr = PetscMalloc(m*sizeof(int),&lu->etree);CHKERRQ(ierr);
  ierr = PetscMalloc(n*sizeof(int),&lu->perm_r);CHKERRQ(ierr);
  ierr = PetscMalloc(m*sizeof(int),&lu->perm_c);CHKERRQ(ierr);
  ierr = PetscMalloc(n*sizeof(int),&lu->R);CHKERRQ(ierr);
  ierr = PetscMalloc(m*sizeof(int),&lu->C);CHKERRQ(ierr);

  /* create rhs and solution x without allocate space for .Store */
#if defined(PETSC_USE_COMPLEX)
  zCreate_Dense_Matrix(&lu->B, m, 1, PETSC_NULL, m, SLU_DN, SLU_Z, SLU_GE);
  zCreate_Dense_Matrix(&lu->X, m, 1, PETSC_NULL, m, SLU_DN, SLU_Z, SLU_GE);
#else
  dCreate_Dense_Matrix(&lu->B, m, 1, PETSC_NULL, m, SLU_DN, SLU_D, SLU_GE);
  dCreate_Dense_Matrix(&lu->X, m, 1, PETSC_NULL, m, SLU_DN, SLU_D, SLU_GE);
#endif

  lu->flg            = DIFFERENT_NONZERO_PATTERN;
  lu->CleanUpSuperLU = PETSC_TRUE;

  *F = B;
  PetscLogObjectMemory(B,(A->m+A->n)*sizeof(int)+sizeof(Mat_SuperLU));
  PetscFunctionReturn(0);
}

/* used by -ksp_view */
#undef __FUNCT__
#define __FUNCT__ "MatFactorInfo_SuperLU"
int MatFactorInfo_SuperLU(Mat A,PetscViewer viewer)
{
  Mat_SuperLU       *lu= (Mat_SuperLU*)A->spptr;
  int               ierr;
  superlu_options_t options;

  PetscFunctionBegin;
  /* check if matrix is superlu_dist type */
  if (A->ops->solve != MatSolve_SuperLU) PetscFunctionReturn(0);

  options = lu->options;
  ierr = PetscViewerASCIIPrintf(viewer,"SuperLU run parameters:\n");CHKERRQ(ierr);
  ierr = PetscViewerASCIIPrintf(viewer,"  Equil: %s\n",(options.Equil != NO) ? "YES": "NO");CHKERRQ(ierr);
  ierr = PetscViewerASCIIPrintf(viewer,"  ColPerm: %d\n",options.ColPerm);CHKERRQ(ierr);
  ierr = PetscViewerASCIIPrintf(viewer,"  IterRefine: %d\n",options.IterRefine);CHKERRQ(ierr);
  ierr = PetscViewerASCIIPrintf(viewer,"  SymmetricMode: %s\n",(options.SymmetricMode != NO) ? "YES": "NO");CHKERRQ(ierr);
  ierr = PetscViewerASCIIPrintf(viewer,"  DiagPivotThresh: %g\n",options.DiagPivotThresh);CHKERRQ(ierr);
  ierr = PetscViewerASCIIPrintf(viewer,"  PivotGrowth: %s\n",(options.PivotGrowth != NO) ? "YES": "NO");CHKERRQ(ierr);
  ierr = PetscViewerASCIIPrintf(viewer,"  ConditionNumber: %s\n",(options.ConditionNumber != NO) ? "YES": "NO");CHKERRQ(ierr);
  ierr = PetscViewerASCIIPrintf(viewer,"  RowPerm: %d\n",options.RowPerm);CHKERRQ(ierr);
  ierr = PetscViewerASCIIPrintf(viewer,"  ReplaceTinyPivot: %s\n",(options.ReplaceTinyPivot != NO) ? "YES": "NO");CHKERRQ(ierr);
  ierr = PetscViewerASCIIPrintf(viewer,"  PrintStat: %s\n",(options.PrintStat != NO) ? "YES": "NO");CHKERRQ(ierr);
  ierr = PetscViewerASCIIPrintf(viewer,"  lwork: %d\n",lu->lwork);CHKERRQ(ierr);

  PetscFunctionReturn(0);
}

#undef __FUNCT__
#define __FUNCT__ "MatDuplicate_SuperLU"
int MatDuplicate_SuperLU(Mat A, MatDuplicateOption op, Mat *M) {
  int         ierr;
  Mat_SuperLU *lu=(Mat_SuperLU *)A->spptr;

  PetscFunctionBegin;
  ierr = (*lu->MatDuplicate)(A,op,M);CHKERRQ(ierr);
  ierr = PetscMemcpy((*M)->spptr,lu,sizeof(Mat_SuperLU));CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

EXTERN_C_BEGIN
#undef __FUNCT__
#define __FUNCT__ "MatConvert_SuperLU_SeqAIJ"
int MatConvert_SuperLU_SeqAIJ(Mat A,const MatType type,Mat *newmat) {
  /* This routine is only called to convert an unfactored PETSc-SuperLU matrix */
  /* to its base PETSc type, so we will ignore 'MatType type'. */
  int                  ierr;
  Mat                  B=*newmat;
  Mat_SuperLU   *lu=(Mat_SuperLU *)A->spptr;

  PetscFunctionBegin;
  if (B != A) {
    ierr = MatDuplicate(A,MAT_COPY_VALUES,&B);CHKERRQ(ierr);
  }
  /* Reset the original function pointers */
  B->ops->duplicate        = lu->MatDuplicate;
  B->ops->view             = lu->MatView;
  B->ops->assemblyend      = lu->MatAssemblyEnd;
  B->ops->lufactorsymbolic = lu->MatLUFactorSymbolic;
  B->ops->destroy          = lu->MatDestroy;
  /* lu is only a function pointer stash unless we've factored the matrix, which we haven't! */
  ierr = PetscFree(lu);CHKERRQ(ierr);
  ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr);
  *newmat = B;
  PetscFunctionReturn(0);
}
EXTERN_C_END

EXTERN_C_BEGIN
#undef __FUNCT__
#define __FUNCT__ "MatConvert_SeqAIJ_SuperLU"
int MatConvert_SeqAIJ_SuperLU(Mat A,const MatType type,Mat *newmat) {
  /* This routine is only called to convert to MATSUPERLU */
  /* from MATSEQAIJ, so we will ignore 'MatType type'. */
  int         ierr;
  Mat         B=*newmat;
  Mat_SuperLU *lu;

  PetscFunctionBegin;
  if (B != A) {
    ierr = MatDuplicate(A,MAT_COPY_VALUES,&B);CHKERRQ(ierr);
  }

  ierr = PetscNew(Mat_SuperLU,&lu);CHKERRQ(ierr);
  lu->MatDuplicate         = A->ops->duplicate;
  lu->MatView              = A->ops->view;
  lu->MatAssemblyEnd       = A->ops->assemblyend;
  lu->MatLUFactorSymbolic  = A->ops->lufactorsymbolic;
  lu->MatDestroy           = A->ops->destroy;
  lu->CleanUpSuperLU       = PETSC_FALSE;

  B->spptr                 = (void*)lu;
  B->ops->duplicate        = MatDuplicate_SuperLU;
  B->ops->view             = MatView_SuperLU;
  B->ops->assemblyend      = MatAssemblyEnd_SuperLU;
  B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU;
  B->ops->choleskyfactorsymbolic = 0;
  B->ops->destroy          = MatDestroy_SuperLU;

  ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_superlu_C",
                                           "MatConvert_SeqAIJ_SuperLU",MatConvert_SeqAIJ_SuperLU);CHKERRQ(ierr);
  ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_superlu_seqaij_C",
                                           "MatConvert_SuperLU_SeqAIJ",MatConvert_SuperLU_SeqAIJ);CHKERRQ(ierr);
  PetscLogInfo(0,"Using SuperLU for SeqAIJ LU factorization and solves.");
  ierr = PetscObjectChangeTypeName((PetscObject)B,MATSUPERLU);CHKERRQ(ierr);
  *newmat = B;
  PetscFunctionReturn(0);
}
EXTERN_C_END

/*MC
  MATSUPERLU - MATSUPERLU = "superlu" - A matrix type providing direct solvers (LU) for sequential matrices
  via the external package SuperLU.

  If SuperLU is installed (see the manual for
  instructions on how to declare the existence of external packages),
  a matrix type can be constructed which invokes SuperLU solvers.
  After calling MatCreate(...,A), simply call MatSetType(A,MATSUPERLU).
  This matrix type is only supported for double precision real.

  This matrix inherits from MATSEQAIJ.  As a result, MatSeqAIJSetPreallocation is
  supported for this matrix type.  One can also call MatConvert for an inplace conversion to or from
  the MATSEQAIJ type without data copy.

  Options Database Keys:
+ -mat_type superlu - sets the matrix type to "superlu" during a call to MatSetFromOptions()
- -mat_superlu_ordering <0,1,2,3> - 0: natural ordering,
                                    1: MMD applied to A'*A,
                                    2: MMD applied to A'+A,
                                    3: COLAMD, approximate minimum degree column ordering

   Level: beginner

.seealso: PCLU
M*/

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

  PetscFunctionBegin;
  /* Change type name before calling MatSetType to force proper construction of SeqAIJ and SUPERLU types */
  ierr = PetscObjectChangeTypeName((PetscObject)A,MATSUPERLU);CHKERRQ(ierr);
  ierr = MatSetType(A,MATSEQAIJ);CHKERRQ(ierr);
  ierr = MatConvert_SeqAIJ_SuperLU(A,MATSUPERLU,&A);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}
EXTERN_C_END