ilu_mpi_bj.c

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//       Ifpack: Object-Oriented Algebraic Preconditioner Package
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/* to do: re-integrate fix-smalll-pivots */

#include "ilu_dh.h"
#include "Mem_dh.h"
#include "Parser_dh.h"
#include "Euclid_dh.h"
#include "getRow_dh.h"
#include "Factor_dh.h"
#include "SubdomainGraph_dh.h"


int symbolic_row_private (int localRow, int beg_row, int end_row,
              int *list, int *marker, int *tmpFill,
              int len, int *CVAL, double *AVAL,
              int *o2n_col, Euclid_dh ctx);

static int numeric_row_private (int localRow, int beg_row, int end_row,
                int len, int *CVAL, double *AVAL,
                REAL_DH * work, int *o2n_col, Euclid_dh ctx);


/* all non-local column indices are discarded in symbolic_row_private() */
#undef __FUNC__
#define __FUNC__ "iluk_mpi_bj"
void
iluk_mpi_bj (Euclid_dh ctx)
{
  START_FUNC_DH int *rp, *cval, *diag;
  int *CVAL;
  int i, j, len, count, col, idx = 0;
  int *list, *marker, *fill, *tmpFill;
  int temp, m, from = ctx->from, to = ctx->to;
  int *n2o_row, *o2n_col;
  int first_row, last_row;
  double *AVAL;
  REAL_DH *work, *aval;
  Factor_dh F = ctx->F;
  SubdomainGraph_dh sg = ctx->sg;

  if (ctx->F == NULL)
    {
      SET_V_ERROR ("ctx->F is NULL");
    }
  if (ctx->F->rp == NULL)
    {
      SET_V_ERROR ("ctx->F->rp is NULL");
    }

/*  printf_dh("====================== starting iluk_mpi_bj; level= %i\n\n", ctx->level);
*/

  m = F->m;
  rp = F->rp;
  cval = F->cval;
  fill = F->fill;
  diag = F->diag;
  aval = F->aval;
  work = ctx->work;

  n2o_row = sg->n2o_row;
  o2n_col = sg->o2n_col;

  /* allocate and initialize working space */
  list = (int *) MALLOC_DH ((m + 1) * sizeof (int));
  CHECK_V_ERROR;
  marker = (int *) MALLOC_DH (m * sizeof (int));
  CHECK_V_ERROR;
  tmpFill = (int *) MALLOC_DH (m * sizeof (int));
  CHECK_V_ERROR;
  for (i = 0; i < m; ++i)
    {
      marker[i] = -1;
      work[i] = 0.0;
    }

  /*---------- main loop ----------*/

  /* global numbers of first and last locally owned rows,
     with respect to A 
   */
  first_row = sg->beg_row[myid_dh];
  last_row = first_row + sg->row_count[myid_dh];
  for (i = from; i < to; ++i)
    {

      int row = n2o_row[i]; /* local row number */
      int globalRow = row + first_row;  /* global row number */

      EuclidGetRow (ctx->A, globalRow, &len, &CVAL, &AVAL);
      CHECK_V_ERROR;

      /* compute scaling value for row(i) */
      if (ctx->isScaled)
    {
      compute_scaling_private (i, len, AVAL, ctx);
      CHECK_V_ERROR;
    }

      /* Compute symbolic factor for row(i);
         this also performs sparsification
       */
      count = symbolic_row_private (i, first_row, last_row,
                    list, marker, tmpFill,
                    len, CVAL, AVAL, o2n_col, ctx);
      CHECK_V_ERROR;

      /* Ensure adequate storage; reallocate, if necessary. */
      if (idx + count > F->alloc)
    {
      Factor_dhReallocate (F, idx, count);
      CHECK_V_ERROR;
      SET_INFO ("REALLOCATED from lu_mpi_bj");
      cval = F->cval;
      fill = F->fill;
      aval = F->aval;
    }

      /* Copy factored symbolic row to permanent storage */
      col = list[m];
      while (count--)
    {
      cval[idx] = col;
      fill[idx] = tmpFill[col];
      ++idx;
      col = list[col];
    }

      /* add row-pointer to start of next row. */
      rp[i + 1] = idx;

      /* Insert pointer to diagonal */
      temp = rp[i];
      while (cval[temp] != i)
    ++temp;
      diag[i] = temp;

      /* compute numeric factor for current row */
      numeric_row_private (i, first_row, last_row,
               len, CVAL, AVAL, work, o2n_col, ctx);
      CHECK_V_ERROR EuclidRestoreRow (ctx->A, globalRow, &len, &CVAL, &AVAL);
      CHECK_V_ERROR;

      /* Copy factored numeric row to permanent storage,
         and re-zero work vector
       */
      for (j = rp[i]; j < rp[i + 1]; ++j)
    {
      col = cval[j];
      aval[j] = work[col];
      work[col] = 0.0;
    }

      /* check for zero diagonal */
      if (!aval[diag[i]])
    {
      sprintf (msgBuf_dh, "zero diagonal in local row %i", i + 1);
      SET_V_ERROR (msgBuf_dh);
    }
    }

  FREE_DH (list);
  CHECK_V_ERROR;
  FREE_DH (tmpFill);
  CHECK_V_ERROR;
  FREE_DH (marker);
  CHECK_V_ERROR;

END_FUNC_DH}



/* Computes ILU(K) factor of a single row; returns fill 
   count for the row.  Explicitly inserts diag if not already 
   present.  On return, all column indices are local 
   (i.e, referenced to 0).
*/
#undef __FUNC__
#define __FUNC__ "symbolic_row_private"
int
symbolic_row_private (int localRow, int beg_row, int end_row,
              int *list, int *marker, int *tmpFill,
              int len, int *CVAL, double *AVAL,
              int *o2n_col, Euclid_dh ctx)
{
  START_FUNC_DH int level = ctx->level, m = ctx->F->m;
  int *cval = ctx->F->cval, *diag = ctx->F->diag, *rp = ctx->F->rp;
  int *fill = ctx->F->fill;
  int count = 0;
  int j, node, tmp, col, head;
  int fill1, fill2;
  float val;
  double thresh = ctx->sparseTolA;
  REAL_DH scale;

  scale = ctx->scale[localRow];
  ctx->stats[NZA_STATS] += (double) len;

  /* Insert col indices in linked list, and values in work vector.
   * List[m] points to the first (smallest) col in the linked list.
   * Column values are adjusted from global to local numbering.
   */
  list[m] = m;
  for (j = 0; j < len; ++j)
    {
      tmp = m;
      col = *CVAL++;
      val = *AVAL++;

      /* throw out nonlocal columns */
      if (col >= beg_row && col < end_row)
    {
      col -= beg_row;   /* adjust column to local zero-based */
      col = o2n_col[col];   /* permute column */
      if (fabs (scale * val) > thresh || col == localRow)
        {           /* sparsification */
          ++count;
          while (col > list[tmp])
        tmp = list[tmp];
          list[col] = list[tmp];
          list[tmp] = col;
          tmpFill[col] = 0;
          marker[col] = localRow;
        }
    }
    }

  /* insert diag if not already present */
  if (marker[localRow] != localRow)
    {
/*     ctx->symbolicZeroDiags += 1; */
      tmp = m;
      while (localRow > list[tmp])
    tmp = list[tmp];
      list[localRow] = list[tmp];
      list[tmp] = localRow;
      tmpFill[localRow] = 0;
      marker[localRow] = localRow;
      ++count;
    }
  ctx->stats[NZA_USED_STATS] += (double) count;

  /* update row from previously factored rows */
  head = m;
  if (level > 0)
    {
      while (list[head] < localRow)
    {
      node = list[head];
      fill1 = tmpFill[node];

      if (fill1 < level)
        {
          for (j = diag[node] + 1; j < rp[node + 1]; ++j)
        {
          col = cval[j];
          fill2 = fill1 + fill[j] + 1;

          if (fill2 <= level)
            {
              /* if newly discovered fill entry, mark it as discovered;
               * if entry has level <= K, add it to the linked-list.
               */
              if (marker[col] < localRow)
            {
              tmp = head;
              marker[col] = localRow;
              tmpFill[col] = fill2;
              while (col > list[tmp])
                tmp = list[tmp];
              list[col] = list[tmp];
              list[tmp] = col;
              ++count;  /* increment fill count */
            }

              /* if previously-discovered fill, update the entry's level. */
              else
            {
              tmpFill[col] =
                (fill2 < tmpFill[col]) ? fill2 : tmpFill[col];
            }
            }
        }
        }
      head = list[head];    /* advance to next item in linked list */
    }
    }
END_FUNC_VAL (count)}


#undef __FUNC__
#define __FUNC__ "numeric_row_private"
int
numeric_row_private (int localRow, int beg_row, int end_row,
             int len, int *CVAL, double *AVAL,
             REAL_DH * work, int *o2n_col, Euclid_dh ctx)
{
  START_FUNC_DH double pc, pv, multiplier;
  int j, k, col, row;
  int *rp = ctx->F->rp, *cval = ctx->F->cval;
  int *diag = ctx->F->diag;
  double val;
  REAL_DH *aval = ctx->F->aval, scale;

  scale = ctx->scale[localRow];

  /* zero work vector */
  /* note: indices in col[] are already permuted, and are 
     local (zero-based)
   */
  for (j = rp[localRow]; j < rp[localRow + 1]; ++j)
    {
      col = cval[j];
      work[col] = 0.0;
    }

  /* init work vector with values from A */
  /* (note: some values may be na due to sparsification; this is O.K.) */
  for (j = 0; j < len; ++j)
    {
      col = *CVAL++;
      val = *AVAL++;

      if (col >= beg_row && col < end_row)
    {
      col -= beg_row;   /* adjust column to local zero-based */
      col = o2n_col[col];   /* we permute the indices from A */
      work[col] = val * scale;
    }
    }

  for (j = rp[localRow]; j < diag[localRow]; ++j)
    {
      row = cval[j];
      pc = work[row];

      if (pc != 0.0)
    {
      pv = aval[diag[row]];
      multiplier = pc / pv;
      work[row] = multiplier;

      for (k = diag[row] + 1; k < rp[row + 1]; ++k)
        {
          col = cval[k];
          work[col] -= (multiplier * aval[k]);
        }
    }
    }

  /* check for zero or too small of a pivot */
#if 0
  if (fabs (work[i]) <= pivotTol)
    {
      /* yuck! assume row scaling, and just stick in a value */
      aval[diag[i]] = pivotFix;
    }
#endif

END_FUNC_VAL (0)}