void hypre_BoomerAMGTruncateInterp( hypre_ParCSRMatrix *P,
HYPRE_Real eps, HYPRE_Real dlt,
HYPRE_Int * CF_marker )
/* Truncate the interpolation matrix P, but only in rows for which the
marker is <0. Truncation means that an element P(i,j) is set to 0 if
P(i,j)>0 and P(i,j)<eps*max( P(i,j) ) or if
P(i,j)>0 and P(i,j)<dlt*max( -P(i,j) ) or if
P(i,j)<0 and P(i,j)>dlt*min( -P(i,j) ) or if
P(i,j)<0 and P(i,j)>eps*min( P(i,j) )
( 0<eps,dlt<1, typically 0.1=dlt<eps=0.2, )
The min and max are only computed locally, as I'm guessing that there isn't
usually much to be gained (in the way of improved performance) by getting
them perfectly right.
*/
/* The function hypre_BoomerAMGInterpTruncation in par_interp.c is
very similar. It looks at fabs(value) rather than separately
dealing with value<0 and value>0 as recommended by Klaus Stuben,
thus as this function does. In this function, only "marked" rows
are affected. Lastly, in hypre_BoomerAMGInterpTruncation, if any
element gets discarded, it reallocates arrays to the new size.
*/
{
hypre_CSRMatrix *P_diag = hypre_ParCSRMatrixDiag(P);
hypre_CSRMatrix *P_offd = hypre_ParCSRMatrixOffd(P);
HYPRE_Real *P_diag_data = hypre_CSRMatrixData(P_diag);
HYPRE_Int *P_diag_i = hypre_CSRMatrixI(P_diag);
HYPRE_Int *P_diag_j = hypre_CSRMatrixJ(P_diag);
HYPRE_Real *P_offd_data = hypre_CSRMatrixData(P_offd);
HYPRE_Int *P_offd_i = hypre_CSRMatrixI(P_offd);
HYPRE_Int *P_offd_j = hypre_CSRMatrixJ(P_offd);
HYPRE_Int *new_P_diag_i;
HYPRE_Int *new_P_offd_i;
HYPRE_Int num_rows_diag_P = hypre_CSRMatrixNumRows(P_diag);
HYPRE_Int num_rows_offd_P = hypre_CSRMatrixNumRows(P_offd);
HYPRE_Int num_nonzeros_diag = hypre_CSRMatrixNumNonzeros(P_diag);
HYPRE_Int num_nonzeros_offd = hypre_CSRMatrixNumNonzeros(P_offd);
#if 0
MPI_Comm comm = hypre_ParCSRMatrixComm( P );
HYPRE_Real vmax1, vmin1;
#endif
HYPRE_Real vmax = 0.0;
HYPRE_Real vmin = 0.0;
HYPRE_Real v, old_sum, new_sum, scale, wmax, wmin;
HYPRE_Int i1, m, m1d, m1o;
/* compute vmax = eps*max(P(i,j)), vmin = eps*min(P(i,j)) */
for ( i1 = 0; i1 < num_rows_diag_P; i1++ )
{
for ( m=P_diag_i[i1]; m<P_diag_i[i1+1]; ++m )
{
v = P_diag_data[m];
vmax = hypre_max( v, vmax );
vmin = hypre_min( v, vmin );
}
for ( m=P_offd_i[i1]; m<P_offd_i[i1+1]; ++m )
{
v = P_offd_data[m];
vmax = hypre_max( v, vmax );
vmin = hypre_min( v, vmin );
}
}
#if 0
/* This can make max,min global so results don't depend on no. processors
We don't want this except for testing, or maybe this could be put
someplace better. I don't like adding communication here, for a minor reason.
*/
vmax1 = vmax; vmin1 = vmin;
hypre_MPI_Allreduce( &vmax1, &vmax, 1, HYPRE_MPI_REAL, hypre_MPI_MAX, comm );
hypre_MPI_Allreduce( &vmin1, &vmin, 1, HYPRE_MPI_REAL, hypre_MPI_MIN, comm );
#endif
if ( vmax <= 0.0 ) vmax = 1.0; /* make sure no v is v>vmax if no v is v>0 */
if ( vmin >= 0.0 ) vmin = -1.0; /* make sure no v is v<vmin if no v is v<0 */
wmax = - dlt * vmin;
wmin = - dlt * vmax;
vmax *= eps;
vmin *= eps;
/* Repack the i,j,and data arrays so as to discard the small elements of P.
Elements of Coarse rows (CF_marker>=0) are always kept.
The arrays are not re-allocated, so there will generally be unused space
at the ends of the arrays. */
new_P_diag_i = hypre_CTAlloc( HYPRE_Int, num_rows_diag_P+1 );
new_P_offd_i = hypre_CTAlloc( HYPRE_Int, num_rows_offd_P+1 );
m1d = P_diag_i[0];
m1o = P_offd_i[0];
for ( i1 = 0; i1 < num_rows_diag_P; i1++ )
{
old_sum = 0;
new_sum = 0;
for ( m=P_diag_i[i1]; m<P_diag_i[i1+1]; ++m )
{
v = P_diag_data[m];
old_sum += v;
if ( CF_marker[i1]>=0 || ( v>=vmax && v>=wmax ) || ( v<=vmin && v<=wmin ) )
{ /* keep v */
new_sum += v;
P_diag_j[m1d] = P_diag_j[m];
P_diag_data[m1d] = P_diag_data[m];
++m1d;
}
else
{ /* discard v */
--num_nonzeros_diag;
}
}
for ( m=P_offd_i[i1]; m<P_offd_i[i1+1]; ++m )
{
v = P_offd_data[m];
old_sum += v;
if ( CF_marker[i1]>=0 || ( v>=vmax && v>=wmax ) || ( v<=vmin && v<=wmin ) )
{ /* keep v */
new_sum += v;
P_offd_j[m1o] = P_offd_j[m];
P_offd_data[m1o] = P_offd_data[m];
++m1o;
}
else
{ /* discard v */
--num_nonzeros_offd;
}
}
new_P_diag_i[i1+1] = m1d;
if ( i1<num_rows_offd_P ) new_P_offd_i[i1+1] = m1o;
/* rescale to keep row sum the same */
if (new_sum!=0) scale = old_sum/new_sum; else scale = 1.0;
for ( m=new_P_diag_i[i1]; m<new_P_diag_i[i1+1]; ++m )
P_diag_data[m] *= scale;
if ( i1<num_rows_offd_P ) /* this test fails when there is no offd block */
for ( m=new_P_offd_i[i1]; m<new_P_offd_i[i1+1]; ++m )
P_offd_data[m] *= scale;
}
for ( i1 = 1; i1 <= num_rows_diag_P; i1++ )
{
P_diag_i[i1] = new_P_diag_i[i1];
if ( i1<=num_rows_offd_P && num_nonzeros_offd>0 ) P_offd_i[i1] = new_P_offd_i[i1];
}
hypre_TFree( new_P_diag_i );
if ( num_rows_offd_P>0 ) hypre_TFree( new_P_offd_i );
hypre_CSRMatrixNumNonzeros(P_diag) = num_nonzeros_diag;
hypre_CSRMatrixNumNonzeros(P_offd) = num_nonzeros_offd;
hypre_ParCSRMatrixSetDNumNonzeros( P );
hypre_ParCSRMatrixSetNumNonzeros( P );
}
hypre_ParCSRMatrix *
hypre_ParCSRBlockMatrixConvertToParCSRMatrix(hypre_ParCSRBlockMatrix *matrix)
{
MPI_Comm comm = hypre_ParCSRBlockMatrixComm(matrix);
hypre_CSRBlockMatrix *diag = hypre_ParCSRBlockMatrixDiag(matrix);
hypre_CSRBlockMatrix *offd = hypre_ParCSRBlockMatrixOffd(matrix);
HYPRE_Int block_size = hypre_ParCSRBlockMatrixBlockSize(matrix);
HYPRE_Int global_num_rows = hypre_ParCSRBlockMatrixGlobalNumRows(matrix);
HYPRE_Int global_num_cols = hypre_ParCSRBlockMatrixGlobalNumCols(matrix);
HYPRE_Int *row_starts = hypre_ParCSRBlockMatrixRowStarts(matrix);
HYPRE_Int *col_starts = hypre_ParCSRBlockMatrixColStarts(matrix);
HYPRE_Int num_cols_offd = hypre_CSRBlockMatrixNumCols(offd);
HYPRE_Int num_nonzeros_diag = hypre_CSRBlockMatrixNumNonzeros(diag);
HYPRE_Int num_nonzeros_offd = hypre_CSRBlockMatrixNumNonzeros(offd);
hypre_ParCSRMatrix *matrix_C;
HYPRE_Int *matrix_C_row_starts;
HYPRE_Int *matrix_C_col_starts;
HYPRE_Int *counter, *new_j_map;
HYPRE_Int size_j, size_map, index, new_num_cols, removed = 0;
HYPRE_Int *offd_j, *col_map_offd, *new_col_map_offd;
HYPRE_Int num_procs, i, j;
hypre_CSRMatrix *diag_nozeros, *offd_nozeros;
hypre_MPI_Comm_size(comm,&num_procs);
#ifdef HYPRE_NO_GLOBAL_PARTITION
matrix_C_row_starts = hypre_CTAlloc(HYPRE_Int, 2);
matrix_C_col_starts = hypre_CTAlloc(HYPRE_Int, 2);
for(i = 0; i < 2; i++)
{
matrix_C_row_starts[i] = row_starts[i]*block_size;
matrix_C_col_starts[i] = col_starts[i]*block_size;
}
#else
matrix_C_row_starts = hypre_CTAlloc(HYPRE_Int, num_procs + 1);
matrix_C_col_starts = hypre_CTAlloc(HYPRE_Int, num_procs + 1);
for(i = 0; i < num_procs + 1; i++)
{
matrix_C_row_starts[i] = row_starts[i]*block_size;
matrix_C_col_starts[i] = col_starts[i]*block_size;
}
#endif
matrix_C = hypre_ParCSRMatrixCreate(comm, global_num_rows*block_size,
global_num_cols*block_size, matrix_C_row_starts,
matrix_C_col_starts, num_cols_offd*block_size,
num_nonzeros_diag*block_size*block_size,
num_nonzeros_offd*block_size*block_size);
hypre_ParCSRMatrixInitialize(matrix_C);
/* DIAG */
hypre_CSRMatrixDestroy(hypre_ParCSRMatrixDiag(matrix_C));
hypre_ParCSRMatrixDiag(matrix_C) =
hypre_CSRBlockMatrixConvertToCSRMatrix(diag);
/* AB - added to delete zeros */
diag_nozeros = hypre_CSRMatrixDeleteZeros(
hypre_ParCSRMatrixDiag(matrix_C), 1e-14);
if(diag_nozeros)
{
hypre_CSRMatrixDestroy(hypre_ParCSRMatrixDiag(matrix_C));
hypre_ParCSRMatrixDiag(matrix_C) = diag_nozeros;
}
/* OFF-DIAG */
hypre_CSRMatrixDestroy(hypre_ParCSRMatrixOffd(matrix_C));
hypre_ParCSRMatrixOffd(matrix_C) =
hypre_CSRBlockMatrixConvertToCSRMatrix(offd);
/* AB - added to delete zeros - this just deletes from data and j arrays */
offd_nozeros = hypre_CSRMatrixDeleteZeros(
hypre_ParCSRMatrixOffd(matrix_C), 1e-14);
if(offd_nozeros)
{
hypre_CSRMatrixDestroy(hypre_ParCSRMatrixOffd(matrix_C));
hypre_ParCSRMatrixOffd(matrix_C) = offd_nozeros;
removed = 1;
}
/* now convert the col_map_offd */
for (i = 0; i < num_cols_offd; i++)
for (j = 0; j < block_size; j++)
hypre_ParCSRMatrixColMapOffd(matrix_C)[i*block_size + j] =
hypre_ParCSRBlockMatrixColMapOffd(matrix)[i]*block_size + j;
/* if we deleted zeros, then it is possible that col_map_offd can be
compressed as well - this requires some amount of work that could be skipped... */
if (removed)
{
size_map = num_cols_offd*block_size;
counter = hypre_CTAlloc(HYPRE_Int, size_map);
new_j_map = hypre_CTAlloc(HYPRE_Int, size_map);
offd_j = hypre_CSRMatrixJ(hypre_ParCSRMatrixOffd(matrix_C));
col_map_offd = hypre_ParCSRMatrixColMapOffd(matrix_C);
size_j = hypre_CSRMatrixNumNonzeros(hypre_ParCSRMatrixOffd(matrix_C));
/* mark which off_d entries are found in j */
for (i=0; i < size_j; i++)
{
counter[offd_j[i]] = 1;
}
/*now find new numbering for columns (we will delete the
cols where counter = 0*/
index = 0;
for (i=0; i < size_map; i++)
{
if (counter[i]) new_j_map[i] = index++;
}
new_num_cols = index;
/* if there are some col entries to remove: */
if (!(index == size_map))
{
/* go thru j and adjust entries */
for (i=0; i < size_j; i++)
{
offd_j[i] = new_j_map[offd_j[i]];
}
/*now go thru col map and get rid of non-needed entries */
new_col_map_offd = hypre_CTAlloc(HYPRE_Int, new_num_cols);
index = 0;
for (i=0; i < size_map; i++)
{
if (counter[i])
{
new_col_map_offd[index++] = col_map_offd[i];
}
}
/* set the new col map */
hypre_TFree(col_map_offd);
hypre_ParCSRMatrixColMapOffd(matrix_C) = new_col_map_offd;
/* modify the number of cols */
hypre_CSRMatrixNumCols(hypre_ParCSRMatrixOffd(matrix_C)) = new_num_cols;
}
hypre_TFree(new_j_map);
hypre_TFree(counter);
}
hypre_ParCSRMatrixSetNumNonzeros( matrix_C );
hypre_ParCSRMatrixSetDNumNonzeros( matrix_C );
/* we will not copy the comm package */
hypre_ParCSRMatrixCommPkg(matrix_C) = NULL;
return matrix_C;
}
