/*
Function: hypre_CSRMatrixElimCreate
Prepare the Ae matrix: count nnz, initialize I, allocate J and data.
*/
void hypre_CSRMatrixElimCreate(hypre_CSRMatrix *A,
hypre_CSRMatrix *Ae,
HYPRE_Int nrows, HYPRE_Int *rows,
HYPRE_Int ncols, HYPRE_Int *cols,
HYPRE_Int *col_mark)
{
HYPRE_Int i, j, col;
HYPRE_Int A_beg, A_end;
HYPRE_Int *A_i = hypre_CSRMatrixI(A);
HYPRE_Int *A_j = hypre_CSRMatrixJ(A);
HYPRE_Int A_rows = hypre_CSRMatrixNumRows(A);
hypre_CSRMatrixI(Ae) = hypre_TAlloc(HYPRE_Int, A_rows+1);
HYPRE_Int *Ae_i = hypre_CSRMatrixI(Ae);
HYPRE_Int nnz = 0;
for (i = 0; i < A_rows; i++)
{
Ae_i[i] = nnz;
A_beg = A_i[i];
A_end = A_i[i+1];
if (hypre_BinarySearch(rows, i, nrows) >= 0)
{
/* full row */
nnz += A_end - A_beg;
if (col_mark)
{
for (j = A_beg; j < A_end; j++)
{
col_mark[A_j[j]] = 1;
}
}
}
else
{
/* count columns */
for (j = A_beg; j < A_end; j++)
{
col = A_j[j];
if (hypre_BinarySearch(cols, col, ncols) >= 0)
{
nnz++;
if (col_mark) {
col_mark[col] = 1;
}
}
}
}
}
Ae_i[A_rows] = nnz;
hypre_CSRMatrixJ(Ae) = hypre_TAlloc(HYPRE_Int, nnz);
hypre_CSRMatrixData(Ae) = hypre_TAlloc(HYPRE_Real, nnz);
hypre_CSRMatrixNumNonzeros(Ae) = nnz;
}
/*
Function: hypre_CSRMatrixEliminateRowsCols
Eliminate rows and columns of A, store eliminated values in Ae.
If 'diag' is nonzero, the eliminated diagonal of A is set to identity.
If 'col_remap' is not NULL it specifies renumbering of columns of Ae.
*/
void hypre_CSRMatrixEliminateRowsCols(hypre_CSRMatrix *A,
hypre_CSRMatrix *Ae,
HYPRE_Int nrows, HYPRE_Int *rows,
HYPRE_Int ncols, HYPRE_Int *cols,
int diag, HYPRE_Int* col_remap)
{
HYPRE_Int i, j, k, col;
HYPRE_Int A_beg, Ae_beg, A_end;
HYPRE_Real a;
HYPRE_Int *A_i = hypre_CSRMatrixI(A);
HYPRE_Int *A_j = hypre_CSRMatrixJ(A);
HYPRE_Real *A_data = hypre_CSRMatrixData(A);
HYPRE_Int A_rows = hypre_CSRMatrixNumRows(A);
HYPRE_Int *Ae_i = hypre_CSRMatrixI(Ae);
HYPRE_Int *Ae_j = hypre_CSRMatrixJ(Ae);
HYPRE_Real *Ae_data = hypre_CSRMatrixData(Ae);
for (i = 0; i < A_rows; i++)
{
A_beg = A_i[i];
A_end = A_i[i+1];
Ae_beg = Ae_i[i];
if (hypre_BinarySearch(rows, i, nrows) >= 0)
{
/* eliminate row */
for (j = A_beg, k = Ae_beg; j < A_end; j++, k++)
{
col = A_j[j];
Ae_j[k] = col_remap ? col_remap[col] : col;
a = (diag && col == i) ? 1.0 : 0.0;
Ae_data[k] = A_data[j] - a;
A_data[j] = a;
}
}
else
{
/* eliminate columns */
for (j = A_beg, k = Ae_beg; j < A_end; j++)
{
col = A_j[j];
if (hypre_BinarySearch(cols, col, ncols) >= 0)
{
Ae_j[k] = col_remap ? col_remap[col] : col;
Ae_data[k] = A_data[j];
A_data[j] = 0.0;
k++;
}
}
}
}
}
hypre_ParCSRMatrix * hypre_ParMatmul_FC(
hypre_ParCSRMatrix * A, hypre_ParCSRMatrix * P, HYPRE_Int * CF_marker,
HYPRE_Int * dof_func, HYPRE_Int * dof_func_offd )
/* hypre_parMatmul_FC creates and returns the "Fine"-designated rows of the
matrix product A*P. A's size is (nC+nF)*(nC+nF), P's size is (nC+nF)*nC
where nC is the number of coarse rows/columns, nF the number of fine
rows/columns. The size of C=A*P is (nC+nF)*nC, even though not all rows
of C are actually computed. If we were to construct a matrix consisting
only of the computed rows of C, its size would be nF*nC.
"Fine" is defined solely by the marker array, and for example could be
a proper subset of the fine points of a multigrid hierarchy.
*/
{
/* To compute a submatrix of C containing only the computed data, i.e.
only "Fine" rows, we would have to do a lot of computational work,
with a lot of communication. The communication is because such a
matrix would need global information that depends on which rows are
"Fine".
*/
MPI_Comm comm = hypre_ParCSRMatrixComm(A);
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
double *A_diag_data = hypre_CSRMatrixData(A_diag);
HYPRE_Int *A_diag_i = hypre_CSRMatrixI(A_diag);
HYPRE_Int *A_diag_j = hypre_CSRMatrixJ(A_diag);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
double *A_offd_data = hypre_CSRMatrixData(A_offd);
HYPRE_Int *A_offd_i = hypre_CSRMatrixI(A_offd);
HYPRE_Int *A_offd_j = hypre_CSRMatrixJ(A_offd);
HYPRE_Int *row_starts_A = hypre_ParCSRMatrixRowStarts(A);
HYPRE_Int num_rows_diag_A = hypre_CSRMatrixNumRows(A_diag);
HYPRE_Int num_cols_diag_A = hypre_CSRMatrixNumCols(A_diag);
HYPRE_Int num_cols_offd_A = hypre_CSRMatrixNumCols(A_offd);
hypre_CSRMatrix *P_diag = hypre_ParCSRMatrixDiag(P);
double *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_CSRMatrix *P_offd = hypre_ParCSRMatrixOffd(P);
HYPRE_Int *col_map_offd_P = hypre_ParCSRMatrixColMapOffd(P);
double *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 first_col_diag_P = hypre_ParCSRMatrixFirstColDiag(P);
HYPRE_Int last_col_diag_P;
HYPRE_Int *col_starts_P = hypre_ParCSRMatrixColStarts(P);
HYPRE_Int num_rows_diag_P = hypre_CSRMatrixNumRows(P_diag);
HYPRE_Int num_cols_diag_P = hypre_CSRMatrixNumCols(P_diag);
HYPRE_Int num_cols_offd_P = hypre_CSRMatrixNumCols(P_offd);
hypre_ParCSRMatrix *C;
HYPRE_Int *col_map_offd_C;
HYPRE_Int *map_P_to_C;
hypre_CSRMatrix *C_diag;
double *C_diag_data;
HYPRE_Int *C_diag_i;
HYPRE_Int *C_diag_j;
hypre_CSRMatrix *C_offd;
double *C_offd_data=NULL;
HYPRE_Int *C_offd_i=NULL;
HYPRE_Int *C_offd_j=NULL;
HYPRE_Int C_diag_size;
HYPRE_Int C_offd_size;
HYPRE_Int num_cols_offd_C = 0;
hypre_CSRMatrix *Ps_ext;
double *Ps_ext_data;
HYPRE_Int *Ps_ext_i;
HYPRE_Int *Ps_ext_j;
double *P_ext_diag_data;
HYPRE_Int *P_ext_diag_i;
HYPRE_Int *P_ext_diag_j;
HYPRE_Int P_ext_diag_size;
double *P_ext_offd_data;
HYPRE_Int *P_ext_offd_i;
HYPRE_Int *P_ext_offd_j;
HYPRE_Int P_ext_offd_size;
HYPRE_Int *P_marker;
HYPRE_Int *temp;
HYPRE_Int i, j;
HYPRE_Int i1, i2, i3;
HYPRE_Int jj2, jj3;
HYPRE_Int jj_count_diag, jj_count_offd;
HYPRE_Int jj_row_begin_diag, jj_row_begin_offd;
HYPRE_Int start_indexing = 0; /* start indexing for C_data at 0 */
HYPRE_Int n_rows_A_global, n_cols_A_global;
HYPRE_Int n_rows_P_global, n_cols_P_global;
HYPRE_Int allsquare = 0;
HYPRE_Int cnt, cnt_offd, cnt_diag;
HYPRE_Int num_procs;
HYPRE_Int value;
double a_entry;
double a_b_product;
n_rows_A_global = hypre_ParCSRMatrixGlobalNumRows(A);
n_cols_A_global = hypre_ParCSRMatrixGlobalNumCols(A);
n_rows_P_global = hypre_ParCSRMatrixGlobalNumRows(P);
n_cols_P_global = hypre_ParCSRMatrixGlobalNumCols(P);
if (n_cols_A_global != n_rows_P_global || num_cols_diag_A != num_rows_diag_P)
{
hypre_printf(" Error! Incompatible matrix dimensions!\n");
return NULL;
}
/* if (num_rows_A==num_cols_P) allsquare = 1; */
/*-----------------------------------------------------------------------
* Extract P_ext, i.e. portion of P that is stored on neighbor procs
* and needed locally for matrix matrix product
*-----------------------------------------------------------------------*/
hypre_MPI_Comm_size(comm, &num_procs);
if (num_procs > 1)
{
/*---------------------------------------------------------------------
* If there exists no CommPkg for A, a CommPkg is generated using
* equally load balanced partitionings within
* hypre_ParCSRMatrixExtractBExt
*--------------------------------------------------------------------*/
Ps_ext = hypre_ParCSRMatrixExtractBExt(P,A,1);
Ps_ext_data = hypre_CSRMatrixData(Ps_ext);
Ps_ext_i = hypre_CSRMatrixI(Ps_ext);
Ps_ext_j = hypre_CSRMatrixJ(Ps_ext);
}
P_ext_diag_i = hypre_CTAlloc(HYPRE_Int, num_cols_offd_A+1);
P_ext_offd_i = hypre_CTAlloc(HYPRE_Int, num_cols_offd_A+1);
P_ext_diag_size = 0;
P_ext_offd_size = 0;
last_col_diag_P = first_col_diag_P + num_cols_diag_P -1;
for (i=0; i < num_cols_offd_A; i++)
{
for (j=Ps_ext_i[i]; j < Ps_ext_i[i+1]; j++)
if (Ps_ext_j[j] < first_col_diag_P || Ps_ext_j[j] > last_col_diag_P)
P_ext_offd_size++;
else
P_ext_diag_size++;
P_ext_diag_i[i+1] = P_ext_diag_size;
P_ext_offd_i[i+1] = P_ext_offd_size;
}
if (P_ext_diag_size)
{
P_ext_diag_j = hypre_CTAlloc(HYPRE_Int, P_ext_diag_size);
P_ext_diag_data = hypre_CTAlloc(double, P_ext_diag_size);
}
if (P_ext_offd_size)
{
P_ext_offd_j = hypre_CTAlloc(HYPRE_Int, P_ext_offd_size);
P_ext_offd_data = hypre_CTAlloc(double, P_ext_offd_size);
}
cnt_offd = 0;
cnt_diag = 0;
for (i=0; i < num_cols_offd_A; i++)
{
for (j=Ps_ext_i[i]; j < Ps_ext_i[i+1]; j++)
if (Ps_ext_j[j] < first_col_diag_P || Ps_ext_j[j] > last_col_diag_P)
{
P_ext_offd_j[cnt_offd] = Ps_ext_j[j];
P_ext_offd_data[cnt_offd++] = Ps_ext_data[j];
}
else
{
P_ext_diag_j[cnt_diag] = Ps_ext_j[j] - first_col_diag_P;
P_ext_diag_data[cnt_diag++] = Ps_ext_data[j];
}
}
if (num_procs > 1)
{
hypre_CSRMatrixDestroy(Ps_ext);
Ps_ext = NULL;
}
cnt = 0;
if (P_ext_offd_size || num_cols_offd_P)
{
temp = hypre_CTAlloc(HYPRE_Int, P_ext_offd_size+num_cols_offd_P);
for (i=0; i < P_ext_offd_size; i++)
temp[i] = P_ext_offd_j[i];
cnt = P_ext_offd_size;
for (i=0; i < num_cols_offd_P; i++)
temp[cnt++] = col_map_offd_P[i];
}
if (cnt)
{
qsort0(temp, 0, cnt-1);
num_cols_offd_C = 1;
value = temp[0];
for (i=1; i < cnt; i++)
{
if (temp[i] > value)
{
value = temp[i];
temp[num_cols_offd_C++] = value;
}
}
}
if (num_cols_offd_C)
col_map_offd_C = hypre_CTAlloc(HYPRE_Int,num_cols_offd_C);
for (i=0; i < num_cols_offd_C; i++)
col_map_offd_C[i] = temp[i];
if (P_ext_offd_size || num_cols_offd_P)
hypre_TFree(temp);
for (i=0 ; i < P_ext_offd_size; i++)
P_ext_offd_j[i] = hypre_BinarySearch(col_map_offd_C,
P_ext_offd_j[i],
num_cols_offd_C);
if (num_cols_offd_P)
{
map_P_to_C = hypre_CTAlloc(HYPRE_Int,num_cols_offd_P);
cnt = 0;
for (i=0; i < num_cols_offd_C; i++)
if (col_map_offd_C[i] == col_map_offd_P[cnt])
{
map_P_to_C[cnt++] = i;
if (cnt == num_cols_offd_P) break;
}
}
/*-----------------------------------------------------------------------
* Allocate marker array.
*-----------------------------------------------------------------------*/
P_marker = hypre_CTAlloc(HYPRE_Int, num_cols_diag_P+num_cols_offd_C);
/*-----------------------------------------------------------------------
* Initialize some stuff.
*-----------------------------------------------------------------------*/
for (i1 = 0; i1 < num_cols_diag_P+num_cols_offd_C; i1++)
{
P_marker[i1] = -1;
}
/* no changes for the marked version above this point */
/* This function call is the first pass: */
hypre_ParMatmul_RowSizes_Marked(
&C_diag_i, &C_offd_i, &P_marker,
A_diag_i, A_diag_j, A_offd_i, A_offd_j,
P_diag_i, P_diag_j, P_offd_i, P_offd_j,
P_ext_diag_i, P_ext_diag_j, P_ext_offd_i, P_ext_offd_j,
map_P_to_C,
&C_diag_size, &C_offd_size,
num_rows_diag_A, num_cols_offd_A, allsquare,
num_cols_diag_P, num_cols_offd_P,
num_cols_offd_C, CF_marker, dof_func, dof_func_offd
);
/* The above call of hypre_ParMatmul_RowSizes_Marked computed
two scalars: C_diag_size, C_offd_size,
and two arrays: C_diag_i, C_offd_i
( P_marker is also computed, but only used internally )
*/
/*-----------------------------------------------------------------------
* Allocate C_diag_data and C_diag_j arrays.
* Allocate C_offd_data and C_offd_j arrays.
*-----------------------------------------------------------------------*/
last_col_diag_P = first_col_diag_P + num_cols_diag_P - 1;
C_diag_data = hypre_CTAlloc(double, C_diag_size);
C_diag_j = hypre_CTAlloc(HYPRE_Int, C_diag_size);
if (C_offd_size)
{
C_offd_data = hypre_CTAlloc(double, C_offd_size);
C_offd_j = hypre_CTAlloc(HYPRE_Int, C_offd_size);
}
/*-----------------------------------------------------------------------
* Second Pass: Fill in C_diag_data and C_diag_j.
* Second Pass: Fill in C_offd_data and C_offd_j.
*-----------------------------------------------------------------------*/
/*-----------------------------------------------------------------------
* Initialize some stuff.
*-----------------------------------------------------------------------*/
jj_count_diag = start_indexing;
jj_count_offd = start_indexing;
for (i1 = 0; i1 < num_cols_diag_P+num_cols_offd_C; i1++)
{
P_marker[i1] = -1;
}
/*-----------------------------------------------------------------------
* Loop over interior c-points.
*-----------------------------------------------------------------------*/
for (i1 = 0; i1 < num_rows_diag_A; i1++)
{
if ( CF_marker[i1] < 0 ) /* i1 is a fine row */
/* ... This and the coarse row code are the only parts between first pass
and near the end where
hypre_ParMatmul_FC is different from the regular hypre_ParMatmul */
{
/*--------------------------------------------------------------------
* Create diagonal entry, C_{i1,i1}
*--------------------------------------------------------------------*/
jj_row_begin_diag = jj_count_diag;
jj_row_begin_offd = jj_count_offd;
/*-----------------------------------------------------------------
* Loop over entries in row i1 of A_offd.
*-----------------------------------------------------------------*/
if (num_cols_offd_A)
{
for (jj2 = A_offd_i[i1]; jj2 < A_offd_i[i1+1]; jj2++)
{
i2 = A_offd_j[jj2];
if( dof_func==NULL || dof_func[i1] == dof_func_offd[i2] )
{ /* interpolate only like "functions" */
a_entry = A_offd_data[jj2];
/*-----------------------------------------------------------
* Loop over entries in row i2 of P_ext.
*-----------------------------------------------------------*/
for (jj3 = P_ext_offd_i[i2]; jj3 < P_ext_offd_i[i2+1]; jj3++)
{
i3 = num_cols_diag_P+P_ext_offd_j[jj3];
a_b_product = a_entry * P_ext_offd_data[jj3];
/*--------------------------------------------------------
* Check P_marker to see that C_{i1,i3} has not already
* been accounted for. If it has not, create a new entry.
* If it has, add new contribution.
*--------------------------------------------------------*/
if (P_marker[i3] < jj_row_begin_offd)
{
P_marker[i3] = jj_count_offd;
C_offd_data[jj_count_offd] = a_b_product;
C_offd_j[jj_count_offd] = i3-num_cols_diag_P;
jj_count_offd++;
}
else
C_offd_data[P_marker[i3]] += a_b_product;
}
for (jj3 = P_ext_diag_i[i2]; jj3 < P_ext_diag_i[i2+1]; jj3++)
{
i3 = P_ext_diag_j[jj3];
a_b_product = a_entry * P_ext_diag_data[jj3];
if (P_marker[i3] < jj_row_begin_diag)
{
P_marker[i3] = jj_count_diag;
C_diag_data[jj_count_diag] = a_b_product;
C_diag_j[jj_count_diag] = i3;
jj_count_diag++;
}
else
C_diag_data[P_marker[i3]] += a_b_product;
}
}
else
{ /* Interpolation mat should be 0 where i1 and i2 correspond to
different "functions". As we haven't created an entry for
C(i1,i2), nothing needs to be done. */
}
}
}
/*-----------------------------------------------------------------
* Loop over entries in row i1 of A_diag.
*-----------------------------------------------------------------*/
for (jj2 = A_diag_i[i1]; jj2 < A_diag_i[i1+1]; jj2++)
{
i2 = A_diag_j[jj2];
if( dof_func==NULL || dof_func[i1] == dof_func[i2] )
{ /* interpolate only like "functions" */
a_entry = A_diag_data[jj2];
/*-----------------------------------------------------------
* Loop over entries in row i2 of P_diag.
*-----------------------------------------------------------*/
for (jj3 = P_diag_i[i2]; jj3 < P_diag_i[i2+1]; jj3++)
{
i3 = P_diag_j[jj3];
a_b_product = a_entry * P_diag_data[jj3];
/*--------------------------------------------------------
* Check P_marker to see that C_{i1,i3} has not already
* been accounted for. If it has not, create a new entry.
* If it has, add new contribution.
*--------------------------------------------------------*/
if (P_marker[i3] < jj_row_begin_diag)
{
P_marker[i3] = jj_count_diag;
C_diag_data[jj_count_diag] = a_b_product;
C_diag_j[jj_count_diag] = i3;
jj_count_diag++;
}
else
{
C_diag_data[P_marker[i3]] += a_b_product;
}
}
if (num_cols_offd_P)
{
for (jj3 = P_offd_i[i2]; jj3 < P_offd_i[i2+1]; jj3++)
{
i3 = num_cols_diag_P+map_P_to_C[P_offd_j[jj3]];
a_b_product = a_entry * P_offd_data[jj3];
/*--------------------------------------------------------
* Check P_marker to see that C_{i1,i3} has not already
* been accounted for. If it has not, create a new entry.
* If it has, add new contribution.
*--------------------------------------------------------*/
if (P_marker[i3] < jj_row_begin_offd)
{
P_marker[i3] = jj_count_offd;
C_offd_data[jj_count_offd] = a_b_product;
C_offd_j[jj_count_offd] = i3-num_cols_diag_P;
jj_count_offd++;
}
else
{
C_offd_data[P_marker[i3]] += a_b_product;
}
}
}
}
else
{ /* Interpolation mat should be 0 where i1 and i2 correspond to
different "functions". As we haven't created an entry for
C(i1,i2), nothing needs to be done. */
}
}
}
else /* i1 is a coarse row.*/
/* Copy P coarse-row values to C. This is useful if C is meant to
become a replacement for P */
{
if (num_cols_offd_P)
{
for (jj2 = P_offd_i[i1]; jj2 < P_offd_i[i1+1]; jj2++)
{
C_offd_j[jj_count_offd] = P_offd_j[jj_count_offd];
C_offd_data[jj_count_offd] = P_offd_data[jj_count_offd];
++jj_count_offd;
}
}
for (jj2 = P_diag_i[i1]; jj2 < P_diag_i[i1+1]; jj2++)
{
C_diag_j[jj_count_diag] = P_diag_j[jj2];
C_diag_data[jj_count_diag] = P_diag_data[jj2];
++jj_count_diag;
}
}
}
C = hypre_ParCSRMatrixCreate(
comm, n_rows_A_global, n_cols_P_global,
row_starts_A, col_starts_P, num_cols_offd_C, C_diag_size, C_offd_size );
/* Note that C does not own the partitionings */
hypre_ParCSRMatrixSetRowStartsOwner(C,0);
hypre_ParCSRMatrixSetColStartsOwner(C,0);
C_diag = hypre_ParCSRMatrixDiag(C);
hypre_CSRMatrixData(C_diag) = C_diag_data;
hypre_CSRMatrixI(C_diag) = C_diag_i;
hypre_CSRMatrixJ(C_diag) = C_diag_j;
C_offd = hypre_ParCSRMatrixOffd(C);
hypre_CSRMatrixI(C_offd) = C_offd_i;
hypre_ParCSRMatrixOffd(C) = C_offd;
if (num_cols_offd_C)
{
hypre_CSRMatrixData(C_offd) = C_offd_data;
hypre_CSRMatrixJ(C_offd) = C_offd_j;
hypre_ParCSRMatrixColMapOffd(C) = col_map_offd_C;
}
/*-----------------------------------------------------------------------
* Free various arrays
*-----------------------------------------------------------------------*/
hypre_TFree(P_marker);
hypre_TFree(P_ext_diag_i);
if (P_ext_diag_size)
{
hypre_TFree(P_ext_diag_j);
hypre_TFree(P_ext_diag_data);
}
hypre_TFree(P_ext_offd_i);
if (P_ext_offd_size)
{
hypre_TFree(P_ext_offd_j);
hypre_TFree(P_ext_offd_data);
}
if (num_cols_offd_P) hypre_TFree(map_P_to_C);
return C;
}
HYPRE_Int hypre_HarmonicExtension (hypre_CSRMatrix *A,
hypre_CSRMatrix *P,
HYPRE_Int num_DOF, HYPRE_Int *DOF,
HYPRE_Int num_idof, HYPRE_Int *idof,
HYPRE_Int num_bdof, HYPRE_Int *bdof)
{
HYPRE_Int ierr = 0;
HYPRE_Int i, j, k, l, m;
double factor;
HYPRE_Int *IA = hypre_CSRMatrixI(A);
HYPRE_Int *JA = hypre_CSRMatrixJ(A);
double *dataA = hypre_CSRMatrixData(A);
HYPRE_Int *IP = hypre_CSRMatrixI(P);
HYPRE_Int *JP = hypre_CSRMatrixJ(P);
double *dataP = hypre_CSRMatrixData(P);
double * Aii = hypre_CTAlloc(double, num_idof*num_idof);
double * Pi = hypre_CTAlloc(double, num_idof*num_DOF);
/* Loop over the rows of A */
for (i = 0; i < num_idof; i++)
for (j = IA[i]; j < IA[i+1]; j++)
{
/* Global to local*/
k = hypre_BinarySearch(idof,JA[j], num_idof);
/* If a column is a bdof, compute its participation in Pi = Aib x Pb */
if (k == -1)
{
k = hypre_BinarySearch(bdof,JA[j], num_bdof);
if (k > -1)
{
for (l = IP[k+num_idof]; l < IP[k+num_idof+1]; l++)
{
m = hypre_BinarySearch(DOF,JP[l], num_DOF);
if (m > -1)
{
m+=i*num_DOF;
/* Pi[i*num_DOF+m] += dataA[j] * dataP[l];*/
Pi[m] += dataA[j] * dataP[l];
}
}
}
}
/* If a column is an idof, put it in Aii */
else
Aii[i*num_idof+k] = dataA[j];
}
/* Perform Gaussian elimination in [Aii, Pi] */
for (j = 0; j < num_idof-1; j++)
if (Aii[j*num_idof+j] != 0.0)
for (i = j+1; i < num_idof; i++)
if (Aii[i*num_idof+j] != 0.0)
{
factor = Aii[i*num_idof+j]/Aii[j*num_idof+j];
for (m = j+1; m < num_idof; m++)
Aii[i*num_idof+m] -= factor * Aii[j*num_idof+m];
for (m = 0; m < num_DOF; m++)
Pi[i*num_DOF+m] -= factor * Pi[j*num_DOF+m];
}
/* Back Substitution */
for (i = num_idof-1; i >= 0; i--)
{
for (j = i+1; j < num_idof; j++)
if (Aii[i*num_idof+j] != 0.0)
for (m = 0; m < num_DOF; m++)
Pi[i*num_DOF+m] -= Aii[i*num_idof+j] * Pi[j*num_DOF+m];
for (m = 0; m < num_DOF; m++)
Pi[i*num_DOF+m] /= Aii[i*num_idof+i];
}
/* Put -Pi back in P. We assume that each idof depends on _all_ DOFs */
for (i = 0; i < num_idof; i++, JP += num_DOF, dataP += num_DOF)
for (j = 0; j < num_DOF; j++)
{
JP[j] = DOF[j];
dataP[j] = -Pi[i*num_DOF+j];
}
hypre_TFree(Aii);
hypre_TFree(Pi);
return ierr;
}
HYPRE_Int HYPRE_ParCSRMLConstructMHMatrix(HYPRE_ParCSRMatrix A, MH_Matrix *mh_mat,
MPI_Comm comm, HYPRE_Int *partition,MH_Context *obj)
{
HYPRE_Int i, j, index, my_id, nprocs, msgid, *tempCnt;
HYPRE_Int sendProcCnt, *sendLeng, *sendProc, **sendList;
HYPRE_Int recvProcCnt, *recvLeng, *recvProc;
HYPRE_Int rowLeng, *colInd, startRow, endRow, localEqns;
HYPRE_Int *diagSize, *offdiagSize, externLeng, *externList, ncnt, nnz;
HYPRE_Int *rowptr, *columns, num_bdry;
double *colVal, *values;
hypre_MPI_Request *Request;
hypre_MPI_Status status;
/* -------------------------------------------------------- */
/* get machine information and local matrix information */
/* -------------------------------------------------------- */
hypre_MPI_Comm_rank(comm, &my_id);
hypre_MPI_Comm_size(comm, &nprocs);
startRow = partition[my_id];
endRow = partition[my_id+1] - 1;
localEqns = endRow - startRow + 1;
/* -------------------------------------------------------- */
/* probe A to find out about diagonal and off-diagonal */
/* block information */
/* -------------------------------------------------------- */
diagSize = (HYPRE_Int*) malloc( sizeof(HYPRE_Int) * localEqns );
offdiagSize = (HYPRE_Int*) malloc( sizeof(HYPRE_Int) * localEqns );
num_bdry = 0;
for ( i = startRow; i <= endRow; i++ )
{
diagSize[i-startRow] = offdiagSize[i-startRow] = 0;
HYPRE_ParCSRMatrixGetRow(A, i, &rowLeng, &colInd, &colVal);
for (j = 0; j < rowLeng; j++)
if ( colInd[j] < startRow || colInd[j] > endRow )
{
//if ( colVal[j] != 0.0 ) offdiagSize[i-startRow]++;
offdiagSize[i-startRow]++;
}
else
{
//if ( colVal[j] != 0.0 ) diagSize[i-startRow]++;
diagSize[i-startRow]++;
}
HYPRE_ParCSRMatrixRestoreRow(A, i, &rowLeng, &colInd, &colVal);
if ( diagSize[i-startRow] + offdiagSize[i-startRow] == 1 ) num_bdry++;
}
/* -------------------------------------------------------- */
/* construct external node list in global eqn numbers */
/* -------------------------------------------------------- */
externLeng = 0;
for ( i = 0; i < localEqns; i++ ) externLeng += offdiagSize[i];
if ( externLeng > 0 )
externList = (HYPRE_Int *) malloc( sizeof(HYPRE_Int) * externLeng);
else externList = NULL;
externLeng = 0;
for ( i = startRow; i <= endRow; i++ )
{
HYPRE_ParCSRMatrixGetRow(A, i, &rowLeng, &colInd, &colVal);
for (j = 0; j < rowLeng; j++)
{
if ( colInd[j] < startRow || colInd[j] > endRow )
//if ( colVal[j] != 0.0 ) externList[externLeng++] = colInd[j];
externList[externLeng++] = colInd[j];
}
HYPRE_ParCSRMatrixRestoreRow(A, i, &rowLeng, &colInd, &colVal);
}
qsort0( externList, 0, externLeng-1 );
ncnt = 0;
for ( i = 1; i < externLeng; i++ )
{
if ( externList[i] != externList[ncnt] )
externList[++ncnt] = externList[i];
}
externLeng = ncnt + 1;
/* -------------------------------------------------------- */
/* allocate the CSR matrix */
/* -------------------------------------------------------- */
nnz = 0;
for ( i = 0; i < localEqns; i++ ) nnz += diagSize[i] + offdiagSize[i];
rowptr = (HYPRE_Int *) malloc( (localEqns + 1) * sizeof(HYPRE_Int) );
columns = (HYPRE_Int *) malloc( nnz * sizeof(HYPRE_Int) );
values = (double *) malloc( nnz * sizeof(double) );
rowptr[0] = 0;
for ( i = 1; i <= localEqns; i++ )
rowptr[i] = rowptr[i-1] + diagSize[i-1] + offdiagSize[i-1];
free( diagSize );
free( offdiagSize );
/* -------------------------------------------------------- */
/* put the matrix data in the CSR matrix */
/* -------------------------------------------------------- */
rowptr[0] = 0;
ncnt = 0;
for ( i = startRow; i <= endRow; i++ )
{
HYPRE_ParCSRMatrixGetRow(A, i, &rowLeng, &colInd, &colVal);
for (j = 0; j < rowLeng; j++)
{
index = colInd[j];
//if ( colVal[j] != 0.0 )
{
if ( index < startRow || index > endRow )
{
columns[ncnt] = hypre_BinarySearch(externList,index,
externLeng );
columns[ncnt] += localEqns;
values [ncnt++] = colVal[j];
}
else
{
columns[ncnt] = index - startRow;
values[ncnt++] = colVal[j];
}
}
}
rowptr[i-startRow+1] = ncnt;
HYPRE_ParCSRMatrixRestoreRow(A, i, &rowLeng, &colInd, &colVal);
}
assert( ncnt == nnz );
/* -------------------------------------------------------- */
/* initialize the MH_Matrix data structure */
/* -------------------------------------------------------- */
mh_mat->Nrows = localEqns;
mh_mat->rowptr = rowptr;
mh_mat->colnum = columns;
mh_mat->values = values;
mh_mat->sendProcCnt = 0;
mh_mat->recvProcCnt = 0;
mh_mat->sendLeng = NULL;
mh_mat->recvLeng = NULL;
mh_mat->sendProc = NULL;
mh_mat->recvProc = NULL;
mh_mat->sendList = NULL;
mh_mat->map = externList;
/* -------------------------------------------------------- */
/* form the remote portion of the matrix */
/* -------------------------------------------------------- */
if ( nprocs > 1 )
{
/* ----------------------------------------------------- */
/* count number of elements to be received from each */
/* remote processor (assume sequential mapping) */
/* ----------------------------------------------------- */
tempCnt = (HYPRE_Int *) malloc( sizeof(HYPRE_Int) * nprocs );
for ( i = 0; i < nprocs; i++ ) tempCnt[i] = 0;
for ( i = 0; i < externLeng; i++ )
{
for ( j = 0; j < nprocs; j++ )
{
if ( externList[i] >= partition[j] &&
externList[i] < partition[j+1] )
{
tempCnt[j]++;
break;
}
}
}
/* ----------------------------------------------------- */
/* compile a list processors data is to be received from */
/* ----------------------------------------------------- */
recvProcCnt = 0;
for ( i = 0; i < nprocs; i++ )
if ( tempCnt[i] > 0 ) recvProcCnt++;
recvLeng = (HYPRE_Int*) malloc( sizeof(HYPRE_Int) * recvProcCnt );
recvProc = (HYPRE_Int*) malloc( sizeof(HYPRE_Int) * recvProcCnt );
recvProcCnt = 0;
for ( i = 0; i < nprocs; i++ )
{
if ( tempCnt[i] > 0 )
{
recvProc[recvProcCnt] = i;
recvLeng[recvProcCnt++] = tempCnt[i];
}
}
/* ----------------------------------------------------- */
/* each processor has to find out how many processors it */
/* has to send data to */
/* ----------------------------------------------------- */
sendLeng = (HYPRE_Int *) malloc( nprocs * sizeof(HYPRE_Int) );
for ( i = 0; i < nprocs; i++ ) tempCnt[i] = 0;
for ( i = 0; i < recvProcCnt; i++ ) tempCnt[recvProc[i]] = 1;
hypre_MPI_Allreduce(tempCnt, sendLeng, nprocs, HYPRE_MPI_INT, hypre_MPI_SUM, comm );
sendProcCnt = sendLeng[my_id];
free( sendLeng );
if ( sendProcCnt > 0 )
{
sendLeng = (HYPRE_Int *) malloc( sendProcCnt * sizeof(HYPRE_Int) );
sendProc = (HYPRE_Int *) malloc( sendProcCnt * sizeof(HYPRE_Int) );
sendList = (HYPRE_Int **) malloc( sendProcCnt * sizeof(HYPRE_Int*) );
}
else
{
sendLeng = sendProc = NULL;
sendList = NULL;
}
/* ----------------------------------------------------- */
/* each processor sends to all processors it expects to */
/* receive data about the lengths of data expected */
/* ----------------------------------------------------- */
msgid = 539;
for ( i = 0; i < recvProcCnt; i++ )
{
hypre_MPI_Send((void*) &recvLeng[i],1,HYPRE_MPI_INT,recvProc[i],msgid,comm);
}
for ( i = 0; i < sendProcCnt; i++ )
{
hypre_MPI_Recv((void*) &sendLeng[i],1,HYPRE_MPI_INT,hypre_MPI_ANY_SOURCE,msgid,
comm,&status);
sendProc[i] = status.hypre_MPI_SOURCE;
sendList[i] = (HYPRE_Int *) malloc( sendLeng[i] * sizeof(HYPRE_Int) );
if ( sendList[i] == NULL )
hypre_printf("allocate problem %d \n", sendLeng[i]);
}
/* ----------------------------------------------------- */
/* each processor sends to all processors it expects to */
/* receive data about the equation numbers */
/* ----------------------------------------------------- */
for ( i = 0; i < nprocs; i++ ) tempCnt[i] = 0;
ncnt = 1;
for ( i = 0; i < externLeng; i++ )
{
if ( externList[i] >= partition[ncnt] )
{
tempCnt[ncnt-1] = i;
i--;
ncnt++;
}
}
for ( i = ncnt-1; i < nprocs; i++ ) tempCnt[i] = externLeng;
/* ----------------------------------------------------- */
/* send the global equation numbers */
/* ----------------------------------------------------- */
msgid = 540;
for ( i = 0; i < recvProcCnt; i++ )
{
if ( recvProc[i] == 0 ) j = 0;
else j = tempCnt[recvProc[i]-1];
rowLeng = recvLeng[i];
hypre_MPI_Send((void*) &externList[j],rowLeng,HYPRE_MPI_INT,recvProc[i],
msgid,comm);
}
for ( i = 0; i < sendProcCnt; i++ )
{
rowLeng = sendLeng[i];
hypre_MPI_Recv((void*)sendList[i],rowLeng,HYPRE_MPI_INT,sendProc[i],
msgid,comm,&status);
}
/* ----------------------------------------------------- */
/* convert the send list from global to local numbers */
/* ----------------------------------------------------- */
for ( i = 0; i < sendProcCnt; i++ )
{
for ( j = 0; j < sendLeng[i]; j++ )
{
index = sendList[i][j] - startRow;
if ( index < 0 || index >= localEqns )
{
hypre_printf("%d : Construct MH matrix Error - index out ");
hypre_printf("of range%d\n", my_id, index);
}
sendList[i][j] = index;
}
}
/* ----------------------------------------------------- */
/* convert the send list from global to local numbers */
/* ----------------------------------------------------- */
mh_mat->sendProcCnt = sendProcCnt;
mh_mat->recvProcCnt = recvProcCnt;
mh_mat->sendLeng = sendLeng;
mh_mat->recvLeng = recvLeng;
mh_mat->sendProc = sendProc;
mh_mat->recvProc = recvProc;
mh_mat->sendList = sendList;
/* ----------------------------------------------------- */
/* clean up */
/* ----------------------------------------------------- */
free( tempCnt );
}
return 0;
}
HYPRE_Int hypre_CreateLambda(void *amg_vdata)
{
hypre_ParAMGData *amg_data = amg_vdata;
/* Data Structure variables */
MPI_Comm comm;
hypre_ParCSRMatrix **A_array;
hypre_ParVector **F_array;
hypre_ParVector **U_array;
hypre_ParCSRMatrix *A_tmp;
hypre_ParCSRMatrix *Lambda;
hypre_CSRMatrix *L_diag;
hypre_CSRMatrix *L_offd;
hypre_CSRMatrix *A_tmp_diag;
hypre_CSRMatrix *A_tmp_offd;
hypre_ParVector *Xtilde;
hypre_ParVector *Rtilde;
hypre_Vector *Xtilde_local;
hypre_Vector *Rtilde_local;
hypre_ParCSRCommPkg *comm_pkg;
hypre_ParCSRCommPkg *L_comm_pkg = NULL;
hypre_ParCSRCommHandle *comm_handle;
HYPRE_Real *L_diag_data;
HYPRE_Real *L_offd_data;
HYPRE_Real *buf_data = NULL;
HYPRE_Real *tmp_data;
HYPRE_Real *x_data;
HYPRE_Real *r_data;
HYPRE_Real *l1_norms;
HYPRE_Real *A_tmp_diag_data;
HYPRE_Real *A_tmp_offd_data;
HYPRE_Real *D_data = NULL;
HYPRE_Real *D_data_offd = NULL;
HYPRE_Int *L_diag_i;
HYPRE_Int *L_diag_j;
HYPRE_Int *L_offd_i;
HYPRE_Int *L_offd_j;
HYPRE_Int *A_tmp_diag_i;
HYPRE_Int *A_tmp_offd_i;
HYPRE_Int *A_tmp_diag_j;
HYPRE_Int *A_tmp_offd_j;
HYPRE_Int *L_recv_ptr = NULL;
HYPRE_Int *L_send_ptr = NULL;
HYPRE_Int *L_recv_procs = NULL;
HYPRE_Int *L_send_procs = NULL;
HYPRE_Int *L_send_map_elmts = NULL;
HYPRE_Int *recv_procs;
HYPRE_Int *send_procs;
HYPRE_Int *send_map_elmts;
HYPRE_Int *send_map_starts;
HYPRE_Int *recv_vec_starts;
HYPRE_Int *all_send_procs = NULL;
HYPRE_Int *all_recv_procs = NULL;
HYPRE_Int *remap = NULL;
HYPRE_Int *level_start;
HYPRE_Int addlvl;
HYPRE_Int additive;
HYPRE_Int mult_additive;
HYPRE_Int num_levels;
HYPRE_Int num_add_lvls;
HYPRE_Int num_procs;
HYPRE_Int num_sends, num_recvs;
HYPRE_Int num_sends_L = 0;
HYPRE_Int num_recvs_L = 0;
HYPRE_Int send_data_L = 0;
HYPRE_Int num_rows_L = 0;
HYPRE_Int num_rows_tmp = 0;
HYPRE_Int num_cols_offd_L = 0;
HYPRE_Int num_cols_offd = 0;
HYPRE_Int level, i, j, k;
HYPRE_Int this_proc, cnt, cnt_diag, cnt_offd;
HYPRE_Int cnt_recv, cnt_send, cnt_row, row_start;
HYPRE_Int start_diag, start_offd, indx, cnt_map;
HYPRE_Int start, j_indx, index, cnt_level;
HYPRE_Int max_sends, max_recvs;
/* Local variables */
HYPRE_Int Solve_err_flag = 0;
HYPRE_Int num_threads;
HYPRE_Int num_nonzeros_diag;
HYPRE_Int num_nonzeros_offd;
HYPRE_Real **l1_norms_ptr = NULL;
HYPRE_Real *relax_weight = NULL;
HYPRE_Real relax_type;
/* Acquire data and allocate storage */
num_threads = hypre_NumThreads();
A_array = hypre_ParAMGDataAArray(amg_data);
F_array = hypre_ParAMGDataFArray(amg_data);
U_array = hypre_ParAMGDataUArray(amg_data);
additive = hypre_ParAMGDataAdditive(amg_data);
mult_additive = hypre_ParAMGDataMultAdditive(amg_data);
num_levels = hypre_ParAMGDataNumLevels(amg_data);
relax_weight = hypre_ParAMGDataRelaxWeight(amg_data);
relax_type = hypre_ParAMGDataGridRelaxType(amg_data)[1];
comm = hypre_ParCSRMatrixComm(A_array[0]);
hypre_MPI_Comm_size(comm,&num_procs);
l1_norms_ptr = hypre_ParAMGDataL1Norms(amg_data);
addlvl = hypre_max(additive, mult_additive);
num_add_lvls = num_levels+1-addlvl;
level_start = hypre_CTAlloc(HYPRE_Int, num_add_lvls+1);
send_data_L = 0;
num_rows_L = 0;
num_cols_offd_L = 0;
num_nonzeros_diag = 0;
num_nonzeros_offd = 0;
level_start[0] = 0;
cnt = 1;
max_sends = 0;
max_recvs = 0;
for (i=addlvl; i < num_levels; i++)
{
A_tmp = A_array[i];
A_tmp_diag = hypre_ParCSRMatrixDiag(A_tmp);
A_tmp_offd = hypre_ParCSRMatrixOffd(A_tmp);
A_tmp_diag_i = hypre_CSRMatrixI(A_tmp_diag);
A_tmp_offd_i = hypre_CSRMatrixI(A_tmp_offd);
num_rows_tmp = hypre_CSRMatrixNumRows(A_tmp_diag);
num_cols_offd = hypre_CSRMatrixNumCols(A_tmp_offd);
num_rows_L += num_rows_tmp;
level_start[cnt] = level_start[cnt-1] + num_rows_tmp;
cnt++;
num_cols_offd_L += num_cols_offd;
num_nonzeros_diag += A_tmp_diag_i[num_rows_tmp];
num_nonzeros_offd += A_tmp_offd_i[num_rows_tmp];
comm_pkg = hypre_ParCSRMatrixCommPkg(A_tmp);
if (comm_pkg)
{
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
max_sends += num_sends;
if (num_sends)
send_data_L += hypre_ParCSRCommPkgSendMapStart(comm_pkg,num_sends);
max_recvs += hypre_ParCSRCommPkgNumRecvs(comm_pkg);
}
}
if (max_sends >= num_procs ||max_recvs >= num_procs)
{
max_sends = num_procs;
max_recvs = num_procs;
}
if (max_sends) all_send_procs = hypre_CTAlloc(HYPRE_Int, max_sends);
if (max_recvs) all_recv_procs = hypre_CTAlloc(HYPRE_Int, max_recvs);
cnt_send = 0;
cnt_recv = 0;
if (max_sends || max_recvs)
{
if (max_sends < num_procs && max_recvs < num_procs)
{
for (i=addlvl; i < num_levels; i++)
{
A_tmp = A_array[i];
comm_pkg = hypre_ParCSRMatrixCommPkg(A_tmp);
if (comm_pkg)
{
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg);
send_procs = hypre_ParCSRCommPkgSendProcs(comm_pkg);
recv_procs = hypre_ParCSRCommPkgRecvProcs(comm_pkg);
for (j = 0; j < num_sends; j++)
all_send_procs[cnt_send++] = send_procs[j];
for (j = 0; j < num_recvs; j++)
all_recv_procs[cnt_recv++] = recv_procs[j];
}
}
if (max_sends)
{
qsort0(all_send_procs, 0, max_sends-1);
num_sends_L = 1;
this_proc = all_send_procs[0];
for (i=1; i < max_sends; i++)
{
if (all_send_procs[i] > this_proc)
{
this_proc = all_send_procs[i];
all_send_procs[num_sends_L++] = this_proc;
}
}
L_send_procs = hypre_CTAlloc(HYPRE_Int, num_sends_L);
for (j=0; j < num_sends_L; j++)
L_send_procs[j] = all_send_procs[j];
hypre_TFree(all_send_procs);
}
if (max_recvs)
{
qsort0(all_recv_procs, 0, max_recvs-1);
num_recvs_L = 1;
this_proc = all_recv_procs[0];
for (i=1; i < max_recvs; i++)
{
if (all_recv_procs[i] > this_proc)
{
this_proc = all_recv_procs[i];
all_recv_procs[num_recvs_L++] = this_proc;
}
}
L_recv_procs = hypre_CTAlloc(HYPRE_Int, num_recvs_L);
for (j=0; j < num_recvs_L; j++)
L_recv_procs[j] = all_recv_procs[j];
hypre_TFree(all_recv_procs);
}
L_recv_ptr = hypre_CTAlloc(HYPRE_Int, num_recvs_L+1);
L_send_ptr = hypre_CTAlloc(HYPRE_Int, num_sends_L+1);
for (i=addlvl; i < num_levels; i++)
{
A_tmp = A_array[i];
comm_pkg = hypre_ParCSRMatrixCommPkg(A_tmp);
if (comm_pkg)
{
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg);
send_procs = hypre_ParCSRCommPkgSendProcs(comm_pkg);
recv_procs = hypre_ParCSRCommPkgRecvProcs(comm_pkg);
send_map_starts = hypre_ParCSRCommPkgSendMapStarts(comm_pkg);
recv_vec_starts = hypre_ParCSRCommPkgRecvVecStarts(comm_pkg);
}
else
{
num_sends = 0;
num_recvs = 0;
}
for (k = 0; k < num_sends; k++)
{
this_proc = hypre_BinarySearch(L_send_procs,send_procs[k],num_sends_L);
L_send_ptr[this_proc+1] += send_map_starts[k+1]-send_map_starts[k];
}
for (k = 0; k < num_recvs; k++)
{
this_proc = hypre_BinarySearch(L_recv_procs,recv_procs[k],num_recvs_L);
L_recv_ptr[this_proc+1] += recv_vec_starts[k+1]-recv_vec_starts[k];
}
}
L_recv_ptr[0] = 0;
for (i=1; i < num_recvs_L; i++)
L_recv_ptr[i+1] += L_recv_ptr[i];
L_send_ptr[0] = 0;
for (i=1; i < num_sends_L; i++)
L_send_ptr[i+1] += L_send_ptr[i];
}
else
{
num_recvs_L = 0;
num_sends_L = 0;
for (i=addlvl; i < num_levels; i++)
{
A_tmp = A_array[i];
comm_pkg = hypre_ParCSRMatrixCommPkg(A_tmp);
if (comm_pkg)
{
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg);
send_procs = hypre_ParCSRCommPkgSendProcs(comm_pkg);
recv_procs = hypre_ParCSRCommPkgRecvProcs(comm_pkg);
send_map_starts = hypre_ParCSRCommPkgSendMapStarts(comm_pkg);
recv_vec_starts = hypre_ParCSRCommPkgRecvVecStarts(comm_pkg);
for (j = 0; j < num_sends; j++)
{
this_proc = send_procs[j];
if (all_send_procs[this_proc] == 0)
num_sends_L++;
all_send_procs[this_proc] += send_map_starts[j+1]-send_map_starts[j];
}
for (j = 0; j < num_recvs; j++)
{
this_proc = recv_procs[j];
if (all_recv_procs[this_proc] == 0)
num_recvs_L++;
all_recv_procs[this_proc] += recv_vec_starts[j+1]-recv_vec_starts[j];
}
}
}
if (max_sends)
{
L_send_procs = hypre_CTAlloc(HYPRE_Int, num_sends_L);
L_send_ptr = hypre_CTAlloc(HYPRE_Int, num_sends_L+1);
num_sends_L = 0;
for (j=0; j < num_procs; j++)
{
this_proc = all_send_procs[j];
if (this_proc)
{
L_send_procs[num_sends_L++] = j;
L_send_ptr[num_sends_L] = this_proc + L_send_ptr[num_sends_L-1];
}
}
}
if (max_recvs)
{
L_recv_procs = hypre_CTAlloc(HYPRE_Int, num_recvs_L);
L_recv_ptr = hypre_CTAlloc(HYPRE_Int, num_recvs_L+1);
num_recvs_L = 0;
for (j=0; j < num_procs; j++)
{
this_proc = all_recv_procs[j];
if (this_proc)
{
L_recv_procs[num_recvs_L++] = j;
L_recv_ptr[num_recvs_L] = this_proc + L_recv_ptr[num_recvs_L-1];
}
}
}
}
}
if (max_sends) hypre_TFree(all_send_procs);
if (max_recvs) hypre_TFree(all_recv_procs);
L_diag = hypre_CSRMatrixCreate(num_rows_L, num_rows_L, num_nonzeros_diag);
L_offd = hypre_CSRMatrixCreate(num_rows_L, num_cols_offd_L, num_nonzeros_offd);
hypre_CSRMatrixInitialize(L_diag);
hypre_CSRMatrixInitialize(L_offd);
if (num_nonzeros_diag)
{
L_diag_data = hypre_CSRMatrixData(L_diag);
L_diag_j = hypre_CSRMatrixJ(L_diag);
}
L_diag_i = hypre_CSRMatrixI(L_diag);
if (num_nonzeros_offd)
{
L_offd_data = hypre_CSRMatrixData(L_offd);
L_offd_j = hypre_CSRMatrixJ(L_offd);
}
L_offd_i = hypre_CSRMatrixI(L_offd);
if (num_rows_L) D_data = hypre_CTAlloc(HYPRE_Real,num_rows_L);
if (send_data_L)
{
L_send_map_elmts = hypre_CTAlloc(HYPRE_Int, send_data_L);
buf_data = hypre_CTAlloc(HYPRE_Real,send_data_L);
}
if (num_cols_offd_L)
{
D_data_offd = hypre_CTAlloc(HYPRE_Real,num_cols_offd_L);
/*L_col_map_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd_L);*/
remap = hypre_CTAlloc(HYPRE_Int, num_cols_offd_L);
}
Rtilde = hypre_CTAlloc(hypre_ParVector, 1);
Rtilde_local = hypre_SeqVectorCreate(num_rows_L);
hypre_SeqVectorInitialize(Rtilde_local);
hypre_ParVectorLocalVector(Rtilde) = Rtilde_local;
hypre_ParVectorOwnsData(Rtilde) = 1;
Xtilde = hypre_CTAlloc(hypre_ParVector, 1);
Xtilde_local = hypre_SeqVectorCreate(num_rows_L);
hypre_SeqVectorInitialize(Xtilde_local);
hypre_ParVectorLocalVector(Xtilde) = Xtilde_local;
hypre_ParVectorOwnsData(Xtilde) = 1;
x_data = hypre_VectorData(hypre_ParVectorLocalVector(Xtilde));
r_data = hypre_VectorData(hypre_ParVectorLocalVector(Rtilde));
cnt = 0;
cnt_level = 0;
cnt_diag = 0;
cnt_offd = 0;
cnt_row = 1;
L_diag_i[0] = 0;
L_offd_i[0] = 0;
for (level=addlvl; level < num_levels; level++)
{
row_start = level_start[cnt_level];
if (level != 0)
{
tmp_data = hypre_VectorData(hypre_ParVectorLocalVector(F_array[level]));
if (tmp_data) hypre_TFree(tmp_data);
hypre_VectorData(hypre_ParVectorLocalVector(F_array[level])) = &r_data[row_start];
hypre_VectorOwnsData(hypre_ParVectorLocalVector(F_array[level])) = 0;
tmp_data = hypre_VectorData(hypre_ParVectorLocalVector(U_array[level]));
if (tmp_data) hypre_TFree(tmp_data);
hypre_VectorData(hypre_ParVectorLocalVector(U_array[level])) = &x_data[row_start];
hypre_VectorOwnsData(hypre_ParVectorLocalVector(U_array[level])) = 0;
}
cnt_level++;
start_diag = L_diag_i[cnt_row-1];
start_offd = L_offd_i[cnt_row-1];
A_tmp = A_array[level];
A_tmp_diag = hypre_ParCSRMatrixDiag(A_tmp);
A_tmp_offd = hypre_ParCSRMatrixOffd(A_tmp);
comm_pkg = hypre_ParCSRMatrixCommPkg(A_tmp);
A_tmp_diag_i = hypre_CSRMatrixI(A_tmp_diag);
A_tmp_offd_i = hypre_CSRMatrixI(A_tmp_offd);
A_tmp_diag_j = hypre_CSRMatrixJ(A_tmp_diag);
A_tmp_offd_j = hypre_CSRMatrixJ(A_tmp_offd);
A_tmp_diag_data = hypre_CSRMatrixData(A_tmp_diag);
A_tmp_offd_data = hypre_CSRMatrixData(A_tmp_offd);
num_rows_tmp = hypre_CSRMatrixNumRows(A_tmp_diag);
if (comm_pkg)
{
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg);
send_procs = hypre_ParCSRCommPkgSendProcs(comm_pkg);
recv_procs = hypre_ParCSRCommPkgRecvProcs(comm_pkg);
send_map_starts = hypre_ParCSRCommPkgSendMapStarts(comm_pkg);
send_map_elmts = hypre_ParCSRCommPkgSendMapElmts(comm_pkg);
recv_vec_starts = hypre_ParCSRCommPkgRecvVecStarts(comm_pkg);
}
else
{
num_sends = 0;
num_recvs = 0;
}
/* Compute new combined communication package */
for (i=0; i < num_sends; i++)
{
this_proc = hypre_BinarySearch(L_send_procs,send_procs[i],num_sends_L);
indx = L_send_ptr[this_proc];
for (j=send_map_starts[i]; j < send_map_starts[i+1]; j++)
{
L_send_map_elmts[indx++] = row_start + send_map_elmts[j];
}
L_send_ptr[this_proc] = indx;
}
cnt_map = 0;
for (i = 0; i < num_recvs; i++)
{
this_proc = hypre_BinarySearch(L_recv_procs,recv_procs[i],num_recvs_L);
indx = L_recv_ptr[this_proc];
for (j=recv_vec_starts[i]; j < recv_vec_starts[i+1]; j++)
{
remap[cnt_map++] = indx++;
}
L_recv_ptr[this_proc] = indx;
}
/* Compute Lambda */
if (relax_type == 0)
{
HYPRE_Real rlx_wt = relax_weight[level];
#ifdef HYPRE_USING_OPENMP
#pragma omp for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i=0; i < num_rows_tmp; i++)
{
D_data[i] = rlx_wt/A_tmp_diag_data[A_tmp_diag_i[i]];
L_diag_i[cnt_row+i] = start_diag + A_tmp_diag_i[i+1];
L_offd_i[cnt_row+i] = start_offd + A_tmp_offd_i[i+1];
}
}
else
{
l1_norms = l1_norms_ptr[level];
#ifdef HYPRE_USING_OPENMP
#pragma omp for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i=0; i < num_rows_tmp; i++)
{
D_data[i] = 1.0/l1_norms[i];
L_diag_i[cnt_row+i] = start_diag + A_tmp_diag_i[i+1];
L_offd_i[cnt_row+i] = start_offd + A_tmp_offd_i[i+1];
}
}
if (num_procs > 1)
{
index = 0;
for (i=0; i < num_sends; i++)
{
start = send_map_starts[i];
for (j=start; j < send_map_starts[i+1]; j++)
buf_data[index++] = D_data[send_map_elmts[j]];
}
comm_handle = hypre_ParCSRCommHandleCreate(1, comm_pkg,
buf_data, D_data_offd);
hypre_ParCSRCommHandleDestroy(comm_handle);
}
for (i = 0; i < num_rows_tmp; i++)
{
j_indx = A_tmp_diag_i[i];
L_diag_data[cnt_diag] = (2.0 - A_tmp_diag_data[j_indx]*D_data[i])*D_data[i];
L_diag_j[cnt_diag++] = i+row_start;
for (j=A_tmp_diag_i[i]+1; j < A_tmp_diag_i[i+1]; j++)
{
j_indx = A_tmp_diag_j[j];
L_diag_data[cnt_diag] = (- A_tmp_diag_data[j]*D_data[j_indx])*D_data[i];
L_diag_j[cnt_diag++] = j_indx+row_start;
}
for (j=A_tmp_offd_i[i]; j < A_tmp_offd_i[i+1]; j++)
{
j_indx = A_tmp_offd_j[j];
L_offd_data[cnt_offd] = (- A_tmp_offd_data[j]*D_data_offd[j_indx])*D_data[i];
L_offd_j[cnt_offd++] = remap[j_indx];
}
}
cnt_row += num_rows_tmp;
}
if (L_send_ptr)
{
for (i=num_sends_L-1; i > 0; i--)
L_send_ptr[i] = L_send_ptr[i-1];
L_send_ptr[0] = 0;
}
else
L_send_ptr = hypre_CTAlloc(HYPRE_Int,1);
if (L_recv_ptr)
{
for (i=num_recvs_L-1; i > 0; i--)
L_recv_ptr[i] = L_recv_ptr[i-1];
L_recv_ptr[0] = 0;
}
else
L_recv_ptr = hypre_CTAlloc(HYPRE_Int,1);
L_comm_pkg = hypre_CTAlloc(hypre_ParCSRCommPkg,1);
hypre_ParCSRCommPkgNumRecvs(L_comm_pkg) = num_recvs_L;
hypre_ParCSRCommPkgNumSends(L_comm_pkg) = num_sends_L;
hypre_ParCSRCommPkgRecvProcs(L_comm_pkg) = L_recv_procs;
hypre_ParCSRCommPkgSendProcs(L_comm_pkg) = L_send_procs;
hypre_ParCSRCommPkgRecvVecStarts(L_comm_pkg) = L_recv_ptr;
hypre_ParCSRCommPkgSendMapStarts(L_comm_pkg) = L_send_ptr;
hypre_ParCSRCommPkgSendMapElmts(L_comm_pkg) = L_send_map_elmts;
hypre_ParCSRCommPkgComm(L_comm_pkg) = comm;
Lambda = hypre_CTAlloc(hypre_ParCSRMatrix, 1);
hypre_ParCSRMatrixDiag(Lambda) = L_diag;
hypre_ParCSRMatrixOffd(Lambda) = L_offd;
hypre_ParCSRMatrixCommPkg(Lambda) = L_comm_pkg;
hypre_ParCSRMatrixComm(Lambda) = comm;
hypre_ParCSRMatrixOwnsData(Lambda) = 1;
hypre_ParAMGDataLambda(amg_data) = Lambda;
hypre_ParAMGDataRtilde(amg_data) = Rtilde;
hypre_ParAMGDataXtilde(amg_data) = Xtilde;
hypre_TFree(D_data_offd);
hypre_TFree(D_data);
if (num_procs > 1) hypre_TFree(buf_data);
hypre_TFree(remap);
hypre_TFree(buf_data);
hypre_TFree(level_start);
return Solve_err_flag;
}
