int
hypre_BoomerAMGIndepSetInit( hypre_ParCSRMatrix *S,
double *measure_array ,
int seq_rand)
{
hypre_CSRMatrix *S_diag = hypre_ParCSRMatrixDiag(S);
MPI_Comm comm = hypre_ParCSRMatrixComm(S);
int S_num_nodes = hypre_CSRMatrixNumRows(S_diag);
HYPRE_BigInt i;
int j, my_id;
int ierr = 0;
MPI_Comm_rank(comm,&my_id);
j = 2747+my_id;
if (seq_rand) j = 2747;
hypre_SeedRand(j);
if (seq_rand)
{
for (i = 0; i < hypre_ParCSRMatrixFirstRowIndex(S); i++)
hypre_Rand();
}
for (j = 0; j < S_num_nodes; j++)
{
measure_array[j] += hypre_Rand();
}
return (ierr);
}
/*
Assume that we are given a fine and coarse topology and the
coarse degrees of freedom (DOFs) have been chosen. Assume also,
that the global interpolation matrix dof_DOF has a prescribed
nonzero pattern. Then, the fine degrees of freedom can be split
into 4 groups (here "i" stands for "interior"):
NODEidof - dofs which are interpolated only from the DOF
in one coarse vertex
EDGEidof - dofs which are interpolated only from the DOFs
in one coarse edge
FACEidof - dofs which are interpolated only from the DOFs
in one coarse face
ELEMidof - dofs which are interpolated only from the DOFs
in one coarse element
The interpolation operator dof_DOF can be build in 4 steps, by
consequently filling-in the rows corresponding to the above groups.
The code below uses harmonic extension to extend the interpolation
from one group to the next.
*/
HYPRE_Int hypre_ND1AMGeInterpolation (hypre_ParCSRMatrix * Aee,
hypre_ParCSRMatrix * ELEM_idof,
hypre_ParCSRMatrix * FACE_idof,
hypre_ParCSRMatrix * EDGE_idof,
hypre_ParCSRMatrix * ELEM_FACE,
hypre_ParCSRMatrix * ELEM_EDGE,
HYPRE_Int num_OffProcRows,
hypre_MaxwellOffProcRow ** OffProcRows,
hypre_IJMatrix * IJ_dof_DOF)
{
HYPRE_Int ierr = 0;
HYPRE_Int i, j, k;
HYPRE_Int *offproc_rnums, *swap;
hypre_ParCSRMatrix * dof_DOF = hypre_IJMatrixObject(IJ_dof_DOF);
hypre_ParCSRMatrix * ELEM_DOF = ELEM_EDGE;
hypre_ParCSRMatrix * ELEM_FACEidof;
hypre_ParCSRMatrix * ELEM_EDGEidof;
hypre_CSRMatrix *A, *P;
HYPRE_Int numELEM = hypre_CSRMatrixNumRows(hypre_ParCSRMatrixDiag(ELEM_EDGE));
HYPRE_Int getrow_ierr;
HYPRE_Int three_dimensional_problem;
MPI_Comm comm= hypre_ParCSRMatrixComm(Aee);
HYPRE_Int myproc;
hypre_MPI_Comm_rank(comm, &myproc);
#if 0
hypre_IJMatrix * ij_dof_DOF = hypre_CTAlloc(hypre_IJMatrix, 1);
/* Convert dof_DOF to IJ matrix, so we can use AddToValues */
hypre_IJMatrixComm(ij_dof_DOF) = hypre_ParCSRMatrixComm(dof_DOF);
hypre_IJMatrixRowPartitioning(ij_dof_DOF) =
hypre_ParCSRMatrixRowStarts(dof_DOF);
hypre_IJMatrixColPartitioning(ij_dof_DOF) =
hypre_ParCSRMatrixColStarts(dof_DOF);
hypre_IJMatrixObject(ij_dof_DOF) = dof_DOF;
hypre_IJMatrixAssembleFlag(ij_dof_DOF) = 1;
#endif
/* sort the offproc rows to get quicker comparison for later */
if (num_OffProcRows)
{
offproc_rnums= hypre_TAlloc(HYPRE_Int, num_OffProcRows);
swap = hypre_TAlloc(HYPRE_Int, num_OffProcRows);
for (i= 0; i< num_OffProcRows; i++)
{
offproc_rnums[i]=(OffProcRows[i] -> row);
swap[i] = i;
}
}
if (num_OffProcRows > 1)
{
hypre_qsort2i(offproc_rnums, swap, 0, num_OffProcRows-1);
}
if (FACE_idof == EDGE_idof)
three_dimensional_problem = 0;
else
three_dimensional_problem = 1;
/* ELEM_FACEidof = ELEM_FACE x FACE_idof */
if (three_dimensional_problem)
ELEM_FACEidof = hypre_ParMatmul(ELEM_FACE, FACE_idof);
/* ELEM_EDGEidof = ELEM_EDGE x EDGE_idof */
ELEM_EDGEidof = hypre_ParMatmul(ELEM_EDGE, EDGE_idof);
/* Loop over local coarse elements */
k = hypre_ParCSRMatrixFirstRowIndex(ELEM_EDGE);
for (i = 0; i < numELEM; i++, k++)
{
HYPRE_Int size1, size2;
HYPRE_Int *col_ind0, *col_ind1, *col_ind2;
HYPRE_Int num_DOF, *DOF0, *DOF;
HYPRE_Int num_idof, *idof0, *idof;
HYPRE_Int num_bdof, *bdof;
double *boolean_data;
/* Determine the coarse DOFs */
hypre_ParCSRMatrixGetRow (ELEM_DOF, k, &num_DOF, &DOF0, &boolean_data);
DOF= hypre_TAlloc(HYPRE_Int, num_DOF);
for (j= 0; j< num_DOF; j++)
{
DOF[j]= DOF0[j];
}
hypre_ParCSRMatrixRestoreRow (ELEM_DOF, k, &num_DOF, &DOF0, &boolean_data);
qsort0(DOF,0,num_DOF-1);
/* Find the fine dofs interior for the current coarse element */
hypre_ParCSRMatrixGetRow (ELEM_idof, k, &num_idof, &idof0, &boolean_data);
idof= hypre_TAlloc(HYPRE_Int, num_idof);
for (j= 0; j< num_idof; j++)
{
idof[j]= idof0[j];
}
hypre_ParCSRMatrixRestoreRow (ELEM_idof, k, &num_idof, &idof0, &boolean_data);
/* Sort the interior dofs according to their global number */
qsort0(idof,0,num_idof-1);
/* Find the fine dofs on the boundary of the current coarse element */
if (three_dimensional_problem)
{
hypre_ParCSRMatrixGetRow (ELEM_FACEidof, k, &size1, &col_ind0, &boolean_data);
col_ind1= hypre_TAlloc(HYPRE_Int, size1);
for (j= 0; j< size1; j++)
{
col_ind1[j]= col_ind0[j];
}
hypre_ParCSRMatrixRestoreRow (ELEM_FACEidof, k, &size1, &col_ind0, &boolean_data);
}
else
size1 = 0;
hypre_ParCSRMatrixGetRow (ELEM_EDGEidof, k, &size2, &col_ind0, &boolean_data);
col_ind2= hypre_TAlloc(HYPRE_Int, size2);
for (j= 0; j< size2; j++)
{
col_ind2[j]= col_ind0[j];
}
hypre_ParCSRMatrixRestoreRow (ELEM_EDGEidof, k, &size2, &col_ind0, &boolean_data);
/* Merge and sort the boundary dofs according to their global number */
num_bdof = size1 + size2;
bdof = hypre_CTAlloc(HYPRE_Int, num_bdof);
if (three_dimensional_problem)
memcpy(bdof, col_ind1, size1*sizeof(HYPRE_Int));
memcpy(bdof+size1, col_ind2, size2*sizeof(HYPRE_Int));
qsort0(bdof,0,num_bdof-1);
/* A = extract_rows(Aee, idof) */
A = hypre_CSRMatrixCreate (num_idof, num_idof + num_bdof,
num_idof * (num_idof + num_bdof));
hypre_CSRMatrixInitialize(A);
{
HYPRE_Int *I = hypre_CSRMatrixI(A);
HYPRE_Int *J = hypre_CSRMatrixJ(A);
double *data = hypre_CSRMatrixData(A);
HYPRE_Int *tmp_J;
double *tmp_data;
I[0] = 0;
for (j = 0; j < num_idof; j++)
{
getrow_ierr= hypre_ParCSRMatrixGetRow (Aee, idof[j], &I[j+1], &tmp_J, &tmp_data);
if (getrow_ierr <0)
hypre_printf("getrow Aee off proc[%d] = \n",myproc);
memcpy(J, tmp_J, I[j+1]*sizeof(HYPRE_Int));
memcpy(data, tmp_data, I[j+1]*sizeof(double));
J+= I[j+1];
data+= I[j+1];
hypre_ParCSRMatrixRestoreRow (Aee, idof[j], &I[j+1], &tmp_J, &tmp_data);
I[j+1] += I[j];
}
}
/* P = extract_rows(dof_DOF, idof+bdof) */
P = hypre_CSRMatrixCreate (num_idof + num_bdof, num_DOF,
(num_idof + num_bdof) * num_DOF);
hypre_CSRMatrixInitialize(P);
{
HYPRE_Int *I = hypre_CSRMatrixI(P);
HYPRE_Int *J = hypre_CSRMatrixJ(P);
double *data = hypre_CSRMatrixData(P);
HYPRE_Int m;
HYPRE_Int *tmp_J;
double *tmp_data;
I[0] = 0;
for (j = 0; j < num_idof; j++)
{
getrow_ierr= hypre_ParCSRMatrixGetRow (dof_DOF, idof[j], &I[j+1], &tmp_J, &tmp_data);
if (getrow_ierr >= 0)
{
memcpy(J, tmp_J, I[j+1]*sizeof(HYPRE_Int));
memcpy(data, tmp_data, I[j+1]*sizeof(double));
J+= I[j+1];
data+= I[j+1];
hypre_ParCSRMatrixRestoreRow (dof_DOF, idof[j], &I[j+1], &tmp_J, &tmp_data);
I[j+1] += I[j];
}
else /* row offproc */
{
hypre_ParCSRMatrixRestoreRow (dof_DOF, idof[j], &I[j+1], &tmp_J, &tmp_data);
/* search for OffProcRows */
m= 0;
while (m < num_OffProcRows)
{
if (offproc_rnums[m] == idof[j])
{
break;
}
else
{
m++;
}
}
I[j+1]= (OffProcRows[swap[m]] -> ncols);
tmp_J = (OffProcRows[swap[m]] -> cols);
tmp_data= (OffProcRows[swap[m]] -> data);
memcpy(J, tmp_J, I[j+1]*sizeof(HYPRE_Int));
memcpy(data, tmp_data, I[j+1]*sizeof(double));
J+= I[j+1];
data+= I[j+1];
I[j+1] += I[j];
}
}
for ( ; j < num_idof + num_bdof; j++)
{
getrow_ierr= hypre_ParCSRMatrixGetRow (dof_DOF, bdof[j-num_idof], &I[j+1], &tmp_J, &tmp_data);
if (getrow_ierr >= 0)
{
memcpy(J, tmp_J, I[j+1]*sizeof(HYPRE_Int));
memcpy(data, tmp_data, I[j+1]*sizeof(double));
J+= I[j+1];
data+= I[j+1];
hypre_ParCSRMatrixRestoreRow (dof_DOF, bdof[j-num_idof], &I[j+1], &tmp_J, &tmp_data);
I[j+1] += I[j];
}
else /* row offproc */
{
hypre_ParCSRMatrixRestoreRow (dof_DOF, bdof[j-num_idof], &I[j+1], &tmp_J, &tmp_data);
/* search for OffProcRows */
m= 0;
while (m < num_OffProcRows)
{
if (offproc_rnums[m] == bdof[j-num_idof])
{
break;
}
else
{
m++;
}
}
if (m>= num_OffProcRows)hypre_printf("here the mistake\n");
I[j+1]= (OffProcRows[swap[m]] -> ncols);
tmp_J = (OffProcRows[swap[m]] -> cols);
tmp_data= (OffProcRows[swap[m]] -> data);
memcpy(J, tmp_J, I[j+1]*sizeof(HYPRE_Int));
memcpy(data, tmp_data, I[j+1]*sizeof(double));
J+= I[j+1];
data+= I[j+1];
I[j+1] += I[j];
}
}
}
/* Pi = Aii^{-1} Aib Pb */
hypre_HarmonicExtension (A, P, num_DOF, DOF,
num_idof, idof, num_bdof, bdof);
/* Insert Pi in dof_DOF */
{
HYPRE_Int * ncols = hypre_CTAlloc(HYPRE_Int, num_idof);
for (j = 0; j < num_idof; j++)
ncols[j] = num_DOF;
hypre_IJMatrixAddToValuesParCSR (IJ_dof_DOF,
num_idof, ncols, idof,
hypre_CSRMatrixJ(P),
hypre_CSRMatrixData(P));
hypre_TFree(ncols);
}
hypre_TFree(DOF);
hypre_TFree(idof);
if (three_dimensional_problem)
{
hypre_TFree(col_ind1);
}
hypre_TFree(col_ind2);
hypre_TFree(bdof);
hypre_CSRMatrixDestroy(A);
hypre_CSRMatrixDestroy(P);
}
#if 0
hypre_TFree(ij_dof_DOF);
#endif
if (three_dimensional_problem)
hypre_ParCSRMatrixDestroy(ELEM_FACEidof);
hypre_ParCSRMatrixDestroy(ELEM_EDGEidof);
if (num_OffProcRows)
{
hypre_TFree(offproc_rnums);
hypre_TFree(swap);
}
return ierr;
}
HYPRE_Int hypre_seqAMGSetup( hypre_ParAMGData *amg_data,
HYPRE_Int p_level,
HYPRE_Int coarse_threshold)
{
/* Par Data Structure variables */
hypre_ParCSRMatrix **Par_A_array = hypre_ParAMGDataAArray(amg_data);
MPI_Comm comm = hypre_ParCSRMatrixComm(Par_A_array[0]);
MPI_Comm new_comm, seq_comm;
hypre_ParCSRMatrix *A_seq = NULL;
hypre_CSRMatrix *A_seq_diag;
hypre_CSRMatrix *A_seq_offd;
hypre_ParVector *F_seq = NULL;
hypre_ParVector *U_seq = NULL;
hypre_ParCSRMatrix *A;
HYPRE_Int **dof_func_array;
HYPRE_Int num_procs, my_id;
HYPRE_Int not_finished_coarsening;
HYPRE_Int level;
HYPRE_Solver coarse_solver;
/* misc */
dof_func_array = hypre_ParAMGDataDofFuncArray(amg_data);
/*MPI Stuff */
hypre_MPI_Comm_size(comm, &num_procs);
hypre_MPI_Comm_rank(comm,&my_id);
/*initial */
level = p_level;
not_finished_coarsening = 1;
/* convert A at this level to sequential */
A = Par_A_array[level];
{
double *A_seq_data = NULL;
HYPRE_Int *A_seq_i = NULL;
HYPRE_Int *A_seq_offd_i = NULL;
HYPRE_Int *A_seq_j = NULL;
double *A_tmp_data = NULL;
HYPRE_Int *A_tmp_i = NULL;
HYPRE_Int *A_tmp_j = NULL;
HYPRE_Int *info, *displs, *displs2;
HYPRE_Int i, j, size, num_nonzeros, total_nnz, cnt;
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
HYPRE_Int *col_map_offd = hypre_ParCSRMatrixColMapOffd(A);
HYPRE_Int *A_diag_i = hypre_CSRMatrixI(A_diag);
HYPRE_Int *A_offd_i = hypre_CSRMatrixI(A_offd);
HYPRE_Int *A_diag_j = hypre_CSRMatrixJ(A_diag);
HYPRE_Int *A_offd_j = hypre_CSRMatrixJ(A_offd);
double *A_diag_data = hypre_CSRMatrixData(A_diag);
double *A_offd_data = hypre_CSRMatrixData(A_offd);
HYPRE_Int num_rows = hypre_CSRMatrixNumRows(A_diag);
HYPRE_Int first_row_index = hypre_ParCSRMatrixFirstRowIndex(A);
hypre_MPI_Group orig_group, new_group;
HYPRE_Int *ranks, new_num_procs, *row_starts;
info = hypre_CTAlloc(HYPRE_Int, num_procs);
hypre_MPI_Allgather(&num_rows, 1, HYPRE_MPI_INT, info, 1, HYPRE_MPI_INT, comm);
ranks = hypre_CTAlloc(HYPRE_Int, num_procs);
new_num_procs = 0;
for (i=0; i < num_procs; i++)
if (info[i])
{
ranks[new_num_procs] = i;
info[new_num_procs++] = info[i];
}
MPI_Comm_group(comm, &orig_group);
hypre_MPI_Group_incl(orig_group, new_num_procs, ranks, &new_group);
MPI_Comm_create(comm, new_group, &new_comm);
hypre_MPI_Group_free(&new_group);
hypre_MPI_Group_free(&orig_group);
if (num_rows)
{
/* alloc space in seq data structure only for participating procs*/
HYPRE_BoomerAMGCreate(&coarse_solver);
HYPRE_BoomerAMGSetMaxRowSum(coarse_solver,
hypre_ParAMGDataMaxRowSum(amg_data));
HYPRE_BoomerAMGSetStrongThreshold(coarse_solver,
hypre_ParAMGDataStrongThreshold(amg_data));
HYPRE_BoomerAMGSetCoarsenType(coarse_solver,
hypre_ParAMGDataCoarsenType(amg_data));
HYPRE_BoomerAMGSetInterpType(coarse_solver,
hypre_ParAMGDataInterpType(amg_data));
HYPRE_BoomerAMGSetTruncFactor(coarse_solver,
hypre_ParAMGDataTruncFactor(amg_data));
HYPRE_BoomerAMGSetPMaxElmts(coarse_solver,
hypre_ParAMGDataPMaxElmts(amg_data));
if (hypre_ParAMGDataUserRelaxType(amg_data) > -1)
HYPRE_BoomerAMGSetRelaxType(coarse_solver,
hypre_ParAMGDataUserRelaxType(amg_data));
HYPRE_BoomerAMGSetRelaxOrder(coarse_solver,
hypre_ParAMGDataRelaxOrder(amg_data));
HYPRE_BoomerAMGSetRelaxWt(coarse_solver,
hypre_ParAMGDataUserRelaxWeight(amg_data));
if (hypre_ParAMGDataUserNumSweeps(amg_data) > -1)
HYPRE_BoomerAMGSetNumSweeps(coarse_solver,
hypre_ParAMGDataUserNumSweeps(amg_data));
HYPRE_BoomerAMGSetNumFunctions(coarse_solver,
hypre_ParAMGDataNumFunctions(amg_data));
HYPRE_BoomerAMGSetMaxIter(coarse_solver, 1);
HYPRE_BoomerAMGSetTol(coarse_solver, 0);
/* Create CSR Matrix, will be Diag part of new matrix */
A_tmp_i = hypre_CTAlloc(HYPRE_Int, num_rows+1);
A_tmp_i[0] = 0;
for (i=1; i < num_rows+1; i++)
A_tmp_i[i] = A_diag_i[i]-A_diag_i[i-1]+A_offd_i[i]-A_offd_i[i-1];
num_nonzeros = A_offd_i[num_rows]+A_diag_i[num_rows];
A_tmp_j = hypre_CTAlloc(HYPRE_Int, num_nonzeros);
A_tmp_data = hypre_CTAlloc(double, num_nonzeros);
cnt = 0;
for (i=0; i < num_rows; i++)
{
for (j=A_diag_i[i]; j < A_diag_i[i+1]; j++)
{
A_tmp_j[cnt] = A_diag_j[j]+first_row_index;
A_tmp_data[cnt++] = A_diag_data[j];
}
for (j=A_offd_i[i]; j < A_offd_i[i+1]; j++)
{
A_tmp_j[cnt] = col_map_offd[A_offd_j[j]];
A_tmp_data[cnt++] = A_offd_data[j];
}
}
displs = hypre_CTAlloc(HYPRE_Int, new_num_procs+1);
displs[0] = 0;
for (i=1; i < new_num_procs+1; i++)
displs[i] = displs[i-1]+info[i-1];
size = displs[new_num_procs];
A_seq_i = hypre_CTAlloc(HYPRE_Int, size+1);
A_seq_offd_i = hypre_CTAlloc(HYPRE_Int, size+1);
hypre_MPI_Allgatherv ( &A_tmp_i[1], num_rows, HYPRE_MPI_INT, &A_seq_i[1], info,
displs, HYPRE_MPI_INT, new_comm );
displs2 = hypre_CTAlloc(HYPRE_Int, new_num_procs+1);
A_seq_i[0] = 0;
displs2[0] = 0;
for (j=1; j < displs[1]; j++)
A_seq_i[j] = A_seq_i[j]+A_seq_i[j-1];
for (i=1; i < new_num_procs; i++)
{
for (j=displs[i]; j < displs[i+1]; j++)
{
A_seq_i[j] = A_seq_i[j]+A_seq_i[j-1];
}
}
A_seq_i[size] = A_seq_i[size]+A_seq_i[size-1];
displs2[new_num_procs] = A_seq_i[size];
for (i=1; i < new_num_procs+1; i++)
{
displs2[i] = A_seq_i[displs[i]];
info[i-1] = displs2[i] - displs2[i-1];
}
total_nnz = displs2[new_num_procs];
A_seq_j = hypre_CTAlloc(HYPRE_Int, total_nnz);
A_seq_data = hypre_CTAlloc(double, total_nnz);
hypre_MPI_Allgatherv ( A_tmp_j, num_nonzeros, HYPRE_MPI_INT,
A_seq_j, info, displs2,
HYPRE_MPI_INT, new_comm );
hypre_MPI_Allgatherv ( A_tmp_data, num_nonzeros, hypre_MPI_DOUBLE,
A_seq_data, info, displs2,
hypre_MPI_DOUBLE, new_comm );
hypre_TFree(displs);
hypre_TFree(displs2);
hypre_TFree(A_tmp_i);
hypre_TFree(A_tmp_j);
hypre_TFree(A_tmp_data);
row_starts = hypre_CTAlloc(HYPRE_Int,2);
row_starts[0] = 0;
row_starts[1] = size;
/* Create 1 proc communicator */
seq_comm = hypre_MPI_COMM_SELF;
A_seq = hypre_ParCSRMatrixCreate(seq_comm,size,size,
row_starts, row_starts,
0,total_nnz,0);
A_seq_diag = hypre_ParCSRMatrixDiag(A_seq);
A_seq_offd = hypre_ParCSRMatrixOffd(A_seq);
hypre_CSRMatrixData(A_seq_diag) = A_seq_data;
hypre_CSRMatrixI(A_seq_diag) = A_seq_i;
hypre_CSRMatrixJ(A_seq_diag) = A_seq_j;
hypre_CSRMatrixI(A_seq_offd) = A_seq_offd_i;
F_seq = hypre_ParVectorCreate(seq_comm, size, row_starts);
U_seq = hypre_ParVectorCreate(seq_comm, size, row_starts);
hypre_ParVectorOwnsPartitioning(F_seq) = 0;
hypre_ParVectorOwnsPartitioning(U_seq) = 0;
hypre_ParVectorInitialize(F_seq);
hypre_ParVectorInitialize(U_seq);
hypre_BoomerAMGSetup(coarse_solver,A_seq,F_seq,U_seq);
hypre_ParAMGDataCoarseSolver(amg_data) = coarse_solver;
hypre_ParAMGDataACoarse(amg_data) = A_seq;
hypre_ParAMGDataFCoarse(amg_data) = F_seq;
hypre_ParAMGDataUCoarse(amg_data) = U_seq;
hypre_ParAMGDataNewComm(amg_data) = new_comm;
}
hypre_TFree(info);
hypre_TFree(ranks);
}
return 0;
}
HYPRE_Int hypre_BlockTridiagSetup(void *data, hypre_ParCSRMatrix *A,
hypre_ParVector *b, hypre_ParVector *x)
{
HYPRE_Int i, j, *index_set1, print_level, nsweeps, relax_type;
HYPRE_Int nrows, nrows1, nrows2, start1, start2, *index_set2;
HYPRE_Int count, ierr;
double threshold;
hypre_ParCSRMatrix **submatrices;
HYPRE_Solver precon1;
HYPRE_Solver precon2;
HYPRE_IJVector ij_u1, ij_u2, ij_f1, ij_f2;
hypre_ParVector *vector;
MPI_Comm comm;
hypre_BlockTridiagData *b_data = (hypre_BlockTridiagData *) data;
HYPRE_ParCSRMatrixGetComm((HYPRE_ParCSRMatrix) A, &comm);
index_set1 = b_data->index_set1;
nrows1 = index_set1[0];
nrows = hypre_ParCSRMatrixNumRows(A);
nrows2 = nrows - nrows1;
b_data->index_set2 = hypre_CTAlloc(HYPRE_Int, nrows2+1);
index_set2 = b_data->index_set2;
index_set2[0] = nrows2;
count = 1;
for (i = 0; i < index_set1[1]; i++) index_set2[count++] = i;
for (i = 1; i < nrows1; i++)
for (j = index_set1[i]+1; j < index_set1[i+1]; j++)
index_set2[count++] = j;
for (i = index_set1[nrows1]+1; i < nrows; i++) index_set2[count++] = i;
submatrices = hypre_CTAlloc(hypre_ParCSRMatrix *, 4);
hypre_ParCSRMatrixExtractSubmatrices(A, index_set1, &submatrices);
nrows1 = hypre_ParCSRMatrixNumRows(submatrices[0]);
nrows2 = hypre_ParCSRMatrixNumRows(submatrices[3]);
start1 = hypre_ParCSRMatrixFirstRowIndex(submatrices[0]);
start2 = hypre_ParCSRMatrixFirstRowIndex(submatrices[3]);
HYPRE_IJVectorCreate(comm, start1, start1+nrows1-1, &ij_u1);
HYPRE_IJVectorSetObjectType(ij_u1, HYPRE_PARCSR);
ierr = HYPRE_IJVectorInitialize(ij_u1);
ierr += HYPRE_IJVectorAssemble(ij_u1);
hypre_assert(!ierr);
HYPRE_IJVectorCreate(comm, start1, start1+nrows1-1, &ij_f1);
HYPRE_IJVectorSetObjectType(ij_f1, HYPRE_PARCSR);
ierr = HYPRE_IJVectorInitialize(ij_f1);
ierr += HYPRE_IJVectorAssemble(ij_f1);
hypre_assert(!ierr);
HYPRE_IJVectorCreate(comm, start2, start2+nrows2-1, &ij_u2);
HYPRE_IJVectorSetObjectType(ij_u2, HYPRE_PARCSR);
ierr = HYPRE_IJVectorInitialize(ij_u2);
ierr += HYPRE_IJVectorAssemble(ij_u2);
hypre_assert(!ierr);
HYPRE_IJVectorCreate(comm, start2, start2+nrows1-1, &ij_f2);
HYPRE_IJVectorSetObjectType(ij_f2, HYPRE_PARCSR);
ierr = HYPRE_IJVectorInitialize(ij_f2);
ierr += HYPRE_IJVectorAssemble(ij_f2);
hypre_assert(!ierr);
HYPRE_IJVectorGetObject(ij_f1, (void **) &vector);
b_data->F1 = vector;
HYPRE_IJVectorGetObject(ij_u1, (void **) &vector);
b_data->U1 = vector;
HYPRE_IJVectorGetObject(ij_f2, (void **) &vector);
b_data->F2 = vector;
HYPRE_IJVectorGetObject(ij_u2, (void **) &vector);
b_data->U2 = vector;
print_level = b_data->print_level;
threshold = b_data->threshold;
nsweeps = b_data->num_sweeps;
relax_type = b_data->relax_type;
threshold = b_data->threshold;
HYPRE_BoomerAMGCreate(&precon1);
HYPRE_BoomerAMGSetMaxIter(precon1, 1);
HYPRE_BoomerAMGSetCycleType(precon1, 1);
HYPRE_BoomerAMGSetPrintLevel(precon1, print_level);
HYPRE_BoomerAMGSetMaxLevels(precon1, 25);
HYPRE_BoomerAMGSetMeasureType(precon1, 0);
HYPRE_BoomerAMGSetCoarsenType(precon1, 0);
HYPRE_BoomerAMGSetStrongThreshold(precon1, threshold);
HYPRE_BoomerAMGSetNumFunctions(precon1, 1);
HYPRE_BoomerAMGSetNumSweeps(precon1, nsweeps);
HYPRE_BoomerAMGSetRelaxType(precon1, relax_type);
hypre_BoomerAMGSetup(precon1, submatrices[0], b_data->U1, b_data->F1);
HYPRE_BoomerAMGCreate(&precon2);
HYPRE_BoomerAMGSetMaxIter(precon2, 1);
HYPRE_BoomerAMGSetCycleType(precon2, 1);
HYPRE_BoomerAMGSetPrintLevel(precon2, print_level);
HYPRE_BoomerAMGSetMaxLevels(precon2, 25);
HYPRE_BoomerAMGSetMeasureType(precon2, 0);
HYPRE_BoomerAMGSetCoarsenType(precon2, 0);
HYPRE_BoomerAMGSetMeasureType(precon2, 1);
HYPRE_BoomerAMGSetStrongThreshold(precon2, threshold);
HYPRE_BoomerAMGSetNumFunctions(precon2, 1);
HYPRE_BoomerAMGSetNumSweeps(precon2, nsweeps);
HYPRE_BoomerAMGSetRelaxType(precon2, relax_type);
hypre_BoomerAMGSetup(precon2, submatrices[3], NULL, NULL);
b_data->precon1 = precon1;
b_data->precon2 = precon2;
b_data->A11 = submatrices[0];
hypre_ParCSRMatrixDestroy(submatrices[1]);
b_data->A21 = submatrices[2];
b_data->A22 = submatrices[3];
hypre_TFree(submatrices);
return (0);
}
/*--------------------------------------------------------------------------
* hypre_SStructSharedDOF_ParcsrMatRowsComm
* Given a sstruct_grid & parcsr matrix with rows corresponding to the
* sstruct_grid, determine and extract the rows that must be communicated.
* These rows are for shared dof that geometrically lie on processor
* boundaries but internally are stored on one processor.
* Algo:
* for each cellbox
* RECVs:
* i) stretch the cellbox to the variable box
* ii) in the appropriate (dof-dependent) direction, take the
* boundary and boxman_intersect to extract boxmanentries
* that contain these boundary edges.
* iii)loop over the boxmanentries and see if they belong
* on this proc or another proc
* a) if belong on another proc, these are the recvs:
* count and prepare the communication buffers and
* values.
*
* SENDs:
* i) form layer of cells that is one layer off cellbox
* (stretches in the appropriate direction)
* ii) boxman_intersect with the cellgrid boxman
* iii)loop over the boxmanentries and see if they belong
* on this proc or another proc
* a) if belong on another proc, these are the sends:
* count and prepare the communication buffers and
* values.
*
* Note: For the recv data, the dof can come from only one processor.
* For the send data, the dof can go to more than one processor
* (the same dof is on the boundary of several cells).
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_SStructSharedDOF_ParcsrMatRowsComm( hypre_SStructGrid *grid,
hypre_ParCSRMatrix *A,
HYPRE_Int *num_offprocrows_ptr,
hypre_MaxwellOffProcRow ***OffProcRows_ptr)
{
MPI_Comm A_comm= hypre_ParCSRMatrixComm(A);
MPI_Comm grid_comm= hypre_SStructGridComm(grid);
HYPRE_Int matrix_type= HYPRE_PARCSR;
HYPRE_Int nparts= hypre_SStructGridNParts(grid);
HYPRE_Int ndim = hypre_SStructGridNDim(grid);
hypre_SStructGrid *cell_ssgrid;
hypre_SStructPGrid *pgrid;
hypre_StructGrid *cellgrid;
hypre_BoxArray *cellboxes;
hypre_Box *box, *cellbox, vbox, boxman_entry_box;
hypre_Index loop_size, start;
HYPRE_Int loopi, loopj, loopk;
HYPRE_Int start_rank, end_rank, rank;
HYPRE_Int i, j, k, m, n, t, part, var, nvars;
HYPRE_SStructVariable *vartypes;
HYPRE_Int nbdry_slabs;
hypre_BoxArray *recv_slabs, *send_slabs;
hypre_Index varoffset;
hypre_BoxManager **boxmans, *cell_boxman;
hypre_BoxManEntry **boxman_entries, *entry;
HYPRE_Int nboxman_entries;
hypre_Index ishift, jshift, kshift, zero_index;
hypre_Index ilower, iupper, index;
HYPRE_Int proc, nprocs, myproc;
HYPRE_Int *SendToProcs, *RecvFromProcs;
HYPRE_Int **send_RowsNcols; /* buffer for rows & ncols */
HYPRE_Int *send_RowsNcols_alloc;
HYPRE_Int *send_ColsData_alloc;
HYPRE_Int *tot_nsendRowsNcols, *tot_sendColsData;
double **vals; /* buffer for cols & data */
HYPRE_Int *col_inds;
double *values;
hypre_MPI_Request *requests;
hypre_MPI_Status *status;
HYPRE_Int **rbuffer_RowsNcols;
double **rbuffer_ColsData;
HYPRE_Int num_sends, num_recvs;
hypre_MaxwellOffProcRow **OffProcRows;
HYPRE_Int *starts;
HYPRE_Int ierr= 0;
hypre_MPI_Comm_rank(A_comm, &myproc);
hypre_MPI_Comm_size(grid_comm, &nprocs);
start_rank= hypre_ParCSRMatrixFirstRowIndex(A);
end_rank = hypre_ParCSRMatrixLastRowIndex(A);
hypre_SetIndex(ishift, 1, 0, 0);
hypre_SetIndex(jshift, 0, 1, 0);
hypre_SetIndex(kshift, 0, 0, 1);
hypre_SetIndex(zero_index, 0, 0, 0);
/* need a cellgrid boxman to determine the send boxes -> only the cell dofs
are unique so a boxman intersect can be used to get the edges that
must be sent. */
HYPRE_SStructGridCreate(grid_comm, ndim, nparts, &cell_ssgrid);
vartypes= hypre_CTAlloc(HYPRE_SStructVariable, 1);
vartypes[0]= HYPRE_SSTRUCT_VARIABLE_CELL;
for (i= 0; i< nparts; i++)
{
pgrid= hypre_SStructGridPGrid(grid, i);
cellgrid= hypre_SStructPGridCellSGrid(pgrid);
cellboxes= hypre_StructGridBoxes(cellgrid);
hypre_ForBoxI(j, cellboxes)
{
box= hypre_BoxArrayBox(cellboxes, j);
HYPRE_SStructGridSetExtents(cell_ssgrid, i,
hypre_BoxIMin(box), hypre_BoxIMax(box));
}
HYPRE_SStructGridSetVariables(cell_ssgrid, i, 1, vartypes);
}
hypre_CSRMatrix *
hypre_ParCSRMatrixExtractAExt( hypre_ParCSRMatrix *A,
HYPRE_Int data,
HYPRE_Int ** pA_ext_row_map )
{
/* Note that A's role as the first factor in A*A^T is used only
through ...CommPkgT(A), which basically says which rows of A
(columns of A^T) are needed. In all the other places where A
serves as an input, it is through its role as A^T, the matrix
whose data needs to be passed between processors. */
MPI_Comm comm = hypre_ParCSRMatrixComm(A);
HYPRE_Int first_col_diag = hypre_ParCSRMatrixFirstColDiag(A);
HYPRE_Int first_row_index = hypre_ParCSRMatrixFirstRowIndex(A);
HYPRE_Int *col_map_offd = hypre_ParCSRMatrixColMapOffd(A);
hypre_ParCSRCommPkg *comm_pkg = hypre_ParCSRMatrixCommPkgT(A);
/* ... CommPkgT(A) should identify all rows of A^T needed for A*A^T (that is
* generally a bigger set than ...CommPkg(A), the rows of B needed for A*B) */
HYPRE_Int num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg);
HYPRE_Int *recv_vec_starts = hypre_ParCSRCommPkgRecvVecStarts(comm_pkg);
HYPRE_Int num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
HYPRE_Int *send_map_starts = hypre_ParCSRCommPkgSendMapStarts(comm_pkg);
HYPRE_Int *send_map_elmts = hypre_ParCSRCommPkgSendMapElmts(comm_pkg);
hypre_CSRMatrix *diag = hypre_ParCSRMatrixDiag(A);
HYPRE_Int *diag_i = hypre_CSRMatrixI(diag);
HYPRE_Int *diag_j = hypre_CSRMatrixJ(diag);
HYPRE_Complex *diag_data = hypre_CSRMatrixData(diag);
hypre_CSRMatrix *offd = hypre_ParCSRMatrixOffd(A);
HYPRE_Int *offd_i = hypre_CSRMatrixI(offd);
HYPRE_Int *offd_j = hypre_CSRMatrixJ(offd);
HYPRE_Complex *offd_data = hypre_CSRMatrixData(offd);
HYPRE_Int num_cols_A, num_nonzeros;
HYPRE_Int num_rows_A_ext;
hypre_CSRMatrix *A_ext;
HYPRE_Int *A_ext_i;
HYPRE_Int *A_ext_j;
HYPRE_Complex *A_ext_data;
num_cols_A = hypre_ParCSRMatrixGlobalNumCols(A);
num_rows_A_ext = recv_vec_starts[num_recvs];
hypre_ParCSRMatrixExtractBExt_Arrays
( &A_ext_i, &A_ext_j, &A_ext_data, pA_ext_row_map,
&num_nonzeros,
data, 1, comm, comm_pkg,
num_cols_A, num_recvs, num_sends,
first_col_diag, first_row_index,
recv_vec_starts, send_map_starts, send_map_elmts,
diag_i, diag_j, offd_i, offd_j, col_map_offd,
diag_data, offd_data
);
A_ext = hypre_CSRMatrixCreate(num_rows_A_ext,num_cols_A,num_nonzeros);
hypre_CSRMatrixI(A_ext) = A_ext_i;
hypre_CSRMatrixJ(A_ext) = A_ext_j;
if (data) hypre_CSRMatrixData(A_ext) = A_ext_data;
return A_ext;
}
hypre_ParCSRMatrix *hypre_ParCSRAAt( hypre_ParCSRMatrix *A )
{
MPI_Comm comm = hypre_ParCSRMatrixComm(A);
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
HYPRE_Complex *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);
HYPRE_Complex *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 *A_col_map_offd = hypre_ParCSRMatrixColMapOffd(A);
HYPRE_Int *A_ext_row_map;
HYPRE_Int *row_starts_A = hypre_ParCSRMatrixRowStarts(A);
HYPRE_Int num_rows_diag_A = hypre_CSRMatrixNumRows(A_diag);
HYPRE_Int num_cols_offd_A = hypre_CSRMatrixNumCols(A_offd);
hypre_ParCSRMatrix *C;
HYPRE_Int *col_map_offd_C;
hypre_CSRMatrix *C_diag;
HYPRE_Complex *C_diag_data;
HYPRE_Int *C_diag_i;
HYPRE_Int *C_diag_j;
hypre_CSRMatrix *C_offd;
HYPRE_Complex *C_offd_data=NULL;
HYPRE_Int *C_offd_i=NULL;
HYPRE_Int *C_offd_j=NULL;
HYPRE_Int *new_C_offd_j;
HYPRE_Int C_diag_size;
HYPRE_Int C_offd_size;
HYPRE_Int last_col_diag_C;
HYPRE_Int num_cols_offd_C;
hypre_CSRMatrix *A_ext;
HYPRE_Complex *A_ext_data;
HYPRE_Int *A_ext_i;
HYPRE_Int *A_ext_j;
HYPRE_Int num_rows_A_ext=0;
HYPRE_Int first_row_index_A = hypre_ParCSRMatrixFirstRowIndex(A);
HYPRE_Int first_col_diag_A = hypre_ParCSRMatrixFirstColDiag(A);
HYPRE_Int *B_marker;
HYPRE_Int i;
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 count;
HYPRE_Int n_rows_A, n_cols_A;
HYPRE_Complex a_entry;
HYPRE_Complex a_b_product;
HYPRE_Complex zero = 0.0;
n_rows_A = hypre_ParCSRMatrixGlobalNumRows(A);
n_cols_A = hypre_ParCSRMatrixGlobalNumCols(A);
if (n_cols_A != n_rows_A)
{
hypre_printf(" Error! Incompatible matrix dimensions!\n");
return NULL;
}
/*-----------------------------------------------------------------------
* Extract A_ext, i.e. portion of A that is stored on neighbor procs
* and needed locally for A^T in the matrix matrix product A*A^T
*-----------------------------------------------------------------------*/
if (num_rows_diag_A != n_rows_A)
{
/*---------------------------------------------------------------------
* If there exists no CommPkg for A, a CommPkg is generated using
* equally load balanced partitionings
*--------------------------------------------------------------------*/
if (!hypre_ParCSRMatrixCommPkg(A))
{
hypre_MatTCommPkgCreate(A);
}
A_ext = hypre_ParCSRMatrixExtractAExt( A, 1, &A_ext_row_map );
A_ext_data = hypre_CSRMatrixData(A_ext);
A_ext_i = hypre_CSRMatrixI(A_ext);
A_ext_j = hypre_CSRMatrixJ(A_ext);
num_rows_A_ext = hypre_CSRMatrixNumRows(A_ext);
}
/*-----------------------------------------------------------------------
* Allocate marker array.
*-----------------------------------------------------------------------*/
B_marker = hypre_CTAlloc(HYPRE_Int, num_rows_diag_A+num_rows_A_ext );
/*-----------------------------------------------------------------------
* Initialize some stuff.
*-----------------------------------------------------------------------*/
for ( i1=0; i1<num_rows_diag_A+num_rows_A_ext; ++i1 )
{
B_marker[i1] = -1;
}
hypre_ParAat_RowSizes(
&C_diag_i, &C_offd_i, B_marker,
A_diag_i, A_diag_j,
A_offd_i, A_offd_j, A_col_map_offd,
A_ext_i, A_ext_j, A_ext_row_map,
&C_diag_size, &C_offd_size,
num_rows_diag_A, num_cols_offd_A,
num_rows_A_ext,
first_col_diag_A, first_row_index_A
);
#if 0
/* debugging output: */
hypre_printf("A_ext_row_map (%i):",num_rows_A_ext);
for ( i1=0; i1<num_rows_A_ext; ++i1 ) hypre_printf(" %i",A_ext_row_map[i1] );
hypre_printf("\nC_diag_i (%i):",C_diag_size);
for ( i1=0; i1<=num_rows_diag_A; ++i1 ) hypre_printf(" %i",C_diag_i[i1] );
hypre_printf("\nC_offd_i (%i):",C_offd_size);
for ( i1=0; i1<=num_rows_diag_A; ++i1 ) hypre_printf(" %i",C_offd_i[i1] );
hypre_printf("\n");
#endif
/*-----------------------------------------------------------------------
* Allocate C_diag_data and C_diag_j arrays.
* Allocate C_offd_data and C_offd_j arrays.
*-----------------------------------------------------------------------*/
last_col_diag_C = first_row_index_A + num_rows_diag_A - 1;
C_diag_data = hypre_CTAlloc(HYPRE_Complex, C_diag_size);
C_diag_j = hypre_CTAlloc(HYPRE_Int, C_diag_size);
if (C_offd_size)
{
C_offd_data = hypre_CTAlloc(HYPRE_Complex, 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_rows_diag_A+num_rows_A_ext; ++i1 )
{
B_marker[i1] = -1;
}
/*-----------------------------------------------------------------------
* Loop over interior c-points.
*-----------------------------------------------------------------------*/
for (i1 = 0; i1 < num_rows_diag_A; i1++)
{
/*--------------------------------------------------------------------
* Create diagonal entry, C_{i1,i1}
*--------------------------------------------------------------------*/
B_marker[i1] = jj_count_diag;
jj_row_begin_diag = jj_count_diag;
jj_row_begin_offd = jj_count_offd;
C_diag_data[jj_count_diag] = zero;
C_diag_j[jj_count_diag] = i1;
jj_count_diag++;
/*-----------------------------------------------------------------
* Loop over entries in row i1 of A_offd.
*-----------------------------------------------------------------*/
/* There are 3 CSRMatrix or CSRBooleanMatrix objects here:
ext*ext, ext*diag, and ext*offd belong to another processor.
diag*offd and offd*diag don't count - never share a column by definition.
So we have to do 4 cases:
diag*ext, offd*ext, diag*diag, and offd*offd.
*/
for (jj2 = A_diag_i[i1]; jj2 < A_diag_i[i1+1]; jj2++)
{
i2 = A_diag_j[jj2];
a_entry = A_diag_data[jj2];
/* diag*ext */
/*-----------------------------------------------------------
* Loop over entries (columns) i3 in row i2 of (A_ext)^T
* That is, rows i3 having a column i2 of A_ext.
* For now, for each row i3 of A_ext we crudely check _all_
* columns to see whether one matches i2.
* For each entry (i2,i3) of (A_ext)^T, add A(i1,i2)*A(i3,i2)
* to C(i1,i3) . This contributes to both the diag and offd
* blocks of C.
*-----------------------------------------------------------*/
for ( i3=0; i3<num_rows_A_ext; i3++ ) {
for ( jj3=A_ext_i[i3]; jj3<A_ext_i[i3+1]; jj3++ ) {
if ( A_ext_j[jj3]==i2+first_col_diag_A ) {
/* row i3, column i2 of A_ext; or,
row i2, column i3 of (A_ext)^T */
a_b_product = a_entry * A_ext_data[jj3];
/*--------------------------------------------------------
* Check B_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 ( A_ext_row_map[i3] < first_row_index_A ||
A_ext_row_map[i3] > last_col_diag_C ) { /* offd */
if (B_marker[i3+num_rows_diag_A] < jj_row_begin_offd) {
B_marker[i3+num_rows_diag_A] = jj_count_offd;
C_offd_data[jj_count_offd] = a_b_product;
C_offd_j[jj_count_offd] = i3;
jj_count_offd++;
}
else
C_offd_data[B_marker[i3+num_rows_diag_A]] += a_b_product;
}
else { /* diag */
if (B_marker[i3+num_rows_diag_A] < jj_row_begin_diag) {
B_marker[i3+num_rows_diag_A] = jj_count_diag;
C_diag_data[jj_count_diag] = a_b_product;
C_diag_j[jj_count_diag] = i3-first_col_diag_A;
jj_count_diag++;
}
else
C_diag_data[B_marker[i3+num_rows_diag_A]] += a_b_product;
}
}
}
}
}
if (num_cols_offd_A)
{
for (jj2 = A_offd_i[i1]; jj2 < A_offd_i[i1+1]; jj2++)
{
i2 = A_offd_j[jj2];
a_entry = A_offd_data[jj2];
/* offd * ext */
/*-----------------------------------------------------------
* Loop over entries (columns) i3 in row i2 of (A_ext)^T
* That is, rows i3 having a column i2 of A_ext.
* For now, for each row i3 of A_ext we crudely check _all_
* columns to see whether one matches i2.
* For each entry (i2,i3) of (A_ext)^T, add A(i1,i2)*A(i3,i2)
* to C(i1,i3) . This contributes to both the diag and offd
* blocks of C.
*-----------------------------------------------------------*/
for ( i3=0; i3<num_rows_A_ext; i3++ ) {
for ( jj3=A_ext_i[i3]; jj3<A_ext_i[i3+1]; jj3++ ) {
if ( A_ext_j[jj3]==A_col_map_offd[i2] ) {
/* row i3, column i2 of A_ext; or,
row i2, column i3 of (A_ext)^T */
a_b_product = a_entry * A_ext_data[jj3];
/*--------------------------------------------------------
* Check B_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 ( A_ext_row_map[i3] < first_row_index_A ||
A_ext_row_map[i3] > last_col_diag_C ) { /* offd */
if (B_marker[i3+num_rows_diag_A] < jj_row_begin_offd) {
B_marker[i3+num_rows_diag_A] = jj_count_offd;
C_offd_data[jj_count_offd] = a_b_product;
C_offd_j[jj_count_offd] = i3;
jj_count_offd++;
}
else
C_offd_data[B_marker[i3+num_rows_diag_A]] += a_b_product;
}
else { /* diag */
if (B_marker[i3+num_rows_diag_A] < jj_row_begin_diag) {
B_marker[i3+num_rows_diag_A] = jj_count_diag;
C_diag_data[jj_count_diag] = a_b_product;
C_diag_j[jj_count_diag] = i3-first_row_index_A;
jj_count_diag++;
}
else
C_diag_data[B_marker[i3+num_rows_diag_A]] += a_b_product;
}
}
}
}
}
}
/* diag * diag */
/*-----------------------------------------------------------------
* Loop over entries (columns) i2 in row i1 of A_diag.
* For each such column we will find the contributions of the
* corresponding rows i2 of A^T to C=A*A^T . Now we only look
* at the local part of A^T - with columns (rows of A) living
* on this processor.
*-----------------------------------------------------------------*/
for (jj2 = A_diag_i[i1]; jj2 < A_diag_i[i1+1]; jj2++)
{
i2 = A_diag_j[jj2];
a_entry = A_diag_data[jj2];
/*-----------------------------------------------------------
* Loop over entries (columns) i3 in row i2 of A^T
* That is, rows i3 having a column i2 of A (local part).
* For now, for each row i3 of A we crudely check _all_
* columns to see whether one matches i2.
* This i3-loop is for the diagonal block of A.
* It contributes to the diagonal block of C.
* For each entry (i2,i3) of A^T, add A(i1,i2)*A(i3,i2)
* to C(i1,i3)
*-----------------------------------------------------------*/
for ( i3=0; i3<num_rows_diag_A; i3++ ) {
for ( jj3=A_diag_i[i3]; jj3<A_diag_i[i3+1]; jj3++ ) {
if ( A_diag_j[jj3]==i2 ) {
/* row i3, column i2 of A; or,
row i2, column i3 of A^T */
a_b_product = a_entry * A_diag_data[jj3];
/*--------------------------------------------------------
* Check B_marker to see that C_{i1,i3} has not already
* been accounted for. If it has not, mark it and increment
* counter.
*--------------------------------------------------------*/
if (B_marker[i3] < jj_row_begin_diag)
{
B_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[B_marker[i3]] += a_b_product;
}
}
}
} /* end of i3 loop */
} /* end of third i2 loop */
/* offd * offd */
/*-----------------------------------------------------------
* Loop over offd columns i2 of A in A*A^T. Then
* loop over offd entries (columns) i3 in row i2 of A^T
* That is, rows i3 having a column i2 of A (local part).
* For now, for each row i3 of A we crudely check _all_
* columns to see whether one matches i2.
* This i3-loop is for the off-diagonal block of A.
* It contributes to the diag block of C.
* For each entry (i2,i3) of A^T, add A*A^T to C
*-----------------------------------------------------------*/
if (num_cols_offd_A) {
for (jj2 = A_offd_i[i1]; jj2 < A_offd_i[i1+1]; jj2++)
{
i2 = A_offd_j[jj2];
a_entry = A_offd_data[jj2];
for ( i3=0; i3<num_rows_diag_A; i3++ ) {
/* ... note that num_rows_diag_A == num_rows_offd_A */
for ( jj3=A_offd_i[i3]; jj3<A_offd_i[i3+1]; jj3++ ) {
if ( A_offd_j[jj3]==i2 ) {
/* row i3, column i2 of A; or,
row i2, column i3 of A^T */
a_b_product = a_entry * A_offd_data[jj3];
/*--------------------------------------------------------
* Check B_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 (B_marker[i3] < jj_row_begin_diag)
{
B_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[B_marker[i3]] += a_b_product;
}
}
}
} /* end of last i3 loop */
} /* end of if (num_cols_offd_A) */
} /* end of fourth and last i2 loop */
#if 0 /* debugging printout */
hypre_printf("end of i1 loop: i1=%i jj_count_diag=%i\n", i1, jj_count_diag );
hypre_printf(" C_diag_j=");
for ( jj3=0; jj3<jj_count_diag; ++jj3) hypre_printf("%i ",C_diag_j[jj3]);
hypre_printf(" C_diag_data=");
for ( jj3=0; jj3<jj_count_diag; ++jj3) hypre_printf("%f ",C_diag_data[jj3]);
hypre_printf("\n");
hypre_printf(" C_offd_j=");
for ( jj3=0; jj3<jj_count_offd; ++jj3) hypre_printf("%i ",C_offd_j[jj3]);
hypre_printf(" C_offd_data=");
for ( jj3=0; jj3<jj_count_offd; ++jj3) hypre_printf("%f ",C_offd_data[jj3]);
hypre_printf("\n");
hypre_printf( " B_marker =" );
for ( it=0; it<num_rows_diag_A+num_rows_A_ext; ++it )
hypre_printf(" %i", B_marker[it] );
hypre_printf( "\n" );
#endif
} /* end of i1 loop */
/*-----------------------------------------------------------------------
* Delete 0-columns in C_offd, i.e. generate col_map_offd and reset
* C_offd_j. Note that (with the indexing we have coming into this
* block) col_map_offd_C[i3]==A_ext_row_map[i3].
*-----------------------------------------------------------------------*/
for ( i=0; i<num_rows_diag_A+num_rows_A_ext; ++i )
B_marker[i] = -1;
for ( i=0; i<C_offd_size; i++ )
B_marker[ C_offd_j[i] ] = -2;
count = 0;
for (i=0; i < num_rows_diag_A + num_rows_A_ext; i++) {
if (B_marker[i] == -2) {
B_marker[i] = count;
count++;
}
}
num_cols_offd_C = count;
if (num_cols_offd_C) {
col_map_offd_C = hypre_CTAlloc(HYPRE_Int,num_cols_offd_C);
new_C_offd_j = hypre_CTAlloc(HYPRE_Int,C_offd_size);
/* ... a bit big, but num_cols_offd_C is too small. It might be worth
computing the correct size, which is sum( no. columns in row i, over all rows i )
*/
for (i=0; i < C_offd_size; i++) {
new_C_offd_j[i] = B_marker[C_offd_j[i]];
col_map_offd_C[ new_C_offd_j[i] ] = A_ext_row_map[ C_offd_j[i] ];
}
hypre_TFree(C_offd_j);
C_offd_j = new_C_offd_j;
}
/*----------------------------------------------------------------
* Create C
*----------------------------------------------------------------*/
C = hypre_ParCSRMatrixCreate(comm, n_rows_A, n_rows_A, row_starts_A,
row_starts_A, 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;
if (num_cols_offd_C)
{
C_offd = hypre_ParCSRMatrixOffd(C);
hypre_CSRMatrixData(C_offd) = C_offd_data;
hypre_CSRMatrixI(C_offd) = C_offd_i;
hypre_CSRMatrixJ(C_offd) = C_offd_j;
hypre_ParCSRMatrixOffd(C) = C_offd;
hypre_ParCSRMatrixColMapOffd(C) = col_map_offd_C;
}
else
hypre_TFree(C_offd_i);
/*-----------------------------------------------------------------------
* Free B_ext and marker array.
*-----------------------------------------------------------------------*/
if (num_cols_offd_A)
{
hypre_CSRMatrixDestroy(A_ext);
A_ext = NULL;
}
hypre_TFree(B_marker);
if ( num_rows_diag_A != n_rows_A )
hypre_TFree(A_ext_row_map);
return C;
}
int
main(int argc, char *argv[])
{
GRID *g;
DOF *u_h;
MAT *A, *A0, *B;
MAP *map;
INT i;
size_t nnz, mem, mem_peak;
VEC *x, *y0, *y1, *y2;
double t0, t1, dnz, dnz1, mflops, mop;
char *fn = "../test/cube.dat";
FLOAT mem_max = 300;
INT refine = 0;
phgOptionsRegisterFilename("-mesh_file", "Mesh file", (char **)&fn);
phgOptionsRegisterInt("-loop_count", "Loop count", &loop_count);
phgOptionsRegisterInt("-refine", "Refinement level", &refine);
phgOptionsRegisterFloat("-mem_max", "Maximum memory", &mem_max);
phgInit(&argc, &argv);
g = phgNewGrid(-1);
if (!phgImport(g, fn, FALSE))
phgError(1, "can't read file \"%s\".\n", fn);
phgRefineAllElements(g, refine);
u_h = phgDofNew(g, DOF_DEFAULT, 1, "u_h", DofNoAction);
while (TRUE) {
phgPrintf("\n");
if (phgBalanceGrid(g, 1.2, 1, NULL, 0.))
phgPrintf("Repartition mesh, %d submeshes, load imbalance: %lg\n",
g->nprocs, (double)g->lif);
map = phgMapCreate(u_h, NULL);
A = phgMapCreateMat(map, map);
A->handle_bdry_eqns = TRUE;
build_matrix(A, u_h);
phgMatAssemble(A);
/* Note: A is unsymmetric (A' != A) if boundary entries not removed */
phgMatRemoveBoundaryEntries(A);
#if 0
/* test block matrix operation */
A0 = phgMatCreateBlockMatrix(g->comm, 1, 1, &A, NULL);
#else
A0 = A;
#endif
phgPrintf("%d DOF, %d elems, %d submeshes, matrix size: %d, LIF: %lg\n",
DofGetDataCountGlobal(u_h), g->nleaf_global,
g->nprocs, A->rmap->nglobal, (double)g->lif);
/* test PHG mat-vec multiply */
x = phgMapCreateVec(A->cmap, 1);
y1 = phgMapCreateVec(A->rmap, 1);
phgVecRandomize(x, 123);
phgMatVec(MAT_OP_N, 1.0, A0, x, 0.0, &y1);
phgPerfGetMflops(g, NULL, NULL); /* reset flops counter */
t0 = phgGetTime(NULL);
for (i = 0; i < loop_count; i++) {
phgMatVec(MAT_OP_N, 1.0, A0, x, 0.0, &y1);
}
t1 = phgGetTime(NULL);
mflops = phgPerfGetMflops(g, NULL, NULL);
y0 = phgVecCopy(y1, NULL);
nnz = A->nnz_d + A->nnz_o;
#if USE_MPI
dnz1 = nnz;
MPI_Reduce(&dnz1, &dnz, 1, MPI_DOUBLE, MPI_SUM, 0, g->comm);
#else
dnz = nnz;
#endif
mop = loop_count * (dnz + dnz - A->rmap->nlocal) * 1e-6;
phgPrintf("\n");
t1 -= t0;
phgPrintf(" PHG: time %0.4lf, nnz %0.16lg, %0.2lfMF (%0.2lfMF)\n",
t1, dnz, mop / (t1 == 0 ? 1. : t1), mflops);
/* test trans(A)*x */
phgPerfGetMflops(g, NULL, NULL); /* reset flops counter */
t0 = phgGetTime(NULL);
for (i = 0; i < loop_count; i++) {
phgMatVec(MAT_OP_T, 1.0, A0, x, 0.0, &y1);
}
t1 = phgGetTime(NULL);
mflops = phgPerfGetMflops(g, NULL, NULL);
t1 -= t0;
phgPrintf(" A'*x: time %0.4lf, nnz %0.16lg, %0.2lfMF (%0.2lfMF), "
"err: %le\n", t1, dnz, mop / (t1 == 0 ? 1. : t1), mflops,
(double)phgVecNorm2(phgVecAXPBY(-1.0, y0, 1.0, &y1), 0, NULL));
/* time A * trans(A) */
phgPerfGetMflops(g, NULL, NULL); /* reset flops counter */
t0 = phgGetTime(NULL);
B = phgMatMat(MAT_OP_N, MAT_OP_N, 1.0, A, A, 0.0, NULL);
t1 = phgGetTime(NULL);
mflops = phgPerfGetMflops(g, NULL, NULL);
nnz = B->nnz_d + B->nnz_o;
#if USE_MPI
dnz1 = nnz;
MPI_Reduce(&dnz1, &dnz, 1, MPI_DOUBLE, MPI_SUM, 0, g->comm);
#else
dnz = nnz;
#endif
/* compare B*x <--> A*A*x */
y2 = phgMatVec(MAT_OP_N, 1.0, B, x, 0.0, NULL);
phgMatVec(MAT_OP_N, 1.0, A0, y0, 0.0, &y1);
phgMatDestroy(&B);
t1 -= t0;
phgPrintf(" A*A: time %0.4lf, nnz %0.16lg, %0.2lfMF, err: %le\n",
t1, dnz, mflops,
(double)phgVecNorm2(phgVecAXPBY(-1.0, y1, 1.0, &y2), 0, NULL));
#if USE_PETSC
{
Mat ma, mb;
MatInfo info;
Vec va, vb, vc;
PetscScalar *vec;
ma = phgPetscCreateMatAIJ(A);
MatGetVecs(ma, PETSC_NULL, &va);
VecDuplicate(va, &vb);
VecGetArray(va, &vec);
memcpy(vec, x->data, x->map->nlocal * sizeof(*vec));
VecRestoreArray(va, &vec);
MatMult(ma, va, vb);
phgPerfGetMflops(g, NULL, NULL); /* reset flops counter */
t0 = phgGetTime(NULL);
for (i = 0; i < loop_count; i++) {
MatMult(ma, va, vb);
}
t1 = phgGetTime(NULL);
mflops = phgPerfGetMflops(g, NULL, NULL);
VecGetArray(vb, &vec);
memcpy(y1->data, vec, x->map->nlocal * sizeof(*vec));
VecRestoreArray(vb, &vec);
MatGetInfo(ma, MAT_GLOBAL_SUM, &info);
/*phgPrintf(" --------------------------------------------"
"-------------------------\n");*/
phgPrintf("\n");
t1 -= t0;
dnz = info.nz_used;
phgPrintf(" PETSc: time %0.4lf, nnz %0.16lg, %0.2lfMF (%0.2lfMF), "
"err: %le\n", t1, dnz, mop / (t1==0 ? 1.:t1), mflops,
(double)phgVecNorm2(phgVecAXPBY(-1.0, y0, 1.0, &y1), 0, NULL));
phgPerfGetMflops(g, NULL, NULL); /* reset flops counter */
t0 = phgGetTime(NULL);
for (i = 0; i < loop_count; i++) {
MatMultTranspose(ma, va, vb);
}
t1 = phgGetTime(NULL);
mflops = phgPerfGetMflops(g, NULL, NULL);
VecGetArray(vb, &vec);
memcpy(y1->data, vec, x->map->nlocal * sizeof(*vec));
VecRestoreArray(vb, &vec);
t1 -= t0;
phgPrintf(" A'*x: time %0.4lf, nnz %0.16lg, %0.2lfMF (%0.2lfMF), "
"err: %le\n", t1, dnz, mop / (t1==0 ? 1.:t1), mflops,
(double)phgVecNorm2(phgVecAXPBY(-1.0, y0, 1.0, &y1), 0, NULL));
phgPerfGetMflops(g, NULL, NULL); /* reset flops counter */
t0 = phgGetTime(NULL);
MatMatMult(ma, ma, MAT_INITIAL_MATRIX, PETSC_DEFAULT, &mb);
t1 = phgGetTime(NULL);
mflops = phgPerfGetMflops(g, NULL, NULL);
t1 -= t0;
MatGetInfo(mb, MAT_GLOBAL_SUM, &info);
dnz = info.nz_used;
VecDuplicate(va, &vc);
/* compare B*x <--> A*A*x */
MatMult(ma, vb, vc);
MatMult(mb, va, vb);
VecGetArray(vb, &vec);
memcpy(y1->data, vec, x->map->nlocal * sizeof(*vec));
VecRestoreArray(vb, &vec);
VecGetArray(vc, &vec);
memcpy(y2->data, vec, x->map->nlocal * sizeof(*vec));
VecRestoreArray(vc, &vec);
phgPrintf(" A*A: time %0.4lf, nnz %0.16lg, %0.2lfMF, err: %le\n",
t1, dnz, mflops,
(double)phgVecNorm2(phgVecAXPBY(-1.0, y1, 1.0, &y2), 0, NULL));
phgPetscMatDestroy(&mb);
phgPetscMatDestroy(&ma);
phgPetscVecDestroy(&va);
phgPetscVecDestroy(&vb);
phgPetscVecDestroy(&vc);
}
#endif /* USE_PETSC */
#if USE_HYPRE
{
HYPRE_IJMatrix ma;
HYPRE_IJVector va, vb, vc;
HYPRE_ParCSRMatrix par_ma;
hypre_ParCSRMatrix *par_mb;
HYPRE_ParVector par_va, par_vb, par_vc;
HYPRE_Int offset, *ni, start, end;
assert(sizeof(INT)==sizeof(int) && sizeof(FLOAT)==sizeof(double));
setup_hypre_mat(A, &ma);
ni = phgAlloc(2 * A->rmap->nlocal * sizeof(*ni));
offset = A->cmap->partition[A->cmap->rank];
for (i = 0; i < A->rmap->nlocal; i++)
ni[i] = i + offset;
HYPRE_IJVectorCreate(g->comm, offset, offset + A->rmap->nlocal - 1,
&va);
HYPRE_IJVectorCreate(g->comm, offset, offset + A->rmap->nlocal - 1,
&vb);
HYPRE_IJVectorCreate(g->comm, offset, offset + A->rmap->nlocal - 1,
&vc);
HYPRE_IJVectorSetObjectType(va, HYPRE_PARCSR);
HYPRE_IJVectorSetObjectType(vb, HYPRE_PARCSR);
HYPRE_IJVectorSetObjectType(vc, HYPRE_PARCSR);
HYPRE_IJVectorSetMaxOffProcElmts(va, 0);
HYPRE_IJVectorSetMaxOffProcElmts(vb, 0);
HYPRE_IJVectorSetMaxOffProcElmts(vc, 0);
HYPRE_IJVectorInitialize(va);
HYPRE_IJVectorInitialize(vb);
HYPRE_IJVectorInitialize(vc);
HYPRE_IJMatrixGetObject(ma, (void **)(void *)&par_ma);
HYPRE_IJVectorGetObject(va, (void **)(void *)&par_va);
HYPRE_IJVectorGetObject(vb, (void **)(void *)&par_vb);
HYPRE_IJVectorGetObject(vc, (void **)(void *)&par_vc);
HYPRE_IJVectorSetValues(va, A->cmap->nlocal, ni, (double *)x->data);
HYPRE_IJVectorAssemble(va);
HYPRE_IJVectorAssemble(vb);
HYPRE_IJVectorAssemble(vc);
HYPRE_IJMatrixGetRowCounts(ma, A->cmap->nlocal,
ni, ni + A->rmap->nlocal);
for (i = 0, nnz = 0; i < A->rmap->nlocal; i++)
nnz += ni[A->rmap->nlocal + i];
#if USE_MPI
dnz1 = nnz;
MPI_Reduce(&dnz1, &dnz, 1, MPI_DOUBLE, MPI_SUM, 0, g->comm);
#else
dnz = nnz;
#endif
HYPRE_ParCSRMatrixMatvec(1.0, par_ma, par_va, 0.0, par_vb);
phgPerfGetMflops(g, NULL, NULL); /* reset flops counter */
t0 = phgGetTime(NULL);
for (i = 0; i < loop_count; i++) {
HYPRE_ParCSRMatrixMatvec(1.0, par_ma, par_va, 0.0, par_vb);
}
t1 = phgGetTime(NULL);
mflops = phgPerfGetMflops(g, NULL, NULL);
HYPRE_IJVectorGetValues(vb, A->rmap->nlocal, ni, (double*)y1->data);
/*phgPrintf(" --------------------------------------------"
"-------------------------\n");*/
phgPrintf("\n");
t1 -= t0;
phgPrintf(" HYPRE: time %0.4lf, nnz %0.16lg, %0.2lfMF (%0.2lfMF), "
"err: %le\n", t1, dnz, mop / (t1==0 ? 1.:t1), mflops,
(double)phgVecNorm2(phgVecAXPBY(-1.0, y0, 1.0, &y1), 0, NULL));
phgPerfGetMflops(g, NULL, NULL); /* reset flops counter */
t0 = phgGetTime(NULL);
for (i = 0; i < loop_count; i++) {
HYPRE_ParCSRMatrixMatvecT(1.0, par_ma, par_va, 0.0, par_vb);
}
t1 = phgGetTime(NULL);
mflops = phgPerfGetMflops(g, NULL, NULL);
HYPRE_IJVectorGetValues(vb, A->rmap->nlocal, ni, (double*)y1->data);
t1 -= t0;
phgPrintf(" A'*x: time %0.4lf, nnz %0.16lg, %0.2lfMF (%0.2lfMF), "
"err: %le\n", t1, dnz, mop / (t1==0 ? 1.:t1), mflops,
(double)phgVecNorm2(phgVecAXPBY(-1.0, y0, 1.0, &y1), 0, NULL));
phgPerfGetMflops(g, NULL, NULL); /* reset flops counter */
t0 = phgGetTime(NULL);
/* Note: 'HYPRE_ParCSRMatrix' is currently typedef'ed to
* 'hypre_ParCSRMatrix *' */
par_mb = hypre_ParMatmul((hypre_ParCSRMatrix *)par_ma,
(hypre_ParCSRMatrix *)par_ma);
t1 = phgGetTime(NULL);
mflops = phgPerfGetMflops(g, NULL, NULL);
start = hypre_ParCSRMatrixFirstRowIndex(par_mb);
end = hypre_ParCSRMatrixLastRowIndex(par_mb) + 1;
for (i = start, nnz = 0; i < end; i++) {
HYPRE_Int ncols;
hypre_ParCSRMatrixGetRow(par_mb, i, &ncols, NULL, NULL);
hypre_ParCSRMatrixRestoreRow(par_mb, i, &ncols, NULL, NULL);
nnz += ncols;
}
#if USE_MPI
dnz1 = nnz;
MPI_Reduce(&dnz1, &dnz, 1, MPI_DOUBLE, MPI_SUM, 0, g->comm);
#else
dnz = nnz;
#endif
/* compare B*x <--> A*A*x */
HYPRE_ParCSRMatrixMatvec(1.0, par_ma, par_vb, 0.0, par_vc);
HYPRE_ParCSRMatrixMatvec(1.0, (void *)par_mb, par_va, 0.0, par_vb);
HYPRE_IJVectorGetValues(vb, A->rmap->nlocal, ni, (double*)y1->data);
HYPRE_IJVectorGetValues(vc, A->rmap->nlocal, ni, (double*)y2->data);
hypre_ParCSRMatrixDestroy((par_mb));
t1 -= t0;
phgPrintf(" A*A: time %0.4lf, nnz %0.16lg, %0.2lfMF, err: %le\n",
t1, dnz, mflops,
(double)phgVecNorm2(phgVecAXPBY(-1.0, y1, 1.0, &y2), 0, NULL));
phgFree(ni);
HYPRE_IJMatrixDestroy(ma);
HYPRE_IJVectorDestroy(va);
HYPRE_IJVectorDestroy(vb);
HYPRE_IJVectorDestroy(vc);
}
#endif /* USE_HYPRE */
if (A0 != A)
phgMatDestroy(&A0);
#if 0
if (A->rmap->nglobal > 1000) {
VEC *v = phgMapCreateVec(A->rmap, 3);
for (i = 0; i < v->map->nlocal; i++) {
v->data[i + 0 * v->map->nlocal] = 1 * (i + v->map->partition[g->rank]);
v->data[i + 1 * v->map->nlocal] = 2 * (i + v->map->partition[g->rank]);
v->data[i + 2 * v->map->nlocal] = 3 * (i + v->map->partition[g->rank]);
}
phgMatDumpMATLAB(A, "A", "A.m");
phgVecDumpMATLAB(v, "v", "v.m");
phgFinalize();
exit(0);
}
#endif
phgMatDestroy(&A);
phgVecDestroy(&x);
phgVecDestroy(&y0);
phgVecDestroy(&y1);
phgVecDestroy(&y2);
phgMapDestroy(&map);
mem = phgMemoryUsage(g, &mem_peak);
dnz = mem / (1024.0 * 1024.0);
dnz1 = mem_peak / (1024.0 * 1024.0);
/*phgPrintf(" --------------------------------------------"
"-------------------------\n");*/
phgPrintf("\n");
phgPrintf(" Memory: current %0.4lgMB, peak %0.4lgMB\n", dnz, dnz1);
#if 0
{
static int loop_count = 0;
if (++loop_count == 4)
break;
}
#endif
if (mem_peak > 1024 * (size_t)1024 * mem_max)
break;
phgRefineAllElements(g, 1);
}
phgDofFree(&u_h);
phgFreeGrid(&g);
phgFinalize();
return 0;
}
HYPRE_Int
hypre_ParCSRMatrixToParChordMatrix(
hypre_ParCSRMatrix *Ap,
MPI_Comm comm,
hypre_ParChordMatrix **pAc )
{
HYPRE_Int * row_starts = hypre_ParCSRMatrixRowStarts(Ap);
HYPRE_Int * col_starts = hypre_ParCSRMatrixColStarts(Ap);
hypre_CSRMatrix * diag = hypre_ParCSRMatrixDiag(Ap);
hypre_CSRMatrix * offd = hypre_ParCSRMatrixOffd(Ap);
HYPRE_Int * offd_j = hypre_CSRMatrixJ(offd);
HYPRE_Int * diag_j = hypre_CSRMatrixJ(diag);
HYPRE_Int * col_map_offd = hypre_ParCSRMatrixColMapOffd(Ap);
HYPRE_Int first_col_diag = hypre_ParCSRMatrixFirstColDiag(Ap);
hypre_ParChordMatrix * Ac;
hypre_NumbersNode * rdofs, * offd_cols_me;
hypre_NumbersNode ** offd_cols;
HYPRE_Int ** offd_col_array;
HYPRE_Int * len_offd_col_array, * offd_col_array_me;
HYPRE_Int len_offd_col_array_me;
HYPRE_Int num_idofs, num_rdofs, j_local, j_global, row_global;
HYPRE_Int i, j, jj, p, pto, q, qto, my_id, my_q, row, ireq;
HYPRE_Int num_inprocessors, num_toprocessors, num_procs, len_num_rdofs_toprocessor;
HYPRE_Int *inprocessor, *toprocessor, *pcr, *qcr, *num_inchords, *chord, *chordto;
HYPRE_Int *inproc, *toproc, *num_rdofs_toprocessor;
HYPRE_Int **inchord_idof, **inchord_rdof, **rdof_toprocessor;
double **inchord_data;
double data;
HYPRE_Int *first_index_idof, *first_index_rdof;
hypre_MPI_Request * request;
hypre_MPI_Status * status;
hypre_MPI_Comm_rank(comm, &my_id);
hypre_MPI_Comm_size(comm, &num_procs);
num_idofs = row_starts[my_id+1] - row_starts[my_id];
num_rdofs = col_starts[my_id+1] - col_starts[my_id];
hypre_ParChordMatrixCreate( pAc, comm, num_idofs, num_rdofs );
Ac = *pAc;
/* The following block sets Inprocessor:
On each proc. my_id, we find the columns in the offd and diag blocks
(global no.s). The columns are rdofs (contrary to what I wrote in
ChordMatrix.txt).
For each such col/rdof r, find the proc. p which owns row/idof r.
We set the temporary array pcr[p]=1 for such p.
An MPI all-to-all will exchange such arrays so my_id's array qcr has
qcr[q]=1 iff, on proc. q, pcr[my_id]=1. In other words, qcr[q]=1 if
my_id owns a row/idof i which is the same as a col/rdof owned by q.
Collect all such q's into in the array Inprocessor.
While constructing pcr, we also construct pj such that for any index jj
into offd_j,offd_data, pj[jj] is the processor which owns jj as a row (idof)
(the number jj is local to this processor).
*/
pcr = hypre_CTAlloc( HYPRE_Int, num_procs );
qcr = hypre_CTAlloc( HYPRE_Int, num_procs );
for ( p=0; p<num_procs; ++p ) pcr[p]=0;
for ( jj=0; jj<hypre_CSRMatrixNumNonzeros(offd); ++jj ) {
j_local = offd_j[jj];
j_global = col_map_offd[j_local];
for ( p=0; p<num_procs; ++p ) {
if ( j_global >= row_starts[p] && j_global<row_starts[p+1] ) {
pcr[p]=1;
/* not used yet... pj[jj] = p;*/
break;
}
}
}
/* jjd = jj; ...not used yet */
/* pcr[my_id] = 1; ...for square matrices (with nonzero diag block)
this one line would do the job of the following nested loop.
For non-square matrices, the data distribution is too arbitrary. */
for ( jj=0; jj<hypre_CSRMatrixNumNonzeros(diag); ++jj ) {
j_local = diag_j[jj];
j_global = j_local + first_col_diag;
for ( p=0; p<num_procs; ++p ) {
if ( j_global >= row_starts[p] && j_global<row_starts[p+1] ) {
pcr[p]=1;
/* not used yet... pj[jj+jjd] = p;*/
break;
}
}
}
/* Now pcr[p]=1 iff my_id owns a col/rdof r which proc. p owns as a row/idof */
hypre_MPI_Alltoall( pcr, 1, HYPRE_MPI_INT, qcr, 1, HYPRE_MPI_INT, comm );
/* Now qcr[q]==1 if my_id owns a row/idof i which is a col/rdof of proc. q
The array of such q's is the array Inprocessor. */
num_inprocessors = 0;
for ( q=0; q<num_procs; ++q ) if ( qcr[q]==1 ) ++num_inprocessors;
inprocessor = hypre_CTAlloc( HYPRE_Int, num_inprocessors );
p = 0;
for ( q=0; q<num_procs; ++q ) if ( qcr[q]==1 ) inprocessor[ p++ ] = q;
num_toprocessors = 0;
for ( q=0; q<num_procs; ++q ) if ( pcr[q]==1 ) ++num_toprocessors;
toprocessor = hypre_CTAlloc( HYPRE_Int, num_toprocessors );
p = 0;
for ( q=0; q<num_procs; ++q ) if ( pcr[q]==1 ) toprocessor[ p++ ] = q;
hypre_ParChordMatrixNumInprocessors(Ac) = num_inprocessors;
hypre_ParChordMatrixInprocessor(Ac) = inprocessor;
hypre_ParChordMatrixNumToprocessors(Ac) = num_toprocessors;
hypre_ParChordMatrixToprocessor(Ac) = toprocessor;
hypre_TFree( qcr );
/* FirstIndexIdof[p] is the global index of proc. p's row 0 */
/* FirstIndexRdof[p] is the global index of proc. p's col 0 */
/* Fir FirstIndexIdof, we copy the array row_starts rather than its pointers,
because the chord matrix will think it's free to delete FirstIndexIdof */
/* col_starts[p] contains the global index of the first column
in the diag block of p. But for first_index_rdof we want the global
index of the first column in p (whether that's in the diag or offd block).
So it's more involved than row/idof: we also check the offd block, and
have to do a gather to get first_index_rdof for every proc. on every proc. */
first_index_idof = hypre_CTAlloc( HYPRE_Int, num_procs+1 );
first_index_rdof = hypre_CTAlloc( HYPRE_Int, num_procs+1 );
for ( p=0; p<=num_procs; ++p ) {
first_index_idof[p] = row_starts[p];
first_index_rdof[p] = col_starts[p];
};
if ( hypre_CSRMatrixNumRows(offd) > 0 && hypre_CSRMatrixNumCols(offd) > 0 )
first_index_rdof[my_id] =
col_starts[my_id]<col_map_offd[0] ? col_starts[my_id] : col_map_offd[0];
hypre_MPI_Allgather( &first_index_rdof[my_id], 1, HYPRE_MPI_INT,
first_index_rdof, 1, HYPRE_MPI_INT, comm );
/* Set num_inchords: num_inchords[p] is no. chords on my_id connected to p.
Set each chord (idof,jdof,data).
We go through each matrix element in the diag block, find what processor
owns its column no. as a row, then update num_inchords[p], inchord_idof[p],
inchord_rdof[p], inchord_data[p].
*/
inchord_idof = hypre_CTAlloc( HYPRE_Int*, num_inprocessors );
inchord_rdof = hypre_CTAlloc( HYPRE_Int*, num_inprocessors );
inchord_data = hypre_CTAlloc( double*, num_inprocessors );
num_inchords = hypre_CTAlloc( HYPRE_Int, num_inprocessors );
chord = hypre_CTAlloc( HYPRE_Int, num_inprocessors );
chordto = hypre_CTAlloc( HYPRE_Int, num_toprocessors );
num_rdofs = 0;
for ( q=0; q<num_inprocessors; ++q ) num_inchords[q] = 0;
my_q = -1;
for ( q=0; q<num_inprocessors; ++q ) if ( inprocessor[q]==my_id ) my_q = q;
hypre_assert( my_q>=0 );
/* diag block: first count chords (from my_id to my_id),
then set them from diag block's CSR data structure */
num_idofs = hypre_CSRMatrixNumRows(diag);
rdofs = hypre_NumbersNewNode();
for ( row=0; row<hypre_CSRMatrixNumRows(diag); ++row ) {
for ( i=hypre_CSRMatrixI(diag)[row]; i<hypre_CSRMatrixI(diag)[row+1]; ++i ) {
j_local = hypre_CSRMatrixJ(diag)[i];
hypre_NumbersEnter( rdofs, j_local );
++num_inchords[my_q];
}
};
num_rdofs = hypre_NumbersNEntered( rdofs );
inchord_idof[my_q] = hypre_CTAlloc( HYPRE_Int, num_inchords[my_q] );
inchord_rdof[my_q] = hypre_CTAlloc( HYPRE_Int, num_inchords[my_q] );
inchord_data[my_q] = hypre_CTAlloc( double, num_inchords[my_q] );
chord[0] = 0;
for ( row=0; row<hypre_CSRMatrixNumRows(diag); ++row ) {
for ( i=hypre_CSRMatrixI(diag)[row]; i<hypre_CSRMatrixI(diag)[row+1]; ++i ) {
j_local = hypre_CSRMatrixJ(diag)[i];
data = hypre_CSRMatrixData(diag)[i];
inchord_idof[my_q][chord[0]] = row;
/* Here We need to convert from j_local - a column local to
the diag of this proc., to a j which is local only to this
processor - a column (rdof) numbering scheme to be shared by the
diag and offd blocks... */
j_global = j_local + hypre_ParCSRMatrixColStarts(Ap)[my_q];
j = j_global - first_index_rdof[my_q];
inchord_rdof[my_q][chord[0]] = j;
inchord_data[my_q][chord[0]] = data;
hypre_assert( chord[0] < num_inchords[my_q] );
++chord[0];
}
};
hypre_NumbersDeleteNode(rdofs);
/* offd block: */
/* >>> offd_cols_me duplicates rdofs */
offd_cols_me = hypre_NumbersNewNode();
for ( row=0; row<hypre_CSRMatrixNumRows(offd); ++row ) {
for ( i=hypre_CSRMatrixI(offd)[row]; i<hypre_CSRMatrixI(offd)[row+1]; ++i ) {
j_local = hypre_CSRMatrixJ(offd)[i];
j_global = col_map_offd[j_local];
hypre_NumbersEnter( offd_cols_me, j_global );
}
}
offd_col_array = hypre_CTAlloc( HYPRE_Int*, num_inprocessors );
len_offd_col_array = hypre_CTAlloc( HYPRE_Int, num_inprocessors );
offd_col_array_me = hypre_NumbersArray( offd_cols_me );
len_offd_col_array_me = hypre_NumbersNEntered( offd_cols_me );
request = hypre_CTAlloc(hypre_MPI_Request, 2*num_procs );
ireq = 0;
for ( q=0; q<num_inprocessors; ++q )
hypre_MPI_Irecv( &len_offd_col_array[q], 1, HYPRE_MPI_INT,
inprocessor[q], 0, comm, &request[ireq++] );
for ( p=0; p<num_procs; ++p ) if ( pcr[p]==1 ) {
hypre_MPI_Isend( &len_offd_col_array_me, 1, HYPRE_MPI_INT, p, 0, comm, &request[ireq++] );
}
status = hypre_CTAlloc(hypre_MPI_Status, ireq );
hypre_MPI_Waitall( ireq, request, status );
hypre_TFree(status);
ireq = 0;
for ( q=0; q<num_inprocessors; ++q )
offd_col_array[q] = hypre_CTAlloc( HYPRE_Int, len_offd_col_array[q] );
for ( q=0; q<num_inprocessors; ++q )
hypre_MPI_Irecv( offd_col_array[q], len_offd_col_array[q], HYPRE_MPI_INT,
inprocessor[q], 0, comm, &request[ireq++] );
for ( p=0; p<num_procs; ++p ) if ( pcr[p]==1 ) {
hypre_MPI_Isend( offd_col_array_me, len_offd_col_array_me,
HYPRE_MPI_INT, p, 0, comm, &request[ireq++] );
}
status = hypre_CTAlloc(hypre_MPI_Status, ireq );
hypre_MPI_Waitall( ireq, request, status );
hypre_TFree(request);
hypre_TFree(status);
offd_cols = hypre_CTAlloc( hypre_NumbersNode *, num_inprocessors );
for ( q=0; q<num_inprocessors; ++q ) {
offd_cols[q] = hypre_NumbersNewNode();
for ( i=0; i<len_offd_col_array[q]; ++i )
hypre_NumbersEnter( offd_cols[q], offd_col_array[q][i] );
}
len_num_rdofs_toprocessor = 1 + hypre_CSRMatrixI(offd)
[hypre_CSRMatrixNumRows(offd)];
inproc = hypre_CTAlloc( HYPRE_Int, len_num_rdofs_toprocessor );
toproc = hypre_CTAlloc( HYPRE_Int, len_num_rdofs_toprocessor );
num_rdofs_toprocessor = hypre_CTAlloc( HYPRE_Int, len_num_rdofs_toprocessor );
for ( qto=0; qto<len_num_rdofs_toprocessor; ++qto ) {
inproc[qto] = -1;
toproc[qto] = -1;
num_rdofs_toprocessor[qto] = 0;
};
rdofs = hypre_NumbersNewNode();
for ( row=0; row<hypre_CSRMatrixNumRows(offd); ++row ) {
for ( i=hypre_CSRMatrixI(offd)[row]; i<hypre_CSRMatrixI(offd)[row+1]; ++i ) {
j_local = hypre_CSRMatrixJ(offd)[i];
j_global = col_map_offd[j_local];
hypre_NumbersEnter( rdofs, j_local );
/* TO DO: find faster ways to do the two processor lookups below.*/
/* Find a processor p (local index q) from the inprocessor list,
which owns the column(rdof) whichis the same as this processor's
row(idof) row. Update num_inchords for p.
Save q as inproc[i] for quick recall later. It represents
an inprocessor (not unique) connected to a chord i.
*/
inproc[i] = -1;
for ( q=0; q<num_inprocessors; ++q ) if (q!=my_q) {
p = inprocessor[q];
if ( hypre_NumbersQuery( offd_cols[q],
row+hypre_ParCSRMatrixFirstRowIndex(Ap) )
== 1 ) {
/* row is one of the offd columns of p */
++num_inchords[q];
inproc[i] = q;
break;
}
}
if ( inproc[i]<0 ) {
/* For square matrices, we would have found the column in some
other processor's offd. But for non-square matrices it could
exist only in some other processor's diag...*/
/* Note that all data in a diag block is stored. We don't check
whether the value of a data entry is zero. */
for ( q=0; q<num_inprocessors; ++q ) if (q!=my_q) {
p = inprocessor[q];
row_global = row+hypre_ParCSRMatrixFirstRowIndex(Ap);
if ( row_global>=col_starts[p] &&
row_global< col_starts[p+1] ) {
/* row is one of the diag columns of p */
++num_inchords[q];
inproc[i] = q;
break;
}
}
}
hypre_assert( inproc[i]>=0 );
/* Find the processor pto (local index qto) from the toprocessor list,
which owns the row(idof) which is the same as this processor's
column(rdof) j_global. Update num_rdofs_toprocessor for pto.
Save pto as toproc[i] for quick recall later. It represents
the toprocessor connected to a chord i. */
for ( qto=0; qto<num_toprocessors; ++qto ) {
pto = toprocessor[qto];
if ( j_global >= row_starts[pto] && j_global<row_starts[pto+1] ) {
hypre_assert( qto < len_num_rdofs_toprocessor );
++num_rdofs_toprocessor[qto];
/* ... an overestimate, as if two chords share an rdof, that
rdof will be counted twice in num_rdofs_toprocessor.
It can be fixed up later.*/
toproc[i] = qto;
break;
}
}
}
};
num_rdofs += hypre_NumbersNEntered(rdofs);
hypre_NumbersDeleteNode(rdofs);
for ( q=0; q<num_inprocessors; ++q ) if (q!=my_q) {
inchord_idof[q] = hypre_CTAlloc( HYPRE_Int, num_inchords[q] );
inchord_rdof[q] = hypre_CTAlloc( HYPRE_Int, num_inchords[q] );
inchord_data[q] = hypre_CTAlloc( double, num_inchords[q] );
chord[q] = 0;
};
