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rAKA/test/test_solver/test_sparse_matrix_product.cc
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test_sparse_matrix_product.cc
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/**
* @file test_sparse_matrix_product.cc
*
* @author Nicolas Richart <nicolas.richart@epfl.ch>
*
* @date creation: Fri Jun 17 2011
* @date last modification: Mon Sep 15 2014
*
* @brief test the matrix vector product in parallel
*
* @section LICENSE
*
* Copyright (©) 2014 EPFL (Ecole Polytechnique Fédérale de Lausanne)
* Laboratory (LSMS - Laboratoire de Simulation en Mécanique des Solides)
*
* Akantu is free software: you can redistribute it and/or modify it under the
* terms of the GNU Lesser General Public License as published by the Free
* Software Foundation, either version 3 of the License, or (at your option) any
* later version.
*
* Akantu is distributed in the hope that it will be useful, but WITHOUT ANY
* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
* A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more
* details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with Akantu. If not, see <http://www.gnu.org/licenses/>.
*
*/
/* -------------------------------------------------------------------------- */
#include <iostream>
/* -------------------------------------------------------------------------- */
#include "aka_common.hh"
#include "mesh.hh"
#include "mesh_partition_scotch.hh"
#include "distributed_synchronizer.hh"
#include "sparse_matrix.hh"
#include "dof_synchronizer.hh"
/* -------------------------------------------------------------------------- */
using namespace akantu;
/* -------------------------------------------------------------------------- */
int main(int argc, char *argv[])
{
initialize(argc, argv);
const UInt spatial_dimension = 2;
const UInt nb_dof = 3;
StaticCommunicator & comm = akantu::StaticCommunicator::getStaticCommunicator();
Int psize = comm.getNbProc();
Int prank = comm.whoAmI();
Mesh mesh(spatial_dimension);
/* ------------------------------------------------------------------------ */
/* Parallel initialization */
/* ------------------------------------------------------------------------ */
MeshPartition * partition;
if(prank == 0) {
mesh.read("bar.msh");
std::cout << "Partitioning mesh..." << std::endl;
partition = new akantu::MeshPartitionScotch(mesh, spatial_dimension);
partition->partitionate(psize);
DistributedSynchronizer::createDistributedSynchronizerMesh(mesh, partition);
delete partition;
} else {
DistributedSynchronizer::createDistributedSynchronizerMesh(mesh, NULL);
}
UInt nb_nodes = mesh.getNbNodes();
UInt nb_global_node = mesh.getNbGlobalNodes();
// Array<Int> equation_number(nb_nodes, nb_dof);
// for (UInt n = 0; n < nb_nodes; ++n) {
// UInt real_n = mesh.getNodeGlobalId(n);
// bool is_local_node = !(mesh.isPureGhostNode(n));
// for (UInt d = 0; d < nb_dof; ++d) {
// UInt global_eq_num = (is_local_node ? real_n : nb_global_node + real_n) * nb_dof + d;
// equation_number(n, d) = global_eq_num;
// }
// }
if (prank == 0) std::cout << "Creating a SparseMatrix" << std::endl;
SparseMatrix sparse_matrix(nb_global_node * nb_dof, _symmetric, "matrix");
DOFSynchronizer dof_synchronizer(mesh, nb_dof);
dof_synchronizer.initGlobalDOFEquationNumbers();
sparse_matrix.buildProfile(mesh, dof_synchronizer, nb_dof);
Array<Real> dof_vector(nb_nodes, nb_dof, "vector");
if (prank == 0) std::cout << "Filling the matrix" << std::endl;
UInt nz = sparse_matrix.getNbNonZero();
const Array<Int> & irn = sparse_matrix.getIRN();
const Array<Int> & jcn = sparse_matrix.getJCN();
for (UInt i = 0; i < nz; ++i) {
sparse_matrix.addToMatrix(irn(i) - 1, jcn(i) - 1, 1.);
}
std::stringstream str; str << "Matrix_" << prank << ".mtx";
sparse_matrix.saveMatrix(str.str());
for (UInt n = 0; n < nb_nodes; ++n) {
for (UInt d = 0; d < nb_dof; ++d) {
dof_vector(n,d) = 1.;
}
}
if (prank == 0) std::cout << "Computing x = A * x" << std::endl;
dof_vector *= sparse_matrix;
if (prank == 0) std::cout << "Lumping the matrix" << std::endl;
Array<Real> lumped(0,nb_dof);
sparse_matrix.lump(lumped);
if (prank == 0) std::cout << "Gathering the results on proc 0" << std::endl;
if(psize > 1) {
const_cast<DOFSynchronizer &>(sparse_matrix.getDOFSynchronizer()).initScatterGatherCommunicationScheme();
if(prank == 0) {
Array<Real> gathered(0, nb_dof);
Array<Real> lump_gathered(0, nb_dof);
sparse_matrix.getDOFSynchronizer().gather(dof_vector, 0, &gathered);
sparse_matrix.getDOFSynchronizer().gather(lumped, 0, &lump_gathered);
debug::setDebugLevel(dblTest);
std::cout << gathered << std::endl;
std::cout << lump_gathered << std::endl;
debug::setDebugLevel(dblWarning);
} else {
sparse_matrix.getDOFSynchronizer().gather(dof_vector, 0);
sparse_matrix.getDOFSynchronizer().gather(lumped, 0);
}
} else {
debug::setDebugLevel(dblTest);
std::cout << dof_vector << std::endl;
std::cout << lumped << std::endl;
debug::setDebugLevel(dblWarning);
}
finalize();
return 0;
}
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