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https://github.com/OPM/opm-simulators.git
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7bce15c04b
We need to compute quite a few global reductions in the Newton method of opm-autodiff. This commit adds the functionality to compute several reductions combined using only one global communication. Compiles and test succeeds with one or more process.
94 lines
3.1 KiB
C++
94 lines
3.1 KiB
C++
/*
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Copyright 2014 Dr. Markus Blatt - HPC-Simulation-Software & Services
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This file is part of the Open Porous Media project (OPM).
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OPM is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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OPM is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with OPM. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include <config.h>
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#if HAVE_DYNAMIC_BOOST_TEST
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#define BOOST_TEST_DYN_LINK
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#endif
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#define NVERBOSE // to suppress our messages when throwing
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#define BOOST_TEST_MODULE OPM-ParallelIterativeSolverTest
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#include <boost/test/unit_test.hpp>
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// MPI header
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#if HAVE_MPI
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#include <mpi.h>
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#include <dune/common/version.hh>
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#include <opm/core/linalg/ParallelIstlInformation.hpp>
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#else
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#error "This file needs to compiled with MPI support!"
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#endif
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#include "DuneIstlTestHelpers.hpp"
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#include <opm/core/linalg/LinearSolverFactory.hpp>
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#include <opm/core/utility/parameters/ParameterGroup.hpp>
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#include <memory>
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#include <cstdlib>
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#include <string>
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void run_test(const Opm::parameter::ParameterGroup& param)
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{
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int N=100;
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int start, end, istart, iend;
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std::tie(start,istart,iend,end) = computeRegions(N);
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Opm::ParallelISTLInformation comm(MPI_COMM_WORLD);
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auto mat = create1DLaplacian(*comm.indexSet(), N, start, end, istart, iend);
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std::vector<double> x(end-start), b(end-start);
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createRandomVectors(comm, end-start, x, b, *mat);
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std::vector<double> exact(x);
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std::fill(x.begin(), x.end(), 0.0);
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Opm::LinearSolverFactory ls(param);
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boost::any anyComm(comm);
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ls.solve(b.size(), mat->data.size(), &(mat->rowStart[0]),
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&(mat->colIndex[0]), &(mat->data[0]), &(b[0]),
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&(x[0]), anyComm);
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}
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#ifdef HAVE_DUNE_ISTL
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BOOST_AUTO_TEST_CASE(CGAMGTest)
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{
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Opm::parameter::ParameterGroup param;
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param.insertParameter(std::string("linsolver"), std::string("istl"));
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param.insertParameter(std::string("linsolver_type"), std::string("1"));
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param.insertParameter(std::string("linsolver_max_iterations"), std::string("200"));
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run_test(param);
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}
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BOOST_AUTO_TEST_CASE(CGILUTest)
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{
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Opm::parameter::ParameterGroup param;
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param.insertParameter(std::string("linsolver"), std::string("istl"));
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param.insertParameter(std::string("linsolver_type"), std::string("0"));
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param.insertParameter(std::string("linsolver_max_iterations"), std::string("200"));
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run_test(param);
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}
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BOOST_AUTO_TEST_CASE(BiCGILUTest)
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{
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Opm::parameter::ParameterGroup param;
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param.insertParameter(std::string("linsolver"), std::string("istl"));
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param.insertParameter(std::string("linsolver_type"), std::string("2"));
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param.insertParameter(std::string("linsolver_max_iterations"), std::string("200"));
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run_test(param);
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}
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#endif
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