/*
Copyright 2022-2023 SINTEF AS
This file is part of the Open Porous Media project (OPM).
OPM is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
OPM 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 General Public License for more details.
You should have received a copy of the GNU General Public License
along with OPM. If not, see .
*/
#include
#define BOOST_TEST_MODULE TestGpuSparseMatrixOperations
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
using NumericTypes = boost::mpl::list;
BOOST_AUTO_TEST_CASE_TEMPLATE(FlattenAndInvertDiagonalWith3By3Blocks, T, NumericTypes)
{
const size_t blocksize = 3;
const size_t N = 2;
const int nonZeroes = 3;
using M = Dune::FieldMatrix;
using SpMatrix = Dune::BCRSMatrix;
/*
create this sparse matrix
| |1 2 3| | 1 0 0| |
| |5 2 3| | 0 1 0| |
| |2 1 1| | 0 0 1| |
| |
| |0 0 0| |-1 0 0| |
| |0 0 0| | 0 -1 0| |
| |0 0 0| | 0 0 -1| |
The diagonal elements inverted, and put in a vector should look like this
| |-1/4 1/4 0| |
| | 1/4 -4/5 3| |
| | 1/4 3/4 -2| |
| |
| | -1 0 0| |
| | 0 -1 0| |
| | 0 0 -1| |
*/
SpMatrix B(N, N, nonZeroes, SpMatrix::row_wise);
for (auto row = B.createbegin(); row != B.createend(); ++row) {
row.insert(row.index());
if (row.index() == 0) {
row.insert(row.index() + 1);
}
}
B[0][0][0][0] = 1.0;
B[0][0][0][1] = 2.0;
B[0][0][0][2] = 3.0;
B[0][0][1][0] = 5.0;
B[0][0][1][1] = 2.0;
B[0][0][1][2] = 3.0;
B[0][0][2][0] = 2.0;
B[0][0][2][1] = 1.0;
B[0][0][2][2] = 1.0;
B[0][1][0][0] = 1.0;
B[0][1][1][1] = 1.0;
B[0][1][2][2] = 1.0;
B[1][1][0][0] = -1.0;
B[1][1][1][1] = -1.0;
B[1][1][2][2] = -1.0;
Opm::gpuistl::GpuSparseMatrix m = Opm::gpuistl::GpuSparseMatrix::fromMatrix(B);
Opm::gpuistl::GpuVector dInvDiag(blocksize * blocksize * N);
Opm::gpuistl::detail::JAC::invertDiagonalAndFlatten(
m.getNonZeroValues().data(), m.getRowIndices().data(), m.getColumnIndices().data(), N, dInvDiag.data());
std::vector expectedInvDiag {-1.0 / 4.0,
1.0 / 4.0,
0.0,
1.0 / 4.0,
-5.0 / 4.0,
3.0,
1.0 / 4.0,
3.0 / 4.0,
-2.0,
-1.0,
0.0,
0.0,
0.0,
-1.0,
0.0,
0.0,
0.0,
-1.0};
std::vector computedInvDiag = dInvDiag.asStdVector();
BOOST_REQUIRE_EQUAL(expectedInvDiag.size(), computedInvDiag.size());
for (size_t i = 0; i < expectedInvDiag.size(); ++i) {
BOOST_CHECK_CLOSE(expectedInvDiag[i], computedInvDiag[i], 1e-7);
}
}
BOOST_AUTO_TEST_CASE_TEMPLATE(FlattenAndInvertDiagonalWith2By2Blocks, T, NumericTypes)
{
const size_t blocksize = 2;
const size_t N = 2;
const int nonZeroes = 3;
using M = Dune::FieldMatrix;
using SpMatrix = Dune::BCRSMatrix;
/*
create this sparse matrix
| | 1 2| | 1 0| |
| |1/2 2| | 0 1| |
| |
| | 0 0| |-1 0| |
| | 0 0| | 0 -1| |
The diagonal elements inverted, and put in a vector should look like this
| | 2 - 2| |
| |-1/2 1| |
| |
| | -1 0| |
| | 0 -1| |
*/
SpMatrix B(N, N, nonZeroes, SpMatrix::row_wise);
for (auto row = B.createbegin(); row != B.createend(); ++row) {
row.insert(row.index());
if (row.index() == 0) {
row.insert(row.index() + 1);
}
}
B[0][0][0][0] = 1.0;
B[0][0][0][1] = 2.0;
B[0][0][1][0] = 1.0 / 2.0;
B[0][0][1][1] = 2.0;
B[0][1][0][0] = 1.0;
B[0][1][1][1] = 1.0;
B[1][1][0][0] = -1.0;
B[1][1][1][1] = -1.0;
Opm::gpuistl::GpuSparseMatrix m = Opm::gpuistl::GpuSparseMatrix::fromMatrix(B);
Opm::gpuistl::GpuVector dInvDiag(blocksize * blocksize * N);
Opm::gpuistl::detail::JAC::invertDiagonalAndFlatten(
m.getNonZeroValues().data(), m.getRowIndices().data(), m.getColumnIndices().data(), N, dInvDiag.data());
std::vector expectedInvDiag {2.0, -2.0, -1.0 / 2.0, 1.0, -1.0, 0.0, 0.0, -1.0};
std::vector computedInvDiag = dInvDiag.asStdVector();
BOOST_REQUIRE_EQUAL(expectedInvDiag.size(), computedInvDiag.size());
for (size_t i = 0; i < expectedInvDiag.size(); ++i) {
BOOST_CHECK_CLOSE(expectedInvDiag[i], computedInvDiag[i], 1e-7);
}
}