opm-simulators/tests/gpuistl/test_cuSparse_matrix_operations.cpp

/*
  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 <http://www.gnu.org/licenses/>.
*/
#include <config.h>

#define BOOST_TEST_MODULE TestGpuSparseMatrixOperations
#include <boost/mpl/list.hpp>
#include <boost/test/unit_test.hpp>
#include <cuda_runtime.h>
#include <dune/istl/bcrsmatrix.hh>
#include <opm/simulators/linalg/gpuistl/GpuSparseMatrix.hpp>
#include <opm/simulators/linalg/gpuistl/GpuVector.hpp>
#include <opm/simulators/linalg/gpuistl/PreconditionerAdapter.hpp>
#include <opm/simulators/linalg/gpuistl/detail/cusparse_matrix_operations.hpp>
#include <opm/simulators/linalg/gpuistl/detail/fix_zero_diagonal.hpp>
#include <opm/simulators/linalg/gpuistl/detail/preconditionerKernels/JacKernels.hpp>

using NumericTypes = boost::mpl::list<double, float>;

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<T, blocksize, blocksize>;
    using SpMatrix = Dune::BCRSMatrix<M>;
    /*
        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<T> m = Opm::gpuistl::GpuSparseMatrix<T>::fromMatrix(B);
    Opm::gpuistl::GpuVector<T> dInvDiag(blocksize * blocksize * N);

    Opm::gpuistl::detail::JAC::invertDiagonalAndFlatten<T, 3>(
        m.getNonZeroValues().data(), m.getRowIndices().data(), m.getColumnIndices().data(), N, dInvDiag.data());

    std::vector<T> 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<T> 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<T, blocksize, blocksize>;
    using SpMatrix = Dune::BCRSMatrix<M>;
    /*
        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<T> m = Opm::gpuistl::GpuSparseMatrix<T>::fromMatrix(B);
    Opm::gpuistl::GpuVector<T> dInvDiag(blocksize * blocksize * N);

    Opm::gpuistl::detail::JAC::invertDiagonalAndFlatten<T, 2>(
        m.getNonZeroValues().data(), m.getRowIndices().data(), m.getColumnIndices().data(), N, dInvDiag.data());

    std::vector<T> expectedInvDiag {2.0, -2.0, -1.0 / 2.0, 1.0, -1.0, 0.0, 0.0, -1.0};
    std::vector<T> 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);
    }
}