/*
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 TestGpuVector
#include
#include
#include
#include
#include
#include
#include
BOOST_AUTO_TEST_CASE(TestDocumentedUsage)
{
auto someDataOnCPU = std::vector({1.0, 2.0, 42.0, 59.9451743, 10.7132692});
auto dataOnGPU = ::Opm::gpuistl::GpuVector(someDataOnCPU);
// Multiply by 4.0:
dataOnGPU *= 4.0;
// Get data back on CPU in another vector:
auto stdVectorOnCPU = dataOnGPU.asStdVector();
std::vector correctVector(someDataOnCPU.size());
std::transform(someDataOnCPU.begin(), someDataOnCPU.end(), correctVector.begin(), [](double x) { return 4 * x; });
BOOST_CHECK_EQUAL_COLLECTIONS(
stdVectorOnCPU.begin(), stdVectorOnCPU.end(), correctVector.begin(), correctVector.end());
}
BOOST_AUTO_TEST_CASE(TestConstructionSize)
{
const int numberOfElements = 1234;
auto vectorOnGPU = Opm::gpuistl::GpuVector(numberOfElements);
BOOST_CHECK_EQUAL(numberOfElements, vectorOnGPU.dim());
}
BOOST_AUTO_TEST_CASE(TestCopyFromHostConstructor)
{
std::vector data {{1, 2, 3, 4, 5, 6, 7}};
auto vectorOnGPU = Opm::gpuistl::GpuVector(data.data(), data.size());
BOOST_CHECK_EQUAL(data.size(), vectorOnGPU.dim());
std::vector buffer(data.size(), 0.0);
vectorOnGPU.copyToHost(buffer.data(), buffer.size());
BOOST_CHECK_EQUAL_COLLECTIONS(buffer.begin(), buffer.end(), data.begin(), data.end());
}
BOOST_AUTO_TEST_CASE(TestCopyFromHostFunction)
{
std::vector data {{1, 2, 3, 4, 5, 6, 7}};
auto vectorOnGPU = Opm::gpuistl::GpuVector(data.size());
BOOST_CHECK_EQUAL(data.size(), vectorOnGPU.dim());
vectorOnGPU.copyFromHost(data.data(), data.size());
std::vector buffer(data.size(), 0.0);
vectorOnGPU.copyToHost(buffer.data(), buffer.size());
BOOST_CHECK_EQUAL_COLLECTIONS(buffer.begin(), buffer.end(), data.begin(), data.end());
}
BOOST_AUTO_TEST_CASE(TestCopyFromBvector)
{
auto blockVector = Dune::BlockVector> {{{42, 43}, {44, 45}, {46, 47}}};
auto vectorOnGPU = Opm::gpuistl::GpuVector(blockVector.dim());
vectorOnGPU.copyFromHost(blockVector);
std::vector buffer(vectorOnGPU.dim());
vectorOnGPU.copyToHost(buffer.data(), buffer.size());
BOOST_CHECK_EQUAL_COLLECTIONS(
buffer.begin(), buffer.end(), &blockVector[0][0], &blockVector[0][0] + blockVector.dim());
}
BOOST_AUTO_TEST_CASE(TestCopyToBvector)
{
std::vector data {{1, 2, 3, 4, 5, 6, 7, 8, 9}};
auto blockVector = Dune::BlockVector>(3);
auto vectorOnGPU = Opm::gpuistl::GpuVector(data.data(), data.size());
vectorOnGPU.copyToHost(blockVector);
BOOST_CHECK_EQUAL_COLLECTIONS(data.begin(), data.end(), &blockVector[0][0], &blockVector[0][0] + blockVector.dim());
}
BOOST_AUTO_TEST_CASE(TestDataPointer)
{
std::vector data {{1, 2, 3, 4, 5, 6, 7, 8, 9}};
auto vectorOnGPU = Opm::gpuistl::GpuVector(data.data(), data.size());
std::vector buffer(data.size(), 0.0);
OPM_GPU_SAFE_CALL(cudaMemcpy(buffer.data(), vectorOnGPU.data(), sizeof(double) * data.size(), cudaMemcpyDeviceToHost));
BOOST_CHECK_EQUAL_COLLECTIONS(data.begin(), data.end(), buffer.begin(), buffer.end());
}
BOOST_AUTO_TEST_CASE(TestCopyScalarMultiply)
{
std::vector data {{1, 2, 3, 4, 5, 6, 7}};
auto vectorOnGPU = Opm::gpuistl::GpuVector(data.data(), data.size());
BOOST_CHECK_EQUAL(data.size(), vectorOnGPU.dim());
const double scalar = 42.25;
vectorOnGPU *= scalar;
std::vector buffer(data.size(), 0.0);
vectorOnGPU.copyToHost(buffer.data(), buffer.size());
for (size_t i = 0; i < buffer.size(); ++i) {
BOOST_CHECK_EQUAL(buffer[i], scalar * data[i]);
}
}
BOOST_AUTO_TEST_CASE(TestTwoNorm)
{
std::vector data {{1, 2, 3, 4, 5, 6, 7}};
auto vectorOnGPU = Opm::gpuistl::GpuVector(data.data(), data.size());
auto twoNorm = vectorOnGPU.two_norm();
double correctAnswer = 0.0;
for (double d : data) {
correctAnswer += d * d;
}
correctAnswer = std::sqrt(correctAnswer);
BOOST_CHECK_EQUAL(correctAnswer, twoNorm);
}
BOOST_AUTO_TEST_CASE(TestDot)
{
std::vector dataA {{1, 2, 3, 4, 5, 6, 7}};
std::vector dataB {{8, 9, 10, 11, 12, 13, 14}};
auto vectorOnGPUA = Opm::gpuistl::GpuVector(dataA.data(), dataA.size());
auto vectorOnGPUB = Opm::gpuistl::GpuVector(dataB.data(), dataB.size());
auto dot = vectorOnGPUA.dot(vectorOnGPUB);
double correctAnswer = 0.0;
for (size_t i = 0; i < dataA.size(); ++i) {
correctAnswer += dataA[i] * dataB[i];
}
correctAnswer = correctAnswer;
BOOST_CHECK_EQUAL(correctAnswer, dot);
}
BOOST_AUTO_TEST_CASE(Assigment)
{
std::vector data {{1, 2, 3, 4, 5, 6, 7}};
auto vectorOnGPU = Opm::gpuistl::GpuVector(data.data(), data.size());
vectorOnGPU = 10.0;
vectorOnGPU.copyToHost(data.data(), data.size());
for (double x : data) {
BOOST_CHECK_EQUAL(10.0, x);
}
}
BOOST_AUTO_TEST_CASE(CopyAssignment)
{
std::vector data {{1, 2, 3, 4, 5, 6, 7}};
auto vectorOnGPU = Opm::gpuistl::GpuVector(data.data(), data.size());
vectorOnGPU.copyToHost(data.data(), data.size());
auto vectorOnGPUB = Opm::gpuistl::GpuVector(data.size());
vectorOnGPUB = 4.0;
vectorOnGPUB = vectorOnGPU;
std::vector output(data.size());
vectorOnGPUB.copyToHost(output.data(), output.size());
BOOST_CHECK_EQUAL_COLLECTIONS(output.begin(), output.end(), data.begin(), data.end());
}
BOOST_AUTO_TEST_CASE(RandomVectors)
{
using GVector = Opm::gpuistl::GpuVector;
std::srand(0);
std::mt19937 generator;
std::uniform_real_distribution distribution(-100.0, 100.0);
std::uniform_real_distribution distribution01(.0, 1.0);
const size_t N = 1000;
const size_t retries = 100;
for (size_t retry = 0; retry < retries; ++retry) {
std::vector a(N);
std::vector b(N);
for (size_t i = 0; i < N; ++i) {
a[i] = distribution(generator);
b[i] = distribution(generator);
}
auto aGPU = GVector(a);
auto bGPU = GVector(b);
aGPU += bGPU;
auto aOutputPlus = aGPU.asStdVector();
for (size_t i = 0; i < N; ++i) {
BOOST_CHECK_EQUAL(aOutputPlus[i], a[i] + b[i]);
}
aGPU = GVector(a);
aGPU -= bGPU;
auto aOutputMinus = aGPU.asStdVector();
for (size_t i = 0; i < N; ++i) {
BOOST_CHECK_EQUAL(aOutputMinus[i], a[i] - b[i]);
}
aGPU = GVector(a);
auto scalar = distribution(generator);
aGPU *= scalar;
auto aOutputScalar = aGPU.asStdVector();
for (size_t i = 0; i < N; ++i) {
BOOST_CHECK_EQUAL(aOutputScalar[i], scalar * a[i]);
}
aGPU = GVector(a);
aGPU.axpy(scalar, bGPU);
auto aOutputSaxypy = aGPU.asStdVector();
for (size_t i = 0; i < N; ++i) {
BOOST_CHECK_CLOSE(aOutputSaxypy[i], a[i] + scalar * b[i], 1e-10);
}
aGPU = GVector(a);
auto dotted = aGPU.dot(bGPU);
double correct = 0.0;
for (size_t i = 0; i < N; ++i) {
correct += a[i] * b[i];
}
BOOST_CHECK_CLOSE(dotted, correct, 1e-10);
aGPU = GVector(a);
auto twoNorm = aGPU.two_norm();
double correctTwoNorm = 0.0;
for (size_t i = 0; i < N; ++i) {
correctTwoNorm += a[i] * a[i];
}
correctTwoNorm = std::sqrt(correctTwoNorm);
BOOST_CHECK_CLOSE(twoNorm, correctTwoNorm, 1e-12);
aGPU = GVector(a);
std::vector indexSet;
const double rejectCriteria = 0.2;
for (size_t i = 0; i < N; ++i) {
const auto reject = distribution01(generator);
if (reject < rejectCriteria) {
indexSet.push_back(i);
}
}
auto indexSetGPU = Opm::gpuistl::GpuVector(indexSet);
aGPU.setZeroAtIndexSet(indexSetGPU);
auto projectedA = aGPU.asStdVector();
for (size_t i = 0; i < N; ++i) {
// Yeah, O(N^2) so sue me
bool found = std::find(indexSet.begin(), indexSet.end(), i) != indexSet.end();
if (found) {
BOOST_CHECK_EQUAL(projectedA[i], 0);
} else {
BOOST_CHECK_EQUAL(projectedA[i], a[i]);
}
}
aGPU = GVector(a);
auto twoNormAtIndices = aGPU.two_norm(indexSetGPU);
double correctTwoNormAtIndices = 0.0;
for (size_t i = 0; i < indexSet.size(); ++i) {
correctTwoNormAtIndices += a[indexSet[i]] * a[indexSet[i]];
}
correctTwoNormAtIndices = std::sqrt(correctTwoNormAtIndices);
BOOST_CHECK_CLOSE(correctTwoNormAtIndices, twoNormAtIndices, 1e-13);
}
}