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#include "gtest/gtest.h"
#include "src/storage/SparseMatrix.h"
#include "src/exceptions/InvalidStateException.h"
#include "src/exceptions/OutOfRangeException.h"
#include "storm-config.h"
#ifdef STORM_HAVE_CUDAFORSTORM
#include "cudaForStorm.h"
TEST(CudaPlugin, SpMV_4x4) { storm::storage::SparseMatrixBuilder<double> matrixBuilder(4, 4, 10); ASSERT_NO_THROW(matrixBuilder.addNextValue(0, 1, 1.0)); ASSERT_NO_THROW(matrixBuilder.addNextValue(0, 3, -1.0)); ASSERT_NO_THROW(matrixBuilder.addNextValue(1, 0, 8.0)); ASSERT_NO_THROW(matrixBuilder.addNextValue(1, 1, 7.0)); ASSERT_NO_THROW(matrixBuilder.addNextValue(1, 2, -5.0)); ASSERT_NO_THROW(matrixBuilder.addNextValue(1, 3, 2.0)); ASSERT_NO_THROW(matrixBuilder.addNextValue(2, 0, 2.0)); ASSERT_NO_THROW(matrixBuilder.addNextValue(2, 1, 2.0)); ASSERT_NO_THROW(matrixBuilder.addNextValue(2, 2, 4.0)); ASSERT_NO_THROW(matrixBuilder.addNextValue(2, 3, 4.0));
storm::storage::SparseMatrix<double> matrix; ASSERT_NO_THROW(matrix = matrixBuilder.build()); ASSERT_EQ(4, matrix.getRowCount()); ASSERT_EQ(4, matrix.getColumnCount()); ASSERT_EQ(10, matrix.getEntryCount());
std::vector<double> x({0, 4, 1, 1}); std::vector<double> b({0, 0, 0, 0});
ASSERT_NO_THROW(basicValueIteration_spmv_uint64_double(matrix.getColumnCount(), matrix.__internal_getRowIndications(), matrix.__internal_getColumnsAndValues(), x, b));
ASSERT_EQ(b.at(0), 3); ASSERT_EQ(b.at(1), 25); ASSERT_EQ(b.at(2), 16); ASSERT_EQ(b.at(3), 0); }
TEST(CudaPlugin, SpMV_VerySmall) { storm::storage::SparseMatrixBuilder<double> matrixBuilder(2, 2, 2); ASSERT_NO_THROW(matrixBuilder.addNextValue(0, 0, 1.0)); ASSERT_NO_THROW(matrixBuilder.addNextValue(1, 1, 2.0));
storm::storage::SparseMatrix<double> matrix; ASSERT_NO_THROW(matrix = matrixBuilder.build());
ASSERT_EQ(2, matrix.getRowCount()); ASSERT_EQ(2, matrix.getColumnCount()); ASSERT_EQ(2, matrix.getEntryCount());
std::vector<double> x({ 4.0, 8.0 }); std::vector<double> b({ 0.0, 0.0 });
ASSERT_NO_THROW(basicValueIteration_spmv_uint64_double(matrix.getColumnCount(), matrix.__internal_getRowIndications(), matrix.__internal_getColumnsAndValues(), x, b));
ASSERT_EQ(b.at(0), 4.0); ASSERT_EQ(b.at(1), 16.0); }
TEST(CudaPlugin, AddVectorsInplace) { std::vector<double> vectorA_1 = { 0.0, 42.0, 21.4, 3.1415, 1.0, 7.3490390, 94093053905390.21, -0.000000000023 }; std::vector<double> vectorA_2 = { 0.0, 42.0, 21.4, 3.1415, 1.0, 7.3490390, 94093053905390.21, -0.000000000023 }; std::vector<double> vectorA_3 = { 0.0, 42.0, 21.4, 3.1415, 1.0, 7.3490390, 94093053905390.21, -0.000000000023 }; std::vector<double> vectorB = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; std::vector<double> vectorC = { -5000.0, -5000.0, -5000.0, -5000.0, -5000.0, -5000.0, -5000.0, -5000.0 };
ASSERT_EQ(vectorA_1.size(), 8); ASSERT_EQ(vectorA_2.size(), 8); ASSERT_EQ(vectorA_3.size(), 8); ASSERT_EQ(vectorB.size(), 8); ASSERT_EQ(vectorC.size(), 8);
ASSERT_NO_THROW(basicValueIteration_addVectorsInplace_double(vectorA_1, vectorB)); ASSERT_NO_THROW(basicValueIteration_addVectorsInplace_double(vectorA_2, vectorC));
ASSERT_EQ(vectorA_1.size(), 8); ASSERT_EQ(vectorA_2.size(), 8); ASSERT_EQ(vectorA_3.size(), 8); ASSERT_EQ(vectorB.size(), 8); ASSERT_EQ(vectorC.size(), 8);
for (size_t i = 0; i < vectorA_3.size(); ++i) { double cpu_result_b = vectorA_3.at(i) + vectorB.at(i); double cpu_result_c = vectorA_3.at(i) + vectorC.at(i);
ASSERT_EQ(cpu_result_b, vectorA_1.at(i)); ASSERT_EQ(cpu_result_c, vectorA_2.at(i)); } }
TEST(CudaPlugin, ReduceGroupedVector) { std::vector<double> groupedVector = { 0.0, -1000.0, 0.000004, // Group 0
5.0, // Group 1
0.0, 1.0, 2.0, 3.0, // Group 2
-1000.0, -3.14, -0.0002,// Group 3 (neg only)
25.25, 25.25, 25.25, // Group 4
0.0, 0.0, 1.0, // Group 5
-0.000001, 0.000001 // Group 6
}; std::vector<uint_fast64_t> grouping = { 0, 3, 4, 8, 11, 14, 17, 19 };
std::vector<double> result_minimize = { -1000.0, // Group 0
5.0, 0.0, -1000.0, 25.25, 0.0, -0.000001 }; std::vector<double> result_maximize = { 0.000004, 5.0, 3.0, -0.0002, 25.25, 1.0, 0.000001 };
std::vector<double> result_cuda_minimize = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; std::vector<double> result_cuda_maximize = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
ASSERT_NO_THROW(basicValueIteration_reduceGroupedVector_uint64_double_minimize(groupedVector, grouping, result_cuda_minimize)); ASSERT_NO_THROW(basicValueIteration_reduceGroupedVector_uint64_double_maximize(groupedVector, grouping, result_cuda_maximize));
for (size_t i = 0; i < result_minimize.size(); ++i) { ASSERT_EQ(result_minimize.at(i), result_cuda_minimize.at(i)); ASSERT_EQ(result_maximize.at(i), result_cuda_maximize.at(i)); } }
TEST(CudaPlugin, equalModuloPrecision) { std::vector<double> x = { 123.45L, 67.8L, 901.23L, 456789.012L, 3.456789L, -4567890.12L }; std::vector<double> y1 = { 0.45L, 0.8L, 0.23L, 0.012L, 0.456789L, -0.12L }; std::vector<double> y2 = { 0.45L, 0.8L, 0.23L, 456789.012L, 0.456789L, -4567890.12L }; std::vector<double> x2; std::vector<double> x3; std::vector<double> y3; std::vector<double> y4; x2.reserve(1000); x3.reserve(1000); y3.reserve(1000); y4.reserve(1000); for (size_t i = 0; i < 1000; ++i) { x2.push_back(static_cast<double>(i)); y3.push_back(1.0); x3.push_back(-(1000.0 - static_cast<double>(i))); y4.push_back(1.0); }
double maxElement1 = 0.0L; double maxElement2 = 0.0L; double maxElement3 = 0.0L; double maxElement4 = 0.0L; ASSERT_NO_THROW(basicValueIteration_equalModuloPrecision_double_NonRelative(x, y1, maxElement1)); ASSERT_NO_THROW(basicValueIteration_equalModuloPrecision_double_NonRelative(x, y2, maxElement2));
ASSERT_NO_THROW(basicValueIteration_equalModuloPrecision_double_Relative(x2, y3, maxElement3)); ASSERT_NO_THROW(basicValueIteration_equalModuloPrecision_double_Relative(x3, y4, maxElement4));
ASSERT_DOUBLE_EQ(4567890.0L, maxElement1); ASSERT_DOUBLE_EQ(901.0L, maxElement2);
ASSERT_DOUBLE_EQ(998.0L, maxElement3); ASSERT_DOUBLE_EQ(1001.0L, maxElement4); }
#endif
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