#include "basicValueIteration.h" #include <iostream> #include <chrono> #include <cuda_runtime.h> #include "cusparse_v2.h" #include "cuspExtension.h" __global__ void cuda_kernel_basicValueIteration_mvReduce(int const * const A, int * const B) { *B = *A; } template <typename IndexType, typename ValueType> void basicValueIteration_mvReduce(uint_fast64_t const maxIterationCount, std::vector<IndexType> const& matrixRowIndices, std::vector<std::pair<IndexType, ValueType>> columnIndicesAndValues, std::vector<ValueType>& x, std::vector<ValueType> const& b, std::vector<IndexType> const& nondeterministicChoiceIndices) { IndexType* device_matrixRowIndices = nullptr; IndexType* device_matrixColIndicesAndValues = nullptr; ValueType* device_x = nullptr; ValueType* device_b = nullptr; ValueType* device_multiplyResult = nullptr; IndexType* device_nondeterministicChoiceIndices = nullptr; cudaError_t cudaMallocResult; cudaMallocResult = cudaMalloc<IndexType>(&device_matrixRowIndices, matrixRowIndices.size()); if (cudaMallocResult != cudaSuccess) { std::cout << "Could not allocate memory for Matrix Row Indices, Error Code " << cudaMallocResult << "." << std::endl; goto cleanup; } cudaMallocResult = cudaMalloc<IndexType>(&device_matrixColIndicesAndValues, columnIndicesAndValues.size() * 2); if (cudaMallocResult != cudaSuccess) { std::cout << "Could not allocate memory for Matrix Column Indices and Values, Error Code " << cudaMallocResult << "." << std::endl; goto cleanup; } cudaMallocResult = cudaMalloc<ValueType>(&device_x, x.size()); if (cudaMallocResult != cudaSuccess) { std::cout << "Could not allocate memory for Vector x, Error Code " << cudaMallocResult << "." << std::endl; goto cleanup; } cudaMallocResult = cudaMalloc<ValueType>(&device_b, b.size()); if (cudaMallocResult != cudaSuccess) { std::cout << "Could not allocate memory for Vector b, Error Code " << cudaMallocResult << "." << std::endl; goto cleanup; } cudaMallocResult = cudaMalloc<ValueType>(&device_multiplyResult, b.size()); if (cudaMallocResult != cudaSuccess) { std::cout << "Could not allocate memory for Vector multiplyResult, Error Code " << cudaMallocResult << "." << std::endl; goto cleanup; } cudaMallocResult = cudaMalloc<IndexType>(&device_nondeterministicChoiceIndices, nondeterministicChoiceIndices.size()); if (cudaMallocResult != cudaSuccess) { std::cout << "Could not allocate memory for Nondeterministic Choice Indices, Error Code " << cudaMallocResult << "." << std::endl; goto cleanup; } // Memory allocated, copy data to device cudaError_t cudaCopyResult; cudaCopyResult = cudaMemcpy(device_matrixRowIndices, matrixRowIndices.data(), sizeof(IndexType) * matrixRowIndices.size(), cudaMemcpyHostToDevice); if (cudaCopyResult != cudaSuccess) { std::cout << "Could not copy data for Matrix Row Indices, Error Code " << cudaCopyResult << std::endl; goto cleanup; } cudaCopyResult = cudaMemcpy(device_matrixColIndicesAndValues, columnIndicesAndValues.data(), (sizeof(IndexType) * columnIndicesAndValues.size()) + (sizeof(ValueType) * columnIndicesAndValues.size()), cudaMemcpyHostToDevice); if (cudaCopyResult != cudaSuccess) { std::cout << "Could not copy data for Matrix Column Indices and Values, Error Code " << cudaCopyResult << std::endl; goto cleanup; } cudaCopyResult = cudaMemcpy(device_x, x.data(), sizeof(ValueType) * x.size(), cudaMemcpyHostToDevice); if (cudaCopyResult != cudaSuccess) { std::cout << "Could not copy data for Vector x, Error Code " << cudaCopyResult << std::endl; goto cleanup; } cudaCopyResult = cudaMemcpy(device_b, b.data(), sizeof(ValueType) * b.size(), cudaMemcpyHostToDevice); if (cudaCopyResult != cudaSuccess) { std::cout << "Could not copy data for Vector b, Error Code " << cudaCopyResult << std::endl; goto cleanup; } cudaCopyResult = cudaMemcpy(device_nondeterministicChoiceIndices, nondeterministicChoiceIndices.data(), sizeof(IndexType) * nondeterministicChoiceIndices.size(), cudaMemcpyHostToDevice); if (cudaCopyResult != cudaSuccess) { std::cout << "Could not copy data for Vector b, Error Code " << cudaCopyResult << std::endl; goto cleanup; } // Data is on device, start Kernel // All code related to freeing memory and clearing up the device cleanup: if (device_matrixRowIndices != nullptr) { cudaError_t cudaFreeResult = cudaFree(device_matrixRowIndices); if (cudaFreeResult != cudaSuccess) { std::cout << "Could not free Memory of Matrix Row Indices, Error Code " << cudaFreeResult << "." << std::endl; } device_matrixRowIndices = nullptr; } if (device_matrixColIndicesAndValues != nullptr) { cudaError_t cudaFreeResult = cudaFree(device_matrixColIndicesAndValues); if (cudaFreeResult != cudaSuccess) { std::cout << "Could not free Memory of Matrix Column Indices and Values, Error Code " << cudaFreeResult << "." << std::endl; } device_matrixColIndicesAndValues = nullptr; } if (device_x != nullptr) { cudaError_t cudaFreeResult = cudaFree(device_x); if (cudaFreeResult != cudaSuccess) { std::cout << "Could not free Memory of Vector x, Error Code " << cudaFreeResult << "." << std::endl; } device_x = nullptr; } if (device_b != nullptr) { cudaError_t cudaFreeResult = cudaFree(device_b); if (cudaFreeResult != cudaSuccess) { std::cout << "Could not free Memory of Vector b, Error Code " << cudaFreeResult << "." << std::endl; } device_b = nullptr; } if (device_multiplyResult != nullptr) { cudaError_t cudaFreeResult = cudaFree(device_multiplyResult); if (cudaFreeResult != cudaSuccess) { std::cout << "Could not free Memory of Vector multiplyResult, Error Code " << cudaFreeResult << "." << std::endl; } device_multiplyResult = nullptr; } if (device_nondeterministicChoiceIndices != nullptr) { cudaError_t cudaFreeResult = cudaFree(device_nondeterministicChoiceIndices); if (cudaFreeResult != cudaSuccess) { std::cout << "Could not free Memory of Nondeterministic Choice Indices, Error Code " << cudaFreeResult << "." << std::endl; } device_nondeterministicChoiceIndices = nullptr; } } /* * Declare and implement all exported functions for these Kernels here * */ void cudaForStormTestFunction(int a, int b) { std::cout << "Cuda for Storm: a + b = " << (a+b) << std::endl; } void basicValueIteration_mvReduce_uint64_double(uint_fast64_t const maxIterationCount, std::vector<uint_fast64_t> const& matrixRowIndices, std::vector<std::pair<uint_fast64_t, double>> columnIndicesAndValues, std::vector<double>& x, std::vector<double> const& b, std::vector<uint_fast64_t> const& nondeterministicChoiceIndices) { basicValueIteration_mvReduce<uint_fast64_t, double>(maxIterationCount, matrixRowIndices, columnIndicesAndValues, x, b, nondeterministicChoiceIndices); }