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Add SYCL testing of expint Add markers to forward decls Add CUDA testing of expint Fix static variable usage under NVRTC Add NVRTC testing Add configurable definition of complex Add function aliases Add GPU support to gegenbauer polynomials Add SYCL testing of gegenbauer Add NVCC testing of gegenbauer Add NVRTC testing of gegenbauer Add GPU support for hankel Add SYCL testing of hankel Add NVCC testing of cyl_hankel_1 Add comprehensive NVCC testing Add NVRTC testing of cyl and sph hankel Update docs Fix writing cuda::std::complex<T> to stdout Add GPU support to hermite Add SYCL testing of hermite Add CUDA testing of hermite Add NVRTC testing of hermite Add markers to hermite docs
200 lines
6.9 KiB
C++
200 lines
6.9 KiB
C++
// Copyright John Maddock 2016.
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// Copyright Matt Borland 2024.
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// Use, modification and distribution are subject to the
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// Boost Software License, Version 1.0. (See accompanying file
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// LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
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#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
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#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
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// Must be included first
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#include <nvrtc.h>
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#include <cuda.h>
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#include <cuda_runtime.h>
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#include <iostream>
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#include <iomanip>
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#include <vector>
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#include <random>
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#include <exception>
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#include <boost/math/tools/complex.hpp>
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#include <boost/math/special_functions/hankel.hpp>
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#include <boost/math/special_functions/relative_difference.hpp>
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typedef float float_type;
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const char* cuda_kernel = R"(
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typedef float float_type;
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#include <cuda/std/type_traits>
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#include <boost/math/special_functions/hankel.hpp>
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extern "C" __global__
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void test_cyl_hankel_2_kernel(const float_type *in1, const float_type* in2, boost::math::complex<float_type> *out, int numElements)
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{
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int i = blockDim.x * blockIdx.x + threadIdx.x;
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if (i < numElements)
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{
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out[i] = boost::math::cyl_hankel_2(in1[i], in2[i]);
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}
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}
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)";
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void checkCUDAError(cudaError_t result, const char* msg)
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{
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if (result != cudaSuccess)
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{
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std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
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exit(EXIT_FAILURE);
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}
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}
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void checkCUError(CUresult result, const char* msg)
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{
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if (result != CUDA_SUCCESS)
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{
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const char* errorStr;
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cuGetErrorString(result, &errorStr);
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std::cerr << msg << ": " << errorStr << std::endl;
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exit(EXIT_FAILURE);
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}
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}
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void checkNVRTCError(nvrtcResult result, const char* msg)
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{
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if (result != NVRTC_SUCCESS)
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{
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std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
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exit(EXIT_FAILURE);
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}
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}
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int main()
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{
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try
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{
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// Initialize CUDA driver API
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checkCUError(cuInit(0), "Failed to initialize CUDA");
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// Create CUDA context
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CUcontext context;
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CUdevice device;
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checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
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checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
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nvrtcProgram prog;
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nvrtcResult res;
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res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_hankel_2_kernel.cu", 0, nullptr, nullptr);
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checkNVRTCError(res, "Failed to create NVRTC program");
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nvrtcAddNameExpression(prog, "test_cyl_hankel_2_kernel");
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#ifdef BOOST_MATH_NVRTC_CI_RUN
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const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
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#else
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const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
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#endif
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// Compile the program
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res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
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if (res != NVRTC_SUCCESS)
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{
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size_t log_size;
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nvrtcGetProgramLogSize(prog, &log_size);
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char* log = new char[log_size];
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nvrtcGetProgramLog(prog, log);
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std::cerr << "Compilation failed:\n" << log << std::endl;
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delete[] log;
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exit(EXIT_FAILURE);
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}
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// Get PTX from the program
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size_t ptx_size;
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nvrtcGetPTXSize(prog, &ptx_size);
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char* ptx = new char[ptx_size];
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nvrtcGetPTX(prog, ptx);
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// Load PTX into CUDA module
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CUmodule module;
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CUfunction kernel;
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checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
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checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_hankel_2_kernel"), "Failed to get kernel function");
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int numElements = 5000;
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float_type *h_in1, *h_in2;
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float_type *d_in1, *d_in2;
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boost::math::complex<float_type> *h_out, *d_out;
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// Allocate memory on the host
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h_in1 = new float_type[numElements];
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h_in2 = new float_type[numElements];
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h_out = new boost::math::complex<float_type>[numElements];
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// Initialize input arrays
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std::mt19937_64 rng(42);
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std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
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for (int i = 0; i < numElements; ++i)
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{
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h_in1[i] = static_cast<float_type>(dist(rng));
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h_in2[i] = static_cast<float_type>(dist(rng));
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}
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checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
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checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
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checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(boost::math::complex<float_type>)), "Failed to allocate device memory for d_out");
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checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
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checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
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int blockSize = 256;
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int numBlocks = (numElements + blockSize - 1) / blockSize;
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void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
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checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
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checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(boost::math::complex<float_type>), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
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// Verify Result
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int fail_counter = 0;
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for (int i = 0; i < numElements; ++i)
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{
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const auto res = boost::math::cyl_hankel_2(h_in1[i], h_in2[i]);
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if (boost::math::epsilon_difference(res.real(), h_out[i].real()) > 300)
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{
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std::cout << "error at line: " << i
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<< "\nParallel: " << h_out[i].real() << ", " << h_out[i].imag()
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<< "\n Serial: " << res.real() << ", " << res.imag()
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<< "\n Dist: " << boost::math::epsilon_difference(res.real(), h_out[i].real()) << std::endl;
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++fail_counter;
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if (fail_counter > 100)
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{
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break;
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}
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}
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}
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cudaFree(d_in1);
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cudaFree(d_in2);
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cudaFree(d_out);
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delete[] h_in1;
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delete[] h_in2;
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delete[] h_out;
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nvrtcDestroyProgram(&prog);
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delete[] ptx;
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cuCtxDestroy(context);
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if (fail_counter > 0)
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{
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return 1;
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}
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std::cout << "Kernel executed successfully." << std::endl;
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return 0;
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}
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catch(const std::exception& e)
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{
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std::cerr << "Stopped with exception: " << e.what() << std::endl;
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return EXIT_FAILURE;
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}
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}
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