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Add saspoint5 NVRTC testing
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mborland committed Aug 15, 2024
1 parent a9cf968 commit 42ccc22
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7 changes: 7 additions & 0 deletions test/nvrtc_jamfile
Original file line number Diff line number Diff line change
Expand Up @@ -80,6 +80,13 @@ run test_mapairy_pdf_nvrtc_float.cpp ;
run test_mapairy_quan_nvrtc_double.cpp ;
run test_mapairy_quan_nvrtc_float.cpp ;

run test_saspoint5_cdf_nvrtc_double.cpp ;
run test_saspoint5_cdf_nvrtc_float.cpp ;
run test_saspoint5_pdf_nvrtc_double.cpp ;
run test_saspoint5_pdf_nvrtc_float.cpp ;
run test_saspoint5_quan_nvrtc_double.cpp ;
run test_saspoint5_quan_nvrtc_float.cpp ;

# Special Functions
run test_cbrt_nvrtc_double.cpp ;
run test_cbrt_nvrtc_float.cpp ;
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191 changes: 191 additions & 0 deletions test/test_saspoint5_cdf_nvrtc_double.cpp
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// Copyright John Maddock 2016.
// Copyright Matt Borland 2024.
// Use, modification and distribution are subject to the
// Boost Software License, Version 1.0. (See accompanying file
// LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)

#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false

// Must be included first
#include <nvrtc.h>
#include <cuda.h>
#include <cuda_runtime.h>

#include <iostream>
#include <iomanip>
#include <vector>
#include <random>
#include <exception>
#include <boost/math/distributions/saspoint5.hpp>
#include <boost/math/special_functions/fpclassify.hpp>
#include <boost/math/special_functions/relative_difference.hpp>

typedef double float_type;

const char* cuda_kernel = R"(
typedef double float_type;
#include <cuda/std/type_traits>
#include <boost/math/distributions/saspoint5.hpp>
extern "C" __global__
void test_saspoint5_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < numElements)
{
out[i] = cdf(boost::math::saspoint5_distribution<float_type>(), in1[i]);
}
}
)";

void checkCUDAError(cudaError_t result, const char* msg)
{
if (result != cudaSuccess)
{
std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
exit(EXIT_FAILURE);
}
}

void checkCUError(CUresult result, const char* msg)
{
if (result != CUDA_SUCCESS)
{
const char* errorStr;
cuGetErrorString(result, &errorStr);
std::cerr << msg << ": " << errorStr << std::endl;
exit(EXIT_FAILURE);
}
}

void checkNVRTCError(nvrtcResult result, const char* msg)
{
if (result != NVRTC_SUCCESS)
{
std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
exit(EXIT_FAILURE);
}
}

int main()
{
try
{
// Initialize CUDA driver API
checkCUError(cuInit(0), "Failed to initialize CUDA");

// Create CUDA context
CUcontext context;
CUdevice device;
checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");

nvrtcProgram prog;
nvrtcResult res;

res = nvrtcCreateProgram(&prog, cuda_kernel, "test_saspoint5_kernel.cu", 0, nullptr, nullptr);
checkNVRTCError(res, "Failed to create NVRTC program");

nvrtcAddNameExpression(prog, "test_saspoint5_kernel");

#ifdef BOOST_MATH_NVRTC_CI_RUN
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"};
#else
const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
#endif

// Compile the program
res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
if (res != NVRTC_SUCCESS)
{
size_t log_size;
nvrtcGetProgramLogSize(prog, &log_size);
char* log = new char[log_size];
nvrtcGetProgramLog(prog, log);
std::cerr << "Compilation failed:\n" << log << std::endl;
delete[] log;
exit(EXIT_FAILURE);
}

// Get PTX from the program
size_t ptx_size;
nvrtcGetPTXSize(prog, &ptx_size);
char* ptx = new char[ptx_size];
nvrtcGetPTX(prog, ptx);

// Load PTX into CUDA module
CUmodule module;
CUfunction kernel;
checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
checkCUError(cuModuleGetFunction(&kernel, module, "test_saspoint5_kernel"), "Failed to get kernel function");

int numElements = 5000;
float_type *h_in1, *h_in2, *h_out;
float_type *d_in1, *d_in2, *d_out;

// Allocate memory on the host
h_in1 = new float_type[numElements];
h_in2 = new float_type[numElements];
h_out = new float_type[numElements];

// Initialize input arrays
std::mt19937_64 rng(42);
std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
for (int i = 0; i < numElements; ++i)
{
h_in1[i] = static_cast<float_type>(dist(rng));
h_in2[i] = static_cast<float_type>(dist(rng));
}

checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");

checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");

int blockSize = 256;
int numBlocks = (numElements + blockSize - 1) / blockSize;
void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");

checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");

// Verify Result
for (int i = 0; i < numElements; ++i)
{
auto res = cdf(boost::math::saspoint5_distribution<float_type>(), h_in1[i]);

if (boost::math::isfinite(res))
{
if (boost::math::epsilon_difference(res, h_out[i]) > 300)
{
std::cout << "error at line: " << i
<< "\nParallel: " << h_out[i]
<< "\n Serial: " << res
<< "\n Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
}
}
}

cudaFree(d_in1);
cudaFree(d_in2);
cudaFree(d_out);
delete[] h_in1;
delete[] h_in2;
delete[] h_out;

nvrtcDestroyProgram(&prog);
delete[] ptx;

cuCtxDestroy(context);

std::cout << "Kernel executed successfully." << std::endl;
return 0;
}
catch(const std::exception& e)
{
std::cerr << "Stopped with exception: " << e.what() << std::endl;
return EXIT_FAILURE;
}
}
191 changes: 191 additions & 0 deletions test/test_saspoint5_cdf_nvrtc_float.cpp
Original file line number Diff line number Diff line change
@@ -0,0 +1,191 @@
// Copyright John Maddock 2016.
// Copyright Matt Borland 2024.
// Use, modification and distribution are subject to the
// Boost Software License, Version 1.0. (See accompanying file
// LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)

#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false

// Must be included first
#include <nvrtc.h>
#include <cuda.h>
#include <cuda_runtime.h>

#include <iostream>
#include <iomanip>
#include <vector>
#include <random>
#include <exception>
#include <boost/math/distributions/saspoint5.hpp>
#include <boost/math/special_functions/fpclassify.hpp>
#include <boost/math/special_functions/relative_difference.hpp>

typedef float float_type;

const char* cuda_kernel = R"(
typedef float float_type;
#include <cuda/std/type_traits>
#include <boost/math/distributions/saspoint5.hpp>
extern "C" __global__
void test_saspoint5_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
{
int i = blockDim.x * blockIdx.x + threadIdx.x;
if (i < numElements)
{
out[i] = cdf(boost::math::saspoint5_distribution<float_type>(), in1[i]);
}
}
)";

void checkCUDAError(cudaError_t result, const char* msg)
{
if (result != cudaSuccess)
{
std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
exit(EXIT_FAILURE);
}
}

void checkCUError(CUresult result, const char* msg)
{
if (result != CUDA_SUCCESS)
{
const char* errorStr;
cuGetErrorString(result, &errorStr);
std::cerr << msg << ": " << errorStr << std::endl;
exit(EXIT_FAILURE);
}
}

void checkNVRTCError(nvrtcResult result, const char* msg)
{
if (result != NVRTC_SUCCESS)
{
std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
exit(EXIT_FAILURE);
}
}

int main()
{
try
{
// Initialize CUDA driver API
checkCUError(cuInit(0), "Failed to initialize CUDA");

// Create CUDA context
CUcontext context;
CUdevice device;
checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");

nvrtcProgram prog;
nvrtcResult res;

res = nvrtcCreateProgram(&prog, cuda_kernel, "test_saspoint5_kernel.cu", 0, nullptr, nullptr);
checkNVRTCError(res, "Failed to create NVRTC program");

nvrtcAddNameExpression(prog, "test_saspoint5_kernel");

#ifdef BOOST_MATH_NVRTC_CI_RUN
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"};
#else
const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
#endif

// Compile the program
res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
if (res != NVRTC_SUCCESS)
{
size_t log_size;
nvrtcGetProgramLogSize(prog, &log_size);
char* log = new char[log_size];
nvrtcGetProgramLog(prog, log);
std::cerr << "Compilation failed:\n" << log << std::endl;
delete[] log;
exit(EXIT_FAILURE);
}

// Get PTX from the program
size_t ptx_size;
nvrtcGetPTXSize(prog, &ptx_size);
char* ptx = new char[ptx_size];
nvrtcGetPTX(prog, ptx);

// Load PTX into CUDA module
CUmodule module;
CUfunction kernel;
checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
checkCUError(cuModuleGetFunction(&kernel, module, "test_saspoint5_kernel"), "Failed to get kernel function");

int numElements = 5000;
float_type *h_in1, *h_in2, *h_out;
float_type *d_in1, *d_in2, *d_out;

// Allocate memory on the host
h_in1 = new float_type[numElements];
h_in2 = new float_type[numElements];
h_out = new float_type[numElements];

// Initialize input arrays
std::mt19937_64 rng(42);
std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
for (int i = 0; i < numElements; ++i)
{
h_in1[i] = static_cast<float_type>(dist(rng));
h_in2[i] = static_cast<float_type>(dist(rng));
}

checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");

checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");

int blockSize = 256;
int numBlocks = (numElements + blockSize - 1) / blockSize;
void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");

checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");

// Verify Result
for (int i = 0; i < numElements; ++i)
{
auto res = cdf(boost::math::saspoint5_distribution<float_type>(), h_in1[i]);

if (boost::math::isfinite(res))
{
if (boost::math::epsilon_difference(res, h_out[i]) > 300)
{
std::cout << "error at line: " << i
<< "\nParallel: " << h_out[i]
<< "\n Serial: " << res
<< "\n Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
}
}
}

cudaFree(d_in1);
cudaFree(d_in2);
cudaFree(d_out);
delete[] h_in1;
delete[] h_in2;
delete[] h_out;

nvrtcDestroyProgram(&prog);
delete[] ptx;

cuCtxDestroy(context);

std::cout << "Kernel executed successfully." << std::endl;
return 0;
}
catch(const std::exception& e)
{
std::cerr << "Stopped with exception: " << e.what() << std::endl;
return EXIT_FAILURE;
}
}
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