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Add trunc cuda testing
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@ -38,3 +38,5 @@ run test_cbrt_double.cu ;
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run test_cbrt_float.cu ;
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run test_changesign_double.cu ;
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run test_changesign_float.cu ;
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run test_trunc_double.cu ;
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run test_trunc_float.cu ;
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97
test/test_trunc_double.cu
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97
test/test_trunc_double.cu
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@ -0,0 +1,97 @@
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// Copyright John Maddock 2016.
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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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#include <iostream>
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#include <iomanip>
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#include <vector>
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#include <boost/math/special_functions/trunc.hpp>
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#include <boost/math/special_functions/relative_difference.hpp>
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#include "cuda_managed_ptr.hpp"
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#include "stopwatch.hpp"
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// For the CUDA runtime routines (prefixed with "cuda_")
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#include <cuda_runtime.h>
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typedef double float_type;
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/**
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* CUDA Kernel Device code
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*
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*/
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__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
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{
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using std::cos;
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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::trunc(in[i]) + boost::math::itrunc(in[i]) + boost::math::ltrunc(in[i]) + boost::math::lltrunc(in[i]);
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}
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}
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/**
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* Host main routine
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*/
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int main(void)
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{
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// Error code to check return values for CUDA calls
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cudaError_t err = cudaSuccess;
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// Print the vector length to be used, and compute its size
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int numElements = 50000;
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std::cout << "[Vector addition of " << numElements << " elements]" << std::endl;
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// Allocate the managed input vector A
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cuda_managed_ptr<float_type> h_A(numElements);
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// Allocate the managed output vector C
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cuda_managed_ptr<float_type> h_C(numElements);
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// Initialize the input vectors
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for (int i = 0; i < numElements; ++i)
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{
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h_A[i] = rand()/(float_type)RAND_MAX;
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}
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// Launch the Vector Add CUDA Kernel
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int threadsPerBlock = 1024;
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int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
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std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
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watch w;
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cuda_test<<<blocksPerGrid, threadsPerBlock>>>(h_A.get(), h_C.get(), numElements);
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cudaDeviceSynchronize();
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std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
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err = cudaGetLastError();
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if (err != cudaSuccess)
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{
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std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
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return EXIT_FAILURE;
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}
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// Verify that the result vector is correct
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std::vector<float_type> results;
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results.reserve(numElements);
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w.reset();
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for(int i = 0; i < numElements; ++i)
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results.push_back(4 * boost::math::trunc(h_A[i]));
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double t = w.elapsed();
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// check the results
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for(int i = 0; i < numElements; ++i)
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{
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if (boost::math::epsilon_difference(h_C[i], results[i]) > 10)
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{
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std::cerr << "Result verification failed at element " << i << "!" << std::endl;
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return EXIT_FAILURE;
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}
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}
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std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
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std::cout << "Done\n";
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return 0;
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}
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97
test/test_trunc_float.cu
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97
test/test_trunc_float.cu
Normal file
@ -0,0 +1,97 @@
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// Copyright John Maddock 2016.
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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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#include <iostream>
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#include <iomanip>
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#include <vector>
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#include <boost/math/special_functions/trunc.hpp>
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#include <boost/math/special_functions/relative_difference.hpp>
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#include "cuda_managed_ptr.hpp"
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#include "stopwatch.hpp"
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// For the CUDA runtime routines (prefixed with "cuda_")
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#include <cuda_runtime.h>
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typedef float float_type;
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/**
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* CUDA Kernel Device code
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*
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*/
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__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
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{
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using std::cos;
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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::trunc(in[i]) + boost::math::itrunc(in[i]) + boost::math::ltrunc(in[i]) + boost::math::lltrunc(in[i]);
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}
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}
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/**
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* Host main routine
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*/
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int main(void)
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{
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// Error code to check return values for CUDA calls
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cudaError_t err = cudaSuccess;
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// Print the vector length to be used, and compute its size
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int numElements = 50000;
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std::cout << "[Vector addition of " << numElements << " elements]" << std::endl;
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// Allocate the managed input vector A
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cuda_managed_ptr<float_type> h_A(numElements);
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// Allocate the managed output vector C
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cuda_managed_ptr<float_type> h_C(numElements);
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// Initialize the input vectors
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for (int i = 0; i < numElements; ++i)
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{
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h_A[i] = rand()/(float_type)RAND_MAX;
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}
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// Launch the Vector Add CUDA Kernel
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int threadsPerBlock = 1024;
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int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
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std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
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watch w;
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cuda_test<<<blocksPerGrid, threadsPerBlock>>>(h_A.get(), h_C.get(), numElements);
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cudaDeviceSynchronize();
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std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
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err = cudaGetLastError();
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if (err != cudaSuccess)
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{
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std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
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return EXIT_FAILURE;
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}
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// Verify that the result vector is correct
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std::vector<float_type> results;
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results.reserve(numElements);
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w.reset();
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for(int i = 0; i < numElements; ++i)
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results.push_back(4 * boost::math::trunc(h_A[i]));
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double t = w.elapsed();
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// check the results
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for(int i = 0; i < numElements; ++i)
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{
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if (boost::math::epsilon_difference(h_C[i], results[i]) > 10)
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{
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std::cerr << "Result verification failed at element " << i << "!" << std::endl;
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return EXIT_FAILURE;
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}
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}
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std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
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std::cout << "Done\n";
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return 0;
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}
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