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// This program demonstrates how to perform parallel sort with CUDA.
#include <taskflow/cuda/cudaflow.hpp>
#include <taskflow/cuda/algorithm/sort.hpp>
int main(int argc, char* argv[]) {
if(argc != 2) {
std::cerr << "usage: ./cuda_sort N\n";
std::exit(EXIT_FAILURE);
}
unsigned N = std::atoi(argv[1]);
// gpu data
auto d_keys = tf::cuda_malloc_shared<int>(N);
// cpu data
std::vector<int> h_keys(N);
for(unsigned i=0; i<N; i++) {
int k = rand() % 10000;
d_keys[i] = k;
h_keys[i] = k;
}
// --------------------------------------------------------------------------
// Standard GPU sort
// --------------------------------------------------------------------------
auto p = tf::cudaDefaultExecutionPolicy{};
auto beg = std::chrono::steady_clock::now();
tf::cudaStream s;
auto bufsz = tf::cuda_sort_buffer_size<decltype(p), int>(N);
tf::cudaDeviceVector<std::byte> buf(bufsz);
tf::cuda_sort(p, d_keys, d_keys+N, tf::cuda_less<int>{}, buf.data());
s.synchronize();
auto end = std::chrono::steady_clock::now();
std::cout << "GPU sort: "
<< std::chrono::duration_cast<std::chrono::microseconds>(end-beg).count()
<< " us\n";
// --------------------------------------------------------------------------
// CPU sort
// --------------------------------------------------------------------------
beg = std::chrono::steady_clock::now();
std::sort(h_keys.begin(), h_keys.end());
end = std::chrono::steady_clock::now();
std::cout << "CPU sort: "
<< std::chrono::duration_cast<std::chrono::microseconds>(end-beg).count()
<< " us\n";
// --------------------------------------------------------------------------
// verify the result
// --------------------------------------------------------------------------
for(unsigned i=0; i<N; i++) {
if(d_keys[i] != h_keys[i]) {
throw std::runtime_error("incorrect result");
}
}
std::cout << "correct result\n";
};
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