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// This example demonstrates two ways to achieve algorithm invocations that are asynchronous with | |
// the calling thread. | |
// | |
// The first method wraps a call to thrust::reduce inside a __global__ function. Since __global__ function | |
// launches are asynchronous with the launching thread, this achieves asynchrony. The result of the reduction | |
// is stored to a pointer to CUDA global memory. The calling thread waits for the result of the reduction to | |
// be ready by synchronizing with the CUDA stream on which the __global__ function is launched. | |
// | |
// The second method uses the C++11 library function, std::async, to create concurrency. The lambda function | |
// given to std::async returns the result of thrust::reduce to a std::future. The calling thread can use the | |
// std::future to wait for the result of the reduction. This method requires a compiler which supports | |
// C++11-capable language and library constructs. | |
template<typename Iterator, typename T, typename BinaryOperation, typename Pointer> | |
__global__ void reduce_kernel(Iterator first, Iterator last, T init, BinaryOperation binary_op, Pointer result) | |
{ | |
*result = thrust::reduce(thrust::cuda::par, first, last, init, binary_op); | |
} | |
int main() | |
{ | |
size_t n = 1 << 20; | |
thrust::device_vector<unsigned int> data(n, 1); | |
thrust::device_vector<unsigned int> result(1, 0); | |
// method 1: call thrust::reduce from an asynchronous CUDA kernel launch | |
// create a CUDA stream | |
cudaStream_t s; | |
cudaStreamCreate(&s); | |
// launch a CUDA kernel with only 1 thread on our stream | |
reduce_kernel<<<1,1,0,s>>>(data.begin(), data.end(), 0, thrust::plus<int>(), result.data()); | |
// wait for the stream to finish | |
cudaStreamSynchronize(s); | |
// our result should be ready | |
assert(result[0] == n); | |
cudaStreamDestroy(s); | |
// reset the result | |
result[0] = 0; | |
// method 2: use std::async to create asynchrony | |
// copy all the algorithm parameters | |
auto begin = data.begin(); | |
auto end = data.end(); | |
unsigned int init = 0; | |
auto binary_op = thrust::plus<unsigned int>(); | |
// std::async captures the algorithm parameters by value | |
// use std::launch::async to ensure the creation of a new thread | |
std::future<unsigned int> future_result = std::async(std::launch::async, [=] | |
{ | |
return thrust::reduce(begin, end, init, binary_op); | |
}); | |
// wait on the result and check that it is correct | |
assert(future_result.get() == n); | |
return 0; | |
} | |