Thrust is a parallel algorithms library which resembles the C++ Standard Template Library (STL). Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs. Interoperability with established technologies (such as CUDA, TBB, and OpenMP) facilitates integration with existing software. Develop high-performance applications rapidly with Thrust!
Thrust is best explained through examples. The following source code generates random numbers serially and then transfers them to a parallel device where they are sorted.
#include <thrust/host_vector.h> #include <thrust/device_vector.h> #include <thrust/generate.h> #include <thrust/sort.h> #include <thrust/copy.h> #include <algorithm> #include <cstdlib> int main(void) { // generate 32M random numbers serially thrust::host_vector<int> h_vec(32 << 20); std::generate(h_vec.begin(), h_vec.end(), rand); // transfer data to the device thrust::device_vector<int> d_vec = h_vec; // sort data on the device (846M keys per second on GeForce GTX 480) thrust::sort(d_vec.begin(), d_vec.end()); // transfer data back to host thrust::copy(d_vec.begin(), d_vec.end(), h_vec.begin()); return 0; }
This code sample computes the sum of 100 random numbers in parallel:
#include <thrust/host_vector.h> #include <thrust/device_vector.h> #include <thrust/generate.h> #include <thrust/reduce.h> #include <thrust/functional.h> #include <algorithm> #include <cstdlib> int main(void) { // generate random data serially thrust::host_vector<int> h_vec(100); std:generate(h_vec.begin(), h_vec.end(), rand); // transfer to device and compute sum thrust::device_vector<int> d_vec = h_vec; int x = thrust::reduce(d_vec.begin(), d_vec.end(), 0, thrust::plus<int>()); return 0; }
Refer to the Quick Start Guide page for further information and examples.
The primary developers of Thrust are Jared Hoberock and Nathan Bell.