Thrust is a CUDA library of parallel algorithms with an interface resembling the C++ Standard Template Library (STL). Thrust provides a flexible high-level interface for GPU programming that greatly enhances developer productivity. Develop high-performance applications rapidly with Thrust!

• v1.4.0

$ qlogin -q tesla.q

$ module load cuda

Génération des nombres aléatoires sur le CPU, les transférer sur GPU

transfert.cu

#include <thrust/host_vector.h>
#include <thrust/device_vector.h>
#include <thrust/generate.h>
#include <thrust/sort.h>
#include <thrust/copy.h>
#include <cstdlib>
 
int main(void)
{
    // generate 32M random numbers on the host
    thrust::host_vector<int> h_vec(32 << 20);
    thrust::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;
}

Calcul de la somme de 100 nombre sur le GPU

somme.cu

#include <thrust/host_vector.h>
#include <thrust/device_vector.h>
#include <thrust/generate.h>
#include <thrust/reduce.h>
#include <thrust/functional.h>
#include <cstdlib>
 
int main(void)
{
  // generate random data on the host
  thrust::host_vector<int> h_vec(100);
  thrust::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;
}

$ nvcc Example.cpp -o Example

http://code.google.com/p/thrust/