http://code.google.com/p/komrade/
Komrade
is a CUDA library of parallel algorithms with an interface resembling
the C++ Standard Template Library (STL). Komrade provides a high-level
interface for GPU programming while remaining both fast and flexible.
Komrade
is best explained through examples. The following source code generates
random numbers on the host and transfers them to the device where they
are sorted.
#include <komrade/host_vector.h>
#include <komrade/device_vector.h>
#include <komrade/generate.h>
#include <komrade/sort.h>
#include <cstdlib>
int main(void)
{
// generate random data on the host
komrade::host_vector<int> h_vec(20);
komrade::generate(h_vec.begin(), h_vec.end(), rand);
// transfer to device and sort
komrade::device_vector<int> d_vec = h_vec;
komrade::sort(d_vec.begin(), d_vec.end());
return 0;
}
This code sample computes the sum of 100 random
numbers on the GPU.
#include <komrade/host_vector.h>
#include <komrade/device_vector.h>
#include <komrade/generate.h>
#include <komrade/reduce.h>
#include <komrade/functional.h>
#include <cstdlib>
int main(void)
{
// generate random data on the host
komrade::host_vector<int> h_vec(100);
komrade::generate(h_vec.begin(), h_vec.end(), rand);
// transfer to device and compute sum
komrade::device_vector<int> d_vec = h_vec;
int x = komrade::reduce(d_vec.begin(), d_vec.end(), komrade::plus<int>());
return 0;
}
Refer to the Tutorial
page for further information and examples.
We wish to thank the following people who
have made important intellectual and/or software contributions to
Komrade:
Additionally, we thank the compiler group at
NVIDIA for their continued improvements to nvcc. In
particular, we appreciate the work Bastiaan Aarts has done to enhance nvcc's
C++ support.
