Cusp

Cusp is a library for sparse linear algebra and graph computations on CUDA. Cusp provides a flexible, high-level interface for manipulating sparse matrices and solving sparse linear systems. Get Started with Cusp today!

• v0.2.0

$ qlogin -q tesla.q
$ module load gpu/cuda

Calcul le transposé d'une matrice

transpose.cu

#include <cusp/transpose.h>
#include <cusp/array2d.h>
#include <cusp/print.h>
 
int main(void)
{
    // initialize a 2x3 matrix
    cusp::array2d<float, cusp::host_memory> A(2,3);
    A(0,0) = 10;  A(0,1) = 20;  A(0,2) = 30;
    A(1,0) = 40;  A(1,1) = 50;  A(1,2) = 60;
 
    // print A
    cusp::print(A);
 
    // compute the transpose
    cusp::array2d<float, cusp::host_memory> At;
    cusp::transpose(A, At);
 
    // print A^T
    cusp::print(At);
 
    return 0;
}

Chargement d'une matrice depuis un fichier (MatrixMarket), résolution du système A.X=b sur GPU en utilisant la méthode GC.

cg.cu

#include <cusp/hyb_matrix.h>
#include <cusp/io/matrix_market.h>
#include <cusp/krylov/cg.h>
 
int main(void)
{
    // create an empty sparse matrix structure (HYB format)
    cusp::hyb_matrix<int, float, cusp::device_memory> A;
 
    // load a matrix stored in MatrixMarket format
    cusp::io::read_matrix_market_file(A, "5pt_10x10.mtx");
 
    // allocate storage for solution (x) and right hand side (b)
    cusp::array1d<float, cusp::device_memory> x(A.num_rows, 0);
    cusp::array1d<float, cusp::device_memory> b(A.num_rows, 1);
 
    // solve the linear system A * x = b with the Conjugate Gradient method
    cusp::krylov::cg(A, x, b);
 
    return 0;
}

$ nvcc transpose.cu -o transpose

http://code.google.com/p/cusp-library/