My favorites | Sign in
Project Home Downloads Wiki Issues Source
Project Information
Members
Featured
Downloads
Wiki pages
Links

What is 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!



News

  • Cusp v0.3.0 has been released with support for CUDA 4.1. See CHANGELOG for release information.
  • Cusp v0.2.0 has been released! See CHANGELOG for release information.
  • Cusp v0.1.2 has been released! v0.1.2 contains compatibility fixes for Thrust v1.3.0.
  • Cusp v0.1.1 has been released! v0.1.1 contains compatibility fixes for CUDA 3.1.
  • Cusp v0.1.0 has been released!.
  • Added QuickStartGuide page.

Examples

The following example loads a matrix from disk, transparently converts the matrix to the highly-efficient HYB format, and transfers the matrix to the GPU device. The linear system A*x = b is them solved on the device using the Conjugate Gradient method. A more detailed version of this example is also available.

#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;
}
Powered by Google Project Hosting