What is Cusp?

Github

We no longer maintain the CUSP project on Google Code. Find the new home of CUSP at cusplibrary.github.com

News

• CUSP is now host on Github
• 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 http://code.google.com/p/cusp-library/source/browse/examples/Solvers/cg.cu'>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;


}