suitesparse : a suite of sparse matrix software

suitesparse : a suite of sparse matrix software

Click here to DOWNLOAD SuiteSparse from github.com

Now with GraphBLAS and Mongoose

1. •SuiteSparse: with the latest CUDA-accelerated CHOLMOD and SuiteSparseQR, and GraphBLAS (now with OpenMP parallelism, and MATLAB interface).
   

2. •Click here for an archive of all SuiteSparse versions , and for SuiteSparse 4.6.0 BETA (with a multi-GPU CHOLMOD, presented at NVIDIA GTC16). Alternatively, all prior releases have been archived at github: https://github.com/DrTimothyAldenDavis/SuiteSparse
   

3. •Click here for more on GraphBLAS (including slides, videos, and papers)
   

4. •Mongoose 2.0.4: multilevel graph partitioning, based on combinatoric and quadratic programming methods. Appears in SuiteSparse 5.5.0. Click here for our recent submission to ACM TOMS.
   

SuiteSparse is a suite of sparse matrix algorithms, including:

1. •GraphBLAS: graph algorithms in the language of linear algebra
   

2. •Mongoose: graph partitioning
   

3. •ssget: MATLAB and Java interface to the SuiteSparse Matrix Collection
   

4. •UMFPACK: multifrontal LU factorization. Appears as LU and x=A\b in MATLAB.
   

5. •CHOLMOD: supernodal Cholesky. Appears as CHOL and x=A\b in MATLAB. Now with CUDA acceleration, in collaboration with NVIDIA.
   

6. •SPQR: multifrontal QR. Appears as QR and x=A\b in MATLAB, with CUDA acceleration.
   

7. •KLU and BTF: sparse LU factorization, well-suited for circuit simulation.
   

8. •Ordering methods (AMD, CAMD, COLAMD, and CCOLAMD). AMD and COLAMD appear in MATLAB.
   

9. •CSparse and CXSparse: a concise sparse Cholesky factorization package for my SIAM book.
   

10. •spqr_rank: a MATLAB package for reliable sparse rank detection, null set bases, pseudoinverse solutions, and basic solutions.
    

11. •Factorize: an object-oriented solver for MATLAB (a reusable backslash).
    

12. •SSMULT and SFMULT: sparse matrix multiplication. Appears as the built-in C=A*B operator in MATLAB.
    

13. •... and many other packages.
    

REFERENCES:

To cite this software, please see my publications page.

ABOUT THE LOGO:

The SuiteSparse logo at the top of this page was created via a mathematical algorithm that translates an entire piece of music into a single piece of artwork. The algorithm is written in MATLAB, and relies on Fourier transforms, sparse matrices, and force-directed graph visualization. Click here for more information on how I create this art, and here for the full artwork and music behind the SuiteSparse logo.

Windows and CMake: I do not yet have a build script for Visual Studio. Only GraphBLAS and Mongoose use CMake. Try Jose Luis Blanco’s implementation posted on github.

SUITESPARSE ON THE NVIDIA CUDA ZONE:

With support from NSF grants 1514406, 1115297, 0620286, 0324609, 0203270, 0119532, and earlier grants.