SuiteSparse is a suite of sparse matrix algorithms, including UMFPACK, CHOLMOD, SPQR, KLU, BTF, ordering methods (AMD, CAMD, COLAMD, and CCOLAMD), CSparse, CXSparse, UFget, spqr_rank, Factorize, SSMULT, SFMULT, and many other packages.
SuiteSparse is a suite of sparse matrix algorithms, including:
- UMFPACK: multifrontal LU factorization. Appears as LU and x=A\b in MATLAB.
- CHOLMOD: supernodal Cholesky. Appears as CHOL and x=A\b in MATLAB. Used in Google Ceres. Now with CUDA acceleration, in collaboration with NVIDIA.
- SPQR: multifrontal QR. Appears as QR and x=A\b in MATLAB. CUDA acceleration just released (October 10, 2014, SuiteSparse 4.4.0), and submitted to ACM Trans. Math. Software
- KLU and BTF: sparse LU factorization, well-suited for circuit simulation. Appears in Xyce by Sandia, and many commercial circuit simulation packages.
- Ordering methods (AMD, CAMD, COLAMD, and CCOLAMD). AMD and COLAMD appear in MATLAB.
- CSparse and CXSparse: a concise sparse Cholesky factorization package for the book, "direct methods for sparse linear systems" from Tim Davis published by SIAM.
- UFget: a MATLAB interface for the UF Sparse Matrix Collection
- spqr_rank: a MATLAB package for reliable sparse rank detection, null set bases, pseudoinverse solutions, and basic solutions.
- Factorize: an object-oriented solver for MATLAB (a reusable backslash).
- SSMULT and SFMULT: sparse matrix multiplication. Appears as C=A*B in MATLAB.
- ... and many other packages.
