Keyword Analysis & Research: cxsparse vs suitesparse


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Frequently Asked Questions

What is suitesparse?

SuiteSparse is a suite of sparse m atrix algorithms, including: • ssget: MATLAB and Java interface to the SuiteSparse Matrix Collection • 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. Now with CUDA acceleration, in collaboration with NVIDIA.

What is csparse?

CSparse a concise sparse matrix package, developed for my book, "Direct Methods for Sparse Linear Systems", published by SIAM. Intended primarily for teaching. It does have a 'make install' but I recommend using CXSparse instead. In particular, both CSparse and CXSparse have the same include filename: cs.h.

What is the difference between cxsparse and acceleratesparse?

CXSparse: Ceres built with CXSparse ( CXSPARSE=ON ). AccelerateSparse: Ceres built with Apple’s Accelerate sparse solvers ( ACCELERATESPARSE=ON ). EigenSparse: Ceres built with Eigen’s sparse Cholesky factorization ( EIGENSPARSE=ON ).

Is suitesparse fast enough for large linear systems?

However, for large linear systems, it is not as fast as the state-of-the-art sparse linear solvers such as CHOLMOD in SuiteSparse. See this benchmark.


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