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DrTimothyAldenDavis/SuiteSparse

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The official SuiteSparse library: a suite of sparse matrix algorithms authored or co-authored by Tim Davis, Texas A&M University. No AI generated code

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Type
Open Source
Visit Website GitHub (38 stars)

About DrTimothyAldenDavis/SuiteSparse

SuiteSparse is a comprehensive collection of sparse matrix algorithms, authored primarily by Tim Davis at Texas A&M University. It includes over 20 packages for solving sparse linear systems, performing matrix factorizations (LU, Cholesky, QR), ordering (AMD, COLAMD, etc.), graph algorithms via GraphBLAS, and more. The library is widely used in scientific computing, engineering simulations, and data analysis. It is open source, hosted on GitHub, and supports both C/C++ and MATLAB interfaces. As of February 2026, the latest version is 7.12.2. SuiteSparse is developed without AI-generated code, ensuring handcrafted reliability.

Key Features

Sparse LU factorization with UMFPACK
Sparse Cholesky factorization with CHOLMOD
Approximate minimum degree ordering with AMD and CAMD
Column approximate minimum degree ordering with COLAMD and CCOLAMD
Graph algorithms via GraphBLAS (GraphBLAS)
Suite of direct and iterative solvers (KLU, SPQR, etc.)
MATLAB interface via MATLAB_Tools
Cross-platform support with CMake build system
Extensive documentation and demos
Handcrafted code, no AI generation

Pros & Cons

Pros
  • Comprehensive collection of specialized sparse matrix packages
  • High-quality, hand-crafted algorithms by leading experts
  • Widely used and trusted in academia and industry
  • Open source with liberal license
  • Seamless integration with MATLAB
  • Active maintenance with regular releases
Cons
  • Requires compilation for use in C/C++ projects
  • Steep learning curve due to many packages and configurations
  • Not a turnkey application; requires programming knowledge
  • Documentation is primarily technical, aimed at developers and researchers

Best For

Solving large sparse linear systems in scientific computingFinite element analysis and simulationCircuit simulation and power grid analysisNetwork analysis and graph analyticsOptimization and operations researchAcademic research in numerical linear algebra

FAQ

What is SuiteSparse?
SuiteSparse is a set of sparse-matrix-related packages written or co-authored by Tim Davis, available at https://github.com/DrTimothyAldenDavis/SuiteSparse. It includes algorithms for solving sparse linear systems, factorizations, ordering, and graph operations.
Who created SuiteSparse?
SuiteSparse is primarily authored by Tim Davis of Texas A&M University, with contributions from many co-authors listed in the repository.
Is SuiteSparse free and open source?
Yes, SuiteSparse is free and open source, hosted on GitHub. It uses a permissive license (see LICENSE.txt in the repository).
What packages are included in SuiteSparse?
SuiteSparse includes AMD, BTF, CAMD, CCOLAMD, CHOLMOD, COLAMD, CSparse, CXSparse, GraphBLAS, KLU, LAGraph, LDL, MATLAB_Tools, Mongoose, ParU, RBio, SPEX, SPQR, SuiteSparse_config, UMFPACK, and others.