The University of Florida Sparse Matrix Collection is a large and actively growing set
of sparse matrices that arise in real applications. The Collection is widely used by the numerical linear algebra community for the development and performance evaluation of sparse matrix algorithms. It allows for robust and repeatable experiments. Its matrices cover a wide spectrum of domains, include those arising from problems with underlying 2D or 3D geometry (as structural engineering, computational fluid dynamics, model reduction, electromagnetics, semiconductor devices, thermodynamics, materials, acoustics, computer graphics/vision, robotics/kinematics, and
other discretizations) and those that typically do not have such geometry (optimization, circuit simulation, economic and financial modeling, theoretical and quantum chemistry, chemical process simulation, mathematics and statistics, power networks, and other networks and graphs.
The University of Florida Sparse Matrix Collection is covered by Thomson Reuters Data Citation Index. We provide software for accessing and managing the Collection, from MATLABTM, MathematicaTM,
Fortran, and C, as well as an online search capability. Graph visualization of the matrices is provided, and a new multilevel coarsening scheme is proposed to facilitate this task. The collection also appears as a Public Data Set hosted by Amazon Web Services, at aws.amazon.com This collection is managed by Tim Davis (University of Florida, Department of Computer and Information Science and Engineering) , with images created by Yifan Hu (AT&T Labs Research).
re3data.org: The University of Florida Sparse Matrix Collection;
editing status 2015-11-13;
re3data.org - Registry of Research Data Repositories. http://doi.org/10.17616/R3WG6Z
last accessed: 2017-01-20