SuperLU Users'' Guide
By J. Demmel, John R. Gilbert, Xiaoye Sherry Li. 1997
This document describes a collection of three related ANSI C subroutine libraries for solving sparse linear systems of equations AX = B: Here A is a square, nonsingular, n x n sparse matrix, and X and B are dense n x nrhs matrices, where nrhs is the number of right-hand sides and solution vectors. Matrix A need not be symmetric or definite; indeed, SuperLU is particularly appropriate for matrices with very unsymmetric structure. All three libraries use variations of Gaussian elimination optimized to take advantage both of sparsity and the computer architecture, in particular memory hierarchies (caches) and parallelism.
Subfields: Numerical Methods & Scientific Computing
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In Numerical Methods & Scientific Computing
- Natarajan Sukumar
- A. Tabarraei
- Ian Henriksen
- Xiaoye Sherry Li
- K. Jarrod Millman
- Fabian Pedregosa
- S. Van Der Walt
- J. Vanderplas
Citations in the corpus
- Extended finite element method on polygonal and quadtree meshes (2008, methodology): “The direct sparse solver, SuperLU [ 39 ], has been interfaced to our code to solve the linear system of equations.”
- SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python (2019, background): “In summary, there are five specific guidelines: be open to everyone participating in our community; be empathetic and patient in resolving conflicts; be collaborative, as we depend on each other to build the library; be inquisitive, as early identification of issues can prevent serious…”
- An overview of SuperLU: Algorithms, implementation, and user interface (2003, methodology): “The reader may refer to the Users Guide for the memory layout of each storage format [Demmel et al. 1999c].”