Book ChapterDOI
Full matrix techniques in sparse Gaussian elimination
Iain S. Duff
- pp 71-84
TLDR
The benefits of using full matrix techniques in the later stages of Gaussian elimination are indicated and frontal and multi-frontal schemes where such benefits are obtained automatically are described.Abstract:
We discuss ways in which code for Gaussian elimination on full systems can be used in crucial parts of the code for the solution of sparse linear equations. We indicate the benefits of using full matrix techniques in the later stages of Gaussian elimination and describe frontal and multi-frontal schemes where such benefits are obtained automatically. We also illustrate the advantages of such approaches when running sparse codes on vector machines.read more
Citations
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Journal ArticleDOI
A set of level 3 basic linear algebra subprograms
TL;DR: This paper describes an extension to the set of Basic Linear Algebra Subprograms targeted at matrix-vector operations that should provide for efficient and portable implementations of algorithms for high-performance computers.
Journal ArticleDOI
The LINPACK Benchmark: past, present and future
TL;DR: Aside from the LINPACK Benchmark suite, the TOP500 and the HPL codes are presented and information is given on how to interpret the results of the benchmark and how the results fit into the performance evaluation process.
Journal ArticleDOI
The multifrontal method for sparse matrix solution: theory and practice
TL;DR: This paper presents an overview of the multifrontal method for the solution of large sparse symmetric positive definite linear systems, formulated in terms of frontal matrices, updateMatrices, and an assembly tree.
Journal ArticleDOI
A proposal for a set of level 3 basic linear algebra subprograms
TL;DR: The Level 3 BLAS are targeted at matrix-matrix operations with the aim of providing more efficient, but portable, implementations of algorithms on high-performance computers, especially those with hierarchical memory and parallel processing capability.
References
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Journal ArticleDOI
Computer solution of large sparse positive definite systems
Journal ArticleDOI
A frontal solution program for finite element analysis
TL;DR: The program given here assembles and solves symmetric positive–definite equations as met in finite element applications, more involved than the standard band–matrix algorithms, but more efficient in the important case when two-dimensional or three-dimensional elements have other than corner nodes.
Journal ArticleDOI
Frontal solution program for unsymmetric matrices
TL;DR: A frontal solution program is presented which may be used for the solution of unsymmetric matrix equations arising in certain applications of the finite element method to boundary value problems based on the Gaussian elimination algorithm.
Journal ArticleDOI
Yale sparse matrix package I: The symmetric codes
TL;DR: This report presents a package of efficient, reliable, well-documented, and portable FORTRAN subroutines for solving NxN system of linear equations M x = b, where the coefficient matrix M is large, sparse, and nonsymmetric.