Graph theory and sparse matrix computation
著者
書誌事項
Graph theory and sparse matrix computation
（The IMA volumes in mathematics and its applications, v. 56）
Springer-Verlag, c1993
- : us
- : gw
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注記
"Proceedings of a workshop that was an integral part of the 1991-92 IMA program on "Applied Linear Algebra"" -- Foreword
Includes bibliographical references
内容説明・目次
- 巻冊次
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: us ISBN 9780387941318
目次
An introduction to chordal graphs and clique trees.- Cutting down on fill using nested dissection: Provably good elimination orderings.- Automatic Mesh Partitioning.- Structural representations of Schur complements in sparse matrices.- Irreducibility and primitivity of Perron complements: Application of the compressed directed graph.- Predicting structure in nonsymmetric sparse matrix factorizations.- Highly parallel sparse triangular solution.- The fan-both family of column-based distributed Cholesky factorization algorithms.- Scalability of sparse direct solvers.- Sparse matrix factorization on SIMD parallel computers.- The efficient parallel iterative solution of large sparse linear systems.
- 巻冊次
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: gw ISBN 9783540941316
内容説明
When reality is modelled by computation, matrices are often the connection between the continuous physical world and the finite algorithmic one. Usually, the more detailed the model, the bigger the matrix; however, efficiency demands that every possible advantage be exploited. The articles in this volume are based on recent research on sparse matrix computations. They examine graph theory as it connects to linear algebra, parallel computing, data structures, geometry and both numerical and discrete algorithms. The articles are grouped into three general categories: graph models of symmetric matrices and factorizations; graph models of algorithms on nonsymmetric matrices; and parallel sparse matrix algorithms.
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