Graph Theory and Sparse Matrix Computation

Graph Theory and Sparse Matrix Computation
Alan George, J. R. Gilbert, Al ...
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Last edited by ImportBot
December 26, 2021 | History

Graph Theory and Sparse Matrix Computation

When reality is modeled 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, the better the answer, however, efficiency demands that every possible advantage be exploited. The articles in this volume are based on recent research on sparse matrix computations. This volume looks at 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. This book will be a resource for the researcher or advanced student of either graphs or sparse matrices; it will be useful to mathematicians, numerical analysts and theoretical computer scientists alike.

Publish Date
Publisher
Springer
Language
English

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Edition Availability
Cover of: Graph Theory and Sparse Matrix Computation
Graph Theory and Sparse Matrix Computation
2012, Springer
in English
Cover of: Graph Theory and Sparse Matrix Computation
Graph Theory and Sparse Matrix Computation
2011, Springer
in English
Cover of: Graph Theory and Sparse Matrix Computation
Graph Theory and Sparse Matrix Computation
1993, Island Press
in English
Cover of: Graph theory and sparse matrix computation
Graph theory and sparse matrix computation
1993, Springer-Verlag, Springer
in English

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Book Details


Classifications

Library of Congress
QA1-939

The Physical Object

Pagination
245

ID Numbers

Open Library
OL35923033M
ISBN 13
9781461383697

Source records

Better World Books record

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December 26, 2021 Created by ImportBot Imported from Better World Books record