ENGLISH

Graph Theory and Sparse Matrix Computation

By Alan George , John R. Gilbert , Jean R. S. Blair , Barry Peyton (auth.) , Joseph W. H. Liu (eds.)

Book information

Publisher
Springer-Verlag New York
Year
1993
ISBN
978-1-4613-8371-0, 978-1-4613-8369-7
DOI
10.1007/978-1-4613-8369-7
Language
english
Format
PDF
Filesize
13 MB (13711706 bytes)
Series
The IMA Volumes in Mathematics and its Applications 56
Edition
1
Pages
245\253
Orientation
yes
Scanned
yes
Time added
2013-08-01 04:00:00
Combinatorics; Numerical Analysis

Description

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.

Similar books