Graph theory and sparse matrix computation
Alan George, J. R. Gilbert · 2011
Where to buy
Check today’s price on Amazon. We do not show prices because they change daily.
View on AmazonAffiliate link. As an Amazon Associate we earn from qualifying purchases.
About the book
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.
Book details
- Year
- 2011
- Language
- English
- Publisher
- Springer
- Editions
- 3
- Pages
- 245
- ISBN
- 9781461383710
Data source: Wikidata
