Paradigms for Fast Parallel Approximability

A survey of the basic techniques for approximating combinatorial problems using parallel algorithms.

Josep Díaz (Author), Maria Serna (Author), Paul Spirakis (Author), Jacobo Torán (Author)

9780521117920, Cambridge University Press

Paperback, published 30 July 2009

168 pages, 32 b/w illus.
24.4 x 17 x 0.9 cm, 0.28 kg

Review of the hardback: 'Required reading for researchers working on parallel algorithms and of interest to anyone working in the area of parallel computing in general.' Brian Bramer, CVu

Various problems in computer science are 'hard', that is NP-complete, and so not realistically computable; thus in order to solve them they have to be approximated. This book is a survey of the basic techniques for approximating combinatorial problems using parallel algorithms. Its core is a collection of techniques that can be used to provide parallel approximations for a wide range of problems (for example, flows, coverings, matchings, travelling salesman problems, graphs), but in order to make the book reasonably self-contained, the authors provide an introductory chapter containing the basic definitions and results. A final chapter deals with problems that cannot be approximated, and the book is ended by an appendix that gives a convenient summary of the problems described in the book. This is an up-to-date reference for research workers in the area of algorithms, but it can also be used for graduate courses in the subject.

1. Introduction
2. Basic concepts
3. Extremal graph properties
4. Rounding, interval partitioning and separation
5. Primal-dual method
6. Graph decomposition
7. Further parallel approximations
8. Non-approximability
9. Syntactical defined phrases
Appendix: Definition of problems
Bibliography
Index.

Subject Areas: Parallel processing [UYFP], Algorithms & data structures [UMB]