Elements of Parallel Computing

Eric Aubanel

ISBN 10: 1498727891 / ISBN 13: 9781498727891

Published by Chapman And Hall/CRC, 2016

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - This textbook covers the core principles of parallel computing using language-neutral programming models together with abstract machine models. It focuses on patterns of parallel programming and mental models of parallel computing, using a task graph approach. Pseudocode is used for the programming examples in order to capture the essential behavior, without getting tied up in syntactical details. The author provides implementations of all examples in several parallel programming languages as part of the supplementary material.

Seller Inventory # 9781498727891

Bibliographic Details

• Title: Elements of Parallel Computing
• Publisher: Chapman And Hall/CRC
• Publication Date: 2016
• Language: English
• ISBN 10: 1498727891
• ISBN 13: 9781498727891
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 254W x 178H x 13D millimeters 254 millimeters width by 178 millimeters height by 13 millimeters depth
• Weight: 460 grams

About this title

Synopsis

Designed for introductory parallel computing courses at the advanced undergraduate or beginning graduate level, Elements of Parallel Computing presents the fundamental concepts of parallel computing not from the point of view of hardware, but from a more abstract view of algorithmic and implementation patterns. The aim is to facilitate the teaching of parallel programming by surveying some key algorithmic structures and programming models, together with an abstract representation of the underlying hardware. The presentation is friendly and informal. The content of the book is language neutral, using pseudocode that represents common programming language models.

The first five chapters present core concepts in parallel computing. SIMD, shared memory, and distributed memory machine models are covered, along with a brief discussion of what their execution models look like. The book also discusses decomposition as a fundamental activity in parallel algorithmic design, starting with a naive example, and continuing with a discussion of some key algorithmic structures. Important programming models are presented in depth, as well as important concepts of performance analysis, including work-depth analysis of task graphs, communication analysis of distributed memory algorithms, key performance metrics, and a discussion of barriers to obtaining good performance.

The second part of the book presents three case studies that reinforce the concepts of the earlier chapters. One feature of these chapters is to contrast different solutions to the same problem, using select problems that aren't discussed frequently in parallel computing textbooks. They include the Single Source Shortest Path Problem, the Eikonal equation, and a classical computational geometry problem: computation of the two-dimensional convex hull. After presenting the problem and sequential algorithms, each chapter first discusses the sources of parallelism then surveys parallel algorithms.

About the Author

Eric Aubanel is a Professor in the Faculty of Computer Science at the University of New Brunswick, Fredericton , C anada. His area of research is High Performance Computing. He is part of the IBM Center for Advanced Studies - Atlantic and associated with the Atlantic Computational Excellence Network (ACEnet). His research is funded by NSERC.