The SIMD Model of Parallel Computation

Robert Cypher

ISBN 10: 1461276063 / ISBN 13: 9781461276067

Published by Springer, Humana, 2011

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 1.1 Background There are many paradigmatic statements in the literature claiming that this is the decade of parallel computation. A great deal of research is being de voted to developing architectures and algorithms for parallel machines with thousands, or even millions, of processors. Such massively parallel computers have been made feasible by advances in VLSI (very large scale integration) technology. In fact, a number of computers having over one thousand pro cessors are commercially available. Furthermore, it is reasonable to expect that as VLSI technology continues to improve, massively parallel computers will become increasingly affordable and common. However, despite the significant progress made in the field, many funda mental issues still remain unresolved. One of the most significant of these is the issue of a general purpose parallel architecture. There is currently a huge variety of parallel architectures that are either being built or proposed. The problem is whether a single parallel computer can perform efficiently on all computing applications.

Seller Inventory # 9781461276067

Bibliographic Details

• Title: The SIMD Model of Parallel Computation
• Publisher: Springer, Humana
• Publication Date: 2011
• Language: English
• ISBN 10: 1461276063
• ISBN 13: 9781461276067
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 9D millimeters 235 millimeters width by 155 millimeters height by 9 millimeters depth
• Weight: 254 grams

About this title

Synopsis

This monograph is intended to teach parallel architecture and parallel algorithms to non-specialists. It is self-contained and includes both introductory and advanced material. It emphasizes the interaction between parallel architectures and parallel algorithms. It is intended for researchers, advanced undergraduate students or graduate students in the fields of parallel computing, machine vision.