Process Algebra for Parallel and Distributed Processing

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ISBN 10: 0367386100 / ISBN 13: 9780367386108

Published by Taylor & Francis Ltd, 2019

About this Item

Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher.

Seller Inventory # 35525903/1

Bibliographic Details

• Title: Process Algebra for Parallel and Distributed Processing
• Publisher: Taylor & Francis Ltd
• Publication Date: 2019
• Language: English
• ISBN 10: 0367386100
• ISBN 13: 9780367386108
• Binding: Soft cover
• Condition: Hervorragend
• Seller catalogs:
  • Bücher

About this title

Synopsis

Collects the Latest Research Involving the Application of Process Algebra to Computing

Exploring state-of-the-art applications, Process Algebra for Parallel and Distributed Processing shows how one formal method of reasoning―process algebra―has become a powerful tool for solving design and implementation challenges of concurrent systems.

Parallel ProgrammingDivided into three parts, the book begins by parallelizing an algorithm for the Cell Broadband Engine processor of IBM, Sony, and Toshiba. It also develops a runtime environment that can be ported to different parallel platforms and describes the formal model of action systems.

Distributed SystemsThe next part presents a process algebra (mCRL2) that targets distributed applications, looks at how to turn prose descriptions into unambiguous specifications, extends pi-calculus to create a service-oriented mobility abstract machine, and introduces the Channel Ambient Machine for mobile applications.

Embedded SystemsThe final section combines state-based Z with the event-based process algebra CSP in a formal methodology called Circus. It also develops a pair of process algebras (PARS) to address the problem of scheduling in real-time embedded systems and emphasizes the reuse of concurrent artifacts across different hardware platforms.

Highlighting recent research work, this volume addresses multicore programming problems and the evolution of the growing body of concurrency-enabled languages. It proposes solutions to the problems of designing and implementing today’s concurrency-constrained multicore processor and cloud architectures.

About the Author

Dr. Michael Alexander, IBM, Vienna, Austria

Dr. William Gardner, University of Guelph, Ontario, Canada