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portada Process Algebra for Parallel and Distributed Processing
Type
Physical Book
Publisher
Language
English
Pages
438
Format
Hardcover
Dimensions
23.6 x 16.0 x 2.8 cm
Weight
0.75 kg.
ISBN
142006486X
ISBN13
9781420064865

Process Algebra for Parallel and Distributed Processing

Alexander, Michael ; Gardner, William (Author) · CRC Press · Hardcover

Process Algebra for Parallel and Distributed Processing - Alexander, Michael ; Gardner, William

Physical Book

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Synopsis "Process Algebra for Parallel and Distributed Processing"

Collects the Latest Research Involving the Application of Process Algebra to ComputingExploring 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.

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