Foundations of Multithreaded, Parallel, and Distributed Programming

Andrews, Gregory

ISBN 10: 0201357526 / ISBN 13: 9780201357523

Editore: Pearson, 1999

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Titolo: Foundations of Multithreaded, Parallel, and ...

Casa editrice: Pearson

Data di pubblicazione: 1999

Legatura: Brossura

Condizione: Good

Descrizione articolo

Riassunto:

Foundations of Multithreaded, Parallel, and Distributed Programming covers, and then applies, the core concepts and techniques needed for an introductory course in this subject. Its emphasis is on the practice and application of parallel systems, using real-world examples throughout.

Greg Andrews teaches the fundamental concepts of multithreaded, parallel and distributed computing and relates them to the implementation and performance processes. He presents the appropriate breadth of topics and supports these discussions with an emphasis on performance.

Informazioni sull?autore:

Gregory Andrews received a B.S. degree in Mathematics from Stanford University in 1969 and a Ph.D. degree in Computer Science from the University of Washington in 1974. From 1974-79 he was an Assistant Professor at Cornell University. Since 1979 he has been at The University of Arizona, where he is currently Professor of Computer Science. From 1986-93 he chaired the department; in 1986 he received a distinguished teaching award.

Greg has been on the editorial board of Information Processing Letters since 1979. He was the general chair of the Twelfth ACM Symposium on Operating Systems Principles in 1989 and has been on the program committees of numerous conferences. From 1988-92 he was on advisory committees for the computing directorate of the National Science Foundation. Since 1991 he has been on the Board of Directors of the Computing Research Association (CRA).

Greg's research interests include all aspects of concurrent programming. A long-term project has been the design and implementation of the SR programming language. Current work focuses on the development of Filaments, a software package that provides efficient fine-grain parallelism on a variety of parallel machines.

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