This item is printed on demand - Print on Demand Titel. Neuware -This book helps to find: Concurrency in a program - how to help programmers �think parallel� Scheduling tasks at the right granularity onto the processors of a parallel machine. The data locality problem: associating data with tasks and doing it in a way that our target audience will be able to use correctly. Scalability support in hardware: bandwidth and latencies to memory plus interconnects between processing elements. Scalability support in software: libraries, scalable algorithms, and adaptive run times to map high level software onto platform details. Synchronization constructs (and protocols) that enable programmers write programs free from deadlock and race conditions. Tools, API�s and methodologies to support the debugging process. Error recovery and support for fault tolerance. Support for good software engineering practices: compos ability, incremental parallelism, and code reuse. Support for portable performance. What are the right models (or abstractions) so programmers can write code once and expect it to execute well on the important parallel platforms Books on Demand GmbH, �berseering 33, 22297 Hamburg 168 pp. Englisch.

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T�tulo: Key challenges in Distributed computing
Editor: LAP LAMBERT Academic Publishing Jul 2012
Fecha de publicaci�n: 2012
Idioma: Ingl�s
ISBN 10: 3659175226
ISBN 13: 9783659175220
Encuadernaci�n: Taschenbuch
Estado: Neu
Dimensiones: 220�mil�metros de ancho por 150 de alto por 11 de largo
Peso: 268 gramos

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This book helps to find: Concurrency in a program - how to help programmers "think parallel"? Scheduling tasks at the right granularity onto the processors of a parallel machine. The data locality problem: associating data with tasks and doing it in a way that our target audience will be able to use correctly. Scalability support in hardware: bandwidth and latencies to memory plus interconnects between processing elements. Scalability support in software: libraries, scalable algorithms, and adaptive run times to map high level software onto platform details. Synchronization constructs (and protocols) that enable programmers write programs free from deadlock and race conditions. Tools, API's and methodologies to support the debugging process. Error recovery and support for fault tolerance. Support for good software engineering practices: compos ability, incremental parallelism, and code reuse. Support for portable performance. What are the right models (or abstractions) so programmers can write code once and expect it to execute well on the important parallel platforms?

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Dilbag Singh Gill [BSC(Eco), MSC(CS) and Mtech(CSE)] belongs to SangtuNangal.org and has done and still doing work for Greenit. This book is dedicated to all my friends....

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