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Parallel and distributed computation has been gaining a great lot
of attention in the last decades. During this period, the advances
attained in computing and communication technologies, and the
reduction in the costs of those technolo gies, played a central
role in the rapid growth of the interest in the use of parallel and
distributed computation in a number of areas of engineering and
sciences. Many actual applications have been successfully
implemented in various plat forms varying from pure shared-memory
to totally distributed models, passing through hybrid approaches
such as distributed-shared memory architectures. Parallel and
distributed computation differs from dassical sequential compu
tation in some of the following major aspects: the number of
processing units, independent local dock for each unit, the number
of memory units, and the programming model. For representing this
diversity, and depending on what level we are looking at the
problem, researchers have proposed some models to abstract the main
characteristics or parameters (physical components or logical
mechanisms) of parallel computers. The problem of establishing a
suitable model is to find a reasonable trade-off among simplicity,
power of expression and universality. Then, be able to study and
analyze more precisely the behavior of parallel applications."
Parallel and distributed computation has been gaining a great lot
of attention in the last decades. During this period, the advances
attained in computing and communication technologies, and the
reduction in the costs of those technolo gies, played a central
role in the rapid growth of the interest in the use of parallel and
distributed computation in a number of areas of engineering and
sciences. Many actual applications have been successfully
implemented in various plat forms varying from pure shared-memory
to totally distributed models, passing through hybrid approaches
such as distributed-shared memory architectures. Parallel and
distributed computation differs from dassical sequential compu
tation in some of the following major aspects: the number of
processing units, independent local dock for each unit, the number
of memory units, and the programming model. For representing this
diversity, and depending on what level we are looking at the
problem, researchers have proposed some models to abstract the main
characteristics or parameters (physical components or logical
mechanisms) of parallel computers. The problem of establishing a
suitable model is to find a reasonable trade-off among simplicity,
power of expression and universality. Then, be able to study and
analyze more precisely the behavior of parallel applications."
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High Performance Computing for Computational Science - VECPAR 2016 - 12th International Conference, Porto, Portugal, June 28-30, 2016, Revised Selected Papers (Paperback, 1st ed. 2017)
Ines De Castro Dutra, Rui Camacho, Jorge G. Barbosa, Osni Marques
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R2,416
Discovery Miles 24 160
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Ships in 10 - 15 working days
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This book constitutes the thoroughly refereed post-conference
proceedings of the 12fth International Conference on High
Performance Computing in Computational Science, VECPAR 2016, held
in Porto, Portugal, in June 2016. The 20 full papers presented were
carefully reviewed and selected from 36 submissions. The papers are
organized in topical sections on applications; performance modeling
and analysis; low level support; environments/libraries to support
parallelization.
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