Abstract Machine Models For Parallel And Distributed Computing

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Abstract Machine Models for Parallel and Distributed Computing

Abstract Machine Models have played a profound though frequently unacknowledged role in the development of modern computing systems. They provide a precise definition of vital concepts, allow system complexity to be managed by providing appropriate views of the activity under consideration, enable reasoning about the correctness and quantitative performance of proposed problem solutions, and encourage communication through a common medium of expression. Abstract Models in Parallel and Distributed computing have a particularly important role in the development of contemporary systems, encapsulating and controlling an inherently high degree of complexity. The Parallel and Distributed computing communities have traditionally considered themselves to be separate. However, there is a significant contemporary interest in both of these communities in a common hardware model; a set of workstation-class machines connected by a high-performance network. The traditional Parallel/Distributed distinction therefore appears under threat.
Models for Parallel and Distributed Computation

Author: R. Correa
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-06-29
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.
Patterns and Skeletons for Parallel and Distributed Computing

Author: Fethi A. Rabhi
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-06-28
Patterns and Skeletons for Parallel and Distributed Computing is a unique survey of research work in high-level parallel and distributed computing over the past ten years. Comprising contributions from the leading researchers in Europe and the US, it looks at interaction patterns and their role in parallel and distributed processing, and demonstrates for the first time the link between skeletons and design patterns. It focuses on computation and communication structures that are beyond simple message-passing or remote procedure calling, and also on pragmatic approaches that lead to practical design and programming methodologies with their associated compilers and tools. The book is divided into two parts which cover: skeletons-related material such as expressing and composing skeletons, formal transformation, cost modelling and languages, compilers and run-time systems for skeleton-based programming.- design patterns and other related concepts, applied to other areas such as real-time, embedded and distributed systems. It will be an essential reference for researchers undertaking new projects in this area, and will also provide useful background reading for advanced undergraduate and postgraduate courses on parallel or distributed system design.