Self adaptivity in Grid computing

Vadhiyar, Sathish; Dongarra, Jack

doi:10.1002/cpe.927

Cited by 104 publications

(62 citation statements)

References 25 publications

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“…This programming model, although higher level than classical Grid programming at the Grid middleware level is far from the abstraction level provided by either ASSIST or HOC, however. Recent papers on GrADs adaptivity present results that can be considered preliminary to the ones achieved in ASSIST [37].…”

Section: Related Workmentioning

confidence: 86%

High level Grid programming with ASSIST*

Aldinucci¹,

Coppola²,

Danelutto³

et al. 2006

CMST

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Abstract:The development of efficient Grid applications usually requires writing huge portions of code directly at the level of abstraction provided by the underlying Grid middleware. In this work we discuss an alternative approach, raising the level of abstraction used when programming Grid applications. Our approach requires programmers just to describe in a qualitative way the kind of parallelism they want to express. Then, compiler tools, loader tools and run time system take complete care of running the application on a Grid target architecture. This allows to move most of the cumbersome tasks related to Grid targeting and management from programmer responsibility to tools. This paper introduces the structured parallel programming environment ASSIST, whose design is aimed at raising the level of abstraction in Grid programming and discusses how it can support transparent Grid programming while implementing Grid adaptivity.

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Section: Related Workmentioning

confidence: 86%

High level Grid programming with ASSIST*

Aldinucci¹,

Coppola²,

Danelutto³

et al. 2006

CMST

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“…Placement of concurrent components derived from the compilation of high level parallel patterns on multicore, heterogenous architectures poses different problems related to efficiency and performance. Vadhiyar and Dongarra [61] suggest that a "self-adaptive software system examines the characteristics of the computing environments and chooses the software parameters needed to achieve high efficiency on that environment". Thus, we consider that the key challenges in adaptively improving the performance of parallel programs in a heterogeneous system are therefore:…”

Section: Related Workmentioning

confidence: 99%

The ParaPhrase Project: Parallel Patterns for Adaptive Heterogeneous Multicore Systems

Hammond

Aldinucci²,

Brown

et al. 2013

Formal Methods for Components and Objects

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Abstract. This paper describes the ParaPhrase project, a new 3-year targeted research project funded under EU Framework 7 Objective 3.4 (Computer Systems), starting in October 2011. ParaPhrase aims to follow a new approach to introducing parallelism using advanced refactoring techniques coupled with high-level parallel design patterns. The refactoring approach will use these design patterns to restructure programs defined as networks of software components into other forms that are more suited to parallel execution. The programmer will be aided by high-level cost information that will be integrated into the refactoring tools. The implementation of these patterns will then use a wellunderstood algorithmic skeleton approach to achieve good parallelism.A key ParaPhrase design goal is that parallel components are intended to match heterogeneous architectures, defined in terms of CPU/GPU combinations, for example. In order to achieve this, the ParaPhrase approach will map components at link time to the available hardware, and will then re-map them during program execution, taking account of multiple applications, changes in hardware resource availability, the desire to reduce communication costs etc. In this way, we aim to develop a new approach to programming that will be able to produce software that can adapt to dynamic changes in the system environment. Moreover, by using a strong component basis for parallelism, we can achieve potentially significant gains in terms of reducing sharing at a high level of abstraction, and so in reducing or even eliminating the costs that are usually associated with cache management, locking, and synchronisation.

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“…Vadhiyar and Dongarra presented a migration framework and self adaptivity in GrADS system (Vadhiyar & Dongarra, 2005). The gain with rescheduling is based on the remaining execution time prediction over a new specified resource.…”

Section: Related Workmentioning

confidence: 99%