Gallop: The Benefits of Wide-Area Computing for Parallel Processing

Weissman, Jon

doi:10.1006/jpdc.1998.1487

Cited by 25 publications

(9 citation statements)

References 19 publications

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“…Application adaptivity in response to CPU sharing was achieved by the following techniques: dynamic load balancing, migration, processor addition, and processor removal. Prior work established that performance prediction for non-adaptive SPMD applications can be done accurately [23,24]. In this paper, we extend our earlier models to include the cost and benefit of adaptation.…”

Section: Introductionmentioning

confidence: 87%

Predicting the Cost and Benefit of Adapting Data Parallel Applications in Clusters

Weissman

2002

Journal of Parallel and Distributed Computing

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This paper examines the problem of adapting data parallel applications in a shared dynamic environment of PC or workstation clusters. We developed an analytic framework to compare and contrast a wide range of adaptation strategies: dynamic load balancing, migration, processor addition and removal. These strategies have been evaluated with respect to the cost and benefit they provide for three representative parallel applications: an iterative jacobi solver for Laplace's equation, gaussian elimination with partial pivoting, and a gene sequence comparison application. We found that the cost and benefit of each method can be predicted with high accuracy (within 10%) for all applications and show that the framework is applicable to a wide variety of parallel applications. We then show that accurate prediction allows the most appropriate method to be selected dynamically. Performance improvement for the three applications ranged from 25% to 45% using our adaptation library. In addition, we dispel the conventional wisdom that migration is too expensive, and show that it can be beneficial even for running parallel applications with non-trivial communication. # 2002 Elsevier Science (USA)

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Section: Introductionmentioning

confidence: 87%

Predicting the Cost and Benefit of Adapting Data Parallel Applications in Clusters

Weissman

2002

Journal of Parallel and Distributed Computing

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“…While in case of dynamic replication, new replicas can be generated during run time. Gallop [40] used an initial set of replicas based on user preferences which we call static replicas (e.g. the user wants x replicas).…”

Section: Static Vs Dynamic Replicationmentioning

confidence: 99%

Fault Tolerance In Grid Computing: State of the Art and Open Issues

Garg¹,

Singh²

2011

IJCSES

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“…Future developments may even lead to Internet-wide metacomputing [23]. Consequently, there has been a growing interest in coarsegrain computational models and algorithms, mainly because the algorithms for fine-grain models rarely translate to fast code on multicomputer systems [5].…”

Section: Introductionmentioning

confidence: 99%