Implementing a performance forecasting system for metacomputing

Wolski, Rich; Spring, Neil; Peterson, Chris L.

doi:10.1145/509593.509600

Cited by 91 publications

(59 citation statements)

References 13 publications

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“…Measurement and modeling of network bandwidth and latency is a very active area of research [7,14,21,30]. NWS (Network Weather Service) [38] and REMOS (Resource Monitoring System) [17] are two systems that have been specifically designed for measurement of available CPU and network resources in grid environments.…”

Section: Related Workmentioning

confidence: 99%

Performance prediction with skeletons

Sodhi

Subhlok

2007

Cluster Comput

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The performance skeleton of an application is a short running program whose performance in any scenario reflects the performance of the application it represents. Specifically, the execution time of the performance skeleton is a small fixed fraction of the execution time of the corresponding application in any execution environment. Such a skeleton can be employed to quickly estimate the performance of a large application under existing network and node sharing. This paper presents a framework for automatic construction of performance skeletons of a specified execution time and evaluates their use in performance prediction with CPU and network sharing. The approach is based on capturing the execution behavior of an application and automatically generating a synthetic skeleton program that reflects that execution behavior.The paper demonstrates that performance skeletons running for a few seconds can predict the application execution time fairly accurately. Relationship of skeleton execution time, application characteristics, and nature of resource sharing, to accuracy of skeleton based performance prediction, is analyzed in detail. The goal of this research is accurate performance estimation in heterogeneous and shared computational grids.

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Section: Related Workmentioning

confidence: 99%

Performance prediction with skeletons

Sodhi

Subhlok

2007

Cluster Comput

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“…We have demonstrated in previous work [37] that it is easy to "plug in" various external components into the Scheduling Unit (e.g. predictor from the Network Weather Service [39]). We refer the reader to [3,37] for evaluation and validation results concerning Bricks.…”

Section: The Bricks System and The Extensionmentioning

confidence: 99%

“…In general, schedulers use prediction concerning the performance of Grid resources. Such predictions are available through systems such as the NWS [39] and contain some error.…”

Section: A Deadline Scheduling Algorithmmentioning

confidence: 99%

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A study of deadline scheduling for client-server systems on the Computational Grid

Takefusa

Casanova

Matsuoka

et al.

Proceedings 10th IEEE International Symposium on High Performance Distributed Computing

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“…The Network Weather Service (NWS) is a tool for predicting computer and network performance for use by metacomputing applications [WOLS97] [SPRI97].…”

Section: Network Weather Servicementioning

confidence: 99%

Passive, domain-independent, end-to-end message passing performance monitoring to support adaptive applications in MSHN

Schnaidt

Hensgen²,

Falby³

et al.

Proceedings. The Eighth International Symposium on High Performance Distributed Computing (Cat. No.99TH8469)

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This paper focuses on the problem of monitoring the end-to-end performance of message passing to support adaptive applications to be executed using the MSHN system (Management System for Heterogeneous Networks). Eight commercial and research tools and application components that attempt to measure perceived end-to-end message passing performance were identified. Two were dismissed; one because of recently published findings and the other because it is typically used in too many inconsistent configurations. The remaining six are carefully described in the paper. We were able to characterize each as either passive or active, determine whether they require domain-specific knowledge of an application, identify sources of inaccuracies, and enumerate their limitations. Based upon this survey, and previous analytical experiments, we conclude that the optimal monitoring mechanism: (1) should be passive; (2) should not require domain-specific knowledge of an application; (3) should minimize sources of error; and (4) should have few limitations. No single tool or application component surveyed has all of these characteristics. Based upon the surveyed work and other recent research in distributed systems, we have synthesized a new tool whose mechanisms have all of the desired characteristics. This paper describes our mechanism, and how we implemented it, in detail.

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Implementing a performance forecasting system for metacomputing

Cited by 91 publications

References 13 publications

Performance prediction with skeletons

Performance prediction with skeletons

A study of deadline scheduling for client-server systems on the Computational Grid

Passive, domain-independent, end-to-end message passing performance monitoring to support adaptive applications in MSHN

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