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Predictive performance modelling of parallel component compositions

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Abstract

Large-scale scientific computing applications frequently make use of closely-coupled distributed parallel components. The performance of such applications is therefore dependent on the component parts and their interaction at run-time. This paper describes a methodology for predictive performance modelling and evaluation of parallel applications composed of multiple interacting components. In this paper, the fundamental steps and required operations involved in the modelling and evaluation process are identified—including component decomposition, component model combination, M×N communication modelling, dataflow analysis and overall performance evaluation. A case study is presented to illustrate the modelling process and the methodology is verified through experimental analysis.

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Authors and Affiliations

  1. High Performance Systems Group, Department of Computer Science, University of Warwick, Coventry, UK

    Lei Zhao & Stephen A. Jarvis

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  1. Lei Zhao
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  2. Stephen A. Jarvis
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Correspondence to Lei Zhao.

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Zhao, L., Jarvis, S.A. Predictive performance modelling of parallel component compositions. Cluster Comput 10, 155–166 (2007). https://doi.org/10.1007/s10586-007-0010-2

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