Predictive performance modelling of parallel component composition

Lei Zhao*, Stephen A. Jarvis, Daniel P. Spooner, Graham R. Nudd

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

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

Original languageEnglish
Title of host publicationProceedings - 19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005
DOIs
Publication statusPublished - 2005
Event19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005 - Denver, CO, United States
Duration: 4 Apr 20058 Apr 2005

Publication series

NameProceedings - 19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005
Volume2005

Conference

Conference19th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2005
Country/TerritoryUnited States
CityDenver, CO
Period4/04/058/04/05

ASJC Scopus subject areas

  • Engineering(all)

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