Performance prediction and its use in parallel and distributed computing systems

Stephen A. Jarvis, Daniel P. Spooner, Helene N.Lim Choi Keung, Graham R. Nudd, Junwei Cao, Subhash Saini

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

5 Citations (Scopus)

Abstract

A performance prediction framework is described in which predictive data generated by the PACE toolkit is stored and published through a Globus MDS-based performance information service. Distributing this data allows additional performance-based middleware tools to be built; the paper describes two such tools, a local-level scheduler and a system for wide-area task management. Experimental evidence shows that by integrating these performance tools for local- and wide-area management, considerable improvements can be made to task scheduling, resource utilisation and load balancing on heterogeneous distributed computing systems.

Original languageEnglish
Title of host publicationProceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)0769519261, 9780769519265
DOIs
Publication statusPublished - 2003
EventInternational Parallel and Distributed Processing Symposium, IPDPS 2003 - Nice, France
Duration: 22 Apr 200326 Apr 2003

Publication series

NameProceedings - International Parallel and Distributed Processing Symposium, IPDPS 2003

Conference

ConferenceInternational Parallel and Distributed Processing Symposium, IPDPS 2003
Country/TerritoryFrance
CityNice
Period22/04/0326/04/03

Bibliographical note

Publisher Copyright:
© 2003 IEEE.

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science
  • Software

Fingerprint

Dive into the research topics of 'Performance prediction and its use in parallel and distributed computing systems'. Together they form a unique fingerprint.

Cite this