ScienceDirect® Home Skip Main Navigation Links
You have guest access to ScienceDirect. Find out more.
 
Home
Browse
My Settings
Alerts
Help
 Quick Search
 Search tips (Opens new window)
    Clear all fields    
Performance Evaluation
Volume 60, Issues 1-4, May 2005, Pages 127-139
Performance Modeling and Evaluation of High-Performance Parallel and Distributed Systems
 
Font Size: Decrease Font Size  Increase Font Size
 Abstract - selected
Article
Purchase PDF (239 K)

Article Toolbox
 
 
 
Related Articles in ScienceDirect
View More Related Articles
 
View Record in Scopus
 
doi:10.1016/j.peva.2004.10.015    
How to Cite or Link Using DOI (Opens New Window)

Copyright © 2004 Elsevier B.V. All rights reserved.

The impact of predictive inaccuracies on execution scheduling

Purchase the full-text article



References and further reading may be available for this article. To view references and further reading you must purchase this article.

Stephen A. JarvisCorresponding Author Contact Information, E-mail The Corresponding Author, Ligang He, Daniel P. Spooner and Graham R. Nudd

High Performance Systems Group, Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK


Available online 7 December 2004.

Abstract

This paper investigates the underlying impact of predictive inaccuracies on execution scheduling, with particular reference to execution time predictions. This study is conducted from two perspectives: from that of job selection and from that of resource allocation, both of which are fundamental components in execution scheduling. A new performance metric, termed the degree of misperception, is introduced to express the probability that the predicted execution times of jobs display different ordering characteristics from their real execution times due to inaccurate prediction. Specific formulae are developed to calculate the degree of misperception in both job selection and resource allocation scenarios. The parameters which influence the degree of misperception are also extensively investigated. The results presented in this paper are of significant benefit to scheduling approaches that take into account predictive data; the results are also of importance to the application of these scheduling techniques to real-world high-performance systems.

Keywords: Performance prediction; Execution time; Scheduling; Job selection; Resource allocation; Performance evaluation

Article Outline

1. Introduction
2. An analysis of the degree of misperception
2.1. Job selection
2.2. Resource allocation
3. An evaluation of the degree of misperception
3.1. Job selection
3.2. Resource allocation
4. Conclusions
Acknowledgements
References
Vitae








Corresponding Author Contact InformationCorresponding author. Tel.: +44 2476 524258; fax: +44 2476 573024.

Performance Evaluation
Volume 60, Issues 1-4, May 2005, Pages 127-139
Performance Modeling and Evaluation of High-Performance Parallel and Distributed Systems
 
Home
Browse
My Settings
Alerts
Help
Elsevier.com (Opens new window)
About ScienceDirect  |  Contact Us  |  Information for Advertisers  |  Terms & Conditions  |  Privacy Policy
Copyright © 2008 Elsevier B.V. All rights reserved. ScienceDirect® is a registered trademark of Elsevier B.V.