Papaefstathiou, E., Kerbyson, D. J., Nudd, G. R. and Atherton, T. J. (1994) An analysis of processor resource models for use in performance prediction. University of Warwick. Department of Computer Science. (Department of Computer Science research report). (Unpublished)

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Abstract

With the increasing sophistication of both software and hardware systems, methodologies to analyse and predict system performance is a topic of vital interest. This is particularly true for parallel systems where there is currently a wide choice of both architectural and parallelisation options; and where the costs are likely to be high. Performance data is vital to a diffuse range of users including; system developers, application programmers and tuning experts. However, the level of sophistication and accuracy required by each of these users is substantially different. In this paper characterisation based technique is described (considering both application and hardware resources) which addresses these issues directly. Initially, a framework is described for characterisation based approaches. A classification scheme is used to illustrate differences in the level of sophistication and detail in which the underlying resource models are specified. Finally, verification is provided of the characterisation techniques applied to several application kernels on a MIMD system. The performance predictions and error bounds resulting from the level of resource specification are also discussed.

Item Type:	Report
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions:	Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH):	Parallel processing (Electronic computers)
Series Name:	Department of Computer Science research report
Publisher:	University of Warwick. Department of Computer Science
Official Date:	1994
Dates:	Date Event 1994 Completion
Number:	Number 279
Number of Pages:	22
DOI:	CS-RR-279
Institution:	University of Warwick
Theses Department:	Department of Computer Science
Status:	Not Peer Reviewed
Publication Status:	Unpublished
Funder:	European Strategic Programme of Research and Development in Information Technology (ESPRIT)
Grant number:	6942 (ESPRIT)
Related URLs:	Organisation

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