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A comparative study of real workload traces and synthetic workload models for parallel job scheduling

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Job Scheduling Strategies for Parallel Processing (JSSPP 1998)

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Abstract

Two basic approaches are taken when modeling workloads in simulation-based performance evaluation of parallel job scheduling algorithms: (1) a carefully reconstructed trace from a real supercomputer can provide a very realistic job stream, or (2) a flexible synthetic model that attempts to capture the behavior of observed workloads can be devised. Both approaches require that accurate statistical observations be made and that the researcher be aware of the applicability of a given trace for his or her experimental goals.

In this paper, we compare a number of real workload traces and synthetic workload models currently used to evaluate job scheduling and allocation strategies. Our results indicate that the choice of workload model alone — real workload trace versus synthetic workload models — did not significantly affect the relative performance of the algorithms in this study (two scheduling algorithms and three static processor allocation algorithms). Almost all traces and models gave the same ranking of algorithms from best to worst. However, two specific workload characteristics were found to significantly affect algorithm performance: (a) proportion of power-of-two job sizes and (b) degree of correlation between job size and job runtime. When used in the experimental evaluation of resource management algorithms, workloads differing in these two characteristics may lead to discrepant conclusions.

This research was sponsored by NSF grant MIP-9108528.

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Dror G. Feitelson Larry Rudolph

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© 1998 Springer-Verlag Berlin Heidelberg

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Lo, V., Mache, J., Windisch, K. (1998). A comparative study of real workload traces and synthetic workload models for parallel job scheduling. In: Feitelson, D.G., Rudolph, L. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP 1998. Lecture Notes in Computer Science, vol 1459. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0053979

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  • DOI: https://doi.org/10.1007/BFb0053979

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  • Online ISBN: 978-3-540-68536-4

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