Locality of sampling and diversity in parallel system workloads

Dror G. Feitelson

doi:10.1145/1274971.1274982

Locality of sampling and diversity in parallel system workloads

Dror G. Feitelson^*

^*Corresponding author for this work

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

21 Scopus citations

Abstract

Observing the workload on a computer system during a short (but not too short) time interval may lead to distributions that are significantly different from those that would be observed over much longer intervals. Rather than describing such phenomena using involved non-stationary models, we propose a simple global distribution coupled with a localized sampling process. We quantify the effect by the maximal deviation between the global distribution and the distribution as observed over a limited slice of time, and find that in real workload data from parallel supercomputers this deviation is significantly larger than would be observed at random. Likewise, we find that the workloads at different sites also differ from each other. These findings motivate the development of adaptive systems, which adjust their parameters as they learn about their workloads, and also the development of parametrized workload models that exhibit such locality of sampling, which are required in order to evaluate adaptive systems.

Original language	English
Title of host publication	Proceedings of ICS07
Subtitle of host publication	21st ACM International Conference on Supercomputing
Pages	53-63
Number of pages	11
DOIs	https://doi.org/10.1145/1274971.1274982
State	Published - 2007
Event	21st ACM International Conference on Supercomputing, ICS07 - Seattle, WA, United States Duration: 17 Jun 2007 → 21 Jun 2007

Publication series

Name	Proceedings of the International Conference on Supercomputing

Conference

Conference	21st ACM International Conference on Supercomputing, ICS07
Country/Territory	United States
City	Seattle, WA
Period	17/06/07 → 21/06/07

Bibliographical note

Funding Information:
The author would like to thank individually all the participants, from private and public organizations located in France, Switzerland and the UK, that have taken part in the research and interviews. Such support and open discussions highlighting project experiences, have substantively contributed to both match research aim and goals, and provide a handout for practical reflection and learning. The author would like also to acknowledge the help and resources provided by the University of Southampton and the allocated supervisor's contribution.

Keywords

Locality
Workload characterization
Workload modeling

Access to Document

10.1145/1274971.1274982

Cite this

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title = "Locality of sampling and diversity in parallel system workloads",

abstract = "Observing the workload on a computer system during a short (but not too short) time interval may lead to distributions that are significantly different from those that would be observed over much longer intervals. Rather than describing such phenomena using involved non-stationary models, we propose a simple global distribution coupled with a localized sampling process. We quantify the effect by the maximal deviation between the global distribution and the distribution as observed over a limited slice of time, and find that in real workload data from parallel supercomputers this deviation is significantly larger than would be observed at random. Likewise, we find that the workloads at different sites also differ from each other. These findings motivate the development of adaptive systems, which adjust their parameters as they learn about their workloads, and also the development of parametrized workload models that exhibit such locality of sampling, which are required in order to evaluate adaptive systems.",

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note = "Funding Information: The author would like to thank individually all the participants, from private and public organizations located in France, Switzerland and the UK, that have taken part in the research and interviews. Such support and open discussions highlighting project experiences, have substantively contributed to both match research aim and goals, and provide a handout for practical reflection and learning. The author would like also to acknowledge the help and resources provided by the University of Southampton and the allocated supervisor's contribution.; 21st ACM International Conference on Supercomputing, ICS07 ; Conference date: 17-06-2007 Through 21-06-2007",

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Feitelson, DG 2007, Locality of sampling and diversity in parallel system workloads. in Proceedings of ICS07: 21st ACM International Conference on Supercomputing. Proceedings of the International Conference on Supercomputing, pp. 53-63, 21st ACM International Conference on Supercomputing, ICS07, Seattle, WA, United States, 17/06/07. https://doi.org/10.1145/1274971.1274982

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KW - Workload modeling

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Locality of sampling and diversity in parallel system workloads

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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Cite this