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Selective preemption strategies for parallel job scheduling

Authors: Rajkumar Kettimuthu; Vijay Subramani; Srividya Srinivasan; Thiagaraja Gopalsamy; Dhabaleswar K. Panda 0001; P. Sadayappan;

Selective preemption strategies for parallel job scheduling

Abstract

Although theoretical results have been established regarding the utility of pre-emptive scheduling in reducing average job turn-around time, job suspension/restart is not much used in practice at supercomputer centers for parallel job scheduling. A number of questions remain unanswered regarding the practical utility of pre-emptive scheduling. We explore this issue through a simulation-based study, using job logs from a supercomputer center We develop a tunable selective-suspension strategy, and demonstrate its effectiveness. We also present new insights into the effect of pre-emptive scheduling on different job classes and address the impact of suspensions on worst-case slowdown.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Average
Top 10%
Average
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