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Cluster Workload Analytics Revisited

Abstract : Community compute clusters are now common in big organizations such as in universities and industries. These are excellent targets for analyzing resource usage and failure events because of the diverse user base and corresponding diversity of workloads. We introduce an public repository that hosts such rich dataset and would be useful for systems and dependability research communities. In this paper, we discuss our goals, provide details of the dataset, and present some statistical analysis.
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https://hal.archives-ouvertes.fr/hal-01316530
Contributor : Matthieu Roy <>
Submitted on : Tuesday, May 17, 2016 - 11:51:38 AM
Last modification on : Saturday, November 25, 2017 - 1:56:01 PM
Long-term archiving on: : Thursday, August 18, 2016 - 10:14:11 AM

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Subrata Mitra, Suhas Javagal, Todd Gamblin, Adam Moody, Stephen Harrell, et al.. Cluster Workload Analytics Revisited. Fast Abstract in the 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, Jun 2016, Toulouse, France. ⟨hal-01316530⟩

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