FRESCO: Open Source Data Repository for Computational Usage and Failures

By Saurabh Bagchi1, Rakesh Kumar, Rajesh Kalyanam1, Stephen Harrell, Carolyn A Ellis1, Carol Song1

1. Purdue University

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Abstract

FRESCO is a repository of performance data for scientific code execution jobs submitted to Purdue University's central computing cluster called Conte during March 2015 through June 2017.  Data in the repository can be used to identify failed jobs and analyze reasons for failure by studying the performance parameters during the job's execution on individual cluster nodes. The data comprises job submission and exit status data, resource usage data from each cluster node, outage of nodes, and libraries that are used by jobs executing on each node.

The actual dataset can be accessed through the following URL:

https://www.rcac.purdue.edu/fresco/index.html

The documentation to explain the data set is available through the following URL:

https://diagrid.org/resources/1099/download/FRESCO_Repository_Description.pdf

Sponsored by

NSF Grant No. CNS-1548114, CNS-1405906.

Cite this work

Researchers should cite this work as follows:

  • Saurabh Bagchi; Rakesh Kumar; Rajesh Kalyanam; Stephen Harrell; Carolyn A Ellis; Carol Song (2019), "FRESCO: Open Source Data Repository for Computational Usage and Failures," https://diagrid.org/resources/1093.

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