FRESCO: Open Source Data Repository for Computational Usage and Failures

By Saurabh Bagchi, Rakesh Kumar, Rajesh Kalyanam, Stephen Harrell, Carolyn A Ellis, Carol Song

Category

Downloads

Published on

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 actual dataset can be accessed through the following URL:

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

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 (2018), "FRESCO: Open Source Data Repository for Computational Usage and Failures," https://diagrid.org/resources/1093.

    BibTex | EndNote

Tags

  1. job submission
  2. Cluster Computing
  3. tacc_stats
  4. conte
  5. fresco
  6. hpc
  7. torque
  8. PBS