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Execution data logs of a supercomputer workload over its extended lifetime.

Manuel Rodríguez-Pascual1, Antonio J Rubio-Montero1, José A Moríñigo1

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Data in Brief
|January 8, 2020
PubMed
Summary

This research presents logged usage data from the Euler supercomputer at CIEMAT (Centre for Energy, Environment, and Technology Research) between 2008 and 2018. The open-access Parallel Workload Archive data enables new computer science research opportunities.

Keywords:
Cluster computingComputer scienceHPC infrastructureParallel workload archive

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Area of Science:

  • Computer Science
  • High-Performance Computing
  • Data Science

Background:

  • The Euler cluster at CIEMAT (Centre for Energy, Environment, and Technology Research) has generated extensive usage logs.
  • Understanding cluster usage patterns is crucial for resource optimization and performance analysis.

Purpose of the Study:

  • To document and provide open access to the logged usage data of the Euler cluster.
  • To facilitate new research avenues in computer science by making historical performance data available.

Main Methods:

  • Data collection from the Euler cluster's operational logs.
  • Data organization and archiving in the Parallel Workload Archive (PWA) format.
  • Ensuring open accessibility of the dataset through repositories.

Main Results:

  • A comprehensive dataset of Euler cluster usage from November 2008 to March 2018 is now available.
  • The data is formatted according to the Parallel Workload Archive standards.
  • The dataset is publicly accessible via the PWA repository and Mendeley Data.

Conclusions:

  • The release of the Euler cluster usage data opens up significant opportunities for research in areas such as workload characterization, performance modeling, and resource management.
  • Open access to high-performance computing data promotes reproducibility and innovation in the scientific community.