EPJ Web of Conferences (Jan 2024)

Predicting Resource Utilization Trends with Southern California Petabyte Scale Cache

  • Sim Caitlin,
  • Wu Kesheng,
  • Sim Alex,
  • Monga Inder,
  • Guok Chin,
  • Hazen Damian,
  • Würthwein Frank,
  • Davila Diego,
  • Newman Harvey,
  • Balcas Justas

DOI
https://doi.org/10.1051/epjconf/202429501044
Journal volume & issue
Vol. 295
p. 01044

Abstract

Read online

Large community of high-energy physicists share their data all around world making it necessary to ship a large number of files over wide- area networks. Regional disk caches such as the Southern California Petabyte Scale Cache have been deployed to reduce the data access latency. We observe that about 94% of the requested data volume were served from this cache, without remote transfers, between Sep. 2022 and July 2023. In this paper, we show the predictability of the resource utilization by exploring the trends of recent cache usage. The time series based prediction is made with a machine learning approach and the prediction errors are small relative to the variation in the input data. This work would help understanding the characteristics of the resource utilization and plan for additional deployments of caches in the future.