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Predicting Resource Utilization Trends with Southern California Petabyte Scale Cache.

Authors :
Sim, Caitlin
Wu, Kesheng
Sim, Alex
Monga, Inder
Guok, Chin
Hazen, Damian
Würthwein, Frank
Davila, Diego
Newman, Harvey
Balcas, Justas
Source :
EPJ Web of Conferences; 5/6/2024, Vol. 295, p1-9, 9p
Publication Year :
2024

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21016275
Volume :
295
Database :
Complementary Index
Journal :
EPJ Web of Conferences
Publication Type :
Conference
Accession number :
177902243
Full Text :
https://doi.org/10.1051/epjconf/202429501044