| Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
|---|---|---|
| Article Number | 04025 | |
| Number of page(s) | 8 | |
| Section | T4 - Data handling | |
| DOI | https://doi.org/10.1051/epjconf/201921404025 | |
| Published online | 17 September 2019 | |
https://doi.org/10.1051/epjconf/201921404025
Performance and impact of dynamic data placement in ATLAS
1
Ludwig-Maximilians-Universität München,
Germany
2
Universität Innsbruck,
Austria
3
CERN,
Geneva,
Switzerland
4
INFN Turin,
Italy
5
Politecnico di Torino,
Italy
6
University of Chicago,
USA
* Corresponding author: thomas.maier@physik.uni-muenchen.de
Published online: 17 September 2019
For high-throughput computing the efficient use of distributed computing resources relies on an evenly distributed workload, which in turn requires wide availability of input data that is used in physics analysis. In ATLAS, the dynamic data placement agent C3PO was implemented in the ATLAS distributed data management system Rucio which identifies popular data and creates additional, transient replicas to make data more widely and more reliably available. This proceedings presents studies on the performance of C3PO and the impact it has on throughput rates of distributed computing in ATLAS. Furthermore, results of a study on popularity prediction using machine learning techniques are presented.
© The Authors, published by EDP Sciences, 2019
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