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Sim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farm

Authors :
Berghaus Frank
Brasolin Franco
Casteels Kevin
Driemel Colson
Ebert Marcus
Leavatt-Brown Colin
Lee Chris
Love Peter
Paterson Michael
Scannicchio Diana
Seuster Rolf
Sobie Randall
Weiss-Gibbons Tahya
Source :
EPJ Web of Conferences, Vol 214, p 07021 (2019)
Publication Year :
2019
Publisher :
EDP Sciences, 2019.

Abstract

The Simulation at Point1 (Sim@P1) project was established in 2013 to take advantage of the Trigger and Data Acquisition High Level Trigger (HLT) farm of the ATLAS experiment at the LHC. The HLT farm is a significant compute resource, which is critical to ATLAS during data taking. This large compute resource is used to generate and process simulation data for the experiment when ATLAS is not recording data. The Sim@P1 system uses virtual machines, deployed by OpenStack, in order to isolate the resources from the ATLAS technical and control network. During the upcoming long shutdown in 2019 (LS2), the HLT farm including the Sim@P1 infrastructure will be upgraded. A previous paper on the project emphasized the need for “simple, reliable, and efficient tools” to quickly switch between data acquisition operation and offline processing. In this contribution we assess various options for updating and simplifying the provisional tools. Cloudscheduler is a tool for provisioning cloud resources for batch computing that has been managing cloud resources in HEP offline computing since 2012. We present the argument for choosing Cloudscheduler, and describe technical details regarding optimal utilization of the Sim@P1 re-sources.

Subjects

Subjects :
Physics
QC1-999

Details

Language :
English
ISSN :
2100014X
Volume :
214
Database :
Directory of Open Access Journals
Journal :
EPJ Web of Conferences
Publication Type :
Academic Journal
Accession number :
edsdoj.7824806b0e8b4d5f99f6d127ec14bd77
Document Type :
article
Full Text :
https://doi.org/10.1051/epjconf/201921407021