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Optimizing access to conditions data in ATLAS event data processing

Abstract:
The processing of ATLAS event data requires access to conditions data which are stored in database systems. This data includes, for example alignment, calibration, and configuration information which may be characterized by large volumes, diverse content, and/or information which evolves over time as refinements are made in those conditions. Additional layers of complexity are added by the need to provide this information across the worldwide ATLAS computing grid and the sheer number of simultaneously executing processes on the grid, each demanding a unique set of conditions to proceed. Distributing this data to all the processes that require it in an efficient manner has proven to be an increasing challenge with the growing needs and numbers of event-wise tasks. In this presentation, we briefly describe the systems in which we have collected information about the database content and the use of conditions in event data processing. We then proceed to explain how this information has been used not only to refine reconstruction software and job configuration but also to guide modifications of underlying conditions data configuration and in some cases, rewrites of the data in the database into a more harmonious form for offline usage in the processing of both real and simulated data..
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1051/epjconf/201921404051

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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Particle Physics
Role:
Author
ORCID:
0000-0002-1259-1034


Publisher:
EDP Sciences
Host title:
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
Journal:
CHEP 2018 - 23rd International Conference on Computing in High Energy and Nuclear Physics More from this journal
Article number:
04051
Publication date:
2019-09-17
Acceptance date:
2019-02-20
DOI:
EISSN:
2100-014X


Keywords:
Pubs id:
pubs:1053909
UUID:
uuid:a0673460-7a54-49cc-8bc8-8c82bfaf792c
Local pid:
pubs:1053909
Source identifiers:
1053909
Deposit date:
2019-09-17

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