EPJ Web Conf.
Volume 251, 202125th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021)
|Number of page(s)||11|
|Published online||23 August 2021|
ATLAS in-file metadata and multi-threaded processing
1 Argonne, Illinois, USA
2 CERN, Geneva, Switzerland
3 University of Warwick, Coventry, UK
4 DESY, Hamburg, Germany
5 BNL, New York, USA
6 IJCLab, Université Paris-Saclay, CNRS/IN2P3, 91405, Orsay ; France
7 LBNL, Berkeley, USA
* e-mail: firstname.lastname@example.org
** Copyright 2021 CERN for the benefit of the ATLAS Collaboration. Reproduction of this article or parts of it is allowed as specified in the CC-BY-4.0 license.
*** Argonne National Laboratory's work was supported by the U.S. Department of Energy, Office of Science, under contract DE-AC02-06CH11357.
Published online: 23 August 2021
Processing and scientific analysis of the data taken by the ATLAS experiment requires reliable information describing the event data recorded by the detector or generated in software. ATLAS event processing applications store such descriptive metadata information in the output data files along with the event information.
To better leverage the available computing resources during LHC Run3 the ATLAS experiment has migrated its data processing and analysis software to a multi-threaded framework: AthenaMT. Therefore in-file metadata must support concurrent event processing, especially around input file boundaries. The in-file metadata handling software was originally designed for serial event processing. It grew into a rather complex system over the many years of ATLAS operation. To migrate this system to the multi-threaded environment it was necessary to adopt several pragmatic solutions, mainly because of the shortage of available person-power to work on this project in early phases of the AthenaMT development.
In order to simplify the migration, first the redundant parts of the code were cleaned up wherever possible. Next the infrastructure was improved by removing reliance on constructs that are problematic during multi-threaded processing. Finally, the remaining software infrastructure was redesigned for thread safety.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.