EPJ Web Conf.
Volume 251, 202125th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021)
|Number of page(s)||11|
|Section||Distributed Computing, Data Management and Facilities|
|Published online||23 August 2021|
Evolution of ATLAS analysis workflows and tools for the HL-LHC era
1 University of Oslo, P.b. 1048 Blindern, 0316 Oslo, Norway
2 School of Physics and Astronomy, University of Manchester, Oxford Rd, Manchester, M13 9PL, UK
3 Brookhaven National Laboratory, 98 Rochester St, Upton, NY 11973, USA
4 Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, 08193 Bellaterra (Barcelona), Spain
5 Port d’Informació Científica (PIC), Campus UAB, 08913 Bellaterra (Cerdanyola del Vallès), Spain
6 Deutsches Elektronen-Synchrotron (DESY), Notkestr. 85, 22607 Hamburg, Germany
* e-mail: Alessandra.Forti@cern.ch
Published online: 23 August 2021
The High Luminosity LHC project at CERN, which is expected to deliver a ten-fold increase in the luminosity of proton-proton collisions over LHC, will start operation towards the end of this decade and will deliver an unprecedented scientific data volume of multi-exabyte scale. This vast amount of data has to be processed and analysed, and the corresponding computing facilities must ensure fast and reliable data processing for physics analyses by scientific groups distributed all over the world. The present LHC computing model will not be able to provide the required infrastructure growth, even taking into account the expected evolution in hardware technology. To address this challenge, several novel methods of how end-users analysis will be conducted are under evaluation by the ATLAS Collaboration. State-of-the-art workflow management technologies and tools to handle these methods within the existing distributed computing system are now being evaluated and developed. In addition the evolution of computing facilities and how this impacts ATLAS analysis workflows is being closely followed.
© 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.
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