Enabling ATLAS big data processing on Piz Daint at CSCS

Predictions for requirements for the LHC computing for Run 3 and Run 4 (HLLHC) over the course of the next 10 years show a considerable gap between required and available resources, assuming budgets will globally remain flat at best. This will require some radical changes to the computing models for...

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Main Author: Sciacca F G
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:EPJ Web of Conferences
Online Access:https://www.epj-conferences.org/articles/epjconf/pdf/2020/21/epjconf_chep2020_09005.pdf
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spelling doaj-0ab18e0834a3439293a222a73a91731e2021-08-02T15:10:41ZengEDP SciencesEPJ Web of Conferences2100-014X2020-01-012450900510.1051/epjconf/202024509005epjconf_chep2020_09005Enabling ATLAS big data processing on Piz Daint at CSCSSciacca F GPredictions for requirements for the LHC computing for Run 3 and Run 4 (HLLHC) over the course of the next 10 years show a considerable gap between required and available resources, assuming budgets will globally remain flat at best. This will require some radical changes to the computing models for the data processing of the LHC experiments. Concentrating computational resources in fewer larger and more efficient centres should increase the cost-efficiency of the operation and, thus, of the data processing. Large scale general purpose HPC centres could play a crucial role in such a model. We report on the technical challenges and solutions adopted to enable the processing of the ATLAS experiment data on the European flagship HPC Piz Daint at CSCS, now acting as a pledged WLCG Tier-2 centre. As the transition of the Tier-2 from classic to HPC resources has been finalised, we also report on performance figures over two years of production running and on efforts for a deeper integration of the HPC resource within the ATLAS computing framework at different tiers.https://www.epj-conferences.org/articles/epjconf/pdf/2020/21/epjconf_chep2020_09005.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Sciacca F G
spellingShingle Sciacca F G
Enabling ATLAS big data processing on Piz Daint at CSCS
EPJ Web of Conferences
author_facet Sciacca F G
author_sort Sciacca F G
title Enabling ATLAS big data processing on Piz Daint at CSCS
title_short Enabling ATLAS big data processing on Piz Daint at CSCS
title_full Enabling ATLAS big data processing on Piz Daint at CSCS
title_fullStr Enabling ATLAS big data processing on Piz Daint at CSCS
title_full_unstemmed Enabling ATLAS big data processing on Piz Daint at CSCS
title_sort enabling atlas big data processing on piz daint at cscs
publisher EDP Sciences
series EPJ Web of Conferences
issn 2100-014X
publishDate 2020-01-01
description Predictions for requirements for the LHC computing for Run 3 and Run 4 (HLLHC) over the course of the next 10 years show a considerable gap between required and available resources, assuming budgets will globally remain flat at best. This will require some radical changes to the computing models for the data processing of the LHC experiments. Concentrating computational resources in fewer larger and more efficient centres should increase the cost-efficiency of the operation and, thus, of the data processing. Large scale general purpose HPC centres could play a crucial role in such a model. We report on the technical challenges and solutions adopted to enable the processing of the ATLAS experiment data on the European flagship HPC Piz Daint at CSCS, now acting as a pledged WLCG Tier-2 centre. As the transition of the Tier-2 from classic to HPC resources has been finalised, we also report on performance figures over two years of production running and on efforts for a deeper integration of the HPC resource within the ATLAS computing framework at different tiers.
url https://www.epj-conferences.org/articles/epjconf/pdf/2020/21/epjconf_chep2020_09005.pdf
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