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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2020-01-01
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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 |
work_keys_str_mv |
AT sciaccafg enablingatlasbigdataprocessingonpizdaintatcscs |
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1721230768431169536 |