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Abstract

Due to the increase of data volumes expected for the LHC Run 3 and Run 4, the ALICE Collaboration designed and deployed a new, energy efficient, computing model to run Online and Offline O\(^2\) data processing within a single software framework. The ALICE O\(^2\) Event Processing Nodes (EPN) project performs online data reconstruction using GPUs (Graphic Processing Units) instead of CPUs and applies an efficient, entropy-based, online data compression to cope with PbPb collision data at a 50 kHz hadronic interaction rate. Also, the O\(^2\) EPN farm infrastructure features an energy efficient, environmentally friendly, adiabatic cooling system which allows for operational and capital cost savings.

Details

1009240
Title
Efficient high performance computing with the ALICE Event Processing Nodes GPU-based farm
Publication title
arXiv.org; Ithaca
Publication year
2024
Publication date
Dec 18, 2024
Section
High Energy Physics - Experiment
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2024-12-19
Milestone dates
2024-12-18 (Submission v1)
Publication history
 
 
   First posting date
19 Dec 2024
ProQuest document ID
3147267400
Document URL
https://www.proquest.com/working-papers/efficient-high-performance-computing-with-alice/docview/3147267400/se-2?accountid=208611
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Copyright
© 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-09-12
Database
2 databases
  • ProQuest One Academic
  • ProQuest One Academic