Efficient high performance computing with the ALICE Event Processing Nodes GPU-based farm

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) projec...

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Veröffentlicht in:	arXiv.org 2024-12
Hauptverfasser:	Ronchetti, Federico, Akishina, Valentina, Andreassen, Edvard, Bluhme, Nora, Dange, Gautam, de Cuveland, Jan, Erba, Giada, Gaur, Hari, Hutter, Dirk, Kozlov, Grigory, Krčál, Luboš, Sarah La Pointe, Lehrbach, Johannes, Lindenstruth, Volker, Neskovic, Gvozden, Redelbach, Andreas, Rohr, David, Weiglhofer, Felix, Wilhelmi, Alexander
Format:	Artikel
Sprache:	eng
Schlagworte:	Capital costs Computation Cooling systems Data compression Data processing Graphics processing units Nodes
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Beschreibung
Zusammenfassung:	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.
ISSN:	2331-8422