Efficient high performance computing with the ALICE event processing nodes GPU-based farm

被引：0

作者：

Ronchetti, Federico ^{[1
,2
]}

Akishina, Valentina ^{[3
,4
]}

Andreassen, Edvard ^{[1
]}

Bluhme, Nora ^{[3
,4
]}

Dange, Gautam ^{[3
,4
]}

de Cuveland, Jan ^{[3
,4
]}

Erba, Giada ^{[1
]}

Gaur, Hari ^{[3
,4
]}

Hutter, Dirk ^{[3
,4
]}

Kozlov, Grigory ^{[3
,4
]}

Krcal, Lubos ^{[1
]}

La Pointe, Sarah ^{[3
,4
]}

Lehrbach, Johannes ^{[3
,4
]}

Lindenstruth, Volker ^{[3
,4
,5
]}

Neskovic, Gvozden ^{[3
,4
]}

Redelbach, Andreas ^{[3
,4
]}

Rohr, David ^{[1
]}

Weiglhofer, Felix ^{[3
,4
]}

Wilhelmi, Alexander ^{[3
,4
]}

机构：

[1] European Org Nucl Res CERN, Geneva, Switzerland

[2] Ist Nazl Fis Nucl INFN, Lab Nazl Frascati, Frascati, Italy

[3] Frankfurt Inst Adv Studies, Frankfurt, Germany

[4] Goethe Univ Frankfurt, Frankfurt, Germany

[5] GSI Helmholtz Ctr, Darmstadt, Germany

来源：

FRONTIERS IN PHYSICS | 2025年 / 13卷

关键词：

scientific computing; sustainable computing; HTC; HPC; gpu; online data reconstruction and calibration; online data compression; synchronous data processing;

D O I：

10.3389/fphy.2025.1541854

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

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 Pb-Pb 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.

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页数：10

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