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.
引用
收藏
页数:10
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