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arXiv · 2412.13755

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

Federico Ronchetti·Valentina Akishina·Edvard Andreassen·Nora Bluhme·Gautam Dange·Jan de Cuveland·Giada Erba·Hari Gaur·Dirk Hutter·Grigory Kozlov·Luboš Krčál·Sarah La Pointe·Johannes Lehrbach·Volker Lindenstruth·Gvozden Neskovic·Andreas Redelbach·David Rohr·Felix Weiglhofer·Alexander Wilhelmi
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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.

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Federico Ronchetti, Valentina Akishina, Edvard Andreassen, Nora Bluhme, Gautam Dange, Jan de Cuveland, Giada Erba, Hari Gaur, Dirk Hutter, Grigory Kozlov, Luboš Krčál, Sarah La Pointe, Johannes Lehrbach, Volker Lindenstruth, Gvozden Neskovic, Andreas Redelbach, David Rohr, Felix Weiglhofer, Alexander Wilhelmi. 2024-12-18. Efficient high performance computing with the ALICE Event Processing Nodes GPU-based farm. https://arxiv.org/abs/2412.13755

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