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Real-time data processing in the ALICE High Level Trigger at the LHC

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arxiv 1812.08036 v2 pith:YEZSDKJR submitted 2018-12-19 physics.ins-det

classification physics.ins-det
keywords dataalicedetectorhighlevelcollisiononlineparticles
verification ladder T0 review T1 audit T2 compute T3 formal

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abstract

At the Large Hadron Collider at CERN in Geneva, Switzerland, atomic nuclei are collided at ultra-relativistic energies. Many final-state particles are produced in each collision and their properties are measured by the ALICE detector. The detector signals induced by the produced particles are digitized leading to data rates that are in excess of 48 GB/$s$. The ALICE High Level Trigger (HLT) system pioneered the use of FPGA- and GPU-based algorithms to reconstruct charged-particle trajectories and reduce the data size in real time. The results of the reconstruction of the collision events, available online, are used for high level data quality and detector-performance monitoring and real-time time-dependent detector calibration. The online data compression techniques developed and used in the ALICE HLT have more than quadrupled the amount of data that can be stored for offline event processing.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Usage of GPUs for online and offline Reconstruction in ALICE in Run 3

    physics.ins-det 2025-02 accept novelty 5.0 of 10

    ALICE uses GPUs to process 50 kHz Pb-Pb collisions online and to accelerate offline reconstruction by 2x to 2.5x, targeting 5x with further offloads.

  2. Usage of GPUs for ALICE Run 3 Offline Reconstruction on the GRID

    physics.ins-det 2026-08 conditional novelty 4.0 of 10

    ALICE reports a 29% throughput gain from porting track model decoding and ITS tracking to GPU, and the first LHC offline reconstruction jobs on external GRID GPUs.

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