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Real-time data processing in the ALICE High Level Trigger at the LHC
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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.
Forward citations
Cited by 2 Pith papers
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Usage of GPUs for online and offline Reconstruction in ALICE in Run 3
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.
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Usage of GPUs for ALICE Run 3 Offline Reconstruction on the GRID
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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