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

Acharya, S ; Adolfsson, Jonatan LU ; Christiansen, Peter LU ; Ljunggren, Martin LU ; Nassirpour, Adrian LU orcid ; Oskarsson, Anders LU ; Richert, Tuva LU ; Vazquez Rueda, Omar LU ; Silvermyr, David LU orcid and Stenlund, Evert LU , et al. (2019) In Computer Physics Communications 242. p.25-48
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... (More)
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. (Less)
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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Computer Physics Communications
volume
242
pages
24 pages
publisher
Elsevier
external identifiers
  • scopus:85065619163
ISSN
0010-4655
DOI
10.1016/j.cpc.2019.04.011
language
English
LU publication?
yes
id
30042080-4613-4b4c-b01a-073b0272583c
date added to LUP
2022-03-29 11:11:14
date last changed
2023-03-08 06:20:41
@article{30042080-4613-4b4c-b01a-073b0272583c,
  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.}},
  author       = {{Acharya, S and Adolfsson, Jonatan and Christiansen, Peter and Ljunggren, Martin and Nassirpour, Adrian and Oskarsson, Anders and Richert, Tuva and Vazquez Rueda, Omar and Silvermyr, David and Stenlund, Evert and Zurlo, N}},
  issn         = {{0010-4655}},
  language     = {{eng}},
  pages        = {{25--48}},
  publisher    = {{Elsevier}},
  series       = {{Computer Physics Communications}},
  title        = {{Real-time data processing in the ALICE High Level Trigger at the LHC}},
  url          = {{http://dx.doi.org/10.1016/j.cpc.2019.04.011}},
  doi          = {{10.1016/j.cpc.2019.04.011}},
  volume       = {{242}},
  year         = {{2019}},
}