Open Access
Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
---|---|---|
Article Number | 02023 | |
Number of page(s) | 8 | |
Section | Online Computing | |
DOI | https://doi.org/10.1051/epjconf/202429502023 | |
Published online | 06 May 2024 |
- I. Bediaga et al. Framework TDR for the LHCb upgrade: technical design report. Tech. rep. LHCb-TDR-012, 2012. [Google Scholar]
- R. Aaij et al. “A comprehensive real-time analysis model at the LHCb experiment”. In: Journal of Instrumentation 14.04 (2019), P04006. doi: 10.1088/1748-0221/14/04/ P04006. [CrossRef] [Google Scholar]
- LHCb collaboration. “LHCb Upgrade GPU High Level Trigger Technical Design Report”. In: CERN-LHCC-2020-006 (2020). [Google Scholar]
- D. H. Cámpora Pérez, N. Neufeld, and A. Riscos Núñez. “Search by triplet: An efficient local track reconstruction algorithm for parallel architectures”. In: Journal of Computational Science 54 (2021), p. 101422. issn: 1877-7503. doi: https://doi.org/10. 1016/j.jocs.2021.101422. [CrossRef] [Google Scholar]
- P. Fernandez Declara et al. “A Parallel-Computing Algorithm for High-Energy Physics Particle Tracking and Decoding Using GPU Architectures”. In: IEEE Access 7 (2019), pp. 91612–91626. doi: 10.1109/ACCESS.2019.2927261. [CrossRef] [Google Scholar]
- R. Aaij et al. “Allen: A High-Level Trigger on GPUs for LHCb”. In: Computing and Software for Big Science 4.1 (2020). doi: 10.1007/s41781-020-00039-7. [Google Scholar]
- LHCb collaboration. “LHCb PID Upgrade Technical Design Report”. In: CERN-LHCC-2013-022 (2013). [Google Scholar]
- ATLAS Collaboration. “Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1”. In: The European Physical Journal C 77.7 (July 2017). doi: 10.1140/epjc/s10052-017-5004-5. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
- T. Reis for the CMS Collaboration. “Developing GPU-compliant algorithms for CMS ECAL local reconstruction during LHC Run 3 and Phase 2”. In: Journal of Physics: Conference Series 2438.1 (2023), p. 012027. doi: 10.1088/1742-6596/2438/1/012027. [CrossRef] [Google Scholar]
- Z. Chen et al. “GPU-based Clustering Algorithm for the CMS High Granularity Calorimeter”. In: EPJ Web Conf. 245 (2020). Ed. by C. Doglioni et al., p. 05005. doi: 10.1051/epjconf/202024505005. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
- N. Valls Canudas et al. “Graph Clustering: a graph-based clustering algorithm for the electromagnetic calorimeter in LHCb”. In: The European Physical Journal C 83.2 (2023), p. 179. doi: 10.1140/epjc/s10052-023-11332-1. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
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