Open Access
| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01307 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/epjconf/202533701307 | |
| Published online | 07 October 2025 | |
- CERN openlab 2025, accessed 19th Feb 2025, https://openlab.cern. [Google Scholar]
- G. Apollinari et al. “High-Luminosity Large Hadron Collider (HL-LHC) : Preliminary Design Report”, CERN-2015-005, (2015) https://cds.cern.ch/record/2116337?ln=en [Google Scholar]
- M. Girone et al. “CERN openlab Phase VIII Strategy”. Zenodo (2025) doi:10.5281/zenodo.14777222. [Google Scholar]
- HEPiX Benchmarking Working Group, accessed 23rd Feb 2025, https://w3.hepix.org/benchmarking.html [Google Scholar]
- D. Giordano et al. “HEPScore: A new CPU benchmark for the WLCG”, EPJ Web of Conferences 295, p. 07024 (2024), presented at the 26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023) https://doi.org/10.1051/epjconf/202429507024 [Google Scholar]
- The European High Performance Computing Joint Undertaking (EuroHPC JU), accessed 25th Feb 2025, https://eurohpc-ju.europa.eu/index_en [Google Scholar]
- The Simons Foundation, accessed 25th Feb 2025, https://www.simonsfoundation.org [Google Scholar]
- The CoE RAISE Project, accessed 25th Feb 2025, https://www.coe-raise.eu [Google Scholar]
- The SPECTRUM Project, accessed 25th Feb 2025, https://www.spectrumproject.eu [Google Scholar]
- J. Pata et al. “Improved particle-flow event reconstruction with scalable neural networks for current and future particle detectors” Commun Phys 7, 124 (2024). https://doi.org/10. 1038/s42005-024-01599-5 [Google Scholar]
- J. Pata et al. “Machine Learning for Particle Flow Reconstruction at CMS” J. Phys.: Conf. Ser. 2438 012100 (2023) https://doi.org/10.1088/1742-6596/2438/1/012100 [Google Scholar]
- J. Pata et al. “Progress towards an improved particle flow algorithm at CMS with machine learning” (2023) https://cds.cern.ch/record/2856311 [Google Scholar]
- The interTwin Project, accessed 25th Feb 2025, https://www.intertwin.eu [Google Scholar]
- Micron Technology Inc., accessed 28th Feb 2025, https://www.micron.com [Google Scholar]
- T. James, “The Level 1 Scouting system of the CMS experiment”, (2023), proceedings of 21st International Workshop on Advanced Computing and Analysis Techniques in Physics Research, Bari, It, 24 - 28 Oct 2022, https://cds.cern.ch/record/2852916 [Google Scholar]
- Oracle Corporation, accessed 28th Feb 2025, https://www.oracle.com/corporate/ [Google Scholar]
- E. Govorkova et al. “Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider”. Nat Mach Intell 4, 154–161 (2022), https://doi.org/10.1038/s42256-022-00441-3 [Google Scholar]
- Compute Express Link, 2025, https://computeexpresslink.org [Google Scholar]
- Pure Storage, accessed 24th Feb 2025, https://www.purestorage.com [Google Scholar]
- Cerabyte, accessed 24th Feb 2025, https://www.cerabyte.com [Google Scholar]
- C. Caffy et al. “EOS software evolution enabling LHC Run 3”, EPJ Web of Conf, 295, p. 01022 (2024), presented at 26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023) https://doi.org/10.1051/epjconf/202429501022 [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.