Open Access
Issue
EPJ Web Conf.
Volume 245, 2020
24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
Article Number 02034
Number of page(s) 7
Section 2 - Offline Computing
DOI https://doi.org/10.1051/epjconf/202024502034
Published online 16 November 2020
  1. The HEP Software Foundation, J. Albrecht et al., Computing and Software for Big Science 3, 7 (2019) [CrossRef] [Google Scholar]
  2. W. Lucas, in International Conference on Computing in High Energy and Nuclear Physics (2012), Vol. 396 [Google Scholar]
  3. D. Orbaker, in International Conference on Computing in High Energy and Nuclear Physics (2010), Vol. 219 [Google Scholar]
  4. D. Autiero et al. (NOMAD Collaboration), Nucl. Instrum. Methods Phys. Res., A 425, 188. 28 p (1998) [Google Scholar]
  5. E. Barberio et al., J. Phys. Conf. Ser. 160, 012082 (2009) [Google Scholar]
  6. M. Erdmann et al., https://arxiv.org/abs/1807.01954 [Google Scholar]
  7. V. Chekalina et al., https://arxiv.org/abs/1812.01319 [Google Scholar]
  8. M. Paganini, L. de Oliveira, B. Nachman, arXiv preprint arXiv:1705.02355 (2017) [Google Scholar]
  9. G.R. Khattak, S. Vallecorsa, F. Carminati, in 2018 25th IEEE International Conference on Image Processing (ICIP) (2018), pp. 3913–3917, ISSN 2381-8549 [CrossRef] [Google Scholar]
  10. I.J. Goodfellow et al., ArXiv e-prints (2014), 1406.2661 [Google Scholar]
  11. A. Odena, C. Olah, J. Shlens, ArXiv e-prints (2016), 1610.09585 [Google Scholar]
  12. L. de Oliveira, M. Paganini, B. Nachman, arXiv preprint arXiv:1701.05927 (2017) [Google Scholar]
  13. CERN, http://clic-study.web.cern.ch/ [Google Scholar]
  14. F. Carminati et al., in NIPS (2017), https://dl4physicalsciences.github.io/files/nips_dlps_2017_15.pdf [Google Scholar]
  15. CERN, Geant (accessed July 31, 2017), http://geant.cern.ch/ [Google Scholar]
  16. G. Khattak et al., in IEEE International Conference on Machine Learning and Applications, ICML2019 (2019) [Google Scholar]
  17. F. Chollet et al., Keras, https://github.com/fchollet/keras (2015) [Google Scholar]
  18. M. Abadi et al. (2015), software available from tensorflow.org, https://www.tensorflow.org/ [Google Scholar]
  19. J.R. Vlimant et al., in CHEP 2018 conference, in publication (2018) [Google Scholar]
  20. A. Sergeev, M.D. Balso, CoRR abs/1802.05799 (2018), 1802.05799 [Google Scholar]
  21. D. Anderson, J. Vlimant, M. Spiropulu, CoRR abs/1712.05878 (2017), 1712.05878 [Google Scholar]
  22. S. Vallecorsa et al., in High Performance Computing (2018), Vol. 11203, https://doi.org/10.1007/978-3-030-02465-9_35 [Google Scholar]
  23. J. Fernandes et al., Activity report HNSciCloud pilot phase (2018) [Google Scholar]
  24. D. Merkel, Linux J. 2014 (2014) [Google Scholar]
  25. The Kubernetes authors, [Online; accessed 31-May-2019], https://kubernetes.io/ [Google Scholar]
  26. The Kubeflow authors, [Online; accessed 31-May-2019], https://www.kubeflow.org/ [Google Scholar]
  27. G. Apollinari et al., CERN Yellow Rep. Monogr. 4, 1 (2017) [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.