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Specific informations of {{{1}}}'s site:

  • [[{{{1}}}:Hardware|Hardware]]
  • [[{{{1}}}:Network|Network]]
  • [[{{{1}}}:Storage|Storage]]
  • [[{{{1}}}:External access|External access]]
  • [[{{{1}}}:People|People]]
  • Administration

Direct access to resources for {{{1}}}'s site:

Shortcuts to global tools and informations:

Latest updated publications Five random publications that benefited from Grid'5000 (at least 3000 overall):

  • Ndeye-Emilie Mbengue, Pierre Monnin, Miguel Couceiro, Fabien Gandon. Which Are the Low-Resource Languages of the Semantic Web?. ESWC 2026 - 23rd European Semantic Web Conference, May 2026, Dubrovnik, Croatia. hal-05607932 view on HAL pdf
  • Cédric Prigent. Towards Efficient and Trustworthy Federated Learning on the Computing Continuum. Machine Learning cs.LG. INSA de Rennes, 2025. English. NNT : 2025ISAR0003. tel-05279213 view on HAL pdf
  • Alan Lira Nunes, Cristina Boeres, Lúcia Maria de A. Drummond, Laércio Lima Pilla. Optimal Time and Energy-Aware Client Selection Algorithms for Federated Learning on Heterogeneous Resources. 2024 IEEE 36th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Nov 2024, Hilo, France. pp.148-158, 10.1109/SBAC-PAD63648.2024.00021. hal-04690494v2 view on HAL pdf
  • Danilo Carastan-Santos, Georges da Costa, Igor Fontana de Nardin, Millian Poquet, Krzysztof Rzadca, et al.. Scheduling with lightweight predictions in power-constrained HPC platforms. IEEE Transactions on Parallel and Distributed Systems, 2025, pp.1-12. 10.1109/TPDS.2025.3586723. hal-04747713v3 view on HAL pdf
  • Cédric Prigent, Melvin Chelli, Alexandru Costan, Loïc Cudennec, René Schubotz, et al.. Efficient Resource-Constrained Federated Learning Clustering with Local Data Compression on the Edge-to-Cloud Continuum. HiPC 2024 - 31st IEEE International Conference on High Performance Computing, Data, and Analytics, Dec 2024, Bengaluru (Bangalore), India. pp.1-11, 10.1109/HiPC62374.2024.00033. hal-04779813 view on HAL pdf

Latest updated experiments {{#experiments: 5|{{{1}}}}}

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