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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]]
- internal Administration
Direct access to resources for {{{1}}}'s site:
- reservation state (monika) and reservation history (drawgantt) via OAR
- available resources via Ganglia
- critical services via Nagios
- opened bugs via BugZilla
- support-staff via mail
Shortcuts to global tools and informations:
- support procedures to report bugs or ask for enhancements
- global reservation state and global reservation history via OARgrid.
- registered users via UMS
Latest updated publications Five random publications that benefited from Grid'5000 (at least 2932 overall):
- Volodia Parol-Guarino, Nikos Parlavantzas. Auction-based Placement of Function Chains in the Fog at Scale. Europar 2025 - 31st International European Conference on Parallel and Distributed Computing, Aug 2025, Dresden, Germany. pp.1-14. hal-05121317 view on HAL pdf
- Barbara Gendron, Gaël Guibon. SEC : contexte émotionnel phrastique intégré pour la reconnaissance émotionnelle efficiente dans la conversation. 35èmes Journées d'Études sur la Parole (JEP 2024) 31ème Conférence sur le Traitement Automatique des Langues Naturelles (TALN 2024) 26ème Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RECITAL 2024), Jul 2024, Toulouse, France. pp.219-233. hal-04623019 view on HAL pdf
- Maxime Gonthier, Samuel Thibault, Loris Marchal. A generic scheduler to foster data locality for GPU and out-of-core task-based applications. 2024. hal-04146714v2 view on HAL pdf
- Cherif Latreche, Nikos Parlavantzas, Hector A Duran-Limon. FoRLess: A Deep Reinforcement Learning-based approach for FaaS Placement in Fog. UCC 2024 - 17th IEEE/ACM International Conference on Utility and Cloud Computing, Dec 2024, Sharjah, United Arab Emirates. pp.1-9. hal-04791252 view on HAL pdf
- Rahma Hellali, Zaineb Chelly Dagdia, Karine Zeitouni. A Multi-Objective Multi-Agent Interactive Deep Reinforcement Learning Approach for Feature Selection. International conference on neural information processing, Dec 2024, Auckland (Nouvelle Zelande), New Zealand. pp.15. hal-04723314 view on HAL pdf
Latest updated experiments {{#experiments: 5|{{{1}}}}}
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