Template:Site description
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:
- 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 3048 overall):
- Matthieu Simonin, Anne-Cécile Orgerie. Méthodologies de calcul d'empreinte carbone sur une plateforme de calcul : exemple du site Grid'5000 de Rennes. JRES 2024 - Journées réseaux de l'enseignement et de la recherche, Renater, Dec 2024, Rennes, France. pp.1-14. hal-04893984 view on HAL pdf
- Rahma Hellali, Zaineb Chelly Dagdia, Karine Zeitouni. Variables Selection using a Novel Interactive Deep Reinforcement Learning Approach. Extraction et Gestion des Connaissances (EGC) 2025, Jan 2025, Strasbourg, France. hal-05333566 view on HAL pdf
- Sofya Dymchenko, Abhishek Purandare, Bruno Raffin. MelissaDL x Breed: Towards Data-Efficient On-line Supervised Training of Multi-parametric Surrogates with Active Learning. AI4S 2024 - 5th Workshop on artificial intelligence and machine learning for scientific applications, Nov 2024, Atlanta (Georgia), United States. pp.1-9. hal-04712480 view on HAL pdf
- Karina Pats, Igor Glukhov, Stepan Petrosian, Maria Mamaeva, Alexey Sergushichev, et al.. GEODES: Geometric Descriptors for the Assessment of Global and Local Flexibility of Proteins During Molecular Dynamics Simulation. IEEE Access, 2025, 13, pp.64259-64270. 10.1109/ACCESS.2025.3558781. hal-05063673 view on HAL pdf
- François Lemaire, Louis Roussel. Deep Learning for Integro-Differential Modelling. RISC Proceedings on Symbolic Computation and Machine Learning, Johannes Kepler Universität Linz, 2026, Mar 2026, Hagenberg Castle, Austria. 10.35011/risc-proceedings-scml.2. hal-05230281v3 view on HAL pdf
Latest updated experiments {{#experiments: 5|{{{1}}}}}
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