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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]]
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- [[{{{1}}}:Administration|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 2925 overall):
- Mathieu Bacou. FaaSLoad : fine-grained performance and resource measurement for function-as-a-service. 2024. hal-04836444 view on HAL pdf
- Thomas Firmin, Pierre Boulet, El-Ghazali Talbi. Asynchronous Multi-fidelity Hyperparameter Optimization Of Spiking Neural Networks. International Conference on Neuromorphic Systems (ICONS 2024), Jul 2024, Washington, United States. hal-04781629 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
- Maxime Agusti, Eddy Caron, Benjamin Fichel, Laurent Lefèvre, Olivier Nicol, et al.. PowerHeat: A non-intrusive approach for estimating the power consumption of bare metal water-cooled servers. 2024 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics, Aug 2024, Copenhagen, Denmark. pp.1-7. hal-04662683 view on HAL pdf
- Mai Huong Do, Millian Poquet, Georges da Costa. FedE-ator : A framework for energy consumption analysis of federated learning in distributed systems. Compas’2025 : Parallélisme / Architecture/ Système, Jul 2025, Bordeaux, France. hal-05181877 view on HAL pdf
Latest updated experiments {{#experiments: 5|{{{1}}}}}
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