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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:
- 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):
- Philippe Ledent, Radu Mateescu, Wendelin Serwe. Testing Resource Isolation for System-on-Chip Architectures. MARS 2024 - 6th Workshop on Models for Formal Analysis of Real Systems, Apr 2024, Luxembourg, Luxembourg. pp.1-40, 10.48550/arXiv.2403.18720. hal-04573384 view on HAL pdf
- Mathieu Bacou. FaaSLoad: Fine-Grained Performance and Resource Measurement for Function-As-a-Service. OPODIS 2024 - 28th International Conference on Principles of Distributed Systems, Dec 2024, Lucca, Italy. pp.22:1-22:21, 10.4230/LIPIcs.OPODIS.2024.22. hal-04886267 view on HAL pdf
- Théophile Bastian. Towards automatic characterization of microarchitectural behaviour form performance modeling of computing kernels : an analysis of the Cortex A72 and Intel microarchitectures. Hardware Architecture cs.AR. Université Grenoble Alpes 2020-.., 2024. English. NNT : 2024GRALM072. tel-05116111 view on HAL pdf
- Quentin Guilloteau, Sophie Cerf, Raphaël Bleuse, Bogdan Robu, Eric Rutten. Under Control: A Control Theory Introduction for Computer Scientists. ACSOS 2024 - 5th IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2024), Sep 2024, Aahrus, Denmark. pp.1-10. hal-04666859 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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