Grid5000:Home
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Grid'5000 is a precursor infrastructure of SLICES-FR, the French node of SLICES-RI, Scientific Large Scale Infrastructure for Computing/Communication Experimental Studies.
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Grid'5000 is a large-scale and flexible testbed for experiment-driven research in all areas of computer science, with a focus on parallel and distributed computing, including Cloud, HPC, Big Data and AI. Key features:
Older documents:
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Most recent news
Dear users, We are pleased to announce that Debian 13 (Trixie) std environment is now the default environment on most nodes. See `kaenv3...
Dear users, The default standard environment has changed to Debian 13 for some selected clusters over the past few weeks. Here the... Hello everyone, Let's start with a quick TLDR, details on the rationale and implementation are available below: new modules will be avail...
Recently, we have observed a critical increase in resource consumption (CPU and memory) on these nodes. This is primarily caused by VS Code Serv... |
Random pick of publications
Five random publications that benefited from Grid'5000 (at least 3009 overall):
- Alexandre Sabbadin, Tom Guérout. Towards a Classification of Edge Service Orchestration Strategies Integrating Renewable Energy. 22nd International Conference on Service-Oriented Computing (ICSOC 2024), Dec 2024, Tunis (Tunisie), Tunisia. hal-05010531 view on HAL pdf
- Chih-Kai Huang, Guillaume Pierre. UnBound: Multi-Tenancy Management in Scalable Fog Meta-Federations. UCC 2024 - 17th IEEE/ACM International Conference on Utility and Cloud Computing, Dec 2024, Sharjah, United Arab Emirates. pp.1-11, 10.1109/UCC63386.2024.00029. hal-04760398 view on HAL pdf
- Antoine Franchini, Stéphane Girard, Anne Dutfoy. Adaptive confidence intervals for extreme quantiles from heavy-tailed distributions. Statistics and Computing, 2026, 36, pp.175. 10.1007/s11222-026-10930-9. hal-05322341v3 view on HAL pdf
- Dorssaf Sellami, Wissem Inoubli, Imed Riadh Farah, Sabeur Aridhi. Knowledge graph representation learning: a comprehensive and experimental overview. Computer Science Review, 2024, 56. hal-04853146 view on HAL pdf
- Houssem Ouertatani. Efficient Deep Neural Architecture Search via Bayesian Optimization : An application to Computer Vision. Computer Vision and Pattern Recognition cs.CV. Université de Lille, 2024. English. NNT : 2024ULILB044. tel-05014154 view on HAL pdf
Grid'5000 sites
Current funding
INRIA |
CNRS |
UniversitiesIMT Atlantique |
Regional councilsAquitaine |