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):
- Cédric Prigent. Towards Efficient and Trustworthy Federated Learning on the Computing Continuum. Machine Learning cs.LG. INSA de Rennes, 2025. English. NNT : 2025ISAR0003. tel-05279213 view on HAL pdf
- Eric Maisonnave. NEMO performance on NVIDIA Grace Superchip. Sorbonne université. 2026, pp.9. hal-05698565 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
- Thomas Morin, Nathalie Furmento, Abdou Guermouche, Samuel Thibault, Pierre-André Wacrenier. Longest-Path-Based Task Splitting for Homogeneous Platforms. PPAM 2026 - International Conference on Parallel Processing and Applied Mathematics, Aug 2026, Poznan, Poland. hal-05666815 view on HAL pdf
- Cédric Prigent, Melvin Chelli, Alexandru Costan, Loïc Cudennec, René Schubotz, et al.. Efficient Resource-Constrained Federated Learning Clustering with Local Data Compression on the Edge-to-Cloud Continuum. HiPC 2024 - 31st IEEE International Conference on High Performance Computing, Data, and Analytics, Dec 2024, Bengaluru (Bangalore), India. pp.1-11, 10.1109/HiPC62374.2024.00033. hal-04779813 view on HAL pdf
Grid'5000 sites
Current funding
INRIA |
CNRS |
UniversitiesIMT Atlantique |
Regional councilsAquitaine |