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Grid'5000

Grid'5000 is a large-scale and versatile testbed for experiment-driven research in all areas of computer science, with a focus on parallel and distributed computing including Cloud, HPC and Big Data.

Key features:

provides access to a large amount of resources: 1000 nodes, 8000 cores, grouped in homogeneous clusters, and featuring various technologies: 10G Ethernet, Infiniband, GPUs, Xeon PHI
highly reconfigurable and controllable: researchers can experiment with a fully customized software stack thanks to bare-metal deployment features, and can isolate their experiment at the networking layer
advanced monitoring and measurement features for traces collection of networking and power consumption, providing a deep understanding of experiments
designed to support Open Science and reproducible research, with full traceability of infrastructure and software changes on the testbed
a vibrant community of 500+ users supported by a solid technical team

Read more about our teams, our publications, and the usage policy of the testbed. Then get an account, and learn how to use the testbed with our Getting Started tutorial and the rest of our Users portal.

Recently published documents:

Grid'5000 is supported by a scientific interest group (GIS) hosted by Inria and including CNRS, RENATER and several Universities as well as other organizations. Inria has been supporting Grid'5000 through ADT ALADDIN-G5K (2007-2013), ADT LAPLACE (2014-2016), and IPL HEMERA (2010-2014).

Current status (at 2026-09-27 04:08): 8 current events, 5 planned (details)

Five random publications that benefited from Grid'5000 (at least 3009 overall):

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
Louis Roussel. Integral equations modelling and deep learning. Machine Learning cs.LG. Université de Lille, 2025. English. NNT : 2025ULILB033. tel-05567799v2 view on HAL pdf
Mathis Valli, Loïc Cudennec, Alexandru Costan, Cédric Tedeschi, Gabriel Antoniu. Evaluating Federated Learning Beyond Simulation: A Deployment-Aware Methodology. CCGrid 2026 - IEEE 26th International Symposium on Cluster, Cloud and Internet Computing, IEEE, May 2026, Sydney, Australia. hal-05477787v2 view on HAL pdf
Albert d'Aviau de Piolant, Hayfa Tayeb, Bérenger Bramas, Mathieu Faverge, Abdou Guermouche, et al.. Improving energy efficiency of HPC applications using unbalanced GPU power capping. HCW (Ipdps workshop), Jun 2025, Milan (Italie), Italy. hal-04883872v2 view on HAL pdf
Maxime Agusti, Eddy Caron, Benjamin Fichel, Laurent Lefèvre, Olivier Nicol, et al.. PPEM-BM: Portable Power Estimation Methodology for Bare Metal Servers. ICPADS 2025 - 31st IEEE International Conference on Parallel and Distributed Systems, Dec 2025, Hefei, China. pp.1-8. hal-05365793 view on HAL pdf

Latest news

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Grid'5000 sites

Current funding

As from June 2008, Inria is the main contributor to Grid'5000 funding.

INRIA

CNRS

Universities

Université Grenoble Alpes, Grenoble INP
Université Rennes 1, Rennes
Institut National Polytechnique de Toulouse / INSA / FERIA / Université Paul Sabatier, Toulouse
Université Bordeaux 1, Bordeaux
Université Lille 1, Lille
École Normale Supérieure, Lyon

Regional councils

Aquitaine
Bretagne
Champagne-Ardenne
Provence Alpes Côte d'Azur
Nord Pas de Calais
Lorraine