Grid5000:Home

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: Slides from Frederic Desprez's keynote at IEEE CLUSTER 2014 Report from the Grid'5000 Science Advisory Board meeting (2014) 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 2026-02-08 02:14): 4 current events, 3 planned (details)

Five random publications that benefited from Grid'5000 (at least 2933 overall):

• Houssam Elbouanani, Chadi Barakat, Walid Dabbous, Thierry Turletti. Fidelity-aware Large-scale Distributed Network Emulation. Computer Networks, 2024, 10.1016/j.comnet.2024.110531. hal-04591699 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
• 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
• Emmanuel Medernach, Gaël Vila, Axel Bonnet, Sorina Camarasu-Pop. ReproVIP Report #2.1.1 Application Deployment Strategies. CREATIS Université Lyon 1. 2024. hal-04551771 view on HAL pdf
• François Lemaire, Louis Roussel. Parameter Estimation with Integral Elimination. Differential Algebra and Related Topics XII, Apr 2024, Kassel, Germany. . hal-04576171 view on HAL pdf

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Grid'5000 sites

Grenoble Lille Luxembourg

Lyon Nancy Nantes

Rennes Sophia-Antipolis Toulouse

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