Grid5000:Home

Grid'5000 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 and Big Data and AI. Key features: provides access to a large amount of resources: 15000 cores, 800 compute-nodes grouped in homogeneous clusters, and featuring various technologies: PMEM, GPU, SSD, NVMe, 10G and 25G Ethernet, Infiniband, Omni-Path 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. Grid'5000 is merging with FIT to build the SILECS Infrastructure for Large-scale Experimental Computer Science. Read an Introduction to SILECS (April 2018) Recently published documents and presentations: Presentation of Grid'5000 (April 2019) Report from the Grid'5000 Science Advisory Board (2018) Older documents: Slides from Frederic Desprez's keynote at IEEE CLUSTER 2014 Report from the Grid'5000 Science Advisory Board (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 2026-05-25 05:11): 7 current events, 1 planned (details)

Random pick of publications

Five random publications that benefited from Grid'5000 (at least 2945 overall):

• 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
• Jolyne Gatt, Maël Madon, Georges da Costa. Digital sufficiency behaviors to deal with intermittent energy sources in a data center. ICT4S 2024: International Conference on ICT for Sustainability, Jun 2024, Stockhlom, Sweden. 10.1109/ICT4S64576.2024.00015. hal-04745218 view on HAL pdf
• Dorian Goepp, Samuel Brun, Quentin Guilloteau, Olivier Richard. Un prototype de cache de métadonnées pour le passage à l'échelle de NixOS-Compose. COMPAS 2024 - Conférence francophone d'informatique en Parallélisme, Architecture et Système, Jul 2024, Nantes, France. pp.1-8. hal-04632952 view on HAL pdf
• Ophélie Renaud, Karol Desnos, Erwan Raffin, Jean-François Nezan. Multicore and Network Topology Codesign for Pareto-Optimal Multinode Architecture. EUSIPCO, EURASIP, Aug 2024, Lyon, France. pp.701-705, 10.23919/EUSIPCO63174.2024.10715023. hal-04608249 view on HAL pdf
• Pierre-François Gimenez, Jérôme Mengin. Learning Conditional Preference Networks: an Approach Based on the Minimum Description Length Principle. IJCAI 2024 - 33rd International Joint Conference on Artificial Intelligence, Aug 2024, Jeju, South Korea. pp.3395-3403, 10.24963/ijcai.2024/376. hal-04572196 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 IMT Atlantique 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 Auvergne-Rhône-Alpes Bretagne Champagne-Ardenne Provence Alpes Côte d'Azur Hauts de France Lorraine