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 2026-02-27 21:58): 5 current events, 3 planned (details)

Random pick of publications

Five random publications that benefited from Grid'5000 (at least 2937 overall):

• Jérémie Rodez, Patricia Stolf, Thierry Monteil. Placement of Distributed Machine Learning Services for AI- and Smart Grid-Enabled IoT Platforms. 2026. hal-05279358 view on HAL pdf
• Louis Roussel, François Lemaire. Deep Learning for Integro-Differential Modelling. 2025. hal-05230281 view on HAL pdf
• Alan Lira Nunes, Cristina Boeres, Lúcia Maria de A. Drummond, Laércio Lima Pilla. Optimal Time and Energy-Aware Client Selection Algorithms for Federated Learning on Heterogeneous Resources. 2024 IEEE 36th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Nov 2024, Hilo, France. pp.148-158, 10.1109/SBAC-PAD63648.2024.00021. hal-04690494v2 view on HAL pdf
• Georges da Costa, Amina Guermouche. Measurement methods sheet, WG6 Exa-Soft. Université de Toulouse; Université de bordeaux. 2025. hal-05272179 view on HAL pdf
• Cherif Latreche, Nikos Parlavantzas, Hector A Duran-Limon. FoRLess: A Deep Reinforcement Learning-based approach for FaaS Placement in Fog. UCC 2024 - 17th IEEE/ACM International Conference on Utility and Cloud Computing, Dec 2024, Sharjah, United Arab Emirates. pp.1-9. hal-04791252 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