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 2026-06-11 15:37): 8 current events, 6 planned (details)

Random pick of publications

Five random publications that benefited from Grid'5000 (at least 2951 overall):

• Chih-Kai Huang, Guillaume Pierre. Aggregate Monitoring for Geo-Distributed Kubernetes Cluster Federations. IEEE Transactions on Cloud Computing, 2024, 12 (4), pp.1449-1462. 10.1109/TCC.2024.3482574. hal-04736577 view on HAL pdf
• Eva Giboulot, Teddy Furon. WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off. NeurIPS 2024 - 38th Conference on Neural Information Processing Systems, Dec 2024, Vancouver, Canada. pp.1-34. hal-04766606 view on HAL pdf
• Cédric Boscher, Nawel Benarba, Fatima Elhattab, Sara Bouchenak. Personalized Privacy-Preserving Federated Learning. Proceedings of the 25th International Middleware Conference, Dec 2024, Hong Kong, China. pp.454--466, 10.1145/3652892.3700785. hal-04770214 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
• Pierre Jacquet, Maxime Agusti, Eddy Caron, Camille Coti, Marcos Dias de Assuncao, et al.. Untangling GPU Power Consumption: Job-Level Inference in Cloud Shared Settings. EUROSYS 2026 - European Conference on Computer Systems, ACM, Apr 2026, Edinbourg, Ecosse, United Kingdom. 10.1145/3767295.3769333. hal-05291033 view on HAL pdf

Latest news

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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