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 2026-08-21 02:14): 8 current events, 2 planned (details)

Random pick of publications

Five random publications that benefited from Grid'5000 (at least 3000 overall):

• Cédric Prigent. Towards Efficient and Trustworthy Federated Learning on the Computing Continuum. Machine Learning cs.LG. INSA de Rennes, 2025. English. NNT : 2025ISAR0003. tel-05279213 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
• Cédric Prigent, Kate Keahey, Alexandru Costan, Loïc Cudennec, Gabriel Antoniu. On the Reproducibility Challenges of Federated Learning: Investigating the Gap between Simulation, Emulation and Real-World Deployments. CCGrid 2025 - IEEE 25th International Symposium on Cluster, Cloud and Internet Computing, May 2025, Tromso, Norway. pp.185-194, 10.1109/ccgrid64434.2025.00054. hal-04997547 view on HAL pdf
• Cherif Latreche, Nikos Parlavantzas, Hector A Duran-Limon. Do We Need Reinforcement Learning for Serverless Scheduling at the Edge? A Comparative Evaluation. 25th IEEE International Symposium on Parallel and Distributed Computing (ISPDC 2026), Jul 2026, Hambourg, Germany. hal-05626844v2 view on HAL pdf
• Alexandre Sabbadin, Tom Guérout. Towards a Classification of Edge Service Orchestration Strategies Integrating Renewable Energy. 22nd International Conference on Service-Oriented Computing (ICSOC 2024), Dec 2024, Tunis (Tunisie), Tunisia. hal-05010531 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