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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:

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 2025-12-15 06:38): 7 current events, 1 planned (details)

Five random publications that benefited from Grid'5000 (at least 2924 overall):

Shashikant Ilager, Daniel Balouek, Sidi Mohammed Kaddour, Ivona Brandic. Proteus: Towards Intent-driven Automated Resource Management Framework for Edge Sensor Nodes. FlexScience'24: Proceedings of the 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures, Jun 2024, Pisa, Italy. pp.1 - 8, 10.1145/3659995.3660037. hal-04775138 view on HAL pdf
Emile Cadorel, Dimitri Saingre. A Protocol to Assess the Accuracy of Process-Level Power Models. Cluster 2024, IEEE, Sep 2024, Kobe, Japan. hal-04720926 view on HAL pdf
Mathis Valli, Alexandru Costan, Cédric Tedeschi, Loïc Cudennec. Towards Efficient Learning on the Computing Continuum: Advancing Dynamic Adaptation of Federated Learning. FlexScience 2024 - 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures, Jun 2024, Pisa, Italy. pp.42-49, 10.1145/3659995.3660042. hal-04698619v2 view on HAL pdf
Alaaeddine Chaoub. Deep learning representations for prognostics and health management. Computer Science cs. Université de Lorraine, 2024. English. NNT : 2024LORR0057. tel-04687618 view on HAL pdf
Rosa Pagano, Sophie Cerf, Bogdan Robu, Quentin Guilloteau, Raphaël Bleuse, et al.. Making Control in High Performance Computing for Overload Avoidance Adaptive in Time and Job Size. CCTA 2024 - 8th IEEE Conference on Control Technology and Applications, Aug 2024, Newcastle Upon Tyne, United Kingdom. pp.1-8. hal-04669743 view on HAL pdf

Latest news

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Grid'5000 sites

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