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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 2026-06-02 20:33): 5 current events, 1 planned (details)

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

Barbara Gendron, Gaël Guibon. SEC: Context-Aware Metric Learning for Efficient Emotion Recognition in Conversation. Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis (WASSA at ACL 2024), Aug 2024, Bangkok, Thailand. hal-04702997 view on HAL pdf
Daniel Richards Arputharaj, Charlotte Rodriguez, Angelo Rodio, Giovanni Neglia. Green Federated Learning via Carbon-Aware Client and Time Slot Scheduling. MASCOTS 2025 - 33rd International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication System, Oct 2025, Paris, France. 10.1109/MASCOTS67699.2025.11283314. hal-05423023 view on HAL pdf
Pierre Neyron. R’n’R building of an experimentation platform for the Edge. Journée Datamove 2024, Jun 2024, Chichillianne, France. pp.1-12. hal-04604573 view on HAL pdf
Houssem Ouertatani. Efficient Deep Neural Architecture Search via Bayesian Optimization : An application to Computer Vision. Computer Vision and Pattern Recognition cs.CV. Université de Lille, 2024. English. NNT : 2024ULILB044. tel-05014154 view on HAL pdf
Cédric Prigent, Melvin Chelli, Alexandru Costan, Loïc Cudennec, René Schubotz, et al.. Efficient Resource-Constrained Federated Learning Clustering with Local Data Compression on the Edge-to-Cloud Continuum. HiPC 2024 - 31st IEEE International Conference on High Performance Computing, Data, and Analytics, Dec 2024, Bengaluru (Bangalore), India. pp.1-11, 10.1109/HiPC62374.2024.00033. hal-04779813 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