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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, Omnipath, 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 and presentations:

Presentation of Grid'5000 during the 1st Grid'5000-FIT school (April 2018)
Report from the Grid'5000 Science Advisory Board (2018)
Grid'5000 is merging with FIT to build the SILECS Infrastructure for Large-scale Experimental Computer Science. Read an Introduction to SILECS (April 2018)

Older documents:

https://www.grid5000.fr/slides/2014-09-24-Cluster2014-KeynoteFD-v2.pdf Slides from Frederic Desprez's keynote at IEEE CLUSTER 2014]
Report from the Grid'5000 Science Advisory Board (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 2026-02-05 03:35): 7 current events, 4 planned (details)

Random pick of publications

Five random publications that benefited from Grid'5000 (at least 2933 overall):

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
Chaima Zoghlami, Rahim Kacimi, Riadh Dhaou. Leveraging RL for Efficient Collection of Perception Messages in Vehicular Networks. Global Information Infrastructure and Networking Symposium (GIIS 2024), Feb 2024, Dubai, United Arab Emirates. à paraître. hal-04408979 view on HAL pdf
Antoine Plin, Lorenzo Casalino, Thomas Rokicki, Ruben Salvador. Knock-Knock: Black-Box, Platform-Agnostic DRAM Address-Mapping Reverse Engineering. uASC 2026 - 2nd Microarchitecture Security Conference, Feb 2026, Leuven, Belgium. hal-05273255 view on HAL pdf
Hee-Soo Choi, Priyansh Trivedi, Mathieu Constant, Karën Fort, Bruno Guillaume. Au-delà de la performance des modèles : la prédiction de liens peut-elle enrichir des graphes lexico-sémantiques du français ?. Actes de JEP-TALN-RECITAL 2024. 31ème Conférence sur le Traitement Automatique des Langues Naturelles, volume 1 : articles longs et prises de position, Jul 2024, Toulouse, France. pp.36-49. hal-04623008 view on HAL pdf
Vania Marangozova, Angelo Gennuso. K8S Auto-Scaler Coordinators. Université Grenoble - Alpes. 2024. hal-04963348 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
Hauts de France
Lorraine

@@ Line 7: / Line 7: @@
 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
+* provides '''access to a large amount of resources''': 1000 nodes, 8000 cores, grouped in homogeneous clusters, and featuring various technologies: 10G Ethernet, Infiniband, Omnipath, 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