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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: 12000 cores, 800 compute-nodes grouped in homogeneous clusters, and featuring various technologies: GPU, SSD, NVMe, 10G and 25G Ethernet, Infiniband, Omni-Path
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 (April 2019)
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 2026-04-25 06:37): 5 current events, 4 planned (details)

Random pick of publications

Five random publications that benefited from Grid'5000 (at least 2940 overall):

Sofya Dymchenko, Abhishek Purandare, Bruno Raffin. MelissaDL x Breed: Towards Data-Efficient On-line Supervised Training of Multi-parametric Surrogates with Active Learning. AI4S 2024 - 5th Workshop on artificial intelligence and machine learning for scientific applications, Nov 2024, Atlanta (Georgia), United States. pp.1-9. hal-04712480 view on HAL pdf
Wèdan Emmanuel Gnibga. Modeling and optimization of Edge infrastructures and their electrical systems. Databases cs.DB. Université de Rennes, 2024. English. NNT : 2024URENS069. tel-04967447 view on HAL pdf
Khaled Arsalane, Guillaume Pierre. Data Stream Processing Effectiveness in Heterogeneous Computing Environments. SAC 2026 - 41st ACM/SIGAPP Symposium On Applied Computing, ACM, Mar 2026, Tessaloniki, Greece. hal-05390665 view on HAL pdf
Natalia Tomashenko, Emmanuel Vincent, Marc Tommasi. Exploiting Context-dependent Duration Features for Voice Anonymization Attack Systems. Interspeech 2025, Aug 2025, Rotterdam, Netherlands. hal-05099074 view on HAL pdf
Roblex Nana Tchakoute, Claude Tadonki, Petr Dokladal, Petr Dokladal, Youssef Mesri. A Flexible Operational Framework for Energy Profiling of Programs. 2024 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW), Nov 2024, Hilo, United States. pp.12-22, 10.1109/SBAC-PADW64858.2024.00014. hal-04819054 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
Auvergne-Rhône-Alpes
Bretagne
Champagne-Ardenne
Provence Alpes Côte d'Azur
Hauts de France
Lorraine