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Grid'5000

Grid'5000 is a large-scale and flexible 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 and AI.

Key features:

provides access to a large amount of resources: 15000 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.

Grid'5000 is merging with FIT to build the SILECS Infrastructure for Large-scale Experimental Computer Science. Read an Introduction to SILECS (April 2018)

Recently published documents and presentations:

Presentation of Grid'5000 (April 2019)
Report from the Grid'5000 Science Advisory Board (2018)

Older 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 2025-08-25 09:42): 5 current events, 4 planned (details)

Random pick of publications

Five random publications that benefited from Grid'5000 (at least 2898 overall):

Prerak Srivastava. Realism in virtually supervised learning for acoustic room characterization and sound source localization. Machine Learning cs.LG. Université de Lorraine, 2023. English. NNT : 2023LORR0184. tel-04313405 view on HAL pdf
Gaël Vila, Emmanuel Medernach, Inés Gonzalez, Axel Bonnet, Yohan Chatelain, et al.. The Impact of Hardware Variability on Applications Packaged with Docker and Guix: a Case Study in Neuroimaging. ACM REP'24, ACM, Jun 2024, Rennes, France. pp.75-84, 10.1145/3641525.3663626. hal-04480308v2 view on HAL pdf
Romaric Pegdwende Nikiema, Marcello Traiola, Angeliki Kritikakou. Impact of Compiler Optimizations on the Reliability of a RISC-V-based Core. DFT 2024 - 37th IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, Oct 2024, Oxfordshire, United Kingdom. pp.1-1. hal-04731794 view on HAL pdf
Pierre-Étienne Polet, Ramy Fantar, Thierry Gautier. Introducing Moldable Tasks in OpenMP. IWOMP 23 - International Workshop on OpenMP, Sep 2023, Bristol, UK, United Kingdom. pp.51-65, 10.1007/978-3-031-40744-4_4. hal-04409117 view on HAL pdf
Hugo Pompougnac, Alban Dutilleul, Christophe Guillon, Nicolas Derumigny, Fabrice Rastello. Performance bottlenecks detection through microarchitectural sensitivity. Institut National de Recherche en Informatique et en Automatique (INRIA). 2024, pp.1-15. hal-04796942 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