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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: PMEM, 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 2025-09-13 09:08): 4 current events, 3 planned (details)

Random pick of publications

Five random publications that benefited from Grid'5000 (at least 2921 overall):

Jérôme Rouzé, Nouredine Melab, Daniel Tuyttens. A Parallel Genetic Algorithm for Qubit Mapping on Noisy Intermediate-Scale Quantum Machines. International Conference in Optimization and Learning - OLA 2024, May 2024, Dubrovnik, Croatia. hal-04916922 view on HAL pdf
Sorina Camarasu-Pop. Computational Reproducibility. 3rd cycle. 12th SLEIGHT Science Event, Saint Etienne (FR), France. 2024. hal-04649287 view on HAL pdf
Celia Mahamdi, Jonathan Lejeune, Julien Sopena, Pierre Sens, Mesaac Makpangou. OMAHA: Opportunistic Message Aggregation for pHase-based Algorithms (extended version). Formal Aspects of Computing, 2024, 36, pp.1 - 23. 10.1145/3698593. hal-05003849 view on HAL pdf
Thomas Firmin, Pierre Boulet, El-Ghazali Talbi. Parallel Hyperparameter Optimization Of Spiking Neural Networks. 2023. hal-04464394 view on HAL pdf
William Soto, Yannick Parmentier, Claire Gardent. Phylogeny-Inspired Soft Prompts For Data-to-Text Generation in Low-Resource Languages. IJCNLP-AACL 2023: The 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, ACL, Nov 2023, Bali, Indonesia. hal-04199557v2 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

@@ Line 7: / Line 7: @@
 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
+* provides '''access to a large amount of resources''': 15000 cores, 800 compute-nodes grouped in homogeneous clusters, and featuring various technologies: PMEM, 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