Grid5000:Home: Difference between revisions
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Key features: | Key features: | ||
* provides '''access to a large amount of resources''': | * 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 Ethernet, Infiniband, Omnipath | ||
* '''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 | * '''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 | * '''advanced monitoring and measurement features for traces collection of networking and power consumption''', providing a deep understanding of experiments | ||
Revision as of 09:23, 18 September 2018
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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:
Older documents:
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Random pick of publications
Five random publications that benefited from Grid'5000 (at least 3000 overall):
- Simon Lambert, Vladimir Ostapenco, Laurent Lefèvre, Eddy Caron, Anne-Cécile Orgerie, et al.. Revisiting virtual machine consolidation to save resources and energy in heterogeneous production cloud infrastructures. International Journal of High Performance Computing Applications, 2025, 10.1177/10943420251399694. hal-05457159 view on HAL pdf
- Nasser-Eddine Monir, Paul Magron, Romain Serizel. A Phoneme-Scale Assessment of Multichannel Speech Enhancement Algorithms. Trends in Hearing, 2024, 28, 10.1177/23312165241292205. hal-04854449 view on HAL pdf
- Samuel Pélissier, Abhishek Kumar Mishra, Mathieu Cunche, Vincent Roca, Didier Donsez. Efficiently linking LoRaWAN identifiers through multi-domain fingerprinting. Pervasive and Mobile Computing, 2025, 112, pp.102082. 10.1016/j.pmcj.2025.102082. hal-05120767 view on HAL pdf
- Thomas Bouvier. Distributed Rehearsal Buffers for Continual Learning at Scale. Machine Learning cs.LG. INSA de Rennes, 2024. English. NNT : 2024ISAR0011. tel-04986111 view on HAL pdf
- Jérémie Rodez, Patricia Stolf, Thierry Monteil. Placement of Distributed Machine Learning Services for AI- and Smart Grid-Enabled IoT Platforms. 2026. hal-05279358 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 |
UniversitiesUniversité Grenoble Alpes, Grenoble INP |
Regional councilsAquitaine |