Grid5000:Home: Difference between revisions
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Key features: | 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 | * '''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 00:57, 12 February 2020
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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:
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:
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Random pick of publications
Five random publications that benefited from Grid'5000 (at least 3009 overall):
- Houssem Ouertatani. Efficient Deep Neural Architecture Search via Bayesian Optimization : An application to Computer Vision. Computer Vision and Pattern Recognition cs.CV. Université de Lille, 2024. English. NNT : 2024ULILB044. tel-05014154 view on HAL pdf
- Guillaume Méroué, Fabien Gandon, Pierre Monnin. Prédiction ou perdition de liens : les graines de l'instabilité dans les plongements de graphes de connaissances. IC2026 - 37es journées de l’Ingénierie des Connaissances, Jul 2026, Arras, France. hal-05646323 view on HAL pdf
- François Lemaire, Louis Roussel. Deep Learning for Integro-Differential Modelling. RISC Proceedings on Symbolic Computation and Machine Learning, Johannes Kepler Universität Linz, 2026, Mar 2026, Hagenberg Castle, Austria. 10.35011/risc-proceedings-scml.2. hal-05230281v3 view on HAL pdf
- Mathis Valli, Loïc Cudennec, Alexandru Costan, Cédric Tedeschi, Gabriel Antoniu. Evaluating Federated Learning Beyond Simulation: A Deployment-Aware Methodology. CCGrid 2026 - IEEE 26th International Symposium on Cluster, Cloud and Internet Computing, IEEE, May 2026, Sydney, Australia. hal-05477787v2 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. 10.1145/3748522.3779774. hal-05390665 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
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CNRS
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UniversitiesUniversité Grenoble Alpes, Grenoble INP |
Regional councilsAquitaine |
