Grid5000:Home: Difference between revisions
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* 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
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 2922 overall):
- Josefine Umlauft, Christopher W. Johnson, Philippe Roux, Daniel Taylor Trugman, Albanne Lecointre, et al.. Mapping Glacier Basal Sliding Applying Machine Learning. Journal of Geophysical Research: Earth Surface, 2023, 128 (11), 10.1029/2023JF007280. insu-04604354 view on HAL pdf
- Geo Johns Antony, Marie Delavergne, Adrien Lebre, Matthieu Rakotojaona Rainimangavelo. Thinking out of replication for geo-distributing applications: the sharding case. ICFEC 2024: 8th IEEE International Conference on Fog and Edge Computing, May 2024, Philadelphia, United States. pp.1-8, 10.1109/ICFEC61590.2024.00019. hal-04522961 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
- Mathis Valli, Alexandru Costan, Cédric Tedeschi, Loïc Cudennec. Towards Efficient Learning on the Computing Continuum: Advancing Dynamic Adaptation of Federated Learning. FlexScience 2024 - 14th Workshop on AI and Scientific Computing at Scale using Flexible Computing Infrastructures, Jun 2024, Pisa, Italy. pp.42-49, 10.1145/3659995.3660042. hal-04698619v2 view on HAL pdf
- William Mocaër, Eric Anquetil, Richard Kulpa. Early gesture detection in untrimmed streams: A controlled CTC approach for reliable decision-making. Pattern Recognition, 2024, pp.110733. 10.1016/j.patcog.2024.110733. hal-04634678 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 |