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 23:57, 11 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 2925 overall):
- Marc Jourdan, Clémence Réda. An Anytime Algorithm for Good Arm Identification. 2024. hal-04688141 view on HAL pdf
- Adrien Berthelot, Eddy Caron, Mathilde Jay, Laurent Lefèvre. Estimating the environmental impact of Generative-AI services using an LCA-based methodology. CIRP LCE 2024 - 31st Conference on Life Cycle Engineering, Jun 2024, Turin, Italy. pp.1-10. hal-04346102v2 view on HAL pdf
- Louis Roussel, François Lemaire. Deep Learning for Integro-Differential Modelling. 2025. hal-05230281 view on HAL pdf
- Volodia Parol-Guarino, Nikos Parlavantzas. GIRAFF: Reverse Auction-based Placement for Fog Functions. WoSC 2023 - 9th International Workshop on Serverless Computing, Dec 2023, Bologna, Italy. pp.53-58, 10.1145/3631295.3631402. hal-04384516 view on HAL pdf
- Pierre-François Gimenez, Jérôme Mengin. Learning Conditional Preference Networks: an Approach Based on the Minimum Description Length Principle. IJCAI 2024 - 33rd International Joint Conference on Artificial Intelligence, Aug 2024, Jeju, South Korea. pp.3395-3403, 10.24963/ijcai.2024/376. hal-04572196 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 |