Grid5000:Home: Difference between revisions
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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.''' | '''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.''' | ||
Revision as of 13:59, 30 November 2022
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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 2924 overall):
- Maël Madon. Digital Sufficiency in Data Centers : Studying the Impact of User Behaviors. Computer Science cs. Université de Toulouse, 2024. English. NNT : 2024TLSES046. tel-04675558 view on HAL pdf
- Thierry Garcia. Algorithmes Parallèles Asynchrones : implémentation et simulation d’applications modélisées par des équations pseudo-linéaires.. Distributed, Parallel, and Cluster Computing cs.DC. Institut National Polytechnique de Toulouse, 2024. tel-04919001 view on HAL pdf
- Mathieu Bacou. FaaSLoad: Fine-Grained Performance and Resource Measurement for Function-As-a-Service. OPODIS 2024 - 28th International Conference on Principles of Distributed Systems, Dec 2024, Lucca, Italy. pp.22:1-22:21, 10.4230/LIPIcs.OPODIS.2024.22. hal-04886267 view on HAL pdf
- Eva Giboulot, Teddy Furon. WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off. NeurIPS 2024 - 38th Conference on Neural Information Processing Systems, Dec 2024, Vancouver, Canada. pp.1-34. hal-04766606 view on HAL pdf
- Reda Khoufache, Anisse Belhadj, Mustapha Lebbah, Hanene Azzag. Distributed MCMC Inference for Bayesian Non-parametric Latent Block Model. 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, May 2024, Taipei, Taiwan. pp.271-283, 10.1007/978-981-97-2242-6_22. hal-04623748 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 |