Grid5000:Home: Difference between revisions
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* [[Media:Grid5000.pdf|Presentation of Grid'5000]] (April 2019) | * [[Media:Grid5000.pdf|Presentation of Grid'5000]] (April 2019) | ||
* [https://www.grid5000.fr/mediawiki/images/Grid5000_science-advisory-board_report_2018.pdf Report from the Grid'5000 Science Advisory Board (2018)] | * [https://www.grid5000.fr/mediawiki/images/Grid5000_science-advisory-board_report_2018.pdf Report from the Grid'5000 Science Advisory Board (2018)] | ||
* Grid'5000 is merging with FIT to build the SILECS Infrastructure for Large-scale Experimental Computer Science. Read [http://www.silecs.net/wp-content/uploads/2018/04/Desprez-SILECS.pdf an Introduction to SILECS] (April 2018) | * Grid'5000 is merging with FIT to build the SILECS Infrastructure for Large-scale Experimental Computer Science. Read [http://www.silecs.net/wp-content/uploads/2018/04/Desprez-SILECS.pdf an Introduction to SILECS] (April 2018) or visit the [http://www.silecs.net/ SILECS website]. | ||
Older documents: | Older documents: | ||
Revision as of 08:44, 24 May 2019
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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 3047 overall):
- Thomas Stavis, Laurent Lefèvre, Anne-Cécile Orgerie. Intel RAPL - Ses impacts sur l’infrastructure et son utilisation comme levier énergétique. 2026. hal-05548910 view on HAL pdf
- Mathieu Bacou. FaaSLoad : fine-grained performance and resource measurement for function-as-a-service. 2024. hal-04836444 view on HAL pdf
- Rahma Hellali, Zaineb Chelly Dagdia, Karine Zeitouni. Variables Selection using a Novel Interactive Deep Reinforcement Learning Approach. Extraction et Gestion des Connaissances (EGC) 2025, Jan 2025, Strasbourg, France. hal-05333566 view on HAL pdf
- Ricky Walsh, Prabhjot Kaur, Davood Karimi, Anne Kerbrat, Simon K Warfield, et al.. LesionSCynth: A simple parametric lesion synthesis method to improve spinal cord lesion segmentation in low-data scenarios. Imaging Neuroscience, 2025. hal-05121315 view on HAL pdf
- Louis Roussel. Integral equations modelling and deep learning. Machine Learning cs.LG. Université de Lille, 2025. English. NNT : 2025ULILB033. tel-05567799v2 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 |
