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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) or visit the [http://www.silecs.net/ SILECS website]. | * Grid'5000 is merging with [https://fit-equipex.fr 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 10:44, 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 2993 overall):
- Mohammad Rizk, Shadi Ibrahim, Thomas Lambert. ALTOCUMULUS: Enabling Efficient Erasure Coding in IPFS. CCGrid 2026 - The 26th IEEE International Symposium on Cluster, Cloud, and Internet Computing, May 2026, Sydney, Australia. hal-05577974 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
- Alan Lira Nunes, Cristina Boeres, Lúcia Maria de A. Drummond, Laércio Lima Pilla. Optimal Time and Energy-Aware Client Selection Algorithms for Federated Learning on Heterogeneous Resources. 2024 IEEE 36th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Nov 2024, Hilo, France. pp.148-158, 10.1109/SBAC-PAD63648.2024.00021. hal-04690494v2 view on HAL pdf
- Pierre Jacquet, Maxime Agusti, Eddy Caron, Camille Coti, Marcos Dias de Assunção, et al.. Untangling GPU Power Consumption: Job-Level Inference in Cloud Shared Settings. EUROSYS 2026 - European Conference on Computer Systems, ACM, Apr 2026, Edinbourg, Ecosse, United Kingdom. pp.624-640, 10.1145/3767295.3769333. hal-05291033 view on HAL pdf
- Cherif Latreche, Nikos Parlavantzas, Hector A Duran-Limon. Do We Need Reinforcement Learning for Serverless Scheduling at the Edge? A Comparative Evaluation. 25th IEEE International Symposium on Parallel and Distributed Computing (ISPDC 2026), Jul 2026, Hambourg, Germany. hal-05626844v2 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 |