Grid5000:Home: Difference between revisions
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Key features: | Key features: | ||
* provides '''access to a large amount of resources''': | * provides '''access to a large amount of resources''': 12000 cores, 800 compute-nodes grouped in homogeneous clusters, and featuring various technologies: GPU, SSD, NVMe, 10G Ethernet, Infiniband, Omnipath | ||
* '''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 09:23, 18 September 2018
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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 2997 overall):
- Danilo Carastan-Santos, Georges da Costa, Igor Fontana de Nardin, Millian Poquet, Krzysztof Rzadca, et al.. Scheduling with lightweight predictions in power-constrained HPC platforms. IEEE Transactions on Parallel and Distributed Systems, 2025, pp.1-12. 10.1109/TPDS.2025.3586723. hal-04747713v3 view on HAL pdf
- Théophile Bastian. Towards automatic characterization of microarchitectural behaviour form performance modeling of computing kernels : an analysis of the Cortex A72 and Intel microarchitectures. Hardware Architecture cs.AR. Université Grenoble Alpes 2020-.., 2024. English. NNT : 2024GRALM072. tel-05116111 view on HAL pdf
- Barbara Gendron, Gaël Guibon. SEC: Context-Aware Metric Learning for Efficient Emotion Recognition in Conversation. Proceedings of the 14th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis (WASSA at ACL 2024), Aug 2024, Bangkok, Thailand. hal-04702997 view on HAL pdf
- Anna Nikiforovskaya, Claire Gardent. Evaluating Knowledge Graph-to-text Generation Models for English and Russian on Out Of Domain Data. 17th International Natural Language Generation Conference, Sep 2024, Tokyo, Japan. hal-04854968 view on HAL pdf
- Celia Mahamdi, Jonathan Lejeune, Julien Sopena, Pierre Sens, Mesaac Makpangou. OMAHA: Opportunistic Message Aggregation for pHase-based Algorithms (extended version). Formal Aspects of Computing, 2024, 36, pp.1 - 23. 10.1145/3698593. hal-05003849 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 |