Grid5000:Home: Difference between revisions
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Key features: | Key features: | ||
* provides '''access to a large amount of resources''': 1000 nodes, 8000 cores, grouped in homogeneous clusters, and featuring various technologies: 10G Ethernet, Infiniband, GPUs, Xeon PHI | * provides '''access to a large amount of resources''': 1000 nodes, 8000 cores, grouped in homogeneous clusters, and featuring various technologies: 10G Ethernet, Infiniband, Omnipath, GPUs, Xeon PHI | ||
* '''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 09:25, 17 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 3000 overall):
- Daniel Richards Arputharaj, Charlotte Rodriguez, Angelo Rodio, Giovanni Neglia. Green Federated Learning via Carbon-Aware Client and Time Slot Scheduling. MASCOTS 2025 - 33rd International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication System, Oct 2025, Paris, France. 10.1109/MASCOTS67699.2025.11283314. hal-05423023 view on HAL pdf
- Georges da Costa, Atom Deutsch-Filippi, Igor Fontana de Nardin, Jean-Marc Nicod, Veronika Rehn-Sonigo, et al.. Cooperative vs. non-cooperative marketplace for computing jobs to be run on geo-distributed data centers only supplied by renewable energies. Cluster Computing, 2025, 28 (10), pp.637. 10.1007/s10586-025-05300-5. hal-05239473 view on HAL pdf
- Cédric Prigent. Towards Efficient and Trustworthy Federated Learning on the Computing Continuum. Machine Learning cs.LG. INSA de Rennes, 2025. English. NNT : 2025ISAR0003. tel-05279213 view on HAL pdf
- Léo Valque. 3D Snap rounding. Computer Science cs. Université de Lorraine, 2024. English. NNT : 2024LORR0337. tel-05016163 view on HAL pdf
- Khaled Arsalane, Guillaume Pierre. Data Stream Processing Effectiveness in Heterogeneous Computing Environments. SAC 2026 - 41st ACM/SIGAPP Symposium On Applied Computing, ACM, Mar 2026, Tessaloniki, Greece. 10.1145/3748522.3779774. hal-05390665 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 |