Grid5000:Home: Difference between revisions
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Key features: | Key features: | ||
* provides '''access to a large amount of resources''': 15000 cores, 800 compute-nodes grouped in homogeneous clusters, and featuring various technologies: GPU, SSD, NVMe, 10G and 25G Ethernet, Infiniband, Omni-Path | * provides '''access to a large amount of resources''': 15000 cores, 800 compute-nodes grouped in homogeneous clusters, and featuring various technologies: PMEM, GPU, SSD, NVMe, 10G and 25G Ethernet, Infiniband, Omni-Path | ||
* '''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 23:57, 11 February 2020
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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 2925 overall):
- Rémi Meunier, Thomas Carle, Thierry Monteil. Multi-core interference over-estimation reduction by static scheduling of multi-phase tasks. Real-Time Systems, 2024, pp.1--39. 10.1007/s11241-024-09427-3. hal-04689317 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
- Ali Golmakani, Mostafa Sadeghi, Xavier Alameda-Pineda, Romain Serizel. A weighted-variance variational autoencoder model for speech enhancement. ICASSP 2024 - International Conference on Acoustics Speech and Signal Processing, IEEE, Apr 2024, Seoul (Korea), South Korea. pp.1-5, 10.1109/ICASSP48485.2024.10446294. hal-03833827v2 view on HAL pdf
- Miguel Felipe Silva Vasconcelos. Strategies for operating and sizing low-carbon cloud data centers. Other cs.OH. Université Grenoble Alpes 2020-..; Universidade de São Paulo (Brésil), 2023. English. NNT : 2023GRALM093. tel-04678116 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 |