Difference between revisions of "Grid5000:Home"
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[[Image:renater5-g5k.jpg|thumbnail|250px|right|Grid'5000]] | [[Image:renater5-g5k.jpg|thumbnail|250px|right|Grid'5000]] | ||
| − | '''Grid'5000 is a large-scale and | + | '''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: | Key features: | ||
| − | * provides '''access to a large amount of resources''': | + | * 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 2143 overall):
- Raphaël Duroselle, Denis Jouvet, Irina Illina. Unsupervised regularization of the embedding extractor for robust language identification. Odyssey 2020 - The Speaker and Language Recognition Workshop, Nov 2020, Tokyo, Japan. hal-02544156 view on HAL pdf
- Zakaria Ournani, Mohammed Chakib Belgaid, Romain Rouvoy, Pierre Rust, Joël Penhoat, et al.. Taming Energy Consumption Variations in Systems Benchmarking. ICPE'2020 - 11th ACM/SPEC International Conference on Performance Engineering, Apr 2020, Edmonton, Canada. 10.1145/3358960.3379142. hal-02403379 view on HAL pdf
- Rafael Ferreira da Silva, Henri Casanova, Anne-Cécile Orgerie, Ryan Tanaka, Ewa Deelman, et al.. Characterizing, Modeling, and Accurately Simulating Power and Energy Consumption of I/O-intensive Scientific Workflows. Journal of computational science, Elsevier, 2020, 44, pp.101157. 10.1016/j.jocs.2020.101157. hal-02876736 view on HAL pdf
- Sophie Cerf. Control Theory for Computing Systems: Application to big-data cloud services & location privacy protection. Systems and Control cs.SY. UNIVERSITÉ GRENOBLE ALPES, 2019. English. tel-02272258 view on HAL pdf
- Amir Wonjiga, Sean Peisert, Louis Rilling, Christine Morin. Blockchain as a Trusted Component in Cloud SLA Verification. UCC 2019 - 12th IEEE/ACM International Conference on Utility and Cloud Computing, Dec 2019, Auckland, New Zealand. pp.93-100, 10.1145/3368235.3368872. hal-02354647v3 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
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CNRS
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UniversitiesUniversité Grenoble Alpes, Grenoble INP |
Regional councilsAquitaine |
