Grid5000:Home: Difference between revisions
No edit summary |
No edit summary |
||
| Line 7: | Line 7: | ||
Key features: | Key features: | ||
* 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, | * 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 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 10:05, 9 November 2018
|
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:
|
Random pick of publications
Five random publications that benefited from Grid'5000 (at least 3000 overall):
- Florian Rascoussier, Romain Billot, Lina Fahed, Christine Solnon. Impact of Scaling and Rounding on Metaheuristic Performance for the Vehicle Routing Problem with Time Windows. 16th Metaheuristics International Conference, 2026, Ischia, Italy. hal-05646952 view on HAL pdf
- Georges da Costa. Hardware and application aware performance, power and energy models for modern HPC servers with DVFS. Sustainable Computing : Informatics and Systems, 2025, 46, pp.101106. 10.1016/j.suscom.2025.101106. hal-04983485 view on HAL pdf
- Sofya Dymchenko, Abhishek Purandare, Bruno Raffin. MelissaDL x Breed: Towards Data-Efficient On-line Supervised Training of Multi-parametric Surrogates with Active Learning. AI4S 2024 - 5th Workshop on artificial intelligence and machine learning for scientific applications, Nov 2024, Atlanta (Georgia), United States. pp.1-9. hal-04712480 view on HAL pdf
- Kenta Ishiguro, Fonyuy-Asheri Caleb, Elouan Barraud, Renaud Lachaize, Yérom-David Bromberg, et al.. Everything You Need to Know About Virtual Machine Live Migration Between Heterogeneous Processors. EUROSYS 2026 - 21st European Conference on Computer Systems, Apr 2026, Edimbourg, United Kingdom. 10.1145/3767295.3803609. hal-05513543v2 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
Latest news
Failed to load RSS feed from https://www.grid5000.fr/mediawiki/index.php?title=News&action=feed&feed=atom: Error parsing XML for RSS
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 |