Grid5000:Home: Difference between revisions
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* 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 00:57, 12 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 2998 overall):
- Roblex Nana Tchakoute, Claude Tadonki, Petr Dokladal, Petr Dokladal, Youssef Mesri. A Flexible Operational Framework for Energy Profiling of Programs. 2024 International Symposium on Computer Architecture and High Performance Computing Workshops (SBAC-PADW), Nov 2024, Hilo, United States. pp.12-22, 10.1109/SBAC-PADW64858.2024.00014. hal-04819054 view on HAL pdf
- Cherif Latreche, Nikos Parlavantzas, Hector A Duran-Limon. Do We Need Reinforcement Learning for Serverless Scheduling at the Edge? A Comparative Evaluation. 25th IEEE International Symposium on Parallel and Distributed Computing (ISPDC 2026), Jul 2026, Hambourg, Germany. hal-05626844v2 view on HAL pdf
- Thomas Stavis, Laurent Lefèvre, Anne-Cécile Orgerie. Intel RAPL - Ses impacts sur l’infrastructure et son utilisation comme levier énergétique. 2026. hal-05548910 view on HAL pdf
- Antoine Franchini, Stéphane Girard, Anne Dutfoy. Adaptive confidence intervals for extreme quantiles from heavy-tailed distributions. Statistics and Computing, 2026, 36, pp.175. hal-05322341v3 view on HAL pdf
- Neuville-Burguière Benjamin, Huet Fabrice, Baude Françoise. Latency Aware and ressource-efficient bin pack autoscaling for distributed event queues : An application to microservices architectures. Conférence francophone d'informatique en Parallélisme, Architecture et Système (COMPAS 2026), Jun 2026, Anglet, France. hal-05659911 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 |
