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.
- 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
- advanced monitoring and measurement features for traces collection of networking and power consumption, providing a deep understanding of experiments
- designed to support Open Science and reproducible research, with full traceability of infrastructure and software changes on the testbed
- a vibrant community of 500+ users supported by a solid technical team
Read more about our teams, our publications, and the usage policy of the testbed. Then get an account, and learn how to use the testbed with our Getting Started tutorial and the rest of our Users portal.
Grid'5000 is merging with FIT to build the SILECS Infrastructure for Large-scale Experimental Computer Science. Read an Introduction to SILECS (April 2018)
Recently published documents and presentations:
Grid'5000 is supported by a scientific interest group (GIS) hosted by Inria and including CNRS, RENATER and several Universities as well as other organizations. Inria has been supporting Grid'5000 through ADT ALADDIN-G5K (2007-2013), ADT LAPLACE (2014-2016), and IPL HEMERA (2010-2014).
Current status (at 2023-11-30 21:56)
: 1 current events, None planned (details)
Random pick of publications
Five random publications that benefited from Grid'5000 (at least 2486 overall):
- Tomer Laor, Naif Mehanna, Antonin Durey, Vitaly Dyadyuk, Pierre Laperdrix, et al.. DRAWNAPART: A Device Identification Technique based on Remote GPU Fingerprinting. Network and Distributed System Security Symposium, Feb 2022, San Diego, United States. 10.14722/ndss.2022.24093. hal-03526240 view on HAL pdf
- Ilias Benjelloun, Efoevi Angelo Koudou, Bart Lamiroy. Convolutional network fabric pruning with label noise. 2022. hal-03569057 view on HAL pdf
- Alexandre Bettinger, Armelle Brun, Anne Boyer. Influence indépendante de l'exploration et de l'exploitation : le cas des systèmes de recommandation par métaheuristiques. CNIA 2022 - Conférence Nationale en Intelligence Artificielle, Jun 2022, Saint Etienne, France. hal-03659318 view on HAL pdf
- Kadir Korkmaz, Joachim Bruneau-Queyreix, Sonia Ben Mokhtar, Laurent Réveillère. ALDER: Unlocking blockchain performance by multiplexing consensus protocols. 2022 IEEE 21st International Symposium on Network Computing and Applications (NCA), Dec 2022, Boston, United States. pp.9-18, 10.1109/NCA57778.2022.10013556. hal-03966159 view on HAL pdf
- Ali Tehranijamsaz, Mihail Popov, Akash Dutta, Emmanuelle Saillard, Ali Jannesari. Learning Intermediate Representations using Graph Neural Networks for NUMA and Prefetchers Optimization. IPDPS 2022 - 36th IEEE International Parallel & Distributed Processing Symposium, May 2022, Lyon / Virtual, France. hal-03603118 view on HAL pdf
New "edge-computing"-class nodes in Toulouse's testing queue: cluster Estats with 12 Nvidia AGX Xavier SoCs
A new cluster named "estats" is available in the testing queue of the Toulouse site, composed of 12 "Edge computing"-class nodes.
Estats is composed of 12 Nvidia AGX Xavier SoCs¹. Each SoC features:
a ARM64 CPU (Nvidia Carmel micro-arch) with 8 cores
a Nvidia GPU (Nvidia Volta micro-arch)
32 GB RAM shared between CPU and GPU
a 2TB NVMe
1 Gbps NIC
The 12 modules are packaged in a chassis manufactured by Connecttech³.
Since it is not a cluster of server-class machines (unlike all current other Grid'5000 nodes), estats runs a different default system environment. This environment includes Nvidia's Linux for Tegra² overlay on top of the Grid'5000 standard environment. This means:
a Debian 11 system like other clusters, but
a special Linux kernel,
several specific tools and services,
and several incompatible tools (e.g. Cuda).
This default environment does not include the required Tegra-specific version of Cuda.
In order to benefit from the whole Nvidia stack with e.g. the specific Cuda version and DL accelerators support for Nvidia Tegra, it is advised to deploy on the node the Nvidia-supported Ubuntu 20.04 OS with the full L4T support, using
kadeploy. You can use the
ubuntu2004-nfsl4t environment. E.g.:
-q testing -t exotic -p estats -t deploy
-l nodes=1 -I
This tutorial page explains how this
ubuntu2004-nfsl4t environment is built and how...
Read more news
As from June 2008, Inria is the main contributor to Grid'5000 funding.
Université Grenoble Alpes, Grenoble INP
Université Rennes 1, Rennes
Institut National Polytechnique de Toulouse / INSA / FERIA / Université Paul Sabatier, Toulouse
Université Bordeaux 1, Bordeaux
Université Lille 1, Lille
École Normale Supérieure, Lyon
Provence Alpes Côte d'Azur
Hauts de France