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 and IA.
- 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
- 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 2019-09-22 12:15)
: No current events, None planned (details)
Random pick of publications
Five random publications that benefited from Grid'5000 (at least 2034 overall):
- Patrick Valduriez, Marta Mattoso, Reza Akbarinia, Heraldo Borges, José Camata, et al.. Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC Project. LADaS: Latin America Data Science Workshop, Aug 2018, Rio de Janeiro, Brazil. lirmm-01867804 view on HAL pdf
- Bastien Confais, Adrien Lebre, Benoît Parrein. A Tree-Based Approach to locate Object Replicas in a Fog Storage Infrastructure. GLOBECOM 2018 - IEEE Global Communications Conference, Dec 2018, Abu Dhabi, United Arab Emirates. pp.1-6. hal-01946365 view on HAL pdf
- Ziteng Wang, Junfeng Li, Yonghong Yan, Emmanuel Vincent. Semi-supervised learning with deep neural networks for relative transfer function inverse regression. ICASSP 2018 – IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, Canada. hal-01797886 view on HAL pdf
- Vikas Jaiman, Sonia Ben Mokhtar, Vivien Quéma, Lydia Chen, Etienne Rivìere. Héron: Taming Tail Latencies in Key-Value Stores under Heterogeneous Workloads. International Symposium on Reliable Distributed Systems (SRDS) 2018, Oct 2018, Salvador, Brazil. pp.191-200, 10.1109/SRDS.2018.00030. hal-01896686 view on HAL pdf
- Daniele Calandriello, Ioannis Koutis, Alessandro Lazaric, Michal Valko. Improved large-scale graph learning through ridge spectral sparsification. International Conference on Machine Learning, ICML 2018 - Thirty-fifth International Conference on Machine Learning, Jul 2018, Stockholm, Sweden. hal-01810980 view on HAL pdf
Default environments and frontends to be updated to Debian 10 "Buster"
We are planning to upgrade nodes default environement (the "-std" variant, provided when deployment is not used) to Debian 10 "Buster". Switchover is scheduled on September, 26th.
In addition, frontends will also be upgraded on October 3rd (It has already been upgraded on Luxembourg site).
Remind that this update may need you to modify your scripts (of course you will still be able to deploy Debian 9 environments).
-- Grid'5000 Team 12:00, 20 September 2019 (CET)
New cluster available in Nancy: graffiti (52 GPUs)
We have the pleasure to announce that the Graffiti cluster in Nancy (production queue) is now fully operational:
It features 13 Dell T640 servers nodes with 2 Intel Silver 4110 (8 cores / 16 threads), 128 GB DDR4, 1x480 GB SSD, 10Gbps Ethernet, and 4 GPU NVidia RTX2080 Ti per node.
As this cluster features 4 GPU per node, we remind you that you can monitor GPU (and node) usage using the Ganglia tool (std environment only):
You can also use the nvidia-smi and htop commands on your reserved nodes to get more information about your GPU/CPU usage.
If your experiments do not require all the GPU of a single node, it is possible to reserve GPU at the resource level (see https://grid5000.fr/w/News#Enabling_GPU_level_resource_reservation_in_OAR for some examples).
Finally, if you know how to use GPUs at their max with widely used software (Tensorflow, NAMD, ...) and would like to share your knowledge about this, we will be happy to transform your knowledge into Grid5000 tutorials.
This cluster has been funded by Ihe CPER LCHN project (Langues, Connaissances & Humanités Numériques, Contrat de plan État / Région Lorraine 2015-2020), and the LARSEN and MULTISPEECH teams at LORIA / Inria Nancy Grand Est.
Special thanks go to:
- Marc Vesin (Inria Sophia) and Marianne Lombard (Inria Saclay) for their contributions and sharing of experiences on the café cluster mailing list which have...
A new version of tgz-g5k has been released
We have released a new version of tgz-g5k. Tgz-g5k is a a tool that allow you to extract a Grid'5000 environment tarball from a running node. The tarball can therefore be used by kadeploy to re-deploy the image on different nodes/reservations (see Advanced Kadeploy for more details)
The new version has two major improvements:
- tgz-g5k is now compatible with Ubuntu and Centos
- tgz-g5k is directly usable on frontends (you do not need to use it through ssh anymore).
To use tgz-g5k from a frontend, you can execute the following command:
frontend$ tgz-g5k -m MY_NODE -f ~/MY_TARBALL.tgz
In case of specific or non-deployed environments:
- tgz-g5k can use a specific user id to access nodes, by using the parameter -u (by default tgz-g5k accesses nodes as root)
- tgz-g5k can access node with oarsh/oarcp instead of ssh/scp, by using the parameter -o (by default tgz-g5k uses ssh/scp)
Note that tg5-g5k is still compatible with the previous command line. For the record, you had to use previously the following command:
frontend$ ssh root@MY_NODE tgz-g5k > ~/MY_TARBALL.tgz
-- Grid'5000 Team 15:00, 07 August 2019 (CET)
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