Grid5000:Home
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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:
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Random pick of publications
Five random publications that benefited from Grid'5000 (at least 2054 overall):
- David Guyon. Supporting energy-awareness for cloud users. Networking and Internet Architecture cs.NI. Université Rennes 1, 2018. English. NNT : 2018REN1S037. tel-01973083 view on HAL pdf
- Jean Luca Bez, Francieli Zanon Boito, Ramon Nou, Alberto Miranda, Toni Cortes, et al.. Detecting I/O Access Patterns of HPC Workloads at Runtime. SBAC-PAD 2019 - International Symposium on Computer Architecture and High Performance Computing, Oct 2019, Campo Grande, Brazil. hal-02276191 view on HAL pdf
- Giuseppe Di Lena, Andrea Tomassilli, Damien Saucez, Frédéric Giroire, Thierry Turletti, et al.. Distributed Network Experiment Emulation. GEFI 19 - Global Experimentation for Future Internet - Workshop, Nov 2019, Coimbra, Portugal. hal-02359801 view on HAL pdf
- Vikas Jaiman. Improving Performance Predictability in Cloud Data Stores. Machine Learning cs.LG. Université Grenoble Alpes, 2019. English. NNT : 2019GREAM016. tel-02301338 view on HAL pdf
- Thomas Durieux. From Runtime Failures to Patches: Study of Patch Generation in Production. Software Engineering cs.SE. University of Lille, 2018. English. tel-01883676 view on HAL pdf
Latest news
Grid'5000 General Conditions of Use now available
To clarify the legal frame and the application of law surrounding Grid'5000 usage, we added a "General Conditions of Use" document to the Usage Policy.
From now on, usage of Grid'5000 must be in accordance with those two documents:
- https://www.grid5000.fr/w/Grid5000:General_Conditions_of_Use
- https://www.grid5000.fr/w/Grid5000:UsagePolicy
-- Grid'5000 Team 17:00, June 30th 2020 (CEST)
New monitoring service for Grid'5000 available for beta testing
We are happy to announce a new service to provide environmental and performance metrics monitoring for Grid'5000 experiments.
The service uses the Kwollect framework and currently makes following metrics available:
- Energy consumption from dedicated “wattmetre” devices (currently available for some clusters in Lyon, Grenoble, Nancy) - Metrics collected from nodes’ Board Management Controller (out-of-band management hardware, such as Dell iDRAC), such as ambient temperature, hardware component temperature, energy consumption from PSU, fan speed, etc. - Traffic collected from network devices - Energy consumption from PDU, when available
It is also planned to add more metrics in the future.
The service documentation is available at:
https://www.grid5000.fr/w/Monitoring_Using_Kwollect
The service is currently in beta. Many things may change in the future. Feel free to give us your feedback at support-staff@lists.grid5000.fr
-- Grid'5000 Team 16:00, June 30th 2020 (CEST)
Grid’5000 resources now available through the Fed4FIRE federation.
We have the pleasure to announce that Grid’5000 is now accessible through the Fed4FIRE European testbed federation. https://www.grid5000.fr/w/Fed4FIRE
Fed4FIRE is the largest federation worldwide of Next Generation Internet (NGI) testbeds, which provide open, accessible and reliable facilities supporting a wide variety of different research and innovation communities and initiatives in Europe.
The Grid’5000 Aggregate Manager will allow the provisioning of Grid’5000 nodes to members of the federation using the federation’s jFed-Experiment application, or tools designed to access GENI testbeds.
Please note that functions related to VLANs and inter-testbed stitching are still in development, and cannot yet be performed through the Aggregate Manager.
Grid’5000 users wanting to use the aggregate manager should link their Fed4FIRE account to their Grid’5000 one using the process described in the wiki.
-- Grid'5000 Team 11:30, June 29th 2020 (CEST)
A short documentation on installing Deep Learning frameworks under Grid'5000
We wrote a short documentation to explain how to install popular Deep Learning frameworks in Grid'5000. It is available at:
https://www.grid5000.fr/w/Deep_Learning_Frameworks
Note that the installation steps in the documentation are regularly executed under our testing infrastructure to ensure these tools work as expected at any time.
-- Grid'5000 Team 09:49, June 29th 2020 (CEST)
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 |
