CANCELLED: 16th Fenix Infrastructure Webinar: Best practices for using NEST on Fenix Scalable Computing Services

15 Jun 2022
Place: Online

The 16th Fenix Infrastructure Webinar "Best practices for using NEST on Fenix Scalable Computing Services" takes place on Wednesday 15 June 2022 at 15:00 CET. Due to a last minute issue with our speaker, we were forced to postpone this webinar. 

Date and Time: CANCELLED, a new date will be coming soon! 

Cost: Free of charge

Speakers: Hans Ekkehard Plesser (NMBU)

Description: This webinar will introduce users to the use of NEST on Fenix Scalable Computing Services. After a brief introduction to neuronal network modelling with NEST locally in the EBRAINS Collaboratory, we will show how to run the same simulation on Fenix HPC resources from the Collaboratory. We then move on to more complex, scientifically interesting network models which require scalable computing services to perform, e.g., parameter scans. We conclude with a brief introduction to the NEST Desktop Graphical User Interface.

Who should attend?

  • Neuroscientists
  • HPC infrastructure users
  • EBRAINS service developers


Main takeaways

  • How to run NEST-based network models in the EBRAINS Collaboratory
  • How to run large-scale NEST-based models from the Collaboratory on Fenix resources
  • How to perform parameter scans of network models from the Collaboratory on Fenix resources
  • How to run NEST Desktop with a NEST Server backend on Fenix resources



  • Introduction: A two-population network model in NEST
  • Running the two-population model on Fenix resources
  • Stepping up: Parameter scans of the Potjans-Diesmann microcircuit model on Fenix
  • Towards the brain scale: Running the Multi-Area Model (van Albada et al)
  • A quick look at NEST Desktop
  • Q&A

The webinar will be recorded and the full recording and presentation slides will become available on the Fenix Webinars page.



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Fenix has received funding from the European Union's Horizon 2020 research and innovation programme through the ICEI project under the grant agreement No. 800858.