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| Talk (non-conference) (After Call) | FZJ-2025-02527 |
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2025
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Please use a persistent id in citations: doi:10.34734/FZJ-2025-02527
Abstract: In the design of neuromorphic systems, it is vital to have a flexible and highly performant way of exploring system parameters. Using NEST Simulator [1] and the NESTML modeling language [2], spiking neural network models can be quickly prototyped and subjected to design constraints that mirror those of the intended neuromorphic platform. NEST has a proven track record on a large and diverse set of use cases, and can run on anywhere from laptops to supercomputers, making it an ideal prototyping and research platform for neuromorphic systems. This benefits reproducibility (obtaining the same numerical results across platforms), highlighting the value of NEST in verification and validation of neuromorphic systems.In this tutorial, participants will get hands-on experience creating neuron and synapse models in NESTML, and using them to build networks in NEST that perform various tasks, such as sequence learning and reinforcement learning. We will introduce several tools and front-ends to implement modeling ideas most effectively, such as the graphical user interface NEST Desktop [3]. Through the use of target-specific code generation options in NESTML, the same model can even be directly run on neuromorphic platforms.Participants do not have to install software as all tools are accessible via the cloud. All parts of the tutorial are hands-on, and take place via Jupyter notebooks. [1] https://nest-simulator.readthedocs.org/ [2] https://nestml.readthedocs.org/ [3] https://nest-desktop.readthedocs.org/
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