GeNN

GeNN is a GPU enhanced Neuronal Network simulation environment based on NVIDIA CUDA technology.

View project on GitHub

Welcome to GeNN.

GeNN 4.5.1

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GeNN 3.3.0

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Download the full documentation as .pdf

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Meet the Team

GeNN is maintained by genn-team.

Dr James Knight is a post-doctoral researcher, working on the Brains-on-Board project at the School of Engineering and Informatics at the University of Sussex
Dr James Turner is a post-doctoral researcher, working on the Human Brain Project at the School of Engineering and Informatics at the University of Sussex
Prof Thomas Nowotny is a Professor of Informatics at the University of Sussex

Get involved

Watch GeNN on GitHub.

Submit an issue on GitHub.

Send an email to the team (James).

Follow the Twitter account of the Brains on Board Project, which is partially supporting the development of GeNN (financed by the EPSRC)

Publications

Knight, J. C., Komissarov, A., & Nowotny, T. (2021). PyGeNN: A Python Library for GPU-Enhanced Neural Networks. Frontiers in Neuroinformatics, 15(April), 1–12.Access online

Knight, J. C., & Nowotny, T. (2021). Larger GPU-accelerated brain simulations with procedural connectivity. Nature Computational Science, 1, 136-142.Access online

Knight, J. C., & Nowotny, T. (2018). GPUs Outperform Current HPC and Neuromorphic Solutions in Terms of Speed and Energy When Simulating a Highly-Connected Cortical Model. Frontiers in Neuroscience, 12(December), 1–19.Access online

Yavuz, E., Turner, J. and Nowotny, T. (2016) GeNN: a code generation framework for accelerated brain simulations. Scientific Reports 6, 18854 Access online