GeNN is a GPU enhanced Neuronal Network simulation environment supporting multiple frontends and backends. Spiking neural network models can be specified directly in Python or C++ or through interfaces to Brian 2, SpineCreator (SpineML), or PyNN. GeNN generates optimised code for computational hardware including CPUs and accelerators that are supported through CUDA or OpenCL.

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

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

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.

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

Project Author(s)

James C Knight; Esin Yavuz; James P Turner; Anton Komissarov; Thomas Nowotny

This post was automatically generated by Thomas Nowotny

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