GeNN target

NESTML features supported: neurons

Introduction

GeNN is a GPU-enhanced Neuronal Network simulation environment based on code generation for Nvidia CUDA [Yav2016] [GeNNGitHub] [GeNNRtD].

NESTML code generation support for GeNN currently covers neuron models with linear dynamics that can be solved with propagators, as well as neurons that require a numeric solver, which for GeNN is implemented (in the neuron code templates) as a forward Euler solver.

Please see the unit tests in https://github.com/nest/nestml/tree/main/tests/genn_tests for usage examples.

Generating code

  1. Install GeNN (see the GeNN documentation [GeNNRtD] for instructions).

  2. Run the tests:

    python3 -m pytest tests/genn_tests

    These will generate rastergrams for a simple, single-neuron example in /tmp, for both the Izhikevich and the integrate-and-fire model with an exponentially decaying postsynaptic kernel.

References

[Yav2016]

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