hxtorch.snn: Machine-learning-inspired Spiking Neural Network Modeling on BrainScaleS-2

@article{Spilger2022hxtorchsnnMS,
  title={hxtorch.snn: Machine-learning-inspired Spiking Neural Network Modeling on BrainScaleS-2},
  author={Philipp Spilger and Elias Arnold and Luca Blessing and Christian Mauch and Christian Pehle and Eric M{\"u}ller and Johannes Schemmel},
  journal={ArXiv},
  year={2022},
  volume={abs/2212.12210}
}
Neuromorphic systems require user-friendly software to support the design and optimization of experiments. In this work, we ad-dressthisneedby presentingour developmentofa machinelearning-based modeling framework for the BrainScaleS-2 neuromorphic system. This work represents an improvement over previous ef-forts, which either focused on the matrix-multiplication mode of BrainScaleS-2 or lacked full automation. Our framework, called hxtorch.snn , enables the hardware-in-the-loop training of… 
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