Spiker: an FPGA-optimized Hardware accelerator for Spiking Neural Networks

@article{Carpegna2022SpikerAF,
  title={Spiker: an FPGA-optimized Hardware accelerator for Spiking Neural Networks},
  author={Alessio Carpegna and Alessandro Savino and Stefano Di Carlo},
  journal={2022 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)},
  year={2022},
  pages={14-19}
}
Spiking Neural Networks (SNN) are an emerging type of biologically plausible and efficient Artificial Neural Network (ANN). This work presents the development of a hardware accelerator for a SNN for high-performance inference, targeting a Xilinx Artix-7 Field Programmable Gate Array (FPGA). The model used inside the neuron is the Leaky Integrate and Fire (LIF). The execution is clock-driven, meaning that the internal state of the neuron is updated at every clock cycle, even in absence of spikes… 

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