Automated Hardware-Oriented Design Space Exploration for Optimizing Spiking Neural Network Accelerators on FPGA

SpikeExplorer is a flexible and modular Python tool that automates the multi-objective optimization of Spiking Neural Network (SNN) accelerators targeting FPGA implementations, enabling the exploration of optimal network architectures, neuron models, and training parameters to meet desired constraints on accuracy, power, latency, and area.