A semantics-preserving co-design exports PyTorch SNNs to event-driven FPGAs via one artifact, achieving 87.4% MNIST accuracy identical to software reference at 0.1375 μs and 31.6 nJ per image.
T2fsnn: Deep spiking neural networks with time-to-first-spike coding
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Hardware-Software Co-Design for Event-Driven SNN Deployment on Low-Cost Neuromorphic FPGAs
A semantics-preserving co-design exports PyTorch SNNs to event-driven FPGAs via one artifact, achieving 87.4% MNIST accuracy identical to software reference at 0.1375 μs and 31.6 nJ per image.