SPIKER-LL extends the open-source Spiker+ SNN accelerator with microarchitectural support for the STSF local learning rule, delivering up to 93% accuracy, sub-millisecond latency, and under 0.1 mJ per inference on MNIST variants while remaining DSP-free.
Spike-Train Level Direct Feedback Alignment: Sidestepping Backpropagation for On-Chip Training of Spiking Neural Nets
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Spiker-LL: An Energy-Efficient FPGA Accelerator Enabling Adaptive Local Learning in Spiking Neural Networks
SPIKER-LL extends the open-source Spiker+ SNN accelerator with microarchitectural support for the STSF local learning rule, delivering up to 93% accuracy, sub-millisecond latency, and under 0.1 mJ per inference on MNIST variants while remaining DSP-free.