SyncNN: Evaluating and Accelerating Spiking Neural Networks on FPGAs

In this paper, we propose a novel synchronous approach for rate encoding based Spiking Neural Networks (SNNs), which is more hardware friendly than conventional asynchronous approaches. We also design and implement the SyncNN framework to accelerate SNNs on Xilinx ARM-FPGA SoCs in a synchronous fashion. To improve the computation and memory access efficiency, we first quantize the network weights ...