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Inspired by the human brain's function and efficiency, neuromorphic computing offers a promising solution for a wide set of tasks, ranging from brain machine interfaces to real-time classification. The spiking neural network (SNN), which encodes and processes information with bionic spikes, is an emerging neuromorphic model with great potential to drastically promote the performance and efficiency of computing systems. However, an energy efficient hardware implementation and the difficulty ofdoi:10.1145/2742060.2743756 dblp:conf/glvlsi/WangTXLGYL015 fatcat:llshlmoijngp7axx5asxzhfn3m