A 4096-Neuron 1M-Synapse 3.8PJ/SOP Spiking Neural Network with On-Chip STDP Learning and Sparse Weights in 10NM FinFET CMOS

Abstract

A 4096-neuron, 1M-synapse SNN in 10nm FinFET CMOS achieves a peak throughput of 25.2GSOP/s at 0.9V, peak energy efficiency of 3.8pJ/SOP at 525mV, and 2.3μW/neuron operation at 450mV. The SNN skips zero-valued activations for up to 9.4× lower energy. Fine-grained sparse weights reduce memory by up to 16×. On-chip STDP trains RBMs to de-noise MNIST digits and to reconstruct natural scene images with RMSE of 0.036. A 50% sparse weight MLP classifies MNIST digits with 97.9% accuracy at 1.7μJ/classification.