A Fully Synthesized 13.7µJ/prediction 88% Accuracy CIFAR-10 Single-Chip Data-Reusing Wired-Logic Processor Using Non-Linear Neural Network

An FPGA-based wired-logic CNN processor is presented that can process CIFAR-10 at 13.7µJ/prediction with an 88% accuracy, which is 2,036 times more energy-efficient than the prior state-of-the-art FPGA-based processor. Energy efficiency is greatly improved by implementing all processing elements and wirings in parallel on a single FPGA chip to eliminate the memory access. By utilizing both (1) a non-linear neural network which saves on neurons and synapses and (2) a shift register-based wired-logic architecture, hardware resource usage is reduced by three orders of magnitude.