Scalable Look-Up Table based Neural Accelerator with Mixed Precision Analysis for Energy-Efficient Inference

A scalable and programmable Look-Up Table (LUT) based Neural Accelerator (LUT-NA) framework that employs a divide-and-conquer approach to overcome the scalability limitations of traditional LUT-based techniques, and utilizes mixed-precision analysis to further reduce energy and area consumption without significant accuracy loss.