Department of Applied Chemistry, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan, and Genesis Research Institute, Inc., 4-1-35 Noritake-Shinmachi, ...

Abstract: In-memory computing (IMC) and quantization have emerged as promising techniques for edge-based deep neural network (DNN) accelerators by reducing their energy, latency and storage ...