Challenges and Trends inDeveloping Nonvolatile Memory-Enabled Computing Chips for Intelligent Edge Devices
Je-Min Hung, Xueqing Li, Juejian Wu, Meng‐Fan Chang
Abstract
Under the von Neumann computing architecture, the edge devices used for artificial intelligence (AI) and the Internet of Things (IoTs) are limited in terms of latency and energy efficiency due to the movement of data between the memory and the processor. Nonvolatile memory-based computation-in-memory (nvCIM) is a promising candidate to overcome this issue, referred to as the memory wall. This article outlines the background and major challenges in the development of nvCIM macros as well as some of the recent progress in nvCIM for logic computation, pattern-matching computation, and multiply-and-accumulate (MAC) computation. We also summarize recent trends in nvCIM development at the end of each section.