Go Shao-Xiang, Lim Kian-Guan, Lee Tae-Hoon, Loke Desmond K
Department of Science, Mathematics and Technology Singapore University of Technology and Design Singapore 487372 Singapore.
Department of Engineering University of Cambridge Trumpington Street Cambridge CB2 1PZ UK.
Small Sci. 2024 Jan 22;4(3):2300139. doi: 10.1002/smsc.202300139. eCollection 2024 Mar.
Separate memory and processing units are utilized in conventional von Neumann computational architectures. However, regarding the energy and the time, it is costly to shuffle data between the memory and the processing entity, and for data-intensive applications associated with artificial intelligence, the demand is ever increasing. A paradigm shift in traditional architectures is required, and in-memory computing is one of the non-von-Neumann computing strategies. By harnessing physical signatures of the memory, computing workloads are administered in the same memory element. For in-memory computing, a wide range of memristive material (MM) systems have been examined. Moreover, developing computing schemes that perform in the same sensory network and that minimize the data shuffle between the processing unit and the sensing element is a requirement, to process large volumes of data efficiently and decrease the energy consumption. In this review, an overview of the switching character and system signature harnessed in three archetypal MM systems is rendered, along with an integrated application survey for developing in-sensor and in-memory computing, viz., brain-inspired or analogue computing, physical unclonable functions, and random number generators. The recent progress in theoretical studies that reveal the structural origin of the fast-switching ability of the MM system is further summarized.
传统的冯·诺依曼计算架构使用分离的内存和处理单元。然而，在能量和时间方面，在内存和处理实体之间转移数据成本高昂，对于与人工智能相关的数据密集型应用，这种需求日益增加。传统架构需要范式转变，内存计算是一种非冯·诺依曼计算策略。通过利用内存的物理特征，计算工作负载在同一内存元件中进行管理。对于内存计算，人们已经研究了多种忆阻材料（MM）系统。此外，需要开发能在同一传感网络中运行且能最小化处理单元与传感元件之间数据转移的计算方案，以便高效处理大量数据并降低能耗。在本综述中，我们概述了三种典型MM系统所利用的开关特性和系统特征，以及用于开发传感器内和内存内计算的综合应用调查，即受脑启发或模拟计算、物理不可克隆功能和随机数生成器。还进一步总结了揭示MM系统快速开关能力结构起源的理论研究的最新进展。
