A review of emerging non-volatile memory (NVM) technologies and applications

A review of emerging non-volatile memory (NVM) technologies and applications
复制标题

DOI:
10.1016/j.sse.2016.07.006
复制
发表时间:
2016-11-01
影响因子:
1.7
通讯作者:
Chen, An
Chen, An
中科院分区:
物理与天体物理3区
文献类型:
--
作者:
Chen, An

文献摘要

被引文献

相似文献

本文综述了近年来出现的非易失性存储器(NVM)技术,重点介绍了相变存储器(PCM)、自旋转移扭矩随机存取存储器(STTRAM)、阻性随机存取存储器(RRAM)和铁电场效应晶体管(FeFET)存储器。对这些前景看好的NVM设备的优势、挑战和应用进行了评估。根据报告的主要工业测试芯片的参数对它们的性能进行了比较。讨论了存储器选择器器件和单元结构。不断变化的低功耗(例如,移动、物联网)和以数据为中心的应用的市场趋势为新兴的NVM创造了机会。高性能和低成本的新兴NVM可以简化存储器层次结构,在逻辑门和电路中引入非易失性,降低系统功耗,并实现新的体系结构。基于高密度NVM的存储级内存(SCM)可以填补内存和存储之间的性能和密度差距。新兴NVM的一些独特特性可以被用于存储空间以外的新应用,例如神经形态计算、硬件安全等。在超越CMOS时代,新兴NVM有可能实现更重要的功能,实现更高效、智能和安全的计算系统。(C)2016爱思唯尔有限公司。保留所有权利。
This paper will review emerging non-volatile memory (NVM) technologies, with the focus on phase change memory (PCM), spin-transfer-torque random-access-memory (STTRAM), resistive randomaccess-memory (RRAM), and ferroelectric field-effect-transistor (FeFET) memory. These promising NVM devices are evaluated in terms of their advantages, challenges, and applications. Their performance is compared based on reported parameters of major industrial test chips. Memory selector devices and cell structures are discussed. Changing market trends toward low power (e.g., mobile, IoT) and data-centric applications create opportunities for emerging NVMs. High-performance and low-cost emerging NVMs may simplify memory hierarchy, introduce non-volatility in logic gates and circuits, reduce system power, and enable novel architectures. Storage-class memory (SCM) based on high-density NVMs could fill the performance and density gap between memory and storage. Some unique characteristics of emerging NVMs can be utilized for novel applications beyond the memory space, e.g., neuromorphic computing, hardware security, etc. In the beyond-CMOS era, emerging NVMs have the potential to fulfill more important functions and enable more efficient, intelligent, and secure computing systems. (C) 2016 Elsevier Ltd. All rights reserved.