计算机科学
计算机数据存储
闪存
内存处理
大数据
非易失性存储器
电阻随机存取存储器
过程(计算)
嵌入式系统
分布式计算
数据科学
计算机硬件
电气工程
工程类
操作系统
电压
万维网
搜索引擎
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作者
Jiaqin Yang,Ye Zhou,Su‐Ting Han
标识
DOI:10.1002/aelm.202001181
摘要
Abstract The development of artificial intelligence and big data analytics is driving a revolution in methods for data processing and storage. Confronting speed and energy consumption issues, these fields require new computing systems to parallelly retrieve, process, and store massive amounts of data. Beyond CMOS devices and technology, advances in data storage technology such as static random‐access memory, dynamic random‐access memory, flash memories, resistive memories, phase change memories, and magnetic memories have made functional computing possible. In this article, a broad overview of current memory systems and their development history spanning fundamental operating schemes, prevailing applications and required figure of merits for applications such as in‐memory computing and some critical issues that need to be addressed in the future development of this emerging technique are provided.
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