Memristive, Spintronic, and 2D-Materials-Based Devices to Improve and Complement Computing Hardware
Memristive, Spintronic, and 2D-Materials-Based Devices to Improve and Complement Computing Hardware
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DOI：
10.1002/aisy.202200068
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发表时间：
2022-07-01
影响因子：
7.4
通讯作者：
Mehonic, Adnan
中科院分区：
文献类型：
--
作者：
Joksas, Dovydas;AlMutairi, AbdulAziz;Mehonic, Adnan
在数据驱动的经济中，几乎所有行业都受益于信息技术的进步——强大的计算系统对于技术的快速进步至关重要。然而，如果当前计算能力需求与现有技术所能提供的能力之间的差异得不到解决，这一进展可能会面临放缓的风险。提高能源效率的主要限制是与冯诺依曼架构相关的数据传输成本的过度增长以及晶体管等互补金属氧化物半导体 (CMOS) 技术的基本限制。本文讨论了可能在未来计算系统中发挥重要作用的三种方法：忆阻电子学、自旋电子学和基于二维材料的电子学。作者介绍了这些技术如何改变传统的数字计算机并有助于采用神经形态计算等新范式。
In a data-driven economy, virtually all industries benefit from advances in information technology-powerful computing systems are critically important for rapid technological progress. However, this progress might be at risk of slowing down if the discrepancy between the current computing power demands and what the existing technologies can offer is not addressed. Key limitations to improving energy efficiency are the excessive growth of data transfer costs associated with the von Neumann architecture and the fundamental limits of complementary metal-oxide-semiconductor (CMOS) technologies, such as transistors. Herein, three approaches that will likely play an essential role in future computing systems are discussed: memristive electronics, spintronics, and electronics based on 2D materials. The authors present how these technologies may transform conventional digital computers and contribute to the adoption of new paradigms, like neuromorphic computing.