论文标题
回忆,自旋和基于2D材料的设备,以改进和补充计算硬件
Memristive, Spintronic, and 2D-Materials-Based Devices to Improve and Complement Computing Hardware
论文作者
论文摘要
在数据驱动的经济中,几乎所有行业都从信息技术的进步中受益 - 强大的计算系统对于快速技术进步至关重要。但是,如果我们不解决当前计算能力需求与现有技术可以提供的差异,那么这种进展可能会放慢速度。提高能源效率的关键局限性是与冯·诺伊曼(Von Neumann)结构相关的数据传输成本的过度增长以及互补金属 - 氧化物 - 氧化型辅助导体(CMOS)技术(例如晶体管)的基本限制。在这篇观点文章中,我们讨论了三种技术,这些技术可能在未来的计算系统中起着至关重要的作用:基于2D材料的回忆电子,自旋和电子产品。我们介绍了它们如何改变传统的数字计算机并有助于采用新范式,例如神经形态计算。
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 we do not address the discrepancy between our current computing power demands and what the existing technologies can offer. 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. In this perspective article, we discuss three technologies that will likely play an essential role in future computing systems: memristive electronics, spintronics, and electronics based on 2D materials. We present how these may transform conventional digital computers and contribute to the adoption of new paradigms, like neuromorphic computing.