Cross-layer Design for Computing-in-Memory: From Devices, Circuits, to Architectures and Applications

H. Amrouch, X. Hu, M. Imani, Ann Franchesca Laguna, M. Niemier, Simon Thomann, Xunzhao Yin, Cheng Zhuo
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引用次数: 2

Abstract

The era of Big Data, Artificial Intelligence (AI) and Internet of Things (IoT) is approaching, but our underlying computing infrastructures are not sufficiently ready. The end of Moore’s law and process scaling as well as the memory wall associated with von Neumann architectures have throttled the rapid development of conventional architectures based on CMOS technology, and cross-layer efforts that involve the interactions from low-end devices to high-end applications have been prominently studied to overcome the aforementioned challenges. On one hand, various emerging devices, e.g., Ferroelectric FET, have been proposed to either sustain the scaling trends or enable novel circuit and architecture innovations. On the other hand, novel computing architectures/algorithms, e.g., computing-in-memory (CiM), have been proposed to address the challenges faced by conventional von Neumann architectures. Naturally, integrated approaches across the emerging devices and computing architectures/algorithms for data-intensive applications are of great interests. This paper uses the FeFET as a representative device, and discuss about the challenges, opportunities and contributions for the emerging trends of cross-layer co-design for CiM.
内存计算的跨层设计:从器件、电路到体系结构和应用
大数据、人工智能(AI)和物联网(IoT)时代即将来临,但我们的底层计算基础设施还没有准备好。摩尔定律的终结和过程缩放以及与冯·诺伊曼架构相关的内存墙已经抑制了基于CMOS技术的传统架构的快速发展,而涉及从低端设备到高端应用的交互的跨层努力已经得到了突出的研究,以克服上述挑战。一方面,已经提出了各种新兴器件,例如铁电场效应管,以维持缩放趋势或实现新颖的电路和架构创新。另一方面,新的计算架构/算法,例如内存计算(CiM),已经被提出来解决传统冯·诺依曼架构所面临的挑战。当然,跨新兴设备和数据密集型应用的计算架构/算法的集成方法是非常有趣的。本文以场效应晶体管为代表器件,讨论了CiM跨层协同设计的挑战、机遇和贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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