A New Smart-MicroSystems Age Enabled by Heterogeneous Integration of Silicon-Centric and AI Technologies-My Personal View

Nicky Lu
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Abstract

After 60 years of development efforts since the 1960s to the current Giga-/Tera-Scale-Integration or System-on-a-Chip era [1]–[3], it is expected that Monolithic Silicon IC products using 2-nm CMOS devices will appear soon. The subsequent challenge is whether more novel device structures using heterogeneous materials and 3D-structures will be invented to realize manufacturable 1-nm ICs. On the other hand, through 20 years of efforts since 1999, many Heterogeneous Integration (HI) [4]–[6] products, each of which is composed of silicon and non-silicon materials/ dice/chiplets, diversified devices/circuits, innovative architectures and multi-dimensional arrangements of dice and other components inside either Chip-package or Module, have been increasingly emerging, especially recently benefiting from a strong driving force stimulated by the IEEE HI Roadmap unveiled in 2018 [5]. This paper presents an exciting, powerful and new Trend of Semiconductors, Intelligent Grand Scale Integration (IGSI), which is optimally utilizing Mixed Integration of Monolithic and HI Technologies (Si-4.0 [6]) with embedded 3A's (Algorithm, Architecture and AI) Design-Intelligences. A key target of IGSI technologies is to drive much higher energy efficiency of managing electronic information for more-effective/ intelligent future systems with better performance, lower power, higher reliability and smaller form-factor than those of our current systems. One effective way as proposed is to network multiple Self-Smart MicroSystems (S-SmS) each of which is designed with 3A's to a complete system level which can handle huge data processing smartly in its own compact multi-dimensional form factor like in a versatile solid-state micro-universe which has abundant self-contained intelligent functions with maximized speed-power efficiency due to close proximity of electronic/photonic/ micro-mechanical operations. It is projected that in such an S-SmS each Joule (energy unit) be able to operate more than 10^20 devices per die per joule allowed by thermodynamics (on the other hand, its performance can reach over hundreds of thousands of TOPS - Tera Operations Per Second) inside and/or across these MicroSystems to complete the final system need. Then how powerful a future system can be by networking enough S-SmS units and furthermore how many unprecedented and unexpected applications will be unleashed! To use AI computing systems as an example, it is expected that S-SmS be quickly applied to AI's edge, device or wearable applications. Moreover, just like the experiences of migrating from a Mainframe computer to networked PC Servers, Data servers used in AI Clouds may use such a networked S-SmS architecture to build large systems in order to optimize the energy efficiency and heat dissipation. The trend equally adds values to system's transformation and optimization in Autonomous Car areas, Industrial 4.0 Factory areas, Telecommunication and Computing areas and so forth.
一个新的智能微系统时代由硅中心和人工智能技术的异构集成实现-我的个人观点
从20世纪60年代开始,经过60年的发展努力,到目前的千兆/太兆级集成或片上系统时代[1]-[3],预计使用2纳米CMOS器件的单片硅集成电路产品将很快出现。接下来的挑战是是否会发明更多使用异质材料和3d结构的新颖器件结构来实现可制造的1nm集成电路。另一方面,自1999年以来,经过20年的努力,许多异构集成(HI)[4] -[6]产品不断涌现,其中每个产品都由硅和非硅材料/骰子/小芯片,多样化的器件/电路,创新的架构以及骰子和芯片封装或模块内其他组件的多维排列组成,特别是最近受益于2018年公布的IEEE HI路线图的强大推动力[5]。本文提出了一个令人兴奋的、强大的半导体智能大规模集成(IGSI)的新趋势,它最佳地利用了单片和HI技术(Si-4.0[6])与嵌入式3A(算法、架构和人工智能)设计智能的混合集成。IGSI技术的一个关键目标是推动管理电子信息的更高能源效率,为更有效/智能的未来系统提供更好的性能、更低的功耗、更高的可靠性和更小的外形因素,而不是我们目前的系统。提出的一种有效方法是将多个自我智能微系统(S-SmS)联网,每个系统都采用3A设计到一个完整的系统级别,可以在其自身紧凑的多维形状因素中智能地处理大量数据处理,就像在一个多功能的固态微宇宙中一样,它具有丰富的自包含智能功能,并且由于接近电子/光子/微机械操作而具有最大的速度-功率效率。预计在这样的S-SmS中,每焦耳(能量单位)能够在热力学允许的每焦耳中运行超过10^20个器件(另一方面,它的性能可以达到每秒数十万TOPS - Tera操作),以完成这些微系统内部和/或跨这些微系统,以完成最终的系统需求。那么,通过将足够多的S-SmS单元联网,未来的系统将变得多么强大,而且将释放出多少前所未有的和意想不到的应用程序!以人工智能计算系统为例,预计S-SmS将迅速应用于人工智能的边缘、设备或可穿戴应用。此外,就像从大型机迁移到联网PC服务器的体验一样,AI云中使用的数据服务器可能会使用这种联网的S-SmS架构来构建大型系统,以优化能效和散热。这一趋势同样为自动驾驶汽车领域、工业4.0工厂领域、电信和计算领域等系统的转型和优化增加了价值。
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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