FuSe-TG: Advanced Device and System Opportunities for future Neuromorphic Integrated Circuits (NICs) and Their Applications

FuSe-TG：未来神经形态集成电路 (NIC) 及其应用的先进设备和系统机会

• 批准号: 2235411
• 负责人: Payman Zarkesh-Ha
• 金额: $ 30万
• 依托单位: University of New Mexico
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2235411&HistoricalAwards=false
• 关键词: FuSe; TG; Advanced; Device; System

The semiconductor industry has improved beyond imagination over the past 50 years. In 1971, the first Intel microprocessor contained 2,300 transistors. Now, in 2023, Tesla's self-driving chip contains roughly 6,000,000,000 transistors. This improvement of six orders of magnitude of added capability is unheard of in any other industry worldwide. Although the semiconductor industry has made significant progress over the years, it is now reaching the physical limits of silicon, where a transistor contains only a few silicon atoms. Hence the question is, "What is the future of semiconductors over the next 50 years?" The objective of this project is to address this question by building a research team to develop a co-design approach that includes materials, devices, and systems to create a revolutionary breakthrough for shoring up US capabilities in the next generations of the semiconductor industry. The research team in this award represents an interdisciplinary cross-section of several important disciplines within engineering. In addition, the project revolves around participation from underrepresented groups by involving them in science and technology. The neuromorphic integrated circuit (NIC) developed in this project uses the monolithically integrated 3D stacks of a novel floating-gate carbon nanotube field-effect transistor (FG-CNFET) to create a revolutionary breakthrough in semiconductor technology by extending Moore's law beyond transistor scaling in a single layer. It is an enabling technology that provides additional non-deterministic computing capability to conventional deterministic computing hardware to perform complex computation in a highly energy-efficient analog circuit. Moreover, due to its massive parallelism and reconfigurability, the proposed NIC hardware is inherently fault-tolerant, perfectly suitable for devices compatible with monolithic 3D integration, but typically suffers from high defect rates, as for instance exhibited by FG-CNFETs. The proposed NIC has three distinctive features that no existing technology can offer: 1) reconfigurable and scalable neuromorphic architecture, 2) built-in analog signal processing units capable of highly energy-efficient non-deterministic computing, and 3) utilization of advanced devices that are compatible with monolithic 3D integration, rectifying their imperfections.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在过去的50年里，半导体行业的发展超出了人们的想象。1971年，第一款英特尔微处理器包含2，300个晶体管。到2023年，特斯拉的自动驾驶芯片将包含大约60亿个晶体管。这种六个数量级的增加能力的改进在世界上任何其他行业都是闻所未闻的。虽然半导体工业多年来取得了重大进展，但它现在已经达到了硅的物理极限，即晶体管只包含几个硅原子。因此，问题是，“未来50年半导体的未来是什么？”“该项目的目标是通过建立一个研究团队来解决这个问题，以开发一种包括材料，设备和系统在内的协同设计方法，以创造革命性的突破，以支持美国在下一代半导体行业中的能力。该奖项中的研究团队代表了工程学中几个重要学科的跨学科交叉。此外，该项目围绕着代表性不足的群体的参与，让他们参与科学和技术。 在这个项目中开发的神经形态集成电路（NIC）使用单片集成的新型浮栅碳纳米管场效应晶体管（FG-CNFET）的3D堆栈，通过将摩尔定律扩展到单层晶体管缩放之外，创造了半导体技术的革命性突破。它是一种使能技术，其向常规确定性计算硬件提供额外的非确定性计算能力，以在高能效模拟电路中执行复杂计算。此外，由于其大规模并行性和可重新配置性，所提出的NIC硬件具有固有的容错性，非常适合与单片3D集成兼容的设备，但通常具有高缺陷率，例如FG-CNFET所表现出的缺陷率。拟议的NIC具有现有技术无法提供的三个显著特征：1）可重新配置和可扩展的神经形态架构，2）能够进行高能效非确定性计算的内置模拟信号处理单元，以及3）利用与单片3D集成兼容的先进设备，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。