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年中，半导体行业超出了想象力。 1971年，第一个英特尔微处理器包含2300个晶体管。现在，在2023年，特斯拉的自动驾驶芯片大约包含6,000,000,000晶体管。在全球任何其他行业中，闻所未闻的六个数量级数量级数量的改善。尽管多年来的半导体行业已经取得了重大进展，但现在它已经达到了硅的物理极限，晶体管仅包含几个硅原子。因此，问题是：“未来50年的半导体的未来是什么？”该项目的目的是通过建立一个研究团队来开发包括材料，设备和系统的共同设计方法来解决这个问题，以创造革命性的突破，以在下一代的半导体行业中提高美国能力。该奖项的研究团队代表了工程学中几个重要学科的跨学科横截面。此外，该项目围绕着代表性不足的群体参与科学和技术的参与。 该项目中开发的神经形态综合电路（NIC）使用单层集成的3D堆栈的新型浮力碳纳米管纳米管田间效应晶体管（FG-CNFET），通过将Moore的法律扩展到单层的晶体尺度来扩展半导体技术的革命性突破。它是一项有能力的技术，可为传统的确定计算硬件提供其他非确定性计算能力，以在高能节能的模拟电路中执行复杂的计算。此外，由于其庞大的并行性和重新配置性，提出的NIC硬件本质上是易于故障的，非常适合与单片3D整合兼容的设备，但通常具有高缺陷率，例如FG-CNFET所示。拟议的NIC具有三个独特的功能，没有现有技术可以提供：1）可重新配置和可扩展的神经形态架构，2）内置的模拟信号处理单元，能够具有高能能效的非确定性计算，以及3）使用高级设备，这些设备具有与单片3D整合的统一性，并在统计中均具有完整的范围。通过使用基金会的知识分子和更广泛影响的评论标准来通过评估来支持。