Collaborative Research: FuSe: Indium selenides based back end of line neuromorphic accelerators

合作研究：FuSe：基于硒化铟的后端神经形态加速器

• 批准号: 2328742
• 负责人: Priyadarshini Panda
• 金额: $ 40万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2328742&HistoricalAwards=false
• 关键词: Collaborative; Research; FuSe; Indium; selenides

This project aims to use innovative materials called “2D materials” to enhance the capabilities of modern integrated circuits. These materials have unique electronic properties that make them very promising for compute, storage, and sensing technologies. However, integrating them with existing silicon-based technology has been a challenge due to temperature restrictions. Luckily, a new group of materials called “indium-based chalcogenides” offers a solution, as they can be synthesized at low temperatures compatible with current technology. The project team plans to create a range of devices using these materials to accelerate the performance of energy-efficient spiking neural networks (SNNs). These brain-inspired microchips will revolutionize how audio, visual, tactile, and olfactory information is processed, making devices smarter and more responsive. Moreover, these microchips could be used in autonomous vehicles, drones, and robots, helping them navigate and avoid obstacles. The project also focuses on training the next generation of scientists and engineers and promoting diversity and inclusivity in the field.This project aims to address the challenge of integrating novel 2D materials with the state-of-the-art silicon-based complementary metal oxide semiconductor (CMOS) technology at the back end of line (BEOL). The key innovation lies in leveraging indium-based chalcogenides, such as InSe and In2Se3, which can be synthesized at low temperatures, making them compatible with BEOL processes. The team plans to synthesize and characterize these materials to fabricate an array of sensing, encoding, computing, and memory devices for hardware acceleration of energy-efficient spiking neural networks (SNNs). The project will involve a cross-layer co-optimization approach that encompasses material discovery, synthesis and deposition techniques, process flow development, and device-circuit-architecture co-design. The goal is to develop brain-inspired SNN microchips through 2D/CMOS heterogeneous and monolithic integration, which will lead to substantial reductions in energy consumption and pave the way for sustainable computing paradigms. The broader impact of this work extends to applications on the Internet of Things (IoT) domain, where the brain-mimetic SNN microchips will enable advanced audio, visual, tactile, and olfactory information processing. Additionally, the project emphasizes education and training, promoting diversity and inclusiveness in the workforce.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.

该项目旨在使用称为“2D 材料”的创新材料来增强现代集成电路的功能，这些材料具有独特的电子特性，使其在计算、存储和传感技术方面非常有前景，但是，将它们与现有的硅基技术集成。由于温度限制，技术一直是一个挑战，幸运的是，一组称为“铟基硫族化物”的新材料提供了解决方案，因为它们可以在与当前技术兼容的低温下合成。使用这些材料来加速性能的设备这些受大脑启发的微芯片将彻底改变音频、视觉、触觉和嗅觉信息的处理方式，使设备更加智能、反应更快。此外，这些微芯片可用于自动驾驶汽车、无人机、该项目还致力于培训下一代科学家和工程师，并促进该领域的多样性和包容性。该项目旨在解决将新型二维材料与机器人集成的挑战。最先进的硅基互补金属氧化物半导体 (CMOS) 后端技术 (BEOL) 的关键创新在于利用可合成的铟基硫族化物，例如 InSe 和 In2Se3。该团队计划合成和表征这些材料，以制造一系列传感、编码、计算和存储设备，用于节能尖峰神经网络 (SNN) 的硬件加速。该项目将涉及跨层协同优化方法，包括材料发现、合成和沉积技术、工艺流程开发以及器件-电路-架构协同设计，目标是通过 2D/CMOS 开发受大脑启发的 SNN 微芯片。异构和单片集成，这将导致能源消耗的大幅减少，并为可持续计算范式铺平道路，这项工作的更广泛影响延伸到物联网（IoT）领域的应用，其中模拟大脑。 SNN 微芯片将实现先进的音频、视觉、触觉和嗅觉信息处理。此外，该项目强调教育和培训，促进劳动力的多样性和包容性。该奖项反映了 NSF 的法定使命，并通过使用该奖项的评估被认为值得支持。基金会的智力价值和更广泛的影响审查标准。