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综合电路的能力。这些材料具有独特的电子特性，使它们非常有希望对计算，存储和传感技术。但是，由于温度限制，将它们与现有的基于硅的技术集成到现有的技术。幸运的是，一组称为“基于依赖的硫元化的硫化剂”的新材料提供了一种解决方案，因为它们可以在与当前技术兼容的低温下合成。该项目团队计划使用这些材料来创建一系列设备，以加快节能尖峰神经网络（SNN）的性能。这些受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，从而使设备更聪明，更响应。此外，这些微芯片可用于自动驾驶汽车，无人机和机器人，可帮助它们导航和避免物体。该项目还侧重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。该项目旨在应对将新颖的2D材料与最先进的硅基金属氧化物半导体（CMOS）技术相结合的挑战。关键的创新在于利用基于依赖的硫代基因剂，例如INSE和IN2SE3，它们可以在低温下合成，使其与Beol工艺兼容。该团队计划合成和表征这些材料，以制造一系列感应，编码，计算和内存设备，以加速节能尖峰神经网络（SNNS）。该项目将涉及跨层合作方法，该方法包括材料发现，合成和沉积技术，过程流动开发以及设备电路架构共同设计。目的是通过2D/CMOS的异质和单片整合开发受脑启发的SNN微芯片，这将导致能源消耗大量减少，并为可持续计算范式铺平道路。这项工作的更广泛影响扩展到物联网（IoT）域上的应用程序，在该域中，大脑模拟的SNN微芯片将实现高级音频，视觉，触觉和嗅觉信息处理。此外，该项目强调教育和培训，促进劳动力中的多样性和包容性。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响评估标准来评估，认为这是珍贵的支持。