SBIR Phase I: Energy Efficient Superconducting Neuromorphic Computing Circuits

小型企业创新研究(SBIR)第一阶段项目的更广泛影响是超导神经形态计算(NC)电路的潜在商业开发，能够实现真正的生物大脑启发的深度神经网络电路算法，并将NC的效率、速度和可扩展性提高数量级。通过这一努力开发的知识和方法可能有助于推进下一代计算硬件的基础开发，帮助NC继续朝着广泛的市场采用前进，并帮助美国保持其在处理器开发和生产方面的领先地位。此外，集成的合成-表征-应用方法可以扩展到一系列应用，包括传感器、超材料、催化和可再生能源，这些应用需要对材料和界面进行原子尺度的控制。最后，通过与堪萨斯大学的合作，该项目将促进大学技术转让，并将有助于培养下一代材料和先进的电子科学家和工程师。从原子到纳米尺度的设计、制造、表征和应用经验不仅有助于招收高质量的学生，还将为他们提供创业机会。这个小企业创新研究(SBIR)第一阶段项目旨在开发由具有超导互连的原子可调记忆阻器(突触)和超导量子干涉器件(SQUID，神经元)组成的新型超导神经形态计算(NC)电路。这种超导NC电路旨在实现真正的生物大脑启发的深度网络电路算法，并在NC中实现目前无法达到的能效、切换速度和可扩展性水平。拟议的研究将设计、制造和表征超导忆阻器-SQUID NC电路硬件，包括开发相应的模式识别算法，具有机器学习能力，使用修改后的国家标准与技术研究所数据库来证明可行性。拟议研究的智力价值体现在：(1)新颖的、原子可调的忆阻器，其通断比和开关频率的动态范围为3-4个数量级，可以根据新兴深层次电路的要求实现不同幅度和频率的尖峰；(2)具有非常高灵敏度和低噪声的SQUID神经元；以及(3)神经元和互连，可以通过消除寄生导线电阻显著降低功耗，在当前NC电路中，寄生导线电阻随着电路规模的扩大而大幅增加。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is potential commercial development of superconducting neuromorphic computing (NC) circuits with the ability to enable true biological brain-inspired deep neural network circuit algorithms and to improve efficiency, speed, and scalability of NC by orders of magnitude. The knowledge and approaches developed through this effort may help advance the foundational development of next generation computing hardware, helping NC continue its advance toward broad market adoption, and helping the US maintain its position as a leader in processor development and production. Additionally, the integrated synthesis-characterization-application approach can be extended to a range of applications, including sensors, metamaterials, catalysis, and renewables, which require atomic-scale control of materials and interfaces. Finally, through a partnership with University of Kansas, the project will facilitate university technology transfer and will serve to educate the next generation of materials and advanced electronics scientists and engineers. The atomic-to-nanoscale design, fabrication, characterization, and application experience will not only assist in recruiting top-quality students and provide them opportunities for entrepreneurship.This Small Business Innovation Research (SBIR) Phase I project seeks to develop novel superconducting neuromorphic computing (NC) circuits consisting of atomically tunable memristors (synapses) with superconductor interconnects and superconducting quantum interference devices (SQUIDs, neurons). This superconducting NC circuit aims to enable true biological brain-inspired deep network circuit algorithms and to achieve currently unattainable levels of energy efficiency, switching speed, and scalability in NC. The proposed research will design, fabricate, and characterize superconducting memristor-SQUID NC circuit hardware including development of the corresponding algorithms for pattern recognition, with machine learning capabilities, using the Modified National Institute of Standards and Technology database to prove viability. The intellectual merit of the proposed research is illustrated in: (1) novel, atomically-tunable memristors with 3-4 orders of magnitude dynamic range in the on/off ratio and switching frequency that can enable spikes of different amplitudes and frequencies as demanded for emerging deep circuits, (2) SQUID neurons with very high sensitivity and low noise, and (3) neurons and interconnects that can significantly reduce power consumption by eliminating the parasitic wire resistance that, in current NC circuits, increases substantially with circuit scale.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.