SHF: SMALL: A Novel Algorithm for Automated Synthesis of Passive, Causal, and Stable Models for Optical Interconnects

随着大数据和物联网的爆炸性增长，以及对高性能计算、移动性、安全性和高保真体验的需求不断增长，对能够在芯片上高效传输数据的高带宽和低损耗互联技术的需求越来越大。光纤及其用于高带宽数据传输的巨大容量在电信行业中是众所周知的，并在其长距离互连网络中被广泛利用。缩小光学互连以适应纳米级硅芯片显然有利于实现片上高带宽数据传输--然而，一个主要障碍是缺乏准确和高效的可计算随机电磁模型来模拟光学互连结构，所述光学互连结构由多个紧耦合的纳米级绝缘体上硅(SOI)波导组成，其通过片上发射器和接收器携带信息信号(即太赫兹电磁波)。该方案的总体目标是开发一种软件工具的算法，以执行基于表现出随机表面粗糙度的SOI波导的三维(3-D)纳米级光学互连的设计、分析和优化。这个项目的整体教育部分是利用开发的模型和软件来：(1)开发新的研究生课程，(2)为本科课程开发互动学习对象和基于实验的活动，(3)激发本科生对科学的兴趣，并招收和指导包括妇女和少数群体在内的不同群体的学生。项目团队将开发光互连设计器工具(OIDT)软件，其输入包括：(1)表示多端口光互连系统物理描述的指定3-D几何图形；(2)SOI光波导表面粗糙度的随机分布；(3)光波导材料的电学特性。OIDT将自主地综合两种类型的电气模型：(1)用于在频域中优化互连设计的网络散射参数，以及(2)用于在时间域中与有源非线性驱动器和组件集成的无源互连的时序分析和信号/功率完整性分析的稳定、无源和因果SPICE等效电路模型。拟议的基于Python的软件包可以独立使用，也可以集成到现有的计算机辅助设计(CAD)工具和设计流程中，以促进设计自动化，并为包括计算、通信、能源、安全、传感、健康等各种应用的先进微电子研发提供便利。该数值计划将作为开源项目托管在GitHub上，以促进和促进(国际)国家光学设备研究。教育部分扩大了公众的科学素养。这一奖项反映了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。

With the explosive growth of Big Data and Internet of Things, and the ever-growing demand for high-performance computing, mobility, security, and high-fidelity experiences, there is an increasing need for high-bandwidth and low-loss interconnect technologies that enable efficient data transfer across the chip. The optical fiber and its significant capacity for high-bandwidth data transfer are well-known in the telecommunications industry, and widely exploited in their long-distance network of interconnects. Scaling down optical interconnects to fit in nano-scale silicon chips would clearly be advantageous for achieving high-bandwidth data transfer on-chip -- however, a major hurdle is the dearth of accurate and efficient computable stochastic electromagnetic models for simulation of optical interconnect structures comprised of multiple tightly-coupled nano-scale silicon-on-insulator (SOI) wave-guides that carry information signals (i.e., TeraHertz electromagnetic waves) across on-chip transmitters and receivers. The overall goal of this proposal is to develop algorithms for a software tool to perform the design, analysis, and optimization of 3-dimensional (3-D) nano-scale optical interconnects based on SOI wave-guides exhibiting random surface roughness. The overall educational components of this project are to leverage the developed models and software to: (1) develop new graduate courses, (2) develop interactive learning objects and lab-based activities for undergraduate courses, and (3) stimulate undergraduate students' interest in science, and recruit and mentor diverse groups of students including women and minority groups. The project team will develop the Optical Interconnect Designer Tool (OIDT) software, of which the input is comprised of: (1) the specified 3-D geometry representing the physical description of the multi-port optical interconnect system, (2) the random distribution for surface roughness of SOI wave-guide, and (3) the wave-guide material's electrical properties. The OIDT will autonomously synthesize two types of electrical models: (1) network scattering parameters for design optimization of the interconnect, in the frequency-domain, and (2) stable, passive, and causal SPICE equivalent circuit models for timing analysis and signal/power integrity analysis of the passive interconnect, integrated with active non-linear drivers and components, in the time-domain. The proposed Python-based software package may be used stand-alone, or integrated into existing computer aided design (CAD) tools and design-flows to facilitate design automation, and research and development of advanced microelectronics for a variety of applications including computing, communications, energy, security, sensing, health, etc. The numerical program will be hosted on GitHub as an open-source project, to facilitate and promote (inter)national optical device research. The education component expands public's scientific literacy.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.