SHF: Small: Overcoming Nanoscale Modeling Challenges in Analog Synthesis: A Data-Driven Paradigm for Optimization of Approximate Functions

提高模拟集成电路设计领域的生产率需要开发新一代的电路综合工具。一个主要的挑战是，晶体管尺寸的持续缩放遵循摩尔定律使得难以以适合于电路优化的形式描述晶体管的物理行为。本提案下的工作将开发一种新的方法，用于优化晶体管行为的近似描述，这是以适合自动合成的方式捕获模拟电路行为的唯一现实方法。该方法是基于显式建模的精确模型和近似模型之间的分歧。该研究将具体开发：（1）一个新的模拟合成框架，用于基于模型的近似函数优化，该框架能够明确考虑近似模型和精确模型之间的误差分布，以驱动优化到相对于精确模型保证为真的解决方案;（2）一种新的模型拟合算法，为近似函数的高度约束优化而定制，这将进一步增强综合工具产生良好解决方案的能力。该提案的工作成果将提高模拟和混合信号设计的自动化程度，并提高设计生产率，以及更节能和更便宜的集成电路。因此，这项工作将有助于维持半导体技术的发展和增长，在过去的50年里，半导体技术已经产生了巨大的社会影响。开发的概念也将有利于其他科学领域，其中使用近似函数的优化。该提案的教育部分旨在将这一领域的积极研究方案和研究经验与建立教学和教学基础设施联合收割机结合起来。具体而言，研究生课程提供的PI将纳入本研究中开发的设计方法的方面。

Increasing productivity in the area of analog integrated circuit design requires the development of a new generation of circuit synthesis tools. A major challenge is that continued scaling of transistor dimensions following Moore's Law makes it difficult to describe the physical behavior of transistors in the form suitable for circuit optimization. The work under this proposal will develop a new approach for optimization over approximate descriptions of transistor behavior, which is the only realistic way to capture analog circuit behavior in a manner appropriate for automated synthesis. The approach is based on explicitly modeling the divergence between the exact model and the approximate model. The research will specifically develop: (1) a new analog synthesis framework for model-based optimization over approximate functions that is able to explicitly take into account the distribution of errors between the approximate and exact models to drive optimization to a solution guaranteed to be true with respect to the exact model; (2) a new model-fitting algorithm, tailored for highly-constrained optimization over approximate functions, that will further enhance the ability of the synthesis tool to produce a good solution. The outcomes of the work under this proposal will lead to increased automation of analog and mixed-signal design, and result in higher design productivity, as well as more power-efficient and cheaper integrated circuits. Thus, this work will help sustain the evolution and growth of semiconductor technology that has had enormous social implications over the last fifty years. The concepts to be developed will also benefit other scientific domains in which optimization using approximate functions is used. The educational component of this proposal aims to combine the active research program and research experience in this field with the creation of an instructional and teaching infrastructure. Specifically, the graduate courses offered by the PIs will incorporate the aspects of design methodologies developed in this research.