AI-driven Design of Analog Integrated Circuits for Ultrasound Applications

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The analog front end is essential in most ultrasonic hardware systems, which is widely used in communications, industrial inspection, medical diagnosis, robotically enhanced sensing, surgical tools, etc. Although the analog circuit area is usually less than 20% in an SoC, its required design efforts can be more than 80%. The productivity gap between analog and digital circuits keeps widening. While the design automation level for digital circuits has been increasing steadily over the years, the design automation level for analog circuits remains very low. The analog IC design methodology remains almost unchanged over the past four decades: it is still a slow experience and trial-and-error-driven manual process. Recently, developing novel AI techniques to automate the design of analog ICs starts to attract attention. The AI-driven design lab, University of Glasgow, is a pioneer in AI-driven analog IC design. Being the first few to introduce AI techniques to analog IC design (2008), the AI-driven analog IC sizing method, called ESSAB, was proposed in 2021, which firstly addressed industry-level high-performance analog building blocks (considering the full set of "hard to learn" performances). Through comparison, ESSAB surpasses experienced designers' design quality in only a few hours. However, process, voltage, and temperature (PVT) variations have not been considered in ESSAB yet. Built upon this, this project aims to (1) Design various analog ICs for ultrasound applications using ESSAB achieving promising results. (2) Identify the pros and cons of ESSAB. (3) Propose ESSAB-II considering PVT variations obtaining robust designs, which is ready for industry use. This project is interdisciplinary. The student is expected to have a good understanding of AI techniques and have skills to implement AI algorithms through the study. However, more emphasis locates on using ESSAB and possible ESSAB-II to design ultrasonic analog ICs practically.