Tunable analog/RF circuit has emerged as a promising technique to address the significant performance uncertainties caused by process variations. To optimize these tunable circuits after fabrication, most existing post-silicon programming methods are developed by using real-valued performance metrics. However, when measuring a performance of interest on silicon, it is often substantially more expensive to obtain a real-valued measurement than a binary testing outcome (i.e., pass or fail). In this article, we propose a Gaussian Process Classification model to capture the binary performance metrics of tunable analog/RF circuits. Based on these models, post-silicon programming is cast into an optimization problem that can be solved by a novel Bayesian optimization algorithm. Moreover, measurement noises are further incorporated into our proposed post-silicon programming to produce a robust circuit. Two circuit examples demonstrate that the proposed approach can efficiently program tunable circuits with binary performance metrics while other conventional methods are not applicable.

Renjian Pan

Jun Tao

Yangfeng Su

Dian Zhou

Xuan Zeng

Xin Li

ACM Transactions on Design Automation of Electronic Systems

TODAES 是电子系统设计和自动化领域的一流 ACM 期刊。它出版的创新工作记录了电子系统规范、设计、分析、模拟、测试和评估方面的重大研究和开发进展，强调计算机科学/工程方向。欢迎理论分析和实际解决方案。

ACM Transactions on Design Automation of Electronic Systems is a leading journal in the field of electronic system design and automation. It publishes innovative work that documents significant research and development advancements in the specification, design, analysis, simulation, testing, and evaluation of electronic systems, with an emphasis on the intersection of computer science and engineering. We welcome submissions of theoretical analyses and practical solutions.

《ACM Transactions on Design Automation of Electronic Systems》是电子系统设计与自动化领域的顶尖期刊。该期刊发表的创新研究涵盖了电子系统的规范、设计、分析、模拟、测试和评估等方面的重大进展，强调计算机科学与工程的交叉领域。我们欢迎理论分析和实际解决方案的投稿。

Analog/RF Post-silicon Tuning via Bayesian Optimization

This article proposes a Gaussian Process Classification model to capture the binary performance metrics of tunable analog/RF circuits and demonstrates that the proposed approach can efficiently program tunable circuits withbinary performance metrics while other conventional methods are not applicable.

Category	Quartile
计算机科学	4
计算机科学, 计算机硬件	4
计算机科学, 计算机软件工程	4

Analog/RF Post-silicon Tuning via Bayesian Optimization

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Journal Info

Category	Quartile
COMPUTER SCIENCE, SOFTWARE ENGINEERING	2