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An enhanced optimization kernel for analog IC design automation using the shrinking circles technique

机译:使用缩圆技术的用于模拟IC设计自动化的增强型优化内核

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摘要

This paper presents a novel sizing automation tool to improve the efficiency and accuracy of the analog IC design process. A new technique named the "shrinking circles" is proposed to create a balance between the exploration and exploitation capabilities when the optimization algorithm is converging to a possible optimum point. With the help of the shrinking circles concept, an upgraded version of Gravitational Search Algorithm (GSA) named Advanced GSA (AGSA) is proposed to be used as an optimization kernel for our circuit sizing tool. The performance of the proposed AGSA is evaluated over 23 benchmark functions and the results are compared with the standard GSA and Clustered-GSA algorithms. A two-stage op-amp in the 0.35 μm CMOS technology is utilized to validate the performance of the proposed sizing tool. The corners analysis is also performed over the obtained solutions to guarantee their robustness against the process and environmental variations. Finally, a statistical study over the final solutions is conducted from the two aspects of quantitative and qualitative analyses.
机译:本文提出了一种新颖的上浆自动化工具,以提高模拟IC设计过程的效率和准确性。当优化算法收敛到可能的最佳点时,提出了一种称为“收缩圆”的新技术,以在勘探和开发能力之间建立平衡。借助缩圆概念,提出了一种称为高级GSA(AGSA)的引力搜索算法(GSA)的升级版本,它将用作我们的电路尺寸确定工具的优化内核。拟议的AGSA的性能在23个基准功能上进行了评估,并将结果与​​标准GSA和Clustered-GSA算法进行了比较。采用0.35μmCMOS技术的两级运算放大器来验证所提出的尺寸调整工具的性能。还对获得的解决方案执行角点分析,以确保其针对过程和环境变化的稳健性。最后,从定量和定性分析两个方面对最终解决方案进行了统计研究。

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