• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2022, Vol. 44 ›› Issue (03): 396-402.

• 高性能计算 • 上一篇    下一篇

基于机器学习的PCB布线电阻计算方法

刘国强1,赵振宇1,赵晨煜2,韩奥1,杨天豪1   

  1. (1.国防科技大学计算机学院,湖南 长沙 410073; 2.国防科技大学前沿交叉学科学院,湖南 长沙 410073)
  • 收稿日期:2020-12-23 修回日期:2021-02-02 接受日期:2022-03-25 出版日期:2022-03-25 发布日期:2022-03-24
  • 基金资助:
    国家自然科学基金(62034005)

A PCB routing resistance calculation method based on machine learning

 LIU Guo-qiang1,ZHAO Zhen-yu1,ZHAO Chen-yu2,HAN Ao1,YANG Tian-hao1   

  1. (1.College of Computer Science and Technology,National University of Defense Technology,Changsha 410073;
    2.College of Advanced Interdisciplinary Studies,National University of Defense Technology,Changsha 410073,China)
  • Received:2020-12-23 Revised:2021-02-02 Accepted:2022-03-25 Online:2022-03-25 Published:2022-03-24

摘要: 在FPD领域中FPC端口和IC端口之间的布线被称为PCB布线。受到可布线区域形状、线宽和线间距等多种因素的影响,PCB布线可能是规则形状的布线,也可能是不规则形状的布线,导致精确计算布线电阻十分困难。现有的电阻计算方法能够基于布线拐点坐标计算任意形状的PCB布线电阻,但是这些方法时间开销和空间开销都很大,严重影响设计的收敛性,并且也无法有效利用已有的布线数据。首次研究了基于机器学习的PCB布线电阻计算方法:首先,将任意形状的PCB布线划分为多个连续的四边形布线;其次,利用建立的四边形布线电阻计算方法,对单个四边形布线进行电阻预测;最后,将所有四边形布线的电阻值进行累加获得该PCB布线的电阻值。通过“划分-预测-计算”的方式可以对任意形状的PCB布线电阻进行快速、准确的计算。与传统方法相比,该方法的平均绝对误差仅约1 Ω,内存开销和时间开销分别降低了60.9%和97.9%。

关键词: 电阻计算, 机器学习, PCB布线

Abstract: In the field of FPD, the routing between FPC ports and IC ports is called PCB routing. Affected by many factors such as the shape of routing area, the width of interconnect, the space between interconnects and so on, PCB routing may be regular or irregular, which makes it very difficult to accurately and quickly calculate the interconnect resistances. The existing resistance calculation method can calculate the resistance of PCB routing with arbitrary shape based on the coordinates of the inflection point of routing, but has very large time and space overhead, which seriously affects the convergence of the design and cannot effectively utilize historical routing data. The calculation method of PCB routing resistance based on machine learning is studied for the first time. Firstly, the PCB routing with arbitrary shape is divided into several continuous quadrilateral. Secondly, the resistance of a single quadrilateral is predicted by using the established quadrilateral resistance calculation method. Finally, the resistance values of all quadrilateral routing are accumulated to obtain the resistance of the PCB routing. Efficient and accurate calculation of the resistance of PCB routing with ar-bitrary shape is carried out through the “division-prediction-calculation” method. Compared with the tradi-tional method, the average absolute error of our method is only about 1 ohm, and the memory cost and time cost are reduced by 60.9% and 97.9%, respectively.


Key words: resistance calculation, machine learning, PCB routing ,