{"title":"Efficient Selection and Placement of In-Package Decoupling Capacitors Using Matrix-Based Evolutionary Computation","authors":"Akash Jain;Heman Vaghasiya;Jai Narayan Tripathi","doi":"10.1109/OJNANO.2021.3133213","DOIUrl":null,"url":null,"abstract":"In the era of advanced nanotechnology where billions of transistors are fabricated in a single chip, high-speed operations are challenging due to packaging related issues. In High-Speed Very Large Scale Integration (VLSI) systems, decoupling capacitors are essentially used in power delivery networks to reduce power supply noise and to maintain a low impedance of the power delivery networks. In this paper, the cumulative impedance of a power delivery network is reduced below the target impedance by using state-of-the-art metaheuristic algorithms to choose and place decoupling capacitors optimally. A Matrix-based Evolutionary Computing (MEC) approach is used for efficient usage of metaheuristic algorithms. Two case studies are presented on a practical system to demonstrate the proposed approach. A comparative analysis of the performance of state-of-the-art metaheuristics is presented with the insights of practical implementation. The consistency of results in both the case studies confirms the validity of the proposed appraoch.","PeriodicalId":446,"journal":{"name":"IEEE Open Journal of Nanotechnology","volume":"2 ","pages":"191-200"},"PeriodicalIF":1.8000,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8782713/9316416/09640572.pdf","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of Nanotechnology","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/9640572/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 6
Abstract
In the era of advanced nanotechnology where billions of transistors are fabricated in a single chip, high-speed operations are challenging due to packaging related issues. In High-Speed Very Large Scale Integration (VLSI) systems, decoupling capacitors are essentially used in power delivery networks to reduce power supply noise and to maintain a low impedance of the power delivery networks. In this paper, the cumulative impedance of a power delivery network is reduced below the target impedance by using state-of-the-art metaheuristic algorithms to choose and place decoupling capacitors optimally. A Matrix-based Evolutionary Computing (MEC) approach is used for efficient usage of metaheuristic algorithms. Two case studies are presented on a practical system to demonstrate the proposed approach. A comparative analysis of the performance of state-of-the-art metaheuristics is presented with the insights of practical implementation. The consistency of results in both the case studies confirms the validity of the proposed appraoch.