Efficient large scale integration power/ground network optimization based on grid genetic algorithm

Yun Yang, Atsushi Kurokawa, Yasuaki Inoue, Wenqing Zhao

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    In this paper we propose a novel and efficient method for the optimization of the power/ground (P/G) network in VLSI circuit layouts with reliability constraints. Previous algorithms in the P/G network sizing used the sequence-of-linear-programming (SLP) algorithm to solve the nonlinear optimization problems. However the transformation from nonlinear network to linear subnetwork is not optimal enough. Our new method is inspired by the biological evolution and use the grid-geneticalgorithm (GGA) to solve the optimization problem. Experimental results show that new P/G network sizes are smaller than previous algorithms, as the fittest survival in the nature. Another significant advance is that GGA method can be applied for all P/G network problems because it can get the results directly no matter whether these problems are linear or not. Thus GGA can be adopted in the transient behavior of the P/G network sizing in the future, which recently faces on the obstacles in the solution of the complex nonlinear problems.

    Original languageEnglish
    Pages (from-to)3412-3419
    Number of pages8
    JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
    VolumeE88-A
    Issue number12
    DOIs
    Publication statusPublished - 2005 Dec

    Keywords

    • GGA method
    • Global optimum
    • P/G network optimization
    • SLP algorithm

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Hardware and Architecture
    • Information Systems

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