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author:

Zhan, Q.-Q. (Zhan, Q.-Q..) [1] | Zhu, W.-X. (Zhu, W.-X..) [2] | He, X.-P. (He, X.-P..) [3] | Chen, X.-H. (Chen, X.-H..) [4]

Indexed by:

Scopus

Abstract:

Circuit partitioning plays a crucial role in very large-scale integrated circuit (VLSI) physical design automation. With current trends, partitioning with multiple objectives which includes cutsize, area, delay, and power obtains much concentration. In this paper, a multi-objective greedy randomized adaptive search procedure (GRASP) is presented for simultaneous cutsize and circuit delay minimization. Each objective is assigned a preference or weight to direct the search procedure and generate a variety of efficient solutions by changing the preference. To get a good initial partition with minimal cutsize and circuit delay, the gain of each module in a circuit is computed by considering both signal nets and circuit delay. The performance of the proposed algorithm is evaluated on a standard set of partitioning benchmark. The experimental results show that the proposed algorithm can generate a set of Pareto optimal solutions and is efficient for tackling multi-objective circuit partitioning. Copyright © 2012 Editorial Department of Journal of Donghua University.

Keyword:

Circuit partitioning; Greedy randomized adaptive search procedure (GRASP); Multi-objective optimization

Community:

  • [ 1 ] [Zhan, Q.-Q.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China
  • [ 2 ] [Zhu, W.-X.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China
  • [ 3 ] [He, X.-P.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China
  • [ 4 ] [Chen, X.-H.]Department of Basic Courses, Fujian Chuanzheng Communications College, Fuzhou 350007, China

Reprint 's Address:

  • [Zhu, W.-X.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China

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Source :

Journal of Donghua University (English Edition)

ISSN: 1672-5220

Year: 2012

Issue: 1

Volume: 29

Page: 1-4

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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