Rectangular VLSI cell placement using force directed self-organizing maps and delta learning rules

Author

Chang, Ray-I ; Hsiao, Pei-Yung

Author_Institution

Dept. of Comput. & Inf. Sci., Nat. Chiao Tung Univ., Hsinchu, Taiwan

fYear

1994

fDate

22-26 Aug 1994

Firstpage

1020

Abstract

VLSI cell placement, with various constraints on cell size, wire connections and layout dimensions, is complicated and has been proven to be NP-hard. In a previous paper (IEEE Trans. Neural Networks, 1993), we described a force-directed self-organizing map (FDSOM), based on Kohonen´s (1989) algorithm, for resolving the VLSI cell placement problem using the circle cell model and the perceptron learning rule. In this paper, a delta learning FDSOM is presented to resolve the cell placement problem with the rectangular cell model. Experiments show that the total wire length obtained is shorter than that obtained by previous methods

Keywords

VLSI; circuit layout CAD; learning (artificial intelligence); minimisation of switching nets; self-organising feature maps; Kohonen neural net; NP-hard problem; cell size constraints; delta learning rules; force-directed self-organizing map; layout dimension constraints; rectangular VLSI cell placement; rectangular cell model; total wire length; wire connection constraints; Costs; Design optimization; Heuristic algorithms; Information science; Iterative methods; NP-hard problem; Propagation delay; Self organizing feature maps; Very large scale integration; Wire;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '94. IEEE Region 10's Ninth Annual International Conference. Theme: Frontiers of Computer Technology. Proceedings of 1994

Print_ISBN

0-7803-1862-5

Type

conf

DOI

10.1109/TENCON.1994.369136

Filename

369136