DocumentCode :
3250704
Title :
A generalized placement algorithm based on self-organization neural network
Author :
Shen, Tao ; Gan, Jun-ren ; Yao, Lin-sheng
Author_Institution :
Shanghai Inst. of Metall., Acad. Sinica, China
Volume :
4
fYear :
1992
fDate :
7-11 Jun 1992
Firstpage :
761
Abstract :
Kohonen´s self-organization neural network is applied to VLSI cell placement. The algorithm proposed by A. Hemani and A. Postula (1990) adapted for two terminal nets is generalized to accommodate multiterminal nets. In contrast to the traditional gate-as-points model, which was proved improper for cell placement, the authors propose a net-as-points model in the new algorithm. Experiments showed that the convergence speed for the new algorithm was several times faster than for the gate-as-points model while the quality of solutions was better. Placements obtained by the new algorithm were superior to those achieved by the min-cut algorithm in terms of total wire length
Keywords :
VLSI; circuit layout CAD; self-organising feature maps; VLSI cell placement; gate-as-points model; generalized placement algorithm; multiterminal nets; net-as-points model; self-organization neural network; two terminal nets; Algorithm design and analysis; Computational modeling; Computer networks; Cost function; Gallium nitride; Neural networks; Simulated annealing; Stochastic processes; Very large scale integration; Wire;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
Type :
conf
DOI :
10.1109/IJCNN.1992.227226
Filename :
227226
Link To Document :
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