DocumentCode :
2887604
Title :
A parallel min-cut technique for standard cell placement using a modified Hopfield neural network
Author :
Sriram, M. ; Kang, S.M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana-Champaign, IL, USA
fYear :
1991
fDate :
16-17 Jun 1991
Firstpage :
894
Abstract :
The authors present a new min-cut technique for standard cell placement using a modified Hopfield neural network. The neural network has the advantage of a massively parallel architecture, which can drastically reduce computation time in a hardware implementation. It also allows all partitions at a given level of the hierarchical procedure to be performed in parallel, thus overcoming a common drawback of sequential min-cut procedures. The approach has produced very good results on a number of practical standard cell circuits
Keywords :
VLSI; application specific integrated circuits; circuit layout CAD; graph theory; integrated circuit technology; neural nets; parallel processing; ASIC; IC layout design; VLSI design; massively parallel architecture; modified Hopfield neural network; parallel min-cut technique; standard cell placement; Circuits; Computer networks; Concurrent computing; Costs; Hopfield neural networks; Joining processes; Neural network hardware; Neural networks; Neurons; Parallel architectures;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1991. Conference Proceedings, China., 1991 International Conference on
Conference_Location :
Shenzhen
Type :
conf
DOI :
10.1109/CICCAS.1991.184506
Filename :
184506
Link To Document :
بازگشت