Local neurocomputing method for resolving VLSI relocation problems

Author

Karimi, G.R. ; Verki, A. Azizi

Author_Institution

Dept. of Electr. Eng., Fac. of Eng., Kermanshah, Iran

fYear

2010

fDate

15-17 June 2010

Firstpage

45

Lastpage

49

Abstract

In this paper a fast migration method is proposed. Our method executes local relocation on a model placement where an additional module is added to it for modification with minimum number of engaging modules. This method is based on Mean Field Annealing (MFA) which produces a solution as liable as previously used method called simulated annealing (SA) in substantially less time and hardware. In addition, the runtime of solution is mostly independent of size and complexity of input model placement.

Keywords

VLSI; simulated annealing; VLSI relocation problems; input model placement; local neurocomputing method; mean field annealing; model placement; simulated annealing; Algorithm design and analysis; Circuit simulation; Data mining; Design engineering; Hardware; Modular construction; Partitioning algorithms; Runtime; Simulated annealing; Very large scale integration; Circuit Modification; Mean Field Annealing; VLSI; component; formatting;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on

Conference_Location

Taichung

Print_ISBN

978-1-4244-5045-9

Electronic_ISBN

978-1-4244-5046-6

Type

conf

DOI

10.1109/ICIEA.2010.5514997

Filename

5514997