DocumentCode
1254170
Title
Graph-based evolutionary design of arithmetic circuits
Author
Chen, Dingjun ; Aoki, Takafumi ; Homma, Naofumi ; Terasaki, Toshiki ; Higuchi, Tatsuo
Author_Institution
Dept. of Syst. Inf. Sci., Tohoku Univ., Sendai, Japan
Volume
6
Issue
1
fYear
2002
fDate
2/1/2002 12:00:00 AM
Firstpage
86
Lastpage
100
Abstract
We present an efficient graph-based evolutionary optimization technique, called evolutionary graph generation (EGG), and the proposed approach is applied to the design of combinational and sequential arithmetic circuits based on parallel counter-tree architecture. The fundamental idea of EGG is to employ general circuit graphs as individuals and manipulate the circuit graphs directly using new evolutionary graph operations without encoding the graphs into other indirect representations, such as the bit strings used in genetic algorithm (GA) proposed by Holland (1992) and trees used in genetic programming (GP) proposed by Koza et al. (1997). In this paper, the EGG system is applied to the design of constant-coefficient multipliers and the design of bit-serial data-parallel adders. The results demonstrate the potential capability of EGG to solve the practical design problems for arithmetic circuits with limited knowledge of computer arithmetic algorithms. The proposed EGG system can help to simplify and speed up the process of designing arithmetic circuits and can produce better solutions to the given problem
Keywords
adders; circuit CAD; combinational circuits; genetic algorithms; graph theory; multiplying circuits; sequential circuits; adders; canonic signed-digit representation; combinational arithmetic circuits; digital signal processing; electronic design automation; evolutionary graph generation; evolutionary optimization; genetic algorithm; multipliers; parallel counter-tree; sequential arithmetic circuits; Adders; Algorithm design and analysis; Circuits; Design optimization; Digital arithmetic; Encoding; Genetic algorithms; Genetic programming; Process design; Tree graphs;
fLanguage
English
Journal_Title
Evolutionary Computation, IEEE Transactions on
Publisher
ieee
ISSN
1089-778X
Type
jour
DOI
10.1109/4235.985694
Filename
985694
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