Extended genetic algorithm for codesign optimization of DSP systems in FPGAs

Author

Savage, Matthew J W ; Salcic, Zoran ; Coghill, George ; Covic, Grant

Author_Institution

Dept. of Electr. & Comput. Eng., Auckland Univ., New Zealand

fYear

2004

fDate

6-8 Dec. 2004

Firstpage

291

Lastpage

294

Abstract

The multiobjective genetic algorithm is an effective solution to the complex problem of hardware-software codesign. An extended genetic algorithm (EGA) has been developed that implements a novel selection method with function scaling, adaptive crossover and mutation. This EGA is applied in a codesign optimization stage for dataflow oriented applications and synthesis on field-programmable gate arrays (FPGAs). Its effectiveness is illustrated on the problem of codesign of a self-tuning regulator considering area and performance.

Keywords

circuit optimisation; digital signal processing chips; field programmable gate arrays; genetic algorithms; hardware-software codesign; integrated circuit design; DSP systems; FPGA; adaptive crossover; codesign optimization; dataflow oriented applications; extended genetic algorithm; field-programmable gate arrays; function scaling; hardware-software codesign; multiobjective genetic algorithm; mutation; selection method; self-tuning regulator; Application software; Digital signal processing; Field programmable gate arrays; Genetic algorithms; Genetic mutations; Hardware; Regulators; Software design; Software performance; Throughput;

fLanguage

English

Publisher

ieee

Conference_Titel

Field-Programmable Technology, 2004. Proceedings. 2004 IEEE International Conference on

Print_ISBN

0-7803-8651-5

Type

conf

DOI

10.1109/FPT.2004.1393282

Filename

1393282