Evolving parallel machine programs for a multi-ALU processor

Author

Leung, Kwong Sak ; Lee, Kin Hong ; Cheang, Sin Man

Author_Institution

Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, China

Volume

2

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

1703

Lastpage

1708

Abstract

This paper proposes a novel genetic parallel programming (GPP) paradigm for evolving optimal parallel programs running on a multi-ALU processor by linear genetic programming. GPP uses a two-phase evolution approach. It evolves completely correct solution programs in the first phase. Then it optimizes execution speeds of solution programs in the second phase. Besides, GPP also employs a new genetic operation that swaps sub-instructions of a solution program. Three experiments (Sextic, Fibonacci and Factorial) are given as examples to show that GPP could discover novel parallel programs that fully utilize the processor´s parallelism

Keywords

genetic algorithms; instruction sets; multiprocessing systems; parallel programming; Factorial sequence; Fibonacci sequence; Sextic function; experiments; genetic parallel programming; linear genetic programming; multi-ALU processor; optimal parallel program evolution; parallel machine programs; program execution speed optimization; two-phase evolution; Clocks; Computer science; Concurrent computing; Field programmable gate arrays; Genetic engineering; Genetic programming; Parallel machines; Parallel programming; Registers; Silicon compounds;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-7282-4

Type

conf

DOI

10.1109/CEC.2002.1004499

Filename

1004499