The Implementation and Comparison of Two Kinds of Parallel Genetic Algorithm Using Matlab

Author

Nan, Li ; Pengdong, Gao ; Yongquan, Lu ; Wenhua, Yu

Author_Institution

High Performance Comput. Center, Commun. Univ. of China, Beijing, China

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

13

Lastpage

17

Abstract

Two kinds of parallel genetic algorithm (PGA) are implemented in this paper based on the MATLAB^® Parallel Computing Toolbox™ and Distributed Computing Server™ software. Parallel for-loops, SPMD (Single Program Multiple Data) block and co-distributed arrays, three basic parallel programming modes in MATLAB are employed to accomplish the global and coarse-grained PGAs. To validate and compare our implementation, both PGAs are applied to run the problem of range image registration. A set of experiments have illustrated that it is convenient and effective to use MATLAB to parallelize the existing algorithms. At the same time, a higher speed-up and performance enhancement can be obtained obviously.

Keywords

genetic algorithms; image registration; mathematics computing; parallel algorithms; parallel programming; Matlab parallel computing toolbox; codistributed array; distributed computing server software; image registration; parallel for loop; parallel genetic algorithm; parallel programming; single program multiple data block; Arrays; Distributed computing; Electronics packaging; MATLAB; Mathematical model; Parallel processing; MATLAB; distributed computing; parallel genetic algorithm; parallel programming;

fLanguage

English

Publisher

ieee

Conference_Titel

Distributed Computing and Applications to Business Engineering and Science (DCABES), 2010 Ninth International Symposium on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-7539-1

Type

conf

DOI

10.1109/DCABES.2010.9

Filename

5572154