DocumentCode
2007179
Title
Parallel genetic algorithm based on Thread-Level Speculation
Author
Wen-jiang, Zhao ; Hong-bin, Yang ; Yue, Wu
Author_Institution
Sch. of Comput. Eng. & Sci., Shanghai Univ. Shanghai, Shanghai, China
fYear
2010
fDate
23-25 Nov. 2010
Firstpage
244
Lastpage
248
Abstract
An improved method of classic genetic algorithms is proposed which uses Thread-Level Speculation (TLS) technology for the shortcoming that classic genetic algorithm´s search speed is slow. Unlike the classic genetic algorithm, Firstly we replace an individual with a single thread, use TLS technology to process each thread parallel, in order to eliminate the correlation among threads, increase individual diversity in the population, thus accelerate the convergence speed of genetic algorithms. Experimental results demonstrate that the method can increase the individual diversity in the population and accelerate the convergence speed of genetic algorithms, compared with the classic genetic algorithms.
Keywords
convergence; genetic algorithms; parallel programming; convergence speed; parallel genetic algorithm; thread-level speculation; Acceleration; Algorithm design and analysis; Computer architecture; Convergence; Correlation; Instruction sets; Process control;
fLanguage
English
Publisher
ieee
Conference_Titel
Audio Language and Image Processing (ICALIP), 2010 International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-5856-1
Type
conf
DOI
10.1109/ICALIP.2010.5684374
Filename
5684374
Link To Document