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
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;
Conference_Titel :
Audio Language and Image Processing (ICALIP), 2010 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-5856-1
DOI :
10.1109/ICALIP.2010.5684374