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Hybrid parallel genetic algorithm based on Sunway many-core processors
ZHAO Ruixiang, ZHENG Kai, LIU Yao, WANG Su, LIU Yan, SHENG Huanxue, ZHOU Qianhao
Journal of Computer Applications
2017, 37 (9):
2518-2523.
DOI: 10.11772/j.issn.1001-9081.2017.09.2518
When the traditional genetic algorithm is used to solve the computation-intensive task, the execution time of the fitness function increases rapidly, and the convergence rate of the algorithm is very low when the population size or generation increases. A "coarse-grained combined with master-slave" HyBrid Parallel Genetic Algorithm (HBPGA) was designed and implemented on Sunway "TaihuLight" supercomputer which is ranked first in the latest TOP500 list. Two-level parallel architecture was used and two different programming models, MPI and Athread were combined. Compared with the traditional genetic algorithm implemented on single-core or multi-core cluster with single-level parallel architecture, the algorithm using two-level parallel architecture was implemented on the Sunway many-core processors, better performance and higher speedup ratio were achieved. In the experiment, when using 16×64 CPEs (Computing Processing Elements), the maximum speedup can reach 544, and the CPE speedup ratio is more than 31.
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