Journal of Frontiers of Computer Science and Technology ›› 2021, Vol. 15 ›› Issue (10): 2015-2024.DOI: 10.3778/j.issn.1673-9418.2006059

• Theory and Algorithm • Previous Articles    

Parallel SaNSDE for Many-Core Sunway Processor

KANG Shang, QIAN Xuezhong, GAN Lin   

  1. 1. Engineering Research Center of Internet of Things Technology Applications, Ministry of Education, College of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, Jiangsu 214122, China
    2. National Supercomputing Center in Wuxi, Wuxi, Jiangsu 214131, China
    3. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
  • Online:2021-10-01 Published:2021-09-30



  1. 1. 江南大学 人工智能与计算机学院 物联网技术应用教育部工程研究中心,江苏 无锡 214122
    2. 国家超级计算无锡中心,江苏 无锡 214131
    3. 清华大学 计算机科学与技术系,北京 100084


Evolutionary algorithm is an important method for solving large-scale optimization problems, which is widely applied to machine learning, process control, engineering optimization, management science, and social sciences. However, when the traditional evolutionary algorithms are used to high-dimensional and computing-density task, the performance of corresponding applications is difficult to be satisfactory. Parallelization on supercomputer is a popular solution to solve this problem. This paper proposes a two-level parallel self-adaptive differential evolution algorithm with neighborhood search (SaNSDE) on the Sunway TaihuLight, which implements process-level and thread-level parallelism. In the process-level parallelism, the cooperative co-evolution model and pool model are implemented, which divide large-scale problems into multiple low-dimensional problems and distribute them in different processes. In the thread-level parallelism, fitness calculation is accelerated. Experimental results show that the algorithm using the cooperative co-evolution model and the pool model, compared with the traditional parallel algorithm, improves the convergence effect more obviously after multi-core expansion. Compared with the serial algorithm, the two-level parallel SaNSDE algorithm achieves the maximum speedup of 134.29, 186.05, 239.01 and 189.80 in the four benchmark functions, respectively.

Key words: high-performance computing, Sunway heterogeneous multi-core processor, evolutionary algorithm, cooperative co-evolution (CC), pool model



关键词: 高性能计算, 申威异构众核处理器, 演化算法, 合作协同进化模型(CC), 池模型