计算机科学 ›› 2011, Vol. 38 ›› Issue (11): 296-302.

• 体系结构 • 上一篇    

基于通用多核处理器平台的并行基因表达式编程算法

吴江,唐常杰,李太勇,姜玥,李自力,刘洋洋   

  1. (西南财经大学经济信息工程学院 成都610074) (四川大学计算机学院 成都610064)(西南民族大学计算机科学与技术学院 成都610041)
  • 出版日期:2018-12-01 发布日期:2018-12-01

Parallel Gene Expression Programming Based on General Multi-core Processor

  • Online:2018-12-01 Published:2018-12-01

摘要: 基因表达式编程(Gene Expression Programming, GEP)是一种计算量大且通用性强的新型进化算法,其传统计算形式不能充分利用目前主流的多核处理器。为提高算法效率,提出了基于通用多核处理器平台的并行基因表达式编程算法(Parallel Gene Expression Programming Based on General Multi-core Processor, PGEP-MP)。主要工作包括:O)分析通用多核处理器平台下并行基因表达式编程算法的机理;(2)利用MPI和()pcnMP混合编程模型设计基于通用多核处理器平台的基因表达式编程算法的粗粒度与细粒度相结合的并行模型;(3)提出改进PEEP-MP算法效率的进化策略;(4)通过对函数挖掘和分类的实验证明,PEEP-Ml〕算法提高了函数挖掘和分类的效率,在并行双核处理器数为4的情况下,PEEP-MP的平均并行加速比分别是传统GEP算法的4. 22倍和 4. 06倍。

关键词: 基因表达式编程,多核处理器,并行,进化算法

Abstract: Gene Expression Programming(GEP) is a new versatile evolution algorithm with huge calculation. The conventional GEP cannot take advantage of current popular multi-core processors. In order to improve the efficiency of GEP, parallel Gene Expression Programming based on general multi-core processor (PEEP-MP) was proposed. The main contributions include: (1) the mechanism of parallel GEP based on general multi core processor is analyzed; (2)the parallel model of GEP based on general multi core processor combined with coarscgrained and fincgrained levels is designed by the combination of MPI and OpenMP; (3) evolution strategies to improve PEEP-MP are proposed; (4) experiments on function mining and classification show that PGEPMP improves the efficiency of function mining and classification. Compared with conventional GEP, the mean parallel speedup ratio of PEEP-MP are 4. 22 and 4. 02 times while the number of parallel dual core processors is 4.

Key words: Gene expression programming(GEP) , Multi-core processor, Parallel, Evolution algorithm

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