计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 211200075-6.doi: 10.11896/jsjkx.211200075
李辉1, 韩林2, 于哲3, 王威2
LI Hui1, HAN Lin2, YU Zhe3, WANG Wei2
摘要： 人工蜂群算法在农业农村大数据应用开发中被广泛采用,但是串行人工蜂群算法时间的复杂度较高,不适用于多维函数的快速求解问题。针对串行人工蜂群算法对多维函数求解执行效率较低的问题进行分析,通过解析多维函数及人工依赖关系判定,提出了一种基于人工蜂群算法的多维函数优化加速方法,该方法包括任务划分、数据分布、同步操作和任务并行。为了证明方法的有效性,以海光处理器为硬件测试平台,对4个多维函数进行对比测试。实验结果表明,与串行人工蜂群算法对多维函数的求解速度相比,该方法对于4个多维函数的求解速度能得到大幅提升。
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