多尺度量子谐振子优化算法的并行性研究  

Parallelism of multi-scale quantum harmonic oscillator algorithm

作　　者：黄焱[1] 王鹏[2] 程琨[3] 刘峰[4] 

机构地区：[1]淮阴师范学院计算机科学与技术学院,江苏淮安223300 [2]西南民族大学计算机科学与技术学院,四川成都610225 [3]中国科学院成都计算机应用研究所,四川成都610041 [4]成都信息工程大学并行计算实验室,四川成都610225

出　　处：《通信学报》2016年第9期68-74,共7页Journal on Communications

基　　金：国家自然科学基金资助项目(No.60702075);模式识别与智能信息处理四川省高校重点实验室开放基金资助项目(No.MSSB-2015-9)~~

摘　　要：多尺度量子谐振子优化算法(MQHOA,multi-scale quantum harmonic oscillator algorithm)是一种利用量子谐振子波函数构造的新的智能算法,采样运算是MQHOA算法的基本运算单元和主要运算量,采样运算的独立性赋予MQHOA算法内在并行性。通过对MQHOA算法群体参数和采样参数进行实验,确定算法的并行粒度并提出多尺度量子谐振子并行算法(MQHOA-P,multi-scale quantum harmonic oscillator parallel algorithm)。在由10个计算节点构成的集群上对6种标准测试函数进行实验,通过改变计算节点数、函数维数和采样参数测试MQHOA-P算法的加速比,实验结果表明,MQHOA-P算法具有良好的加速比和扩展性,可以在大规模集群中部署、运行。MQHOA was a novel intelligent algorithm constructed by quantum harmonic oscillator＇s wave function. Sampling was the basic operation and main computational burden of MQHOA. The independence of sampling operation constructs MAHOA＇s parallelism. Parallel granularity was obtained by experiments of group parameter and sampling parameter, and MQHOA-P was proposed. Experiments were done in a cluster of ten nodes on six standard test functions. By changing node number, function dimension and sampling parameter, experiments of MQHOA-P＇s speed-up ratio were done. The experimental results show the good performance of MQHOA-P＇s speed-up ratio and expansibility. MQHOA-P can be deployed and run on multiple nodes in a large-scale cluster.

关 键 词：多尺度量子谐振子优化算法 算法并行性 加速比 并行粒度 函数优化 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]