多尺度量子谐振子优化算法的并行性研究
TP393; 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...
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| Published in | 通信学报 Vol. 37; no. 9; pp. 68 - 74 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
淮阴师范学院计算机科学与技术学院,江苏 淮安,223300%西南民族大学计算机科学与技术学院,四川 成都,610225%中国科学院成都计算机应用研究所,四川 成都,610041%成都信息工程大学并行计算实验室,四川 成都,610225
2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-436X |
| DOI | 10.11959/j.issn.1000-436x.2016179 |
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| Abstract | TP393; 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。 |
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| AbstractList | TP393; 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。 |
| Abstract_FL | MQHOA was a novel intelligent algorithm constructed by quantum harmonic oscillator's wave function. Sam-pling was the basic operation and main computational burden of MQHOA. The independence of sampling operation con-structs MAHOA’s parallelism. Parallel granularity was obtained by experiments of group parameter and sampling pa-rameter, 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. |
| Author | 程琨 刘峰 王鹏 黄焱 |
| AuthorAffiliation | 淮阴师范学院计算机科学与技术学院,江苏 淮安,223300%西南民族大学计算机科学与技术学院,四川 成都,610225%中国科学院成都计算机应用研究所,四川 成都,610041%成都信息工程大学并行计算实验室,四川 成都,610225 |
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| Author_FL | CHENG Kun LIU Feng HUANG Yan WANG Peng |
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| DocumentTitle_FL | Parallelism of multi-scale quantum harmonic oscillator algorithm |
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| Issue | 9 |
| Keywords | algorithm parallelization 算法并行性 MQHOA 并行粒度 functional optimization speedup 函数优化 parallel granularity 加速比 多尺度量子谐振子优化算法 |
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| Title | 多尺度量子谐振子优化算法的并行性研究 |
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