摘要
为了提高RNA二级结构预测的准确率和加速遗传算法,提出基于OpenCL大规模种群并行遗传算法。通过研究遗传算法中潜在的并行性,以Acer TMP246M-MG-5086为实验平台,先在CPU中实现遗传算法,再使用OpenCL技术在GPU中实现大规模种群并行遗传算法。测试结果表明,并行遗传算法对于RNA二级结构预测的准确率平均提高了约49.88%,使用GPU平均加速比为9.76x。
In order to improve the accuracy rate of RNA secondary structure prediction and accelerate the genetic algorithm,this thesis proposed the implementation of a large population parallel genetic algorithm based on OpenCL. Through researching the potential parallelism of genetic algorithm,this thesis uses Acer TMP246M-MG-5086 as experimental platform,firstly realizes the genetic algorithm on CPU,then realizes the large population parallel genetic algorithm on GPU. Test results show that the accuracy rate of parallel genetic algorithm prediction has been increased about 49. 88%,and the average speedup of using GPU is 9. 76 x.
出处
《计算机与现代化》
2016年第3期30-34,共5页
Computer and Modernization
关键词
大规模种群
并行遗传算法
RNA二级结构预测
large population
parallel genetic algorithm
RNA secondary structure prediction
