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NUCLEAR FUSION AND PLASMA PHYSICS ›› 2020, Vol. 40 ›› Issue (1): 23-27.DOI: 10.16568/j.0254-6086.202001004

• Plasma Physics • Previous Articles     Next Articles

Research on GPU parallel acceleration of digital harmonic analysis algorithm for motional Stark effect diagnostic on EAST

ZHI Yu-qin1, 2, HUANG Yao1, FU Jia1, CHEN Ying1, WANG Feng1, YU Qing-jiang1, 2, LI Ying-ying1, WU Zhen-wei1, WAN Bao-nian1, Lü Bo1   

  1. (1. Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031; 2. University of Science and Technology of China, Hefei 230026)
  • Received:2018-09-10 Revised:2019-07-07 Online:2020-04-15 Published:2020-04-20

EAST运动斯塔克效应诊断数据处理中GPU并行化加速算法的研究

智玉琴1, 2,黄 耀1,符 佳*1, 陈 颖1,王 枫1,余青江1, 2,李颖颖1,吴振伟1,万宝年1,吕 波1   

  1. (1. 中国科学院等离子体物理研究所,合肥 230031;2. 中国科学技术大学,合肥 230026)
  • 作者简介:智玉琴(1991-),女,山西忻州人,硕士研究生,从事MSE诊断算法加速工作。
  • 基金资助:

    国家磁约束核聚变能发展研究专项(2015GB103003);国家自然科学基金(11605242,11805236);中国科学院等离子体物理研究所基金(DSJJ-17-01);中国科学院合肥大科学中心“高端用户培育基金”项目(2019HSC-UE011);中国科学院合肥大科学中心重点研发项目(2017HSC-KPRD002)

Abstract:

The parallel acceleration of digital harmonic analysis (DHA) algorithm is realized by using the CPU and GPU isomerization model in the data processing for motional Stark effect (MSE) diagnostic system on EAST. This model makes full use of the advantage of GPU parallel computing to complete the calculation process of Fourier transform and other calculation process that has high calculation efficiency and powerful parallelism. The CPU performs logical operations such as data access and process control. Compared with the serial DHA algorithm, the parallel one achieves more than 2000 times acceleration, which can meet the requirements of timely data processing during MSE diagnostic experiments.

Key words: EAST, Motional Stark effect, GPU computing, Parallel acceleration

摘要:

在EAST装置单道运动斯塔克效应(MSE)诊断系统数据处理中,采用CPU(中央处理器)+GPU(图形处理器)异构化模型,实现了数字谐波分析(DHA)算法的并行化加速计算。由CPU完成数据的加载及简单的数学计算,由GPU实现DHA算法的傅里叶正、逆变换及滤波等并行化计算,与串行算法相比,获得了2000倍以上的加速,可以满足MSE诊断实验期间及时数据处理的要求。

关键词: EAST装置, 运动斯塔克效应(MSE)诊断, 图形处理器(GPU)计算, 并行化加速

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