应用于JUNO实验的容器技术研究  

Study of Container Technology Applied to JUNO

作　　者：谭宏楠 石京燕[1] 邹佳恒[1] 杜然[1] 姜晓巍[1] 孙震宇[1,2] TAN Hongnan;SHI Jingyan;ZOU Jiaheng;DU Ran;JIANG Xiaowei;SUN Zhenyu(Institute of High Energy Physics,Chinese Academy of Sciences,Beijing 100049,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院高能物理研究所,北京100049 [2]中国科学院大学,北京100049

出　　处：《计算机工程》2019年第4期1-5,共5页Computer Engineering

基　　金：国家自然科学基金(11775250)

摘　　要：江门中微子实验(JUNO)是以测定中微子质量顺序、精确测量中微子混合参数为主要目的的一项物理科学前沿研究实验,其实验规模庞大,数据处理流程繁杂,需借助统一高效的离线计算平台对数据进行分析处理。为此,利用Docker容器分层的镜像技术将JUNO实验所需的环境依赖库打包在镜像文件中,为其制定针对不同操作系统作业的容器镜像,并将不同JUNO容器作业提交至作业调度器上运行,以实现资源共享。对物理机、容器、虚拟机3种平台的CPU性能、I/O性能及JUNO作业的实际运行效果进行对比测试,结果表明,Docker容器能够胜任JUNO离线数据处理,相比虚拟机具有更小的性能损耗。The Jiangmen Underground Neutrino Observatory (JUNO) is a multipurpose neutrino experiment designed to determine neutrino mass hierarchy and precisely measure oscillation parameters, whose experimental data is large and complicated in processing./ is necessary to analyze and process thedata by means of aunified and efficient offline computing platform. So,this paper builds the customized Docker images with different operating systems for JUNO jobs by packing all software packages and dependency libraries which JUNO computing needs, and submits various types of JUNO jobs to scheduler to achieve resource sharing. A comparison test of CPU and I/O performances and JUNO job running effectiveness among bare metal,virtual machine and container test environments is done. Results show that the Docker container is capable of JUNO offline data processing and has a lower performance penalty than virtual machine.

关 键 词：虚拟机 Docker容器 镜像 江门中微子实验 虚拟化技术 

分 类 号：TP311.5[自动化与计算机技术—计算机软件与理论]