中文摘要：

高能物理计算是典型的高性能计算的应用,运行时需要大量的CPU资源。如果系统的CPU资源利用率不高,会使得计算效率大大下降。传统的高能物理计算环境资源管理是静态的,很难同时满足突发、批处理、CPU密集型、数据密集型等不同类型的作业对于不同的物理资源的需求。文中基于Openstack构建的虚拟计算集群系统,实现以CPU核为粒度进行调度作业,根据当前的作业和虚拟资源情况,动态调度资源,大大提高了资源的利用率。首先介绍本系统的相关研究工作,包括KVM虚拟机的测试优化、高能物理作业在虚拟机上的性能测试及高能物理公共服务云IHEPCloud,这些工作进一步表明了高能物理实验的数据分析在虚拟机上的性能是完全可以被接受的;然后详细介绍了虚拟计算集群系统的设计与实现;最后给出虚拟机计算集群在高能物理计算中的实际应用情况,证明了虚拟计算集群系统能很好地满足高能物理的计算需求。

英文摘要：

High energy physics computing is a high-performance computing application,which requires a lot of computing resource.If the utilization of CPU resource is not high,it will cause the worse computing efficiency.In traditional computing environment,the static resource management leads to the difficulty to satisfy the resource requirements of different kinds of jobs such as sudden jobs,batch jobs,CPU-intensive jobs,IO-intensive jobs and so on.The paper discussed the virtualized computing system based on Openstack,which implements scheduling jobs with CPU cores,danamically schedule the resources,greatly improves the utilization of resources according to the current job and resource status.Firstly,we introduced the relative research activities including KVM performance testing and optimization,performance analysis of HEP（High Energy Physics）jobs running between KVM and physical machines and the public cloud service IHEPCloud.All of them illustrate it＇s totally acceptable to make HEP jobs run in virtualized platform.Then,we demonstrated the design and implementation of virtualized computing system.Finally,the current status of the virtualized computing cluster is shown,which verifies that the performance of virtualized computing system can meet the needs of high energy physics computing.