A tale of two systems: flexibility of usage of Kraken and Nautilus at the National Institute for Computational Sciences

A. Szczepanski, Jian Huang, Sean Ahern, M. Fahey
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引用次数: 1

Abstract

The National Institute for Computational Sciences (NICS) at the University of Tennessee currently operates two computational resources for the eXtreme Science and Engineering Discovery Environment (XSEDE), Kraken, a 112,896-core Cray XT5 for general purpose computation, and Nautilus, a 1,024-core SGI Altix UV 1000 for data analysis and visualization. We analyze a year's worth of accounting logs for Kraken and Nautilus to understand how users take advantage of these two systems and how analysis jobs differ from general HPC computation We find that researchers take advantage of the flexibility offered by these systems, running a wide variety of jobs at many scales and using the full range of core counts and available memory for their jobs. The jobs on Nautilus tend to use less walltime and more memory per core than the jobs run on Kraken. Additionally, researchers are more likely to run interactive jobs on Nautilus than on Kraken. Small jobs experience a good quality of service on both systems. This information can be used for the management and allocation of time on existing HPC and analysis systems as well as for planning for deploying future HPC and analysis systems.
一个关于两个系统的故事:国家计算科学研究所的Kraken和Nautilus的使用灵活性
田纳西大学的国家计算科学研究所(NICS)目前为极限科学与工程发现环境(XSEDE)提供两个计算资源,Kraken是用于通用计算的112,896核Cray XT5, Nautilus是用于数据分析和可视化的1024核SGI Altix UV 1000。我们分析了Kraken和Nautilus一年的会计日志,以了解用户如何利用这两个系统,以及分析工作与一般HPC计算的不同之处。我们发现,研究人员利用这些系统提供的灵活性,在许多规模上运行各种各样的工作,并为他们的工作使用全范围的核心计数和可用内存。与Kraken上运行的作业相比,Nautilus上的作业往往使用更少的运行时间和更多的每个核心内存。此外,研究人员更有可能在鹦鹉螺上进行互动作业,而不是在Kraken上。小的工作在两个系统上都体验到良好的服务质量。这些信息可以用于现有HPC和分析系统的管理和时间分配,也可以用于规划部署未来的HPC和分析系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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