Real Time Visualization of Monitoring Data for Large Scale HPC Systems

M. Showerman
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引用次数: 3

Abstract

High Performance Computing (HPC) system users and administrators are often hampered in their ability understand application performance and system behavior due to a lack of sufficient information about how resources, such as memory, CPU, networks and filesystems are being used. While obtaining the related data is a necessary step, it is insufficient without tools that can turn the data into actionable information. Required capabilities of such tools are the ability to efficiently handle vast amounts of data in a timely fashion, the presentation of effective and understandable information representations for large node counts, and the correlation of that data with job and system events. This paper presents visualization approaches and tools that NCSA is developing, combined with the use of freely available web interfaces, to turn the eight billion platform related data points per day being collected from their 27,648 compute node Blue Waters platform into actionable information for both system administrators and users. Insights from the visualizations both at the system and the job levels are also presented.
大型高性能计算系统监控数据的实时可视化
高性能计算(High Performance Computing, HPC)系统用户和管理员理解应用程序性能和系统行为的能力常常受到阻碍,因为他们缺乏关于如何使用资源(如内存、CPU、网络和文件系统)的足够信息。虽然获取相关数据是必要的步骤,但没有工具将数据转化为可操作的信息是不够的。这些工具所需的功能是能够及时有效地处理大量数据,为大型节点计数提供有效且可理解的信息表示,以及将这些数据与作业和系统事件关联起来。本文介绍了NCSA正在开发的可视化方法和工具,结合使用免费提供的web界面,将每天从其27,648个计算节点Blue Waters平台收集的80亿个平台相关数据点转化为系统管理员和用户可操作的信息。从系统和工作层面的可视化的见解也被提出。
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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