跟踪长时间运行的应用程序:使用gromac的案例研究

M. Wagner, J. Doleschal, A. Knüpfer
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引用次数: 4

摘要

要开发利用当前高性能计算系统的巨大功能的应用程序,性能分析是不可避免的。虽然最近的许多工具研究都集中在大规模上,但对长时间运行的应用程序的性能分析却没有得到太多关注。本文研究了监视长时间运行的实际应用程序所带来的挑战,特别是测量环境中中间内存缓冲区刷新的破坏性偏差。我们提出了一个内存事件跟踪的概念,它完全避免了中间内存缓冲区刷新。我们评估这种内存中的事件跟踪工作流在多大程度上有助于克服关键属性,例如产生的跟踪大小、应用程序速度减慢和测量偏差。我们利用基于Score-P和OTF2的原型实现,以及分子动力学软件包Gromacs,这是一种目前无法在完整生产运行中监控的应用程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tracing long running applications: A case study using Gromacs
Performance analysis is inevitable to develop applications that utilize the enormous capabilities of current HPC systems. While many recent tool studies focused on large scales, performance analysis of long-running applications has not been paid much attention. This paper investigates challenges that arise from monitoring long-running real-life applications, in particular, the disruptive bias of intermediate memory buffer flushes in the measurement environment. We propose a concept for an in-memory event tracing that completely avoids intermediate memory buffer flushes. We evaluate to which extent such an in-memory event tracing workflow helps overcoming the critical properties, such as resulting trace size, application slow down, and measurement bias. We utilize a prototype implementation, based on Score-P and OTF2, with the molecular dynamics packages Gromacs, an application currently infeasible to monitor in a full production run.
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