Visualization and Analysis of Parallel Dataflow Execution with Smart Traces

D. Osmari, H. Vo, Cláudio T. Silva, J. Comba, L. Lins
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引用次数: 9

Abstract

Most performance analysis tools focus on presenting an overload of details, with little application-dependent structure, and predefined statistical summaries. This makes the complex relations present in a parallel program not directly recognisable to the user, making the task of identifying performance issues more costly in both time and effort. In this work we investigate the requirements to create visualisations of execution traces of parallel programs modelled as dataflows. We propose the Smart Trace (ST) concept, to encode the structure of the data, and guide the construction of specialised visualizations. A visualization tool can then leverage the relationships in the data to automate a given analysis task. We show with examples the power and flexibility of visualisations we can create to address specific questions formulated about the analysis of the data, with emphasis in parallel dataflow traces.
智能跟踪并行数据流执行的可视化与分析
大多数性能分析工具都侧重于呈现过多的细节,很少使用与应用程序相关的结构和预定义的统计摘要。这使得用户无法直接识别并行程序中存在的复杂关系,从而使识别性能问题的任务在时间和精力上都更加昂贵。在这项工作中,我们研究了创建可视化的并行程序的执行轨迹建模为数据流的需求。我们提出了智能跟踪(ST)概念,用于对数据结构进行编码,并指导专业可视化的构建。可视化工具可以利用数据中的关系来自动执行给定的分析任务。我们通过示例展示了可视化的强大功能和灵活性,我们可以创建可视化来解决有关数据分析的特定问题,重点是并行数据流跟踪。
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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