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Automatic analysis of inefficiency patterns in parallel applications

机译:自动分析并行应用中的低效率模式

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Event tracing is a powerful method for analyzing the performance behavior of parallel applications. Because event traces record the temporal and spatial relationships between individual runtime events, they allow application developers to analyze dependences of performance phenomena across concurrent control flows. However, in view of the large amounts of data generated on contemporary parallel machines, the depth and coverage of a purely manual analysis is often limited. Our approach automatically searches event traces for patterns of inefficient behavior, classifies detected instances by category, and quantifies the associated performance penalty. This enables developers to study the performance of their applications at a high level of abstraction, while requiring significantly less time and expertise than a manual analysis.
机译:事件跟踪是一种用于分析并行应用程序性能行为的强大方法。因为事件跟踪记录了各个运行时事件之间的时间和空间关系,所以它们使应用程序开发人员可以分析并发控制流之间的性能现象相关性。但是,鉴于在当代并行机上生成的大量数据,纯手工分析的深度和覆盖范围通常受到限制。我们的方法会自动在事件跟踪中搜索低效行为的模式,按类别对检测到的实例进行分类,并量化相关的性能损失。这使开发人员能够以较高的抽象水平研究其应用程序的性能,同时所需的时间和专业知识要比手工分析少得多。

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