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A visualization method of performance data for large scale parallel application based on clustering of function characteristics

机译:一种基于函数特性聚类的大规模并行应用的性能数据可视化方法

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Obtaining performance data of parallel program and analyzing these data are the two basic steps for analysis of parallel program behavior and optimizing program design. With the rapid development of high-performance computers, unceasing expansion of the scale of parallel program, it will produce large scale performance data for each measurement. The problems that how to deal with and demonstrate these data to developers and how to assist the developers to find problems are more difficulty. Towards the profile performance data, this paper provides a visualization method based on clustering of function characteristics, which combines the function grouping with clustering of k-value optimization to process large scale performance data, so as to provide performance analysis support for developers.
机译:获取并行程序的性能数据并分析这些数据是分析并行程序行为和优化程序设计的两个基本步骤。随着高性能计算机的快速发展,不断扩展的并行计划的规模,它将为每次测量产生大规模的性能数据。如何处理和展示这些数据的问题以及开发人员以及如何协助开发人员找到问题更具困难。朝着配置文件性能数据,本文提供了一种基于函数特性的群集的可视化方法,它将功能分组与K值优化的聚类组合以处理大规模性能数据,以便为开发人员提供性能分析支持。

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