Mixed-Tool Performance Analysis on Hybrid Multicore Architectures

Peng Du, P. Luszczek, S. Tomov, J. Dongarra
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引用次数: 2

Abstract

This paper proposes a triangular solve algorithm with variable block size for graphics processing unit (GPU). By using diagonal blocks inversion with recursion, this algorithm works with tunable block size to achieve the best performance. Various methods are shown on how to make use of existing profiling tools to successfully measure and analyze performance of this algorithm. We use some of the most popular CPU and GPU profiling tools for their advantages and overcome their disadvantages with several new techniques to analyze the performance and relationship of different components of applications. With the presented methodologies, insight information is produced which helps to understand and tune the proposed algorithm and considerably improve the performance of the solver itself as well as the application using it.
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混合多核架构的混合工具性能分析
提出了一种面向图形处理器(GPU)的变块大小三角求解算法。该算法通过对角块递归倒换,实现块大小可调,以达到最佳性能。介绍了如何利用现有的分析工具成功地测量和分析该算法的性能的各种方法。我们使用一些最流行的CPU和GPU分析工具来分析它们的优点,并使用几种新技术来克服它们的缺点,以分析应用程序不同组件的性能和关系。使用所提出的方法,可以产生洞察力信息,这有助于理解和调整所提出的算法,并大大提高求解器本身以及使用它的应用程序的性能。
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