Characterizing the Impact of Prefetching on Scientific Application Performance
Characterizing the Impact of Prefetching on Scientific Application Performance
复制标题
表征预取对科学应用程序性能的影响
DOI：
10.1007/978-3-319-10214-6_6
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
J. Vetter
中科院分区：
文献类型：
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作者：
Collin McCurdy;G. Marin;J. Vetter
为了更好地理解硬件和软件数据预取对科学应用性能的影响，本文介绍了两种分析技术，一种是以微架构为中心，另一种是以应用为中心。我们使用这些技术来分析代表性的全面生产应用程序从五个重要的Exascale目标领域。我们发现，尽管在预取的有效性，甚至在应用程序的差异很大，有一个很强的相关性区域之间的预取是最需要的，由于高水平的内存流量，它是最有效的。我们还观察到，以应用程序为中心的分析可以解释许多的差异，在预取的有效性观察到跨研究的应用程序。
In order to better understand the impact of hardware and software data prefetching on scientific application performance, this paper introduces two analysis techniques, one micro-architecture-centric and the other application-centric. We use these techniques to analyze representative full-scale production applications from five important Exascale target areas. We find that despite a great diversity in prefetching effectiveness across and even within applications, there is a strong correlation between regions where prefetching is most needed, due to high levels of memory traffic, and where it is most effective. We also observe that the application-centric analysis can explain many of the differences in prefetching effectiveness observed across the studied applications.