Achieve better performance with PEAK on XSEDE resources
Achieve better performance with PEAK on XSEDE resources
复制标题
利用 PEAK 在 XSEDE 资源上实现更好的性能
DOI：
10.1145/2335755.2335801
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发表时间：
2012
影响因子：
3.8
通讯作者：
S. Moore
中科院分区：
文献类型：
--
作者：
B. Hadri;Haihang You;S. Moore
作为美国开放式科学研究的领先分布式网络基础设施，XSEDE支持全国各地的几台超级计算机，以及对这些研究人员的成功至关重要的计算工具。在大多数情况下，用户正在寻找一种系统的方式来选择和配置其应用程序的可用系统软件和库，以便获得最佳的应用程序性能。然而，很少有科学应用程序开发人员有时间对所有可能的配置进行详尽的搜索以确定最佳配置，并且凭经验执行这样的搜索可能会消耗他们分配时间的很大一部分。我们在这里提出了一个框架，称为性能环境自动配置框架（PEAK），以帮助开发人员和用户的科学应用程序选择最佳的配置，为他们的应用程序在给定的平台上，并更新配置时，底层硬件和系统软件发生变化。要做出的选择包括编译器及其编译选项的设置、数值库和库参数的设置以及其他环境变量的设置，以利用NUMA系统。该框架帮助我们选择了最佳配置，以便在Kraken和Nautilus等XSEDE平台上执行的一些科学应用程序获得显着的加速。
As the leading distributed cyberinfrastructure for open scientific research in the United States, XSEDE supports several supercomputers across the country, as well as computational tools that are critical to the success of those researchers. In most cases, users are looking for a systematic way of selecting and configuring the available systems software and libraries for their applications so as to obtain optimal application performance. However, few scientific application developers have the time for an exhaustive search of all the possible configurations to determine the best one, and performing such a search empirically can consume a significant proportion of their allocation hours. We present here a framework, called the Performance Environment Autoconfiguration frameworK (PEAK), to help developers and users of scientific applications to select the optimal configuration for their application on a given platform and to update that configuration when changes in the underlying hardware and systems software occur. The choices to be made include the compiler with its settings of compiling options, the numerical libraries and settings of library parameters, and settings of other environment variables to take advantage of the NUMA systems. The framework has helped us choose the optimal configuration to get a significant speedup for some scientific applications executed on XSEDE platforms such as Kraken and Nautilus.