Collective I/O Performance on the Santos Dumont Supercomputer

A. Carneiro, J. L. Bez, F. Boito, Bruno Alves Fagundes, Carla Osthoff, P. Navaux
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引用次数: 5

Abstract

The historical gap between processing and data access speeds causes many applications to spend a large portion of their execution on I/O operations. From the point of view of a large-scale, expensive, supercomputer, it is important to ensure applications achieve the best I/O performance to promote an efficient usage of the machine. In this paper, we evaluate the I/O infrastructure of the Santos Dumont supercomputer, the largest one from Latin America. More specifically, we investigate the performance of collective I/O operations. By conducting an analysis of a scientific application that uses the machine, we identify large performance differences between the available MPI implementations. We then further study the observed phenomenon using the BT-IO and IOR benchmarks, in addition to a custom microbenchmark. We conclude that the customized MPI implementation by Bull (used by more than 20% of the jobs) presents the worst performance for small collective write operations. Our results are being used to help the Santos Dumont users to achieve the best performance for their applications. Additionally, by investigating the observed phenomenon, we provide information to help improve future MPI-IO collective write implementations.
Santos Dumont超级计算机的集体I/O性能
处理速度和数据访问速度之间的历史差距导致许多应用程序将大部分执行时间花在I/O操作上。从大型、昂贵的超级计算机的角度来看,确保应用程序实现最佳I/O性能以促进机器的有效使用是很重要的。在本文中,我们评估了Santos Dumont超级计算机的I/O基础设施,这是拉丁美洲最大的超级计算机。更具体地说,我们研究了集合I/O操作的性能。通过对使用该机器的科学应用程序进行分析,我们确定了可用的MPI实现之间的巨大性能差异。然后,我们使用BT-IO和IOR基准测试以及自定义微基准测试进一步研究观察到的现象。我们得出结论,Bull的定制MPI实现(超过20%的作业使用)在小型集体写操作中表现出最差的性能。我们的结果被用来帮助Santos Dumont用户实现其应用程序的最佳性能。此外,通过调查观察到的现象,我们提供了有助于改进未来MPI-IO集体写实现的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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