Diagnosing performance bottlenecks in emerging petascale applications
Diagnosing performance bottlenecks in emerging petascale applications
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DOI：
10.1145/1654059.1654111
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发表时间：
2009-11
期刊：
影响因子：
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通讯作者：
Nathan R. Tallent;J. Mellor-Crummey;L. Adhianto;M. Fagan;Mark W. Krentel
中科院分区：
文献类型：
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作者：
Nathan R. Tallent;J. Mellor-Crummey;L. Adhianto;M. Fagan;Mark W. Krentel
尖端的科学和工程应用需要千万亿次计算。然而，有效地使用千万亿次计算平台是一个重大挑战。因此，迫切需要性能工具，使科学家能够了解新兴的千万亿次系统的性能障碍。在本文中，我们描述了HPCToolkit-一套多平台的工具，支持基于采样的分析应用程序的性能在新兴的千万亿次平台。HPCToolkit使用采样来查明和量化扩展和节点性能瓶颈。我们研究了几个新兴的petascale应用程序的Cray XT和IBM BlueGene/P平台，并使用HPCToolkit来确定特定的源代码行-在其完整的调用上下文-与这些代码中的性能瓶颈。这些信息正是应用程序开发人员需要了解的，以便改进他们的应用程序，充分利用千万亿次系统的强大功能。
Cutting-edge science and engineering applications require petascale computing. It is, however, a significant challenge to use petascale computing platforms effectively. Consequently, there is a critical need for performance tools that enable scientists to understand impediments to performance on emerging petascale systems. In this paper, we describe HPCToolkit-a suite of multi-platform tools that supports sampling-based analysis of application performance on emerging petascale platforms. HPCToolkit uses sampling to pinpoint and quantify both scaling and node performance bottlenecks. We study several emerging petascale applications on the Cray XT and IBM BlueGene/P platforms and use HPCToolkit to identify specific source lines - in their full calling context - associated with performance bottlenecks in these codes. Such information is exactly what application developers need to know to improve their applications to take full advantage of the power of petascale systems.