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A multi-level approach for understanding I/O activity in HPC applications

机译:了解HPC应用程序中I / O活动的多级方法

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I/O has become one of the determining factors of HPC application performance. Understanding an application's I/O activity requires a multi-level view of the I/O function flow that includes high-level I/O libraries. We have developed a tracing framework, called Recorder, that captures I/O function calls at multiple layers of the parallel I/O stack without requiring source code modifications. In this paper, we show how Recorder's trace output can be used to investigate I/O activity and identify performance inefficiencies in two I/O benchmarks running on a leading edge HPC platform. Future work to organize and present the collected information more intuitively will further increase the value of Recorder's capabilities. We believe that a multi-level I/O tracing framework can provide key insights to end users and I/O library developers working to improve I/O on HPC platforms.
机译:I / O已成为HPC应用程序性能的决定因素之一。了解应用程序的I / O活动需要I / O功能流的多层次视图,其中包括高级I / O库。我们已经开发了一个称为Recorder的跟踪框架,该框架可以捕获并行I / O堆栈的多个层上的I / O函数调用,而无需修改源代码。在本文中,我们展示了Recorder的跟踪输出如何用于调查I / O活动并确定在领先的HPC平台上运行的两个I / O基准测试中的性能低下。未来以更直观的方式组织和呈现所收集信息的工作将进一步提高Recorder功能的价值。我们相信,多层I / O跟踪框架可以为致力于改善HPC平台上的I / O的最终用户和I / O库开发人员提供重要见解。

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