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Characterizing I/O workloads of HPC applications through online analysis

机译:通过在线分析表征HPC应用程序的I / O工作负载

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The performance of storage subsystem of super-computers can not meet the demands of complex applications running on them. One of its major causes is that the bandwidth of storage hardware has not been utilized efficiently due to the complex and changing application I/O behavior. Therefore, I/O characterization tools are vital to application development and orchestration of storage system. This paper proposes an I/O characterization tool called FTracer. It captures I/O traces and performs traces analysis at runtime. In order to provide more flexible analysis, this FTracer allows users to vary the analysis instances at runtime. This mechanism ensures users get what exactly they want about the I/O characteristics of their applications when applications are running. In this work, we characterize MADbench2 benchmark to demonstrate the ability of FTracer.
机译:超级计算机的存储子系统的性能无法满足其上运行的复杂应用程序的需求。其主要原因之一是由于复杂且不断变化的应用程序I / O行为,未能有效利用存储硬件的带宽。因此,I / O表征工具对于应用程序开发和存储系统编排至关重要。本文提出了一种称为FTracer的I / O表征工具。它捕获I / O跟踪并在运行时执行跟踪分析。为了提供更灵活的分析,该FTracer允许用户在运行时更改分析实例。这种机制可确保用户在应用程序运行时获得他们对应用程序I / O特性的确切需求。在这项工作中,我们表征了MADbench2基准测试,以演示FTracer的功能。

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