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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:超计算机存储子系统的性能无法满足运行在其上的复杂应用程序的需求。其主要原因之一是由于复杂和更改的应用I / O行为,尚未有效地利用存储硬件的带宽。因此,I / O表征工具对存储系统的应用程序开发和编排是至关重要的。本文提出了一个名为FTRACER的I / O表征工具。它捕获I / O迹线并在运行时执行迹线分析。为了提供更灵活的分析,此ftracer允许用户在运行时改变分析实例。此机制可确保用户在运行应用程序时获得其应用程序的I / O特性所需的内容。在这项工作中,我们表征了Madbench2基准,以证明FTRACER的能力。

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