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Software Probes: Towards a Quick Method for Machine Characterization and Application Performance Prediction

机译:软件探针:寻求一种用于机器表征和应用性能预测的快速方法

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Computers perform different applications in different ways. To characterize an application performance into a machine, the usual method is a throughout execution of it. This work is a step into a synthetic probe able to characterize a master-worker application's performance in a fraction of the time required to run it entirely. This is specially important for CPU-intensive scientific applications, who runs for very long, as it makes sense that it runs as efficiently (and fast) as possible. To know how, and for how long a master-worker application is going to run can guide the decision to use this machine or not. Our software probe takes into account only the performance-relevant parts of the application, discovering a program's relevant phases. Running solely these significant phases is a powerful way to quickly characterize the application's performance on a machine. It can help to select the best computing nodes in a grid or in a multi-cluster to run this application, and even quickly predict the total execution time for this application/data set in the machine analyzed. We also present ongoing work on a fully synthetic probe generated from programs' phases.
机译:计算机以不同的方式执行不同的应用程序。为了将应用程序的性能描述为一台机器,通常的方法是在整个执行过程中使用该方法。这项工作是综合探针的一个步骤,该综合探针可以用完整运行主应用程序所需时间的一小部分来表征主应用程序的性能。这对于运行时间很长的CPU密集型科学应用程序特别重要,因为它可以尽可能高效(且快速)地运行。要知道主应用程序将如何运行以及运行多长时间,可以决定是否使用此计算机。我们的软件探针仅考虑应用程序中与性能相关的部分,从而发现程序的相关阶段。仅运行这些重要阶段是一种快速表征计算机上应用程序性能的有效方法。它可以帮助选择网格或多群集中的最佳计算节点来运行此应用程序,甚至可以快速预测所分析机器中该应用程序/数据集的总执行时间。我们还介绍了从程序阶段生成的全合成探针的正在进行的工作。

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