目的:研究I/O策略的计算机实验室

Jakob Lüttgau, J. Kunkel
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引用次数: 0

摘要

评估跨不同系统的应用程序的I/O性能是一项艰巨的任务,因为它需要准备软件依赖项和所需的输入数据。Feign的目标是为支持任意软件和库层的并行应用程序提供可扩展的跟踪重放解决方案。该工具抽象并简化了重放过程,同时允许插件提供、操作和解释跟踪数据。因此,应用程序的行为可以在没有潜在的专有或机密软件和输入数据的情况下进行评估。更有趣的是,Feign作为I/O研究的虚拟实验室的潜力:通过操纵跟踪数据,可以进行实验;例如,可以评估优化策略的好处。由于插件可以确定“未来”的活动,这使我们能够开发最佳策略作为任何运行时启发式的基线,但也简化了在许多应用程序上测试已开发策略而无需修改它们。本文提出并评估了一个工作流,以自动将优化候选应用于应用程序跟踪并估计潜在的性能增益。通过使用Feign的报告功能,自动优化引擎可以独立地进行实验,通过输入痕迹和策略来比较结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Feign: In-Silico Laboratory for Researching I/O Strategies
Evaluating I/O performance of an application across different systems is a daunting task because it requires preparation of the software dependencies and required input data. Feign aims to be an extensible trace replay solution for parallel applications that supports arbitrary software and library layers. The tool abstracts and streamlines the replay process while allowing plug-ins to provide, manipulate and interpret trace data. Therewith, the application's behavior can be evaluated without potentially proprietary or confidential software and input data.Even more interesting is the potential of Feign as a virtual laboratory for I/O research: by manipulating trace data, experiments can be conducted; for example, it becomes possible to evaluate the benefit of optimization strategies. Since a plug-in could determine "future" activities, this enables us to develop optimal strategies as baselines for any run-time heuristics, but also eases testing of a developed strategy on many applications without modifying them.The paper proposes and evaluates a workflow to automatically apply optimization candidates to application traces and approximate potential performance gains. By using Feign's reporting facilities, an automatic optimization engine can then independently conduct experiments by feeding traces and strategies to compare the results.
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