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Using Magpie for Request Extraction and Workload Modelling

机译:使用喜p进行请求提取和工作量建模

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摘要

Tools to understand complex system behaviour are essential for many performance analysis and debugging tasks, yet there are many open research problems in their development. Magpie is a toolchain for automatically extracting a system's workload under realistic operating conditions. Using low-overhead instrumentation, we monitor the system to record fine-grained events generated by kernel, middleware and application components. The Magpie request extraction tool uses an application-specific event schema to correlate these events, and hence precisely capture the control flow and resource consumption of each and every request. By removing scheduling artefacts, whilst preserving causal dependencies, we obtain canonical request descriptions from which we can construct concise workload models suitable for performance prediction and change detection. In this paper we describe and evaluate the capability of Magpie to accurately extract requests and construct representative models of system behaviour.
机译:理解复杂系统行为的工具对于许多性能分析和调试任务是必不可少的,但是在其开发中仍然存在许多开放的研究问题。 Magpie是一个工具链,用于在实际操作条件下自动提取系统的工作负载。使用低开销的工具,我们监视系统以记录由内核,中间件和应用程序组件生成的细粒度事件。喜p请求提取工具使用特定于应用程序的事件模式来关联这些事件,从而精确捕获每个请求的控制流和资源消耗。通过除去调度伪像,同时保留因果关系,我们获得了规范的请求描述,从中可以构造适合于性能预测和变更检测的简明工作负载模型。在本文中,我们描述并评估了喜p能够准确地提取请求并构建系统行为的代表性模型的能力。

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