Synthesizing representative I/O workloads using iterative distillation

Zachary Kurmas, K. Keeton, K. Mackenzie
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引用次数: 33

Abstract

Storage systems designers are still searching for better methods of obtaining representative I/O workloads to drive studies of I/O systems. Traces of production workloads are very accurate, but inflexible and difficult to obtain. The use of synthetic workloads addresses these limitations; however, synthetic workloads are accurate only if they share certain key properties with the production workload on which they are based (e.g., mean request size, read percentage). Unfortunately, we do not know which properties are "key " for a given workload and storage system. We have developed a tool, the Distiller, that automatically identifies the key properties ("attribute-values") of the workload. The Distiller then uses these attribute-values to generate a synthetic workload representative of the production workload. This paper presents the design and evaluation of the Distiller. We demonstrate how the Distiller finds representative synthetic workloads for simple artificial workloads and three production workload traces.
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使用迭代蒸馏综合代表性的I/O工作负载
存储系统设计人员仍在寻找更好的方法来获得具有代表性的I/O工作负载,以推动对I/O系统的研究。生产工作负载的轨迹非常准确,但不灵活且难以获得。合成工作负载的使用解决了这些限制;然而,合成工作负载只有在与它们所基于的生产工作负载共享某些关键属性(例如,平均请求大小、读取百分比)时才是准确的。不幸的是,我们不知道哪些属性是给定工作负载和存储系统的“关键”。我们已经开发了一个工具蒸馏器,它可以自动识别工作负载的关键属性(“属性值”)。然后,蒸馏器使用这些属性值生成代表生产工作负载的合成工作负载。本文介绍了蒸馏器的设计与评价。我们将演示蒸馏器如何为简单的人工工作负载和三个生产工作负载跟踪找到具有代表性的合成工作负载。
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