使用IO500和Mistral分析平台存储

Nolan D. Monnier, J. Lofstead, Margaret Lawson, M. Curry
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引用次数: 4

摘要

本文探讨了我们如何使用IO500和Ellexus的Mistral工具来观察详细的性能特征,以便在Astra上调优IO性能。Astra是基于arm的Sandia机器,采用全闪存和基于lustret的存储阵列。通过本案例研究,我们证明IO500可以作为有意义的存储基准,甚至适用于所有闪存。我们还演示了使用细粒度分析工具,如Mistral,对于揭示调优需求细节是必不可少的。总的来说,本文展示了广谱基准测试(如IO500)和细粒度性能分析工具(如Mistral)的价值,可以了解详细的存储系统性能,以便更好地进行调优。
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Profiling Platform Storage Using IO500 and Mistral
This paper explores how we used IO500 and the Mistral tool from Ellexus to observe detailed performance characteristics to inform tuning IO performance on Astra, a ARM-based Sandia machine with an all flash, Lustre-based storage array. Through this case study, we demonstrate that IO500 serves as a meaningful storage benchmark, even for all flash storage. We also demonstrate that using fine-grained profiling tools, such as Mistral, is essential for revealing tuning requirement details. Overall, this paper demonstrates the value of a broad spectrum benchmark, like IO500, together with a fine grained performance analysis tool, such as Mistral, for understanding detailed storage system performance for better informed tuning.
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[Copyright notice] Applying Machine Learning to Understand Write Performance of Large-scale Parallel Filesystems Towards Physical Design Management in Storage Systems Profiling Platform Storage Using IO500 and Mistral Active Learning-based Automatic Tuning and Prediction of Parallel I/O Performance
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