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Black-Box Performance Modeling for Solid-State Drives

机译:用于固态驱动器的黑匣子性能建模

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摘要

Flash-based Solid-State Drives (SSDs) have become a promising alternative to magnetic Hard Disk Drives (HDDs) thanks to the large improvements in performance, power consumption, and shock resistance. An accurate SSD performance model will provide the important research tools for exploring the design space of flash-based storage systems. While many HDD performance models have been developed, architectural differences prevent these models from being effective for SSDs, mostly because their designs cannot accurately account for many unique SSD characteristics (e.g., low latencies, slow updates, and expensive erases). In this paper, we utilize the black-box modeling technique to analyze and evaluate SSD performance, including latency, bandwidth, and throughput. Such an approach is appealing because it requires minimal a priori information about SSDs. We construct and evaluate our models on three commercial SSDs. Although this approach may lead to less accurate predictions for HDDs, we find that a black-box model with a comprehensive set of workload characteristics can achieve the mean relative errors of 20%, 13%, and 6% for latency, bandwidth, and throughput predictions, respectively.
机译:由于性能,功耗和抗冲击性的大量改善,基于闪存的固态驱动器(SSD)已成为磁性硬盘驱动器(HDDS)的有希望的替代方案。精确的SSD性能模型将提供重要的研究工具,用于探索基于闪存的存储系统的设计空间。虽然已经开发了许多硬盘性能模型,但架构差异阻止了这些模型对SSD有效,主要是因为他们的设计无法准确地占SSD特征(例如,低延迟,慢更新和昂贵的擦除)。在本文中,我们利用了黑匣子建模技术来分析和评估SSD性能,包括延迟,带宽和吞吐量。这样的方法是吸引人的,因为它需要最初的关于SSD的先验信息。我们在三个商业SSD上构建和评估我们的模型。虽然这种方法可能导致HDD的准确预测不太准确,但我们发现一个带有综合工作量特性的黑匣子型号可以实现20%,13%和6%的平均相对误差,延迟,带宽和吞吐量分别预测。

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