Flashy prefetching for high-performance flash drives

Ahsen J. Uppal, R. C. Chiang, H. H. Huang
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引用次数: 17

Abstract

While hard drives hold on to the capacity advantage, flash-based solid-state drives (SSD) with high bandwidth and low latency have become good alternatives for I/O-intensive applications. Traditional data prefetching has been primarily designed to improve I/O performance on hard drives. The same techniques, if applied unchanged on flash drives, are likely to either fail to fully utilize SSDs, or interfere with application I/O requests, both of which could result in undesirable application performance. In this work, we demonstrate that data prefetching, when effectively harnessing the high performance of SSDs, can provide significant performance benefits for a wide range of data-intensive applications. The new technique, flashy prefetching, consists of accurate prediction of application needs in runtime and adaptive feedback-directed prefetching that scales with application needs, while being considerate to underlying storage devices. We have implemented a real system in Linux and evaluated it on four different SSDs. The results show 65-70% prefetching accuracy and an average 20% speedup on LFS, web search engine traces, BLAST, and TPC-H like benchmarks across various storage drives.
用于高性能闪存驱动器的华丽预取
虽然硬盘驱动器保持着容量优势,但具有高带宽和低延迟的基于闪存的固态驱动器(SSD)已成为I/ o密集型应用程序的良好替代方案。传统的数据预取主要是为了提高硬盘驱动器的I/O性能。同样的技术,如果在闪存驱动器上不加改变地应用,很可能无法充分利用ssd,或者干扰应用程序I/O请求,这两种情况都可能导致不理想的应用程序性能。在这项工作中,我们证明了当有效地利用ssd的高性能时,数据预取可以为广泛的数据密集型应用程序提供显着的性能优势。新技术,浮华预取,包括在运行时对应用程序需求的准确预测和根据应用程序需求进行调整的自适应反馈定向预取,同时考虑到底层存储设备。我们在Linux上实现了一个真实的系统,并在四个不同的ssd上对其进行了评估。结果显示,在各种存储驱动器上,在LFS、web搜索引擎跟踪、BLAST和TPC-H类基准测试中,预取准确率为65-70%,平均加速为20%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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