提高企业闪存存储系统的随机写性能

T. Xie, Janak Koshia
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引用次数: 9

摘要

NAND闪存已成功应用于pda和笔记本电脑等移动设备。随着最近在容量、带宽和耐用性方面的进步,基于NAND闪存的固态硬盘(SSD)开始取代桌面系统中的硬盘驱动器(HDD)。然而,将SSD集成到企业存储系统中要困难得多。其中一个主要挑战是服务器应用程序通常需要异常的随机I/O性能,而当前SSD在随机写方面的性能很差。为了从根本上提高随机写性能,在本文中,我们提出了一种新的写缓存管理方案,称为EPO(元素级并行优化),它重新排序写请求,以便可以有效地利用SSD内的元素级并行性。我们使用经过验证的磁盘模拟器和真实的服务器类跟踪来评估EPO。实验结果表明,EPO明显优于传统的LRU算法和最先进的闪存写入缓冲管理方案BPLRU(最近最少使用的块填充)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Boosting random write performance for enterprise flash storage systems
NAND flash memory has been successfully employed in mobile devices like PDAs and laptops. With recent advances in capacity, bandwidth, and durability, NAND flash memory based Solid State Disk (SSD) is starting to replace hard disk drive (HDD) in desktop systems. Integrating SSD into enterprise storage systems, however, is much more challenging. One of the major challenges is that server applications normally demand an exceptional random I/O performance, whereas current SSD performs poorly in random writes. To fundamentally boost random write performance, in this paper we propose a new write cache management scheme called EPO (element-level parallel optimization), which reorders write requests so that element-level parallelism within SSD can be effectively exploited. We evaluate EPO using a validated disk simulator with realistic server-class traces. Experimental results show that EPO noticeably outperforms traditional LRU algorithm and a state-of-the-art flash write buffer management scheme BPLRU (block padding least recently used).
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