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Analytic models for flash-based SSD performance when subject to trimming

机译:修整时基于闪存的SSD性能的解析模型

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Garbage collection is known to have a profound impact on SSD performance as it strongly influences the write amplification. Another key value that impacts the write amplification is the amount of over-provisioning, which lowers the write amplification at the cost of reducing the user-visible storage capacity. Write amplification occurs as the valid pages that remain on a block selected by garbage collection need to be copied to a free block before an erasure can take place. Some of these valid pages may however belong to a deleted file and therefore copying them is redundant. To avoid copying deleted data, the operating system can issue a Trim command to invalidate pages whenever a file is deleted. Prior analytical studies on the write amplification in SSDs assumed that no trimming takes place. In this paper we generalize a number of mean field models to assess the impact of trimming on the write amplification. Using these models we argue that the write amplification in a (large) system with trimming can be determined by analyzing a system without trimming that uses a larger over-provisioning factor (and modified hot fraction, in case of hot and cold data). Using numerical results we further show that trimming cold data results in a more significant reduction in the write amplification compared to trimming hot data.
机译:众所周知,垃圾回收会对SSD性能产生深远影响,因为它会严重影响写入放大。影响写放大的另一个关键值是过度配置的数量,它以降低用户可见存储容量为代价降低了写放大。写放大的发生是因为保留在垃圾回收所选择的块上的有效页面需要先复制到空闲块,然后才能进行擦除。但是,这些有效页面中的某些页面可能属于已删除的文件,因此复制它们是多余的。为了避免复制已删除的数据,每当删除文件时,操作系统都可以发出Trim命令来使页面无效。先前对SSD中写入放大的分析研究假设没有进行修整。在本文中,我们概括了许多平均场模型,以评估修整对写放大的影响。使用这些模型,我们认为可以通过分析一个没有修整的系统来确定(带有修整的(大型)系统中的写放大),该系统使用了较大的超额配置因子(在热数据和冷数据的情况下,也会修改热分数)。使用数值结果,我们进一步表明,与修整热数据相比,修整冷数据会导致写入放大幅度的显着降低。

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