SplitZNS: Towards an Efficient LSM-tree on Zoned Namespace SSDs

IF 1.5 3区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE ACM Transactions on Architecture and Code Optimization Pub Date : 2023-07-10 DOI:https://dl.acm.org/doi/10.1145/3608476
Dong Huang, Dan Feng, Qiankun Liu, Bo Ding, Wei Zhao, Xueliang Wei, Wei Tong
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Abstract

The Zoned Namespace (ZNS) Solid State Drive (SSD) is a nascent form of storage device that offers novel prospects for the Log Structured Merge Tree (LSM-tree). ZNS exposes erase blocks in SSD as append-only zones, enabling the LSM-tree to gain awareness of the physical layout of data. Nevertheless, LSM-tree on ZNS SSDs necessitates Garbage Collection (GC) owing to the mismatch between the gigantic zones and relatively small Sorted String Tables (SSTables). Through extensive experiments, we observe that a smaller zone size can reduce data migration in GC at the cost of a significant performance decline owing to inadequate parallelism exploitation. In this paper, we present SplitZNS, which introduces small zones by tweaking the zone-to-chip mapping to maximize GC efficiency for LSM-tree on ZNS SSDs. Following the multi-level peculiarity of LSM-tree and the inherent parallel architecture of ZNS SSDs, we propose a number of techniques to leverage and accelerate small zones to alleviate the performance impact due to underutilized parallelism. (1) First, we use small zones selectively to prevent exacerbating write slowdowns and stalls due to their suboptimal performance. (2) Second, to enhance parallelism utilization, we propose SubZone Ring, which employs a per-chip FIFO buffer to imitate a large zone writing style; (3) Read Prefetcher, which prefetches data concurrently through multiple chips during compactions; (4) and Read Scheduler, which assigns query requests the highest priority. We build a prototype integrated with SplitZNS to validate its efficiency and efficacy. Experimental results demonstrate that SplitZNS achieves up to 2.77x performance and reduces data migration considerably compared to the lifetime-based data placement.1

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SplitZNS:在分区命名空间ssd上实现高效的lsm树
分区命名空间(ZNS)固态硬盘(SSD)是一种新兴的存储设备形式,它为日志结构合并树(LSM-tree)提供了新的前景。ZNS将SSD中的擦除块暴露为仅追加区域,使lsm树能够了解数据的物理布局。然而,由于巨大的区域和相对较小的有序字符串表(sstable)之间的不匹配,ZNS ssd上的LSM-tree需要垃圾收集(GC)。通过大量的实验,我们观察到较小的区域大小可以减少GC中的数据迁移,但代价是由于并行性利用不足而导致性能显著下降。在本文中,我们提出了SplitZNS,它通过调整区域到芯片的映射来引入小区域,以最大限度地提高ZNS ssd上lsm树的GC效率。根据LSM-tree的多层次特性和ZNS ssd固有的并行架构,我们提出了一些技术来利用和加速小区域,以减轻由于未充分利用的并行性而导致的性能影响。(1)首先,我们有选择地使用小区域,以防止由于它们的次优性能而加剧写入减速和停滞。(2)其次,为了提高并行利用率,我们提出了子区环,它采用每个芯片FIFO缓冲区来模仿大区写入风格;(3) Read Prefetcher,在压缩时通过多个芯片并发预取数据;(4)和Read Scheduler,它为查询请求分配最高优先级。我们建立了一个与SplitZNS集成的原型,以验证其效率和功效。实验结果表明,与基于生命周期的数据放置相比,SplitZNS实现了高达2.77倍的性能,并大大减少了数据迁移
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来源期刊
ACM Transactions on Architecture and Code Optimization
ACM Transactions on Architecture and Code Optimization 工程技术-计算机:理论方法
CiteScore
3.60
自引率
6.20%
发文量
78
审稿时长
6-12 weeks
期刊介绍: ACM Transactions on Architecture and Code Optimization (TACO) focuses on hardware, software, and system research spanning the fields of computer architecture and code optimization. Articles that appear in TACO will either present new techniques and concepts or report on experiences and experiments with actual systems. Insights useful to architects, hardware or software developers, designers, builders, and users will be emphasized.
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