ScalaAFA: Constructing User-Space All-Flash Array Engine with Holistic Designs

被引:0
|
作者
Yi, Shushu [1 ,2 ]
Pan, Xiurui [1 ]
Li, Qiao [3 ]
Li, Qiang [4 ]
Wang, Chenxi [5 ]
Mao, Bo [3 ]
Jung, Myoungsoo [6 ,7 ]
Zhang, Jie [1 ,2 ]
机构
[1] Peking Univ, Sch Comp Sci, Natl Key Lab Multimedia Informat Proc, Beijing, Peoples R China
[2] Zhongguancun Lab, Beijing, Peoples R China
[3] Xiamen Univ, Xiamen, Peoples R China
[4] Alibaba, Hangzhou, Peoples R China
[5] Univ Chinese Acad Sci, Beijing, Peoples R China
[6] Korea Adv Inst Sci & Technol, Daejeon, South Korea
[7] Panmnesia, Daejeon, South Korea
来源
PROCEEDINGS OF THE 2024 USENIX ANNUAL TECHNICAL CONFERENCE, ATC 2024 | 2024年
基金
中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
All-flash array (AFA) is a popular approach to aggregate the capacity of multiple solid-state drives (SSDs) while guaranteeing fault tolerance. Unfortunately, existing AFA engines inflict substantial software overheads on the I/O path, such as the user-kernel context switches and AFA internal tasks (e.g., parity preparation), thereby failing to adopt next-generation high-performance SSDs. Tackling this challenge, we propose ScalaAFA, a unique holistic design of AFA engine that can extend the throughput of next-generation SSD arrays in scale with low CPU costs. We incorporate ScalaAFA into user space to avoid user-kernel context switches while harnessing SSD built-in resources for handling AFA internal tasks. Specifically, in adherence to the lock-free principle of existing user-space storage framework, ScalaAFA substitutes the traditional locks with an efficient message-passing-based permission management scheme to facilitate inter-thread synchronization. Considering the CPU burden imposed by background I/O and parity computation, ScalaAFA proposes to offload these tasks to SSDs. To mitigate host-SSD communication overheads in offloading, ScalaAFA takes a novel data placement policy that enables transparent data gathering and in-situ parity computation. ScalaAFA also addresses two AFA intrinsic issues, metadata persistence and write amplification, by thoroughly exploiting SSD architectural innovations. Comprehensive evaluation results indicate that ScalaAFA can achieve 2.5 x write throughput and reduce average write latency by a significant 52.7%, compared to the state-of-the-art AFA engines.
引用
收藏
页码:141 / 156
页数:16
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