USENIX ATC '24 - ScalaAFA: Constructing User-Space All-Flash Array Engine with Holistic Designs

ScalaAFA: Constructing User-Space All-Flash Array Engine with Holistic Designs
Shushu Yi, Peking University and Zhongguancun Laboratory; Xiurui Pan, Peking University; Qiao Li, Xiamen University; Qiang Li, Alibaba; Chenxi Wang, University of Chinese Academy of Sciences; Bo Mao, Xiamen University; Myoungsoo Jung, KAIST and Panmnesia; Jie Zhang, Peking University and Zhongguancun Laboratory
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× write throughput and reduce average write latency by a significant 52.7%, compared to the state-of-the-art AFA engines.
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