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

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dc.contributor.authorYi, Shushuko
dc.contributor.authorPan, Xiuruiko
dc.contributor.authorLi, Qiaoko
dc.contributor.authorLi, Qiangko
dc.contributor.authorWang, Chenxiko
dc.contributor.authorMao, Boko
dc.contributor.authorJung, Myoungsooko
dc.contributor.authorZhang, Jieko
dc.date.accessioned2024-09-11T19:00:10Z-
dc.date.available2024-09-11T19:00:10Z-
dc.date.created2024-06-16-
dc.date.issued2024-07-10-
dc.identifier.citation2024 USENIX Annual Technical Conference, ATC 2024-
dc.identifier.urihttp://hdl.handle.net/10203/322919-
dc.description.abstractAll-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.-
dc.languageEnglish-
dc.publisherUSENIX-
dc.titleScalaAFA: Constructing User-Space All-Flash Array Engine with Holistic Designs-
dc.typeConference-
dc.type.rimsCONF-
dc.citation.publicationname2024 USENIX Annual Technical Conference, ATC 2024-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationSanta Clara, CA-
dc.contributor.localauthorJung, Myoungsoo-
dc.contributor.nonIdAuthorYi, Shushu-
dc.contributor.nonIdAuthorPan, Xiurui-
dc.contributor.nonIdAuthorLi, Qiao-
dc.contributor.nonIdAuthorLi, Qiang-
dc.contributor.nonIdAuthorWang, Chenxi-
dc.contributor.nonIdAuthorMao, Bo-
dc.contributor.nonIdAuthorZhang, Jie-
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EE-Conference Papers(학술회의논문)
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