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DC Field Value Language Im, Junsu - Bae, Jinwook - Chung, Chanwoo - Arvind - Lee, Sungjin - 2021-03-02T07:02:20Z - 2021-03-02T07:02:20Z - 2020-10-15 - 2020-07-15 -
dc.identifier.isbn 9781939133144 -
dc.identifier.uri -
dc.description.abstract Key-value store based on a log-structured merge-tree (LSM-tree) is preferable to hash-based KV store because an LSM-tree can support a wider variety of operations and show better performance, especially for writes. However, LSM-tree is difficult to implement in the resource constrained environment of a key-value SSD (KV-SSD) and consequently, KV-SSDs typically use hash-based schemes. We present PinK, a design and implementation of an LSM-tree-based KV-SSD, which compared to a hash-based KV-SSD, reduces 99th percentile tail latency by 73%, improves average read latency by 42% and shows 37% higher throughput. The key idea in improving the performance of an LSM-tree in a resource constrained environment is to avoid the use of Bloom filters and instead, use a small amount of DRAM to keep/pin the top levels of the LSM-tree. Copyright © Proc. of the 2020 USENIX Annual Technical Conference, ATC 2020. All rights reserved. -
dc.language English -
dc.publisher USENIX Association -
dc.title PinK: High-speed In-storage Key-value Store with Bounded Tails -
dc.type Conference Paper -
dc.identifier.scopusid 2-s2.0-85091947760 -
dc.identifier.bibliographicCitation USENIX Annual Technical Conference, pp.173 - 187 -
dc.identifier.url -
dc.citation.conferencePlace US -
dc.citation.conferencePlace 온라인 -
dc.citation.endPage 187 -
dc.citation.startPage 173 -
dc.citation.title USENIX Annual Technical Conference -
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Department of Electrical Engineering and Computer Science Data-Intensive Computing Systems Laboratory 2. Conference Papers


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