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PinK: High-speed In-storage Key-value Store with Bounded Tails

PinK: High-speed In-storage Key-value Store with Bounded Tails
Im, JunsuBae, JinwookChung, ChanwooArvindLee, Sungjin
DGIST Authors
Lee, Sungjin
Issued Date
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.
USENIX Association
Related Researcher
  • 이성진 Lee, Sungjin 전기전자컴퓨터공학과
  • Research Interests Computer System; System Software; Storage System; Non-volatile Memory; Flash-based SSD; Distributed Storage Systems
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Department of Electrical Engineering and Computer Science Data-Intensive Computing Systems Laboratory 2. Conference Papers


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