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


  • Changwoo Min
  • Manya Ghobadi


Russell Sears


[PDF] Final version (536kB) Jun 4, 2020, 12:41:36 AM EDT · 8c9a8228cf264984086e8fabc6f45957738e661ffbc47c95666ef9530a533a1a8c9a8228

[PDF] Submission version

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 99$^{th}$ 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.

J. Im, J. Bae, C. Chung, Arvind, S. Lee

Submission type

Full/long paper

  • Architecture, Devices (including hardware issues related to FPGA, GPU, NVM)
  • Edge, IoT, Embedded, Mobile Systems
  • Key-Value stores, Transactional Data Management Systems (including databases)
  • Storage, File Systems (including deduplication and erasure coding)

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