Abstract

We engineer a GPU implementation of a dynamic B-Tree that supports concurrent queries (point, range, and successor) and updates (insertions and deletions). Our B-tree outperforms the state of the art, a GPU log-structured merge tree (LSM) and a GPU sorted array. In particular, point and range queries are significantly faster than in a GPU LSM (the GPU LSM does not implement successor queries). Furthermore, B-Tree insertions are also faster than LSM and sorted array insertions unless insertions come in batches of more than roughly 100k insertions. Because we cache the upper levels of the tree, we achieve lookup throughput that exceeds the DRAM bandwidth of the GPU. We demonstrate that the key limiter of performance on a GPU is contention and describe the design choices that allow us to achieve this high performance.

Date

February, 2019

Authors

  • Muhammad A. Awad
  • Saman Ashkiani
  • Rob Johnson
  • Martin Farach-Colton
  • John D. Owens

Related projects

Tags

  • B-tree
  • GPU
  • concurrency

Type

Inproceedings

Booktitle

PPoPP