Three-dimensional spatial join count exploiting CPU optimized STR R-tree

Ryuya Mitsuhashi, Hideyuki Kawashima, Takahiro Nishimichi, Osamu Tatebe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this study, we attempt to address the issue regarding the spatial join count, where in the number of particles around a halo is counted only once for a given simulation result. An efficient spatial index is necessary for accelerated counting; therefore, we propose a CPU optimized sort-tile-recursive R-tree that employs a parallel radix sort and node packing with thread pool and single instruction multiple data instructions. In an experiment conducted with astronomical data, the proposed method demonstrates an improvement in performance by 26.8 times compared with that using a conventional CPU optimized R-tree. We also propose a partial materialization approach to handle large amount of data that exceeds the capacity of main memory. To accelerate the approach, we propose a construct-search-destruct pipeline that exploits a thread pool to conceal the latency of the construction and destruction of the index. The pipelining method achieves an improvement in performance by 27.5 times compared with that of a conventional CPU optimized R-tree. All our codes are available on GitHub.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Big Data, Big Data 2016
EditorsRonay Ak, George Karypis, Yinglong Xia, Xiaohua Tony Hu, Philip S. Yu, James Joshi, Lyle Ungar, Ling Liu, Aki-Hiro Sato, Toyotaro Suzumura, Sudarsan Rachuri, Rama Govindaraju, Weijia Xu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2938-2947
Number of pages10
ISBN (Electronic)9781467390040
DOIs
Publication statusPublished - 2016
Event4th IEEE International Conference on Big Data, Big Data 2016 - Washington, United States
Duration: 2016 Dec 52016 Dec 8

Publication series

NameProceedings - 2016 IEEE International Conference on Big Data, Big Data 2016

Other

Other4th IEEE International Conference on Big Data, Big Data 2016
CountryUnited States
CityWashington
Period16/12/516/12/8

Keywords

  • Periodic boundary condition
  • SIMD
  • STR R-tree
  • Spatial join count

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Hardware and Architecture

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  • Cite this

    Mitsuhashi, R., Kawashima, H., Nishimichi, T., & Tatebe, O. (2016). Three-dimensional spatial join count exploiting CPU optimized STR R-tree. In R. Ak, G. Karypis, Y. Xia, X. T. Hu, P. S. Yu, J. Joshi, L. Ungar, L. Liu, A-H. Sato, T. Suzumura, S. Rachuri, R. Govindaraju, & W. Xu (Eds.), Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016 (pp. 2938-2947). [7840944] (Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2016.7840944