Hardware-oriented succinct-data-structure based on block-size-constrained compression

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

1 Citation (Scopus)

Abstract

Succinct data structures are introduced to efficiently solve a given problem while representing the data using as little space as possible. However, the full potential of the succinct data structures have not been utilized in software-based implementations due to the large storage size and the memory access bottleneck. This paper proposes a hardware-oriented data compression method to reduce the storage space without increasing the processing time. We use a parallel processing architecture to reduce the decompression overhead. According to the evaluation, we can compress the data by 37.5% and still have fast data access with small decompression overhead.

Original languageEnglish
Title of host publicationProceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015
EditorsMario Koppen, Azah Kamilah Muda, Kun Ma, Bing Xue, Hideyuki Takagi, Ajith Abraham
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages136-140
Number of pages5
ISBN (Electronic)9781467393607
DOIs
Publication statusPublished - 2016 Jun 15
Event7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015 - Fukuoka, Japan
Duration: 2015 Nov 132015 Nov 15

Publication series

NameProceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015

Other

Other7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015
CountryJapan
CityFukuoka
Period15/11/1315/11/15

Keywords

  • FPGA
  • Succinct data structures
  • big-data
  • data compression
  • text-search

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Control and Optimization
  • Modelling and Simulation

Fingerprint Dive into the research topics of 'Hardware-oriented succinct-data-structure based on block-size-constrained compression'. Together they form a unique fingerprint.

Cite this