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

Research output: Contribution to journalArticlepeer-review

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 has 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 based on clustering of blocks. We use a parallel processing architecture to reduce the decompression overhead. According to the evaluation, we achieve 73% and 27% of storage size and memory access reductions respectively.

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalInternational Journal of Computer Information Systems and Industrial Management Applications
Volume8
Publication statusPublished - 2016 Jan 1

Keywords

  • Big-data
  • Data compression
  • FPGA
  • Succinct data structures
  • Text-search

ASJC Scopus subject areas

  • Management Information Systems
  • Signal Processing
  • Information Systems
  • Computer Vision and Pattern Recognition
  • Strategy and Management
  • Artificial Intelligence

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