Performance analysis of hardware-based numerical data compression on various data formats

Tomohiro Ueno, Kentaro Sano, Takashi Furusawa

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

Abstract

The amount of data processed in high-performance computing has been growing rapidly. Accordingly, the cost of data movement in a large-scale computing system further increases, which has a huge effect on computing performance. To reduce the data movement cost, we have proposed hardware-based data compression for numerical data streams that can greatly reduce overhead has been proposed. Although our proposed hardware compressor works well for scientific computation in previous studies, the compression performance heavily depends on a type of target data. For practical use, we need to know the characteristics of the data compression and the relationship between data types and compression performance. In this paper, we clarify difference in compression performance among different data types by investigating hardware-based compression performance for data types of double, single, and half-precision floating-point and ffixed-point with results of numerical simulation. We also propose an area-saving hardware design for double-precision floating-point data.

Original languageEnglish
Title of host publicationProceedings - DCC 2018
Subtitle of host publication2018 Data Compression Conference
EditorsAli Bilgin, James A. Storer, Joan Serra-Sagrista, Michael W. Marcellin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages345-354
Number of pages10
ISBN (Electronic)9781538648834
DOIs
Publication statusPublished - 2018 Jul 19
Event2018 Data Compression Conference, DCC 2018 - Snowbird, United States
Duration: 2018 Mar 272018 Mar 30

Publication series

NameData Compression Conference Proceedings
Volume2018-March
ISSN (Print)1068-0314

Other

Other2018 Data Compression Conference, DCC 2018
CountryUnited States
CitySnowbird
Period18/3/2718/3/30

Keywords

  • FPGA
  • Floating Point
  • Hardware
  • Numerical Simulation

ASJC Scopus subject areas

  • Computer Networks and Communications

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    Ueno, T., Sano, K., & Furusawa, T. (2018). Performance analysis of hardware-based numerical data compression on various data formats. In A. Bilgin, J. A. Storer, J. Serra-Sagrista, & M. W. Marcellin (Eds.), Proceedings - DCC 2018: 2018 Data Compression Conference (pp. 345-354). (Data Compression Conference Proceedings; Vol. 2018-March). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DCC.2018.00043