Scholars@Duke

Hardware partitioning for big data analytics

Publication ,  Journal Article
Wu, L; Barker, RJ; Kim, MA; Ross, KA
Published in: IEEE Micro
January 1, 2014
Published version (DOI)

Targeted deployment of hardware accelerators can improve the throughput and energy efficiency of large-scale data processing. Data partitioning is a critical operation for manipulating large datasets and is often the limiting factor in database performance. A hardware-software streaming framework offers a seamless execution environment for streaming accelerators such as the Hardware-Accelerated Range Partitioner (HARP). Together, the streaming framework and HARP provide an order of magnitude improvement in partitioning and energy performance. © 2014 IEEE.

Duke Scholars

Lisa Wills
Author Lisa Wills Computer Science

Published In

IEEE Micro

DOI

10.1109/MM.2014.11

ISSN

0272-1732

Publication Date

January 1, 2014

Volume

34

Issue

3

Start / End Page

109 / 119

Related Subject Headings

  • Computer Hardware & Architecture
  • 4606 Distributed computing and systems software
  • 4009 Electronics, sensors and digital hardware
  • 1006 Computer Hardware
  • 0906 Electrical and Electronic Engineering
 

Citation

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ICMJE
MLA
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Wu, L., Barker, R. J., Kim, M. A., & Ross, K. A. (2014). Hardware partitioning for big data analytics. IEEE Micro, 34(3), 109–119. https://doi.org/10.1109/MM.2014.11
Wu, L., R. J. Barker, M. A. Kim, and K. A. Ross. “Hardware partitioning for big data analytics.” IEEE Micro 34, no. 3 (January 1, 2014): 109–19. https://doi.org/10.1109/MM.2014.11.
Wu L, Barker RJ, Kim MA, Ross KA. Hardware partitioning for big data analytics. IEEE Micro. 2014 Jan 1;34(3):109–19.
Wu, L., et al. “Hardware partitioning for big data analytics.” IEEE Micro, vol. 34, no. 3, Jan. 2014, pp. 109–19. Scopus, doi:10.1109/MM.2014.11.
Wu L, Barker RJ, Kim MA, Ross KA. Hardware partitioning for big data analytics. IEEE Micro. 2014 Jan 1;34(3):109–119.

Published In

IEEE Micro

DOI

10.1109/MM.2014.11

ISSN

0272-1732

Publication Date

January 1, 2014

Volume

34

Issue

3

Start / End Page

109 / 119

Related Subject Headings

  • Computer Hardware & Architecture
  • 4606 Distributed computing and systems software
  • 4009 Electronics, sensors and digital hardware
  • 1006 Computer Hardware
  • 0906 Electrical and Electronic Engineering