Parallelizing Hilbert-Huang transform on a GPU

Pulung Waskito, Shinobu Miwa, Yasue Mitsukura, Hironori Nakajo

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

9 Citations (Scopus)

Abstract

In this paper, we show parallel implementation of Hilbert-Huang Transform on GPU. This implementation focused on the reducing the computation complexity from O(N) on a single CPU to O(N/P log (N)) on GPU, as well as the use of 'shared-global' switching method to increase performance. Evaluation results show our single GPU implementation using Tesla C1060 achieves 29.0x speedup in best case, and a total of 7.1x speedup for all results when compared to a single Intel dual core CPU.

Original languageEnglish
Title of host publicationProceedings - 2010 1st International Conference on Networking and Computing, ICNC 2010
Pages184-190
Number of pages7
DOIs
Publication statusPublished - 2010 Dec 1
Externally publishedYes
Event1st International Conference on Networking and Computing, ICNC 2010 - Higashi-Hiroshima, Japan
Duration: 2010 Nov 172010 Nov 19

Publication series

NameProceedings - 2010 1st International Conference on Networking and Computing, ICNC 2010

Other

Other1st International Conference on Networking and Computing, ICNC 2010
CountryJapan
CityHigashi-Hiroshima
Period10/11/1710/11/19

Keywords

  • CUDA
  • Empirical mode decomposition (EMD)
  • GPU
  • Hilbert-Huang transform (HHT)

ASJC Scopus subject areas

  • Computer Networks and Communications

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