Fast implementation of Wyner-Ziv video codec using GPGPU

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

In this paper, we report a fast implementation of Wyner-Ziv video decoder using general-purpose computing on graphics processing units (GPGPU). Despite of its many advantages, Wyner-Ziv video coding has a problem of huge decoding complexity. Since Slepian-Wolf decoding with rate adaptive LDPC accumulate code takes up more than 90% of entire Wyner-Ziv video decoding complexity, in this paper, we focus on fast implementation of the Slepian-Wolf decoder using the CUDA (Compute Unified Device Architecture) which is a GPGPU architecture developed by NVIDIA. Our implementation is shown to be 4-5 times (QCIF size) or 15-20 times (CIF size) faster compared to conventional Slepian-Wolf decoding.

Original languageEnglish
Title of host publicationIEEE International Symposium on Broadband Multimedia Systems and Broadcasting 2010, BMSB 2010 - Final Programme
DOIs
StatePublished - 2010
Event2010 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2010 - Shanghai, China
Duration: 24 Mar 201026 Mar 2010

Publication series

NameIEEE International Symposium on Broadband Multimedia Systems and Broadcasting 2010, BMSB 2010 - Final Programme

Conference

Conference2010 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2010
Country/TerritoryChina
CityShanghai
Period24/03/1026/03/10

Keywords

  • CUDA
  • GPGPU
  • Rate adaptive low density parity check code (LDPCA)
  • Wyner-Ziv video coding

Fingerprint

Dive into the research topics of 'Fast implementation of Wyner-Ziv video codec using GPGPU'. Together they form a unique fingerprint.

Cite this