Many-core HEVC encoding based on wavefront parallel processing and GPU-accelerated motion estimation

Stefan Radicke, Jens-Uwe Hahn, Qi Wang, Christos Grecos

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

4 Citations (Scopus)

Abstract

The High Efficiency Video Coding (HEVC) standard provides an outstanding compression performance and is thus ideally suited for Ultra High Definition (UHD) content. However, the complexity of the encoder is substantial and therefore highly optimized implementations are required to achieve reasonable speeds. For this purpose, high-level parallelization mechanisms like Wavefront Parallel Processing (WPP), can be used to leverage modern multi-core hardware. In this work, the WPP mechanism is theoretically analyzed and a non-intrusive implementation of it based on the reference test model HM-13.0 is presented. Furthermore, a novel extension for heterogeneous computing platforms called Heterogeneous WPP (HWPP) is proposed which largely increases the achievable speedups. To demonstrate the power of HWPP, a Graphics Processing Unit (GPU) accelerated Motion Estimation (ME) algorithm is integrated. Based on a large amount of experimental data, it is shown that the speedups achieved with WPP and HWPP reach up to 8.9 and 17.9 times, respectively.

Original languageEnglish
Title of host publicationE-Business and Telecommunications
Subtitle of host publication11th International Joint Conference, ICETE 2014, Vienna, Austria, August 28-30, 2014, Revised Selected Papers
EditorsM. Obaidat , A. Holzinger , J. Filipe
PublisherSpringer
Pages393-417
Volume554
ISBN (Electronic)978-3-319-25915-4
ISBN (Print)978-3-319-25914-7
DOIs
Publication statusPublished - Dec 2015

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer
ISSN (Print)1865-0929

Keywords

  • High Efficiency Video Coding (HEVC)
  • Wavefront Parallel Processing (WPP)
  • Heterogeneous WPP (HWPP)
  • Graphics Processing Unit (GPU)
  • Motion Estimation (ME)
  • Massively parallel computing

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