Embracing approximate computing for energy-efficient motion estimation in high efficiency video coding

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Contributors

  • Walaa El-Harouni - (Author)
  • Semeen Rehman - , Chair of Processor Design (cfaed) (Author)
  • Bharath Srinivas Prabakaran - , TUD Dresden University of Technology (Author)
  • Akash Kumar - , Chair of Processor Design (cfaed) (Author)
  • Rehan Hafiz - , National University of Sciences and Technology Pakistan (Author)
  • Muhammad Shafique - , Vienna University of Technology (Author)

Abstract

Approximate Computing is an emerging paradigm for developing highly energy-efficient computing systems. It leverages the inherent resilience of applications to trade output quality with energy efficiency. In this paper, we present a novel approximate architecture for energy-efficient motion estimation (ME) in high efficiency video coding (HEVC). We synthesized our designs for both ASIC and FPGA design flows. ModelSim gate-level simulations are used for functional and timing verification. We comprehensively analyze the impact of heterogeneous approximation modes on the power/energy-quality tradeoffs for various video sequences. To facilitate reproducible results for comparisons and further research and development, the RTL and behavioral models of approximate SAD architectures and constituting approximate modules are made available at https://sourceforge.net/projects/lpaclib/.

Details

Original languageEnglish
Title of host publicationDesign, Automation & Test in Europe Conference & Exhibition (DATE), 2017
Place of PublicationLausanne
PublisherIEEE Xplore
Pages1384-1389
Number of pages6
ISBN (electronic)978-3-9815370-8-6, 978-3-9815370-9-3
ISBN (print)978-1-5090-5826-6
Publication statusPublished - 11 May 2017
Peer-reviewedYes

Publication series

SeriesDesign, Automation and Test in Europe Conference and Exhibition (DATE)
ISSN1530-1591

Conference

Title20th Design, Automation and Test in Europe, DATE 2017
Duration27 - 31 March 2017
CitySwisstech, Lausanne
CountrySwitzerland

Keywords

Research priority areas of TU Dresden

Sustainable Development Goals

Keywords

  • Approximate computing, Energy efficiency, Hardware accelerator, HEVC, Motion estimation, Video coding

Library keywords