Adaptive power management of on-chip video memory for multiview video coding

  • Authors:
  • Muhammad Shafique;Bruno Zatt;Fabio Leandro Walter;Sergio Bampi;Jörg Henkel

  • Affiliations:
  • Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany;Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany, and Federal University of Rio Grande do Sul (UFRGS);Federal University of Rio Grande do Sul (UFRGS);Federal University of Rio Grande do Sul (UFRGS);Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

  • Venue:
  • Proceedings of the 49th Annual Design Automation Conference
  • Year:
  • 2012

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Abstract

An adaptive power management of on-chip video memory for Multiview Video Coding is presented. It leverages texture, motion and disparity properties of objects and their correlations in the 3D-neighborhood. It groups different Macroblocks of a frame and predicts the highly-probable motion/disparity search direction in order to power-gate idle memory regions. Exploited are the statistical properties of Macroblock groups to predict idle sectors. Our approach achieves on average 32% and 61% energy reduction (averaged over various video sequences) compared to state-of-the-art DSW [7] and Level C [12], respectively. The Motion/Disparity Estimation architecture with video memory and power management scheme is implemented using an ASIC flow (IBM-65nm Low-Power technology) and it processes 4-view HD1080p@33fps.