Low power motion estimation based on probabilistic computing

Charvi Dhoot, Lap Pui Chau, Shubhajit Roy Chowdhury, Vincent J. Mooney

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)


As CMOS technology driven by Moore's law has approached device sizes in the range of 5-20 nm, noise immunity of such future technology nodes is predicted to decrease considerably, eventually affecting the reliability of computations through them. A shift in the design paradigm is expected from 100% accurate computations to probabilistic computing with accuracy dependent on the target application or circuit specifications. One model developed for CMOS technology that emulates the erroneous behavior predicted is termed probabilistic CMOS (PCMOS). In this paper, we propose a PCMOS-based architecture implementation for traditional motion estimation algorithms and show that up to 57% energy savings are possible for different existing motion estimation algorithms. Furthermore, algorithmic modifications are proposed that can enhance the energy savings to 70% with a PCMOS architectural implementation. About 1.8-5 dB improvement in peak signal-to-noise ratio under energy savings of 57% to 70% for two different motion estimation algorithms is shown, establishing the resilience of the proposed algorithm to probabilistic computing over the comparable conventional algorithm.

Original languageEnglish
Article number6560374
Pages (from-to)1-14
Number of pages14
JournalIEEE Transactions on Circuits and Systems for Video Technology
Issue number1
Publication statusPublished - Jan 2014
Externally publishedYes


  • Error resilient design
  • low power design
  • motion estimation
  • probabilistic CMOS architecture
  • probabilistic computing

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering


Dive into the research topics of 'Low power motion estimation based on probabilistic computing'. Together they form a unique fingerprint.

Cite this