m-SAAC: Multi-stage adaptive approximation control to select approximate computing modes for vision applications

Rida Amjad, Rehan Hafiz, Muhammad U. Ilyas, Muhammad Shahzad Younis, Muhammad Shafique

Research output: Contribution to journalArticlepeer-review

Abstract

The psycho-visual nature of images and iterative nature of processing algorithms make vision and image processing suitable applications for approximate computing. State-of-the-art research in this area examines application resilience to approximation while assuming a uniform distribution for the information source. In this paper, we demonstrate that data-driven analysis can provide better insight into approximation requirements for image processing applications. Furthermore, this analysis is leveraged to design the multi-stage adaptive approximation control (m-SAAC) methodology that can save compute power by utilizing approximate computing, without compromising on image quality. The results demonstrate the efficacy of the proposed methodology for a variety of test cases.

Original languageEnglish (US)
Pages (from-to)84-91
Number of pages8
JournalMicroelectronics Journal
Volume91
DOIs
StatePublished - Sep 2019

Keywords

  • Approximate computing
  • Image processing
  • Resilience analysis

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Condensed Matter Physics
  • Surfaces, Coatings and Films
  • Electrical and Electronic Engineering

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