Demonstration of Inexact Computing Implemented in the JPEG Compression Algorithm using Probabilistic Boolean Logic applied to CMOS Components

Abstract

Probabilistic computing offers potential improvements in energy, performance, and area compared with traditional digital design. This dissertation quantifies energy and energy-delay tradeoffs in digital adders, multipliers, and the JPEG image compression algorithm. This research shows that energy demand can be cut in half with noisesusceptible16-bit Kogge-Stone adders that deviate from the correct value by an average of 3 in 14 nanometer CMOS FinFET technology, while the energy-delay product (EDP) is reduced by 38 . This is achieved by reducing the power supply voltage which drives the noisy transistors. If a 19 average error is allowed, the adders are 13 times more energy-efficient and the EDP is reduced by 35 . This research demonstrates that 92 of the color space transform and discrete cosine transform circuits within the JPEG algorithm can be built from inexact components, and still produce readable images. Given the case in which each binary logic gate has a 1 error probability, the color space transformation has an average pixel error of 5.4 and a 55 energy reduction compared to the error-free circuit, and the discrete cosine transformation has a 55 energy reduction with an average pixel error of 20 .

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Document Details

Document Type
Technical Report
Publication Date
Dec 24, 2015
Accession Number
AD1002544

Entities

People

  • Christopher I. Allen

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Coding
  • Computer Programming
  • Computer Science
  • Cosmic Rays
  • Data Compression
  • Databases
  • Department Of Defense
  • Digital Circuits
  • Energy Consumption
  • Floating Point Operations
  • Logic Gates
  • Random Variables
  • Reliability
  • Two Dimensional
  • United States
  • United States Government

Readers

  • Computer Programming and Software Development.
  • Energy Conservation and Renewable Energy Engineering.
  • Image Processing and Computer Vision.

Technology Areas

  • Space