Approximate multiplier using reordered 4-2 compressor with or-based error compensation

Yufeng Xu, Yi Guo, Shinji Kimura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Today, the approximate circuits have become an efficient solution for low power design on human related error-tolerant applications, such as multimedia, recognition and several signal processing. Approximate multipliers are believed to be an important key to make approximate arithmetic systems, and more area efficient multiplier is expected. The paper proposes a new ar-ea-efficient 4-2 compressor based on input reordering and OR-based error compensation. By the reordering, we can focus on just 2 of 4 inputs, and the compressor becomes very simple and less gates. Two multipliers are proposed with different accuracy based on reordered compressors with OR-based error compensation. The experimental results show that the proposed multipliers achieve high accuracy (98.7% and 97.39%) while reduce power consumption (by 44.72% and 45.95%) and area (by 31.72% and 34.85%). The proposed approximate multipliers are applied on image sharpening process and show high PSNR and SSIM.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 13th International Conference on ASIC, ASICON 2019
EditorsFan Ye, Ting-Ao Tang
PublisherIEEE Computer Society
ISBN (Electronic)9781728107356
DOIs
Publication statusPublished - 2019 Oct
Event13th IEEE International Conference on ASIC, ASICON 2019 - Chongqing, China
Duration: 2019 Oct 292019 Nov 1

Publication series

NameProceedings of International Conference on ASIC
ISSN (Print)2162-7541
ISSN (Electronic)2162-755X

Conference

Conference13th IEEE International Conference on ASIC, ASICON 2019
CountryChina
CityChongqing
Period19/10/2919/11/1

Keywords

  • Approximate multiplier
  • Compressor
  • Energy and area efficiency
  • Input reordering
  • OR-based compensation

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering

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