Low Cost Early Exit Decision Unit Design for CNN Accelerator

Geonho Kim, Jongsun Park

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

Abstract

Early exit has been studied as a way to reduce the complex computation of convolutional neural networks. However, in order to determine whether to exit early in a conventional CNN accelerator, there is a problem that a unit for computing softmax layer having a large hardware overhead is required. To solve this problem, we propose a low cost early exit decision unit. The proposed architecture uses only fully-connected (FC) layer outputs to make early exit decisions, so the computation of the softmax layer is not necessary. Our implementation results show an energy reduction of 68% with an accuracy drop of less than 0.3%.

Original languageEnglish
Title of host publicationProceedings - International SoC Design Conference, ISOCC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages127-128
Number of pages2
ISBN (Electronic)9781728183312
DOIs
Publication statusPublished - 2020 Oct 21
Event17th International System-on-Chip Design Conference, ISOCC 2020 - Yeosu, Korea, Republic of
Duration: 2020 Oct 212020 Oct 24

Publication series

NameProceedings - International SoC Design Conference, ISOCC 2020

Conference

Conference17th International System-on-Chip Design Conference, ISOCC 2020
CountryKorea, Republic of
CityYeosu
Period20/10/2120/10/24

Keywords

  • CNN accelerator
  • early exit
  • softmax

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Instrumentation
  • Artificial Intelligence
  • Hardware and Architecture

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