Error resilience analysis for systematically employing approximate computing in convolutional neural networks

Muhammad Abdullah Hanif, Rehan Hafiz, Muhammad Shafique

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

Abstract

Approximate computing is an emerging paradigm for error resilient applications as it leverages accuracy loss for improving power, energy, area, and/or performance of an application. The spectrum of error resilient applications includes the domains of Image and video processing, Artificial Intelligence (AI) and Machine Learning (ML), data analytics, and other Recognition, Mining, and Synthesis (RMS) applications. In this work, we address one of the most challenging question, i.e., how to systematically employ approximate computing in Convolution Neural Networks (CNNs), which are one of the most compute-intensive and the pivotal part of AI. Towards this, we propose a methodology to systematically analyze error resilience of deep CNNs and identify parameters that can be exploited for improving performance/efficiency of these networks for inference purposes. We also present a case study for significance-driven classification of filters for different convolutional layers, and propose to prune those having the least significance, and thereby enabling accuracy vs. efficiency tradeoffs by exploiting their resilience characteristics in a systematic way.

Original languageEnglish (US)
Title of host publicationProceedings of the 2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages913-916
Number of pages4
ISBN (Electronic)9783981926316
DOIs
StatePublished - Apr 19 2018
Event2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018 - Dresden, Germany
Duration: Mar 19 2018Mar 23 2018

Publication series

NameProceedings of the 2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018
Volume2018-January

Other

Other2018 Design, Automation and Test in Europe Conference and Exhibition, DATE 2018
CountryGermany
CityDresden
Period3/19/183/23/18

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Hardware and Architecture
  • Software
  • Information Systems and Management

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