Tunable precision control for approximate image filtering in an in-memory architecture with embedded neurons

Ayushi Dube, Ankit Wagle, Gian Singh, Sarma Vrudhula

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

Abstract

This paper presents a novel hardware-software co-design consisting of a Processing in-Memory (PiM) architecture with embedded neural processing elements (NPE) that are highly reconfigurable. The PiM platform and proposed approximation strategies are employed for various image filtering applications while providing the user with fine-grain dynamic control over energy efficiency, precision, and throughput (EPT). The proposed co-design can change the Peak Signal to Noise Ratio (PSNR, output quality metric for image filtering applications) from 25dB to 50dB (acceptable PSNR range for image filtering applications) without incurring any extra cost in terms of energy or latency. While switching from accurate to approximate mode of computation in the proposed co-design, the maximum improvement in energy efficiency and throughput is 2X. However, the gains in energy efficiency against a MACbased PE array with the proposed memory platform are 3X-6X. The corresponding improvements in throughput are 2.26X-4.52X, respectively.

Original languageEnglish (US)
Title of host publicationProceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450392174
DOIs
StatePublished - Oct 30 2022
Event41st IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2022 - San Diego, United States
Duration: Oct 30 2022Nov 4 2022

Publication series

NameIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
ISSN (Print)1092-3152

Conference

Conference41st IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2022
Country/TerritoryUnited States
CitySan Diego
Period10/30/2211/4/22

Keywords

  • and throughput (EPT)
  • energy efficiency
  • neural processing elements (NPE)
  • Peak Signal to Noise Ratio (PSNR)
  • precision
  • Processing in-Memory (PiM)

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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