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O-2A: Low overhead DNN compression with outlier-aware approximation

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1 Citation (Scopus)

Abstract

We present a low-latency DNN compression technique to reduce DRAM energy, significant in DNN inferences, namely Outlier-Aware Approximation (O-2A) coding. This technique compresses 8-bit integer, de-facto standard of DNN inferences, to 6-bit without degrading the accuracies of DNNs. The hardware for the O-2A coding can be easily embedded to DRAM controllers due to small overhead. In an Eyeriss platform, the O-2A coding improves both DRAM energy and system performance by 18~20%. The O-2A coding enables us to implement an error-correction scheme without additional parity overhead, opening the possibility of an approximate DRAM to simultaneously reduce DRAM accessing and refresh energy.

Original languageEnglish
Title of host publication2020 57th ACM/IEEE Design Automation Conference, DAC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450367257
DOIs
Publication statusPublished - Jul 2020
Event57th ACM/IEEE Design Automation Conference, DAC 2020 - Virtual, San Francisco, United States
Duration: 20 Jul 202024 Jul 2020

Publication series

NameProceedings - Design Automation Conference
Volume2020-July
ISSN (Print)0738-100X

Conference

Conference57th ACM/IEEE Design Automation Conference, DAC 2020
Country/TerritoryUnited States
CityVirtual, San Francisco
Period20/07/2024/07/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Approximation
  • DRAM
  • Low-latency DNN compression

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