An offline frequent value encoding for energy-efficient MLC/TLC non-volatile memories

Ali Alsuwaiyan, Kartik Mohanram

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations


This paper describes a low overhead, offline frequent value encoding (FVE) solution to reduce the write energy in multi-level/triple-level cell (MLC/TLC) non-volatile memories (NVMs). The proposed solution, which does not require any runtime software support, clusters a set of general-purpose applications according to their data frequency profiles and generates a dedicated offline FVE that minimizes write energy for each cluster. Results show that the write energy reduction of evaluation sets - using FVEs generated for training sets - are close (equal) to the best known solution for MLC (TLC) NVM encoding; however, our solution incurs a memory overhead that is 16× (5.7×) less than the best comparable scheme in the literature for MLC (TLC) NVMs.

Original languageEnglish
Title of host publicationGLSVLSI 2016 - Proceedings of the 2016 ACM Great Lakes Symposium on VLSI
PublisherAssociation for Computing Machinery
Number of pages6
ISBN (Electronic)9781450342742
StatePublished - 18 May 2016
Externally publishedYes

Publication series

NameProceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI

Bibliographical note

Publisher Copyright:
© 2016 ACM.


  • Encoding
  • Energy
  • Non-volatile memories

ASJC Scopus subject areas

  • Engineering (all)


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