MFNW: An MLC/TLC flip-n-write architecture

Ali Alsuwaiyan, Kartik Mohanram

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

The increased capacity of multi-level cells (MLC) and triple-level cells (TLC) in emerging non-volatile memory (NVM) technologies comes at the cost of higher cell write energies and lower cell endurance. In this article, we describe MFNW, a Flip-N-Write encoding that effectively reduces the write energy and improves the endurance of MLC NVMs. Two MFNW modes are analyzed: cell Hamming distance mode and energy Hamming distance mode. We derive an approximate model that accurately predicts the average number of cell writes that is proportional to the energy consumption, enabling word length optimization to maximize energy reduction subject to memory space overhead constraints. In comparison to state-of-the-art MLC NVM encodings, our simulation results indicate that MFNW achieves up to 7%-39% saving for 1.56%-50% NVM space overhead. Extra energy saving (up to 19%-47%) can be achieved for the same NVM space overhead using our proposed variations of MFNW, i.e., MFNW2 and MFNW3. For TLC NVMs, we propose TFNW that can achieve up to 53% energy saving in comparison to state-of-the-art TLC NVM encodings. Endurance simulations indicate that MFNW (TFNW) is capable of extending MLC (TLC) NVM life by up to 100% (87%).

Original languageEnglish
Article number3154841
JournalACM Journal on Emerging Technologies in Computing Systems
Volume14
Issue number2
DOIs
StatePublished - Jul 2018

Bibliographical note

Publisher Copyright:
© 2018 ACM.

Keywords

  • Encoding
  • Low power
  • Multi-level cell (MLC)
  • Non-volatile memories
  • Triple-level cell (TLC)

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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