Two-step state transition minimization for lifetime and performance improvement on MLC STT-RAM

Huizhang Luo, Jingtong Hu, Liang Shi, Chun Jason Xue, Qingfeng Zhuge

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

16 Scopus citations

Abstract

Spin-transfer torque random access memory (STT-RAM) is considered as a promising candidate to replace SRAM as the next generation cache memory since it has better scalability and lower leakage power. Recently, 2-bit multi-level cell (MLC) STT-RAM has been proposed to further increase data density. However, a key drawback for MLC STT-RAM is that the magnetization directions of its hard and soft domains cannot be flipped to two opposite directions simultaneously, which leads to the two-step problem in state transitions. Two-step state transitions would significantly impact the lifetime of MLC STT-RAM due to the wasted flips in the soft domains. To solve the problem, this paper proposes a novel two-step state transition minimization (TSTM) scheme, to improve the lifetime of MLC STT-RAM when it is employed in cache design. The basic idea is by sacrificing certain cells as auxiliary flags, the two-step state transitions in STT-RAM can be well eliminated. Experimental results show that the proposed scheme can improve the lifetime of MLC STT-RAM to 318.5%.

Original languageEnglish (US)
Title of host publicationProceedings of the 53rd Annual Design Automation Conference, DAC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450342360
DOIs
StatePublished - Jun 5 2016
Externally publishedYes
Event53rd Annual ACM IEEE Design Automation Conference, DAC 2016 - Austin, United States
Duration: Jun 5 2016Jun 9 2016

Publication series

NameProceedings - Design Automation Conference
Volume05-09-June-2016
ISSN (Print)0738-100X

Other

Other53rd Annual ACM IEEE Design Automation Conference, DAC 2016
Country/TerritoryUnited States
CityAustin
Period6/5/166/9/16

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation

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