Progressive Scaled STT-RAM for Approximate Computing in Multimedia Applications

Behzad Zeinali, Dimitrios Karsinos, Farshad Moradi

    Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

    22 Citations (Scopus)

    Abstract

    Spintronic memories are one of the most promising candidates as a universal memory. Although they offer superior energy efficiency over the conventional memories, benefiting from approximate computing approach, some novel techniques can be applied to lower the power consumption even further. In this brief, we propose a progressive scaling scheme for spin-transfer torque random access memory (STT-RAM) arrays, by which the power consumption is reduced at the expense of small quality degradation. According to the proposed approach, access transistors in STT-RAM cells are scaled based on an optimized scaling factor, where least significant bits and most significant bits come with different bit error rates in the data word. Simulation results show that the proposed approach provides 36.7% write power dissipation and 25% die area savings, respectively, while negligible quality degradation is observed based on mean structural similarity index.

    Original languageEnglish
    JournalIEEE Transactions on Circuits and Systems II: Express Briefs
    Volume65
    Issue7
    Pages (from-to)938-942
    Number of pages5
    ISSN1549-7747
    DOIs
    Publication statusPublished - Jul 2018

    Keywords

    • Degradation
    • Energy-Efficiency
    • Magnetic tunneling
    • Multimedia application
    • Multimedia communication
    • Random access memory
    • STT-RAM
    • Streaming media
    • Switches
    • Transistors
    • approximate computing.
    • approximate computing
    • multimedia application
    • energy efficiency

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