• DocumentCode
    41787
  • Title

    Large-Scale Memristive Associative Memories

  • Author

    Lehtonen, Eero ; Poikonen, Jussi H. ; Laiho, Mika ; Kanerva, Pentti

  • Author_Institution
    BID Technol., Univ. of Turku, Turku, Finland
  • Volume
    22
  • Issue
    3
  • fYear
    2014
  • fDate
    Mar-14
  • Firstpage
    562
  • Lastpage
    574
  • Abstract
    Associative memories, in contrast to conventional address-based memories, are inherently fault-tolerant and allow retrieval of data based on partial search information. This paper considers the possibility of implementing large-scale associative memories through memristive devices jointly with CMOS circuitry. An advantage of a memristive associative memory is that the memory elements are located physically above the CMOS layer, which yields more die area for the processing elements realized in CMOS. This allows for high-capacity memories even while using an older CMOS technology, as the capacity of the memory depends more on the feature size of the memristive crossbar than on that of the CMOS components. In this paper, we propose the memristive implementations, and present simulations and error analysis of the autoassociative content-addressable memory, the Willshaw memory, and the sparse distributed memory. Furthermore, we present a CMOS cell that can be used to implement the proposed memory architectures.
  • Keywords
    CMOS memory circuits; content-addressable storage; error analysis; memristors; CMOS cell; CMOS circuitry; CMOS components; CMOS layer; Willshaw memory; address-based memories; autoassociative content-addressable memory; error analysis; fault-tolerant; high-capacity memories; large-scale associative memories; memristive associative memory; memristive devices; partial search information; sparse distributed memory; Associative memory; memristors; mixed analog digital integrated circuits;
  • fLanguage
    English
  • Journal_Title
    Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-8210
  • Type

    jour

  • DOI
    10.1109/TVLSI.2013.2250319
  • Filename
    6510498