• DocumentCode
    3764391
  • Title

    Ex-situ programming in a neuromorphic memristor based crossbar circuit

  • Author

    Chris Yakopcic;Tarek M. Taha

  • Author_Institution
    Department of Electrical and Computer Engineering, University of Dayton, Dayton, OH, USA
  • fYear
    2015
  • fDate
    6/1/2015 12:00:00 AM
  • Firstpage
    300
  • Lastpage
    304
  • Abstract
    This paper discusses a feedback programming method for a high density crossbar. This programming technique is capable of operating without the use of any transistor or diode isolation at the memristor crosspoints. A series of reads is applied to the crossbar before each write that is able to determine the resistance of each memristor in the crossbar despite the many parallel resistance paths. This is essential because the variation observed in memristor crossbars makes programming very difficult when using just a single write pulse without error checking. The programming method is then used to program a neuromorphic crossbar. Results show successful ex-situ training of a high density crossbar with significant area savings when compared to a one transistor one memristor (1T1M) design. A comparison between different crossbar designs is performed relative to the A-to-D complexity required to program each circuit for a varying device resistance ratio and programming precision.
  • Keywords
    "Memristors","Resistance","Programming","Mathematical model","Integrated circuit modeling","SPICE","Transistors"
  • Publisher
    ieee
  • Conference_Titel
    Aerospace and Electronics Conference (NAECON), 2015 National
  • Electronic_ISBN
    2379-2027
  • Type

    conf

  • DOI
    10.1109/NAECON.2015.7443087
  • Filename
    7443087