• DocumentCode
    183030
  • Title

    DataCenter 2020: Near-memory acceleration for data-oriented applications

  • Author

    Doller, Edward ; Akel, Ameen ; Wang, Jiacheng ; Curewitz, Ken ; Eilert, Sean

  • Author_Institution
    Memory Syst. Archit. R&D, Micron Technol. Inc., Folsom, CA, USA
  • fYear
    2014
  • fDate
    10-13 June 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In the years between now and 2020, we should expect continued exponential data growth [15][16]. A number of ongoing advances in storage: the transition to solid-state drives (SSDs), the scaling of NAND flash capacity, and advanced silicon packaging techniques will dramatically increase the capacity of storage subsystems over the same timeframe. This will significantly reduce the ratio of storage bandwidth to storage density. Consequently, the majority of data in 2020 will either be cold or will require near-memory acceleration to pull rich information out of the sea of big data. We argue that, increasingly over time, value lies not merely in the size of the data, but rather in what one can do with it.
  • Keywords
    NAND circuits; electronics packaging; elemental semiconductors; flash memories; silicon; DataCenter 2020; NAND flash memory capacity; SSD; Si; advanced silicon packaging technique; data-oriented application; near-memory acceleration; solid-state drive; storage density; Acceleration; Bandwidth; Computer architecture; Databases; Engines; Hardware; Software;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    VLSI Circuits Digest of Technical Papers, 2014 Symposium on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    978-1-4799-3327-3
  • Type

    conf

  • DOI
    10.1109/VLSIC.2014.6858357
  • Filename
    6858357