• DocumentCode
    610875
  • Title

    Numerical Reproducibility and Accuracy at ExaScale

  • Author

    Demmel, J. ; Hong Diep Nguyen

  • Author_Institution
    Math. Dept., Univ. of California at Berkeley, Berkeley, CA, USA
  • fYear
    2013
  • fDate
    7-10 April 2013
  • Firstpage
    235
  • Lastpage
    237
  • Abstract
    Given current hardware trends, ExaScale computing (1018 floating point operations per second) is projected to be available in less than a decade, achieved by using a huge number of processors, of order 109. Given the likely hardware heterogeneity in both platform and network, and the possibility of intermittent failures, dynamic scheduling will be needed to adapt to changing resources and loads. This will make it likely that repeated runs of a program will not execute operations like reductions in exactly the same order. This in turn will make reproducibility, i.e. getting bitwise identical results from run to run, difficult to achieve, because floating point operations like addition are not associative, so computing sums in different orders often leads to different results. Indeed, this is already a challenge on today´s platforms.
  • Keywords
    floating point arithmetic; parallel processing; addition; dynamic scheduling; exascale computing; floating point operations; hardware heterogeneity; hardware trends; intermittent failures; numerical accuracy; numerical reproducibility; Accuracy; Computational modeling; Digital arithmetic; Educational institutions; Hardware; Program processors; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Arithmetic (ARITH), 2013 21st IEEE Symposium on
  • Conference_Location
    Austin, TX
  • ISSN
    1063-6889
  • Print_ISBN
    978-1-4673-5644-2
  • Type

    conf

  • DOI
    10.1109/ARITH.2013.43
  • Filename
    6545912