• DocumentCode
    625659
  • Title

    Exploring SIMD for Molecular Dynamics, Using Intel® Xeon® Processors and Intel® Xeon Phi Coprocessors

  • Author

    Pennycook, S.J. ; Hughes, Christopher J. ; Smelyanskiy, Mikhail ; Jarvis, S.A.

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Warwick, Coventry, UK
  • fYear
    2013
  • fDate
    20-24 May 2013
  • Firstpage
    1085
  • Lastpage
    1097
  • Abstract
    We analyse gather-scatter performance bottlenecks in molecular dynamics codes and the challenges that they pose for obtaining benefits from SIMD execution. This analysis informs a number of novel code-level and algorithmic improvements to Sandia´s miniMD benchmark, which we demonstrate using three SIMD widths (128-, 256and 512bit). The applicability of these optimisations to wider SIMD is discussed, and we show that the conventional approach of exposing more parallelism through redundant computation is not necessarily best. In single precision, our optimised implementation is up to 5x faster than the original scalar code running on Intel®Xeon®processors with 256-bit SIMD, and adding a single Intel®Xeon Phi™coprocessor provides up to an additional 2x performance increase. These results demonstrate: (i) the importance of effective SIMD utilisation for molecular dynamics codes on current and future hardware; and (ii) the considerable performance increase afforded by the use of Intel®Xeon Phi™coprocessors for highly parallel workloads.
  • Keywords
    coprocessors; molecular dynamics method; optimisation; parallel architectures; Intel®Phi™coprocessor; Intel®Xeon® processor; SIMD execution; Sandia´s miniMD benchmark; code level; molecular dynamics code; optimisation; parallel workload; scalar code; single Intel®Xeon Phi™coprocessor; Coprocessors; Force; Hardware; Instruction sets; Optimization; Registers; accelerator architectures; high performance computing; parallel programming; performance analysis; scientific computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel & Distributed Processing (IPDPS), 2013 IEEE 27th International Symposium on
  • Conference_Location
    Boston, MA
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4673-6066-1
  • Type

    conf

  • DOI
    10.1109/IPDPS.2013.44
  • Filename
    6569887