• DocumentCode
    2028004
  • Title

    Enabling a Quantum Monte Carlo application for the DEEP architecture

  • Author

    Emerson, Andrew ; Affinito, Fabio

  • Author_Institution
    Supercomput. Applic. & Innovation (SCAI), Cineca, Casalecchio di Reno, Italy
  • fYear
    2015
  • fDate
    20-24 July 2015
  • Firstpage
    453
  • Lastpage
    457
  • Abstract
    In the DEEP project a prototype Exascale system consisting of a standard Intel Xeon cluster linked to a “Booster” part containing Intel Xeon Phi nodes connected in a high-speed network, is being designed and constructed. In order to evaluate this novel architecture, expected to be available in the second half of 2015, a number of grand challenge applications in computational science and engineering are being modified and optimised. In this study we report on the efforts made by the Cineca project partner and DEEP support staff to enable one of these applications, the TurboRVB Quantum Monte Carlo simulation program, which can be used to study complex phenomena in materials such as superconductivity. The modified code, based on an implementation of the OmpSs offload task model, has been successfully tested on the MareNostrum supercomputer at the Barcelona Supercomputing Center.
  • Keywords
    Monte Carlo methods; parallel machines; quantum computing; Barcelona Supercomputing Center; Cineca project; DEEP architecture; Exascale system; Intel Xeon Phi nodes; Intel Xeon cluster; MareNostrum supercomputer; OmpSs offload task model; TurboRVB Quantum Monte Carlo simulation program; high-speed network; Computer architecture; Lattices; Microwave integrated circuits; Monte Carlo methods; Programming; Prototypes; Software; Exascale Systems; Modeling and Simulation using HPC Systems; Parallelization of Simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing & Simulation (HPCS), 2015 International Conference on
  • Conference_Location
    Amsterdam
  • Print_ISBN
    978-1-4673-7812-3
  • Type

    conf

  • DOI
    10.1109/HPCSim.2015.7237075
  • Filename
    7237075