A performance analysis of ensemble averaging for high fidelity turbulence simulations at the strong scaling limit
作者: Vakhtang MakarashviliElia MerzariAleksandr ObabkoAndrew SiegelPaul Fischer
作者单位: 1Math and Computer Science Division, Argonne National Laboratory, 9700 S. Cass Ave. Lemont, IL 60439, United States
刊名: Computer Physics Communications, 2017, Vol.219 , pp.236-245
来源数据库: Elsevier Journal
DOI: 10.1016/j.cpc.2017.05.023
关键词: Ensemble averagingNek5000
原始语种摘要: Abstract(#br)We analyze the potential performance benefits of estimating expected quantities in large eddy simulations of turbulent flows using true ensembles rather than ergodic time averaging. Multiple realizations of the same flow are simulated in parallel, using slightly perturbed initial conditions to create unique instantaneous evolutions of the flow field. Each realization is then used to calculate statistical quantities. Provided each instance is sufficiently de-correlated, this approach potentially allows considerable reduction in the time to solution beyond the strong scaling limit for a given accuracy. This paper focuses on the theory and implementation of the methodology in Nek5000, a massively parallel open-source spectral element code.
全文获取路径: Elsevier  (合作)
影响因子:3.078 (2012)

  • averaging 求平均数
  • scaling 按比例缩小
  • performance 性能
  • limit 界限
  • instance 例子
  • create 引起
  • methodology 方法学
  • implementation 执行
  • spectral 谱的
  • strong