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Title: A performance analysis of ensemble averaging for high fidelity turbulence simulations at the strong scaling limit

Abstract

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 study focuses on the theory and implementation of the methodology in Nek5000, a massively parallel open-source spectral element code.

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Argonne National Lab. (ANL), Lemont, IL (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1393517
Alternate Identifier(s):
OSTI ID: 1550297
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Accepted Manuscript
Journal Name:
Computer Physics Communications
Additional Journal Information:
Journal Volume: 219; Journal Issue: C; Journal ID: ISSN 0010-4655
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; 97 MATHEMATICS AND COMPUTING; Ensemble averaging; Nek5000

Citation Formats

Makarashvili, Vakhtang, Merzari, Elia, Obabko, Aleksandr, Siegel, Andrew, and Fischer, Paul. A performance analysis of ensemble averaging for high fidelity turbulence simulations at the strong scaling limit. United States: N. p., 2017. Web. doi:10.1016/j.cpc.2017.05.023.
Makarashvili, Vakhtang, Merzari, Elia, Obabko, Aleksandr, Siegel, Andrew, & Fischer, Paul. A performance analysis of ensemble averaging for high fidelity turbulence simulations at the strong scaling limit. United States. https://doi.org/10.1016/j.cpc.2017.05.023
Makarashvili, Vakhtang, Merzari, Elia, Obabko, Aleksandr, Siegel, Andrew, and Fischer, Paul. Wed . "A performance analysis of ensemble averaging for high fidelity turbulence simulations at the strong scaling limit". United States. https://doi.org/10.1016/j.cpc.2017.05.023. https://www.osti.gov/servlets/purl/1393517.
@article{osti_1393517,
title = {A performance analysis of ensemble averaging for high fidelity turbulence simulations at the strong scaling limit},
author = {Makarashvili, Vakhtang and Merzari, Elia and Obabko, Aleksandr and Siegel, Andrew and Fischer, Paul},
abstractNote = {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 study focuses on the theory and implementation of the methodology in Nek5000, a massively parallel open-source spectral element code.},
doi = {10.1016/j.cpc.2017.05.023},
journal = {Computer Physics Communications},
number = C,
volume = 219,
place = {United States},
year = {2017},
month = {6}
}

Journal Article:

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Cited by: 7 works
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