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@ARTICLE{Ganesan:851733,
author = {Ganesan, H. and Teijeiro, C. and Sutmann, G.},
title = {{P}arallelization comparison and optimization of a
scale-bridging framework to model {C}ottrell atmospheres},
journal = {Computational materials science},
volume = {155},
issn = {0927-0256},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {FZJ-2018-05260},
pages = {439 - 449},
year = {2018},
abstract = {Low carbon steels undergo strain aging when heat treated,
which causes an increased yield strength that can be
observed macroscopically. Such strengthening mechanism is
driven by atomistic scale processes, i.e., solute
segregation of carbon (C) or nitrogen interstitial atoms.
Due to its low solubility, alloying elements can diffuse to
defects (e.g., dislocations) and form the so-called Cottrell
atmospheres. Consequently, the mobility of defects is
strongly reduced because of the interaction with solutes,
and higher stresses are needed to unpin them from the
Cottrell atmosphere. As C segregation and atomistic motion
take place at separate timescales, Classical Molecular
Dynamics (MD) and Metropolis Monte Carlo (MC) are coupled in
a unified framework to capture collective effects with
underlying slow dynamics. The number of degrees of freedom
and the need for large computational resources in this
simulation requires the choice of an optimal parallelization
technique for the MC part of such multi-scale simulations
using an unbiased sampling of the configuration space. In
the present work,two different parallel approaches for the
MC routine applied to the simulation of Cottrell atmospheres
are implemented and compared: (i) a manager-worker
speculative scheme and (ii) a distributed manager-worker
over a cell-based domain decomposition approach augmented by
an efficient load balancing scheme. The parallel performance
of different Fe-C containing defects with several millions
of atoms is analyzed, and also the possible optimization of
the efficiency of the MC solute segregation process is
evaluated regarding energy minimization.},
cin = {JSC / JARA-HPC},
ddc = {530},
cid = {I:(DE-Juel1)JSC-20090406 / $I:(DE-82)080012_20140620$},
pnm = {511 - Computational Science and Mathematical Methods
(POF3-511) / Parallel Hybrid Monte Carlo/Molecular Dynamics
for Segregation in Solid State Systems $(jjsc29_20170501)$},
pid = {G:(DE-HGF)POF3-511 / $G:(DE-Juel1)jjsc29_20170501$},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000447748900051},
doi = {10.1016/j.commatsci.2018.08.055},
url = {https://juser.fz-juelich.de/record/851733},
}