Acceleration of the Particle Swarm Optimization for Peierls–Nabarro modeling of dislocations in conventional and highentropy alloys
Dislocations are among the most important defects in determining the mechanical properties of both conventional alloys and highentropy alloys. The PeierlsNabarro model supplies an efficient pathway to their geometries and mobility. The difficulty in solving the integrodifferential PeierlsNabarro equation is how to effectively avoid the local minima in the energy landscape of a dislocation core. Among the other methods to optimize the dislocation core structures, we choose the algorithm of Particle Swarm Optimization, an algorithm that simulates the social behaviors of organisms. By employing more particles (bigger swarm) and more iterative steps (allowing them to explore for longer time), the local minima can be effectively avoided. But this would require more computational cost. The advantage of this algorithm is that it is readily parallelized in modern high computing architecture. We demonstrate the performance of our parallelized algorithm scales linearly with the number of employed cores.
 Authors:

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 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 (Germany)
 Publication Date:
 Grant/Contract Number:
 AC0500OR22725
 Type:
 Accepted Manuscript
 Journal Name:
 Computer Physics Communications
 Additional Journal Information:
 Journal Volume: 215; Journal Issue: C; Journal ID: ISSN 00104655
 Publisher:
 Elsevier
 Research Org:
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
 Sponsoring Org:
 USDOE
 Country of Publication:
 United States
 Language:
 English
 Subject:
 36 MATERIALS SCIENCE
 OSTI Identifier:
 1361334
 Alternate Identifier(s):
 OSTI ID: 1396497
Pei, Zongrui, MaxPlanckInst. fur Eisenforschung, Duseldorf, and Eisenbach, Markus. Acceleration of the Particle Swarm Optimization for Peierls–Nabarro modeling of dislocations in conventional and highentropy alloys. United States: N. p.,
Web. doi:10.1016/j.cpc.2017.01.022.
Pei, Zongrui, MaxPlanckInst. fur Eisenforschung, Duseldorf, & Eisenbach, Markus. Acceleration of the Particle Swarm Optimization for Peierls–Nabarro modeling of dislocations in conventional and highentropy alloys. United States. doi:10.1016/j.cpc.2017.01.022.
Pei, Zongrui, MaxPlanckInst. fur Eisenforschung, Duseldorf, and Eisenbach, Markus. 2017.
"Acceleration of the Particle Swarm Optimization for Peierls–Nabarro modeling of dislocations in conventional and highentropy alloys". United States.
doi:10.1016/j.cpc.2017.01.022. https://www.osti.gov/servlets/purl/1361334.
@article{osti_1361334,
title = {Acceleration of the Particle Swarm Optimization for Peierls–Nabarro modeling of dislocations in conventional and highentropy alloys},
author = {Pei, Zongrui and MaxPlanckInst. fur Eisenforschung, Duseldorf and Eisenbach, Markus},
abstractNote = {Dislocations are among the most important defects in determining the mechanical properties of both conventional alloys and highentropy alloys. The PeierlsNabarro model supplies an efficient pathway to their geometries and mobility. The difficulty in solving the integrodifferential PeierlsNabarro equation is how to effectively avoid the local minima in the energy landscape of a dislocation core. Among the other methods to optimize the dislocation core structures, we choose the algorithm of Particle Swarm Optimization, an algorithm that simulates the social behaviors of organisms. By employing more particles (bigger swarm) and more iterative steps (allowing them to explore for longer time), the local minima can be effectively avoided. But this would require more computational cost. The advantage of this algorithm is that it is readily parallelized in modern high computing architecture. We demonstrate the performance of our parallelized algorithm scales linearly with the number of employed cores.},
doi = {10.1016/j.cpc.2017.01.022},
journal = {Computer Physics Communications},
number = C,
volume = 215,
place = {United States},
year = {2017},
month = {2}
}