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Parallel Monte Carlo Simulation of Molecular Weight Distribution and Chemical Composition Distribution for Copolymerization on a Graphics Processing Unit Platform
Author(s) -
Weng Jinzu,
Chen Xi,
Yao Zhen,
Biegler Lorenz T.
Publication year - 2015
Publication title -
macromolecular theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.37
H-Index - 56
eISSN - 1521-3919
pISSN - 1022-1344
DOI - 10.1002/mats.201500021
Subject(s) - monte carlo method , graphics processing unit , computation , computer science , computational science , graphics , copolymer , statistical physics , computer graphics , distribution (mathematics) , algorithm , parallel computing , polymer , materials science , computer graphics (images) , mathematics , physics , statistics , composite material , mathematical analysis
Polymers can be used in diverse applications in daily life because of their various microstructures. Molecular weight distribution and chemical composition distribution are the two most important microstructural indices for many copolymers. Monte Carlo simulation is an efficient method to obtain those specific distributions that cannot be easily determined via traditional equation‐based methods. However, this method requires long computation time. In this project, a parallel method is proposed for Monte Carlo simulation on a graphics processing unit platform. Both steady state and dynamic state cases are presented to show the accuracy and efficiency of the proposed method. The computation time of the proposed method is greatly decreased by at least 30‐fold compared with the time required by CPU platform.