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Data parallel large‐scale molecular dynamics for liquids
Author(s) -
Hedman Fredrik,
Laaksonen Aatto
Publication year - 1993
Publication title -
international journal of quantum chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.484
H-Index - 105
eISSN - 1097-461X
pISSN - 0020-7608
DOI - 10.1002/qua.560460104
Subject(s) - simd , parallel computing , mimd , computer science , massively parallel , computational science , molecular dynamics , dissipative particle dynamics , scalability , fortran , computation , range (aeronautics) , scale (ratio) , particle (ecology) , sorting , asynchronous communication , parallel algorithm , periodic boundary conditions , algorithm , physics , chemistry , materials science , boundary value problem , computational chemistry , oceanography , quantum mechanics , composite material , geology , computer network , nuclear magnetic resonance , database , operating system , polymer
An efficient data parallel computational scheme is presented for large‐scale molecular dynamics ( MD ) simulations of liquids with short‐range interactions. The method is based on decomposition of the simulation cell into equally sized subcells, with the shortest side length equal to the cutoff radius. Inter‐ and intracell interactions are calculated in a coarse‐grained manner. A geometric sorting procedure, based on particle distances to subcell boundaries, is used to minimize the overall computations and the nonproductive communications. Using only nearest‐neighbor communications, an efficient scheme is developed for periodic updates of the contents of subcells due to the migration of particles. Special “null‐particles” are introduced, which act as buffers during the periodic updates and allow for a globally uniform algorithm during the calculations. Communication cost is about 7% of the total CPU time. The method is found to be linearly scalable with the number of particles, performing better as the ratio of virtual to physical processors increases. The MD code is written in Fortran 90 and implemented on a CM‐200. The overall speed is approximately 5.9 μs. per MD step and per particle for 1 million particles and 5.5 μs for 5 million particles. The method should be easily transferred to other massively parallel computers of SIMD and MIMD type. © 1993 John Wiley & Sons, Inc.