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Computational performance of SequenceL coding of the lattice Boltzmann method for multi-particle flow simulations

Authors :
John R. Harwell
Sauro Succi
Bryant Nelson
Jarred Blount
Justin Blount
Hakan Başağaoğlu
Phil M. Westhart
Source :
Computer physics communications 213 (2017): 92–99. doi:10.1016/j.cpc.2016.12.012, info:cnr-pdr/source/autori:Basagaoglu, Hakan; Blount, Justin; Blount, Jarred; Nelson, Bryant; Succi, Sauro; Westhart, Phil M.; Harwell, John R./titolo:Computational performance of SequenceL coding of the lattice Boltzmann method for multi-particle flow simulations/doi:10.1016%2Fj.cpc.2016.12.012/rivista:Computer physics communications/anno:2017/pagina_da:92/pagina_a:99/intervallo_pagine:92–99/volume:213
Publication Year :
2017
Publisher :
North-Holland, Amsterdam , Paesi Bassi, 2017.

Abstract

This paper reports, for the first time, the computational performance of SequenceL for mesoscale simulations of large numbers of particles in a microfluidic device via the lattice-Boltzmann method. The performance of SequenceL simulations was assessed against the optimized serial and parallelized (via OpenMP directives) FORTRAN90 simulations. At present, OpenMP directives were not included in interparticle and particle-wall repulsive (steric) interaction calculations due to difficulties that arose from inter-iteration dependencies between consecutive iterations of the do-loops. SequenceL simulations, on the other hand, relied on built-in automatic parallelism. Under these conditions, numerical simulations revealed that the parallelized FORTRAN90 outran the performance of SequenceL by a factor of 2.5 or more when the number of particles was 100 or less. SequenceL, however, outran the performance of the parallelized FORTRAN90 by a factor of 1.3 when the number of particles was 300. Our results show that when the number of particles increased by 30-fold, the computational time of SequenceL simulations increased linearly by a factor of 1.5, as compared to a 3.2-fold increase in serial and a 7.7-fold increase in parallelized FORTRAN90 simulations. Considering SequenceL's efficient built-in parallelism that led to a relatively small increase in computational time with increased number of particles, it could be a promising programming language for computationally-efficient mesoscale simulations of large numbers of particles in microfluidic experiments. (C) 2016 Elsevier B.V. All rights reserved.

Details

Language :
English
Database :
OpenAIRE
Journal :
Computer physics communications 213 (2017): 92–99. doi:10.1016/j.cpc.2016.12.012, info:cnr-pdr/source/autori:Basagaoglu, Hakan; Blount, Justin; Blount, Jarred; Nelson, Bryant; Succi, Sauro; Westhart, Phil M.; Harwell, John R./titolo:Computational performance of SequenceL coding of the lattice Boltzmann method for multi-particle flow simulations/doi:10.1016%2Fj.cpc.2016.12.012/rivista:Computer physics communications/anno:2017/pagina_da:92/pagina_a:99/intervallo_pagine:92–99/volume:213
Accession number :
edsair.doi.dedup.....b9b233ec87d38700ff89c8ab13dd19bc
Full Text :
https://doi.org/10.1016/j.cpc.2016.12.012