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

机译:多粒流模拟晶格Boltzmann方法晶格Boltzmann方法的计算性能

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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.
机译:本文首次报告了通过格子玻璃螺柱方法在微流体装置中大量粒子的Messcale模拟的序号的计算性能。针对优化的串行和并行化(通过OpenMP指令)进行评估Sequencel模拟的性能。目前,由于从DO-LOOPS的连续迭代之间的迭代次级依赖性困难,OPENMP指令不包括在颗粒间和粒子壁排斥(空间)交互计算中。另一方面,Sequencel模拟依赖内置自动并行性。在这些条件下,数值模拟显示,当颗粒的数量为100或更小时,并联的FORTRAN90将序列的性能以2.5或更多的增加。然而,当粒子的数量为300时,序列突出的性能是1.3因子1.3的性能。我们的结果表明,当粒子的数量增加30倍时,Sequencel模拟的计算时间因因素线性而增加1.5,相比,平行化Fortran90模拟平行化的3.2倍和7.7倍的增加。考虑序列的高效内置并行,导致计算时间增加的计算时间增加,粒子数量增加,可以是用于在微流体实验中大量粒子的计算有效的Messcale模拟的有望的编程语言。 (c)2016年Elsevier B.v.保留所有权利。

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