基于正规化格点玻尔兹曼法的多层网格并行算法

Zhixiang Liu, Yunhao Zhao, Wenhao Zhu, Yang Wang
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引用次数: 0

摘要

正则化格子波尔兹曼法(RLBM)是对格子波尔兹曼法(LBM)的改进。RLBM 的优点是在不增加计算开销的情况下提高精度。本文介绍了多层网格方法,多层网格具有不同的分辨率,可以在不破坏 RLBM 并行性的情况下精确解决计算流体动力学(CFD)问题。模拟流体流动通常需要大量的网格模拟。因此,有必要设计一种基于多层网格的 RLBM 并行算法。本文提出了一种基于负载平衡的网格划分算法和一种基于 MPI 的多层网格 RLBM 并行算法。基于负载平衡的网格划分算法可确保工作负载在各进程间均匀分布,最大限度地减少计算负载差异。基于 MPI 的多层网格 RLBM 并行算法确保了数值模拟的准确性和高效性。数值模拟验证了所提出的算法在二维和三维实验中均表现出卓越的性能,并保持了较高的稳定性和准确性。在 CPU 运行时间和所需网格数量方面,多层网格方法明显优于单层网格方法。与 OpenMP 多线程方法在多层网格 RLBM 上的对比分析表明,本文提出的算法在速度和效率上都更胜一筹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Parallel Algorithm Based on Regularized Lattice Boltzmann Method for Multi-Layer Grids
The regularized lattice Boltzmann method (RLBM) is an improvement of the lattice Boltzmann method (LBM). The advantage of RLBM is improved accuracy without increasing computational overheads. The paper introduces the method of multi-layer grids, the multi-layer grids have different resolutions which can accurately solve problems in computational fluid dynamics (CFD) without destroying the parallelism of RLBM. Simulating fluid flow usually requires a large number of grid simulations. Therefore, it is necessary to design a parallel algorithm for RLBM based on multi-layer grids. In this paper, a load-balancing-based grid dividing algorithm and an MPI-based parallel algorithm for RLBM on multi-layer grids are proposed. The load balancing-based grid dividing algorithm ensures that the workload is evenly distributed across processes, minimizing the discrepancies in computational load. The MPI-based parallel algorithm for RLBM on multi-layer grids ensures accurate and efficient numerical simulation. Numerical simulations have verified that the proposed algorithms exhibit excellent performance in both 2D and 3D experiments, maintaining high stability and accuracy. The multi-layer grids method is significantly better than single-layer grids in terms of CPU runtime and number of grids required. Comparative analysis with the OpenMP multi-threading method on the multi-layer grid RLBM shows that the proposed algorithm in this paper achieves superior speedup and efficiency.
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