Lethe-DEM: an open-source parallel discrete element solver with load balancing

IF 2.8 3区 工程技术 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Shahab Golshan, Peter Munch, Rene Gassmöller, Martin Kronbichler, Bruno Blais
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引用次数: 9

Abstract

Approximately \({75}\%\) of the raw material and \({50}\%\) of the products in the chemical industry are granular materials. The discrete element method (DEM) provides detailed insights of phenomena at particle scale, and it is therefore often used for modeling granular materials. However, because DEM tracks the motion and contact of individual particles separately, its computational cost increases nonlinearly \(O(n_\mathrm{p}\log (n_\mathrm{p}))\)\(O(n_\mathrm{p}^2)\) (depending on the algorithm) with the number of particles (\(n_\mathrm{p}\)). In this article, we introduce a new open-source parallel DEM software with load balancing: Lethe-DEM. Lethe-DEM, a module of Lethe, consists of solvers for two-dimensional and three-dimensional DEM simulations. Load balancing allows Lethe-DEM to significantly increase the parallel efficiency by \(\approx {25}\)\({70}\%\) depending on the granular simulation. We explain the fundamental modules of Lethe-DEM, its software architecture, and the governing equations. Furthermore, we verify Lethe-DEM with several tests including analytical solutions and comparison with other software. Comparisons with experiments in a flat-bottomed silo, wedge-shaped silo, and rotating drum validate Lethe-DEM. We investigate the strong and weak scaling of Lethe-DEM with \({1}\le n_\mathrm{c} \le {192}\) and \({32}\le n_\mathrm{c} \le {320}\) processes, respectively, with and without load balancing. The strong-scaling analysis is performed on the wedge-shaped silo and rotating drum simulations, while for the weak-scaling analysis, we use a dam-break simulation. The best scalability of Lethe-DEM is obtained in the range of \({5000}\le n_\mathrm{p}/n_\mathrm{c} \le {15{,}000}\). Finally, we demonstrate that large-scale simulations can be carried out with Lethe-DEM using the simulation of a three-dimensional cylindrical silo with \(n_\mathrm{p}={4.3}\times 10^6\) on 320 cores.

Abstract Image

Lethe-DEM:一个具有负载平衡的开源并行离散元素求解器
在化学工业中,大约\({75}\%\)的原料和\({50}\%\)的产品是颗粒状材料。离散元方法(DEM)提供了颗粒尺度上现象的详细见解,因此经常用于颗粒材料的建模。然而,由于DEM单独跟踪单个粒子的运动和接触,其计算成本随着粒子数量(\(n_\mathrm{p}\))非线性增加\(O(n_\mathrm{p}\log (n_\mathrm{p}))\) - \(O(n_\mathrm{p}^2)\)(取决于算法)。在本文中,我们介绍了一种新的开源并行DEM软件:Lethe-DEM。Lethe-DEM是Lethe软件的一个模块,由二维和三维DEM模拟求解器组成。负载平衡允许Lethe-DEM显著提高并行效率\(\approx {25}\) - \({70}\%\)取决于颗粒模拟。我们解释了Lethe-DEM的基本模块,它的软件架构和控制方程。此外,我们通过分析解和与其他软件的比较等几个测试验证了Lethe-DEM。与平底筒仓、楔形筒仓和旋转筒仓的实验比较,验证了Lethe-DEM的有效性。我们分别在负载平衡和不负载平衡的情况下,研究了\({1}\le n_\mathrm{c} \le {192}\)和\({32}\le n_\mathrm{c} \le {320}\)过程中Lethe-DEM的强缩放和弱缩放。对楔形筒仓和旋转筒仓进行了强结垢分析,对溃坝进行了弱结垢分析。Lethe-DEM在\({5000}\le n_\mathrm{p}/n_\mathrm{c} \le {15{,}000}\)范围内可扩展性最佳。最后,我们证明了Lethe-DEM可以在320核上使用\(n_\mathrm{p}={4.3}\times 10^6\)模拟三维圆柱形筒仓进行大规模模拟。
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来源期刊
Computational Particle Mechanics
Computational Particle Mechanics Mathematics-Computational Mathematics
CiteScore
5.70
自引率
9.10%
发文量
75
期刊介绍: GENERAL OBJECTIVES: Computational Particle Mechanics (CPM) is a quarterly journal with the goal of publishing full-length original articles addressing the modeling and simulation of systems involving particles and particle methods. The goal is to enhance communication among researchers in the applied sciences who use "particles'''' in one form or another in their research. SPECIFIC OBJECTIVES: Particle-based materials and numerical methods have become wide-spread in the natural and applied sciences, engineering, biology. The term "particle methods/mechanics'''' has now come to imply several different things to researchers in the 21st century, including: (a) Particles as a physical unit in granular media, particulate flows, plasmas, swarms, etc., (b) Particles representing material phases in continua at the meso-, micro-and nano-scale and (c) Particles as a discretization unit in continua and discontinua in numerical methods such as Discrete Element Methods (DEM), Particle Finite Element Methods (PFEM), Molecular Dynamics (MD), and Smoothed Particle Hydrodynamics (SPH), to name a few.
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