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

TL;DR

Lethe-DEM is an open-source parallel discrete element method software with load balancing that significantly improves computational efficiency for large-scale granular material simulations, validated through various tests and scalability analyses.

Contribution

We introduce Lethe-DEM, a novel open-source parallel DEM software with load balancing, enabling efficient large-scale granular material simulations.

Findings

Load balancing increases parallel efficiency by 25-70%.

Lethe-DEM demonstrates excellent scalability up to 15000 particles per process.

Large-scale simulation of 4.3 million particles on 320 cores is feasible.

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 non-linearly $O(n_p\log(n_p))$ -- $O(n_p^2)$ depending on the algorithm) with the number of particles ($n_p$). 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 $1 \leq n_c \leq 192$ and $32 \leq n_c \leq 320$ 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 $5000 \leq n_p/n_c \leq 15000$. Finally, we demonstrate that large scale simulations can be carried out with Lethe-DEM using the simulation of a three-dimensional cylindrical silo with $n_p=4.3 \times 10^6$ on 320 cores.