A Novel Parallelisation Scheme for DEM on Distributed Memory Computers

  • De Staercke, Emilian (Ecole centrale de Lyon - LTDS)
  • Nougiuer-Lehon, Cécile (Ecole centrale de Lyon - LTDS)
  • Froiio, Francesco (Ecole centrale de Lyon - LTDS)

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Several strategies have been proposed for high performance computing with DEM. Yet, quite few works have been published on this topic (e.g., [1-3]), compared to the extensive use of DE simulations as a modelling tool in research and industry. This is however not surprising, since granular media at the grain scale appear as highly evolutive and disordered systems, which makes effective parallelisation a challenging task. We present an approach which exploits an inherent limitation of DE simulations, as the opportunity for an efficient and flexible parallel implementation on distributed memory computers. Namely, the “numerical sound speed” set by the representative particle diameter and the time step defines an upper bound for the celerity at which perturbations can propagate across the discrete medium. We show how this numerical artefact (of negligible importance for most applications) can be turned into an original criterion of spatial domain decomposition, which leads to a DEM-suited parallelisation scheme. We present our approach through its actual implementation into the DEM’ocritus code [4,5]. We analyse its performance through benchmarks and parametric analyses of biaxial tests, on assemblies of up to 15 million circular particles. REFERENCES [1] A. Maknickas, A. Kaceniauskas, R. Kacianauskas, R. Balevicius, A. Dziugys, “Parallel DEM software for simulation of granular media”, Informatica, 17, 207–224 (2006). [2] E.H. Park, V. Kindratenko, Y.M.A. Hashash, Y. M. A., “Shared memory parallelization for high-fidelity large-scale 3D polyhedral particle simulations”, Comput Geotech, 137, 104008 (2021). [3] B. Yan and R.A. Regueiro, “Comparison between pure MPI and hybrid MPI-OpenMP parallelism for Discrete Element Method (DEM) of ellipsoidal and poly-ellipsoidal particles”, Comp Particle Mech, 6, 271–295 (2019). [4] D.K. Tran, N. Prime, F. Froiio, C. Callari, E. Vincens, “Numerical modelling of backward front propagation in piping erosion by DEM-LBM coupling”, Eur. J. Environ. Civ., 21, 960–987 (2017). [5] F. Froiio, C. Callari, A. Rotunno, “A numerical experiment of backward erosion piping: kinematics and micromechanics”, Meccanica, 54, 2099–2117 (2019).