Iterative load-balancing method with multigrid level relaxation for particle simulation with short-range interactions

Furuichi, Mikito; Nishiura, Daisuke

doi:10.1016/j.cpc.2017.05.015

Cited by 24 publications

(14 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While it is known that the geometry of granules plays an important role in the physics of granular assemblies [23,26,27], round particles are widely used for simplicity. This study utilizes a DEM code using round particles, which has proven parallel efficiency on several supercomputer systems such as Earth Simulator and K computer, with a capability of simulating particles on the order of billions [24,25].…”

Section: Discrete Element Methodsmentioning

confidence: 99%

“…To fully capture such a dynamic process in three dimensions, a 3D DEM simulation is needed. Although the concept of DEM is very simple and straightforward [22,23], a large-scale DEM simulations is non-trivial [24]. In this study, we applied a DEM code which has been parallelized on supercomputers [24] and been successfully applied for a real-scale numerical sandbox experiment [25] to understand the stress states of accretionary prisms formed by sediments.…”

Section: Introductionmentioning

confidence: 99%

“…Although the concept of DEM is very simple and straightforward [22,23], a large-scale DEM simulations is non-trivial [24]. In this study, we applied a DEM code which has been parallelized on supercomputers [24] and been successfully applied for a real-scale numerical sandbox experiment [25] to understand the stress states of accretionary prisms formed by sediments. By utilizing this code, DEPTH (DEM based Parallel mulTi-pHysics simulator), in this study, we carried out 3D DEM simulations with particles of the order of millions to investigate the effect of particle size on the the aforementioned two quantities (the torque on the mixer head and the maximal increase of surface height) and the qualitative indicator (surface mixing patterns revealed by color sand).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Discrete Element Simulation and Validation of a Mixing Process of Granular Materials

2020

Self Cite

View full text Add to dashboard Cite

The mixing processes of granular materials have gained wide interest among various fields of science and engineering. In this study, our focus is a mixing process for offshore mining. We conducted numerical simulations using the discrete element method (DEM) in comparison with experimental works on mixing color sand. Careful calibration of initial packing densities has been performed for the simulations. For validation, the steady-state torques on the mixer head, the maximal increase of surface height after mixing, and the surface mixing patterns have been compared. The effect of particle size on the simulation results has been clarified. With the particle size approaching the actual particle size, consistent torques and mixing patterns indicate the capability of the DEM code for studying the particular mixing process, while the results for the maximal increase of surface height should be interpreted with more caution.

show abstract

Section: Discrete Element Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Discrete Element Simulation and Validation of a Mixing Process of Granular Materials

2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…Thus, it is essential to use parallel computing; nevertheless, the efficient parallel implementation of DEM remains a challenge. We developed new DEM codes designed for HPC systems to overcome the degradation of parallel performance due to the load imbalance by utilizing an iterative dynamic load balancer 13 and overlapping communication techniques with space-filling curves. The details of the parallel implementation method are discussed in 14 .…”

Section: Methodsmentioning

confidence: 99%

“…To overcome the limitations of laboratory experiments, we performed the real-scale numerical simulations of sandbox experiments using the Discrete Element Method (DEM) in which each grain of sand is represented by a discrete particle (Fig. 1(b) and (c) ) 13 , 14 . This method allows one to monitor the motion of each sand particle and to visualize the interparticle stress e.g.…”

Section: Introductionmentioning

confidence: 99%

Arcuate stress state in accretionary prisms from real-scale numerical sandbox experiments

Furuichi

Nishiura

Kuwano

et al. 2018

Sci Rep

Self Cite

View full text Add to dashboard Cite

The stress states in accretionary prisms are important for understanding the building and releasing of seismic energy. Numerous researchers have conducted sandbox experiments as a scaled physical analog model to understand the formation of accretionary prisms. However, measuring stress states in laboratory sandbox experiments is still practically infeasible. Here we performed real-scale numerical sandbox experiments using the discrete element method to understand the 3D stress state in the accretionary prism. Despite the nearly uniform initial conditions, macro-scale undulations of faults, which are similar to those observed in the trenches of an accretionary prism, appear. We reveal that these undulations are caused by the formation of stress arches. We show that the mechanism behind the arch formation is the discontinuous change in the stress orientation during the rearrangement of the stress chain. Furthermore, analyses demonstrate that the in-situ stress orientation from borehole data can be a signal of either the regional direction of plate convergence or the local stress orientation associated with the stress arch. The results may greatly enhance the outcome of long term monitoring in areas, such as the Nankai Trough.

show abstract

Accurate load balancing accelerates Lagrangian simulation of water ages on distributed, multi-GPU platforms

Yang¹,

Maxwell²,

Valent³

2021

Preprint

View full text Add to dashboard Cite

Water age is a fundamental descriptor of source, storage, and mixing of water parcels in a watershed. The Lagrangian, particle tracking, approach is a powerful tool for physically-based modeling of water age distributions, but its application has been hampered since it is computationally demanding. In this study, we present a parallel approach for particle tracking simulations. This approach uses multi-GPU with MPI parallelism based on domain decomposition. An inherent challenge of distributed parallelization of Lagrangian approaches is the disparity in computational work or load imbalance (LIB) among different processing elements (PEs). Here, load balancing (LB) schemes were proposed to dynamically balance the distribution of particles across PEs during runtime. In the followed hillslope simulations, LIB was observed in all LB-disabled runs, e.g., with a load ratio of 423.62% by using 2-GPU in LW Shrub case. LB schemes then accurately balanced the load distribution and improved the parallel scaling. Additionally, the parallel approach showed excellent overall speedup: a 60-fold improvement using 4-GPU relative to the serial run. A regional scale application further demonstrated the LB performance. The parallel time used by 8-GPU without LB was 31.33% reduced after LB was activated. When increasing 8-GPU with LB to 16-GPU with LB, it showed parallel scalability by reducing the parallel time of ˜50%. This work shows how massively parallel computing can be applied to particle tracking in water age simulations. It also demonstrates the practical importance of load balancing in this context, which enables the large-scale simulations with an increased complexity of flow paths.

show abstract

Iterative load-balancing method with multigrid level relaxation for particle simulation with short-range interactions

Cited by 24 publications

References 36 publications

Discrete Element Simulation and Validation of a Mixing Process of Granular Materials

Discrete Element Simulation and Validation of a Mixing Process of Granular Materials

Arcuate stress state in accretionary prisms from real-scale numerical sandbox experiments

Accurate load balancing accelerates Lagrangian simulation of water ages on distributed, multi-GPU platforms

Contact Info

Product

Resources

About