Parallelization of a DEM code based on CPU-GPU heterogeneous architecture
Parallel Computational Fluid Dynamics: 25th International Conference, ParCFD …, 2014•Springer
Particulate flows are commonly encountered in both engineering and environmental
applications. The discrete element method (DEM) has attracted plentiful attentions since it
can predict the whole motion of the particulate flow by monitoring every single particle.
However the computational capability of the method relies strongly on the numerical scheme
as well as the hardware environment. In this study, a parallelization of a DEM based code
titled Trubal was implemented. Numerical simulations were carried out to show the benefits …
applications. The discrete element method (DEM) has attracted plentiful attentions since it
can predict the whole motion of the particulate flow by monitoring every single particle.
However the computational capability of the method relies strongly on the numerical scheme
as well as the hardware environment. In this study, a parallelization of a DEM based code
titled Trubal was implemented. Numerical simulations were carried out to show the benefits …
Abstract
Particulate flows are commonly encountered in both engineering and environmental applications. The discrete element method (DEM) has attracted plentiful attentions since it can predict the whole motion of the particulate flow by monitoring every single particle. However the computational capability of the method relies strongly on the numerical scheme as well as the hardware environment. In this study, a parallelization of a DEM based code titled Trubal was implemented. Numerical simulations were carried out to show the benefits of this research. It is shown that the final parallel code gave a substantial acceleration on the Trubal. By simulating 6,000 particles using a NVIDIA Tesla C2050 card together with Intel Core-Dual 2.93 GHz CPU, an average speedup of 4.69 in computational time was obtained.
Springer
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