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Acceleration of phase-field lattice Boltzmann simulation of dendrite growth with thermosolutal convection by the multi-GPUs parallel computation with multiple mesh and time step method

机译:用多GPU并行计算与多网格和时间步骤方法的多GPU并行计算枝晶晶格Boltzmann模拟枝晶叶片模拟

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Thermosolutal convection inevitably occurs during the solidification of alloys owing to the nonuniform distribution of temperature and/or solute concentration, and this can drastically alter the resulting solidification microstructures. In this study, we present a large-scale simulation scheme for the phase-field lattice Boltzmann model, which can express dendrite growth upon considering the solute, heat transport, and liquid flow. A multiple mesh and time step method was employed to reduce computational costs, where different mesh sizes and time steps are used to solve the phase-field equation, the advection-diffusion equations of heat and solute, and the lattice Boltzmann equations for fluid flow. Furthermore, we implemented parallel computations using multiple graphics processing units (GPUs) to accelerate the large-scale simulation. Through the application of the multiple mesh and time step method, the computation was accelerated by approximately one hundred times compared to the case using a constant mesh and time step for all equations. Moreover, we confirmed that the developed parallel-GPU computation combined with the multiple mesh and time step method could achieve good acceleration and scaling through increasing the number of GPUs. We also confirmed that the developed method could simulate multiple dendrite growth with thermosolutal convection.
机译:由于温度和/或溶质浓度的不均匀分布,在合金的凝固过程中,热沉降型对流不可避免地发生,这可以大大改变所得的凝固微观结构。在这项研究中,我们为基位晶格Boltzmann模型提出了大规模的模拟方案,其可以在考虑溶质,热传输和液体流动时表达枝晶生长。采用多网格和时间步长方法来降低计算成本,其中不同的网格尺寸和时间步长用于解决相位场方程,热和溶质的平坦扩散方程,以及用于流体流动的格子Boltzmann方程。此外,我们使用多个图形处理单元(GPU)来实现并行计算来加速大规模仿真。通过应用多网和时间步长方法,与所有等式的恒定网格和时间步骤相比,计算加速了大约一百次。此外,我们证实,通过增加GPU的数量来实现与多网格和时间步长方法相结合的开发的并行GPU计算可以实现良好的加速和缩放。我们还证实,开发的方法可以通过热沉降对流来模拟多个树突生长。

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