Parallel Implementation for Phase-Field Simulation of Flow Effect on Dendritic Growth with GPU Acceleration

Parallel Implementation for Phase-Field Simulation of Flow Effect on Dendritic Growth with GPU Acceleration
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利用 GPU 加速并行实现流动对枝晶生长影响的相场模拟

DOI:
10.2320/matertrans.m2014269
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发表时间:
2014-12
影响因子:
1.2
通讯作者:
Xiao Rongzhen
Xiao Rongzhen
中科院分区:
材料科学4区
文献类型:
--
作者:
Zhu Changsheng;Jia Jinfang;Zhang Hong;Feng Li;Xiao Rongzhen

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将Sola算法与相场模型相结合,建立了Sola相场模型。随着计算网格的增加,实时仿真变得越来越困难。以纯SCN为例,在GPU上通过CUDA编程实现了流动条件下凝固组织演化过程的加速。介绍了太阳相场模型的GPU实现。还评估了使用具有不同存储器的单个NVIDIA GeForce GTX 780 GPU在流动下模拟树枝状生长的加速结果。实验结果表明,采用共享内存的GPU计算获得了最佳的加速效果,对于2048 © 2048网格大小,其计算速度是单个CPU核上的56.16倍。此外,GPU上的模拟结果与CPU上的模拟结果吻合较好,表明了GPU加速相场模拟的可靠性。[doi:10.2320/matertrans.M2014269]
A Sola-phase field model combined Sola algorithm with phase-field model is established. It is difficult to implement real-time simulation as the computational grids increase. Taking pure SCN for example, the solidification microstructure evolution process in the presence of flow has been accelerated on a GPU with CUDA programming. The GPU implementation of the Sola-phase field model is introduced in this paper. The acceleration results of the dendritic growth simulation under flow by using a single NVIDIA GeForece GTX780 GPU with different memories are also evaluated. The results show that the GPU computation with the shared memory achieves the best acceleration effect, which is 56.16 times faster than that on a single CPU core for 2048 © 2048 grid size. In addition, the simulation results on GPU tally well with that on CPU, which indicates the reliability of GPU-accelerated phase-field simulation. [doi:10.2320/matertrans.M2014269]
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