Abstract
In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.
Highlights
In metal materials, the dendritic structure is the most common solidification microstructure of casting forming process
The algorithm is optimized by changing MPI communication model and changing multi-GPU computing model structure respectively, and the effectiveness of the two optimization schemes is verified by experiments
In order to further improve the efficiency of calculation model of multi-GPU, some improvement is done to the basic multi-GPU+MPI model, to realize the overlap of MPI communication and GPU computing, eventually improve computational efficiency of multi-GPU calculation model
Summary
The dendritic structure is the most common solidification microstructure of casting forming process. George[8] solved binary alloy three-dimensional phase-field model by using MPI. Shimokawabe[9] simulated the evolution process of binary alloy dendritic solidification, in TSUBAME 2.0 super computer with Tesla M2050 GPUs. Changsheng Zhu[10] studied dendritic growth in three-dimensional phase-field, by using single GPU. Yamanaka[11] implemented the acceleration of binary alloy dendritic solidification on NVIDIA TESLA C1060 GPU by using the phase-field method to calculate a grid size of 5763, and achieved 100 times speedup. Under the platform of MPI+CUDA hybrid programming, GPU cluster is used to accelerate the binary alloy dendritic growth on three-dimensional phase-field model. The algorithm is optimized by changing MPI communication model and changing multi-GPU computing model structure respectively, and the effectiveness of the two optimization schemes is verified by experiments
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