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首页> 外文期刊>Journal of Computational Physics >Accelerating solidification process simulation for large-sized system of liquid metal atoms using GPU with CUDA
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Accelerating solidification process simulation for large-sized system of liquid metal atoms using GPU with CUDA

机译：使用带有CUDA的GPU加速大型液态金属原子系统的凝固过程仿真

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Molecular dynamics simulation is a powerful tool to simulate and analyze complex physical processes and phenomena at atomic characteristic for predicting the natural time-evolution of a system of atoms. Precise simulation of physical processes has strong requirements both in the simulation size and computing timescale. Therefore, finding available computing resources is crucial to accelerate computation. However, a tremendous computational resource (GPGPU) are recently being utilized for general purpose computing due to its high performance of floating-point arithmetic operation, wide memory bandwidth and enhanced programmability. As for the most time-consuming component in MD simulation calculation during the case of studying liquid metal solidification processes, this paper presents a fine-grained spatial decomposition method to accelerate the computation of update of neighbor lists and interaction force calculation by take advantage of modern graphics processors units (GPU), enlarging the scale of the simulation system to a simulation system involving 10 000000 atoms. In addition, a number of evaluations and tests, ranging from executions on different precision enabled-CUDA versions, over various types of GPU (NVIDIA 480GTX, 580GTX and M2050) to CPU clusters with different number of CPU cores are discussed. The experimental results demonstrate that GPU-based calculations are typically 9 － 11 times faster than the corresponding sequential execution and approximately 1.5 ~ 2 times faster than 16 CPU cores clusters implementations. On the basis of the simulated results, the comparisons between the theoretical results and the experimental ones are executed, and the good agreement between the two and more complete and larger cluster structures in the actual macroscopic materials are observed. Moreover, different nucleation and evolution mechanism of nano-clusters and nano-crystals formed in the processes of metal solidification is observed with large-sized system.
机译：分子动力学模拟是一种功能强大的工具，可以模拟和分析原子特性下的复杂物理过程和现象，以预测原子系统的自然时间演化。物理过程的精确仿真在仿真大小和计算时间尺度上都有强烈的要求。因此，找到可用的计算资源对于加速计算至关重要。但是，由于其高性能的浮点算术运算，宽的存储带宽和增强的可编程性，最近将大量的计算资源（GPGPU）用于通用计算。针对在研究液态金属凝固过程中MD模拟计算中最耗时的组件，本文提出了一种细粒度的空间分解方法，以利用现代方法来加速邻居列表更新的计算和相互作用力的计算。图形处理器单元（GPU），将模拟系统的规模扩大到涉及10 000000个原子的模拟系统。此外，还讨论了许多评估和测试，从在各种类型的GPU（NVIDIA 480GTX，580GTX和M2050）上对不同精度启用CUDA版本的执行，到具有不同CPU内核数量的CPU群集，进行了讨论。实验结果表明，基于GPU的计算通常比相应的顺序执行快9 － 11倍，比16个CPU内核集群实现快约1.5〜2倍。在模拟结果的基础上，对理论结果与实验结果进行了比较，并在实际的宏观材料中观察到了两个甚至更完整，更大的团簇结构之间的良好一致性。此外，在大型系统中，观察到在金属凝固过程中形成的纳米团簇和纳米晶体的不同成核和演化机理。

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