gpu上计算高阶维里系数的混合精度模型

Chao Feng, A. Schultz, V. Chaudhary, D. Kofke
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引用次数: 0

摘要

维里状态方程(VEOS)是热力学压力相对于理想气体参考的密度展开式。它的系数可以从分子模型中计算出来,但在更高的阶上计算会变得更加昂贵。本文利用GPU,采用Mayer Sampling Monte Carlo (MSMC)方法和Wheatley算法计算Lennard-Jones (LJ)势模型的第8、9和10维里系数。提出了两种混合精度模型,以克服当前gpu潜在的精度限制,同时保持性能优势。在最新的开普勒架构GPU Tesla K40上,这些计算的平均加速达到了20到40。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mixed-precision models for calculation of high-order virial coefficients on GPUs
The virial equation of state (VEOS) is a density expansion of the thermodynamic pressure with respect to an ideal-gas reference. Its coefficients can be computed from a molecular model, and become more expensive to calculate at higher order. In this paper, we use GPU to calculate the 8th, 9th and 10th virial coefficients of the Lennard-Jones (LJ) potential model by the Mayer Sampling Monte Carlo (MSMC) method and Wheatley's algorithm. Two mixed-precision models are proposed to overcome a potential precision limitation of current GPUs while maintaining the performance benefit. On the latest Kepler architecture GPU Tesla K40, an average speedup of 20 to 40 is achieved for these calculations.
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