A fast GPU Monte Carlo radiative heat transfer implementation for coupling with direct numerical simulation

S. Silvestri, R. Pecnik
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引用次数: 8

Abstract

We implemented a fast Reciprocal Monte Carlo algorithm to accurately solve radiative heat transfer in turbulent flows of non-grey participating media that can be coupled to fully resolved turbulent flows, namely to Direct Numerical Simulation (DNS). The spectrally varying absorption coefficient is treated in a narrow-band fashion with a correlated-k distribution. The implementation is verified with analytical solutions and validated with results from literature and line-by-line Monte Carlo computations. The method is implemented on GPU with a thorough attention to memory transfer and computational efficiency. The bottlenecks that dominate the computational expenses are addressed, and several techniques are proposed to optimize the GPU execution. By implementing the proposed algorithmic accelerations, while maintaining the same accuracy, a speed-up of up to 3 orders of magnitude can be achieved.

用于直接数值模拟耦合的快速GPU蒙特卡罗辐射传热实现
我们实现了一种快速的倒数蒙特卡罗算法,以精确求解非灰色参与介质湍流中的辐射传热,该非灰色参与媒体可以与完全解析的湍流相耦合,即直接数值模拟(DNS)。光谱变化的吸收系数以具有相关d-k分布的窄带方式进行处理。该实现通过分析解进行了验证,并通过文献和逐行蒙特卡罗计算的结果进行了验证。该方法在GPU上实现,充分考虑了内存传输和计算效率。解决了影响计算开销的瓶颈,并提出了几种优化GPU执行的技术。通过实现所提出的算法加速度,同时保持相同的精度,可以实现高达3个数量级的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Computational Physics: X
Journal of Computational Physics: X Physics and Astronomy-Physics and Astronomy (miscellaneous)
CiteScore
6.10
自引率
0.00%
发文量
7
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