Monte Carlo uncertainty analysis, model calibration and optimization applications in hydrology, usually involve a very large number of forward transient model solutions, often resulting in computational bottlenecks. Parallel processing can significantly reduce overall simulation time, benefiting from the architecture of modern computers. This work investigates system performance using two realistic flow and transport modeling scenarios, applied to various modeling hardware, to provide information on the expected performance of parallel simulations and inform investment decisions. We investigate how performance, measured in terms of speedup and efficiency, changes with increasing number of parallel processes. We conclude that the maximum performance achieved by parallelization can range from 40% to 100% of the theoretical limit, with the lower increases associated with multi‐CPU servers. The number of parallel processes required to maximize performance is application dependent, and in contrast to common practice, often needs to be significantly larger than the total number of system CPU cores. Further testing is required to better understand how the physical problem being simulated affects the optimal number of parallel processes needed. Finally, when laptops are considered for modeling applications, careful consideration should be given not only to the specifications but also to the intended use designated by the manufacturer.

中文翻译：

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地下水文学中的并行仿真：评估建模计算机的性能。

蒙特卡洛不确定性分析，水文模型校准和优化应用通常涉及大量的正向瞬态模型解，通常会导致计算瓶颈。得益于现代计算机的架构，并行处理可以显着减少总体仿真时间。这项工作使用两种现实的流程和运输建模方案来研究系统性能，这些方案应用于各种建模硬件，以提供有关并行仿真的预期性能的信息并为投资决策提供依据。我们研究了根据加速和效率衡量的性能如何随着并行流程数量的增加而变化。我们得出结论，通过并行化实现的最大性能范围可以是理论极限的40％至100％，与多CPU服务器相关的增长较低。最大化性能所需的并行进程数取决于应用程序，与通常的做法相反，通常需要大大大于系统CPU内核的总数。需要进一步测试以更好地了解所模拟的物理问题如何影响所需的并行处理的最佳数量。最后，在考虑将笔记本电脑用于建模应用程序时，不仅应仔细考虑规格，还应仔细考虑制造商指定的预期用途。需要进一步测试以更好地了解所模拟的物理问题如何影响所需的并行处理的最佳数量。最后，在考虑将笔记本电脑用于建模应用程序时，不仅应仔细考虑规格，还应仔细考虑制造商指定的预期用途。需要进一步测试以更好地了解所模拟的物理问题如何影响所需的并行处理的最佳数量。最后，在考虑将笔记本电脑用于建模应用程序时，不仅应仔细考虑规格，还应仔细考虑制造商指定的预期用途。