INM RAS-MSU地表模型中的河流路径:数值方案与混合超级计算机上的并行实现

V. Stepanenko
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引用次数: 0

摘要

陆面模式(LSM)是任何数值天气预报系统或地球系统模式的必要单元。本文提出了一种新版本的INM RAS-MSU陆面模型,该模型将河流水动力和热力学方案嵌入到MPI和OpenMP并行执行框架中。在东欧地区进行了分辨率为0的数值实验。5◦× 0;5◦1 ~ 144 MPI核的土壤模型并行效率为0.52 ~ 0.79,受海洋面积的存在和土柱间计算负荷不平衡的限制。在MPI水平上,河流模型的加速由区域内最大流域的大小决定。在OpenMP层面上,基于河流网络的分形特性,大型河流流域模拟的加速潜力与使用的线程数接近。数值实验结果表明,在粗地表模式分辨率下,河道阶数的降低阻碍了这种加速,因此在4-6阶时,伏尔加河流域的最佳加速是前者的2.5-3倍。预计该性能将随着LSM空间分辨率的细化而提高。本文提出了一种新的INM陆地模型,将河流水动力和热力学模型嵌入到并行执行框架中,采用两级并行性:第一级是基于mpi的河流流域独立处理,第二级是使用OpenMP技术对相同Strahler阶的河流进行并行模拟。在东欧地区进行了分辨率为0的数值实验。5◦× 0;5◦土壤模型的MPI实现基于传统的模型域均匀经纬度分解,继承了大气模型。土壤模型在1 ~ 144核处的并行效率为0.52 ~ 0.79,受海洋面积的存在、积雪的存在和土壤剖面推进所需的地表温度迭代次数导致的土柱间计算负荷不平衡等因素的限制。在MPI水平上,河流模型的加速(不超过4倍)是由域内最大的河流流域(伏尔加河)的大小决定的,而在OpenMP水平上,大型河流流域模拟的加速潜力被证明与所使用的线程数接近。在我们的数值实验中,由于在粗地表模型分辨率下对河流顺序的低估,阻碍了openmp级别的加速(伏尔加盆地的推荐性能为4-6线程,加速为2.5-3倍)。
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River Routing in the INM RAS-MSU Land Surface Model: Numerical Scheme and Parallel Implementation on Hybrid Supercomputers
The land surface model (LSM) is a necessary compartment of any numerical weather forecast system or the Earth system model. This paper presents a new version of the INM RAS-MSU land surface model where the river hydrodynamic and thermodynamic scheme is embedded into the parallel execution framework using MPI and OpenMP. Numerical experiments have been performed for the East European domain with resolution 0 . 5 ◦ × 0 . 5 ◦ . The soil model parallel efficiency at 1–144 MPI cores was 0.52–0.79 and limited by the presence of ocean area, and by imbalance of computational load between soil columns. The acceleration of the river model at MPI level was defined by the size of the largest river basin in the domain. At the OpenMP level, the potential for acceleration of large river basin simulation is shown to be close to number of threads used, based on fractal properties of the river networks. This acceleration was hindered in our numerical experiments by the reduced river orders at the coarse land surface model resolution, so that the optimal speedup for the Volga river basin was 2.5–3 times attained at 4–6 threads. This performance is projected to improve with refinement of the LSM spatial resolution. This paper presents a new version of the INM land where the river hydrodynamic and thermodynamic model is embedded into the parallel execution framework using two levels of parallelism: the first is MPI-based indepedent processing of river basins, and the second uses OpenMP technique to parallelize the simulation of rivers of the same Strahler order. Numerical experiments have been performed for the East European domain with resolution 0 . 5 ◦ × 0 . 5 ◦ . The MPI implementation of the soil model is based on conventional even longitude-latitude decomposition of the model domain, inherited from the atmospheric model. The soil model parallel efficiency at 1–144 cores was shown to be 0.52–0.79 and limited by the presence of ocean area, and by imbalance of computational load between soil columns depending on the presence of snow cover and number of iterations for the surface temperature needed to advance the soil profiles. The acceleration of the river model at MPI level (not exceeding 4 times) is defined by the size of the largest river basin in the domain (Volga), whereas at OpenMP level the potential for acceleration of large river basin simulation is shown to be close to number of threads used. OpenMP-level speedup was hindered in our numerical experiments by the underestimation of river orders at coarse land surface model resolution (recommended performance for the Volga basin attained at 4–6 threads with 2.5–3 times acceleration).
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