Parallelization of the flow-path network model using a particle-set strategy

High-performance simulation of flow dynamics remains a major challenge in the use of physical-based, fully distributed hydrologic models. Parallel computing has been widely used to overcome efficiency limitation by partitioning a basin into sub-basins and executing calculations among multiple processors. However, existing partition-based parallelization strategies are still hampered by the dependency between inter-connected sub-basins. This study proposed a particle-set strategy to parallelize the flow-path network (FPN) model for achieving higher performance in the simulation of flow dynamics. The FPN model replaced the hydrological calculations on sub-basins with the movements of water packages along the upstream and downstream flow paths. Unlike previous partition-based task decomposition approaches, the proposed particle-set strategy decomposes the computational workload by randomly allocating runoff particles to concurrent computing processors. Simulation experiments of the flow routing process were undertaken to validate the developed particle-set FPN model. The outcomes of hourly outlet discharges were compared with field gauged records, and up to 128 computing processors were tested to explore its speedup capability in parallel computing. The experimental results showed that the proposed framework can achieve similar prediction accuracy and parallel efficiency to that of the Triangulated Irregular Network (TIN)-based Real-Time Integrated Basin Simulator (tRIBS).     

A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.     

武汉区域气象中心数值预报业务并行计算机系统

对武汉区域气象中心并行计算机系统进行了详细地介绍，分析了并行计算机体系结构、网络和存储系统特点；给出了在并行计算机SP上实现数值预报业务并行化的部分结果；对数值预报模式在串、并行编程环境下的结果进行了分析比较。     

大鹏湾潮流数值计算

应用分步杂交方法建立了大鹏湾边界潮流数值模型，并对其进行了模拟计算，重现了该区域潮波及潮流的分布规律，并根据实测资料对其进行了验证，从而可系统地了解这一海区的潮波系统及潮流场等海洋要素的分布情况。     

太湖表面定振波的数值计算和最大熵谱分析

利用水动力学方程对太湖表面的定振波进行计算，算得定振波周期约为４５２ｍｉｎ，另外，利用１９９２年８月２９－３１日在太湖西山观测到的水位资料，采用最大熵谱法，分析太湖表面的定振波，得周期值约为４５０ｍｉｎ。计算和分析的周期值基本吻合，取熵谱分析结果得太湖表面的单节点定振波周期值为４５０ｍｉｎ。     

北部湾三维潮流场数值研究(英文)

本文对北部湾三维潮波进行了数值研究,并将所得结果与现有观测资料作了比较。通过比较发现两者相当一致。文中还绘制了M_2和K_1分潮的同潮图,并对其作了讨论。可以断定,北部湾的日潮优势是由日潮共振所引起的。M_2和K_1分潮流的水平分布表明,强流区位于它们各自的蜕化无潮点附近。还讨论了分潮流的铅直结构,可以看出这种结构十分接近实际分潮流场的特征。     

分潮波模型多资料数值计算方法研究 Ⅱ.有限差分最小二乘方法

对含多资料的分潮波模型的超定问题进行探讨，建立一种有限差分—最小二乘方法，该方法使得岸边资料直接进入了计算方程，并保证岸界法向流速为零条件。通过对渤海的四大分潮的试算，证实本方法可行。     

基于MPI的LAGFD-WAM海浪数值模式并行算法研究

在LAGFD-WAM海浪串行数值模式基础上,利用MPI信息传递机制实现其并行化。通过对模拟区域合理划分,对数据采取分块加载,实现了各个节点的负载平衡;通过对算法的改进实现了粗粒度计算,大幅度减少了通信量,从而提高了程序的执行效率。对串行计算和并行计算的效率比较表明,本文建立的方法能够得到较高的加速比。对全球海浪模式,加速比和CPU数目大致呈线性关系。对高分辨率的区域海浪模式,在128 CPU条件下加速比可以达到91.9。     

受陆岸影响浅水区台风风浪的计算方案

在我国港口工程技术规范的波浪成长理论基础上，考虑到台风波浪的基本特点、等效水深的概念、浅水区波浪的折射、不规则波的能量分布特性、受陆岸和岛屿影响角度范围内的有效能量风区长度等因素，提出了受陆岸、岛屿影响浅水区（包括海湾区）台风风浪的计算方案。本方案只需台风中心位置、中心气压和计算点于各方位的风区长度（受陆岸影响部分）等资料，便可快速地得到计算点的波浪要素。经实测资料验证，效果良好。