OpenMP并行算法在卫星重力场模型反演中的应用

利用卫星重力数据反演地球重力场需要解决重力场模型的高效计算问题。分析了最小二乘直接法求解重力场模型涉及的密集型计算任务,基于OpenMP实现了卫星重力场模型直接求解的并行算法。利用30天、5秒采样间隔的沿轨扰动位T和径向扰动重力梯度Tr数据,分别反演了60阶次的卫星重力场模型,计算结果表明,OpenMP并行算法能够有效提高直接法求解卫星重力场模型的计算效率,并具有很好的稳定性。     

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基于3D-FSM的预紧力端锚数值模拟及其多核并行化研究

在对传统锚杆荷载传递机制分析的基础上,提出了一种考虑托板、锚杆与岩体相互作用的数值模拟方法：通过Kelvin基本解计算出锚杆集中力对围岩的影响,同时就锚杆自由段与相应岩体两端点的位移差相等建立位移方程,结合先前开发的3D-FSM数值模拟系统中的表面受力平衡方程进行联立求解,利用所得结果可以计算域内任意点的应力及位移变化,形成完整的预紧力端锚边界元数值模拟系统。通过与Flac3D系统模拟对比,验证了该系统的可靠性。为提高运算效率,对该系统进行基于OpenMP的多核并行化改进,给出了改进的基本思路和加速比对比图。由于边界元本身具有建模简单、计算区域大、计算精度高等优点,因此,这种模拟方法有很大的应用价值。     

A strategy for raster-based geocomputation under different parallel computing platforms

The demand for parallel geocomputation based on raster data is constantly increasing with the increase of the volume of raster data for applications and the complexity of geocomputation processing. The difficulty of parallel programming and the poor portability of parallel programs between different parallel computing platforms greatly limit the development and application of parallel raster-based geocomputation algorithms. A strategy that hides the parallel details from the developer of raster-based geocomputation algorithms provides a promising way towards solving this problem. However, existing parallel raster-based libraries cannot solve the problem of the poor portability of parallel programs. This paper presents such a strategy to overcome the poor portability, along with a set of parallel raster-based geocomputation operators (PaRGO) designed and implemented under this strategy. The developed operators are compatible with three popular types of parallel computing platforms: graphics processing unit supported by compute unified device architecture, Beowulf cluster supported by message passing interface (MPI), and symmetrical multiprocessing cluster supported by MPI and open multiprocessing, which make the details of the parallel programming and the parallel hardware architecture transparent to users. By using PaRGO in a style similar to sequential program coding, geocomputation developers can quickly develop parallel raster-based geocomputation algorithms compatible with three popular parallel computing platforms. Practical applications in implementing two algorithms for digital terrain analysis show the effectiveness of PaRGO.