A parallel computing approach to viewshed analysis of large terrain data using graphics processing units

Viewshed analysis, often supported by geographic information system, is widely used in many application domains. However, as terrain data continue to become increasingly large and available at high resolutions, data-intensive viewshed analysis poses significant computational challenges. General-purpose computation on graphics processing units (GPUs) provides a promising means to address such challenges. This article describes a parallel computing approach to data-intensive viewshed analysis of large terrain data using GPUs. Our approach exploits the high-bandwidth memory of GPUs and the parallelism of massive spatial data to enable memory-intensive and computation-intensive tasks while central processing units are used to achieve efficient input/output (I/O) management. Furthermore, a two-level spatial domain decomposition strategy has been developed to mitigate a performance bottleneck caused by data transfer in the memory hierarchy of GPU-based architecture. Computational experiments were designed to evaluate computational performance of the approach. The experiments demonstrate significant performance improvement over a well-known sequential computing method, and an enhanced ability of analyzing sizable datasets that the sequential computing method cannot handle.     

An improved algorithm to compute circular functions of Poisson series

The efficiency in the computation of circular functions, such as cos(u) or sin(u), where u is a Poisson series, is important to derive accurate solutions of many problems of Celestial Mechanics, for instance, the orbital or rotational perturbed motion of natural or artificial bodies, since expansions in terms of Legendre functions and multiple Fourier series appear almost everywhere. Therefore, it is worth searching for alternative algorithms with lower computational cost. In this article, we propose a method based on the idea of elimination, which was originally applied to solve numerical problems, mainly in the case of matrix functions. Our comparisons with the traditional Taylor expansion prove that this new method can be more efficient when applied to compute the sine and cosine of a Poisson series.     

基于中间件技术的网格GIS体系结构

在网格计算技术和空间信息网格 (SIG)架构下 ,本文提出基于中间件技术的网格 GIS的体系结构 ,探索其将空间数据、分析软件和计算环境作为共享资源的新一代 GIS的组织体系与运行模式.     

基于PDA的个人移动导航系统的设计

简略分析了嵌入式地理信息系统的研究现状、技术背景、特点及应用，提出了基于PDA的个人移动导航系统的逻辑设计框架、实现原理及应用模式。     

基于流固耦合统一计算框架的三维大规模海域场地地震反应分析?以东京湾为例

海域场地地震响应分析是确定海洋工程结构抗震设计地震动输入的重要环节。然而,针对海水、饱和土、基岩之间的流固耦合分析,目前一般通过对3种介质方程进行离散,然后整体求解或分区耦合求解的方式进行,过程复杂而低效。因此,大规模海域场地地震反应分析仍是一个挑战性问题。本文基于流固耦合统一计算框架求解海域近场波动问题,采用透射边界模拟无限域,通过将海水和基岩视为孔隙率分别等于1和0的广义饱和多孔介质,使得海水、饱和土、基岩之间的相互耦合可在统一计算框架中实现,避免不同介质求解器之间的数据交换。采用集中质量显式有限元并行计算,不同进程之间采用MPI进行数据交换,提高计算效率;采用逐元技术,按单元类别存储单元刚度,大大节省了内存,便于大规模计算。通过自编程,输入界面高程数据和材料参数,实现建模-自由场-三维地震动模拟全流程自动化。以东京湾为例,使用该方法和程序在超级计算机上模拟SV波垂直入射时的地震响应,证实了该方法用于三维大规模海域地震波场模拟的高效性和可行性。     

高速铁路轨道中长波平顺性参数计算方法

高速铁路轨道中长波平顺性参数的计算方法是高速铁路轨道精测与精调的核心技术,现有的中长波平顺性参数计算多采用以轨道点法向偏移量代替矢距差(即设计矢距与实测矢距之差)的近似计算方法。由于该算法忽略实测弦线端点偏差的影响,导致轨道实测轨向(高低)计算结果与严密算法计算结果存在一定的偏差。鉴于现有近似算法存在准确度低的缺点,文中在现有近似算法的基础上提出一种改进算法,并通过对轨道实测坐标数据的计算和对比,验证改进算法的可行性和准确性,并提高高铁轨道中长波平顺性参数计算结果的准确度,可为高速铁路轨道精测与精调提供参考。     

地下溶洞不同枯盈状态下的地震响应差异模拟研究

针对地下溶洞不同枯盈状态下的地震波响应差异问题,选择三种枯盈状态下的溶洞模型进行了一项数值模拟实验。先从弹性波方程理论出发,利用有限差分离散近似,再运用CUDA编程平台进行GPU并行计算,模拟了三种枯盈状态下的溶洞地震波响应。模拟结果表明,P-P波的能量随着溶洞含水量增多而减少,而溶洞尖灭点的绕射现象随着溶洞含水量增多而变得更加明显。     

验收测量建筑面积计算若干问题探讨

对验收测量建筑面积计算时遇到的层高超高、坡地建筑、装饰层厚度、装饰性结构、凹阳台等问题进行探讨,确定合理的建筑面积计算方法。     

地铁暗挖法施工中降水引起地面沉降问题的探讨

近年来,地铁暗挖施工中辅助降水措施取得了很大成功,但由降水引起的地面沉降,其成因、危害性、如何避免和控制是十分重要的问题。本文结合北京地铁7号线双井站工程实际经验,对降水沉降问题进行探讨和总结。车站主体暗挖施工过程中,监测降水沉降值仅4.0mm,证明双井站降水方案和沉降控制措施是合理的。     

网格GIS研究

本文概述了网格(GRID)出现的技术背景、网格(GRID)发展现状及其对地理信息服务的影响。重点阐述了GRIDGIS的关键技术。