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1.
Significant trends in the processing of geographical data require increasingly powerful software and hardware, consistent
with the exploitation of parallel computing. Despite recent progress in technology, exploiting parallel processing is still
difficult so that few applications have been developed in the environmental and geographical domains.
Key issues which must be addressed in the design of parallel geographical software are described with reference to designs
for three examples which use grid and raster data. The implications for parallel processing with vector-topological data are
then explored. The emphasis is upon MIMD architectures using strategies of decomposition into subareas, and upon the need
to facilitate development of parallel geographical applications by encapsulating the parallelism in a low-level layer of software,
forming a skeletal framework upon which application algorithms can be built. The parallel layer will support distribution
of datasets across the multiple processors, and the creation and collation of datasets from those processors. 相似文献
2.
《International Journal of Digital Earth》2013,6(4):383-403
Abstract Geospatial simulation models can help us understand the dynamic aspects of Digital Earth. To implement high-performance simulation models for complex geospatial problems, grid computing and cloud computing are two promising computational frameworks. This research compares the benefits and drawbacks of both in Web-based frameworks by testing a parallel Geographic Information System (GIS) simulation model (Schelling's residential segregation model). The parallel GIS simulation model was tested on XSEDE (a representative grid computing platform) and Amazon EC2 (a representative cloud computing platform). The test results demonstrate that cloud computing platforms can provide almost the same parallel computing capability as high-end grid computing frameworks. However, cloud computing resources are more accessible to individual scientists, easier to request and set up, and have more scalable software architecture for on-demand and dedicated Web services. These advantages may attract more geospatial scientists to utilize cloud computing for the development of Digital Earth simulation models in the future. 相似文献
3.
Geodetic VLBI correlation in software 总被引：1，自引：1，他引：0
Correlation algorithms for geodetic very long baseline interferometry (VLBI) can now be effectively implemented on parallel
computers of modest size. We have undertaken a detailed comparison of the output from a trusted geodetic correlator, one that
has supported global geodetic VLBI observations for many years, with the output of a software correlator implemented on a
small parallel computing cluster. We show that the correlator outputs agree closely, within expected error bounds, after accounting
for the differences in the adopted geometric delay models, and therefore that use of the software correlator is feasible for
geodetic VLBI processing, as a first step toward routine geodetic data processing. Recent developments in software correlation
for geodesy are discussed, including the possibility of real-time processing options. 相似文献
4.
An online spatial biodiversity model (SBM) for optimized and automated spatial modelling and analysis of geospatial data is proposed, which is based on web processing service (WPS) and web service orchestration (WSO) in parallel computing environment. The developed model integrates distributed geospatial data in geoscientific processing workflow to compute the algorithms of spatial landscape indices over the web using free and open source software. A case study for Uttarakhand state of India demonstrates the model outputs such as spatial biodiversity disturbance index (SBDI) and spatial biological richness index (SBRI). In order to optimize and automate, an interactive web interface is developed using participatory GIS approaches for implementing fuzzy AHP. In addition, sensitivity analysis and geosimulation experiments are also performed under distributed GIS environment. Results suggest that parallel algorithms in SBM execute faster than sequential algorithms and validation of SBRI with biological diversity shows significant correlation by indicating high R2 values. 相似文献
5.
随着卫星遥感技术的发展,需要快速地将卫星遥感图像数据转化为用户需要的信息,并行图像处理技术是解决“快速”的重要途径。并行程序的性能与计算机体系结构密切相关,不但取决于CPU,还与系统架构、指令结构、存储部件的存取速度等因素有关。一般意义上,提高并行程序的性能采用粗粒度并行,指令级优化(ILP)和存储优化等技术。作为尝试,本文讨论了在工业标准化机群上采用软件式共享存储系统做的并行影像匹配方法,以影像匹配算法为例子,讨论了如何在粗粒度并行、指令级优化(ILP)和存储优化三个方面提高图像处理的计算速度。 相似文献
6.
CGCS2000精化及其全球拓展需要采用最新的模型,处理长期积累的大型GNSS观测网数据,大型GNSS网联合、快速和协同解算是空间基准精化、维持与服务的重要技术方向。在大数据技术背景下,以并行计算、云计算为代表的高性能计算技术逐渐成为大规模数据处理的首选方法。针对海量、多源、异构GNSS数据在解算处理与平差分析等方面面临的挑战,阐述了大型GNSS观测网质量控制并行计算、非差模型并行解算、双差模型并行解算、高维模糊度并行搜索固定等方法。介绍了可同时处理上千个观测站的大型GNSS观测网并行计算软件GNSSer,开展了CGCS2000精化计算的试验与验证。构建了一套适合并行计算的大型GNSS观测网解算方法,实现了CGCS2000精化及其全球拓展的多节点协同并行计算的创新。 相似文献
7.
提出了一种共享内存环境下的干涉合成孔径声呐（interferometric synthetic aperture sonar，InSAS）复图像配准优化方法。首先在分析复图像配准算法各处理步骤计算特点和并行性的基础上，针对粗配准和精配准计算中大量的滑动窗口计算操作，根据相邻窗口数据之间的关系进行了计算方法优化设计；然后采用OpenMP指令对粗配准、精配准、复图像插值和干涉相位提取计算步骤进行了并行化设计和计算任务分配，以充分利用多核计算资源加速复图像配准过程；最后通过InSAS复图像的并行配准试验验证了所提方法的正确性和高效性。 相似文献
8.
多核处理器已成为当前通用计算机体系架构的主流,相应的多核并行计算技术及其应用引起了越来越多的重视,而传统的GNSS数据处理程序都是针对单处理器体系架构编写的。本文对当前多核环境下多时段或者多测站的GNSS数据处理所涉及的计算密集型任务并行算法进行研究,分析了GNSS数据处理涉及的热点计算任务,提出基于分块理论的矩阵乘法运算、矩阵分解运算等数值计算并行方法,对比了单核和多核环境下的计算时间。通过多个算例验证多核并行设计方法的有效性,利用.NET4.0框架下的Parallel Extensions实现相关并行设计。实验结果表明,GNSS数据处理的多核并行计算能充分发挥多核体系带来的性能优势,极大提高资源利用效率和GNSS数据处理效率。 相似文献
9.
ABSTRACTAs an effective tool for simulating spatiotemporal urban processes in the real world, urban cellular automata (CA) models involve multiple data layers and complicated calibration algorithms, which make their computational capability become a bottleneck. Numerous approaches and techniques have been applied to the development of high-performance urban CA models, among which the integration of vectorization and parallel computing has broad application prospects due to its powerful computational ability and scalability. Unfortunately, this hybrid algorithm becomes inefficient when the axis-aligned bounding box (AABB) of study areas contains many unavailable cells. This paper presents a minimum-volume oriented bounding box (OBB) strategy to solve the above problem. Specifically, geometric transformation (i.e. translation and rotation) is applied to find the OBB of the study area before implementing the hybrid algorithm, and a set of functions are established to describe the spatial coordinate relationship between the AABB and OBB layers. Experiments conducted in this study demonstrate that the OBB strategy can further reduce the computational time of urban CA models after vectorization and parallelism. For example, when the cell size is 15 m and the neighborhood size is 3 × 3, an approximately 10-fold speedup in computational time can result from vectorization in the MATLAB environment, followed by an 18-fold speedup after implementing parallel computing in a quad-core processor and, finally, a speedup of 25-fold by further using an OBB strategy. We thus argue that OBB strategy can make the integration of vectorization and parallel computing more efficient and may provide scalable solutions for significantly improving the applicability of urban CA models. 相似文献
10.
The PCRaster Software and Course Materials for Teaching Numerical Modelling in the Environmental Sciences 总被引：4，自引：0，他引：4
Derek Karssenberg Peter A. Burrough Raymond Sluiter & Kor de Jong 《Transactions in GIS》2001,5(2):99-110
Teaching numerical modelling in the environmental sciences not only needs good software and course material but also an understanding of how to program the models in the computer. Conventional environmental modelling procedures require computer science and programming skills, which may detract from the important understanding of the environmental processes involved. An alternative strategy is to build a generic toolkit or modelling language that operates with concepts and operations that are familiar to the environmental scientist. PCRaster is such a spatio-temporal environmental modelling language developed at Utrecht University, the Netherlands. It is used for teaching modelling in classrooms and over the Web (distance learning) at three levels: (1) explaining environmental processes and models, where models with a fixed structure of model equations are evaluated by changing model parameters, (2) teaching model construction, where students learn to program spatial and temporal models with the language, and (3) teaching all phases of scientific modelling related to field research. So far, we have received positive responses to these courses, largely because the software provides a set of easily learned functions matching the conceptual thought processes of a geoscientist that can be used at all levels of teaching. 相似文献
11.
Spatial discretisation plays an important role in many numerical environmental models. This paper studies the control of spatial discretisation in coastal oil spill modelling with a view to assure the quality of modelling outputs for given spatial data inputs. Spatial data analysis techniques are effective for investigating and improving the spatial discretisation in different phases of the modelling. Proposed methods are implemented and tested with experimental models. A new “Automatic Search” method based on GIS zone design principles is shown to significantly improve discretisation of bathymetric data and hydrodynamic modelling outputs. The concepts and methods developed in the study are expected to have general relevance for a range of applications in numerical environmental modelling. 相似文献
12.
The Markov chain random field (MCRF) model is a spatial statistical approach for modeling categorical spatial variables in multiple dimensions. However, this approach tends to be computationally costly when dealing with large data sets because of its sequential simulation processes. Therefore, improving its computational efficiency is necessary in order to run this model on larger sizes of spatial data. In this study, we suggested four parallel computing solutions by using both central processing unit (CPU) and graphics processing unit (GPU) for executing the sequential simulation algorithm of the MCRF model, and compared them with the nonparallel computing solution on computation time spent for a land cover post-classification. The four parallel computing solutions are: (1) multicore processor parallel computing (MP), (2) parallel computing by GPU-accelerated nearest neighbor searching (GNNS), (3) MP with GPU-accelerated nearest neighbor searching (MP-GNNS), and (4) parallel computing by GPU-accelerated approximation and GPU-accelerated nearest neighbor searching (GA-GNNS). Experimental results indicated that all of the four parallel computing solutions are at least 1.8× faster than the nonparallel solution. Particularly, the GA-GNNS solution with 512 threads per block is around 83× faster than the nonparallel solution when conducting a land cover post-classification with a remotely sensed image of 1000?×?1000 pixels. 相似文献
13.
Tianjun Wu Liegang Xia Jiancheng Luo Xiaocheng Zhou Xiaodong Hu Jianghong Ma Xueli Song 《Journal of the Indian Society of Remote Sensing》2018,46(11):1805-1814
In high-resolution remote sensing image processing, segmentation is a crucial step that extracts information within the object-based image analysis framework. Because of its robustness, mean-shift segmentation algorithms are widely used in the field of image segmentation. However, the traditional implementation of these methods cannot process large volumes of images rapidly under limited computing resources. Currently, parallel computing models are generally employed for segmentation tasks with massive remote sensing images. This paper presents a parallel implementation of the mean-shift segmentation algorithm based on an analysis of the principle and characteristics of this technique. To avoid the inconsistency on the boundaries of adjacent data chunks, we propose a novel buffer-zone-based data-partitioning strategy. Employing the proposed data-partitioning strategy, two intensively computation steps are performed in parallel on different data chunks. The experimental results show that the proposed algorithm effectively improves the computing efficiency of image segmentation in a parallel computing environment. Furthermore, they demonstrate the practicality of massive image segmentation when computer resources are limited. 相似文献
14.
基于精密单点定位技术的非差模式是当前GNSS数据处理的主要策略之一。随着测站规模的增大,非差模式的处理时间也线性递增,传统的串行处理方法需消耗大量的计算时间。采用工厂模式和责任链模式实现了非差精密单点定位;利用轻量级的并行编程技术从底层设计并实现了基于任务的非差多核并行解算;进一步在网络多节点环境中建立并发布非差计算服务,实现了网络多节点协同并行解算GNSS数据。通过大量数据的测试与试验,验证了多核多节点的非差并行解算方案的高效性。试验结果表明,单节点多核并行、双节点网络并行、四节点网络并行、六节点网络并行的计算效率分别比单节点串行方案平均提高了2.74,5.30,9.38和14.69倍。 相似文献
15.
Due to high data volume, massive spatial data requires considerable computing power for real‐time processing. Currently, high performance clusters are the only economically viable solution given the development of multicore technology and computer component cost reduction in recent years. Massive spatial data processing demands heavy I/O operations, however, and should be characterized as a data‐intensive application. Data‐intensive application parallelization strategies, such as decomposition, scheduling and load‐balance, are much different from that of traditional compute‐intensive applications. In this article we introduce a Split‐and‐Merge paradigm for spatial data processing and also propose a robust parallel framework in a cluster environment to support this paradigm. The Split‐and‐Merge paradigm efficiently exploits data parallelism for massive data processing. The proposed framework is based on the open‐source TORQUE project and hosted on a multicore‐enabled Linux cluster. A specific data‐aware scheduling algorithm was designed to exploit data sharing between tasks and decrease the data communication time. Two LiDAR point cloud algorithms, IDW interpolation and Delaunay triangulation, were implemented on the proposed framework to evaluate its efficiency and scalability. Experimental results demonstrate that the system provides efficient performance speedup. 相似文献
16.
研究了一种基于数据划分的遥感影像并行处理的路径优化算法,用于解决将并行技术应用于海量遥感影像分布式存储和处理领域时其处理模型所具有的多路可达性所引起的路径动态、最优选择问题。在栅格数据可分解性分析及并行模型数据态、元素、相对信息量和映射等8个基本定义和6个性质的基础上,给出并行处理一般数学模型。以该模型为基础获得在一般并行处理情况下,以平均计算代价变量的比值作为控制横向并行与纵向并行选择方式的标志,并进一步给出四叉树索引并行生成、基于四叉树的目标检测并行处理等具体示例。最后,通过试验验证了算法的有效性,分析了算法的特点及影响因素。 相似文献
17.
18.
利用分布式计算的高性能计算、传输和存储能力,解决常规集中式大规模GNSS数据处理中观测站规模受限和时效性差的问题。讨论了GNSS数据的分布式处理方法、算法设计、处理策略和对已有软件的利用,并对GNSS数据进行了分布式计算试验,试验结果表明,基线解算中,8个节点的加速比达到了6.39;网平差计算中,4个节点的平均加速比达到了3.04。 相似文献
19.
本文介绍了球谐合成和分析问题的数值计算原理,研究分析了其内在的并行性,提出了区域划分和聚合通信的并行计算策略。基于傅立叶变换技术,应用MPI(消息传递接口)并行编程模式,实现了球谐分析及合成计算的并行化。实验结果表明,较之串行实现,并行实现大大缩短了计算时间,获得了近似线形加速比,取得很高的并行效率。 相似文献
20.
提出了一种共享内存环境下的并行质量引导相位解缠算法。首先,分析了相邻相位点质量值计算的内在关系,采用行、列数组保存中间结果消除梯度的重复计算;然后,按行进行计算任务分配,简化相邻窗口内的行、列均值计算;最后,通过OpenMP指令实现计算任务分配,完成质量图的并行计算。对于质量引导过程内在的并行性进行了分析,但受限于重复的线程启动和退出时间开销,难以体现速度优势。对合成孔径雷达干涉（synthetic aperture radar interferometry,InSAR）和干涉合成孔径声纳（interferometric synthetic aperture sonar,INSAS）干涉相位图进行解缠实验,结果表明,所提方法提高了相位解缠效率,为在实时条件下进一步提高相位解缠精度奠定了基础。 相似文献