空间数据规模的快速增长对传统矢量数据分析方法提出了更高的计算效率和处理规模要求.随着计算机硬件和软件技术的进步,并行计算为提高GIS中典型几何计算算法的计算效率、扩大问题处理规模提供了有效手段.本文在Visual Studio 2010中,使用标准C++编程语言,基于GDAL(Geospatial Data Abstraction Library)库实现空间数据的读写操作,针对线简化算法的并行化问题,在高性能计算环境下对并行任务调度策略、并行计算粒度、数据分解方法等多个核心内容开展研究.在完成相关串行算法的基础上,实现了该算法的并行化和优化设计,为相关的矢量数据空间分析方法的多核并行优化提供了思路和参考.%The rapid growth of the size of traditional data space vector data analysis a higher computational efficiency and process scale requirements.With advances in computer hardware and software technology, parallel computing to improve the efficiency of GIS typical geometry calculation algorithm, the expansion of the treatment capacity provides an effective means.This article in Visual Studio 2010, using standard C ++ programming language, based on GDAL (Geospatial Data Abstraction Library) library to read and write operations of spatial data for the line to simplify the problem of parallel algorithms in high-performance computing environments for parallel task scheduling strategy a plurality of core research, parallel computing granularity data decomposition methods.Upon completion of the relevant serial algorithm on the realization of the algorithm parallelization and optimization algorithms designed for multi-core parallel vector data related to spatial analysis method of optimization ideas and references.
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