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High-performance computing in GIS: techniques and applications

机译:GIS中的高性能计算:技术和应用

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In this paper, the application of High-Performance Computing (HPC) techniques in processing of geospatial data in Geographic Information System (GIS) is presented. We evaluate two parallel/distributed architectures and programming models: Message Passing Interface (MPI) over Network of Workstations (NoW) and Compute Unified Device Architecture (CUDA) on Graphics Processing Unit (GPU) in well-known problems in GIS: map matching and slope computations. A distributed application for map-matching computation over large-spatial data sets consisting of moving points and a road network was implemented using MPI and experimentally evaluated. A slope computations based on large-digital elevation model data was performed on GPU using CUDA which enable hundreds of threads to run concurrently employing multiprocessors on a graphics card. Experimental evaluations indicate improvement in performance and shows feasibility of using NoW and multiprocessors on a graphic card for HPC in GIS.
机译:本文介绍了高性能计算(HPC)技术在地理信息系统(GIS)中处理地理空间数据的应用。我们评估了两种并行/分布式架构和编程模型:工作站网络上的消息传递接口(MPI)(NoW)和图形处理单元(GPU)上的计算统一设备架构(CUDA),用于GIS中的众所周知问题:地图匹配和斜率计算。使用MPI实现了分布式应用程序,该应用程序在包含移动点和道路网络的大空间数据集上进行地图匹配计算,并进行了实验评估。使用CUDA在GPU上执行了基于大数字高程模型数据的斜率计算,这使数百个线程能够在图形卡上使用多处理器同时运行。实验评估表明性能有所提高,并显示了在图形卡上为GIS中的HPC使用NoW和多处理器的可行性。

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