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Improving the performance of spatial raster analysis in GIS using GPU

机译:使用GPU提高GIS中空间光栅分析的性能

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GIS spatial raster analysis has become a powerful tool for geographical phenomena. Unfortunately the computation-intensive raster operations are likely to create computer performance bottlenecks when running on the CPUs. Over the last few years, GPU performance has improved much more than CPU performance. For this reason, many researches have applied the GPUs for scientific, geometric and database computations beyond graphics. This paper demonstrates a general framework for the GPU-based implementation of GIS raster operations, and conducts experiments to compare the computation performance between GPU-based and CPU-based algorithms. The test results indicate that using GPU on spatial raster operations can significantly improve their computation performance. This means that realizing GIS spatial analysis on the GPU create new opportunities by drastically lowering the cost of raster operations on the same hardware performance.
机译:GIS Spatial Raster分析已成为地理现象的强大工具。不幸的是,在CPU上运行时,计算密集型栅格操作可能会创建计算机性能瓶颈。在过去的几年里,GPU性能提高了超过CPU性能。因此,许多研究已经应用于超出图形的科学,几何和数据库计算的GPU。本文展示了GIS光栅操作的基于GPU的实现的一般框架,并进行了实验,以比较基于GPU和基于CPU的算法之间的计算性能。测试结果表明,使用GPU在空间光栅操作上可以显着提高其计算性能。这意味着通过大大降低相同硬件性能的光栅操作的成本,实现GIS空间分析创造了新的机会。

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