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A high accuracy surface modeling method based on GPU accelerated multi-grid method

机译:基于GPU加速多网格方法的高精度曲面建模方法

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摘要

A high accuracy surface modeling method (HASM) has been developed to provide a solution to many surface modeling problems such as DEM construction, surface estimation and spatial prediction. Although HASM is able to model surfaces with a higher accuracy, its low computing speed limits its popularity in constructing large scale surfaces. Hence, the research described in this article aims to improve the computing efficiency of HASM with a graphic processor unit (GPU) accelerated multi-grid method (HASM-GMG). HASM-GMG was tested with two types of surfaces: a Gauss synthetic surface and a real-world example. Results indicate that HASM-GMG can gain significant speedups compared with CPU-based HASM without acceleration on GPU. Moreover, both the accuracy and speed of HASM-GMG are superior to the classical interpolation methods including Kriging, Spline and IDW.
机译:已经开发出一种高精度的表面建模方法(HASM),以解决许多表面建模问题,例如DEM构造,表面估计和空间预测。尽管HASM能够以较高的精度对曲面进行建模,但其低计算速度限制了其在构建大型曲面时的普及。因此,本文所述的研究旨在通过图形处理器单元(GPU)加速多网格方法(HASM-GMG)来提高HASM的计算效率。 HASM-GMG已通过两种类型的表面进行了测试:一个高斯合成表面和一个实际示例。结果表明,与不基于GPU的加速的基于CPU的HASM相比,HASM-GMG可以显着提高速度。此外,HASM-GMG的准确性和速度均优于经典插值方法,包括Kriging,Spline和IDW。

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