NDLI: Spherical interpolation over graphic processing units

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Spherical interpolation over graphic processing units

Content Provider	ACM Digital Library
Author	Shi, Xuan Liu, Yan Han, Su Yeon Wang, Shaowen Ye, Fei
Abstract	Spatial interpolation is a widely used GIS function for estimating values at locations where observed values are not available or adequate. One popular method for spatial interpolation is inverse distance weighted, which calculates estimated values based on a weighted sum of the values of a number of nearest neighbors that have observed values. This research focuses on solving a large-scale interpolation problem with a global coverage based on the inverse distance weighted method. Specifically, spherical distance is calculated instead of normal Euclidean distance commonly used in GIS software, which is necessary to find correct neighbors in the regions along the 180° longitude and in the polar areas. The computation of the global-scale interpolation based on spherical distance is intensive especially for achieving high-resolution results. This paper introduces how to accelerate such computation by exploiting massive parallelism provided by Graphic Processing Units (GPUs) with significant improvement of computational performance reported.
Starting Page	38
Ending Page	41
Page Count	4
File Format	PDF
ISBN	9781450310406
DOI	10.1145/2070770.2070777
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-11-01
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Inverse distance weighted High performance computing Spatial interpolation Graphic processing units
Content Type	Text
Resource Type	Article

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