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GPU-Parallel Spatially Adaptive Kernel Density Estimation for Point Pattern Analysis

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Guiming/GPUParallelSpatialAdaptiveKDE

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GPUParallelSpatialAdaptiveKDE

The C/C++ implementation of GPU-Parallel and OpenMP-parallel Spatially Adaptive Kernel Density Estimation for Point Pattern Analysis. The OpenMP version is in the 'kde_openmp' directory and the CUDA GPU version in the 'kde_cuda' directory. Find more detail about the code in this paper: http://www.tandfonline.com/eprint/SqqNR3VESnYZScgyzs8F/full.

Environment

Ubuntu OS, with CUDA installed to run the CUDA version.

License

Copyright 2016 Guiming Zhang. Distributed under GNU General Public License (GPL) license.

Citation

Guiming Zhang, A-Xing Zhu & Qunying Huang (2017) A GPU-accelerated adaptive kernel density estimation approach for efficient point pattern analysis on spatial big data, International Journal of Geographical Information Science,31(10): 2068-2097. DOI: 10.1080/13658816.2017.1324975 [Full text: http://www.tandfonline.com/eprint/SqqNR3VESnYZScgyzs8F/full]

Contact

Guiming Zhang (gzhang45@wisc.edu)

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GPU-Parallel Spatially Adaptive Kernel Density Estimation for Point Pattern Analysis

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