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CUDA-Accelerated HD-ODETLAP: Lossy High Dimensional Gridded Data Compression

W. Randolph Franklin, You Li, Tsz-Yam Lau, Peter Fox
Rensselaer Polytechnic Institute, 110 8th Street, Troy, NY, USA 12180
2012 International Workshop on Modern Accelerator Technologies for GIScience (MAT4GIScience 2012), 2012

@article{franklin2012cuda,

   title={CUDA-Accelerated HD-ODETLAP: Lossy High Dimensional Gridded Data Compression?},

   author={Franklin, W.R. and Li, Y. and Lau, T.Y. and Fox, P.},

   year={2012}

}

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We present High-dimensional Overdetermined Laplacian Partial Differential Equations (HD-ODETLAP), a high dimensional lossy compression algorithm and CUDA implementation that exploits data correlations across multiple dimensions of gridded GIS data. Exploiting the GPU gives a considerable speedup. In addition, HD-ODETLAP compresses much better than JPEG2000 and 3D-SPIHT, when fixing either the average or the maximum error.
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