GPU-accelerated raster map reprojection




Raster reprojection, warping, parallelization, OpenCL, GPGPU, GPU


Reprojecting raster maps from one projection to another is an essential part of many cartographic processes (map comparison, overlays, data presentation, ...) and reducing the required computational time is desirable and often significantly decreases overall processing costs.

The raster reprojection process operates per-pixel and is, therefore, a good candidate for GPU-based parallelization where the large number of processors can lead to a very high degree of parallelism.

We have created an experimental implementation of the raster reprojection with GPU-based parallelization (using OpenCL API).
During the evaluation, we compared the performance of our implementation to the optimized GDAL and showed that there is a class of problems where GPU-based parallelization can lead to more than sevenfold speedup.


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