This is part of makepath’s efforts to speed up processing times for common raster analysis functions, as well as leverage GPUs to speed up geospatial data processing and analysis.
The Results: Nvidia GPU + CUDA Toolkit
Viewshed operations using CUDA algorithms were over 300 times faster than traditional CPU algorithms.
To get these results, we used a combination of CUDA algorithms on a Nvidia T4 GPU, and ray tracing with OptiX through RTXpy.
Demo: Real-time Viewshed and Hillshade results on Crater Lake National Park. With each click, the Viewshed is calculated from that point. The illumination source for Hillshade calculations circles around the crater.
Open Source Projects Involved
Three Open Source projects are an active part of makepath’s work with GPUs:
Viewshed finds all visible locations in an input raster surface from a specific place within the raster. This geospatial operation answers the question of, “What can an observer see from this specific location?”
Hillshade makes a shaded relief from a surface raster, taking the illumination source angle and shadows into account. This geospatial operation answers the question of, “If an illumination source (like the sun) was over there, what would the terrain look like?”.
Want to learn more about the work makepath is doing with GPUs?