GPU enabled XDraw viewshed analysis

• Performed performance experiments on four different viewshed analysis algorithms across CPU and GPU domains.
• Utilized the C++  AMP framework to ensure cross-platform generalizability.
• Optimized the XDraw viewshed analysis algorithm for efficiency on a GPU and compared to previous algorithms.
• Optimized GPU XDraw algorithm performed well when compared to similar GPU and CPU algorithms.

Viewshed analysis is an important tool in the study of digital terrain visibility. Current methods rely on the CPU performing computations to linearly calculate visibility for a given position on a portion of digital terrain. The viewshed analysis process can be sped up through the use of a GPU to parallelize the visibility algorithms. This paper presents a novel conversion of the XDraw viewshed analysis algorithm to a parallel context in an effort to increase the speed at which a viewshed can be rendered. The algorithm executed faster than current linear methods and responded well to parallelization. We conclude that XDraw is applicable for GIS applications when rendered in a parallel context.