high performance computing on graphics processing units: hgpu.org

Drainage networks determination from Digital Elevation Models (DEM) has been a widely studied problem in the last three decades. During this time, satellite technology has been improving and optimizing digitalized images, and computers have been increasing their capabilities to manage such a huge quantity of information. The rapid growth of CPU power and memory size has concentrated the discussion of DEM algorithms on the accuracy of their results more than their running times. However obtaining improved running times remains crucial when DEMs dimensions and resolutions increase. Parallel computation provides an opportunity to reduce run times. Recently-developed Graphics Processing Units (GPUs) are giving important results in time not only in Computer Graphics but in General Purpose Computation, the so-called GPGPU. In this paper we explore the parallel characteristics of these GPUs using the C-oriented language of CUDA developed by NVIDIA for drainage network determination. The results are simple algorithms that run on low-cost technology with a high performance response, obtaining CPU improvements in time up to 8X.