high performance computing on graphics processing units: hgpu.org

This thesis puts to the test the power of parallel computing on the GPU against the massive computations needed in image processing of large images. The GPU has long been used to accelerate 3D applications. With the advent of high level programmable interfaces, programming to the GPU is simplified and is being used to accelerate a wider class of applications. More specifically, this thesis focuses on CUDA as its parallel programming platform. This thesis explores on the possible performance gains that can be achieved by using CUDA on image processing. Two well known algorithms for image blurring and edge detection is used in the experiment. Benchmarks are done between the parallel implementation and the sequential implementation.