Master of Science in Computer Science
First Committee Member
Ajoy K. Datta
Second Committee Member
Lawrence L. Larmore
Third Committee Member
Fourth Committee Member
Number of Pages
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 simplied and is being used to accelerate a wider class of applications. More specically, 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.
CUDA (Computer architecture); Graphics processing units; Image processing; Multithreading; Parallel computers; Parallel computing; Parallel processing (Electronic computers); Simultaneous multithreading processors
University of Nevada, Las Vegas
Tse, Jia Jun, "Image Processing with CUDA" (2012). UNLV Theses, Dissertations, Professional Papers, and Capstones. 1699.
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