Award Date

8-1-2012

Degree Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science

First Committee Member

Ajoy K. Datta

Second Committee Member

Lawrence L. Larmore

Third Committee Member

Yoohwan Kim

Fourth Committee Member

Venkatesan Muthukumar

Number of Pages

66

Abstract

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.

Keywords

CUDA (Computer architecture); Graphics processing units; Image processing; Multithreading; Parallel computers; Parallel computing; Parallel processing (Electronic computers); Simultaneous multithreading processors

Disciplines

Computer Sciences

File Format

pdf

Degree Grantor

University of Nevada, Las Vegas

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

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