Electronic Theses and Dissertations

Date of Award

2013

Document Type

Dissertation

Degree Name

Ph.D. in Engineering Science

Department

Electrical Engineering

First Advisor

Atef Z. Elsherbeni

Second Advisor

William Staton

Third Advisor

Ramanarayanan Viswanathan

Relational Format

dissertation/thesis

Abstract

The use of Graphical Processing Units (GPU's) for scientific applications has been evolving and expanding for the decade. GPU's provide an alternative to the CPU in the creation and execution of the numerical codes that are often relied upon in to perform simulations in computational electromagnetics. While originally designed purely to display graphics on the users monitor, GPU's today are essentially powerful floating point co-processors that can be programmed not only to render complex graphics, but also perform the complex mathematical calculations often encountered in scientific computing. Currently the GPU's being produced often contain hundreds of separate cores able to access large amounts of high-speed dedicated memory. By utilizing the power offered by such a specialized processor, it is possible to drastically speed up the calculations required in computational electromagnetics. This increase in speed allows for the use of GPU based simulations in a variety of situations that the computational time has heretofore been a limiting factor in, such as in educational courses. Many situations in teaching electromagnetics often rely upon simple examples of problems due to the simulation times needed to analyze more complex problems. The use of GPU based simulations will be shown to allow demonstrations of more advanced problems than previously alloby adapting the methods for use on the GPU. Modules will be developed for a wide variety of teaching situations utilizing the speed of the GPU to demonstrate various techniques and ideas previously unrealizable.

Concentration/Emphasis

Emphasis: Electrical Engineering

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