Degree Type

Thesis

Date of Award

2019

Degree Name

Master of Science

Department

Electrical and Computer Engineering

Major

Computer Engineering

First Advisor

Joseph Zambreno

Abstract

Dynamic Partial Reconfiguration (DPR) can be a useful tool for maximizing FPGA performance while minimizing power consumption and FPGA size requirements. This work explores the application of the DPR technique in a computer vision application that implements two different edge detection algorithms (FASTX and Sobel). This technique could allow for a similar computer vision system to be realized on a smaller, low-power chipset. Different algorithms can have unique characteristics that yield better performance in certain scenarios; the best algorithm for the current scenario may change during runtime. However, implementing all available algorithms in hardware increases the space and power requirements of the FPGA. We analyze a system that can load an individual edge detection algorithm into the computer vision processing pipeline with negligible interruptions to data processing by using DPR. This application targets the Xilinx UltraScale+ ZCU106 and is able to maintain the same functionality while using an average of 4% less energy when compared to the non-DPR implementation. Additionally, the FPGA utilization for this application is 15% less than that of the traditional implementation that includes both algorithms on the chip at once. These results demonstrate that this technique could allow a similar computer vision system to be realized on a smaller, low-power chipset.

Copyright Owner

Robert Cole Wernsman

Language

en

File Format

application/pdf

File Size

38 pages

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