Abstract
The Raspberry Pi is a small inexpensive computer that is praised for those traits. Said traits also come with steep trade-offs. This project seeks to investigate if those trade-offs are worth it all in all. To do this, a Raspberry Pi 3 is stress-tested using machine learning and memory stress. The performance of the Pi during these tests is recorded, discussed, and compared to better analyze the tests. To better understand the Pi and machine learning, the project also explores the applications and architectures of the Pi and basic machine learning information.
Advisor
Fox, Nathan
Department
Computer Science
Recommended Citation
Golnik, Reid Thomas, "Pushing the Limits of a Raspberry Pi" (2020). Senior Independent Study Theses. Paper 9053.
https://openworks.wooster.edu/independentstudy/9053
Disciplines
Computer and Systems Architecture | Hardware Systems
Keywords
Raspberry Pi, Memory, Machine Learning
Publication Date
2020
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2020 Reid Thomas Golnik