Date of Award

Summer 8-2020

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Jean Gourd

Abstract

Computer architecture courses can be difficult for students to engage with and learn from. This is because, unlike most core courses for a computer science student, learning architecture is an abstract process. To address this, universities have implemented methods for teaching course material other than purely descriptive methods. This typically means using simulations to model some aspect of a CPU or FPGA (fieldprogrammable gate array) boards for hands-on experimentation in CPU design. However, there are issues with these tools. Simulations can only cover a few topics well, are prone to being abandoned, and introduce additional abstraction layers. FPGAs, while great for advanced topics and long class projects, are often best suited for senior and graduate level students. Both methods are useful, but neither offers a tangible learning experience, which is what the Megaprocessor can provide. The Megaprocessor is a room sized, general-purpose computer made from discrete components, whose architecture is comprised of primitive logic gates with LEDs on every input and output. The entire circuitry of the Megaprocessor is transparent to the users, with its entire state visible and unabstracted. Because of these properties, it is a great learning mechanism for computer architecture education. The Megaprocessor is a tool for hands on and project-based learning that can be used to span the learning gap between simulations and FPGAs.

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