Awardee: Tom Yeh, Visiting Assistant Professor of Computer Science
Tom Yeh is currently a Visiting Assistant Professor of Computer Science at Pomona College. He recently came back to academia after working in the industry. He graduated from UCLA with his PhD in computer science and from UC Berkeley with his BS in electrical engineering and computer science.
Title: Visualization of Future Computer Architectures (Machine Learning Accelerators and Quantum Computing)
Goal: To redesign Computer Science courses using advanced CPU designs, such as machine learning accelerators in the open-source tool Logisim Evolution
No stranger to the Hahn Grant, Thomas Yeh has previously utilized the Hahn Grant for Teaching with Technology to create visual Central Processing Unit (CPU) models to augment textbook material used in his CS181OR course. Building off this success, Yeh now plans to develop and model advanced CPU designs from academia and the industry, like machine learning accelerators, to facilitate student visualization of computer architecture concepts within a newly proposed course: Future Computer Architectures. This anticipated Spring 2023 course will focus on teaching introductory quantum computing to 5C undergraduate students. As Yeh notes (presumably of computer science students), “Many students at liberal arts colleges do not have a background in logic design, engineering, or physics.”
Yeh plans to utilize an open-source tool, Logisim Evolution, which he has used in his previous efforts; through its successful implementation in CS181OR, the tool has been shown to be user-friendly. Course content will be pulled from the curriculum used by University of Washington undergraduate and graduate students originating from the work of a Microsoft researcher Yeh is in contact with. Of course, existing visualization tools for quantum circuits can also be leveraged to develop lectures, assignments, and projects, but the crux of the class will rely on student use of Logisim to simulate what would happen in a quantum circuit. It is then that students will be able to make the leap from the classical computing they are more commonly exposed to, to quantum computing–what’s best, they will be able to do so using a familiar tool. The knowledge of basic elements of quantum circuits compiled into a clear learning framework will serve as a steady foundation to thrust into the world of quantum computing.
The main outcomes of this project are to create Logisim models of advanced CPU designs, such as machine learning accelerators, and to teach introductory quantum computing to undergraduate students while incorporating visualization as a key design principle. The project’s success will be evaluated based on the successful completion of these designs and the effectiveness of the visualization tools in enhancing students’ understanding of the concepts.
The project will result in a set of comprehensive and user-friendly Logisim models of advanced CPU designs, which will greatly enhance the learning experience of students in computer architecture courses.