Hardware for Artificial Intelligence and Machine Learning

NEW ECE 410/510 course – Spring 2025

News and updates:

  • The course is currently full. We may increase the cap. For now, please register for the waitlist.
  • This is a new/experimental course. Anything is subject to change.

Course description:

Hardware (HW) is the foundation upon which artificial intelligence (AI) and machine learning (ML) systems are built. It provides the necessary computational power, efficiency, and flexibility to drive innovation in these emerging fields. By using HW/SW co-design, students will learn how to use, design, simulate, optimize, and evaluate specialized HW, such as GPUs, TPUs, FPGAs, and neuromorphic chips, for modern AI/ML algorithms. The intersection of HW and AI/ML is a rapidly growing field with significant career opportunities for computer engineers.

Course organization:

  • The course is organized into lectures, active learning activities, and student presentations.
  • The course is offered in-person only.
  • There will be no course recordings. Your in-person presence is essential for success.

Learning outcomes:

  • Understand the principles and tools for SW/HW co-design.
  • Understand the foundations of neural networks.
  • Understand the foundations of Large Language Models (LLMs).
  • Understand the foundations of specialized hardware for AI/ML, such as GPUs, TPU, FPGAs, and neuromorphic architectures.
  • Capable of mapping algorithms onto hardware.
  • Capable of evaluating HW designs.
  • Capable of optimizing HW designs through co-design for computational power, efficiency, and flexibility.
  • Capable of using modern SW and HW tools for designing and using specialized HW for AI/ML.

Assessment of learning outcomes:

  • You will be graded solely on oral presentations and examinations only.

Tentative course plan:

General catalog and banner information:

  • Course prefix: ECE
  • Course number: 410/510
  • Catalog course title: Hardware for Artificial Intelligence and Machine Learning
  • Credit hours: 4
  • Grading option: Letter grade
  • Course intended for: Graduate and undergraduate students
  • Instructional method: Lecture
  • Prerequisites (recommendations):
    • Undergraduate: ECE 371 and ECE 351
    • Graduate: ECE 485

FAQs:

In no particular order.

  • Q: How can I prepare for this course? A: Brush up on your (Python) programming skills because no matter what you do and design in these days, it will require stellar programming skills. Even as a hardware engineer, you are basically writing software.
  • Q: What will be the balance between theory, foundations, and practice? A: AI is currently an extremely fast moving field, and so is the HW for it. Any practical things and tools that you will learn are likely going to be outdated already by the end of the course. What matters the most for your longer term career success are the foundations and the theory.
  • Q: How is the course aligned with current industry trends? A: As much as possible, but these trends tend to change on a weekly basis. It’s rarely a good idea to focus on trends. What changes on a much slower timescale are the foundations and the theory.
  • Q: Will the prerequisites be enforced: A: No. The prerequisites are recommendations and cannot be enforced for a 410/510 course. If you think you have the right background to be successful in this course, that is fine. Just don’t blame me if you end up not being successful.
  • Q: What projects will you assign? A: Projects will be introduced during class. My projects tend to be open-ended and challenging. Projects are there for you to learn and shine. If your decision whether to take this class or not depends on the projects, then this class may not be for you.
  • Q: Will projects be collaborative? A: Nope, you will be working on your own because I  want you to learn and I want to see what you are capable of.
  • Q: Will I have to present in class: A: Yes, several times. You will be graded solely on oral presentations and examinations.
  • Q: Will this class be recorded. A: No. Your in-person and active engagement is key to this learning experience. We will learn from each other. If you cannot or do not want to attend this class in-person regularly, you may want to look for another class.
  • Q: Will I have to write any project reports? A: Nope, no written documents will be required.
  • Q: Will this be an easy class? A: If you are looking for an easy class, you may want to look elsewhere. Learning about cutting-edge technology at the frontiers of innovation ain’t never be easy.
  • Q: Will AI tools be allowed in this course? A: AI tools are essential tools in these days. They will be not only be allowed (with attribution), they will be encouraged. You probably won’t be able to be successful in this course without heavily using LLM.

Still got questions?