Thank you all for attending my keynote lecture on GPU last week! 486 attended live. I know many couldn’t make it and have been waiting for the recording.
Special thanks for Zain Hasan and Together AI for hosting and sponsoring this lecture. Check out his popular RAG course on DeepLearning.ai.
Special thanks for Shanya Chaubey to volunteer to be my teaching assistant. It was really nice to reunite with her. Go Buffs! 🦬
(👇 Scroll down to find the recording and solution)
Feedback
🙏🙏🙏🙏🙏 Thank you all for the thoughtful feedback! This lecture has been months in the making — it took a lot of trial and error to find a way to break the GPU down to its first principles, all by hand ✍️.
Strengths (in participants’ words):
“Amazing lecture, Dr. Yeh!”
“An excellent and informative course, with fresh ideas and an outstanding instructor.”
“Very intuitive and insightful learning GPU by Hand ✍🏻.”
“Really liked the ‘trace precedents’ trick to visually illustrate memory dependency.”
“Covered all the major pillars of the topic without any fluff.”
“Masterpiece.”
“Matrix multiplication is all you need.”
“I love the Excel workbooks!”
“Great way to see how GPU works — lots of stuff packed in one hour.”
“Fantastic presentation.”
“It was amazing!!”
Weakness: Some beginners found the pacing was too fast. They found it hard to keep up with formulas like MMULT and LET, especially while following the live chat.
Mitigation: I’ll keep the current pace to preserve the rigor and depth that the majority of attendees valued, but I’ll also provide separate warm-up exercises focused on Excel basics, notation, and setup. This way, newcomers can build confidence before the main lecture — without slowing the momentum for experienced learners.
Recording (Raw)
Here’s the unedited recording on Youtube.
Downloads
Use this to follow along the lecture:
Use this to check your solutions:
Video preview of the Excel worksheet:
Next
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Click Here to Join the next Keynote Lecture sponsored by Vectara.








I attended this lecture and I just want to give major props to Professor Yeh as well as those who were helping answer complex questions in the chat! I learned a lot!