Accelerated Computing
Term: Fall 2025
Instructor: Xuhao Chen
Lecture: Time, Location
Office Hour: Time, Location
TAs: TBD
Welcome!
This is a graduate-level course focused on performance engineering for specialized hardware accelerators. We aim to convey both:
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First-principles understanding:
Why do modern accelerator architectures look the way they do? -
Hands-on experience:
How do we write fast code for these platforms in practice?
Most of the assignments in this course focus on programming GPUs, for which we use NVIDIA’s CUDA programming language. Students are expected to complete weekly programming assignments, participate in weekly in-person lab sessions, and present a final project at the end of the semester on a topic of their choice.
Announcements
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Lab 8: One Million Circles has been released! (Instructions)
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Lab 8 Final due Sunday, November 10 (Gradescope)
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Final project instructions have been released! (Instructions)
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Live lab will meet Tuesday, November 12 to discuss final projects
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Final project topic proposals due Friday, November 15 (Gradescope)
Site Map
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Calendar – Lecture, lab, and office hour schedule; assignment due dates.
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Labs – Descriptions and instructions for all lab assignments.
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Syllabus – Course policies, topics covered, general course information.
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Resources – Links to notes and external materials relevant to the course.
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Contact – How to get in touch with course staff.
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Piazza – Main hub for student discussion and staff communication.
Acknowledgements
This course was originally designed and developed by Prof. Jonathan Ragan-Kelley and the 6.S894 course staff at MIT. We extend our gratitude to the 6.S894 staff for generously sharing the course materials and for their invaluable support.
Course infrastructure is made possible by generous support from Jane Street.
Thanks to CS6120 at Cornell for providing the base CSS stylesheet on which this website is built.