Accelerated Computing

a.k.a. CSE 822: Parallel Computing

Term: Spring 2026
Instructor: Xuhao Chen
Lecture: Time, Location
Office Hour: Time, Location
TAs: TBD

Welcome!

This is a graduate-level course focused on performance engineering for parallel computers and accelerators. We aim to convey both:

1. First-principles understanding:
   Why do modern accelerator architectures look the way they do?

2. 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

• This site is online! Hooray!

• Labs have been released! (Instructions)

Site Map

• Calendar – Lecture, lab, and office hour schedule; assignment due dates.

• Labs – Descriptions and instructions for all lab assignments.

• Syllabus – Course policies, topics covered, general course information.

• Resources – Links to notes and external materials relevant to the course.

• Contact – How to get in touch with course staff.

• 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.