2023 Fall
COMPSCI 294 256 - LEC 256
Special Topics
Machine Learning for Hardware Design
John Wawrzynek
Class #:33400
Units: 3
Instruction Mode:
In-Person Instruction
Offered through
Electrical Engineering and Computer Sciences
Current Enrollment
Total Open Seats:
4
Enrolled: 11
Waitlisted: 0
Capacity: 15
Waitlist Max: 5
Open Reserved Seats:
4 reserved for Computer Science and Electrical Engineering and Computer Sciences Graduate Students
Hours & Workload
1 to 3 hours of instructor presentation of course materials per week, and 2 to 11 hours of outside work hours per week.
Final Exam
THU, DECEMBER 14TH
07:00 pm - 10:00 pm
Hearst Mining 310
Other classes by John Wawrzynek
Course Catalog Description
Topics will vary from semester to semester. See Computer Science Division announcements.
Class Description
This course will provide a graduate-level introduction to recent work in applying machine learning techniques to computer hardware design. Like so many other fields, machine learning may soon have a huge impact on
the way we synthesize, optimize, and verify hardware circuits and systems. Recent work have shown promise in helping to get through some of the very difficult problems associated with hardware design with the
promise of vastly improving designer productivity and leading to more efficient and verified correct designs. This semester, we will survey the state of the art in the burgeoning area and work on novel projects and new approaches.
Class Notes
*Please complete this form for permission to enroll:
https://docs.google.com/forms/d/e/1FAIpQLScunFnYGlUfIZlfn-gNVXeOw9iehY-6UYc5DXzpqyXpkEQtsg/viewform
* Prerequisites: background in hardware design at the
level of EECS151/251A or CS152, OR a background in machine learning .. show more
https://docs.google.com/forms/d/e/1FAIpQLScunFnYGlUfIZlfn-gNVXeOw9iehY-6UYc5DXzpqyXpkEQtsg/viewform
* Prerequisites: background in hardware design at the
level of EECS151/251A or CS152, OR a background in machine learning .. show more
*Please complete this form for permission to enroll:
https://docs.google.com/forms/d/e/1FAIpQLScunFnYGlUfIZlfn-gNVXeOw9iehY-6UYc5DXzpqyXpkEQtsg/viewform
* Prerequisites: background in hardware design at the
level of EECS151/251A or CS152, OR a background in machine learning at the level of CS189/289A along with an interest in hardware design.
*No time conflicts allowed show less
https://docs.google.com/forms/d/e/1FAIpQLScunFnYGlUfIZlfn-gNVXeOw9iehY-6UYc5DXzpqyXpkEQtsg/viewform
* Prerequisites: background in hardware design at the
level of EECS151/251A or CS152, OR a background in machine learning at the level of CS189/289A along with an interest in hardware design.
*No time conflicts allowed show less
Rules & Requirements
Requisites
- Graduate students NOT in the Master of Engineering Program other those in EECS
Repeat Rules
Reserved Seats
Current Enrollment
Open Reserved Seats:
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials
Associated Sections
None