Spring 2021 - CMPT 499 D100
Special Topics in Computer Hardware (3)
Class Number: 7025
Delivery Method: Remote
Overview
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Course Times + Location:
Jan 11 – Apr 16, 2021: Mon, Wed, Fri, 3:30–4:20 p.m.
Burnaby
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Instructor:
Arrvindh Shriraman
ashriram@sfu.ca
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Prerequisites:
CMPT/ENSC 250.
Description
CALENDAR DESCRIPTION:
Current topics in computer hardware depending on faculty and student interest.
COURSE DETAILS:
This course will explore, from a computer architecture perspective, the principles of hardware/software codesign for machine learning. One thrust of the course will delve into accelerator, CPU, and GPU enhancements for ML algorithms, including parallelization techniques. The other thrust of the course will focus on how machine learning can be used to optimize conventional architectures by dynamically learning and adapting to program behavior. Is this a machine learning course? ------------------------------------ Not really – the computation behind machine learning and how that is exploited with hardware is what is most relevant here. Prerequisites -------------- Should have taken CMPT 295, CMPT 300, CMPT 431 . It is recommended that you have taken some courses in computer organization. Expected background includes basic knowledge of simple hardware pipelines (ie. how does an inorder processor work?). Strong programming background : C++/C All of that said, we will spend time going in depth on background/review during the first two-or-so weeks to build a foundation for more advanced architecture concepts. Projects and Assignments -------------------------- We will be working with FPGAs, designing hardware targetting specific algorithms.
Topics
- Machine Learning
- Hardware architecture
- Hardware/Software Co-design
Grading
NOTES:
Project - 50% , Assignments - 50%
Registrar Notes:
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html
TEACHING AT SFU IN SPRING 2021
Teaching at SFU in spring 2021 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.
Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112).