ECE 554
Coure Inforamtion
| Instructor | Dr. Weiwen Jiang |
|---|---|
| wjiang8@gmu.edu | |
| Lecture Time | Monday 4:30 pm – 7:10 pm |
| Location | Horizon Hall (HORIZON) 3008 |
| Office Hour | Monday 14:30 - 15:30 |
| Office | Room 3247, Nguyen Engineering Building |
| TA | Zhirui Hu |
|---|---|
| zhu2@gmu.edu |
Course Materials
Course materials will be posted before or after the class. No formal textbook is required. This e-book will be referred to on the course.
Prerequisites
CS 222 and ECE 231 and ECE 350 with the minimum grade of C
The course topics are self-contained so that a background in machine learning is not required. Students should be familiar with programming and embedded systems to complete the course projects.
Course Description
Machine learning (ML) has gradually become the core component of wide applications in different computing scenarios, ranging from edge computing to cloud computing. This course focuses on resource-constrained edge computing, in particular the embedded systems, and introduces techniques for developing energy/time efficient ML algorithms and models for the embedded systems. Topics that are covered include (i) commonly used ML algorithms, (ii) ML model compression techniques, (iii) hardware-aware machine learning, (iv) hardware and neural architecture co-design. The course also provides a comprehensive team-based research and development experience through projects and presentations. Offered by Electrical & Comp. Engineering. May not be repeated for credit.
Tools for Lab
- Google Colab
- Xilinx High-Level Synthesis
Schedule and Documents
| W | Date | Topic | Documents | Note |
|---|---|---|---|---|
| 1 | Aug 22 | Course Information & Introduction to Machine Learning | [Lab1] | |
| 2 | Aug 29 | Train Neural Networks | [HandsOn] | |
| 3 | Sep 12 | Deep Convolutional Neural Networks (CNN) | ||
| 4 | Sep 19 | Deep Convolutional Neural Networks (CNN) - Part 2 | [Lab2] | |
| 5 | Sep 26 | Natural Langue Processing | ||
| 6 | Oct 03 | Reinforcement Learning | ||
| 7 | Oct 11 | ML Accelerator Design | ||
| 8 | Oct 17 | ML System Implementation and Optimization | [Invited Talk] | |
| 9 | Oct 24 | Mid-Term Exam | ||
| 10 | Oct 31 | Model Compression | ||
| 11 | Nov 07 | DNN Design and Compression Review | ||
| 12 | Nov 14 | Neural Architecture Search | ||
| 13 | Nov 21 | Hardware-Aware Neural Architecture Search | ||
| 14 | Nov 28 | HW/SW Co-Design with Neural Architecture Search | ||
| 15 | Dec 12 | Course Project Demonstration |
Readings and Tutorial
| W | Date | Reading (R) & Paper (P) & Tutorial (TT) |
|—————–|————–|————–|——————|————-|
| 1 | Aug 22 | [R1] |
| 4 | Sep 19 | [R3, 9.1-9.3] [TT1] [TT2, Train CIFAR10]|
