ECE 618
Coure Inforamtion
| Instructor | Dr. Weiwen Jiang |
|---|---|
| wjiang8@gmu.edu | |
| Phone | (703)993-5083 |
| Lecture Time | Monday 19:20 - 22:00 |
| Location | Room 1002, Music/Theater Building |
| Office Hour | Monday 16:00 - 17:00 |
| Office | Room 3247, Nguyen Engineering Building |
| Zoom | http://go.gmu.edu/zoom4weiwen |
| TA | Yi Sheng |
|---|---|
| ysheng2@gmu.edu | |
| In-person Office Hour | Thursdays 10:00 to 13:00 |
| In-person Location | ENG3208 |
| On-line Office Hour | Friday 10:00 to 11:00 |
| On-line Location | https://gmu.zoom.us/j/9221922155 |
Course Materials
Course materials will be posted before or after the class. No formal textbook is required.
Recommended Prerequisites
ECE 554 (ECE 499/590 in Fall 2021: Machine Learning for Embedded Systems) with the minimum grade of B- or permission of instructor.
Course Description
This course covers the hardware design principles to deploy different machine learning algorithms. The emphasis is on understanding the fundamentals of machine learning and hardware architectures and determine plausible methods to bridge them. Topics include precision scaling, in-memory computing, hyperdimensional computing, architectural modifications, GPUs and vector architectures, quantum computing as well as recent hardware programming tools such as Xilinx AI Vitis, Xilinx HLS, and IBM Qiskit.
Tools for Lab
- Google Colab
- Xilinx High-Level Synthesis
- IBM Qiskit
Schedule and Documents
| W | Date | Topic | Documents | Note |
|---|---|---|---|---|
| Session I: Classical Computing Accelerators for Machine Learning | ||||
| 1 | Jan. 24 | Course Information & Machine Learning and FPGA Accelerator Recap | [Slides] | |
| 2 | Jan. 31 | Domain-Specific Computing | ||
| 3 | Feb. 7 | Vector Architectures, GPU Architectures, and Benchmarking Metrics | [Hands-On 1] [Lab 1] | |
| 4 | Feb. 14 | FPGA Accelerator | ||
| Session II: Novel Post-Moore Computing Accelerators for ML | ||||
| 5 | Feb. 21 | In-Memory Computing Accelerator Design | ||
| 6 | Feb. 28 | CiM(2) & Hyperdimensional Computing Accelerators (1) | ||
| 7 | Mar. 07 | Hyperdimensional Computing Accelerators (2) and Midterm Review | [Hands-On 2] | |
| 8 | Mar. 21 | Midterm Exam | ||
| Session III: ML Accelerators in Quantum Computing | ||||
| 9 | Mar. 28 | Project Proposal & Single Qubit System | [Hands-On 3] | |
| 10 | Apr. 04 | Multi-Qubits System | ||
| 11 | Apr. 11 | Quantum Data Preparation & Processing | [Hands-On 4] | |
| 12 | Apr. 18 | QuantumNAS | ||
| 13 | Apr. 25 | Project Overview & QuantumFlow | ||
| 14 | May 02 | Project Presentations | ||
| 15 | May 11-18 | Final exam |
Readings and Tutorial
| W | Date | Reading (R) & Paper (P) & Tutorial (TT) |
|—————–|————–|————–|——————|————-|
| 1 | Jan. 24 | [HLS Doc] [HLS Youtube] [ECE554 Lab3] [ECE554 Lab4]|
| 2 | Jan. 31 | [Talk 1] |
| 3 | Feb. 7 | [Data Processing] [Pretrained Model] [Model Count] [NIVIDA GPU Management] |
| 4 | Feb. 14 | [FPGA] [FPGA_NN]
| 5 | Feb. 22 | [Dataflow pp.14]
| 6 | Feb. 28 | [Talk 2]
| 7 | Mar. 07 | [HDC]
| 9 | Mar. 28 | [Qubit] [Q Gate]
| 10 | Apr. 04 | [Multiple Qubits]
| 11 | Apr. 11 | [Transpilation]
| 12 | Apr. 18 | [Talk 3]
