Hardware Accelerators for Machine Learning (Spring 2022)

ECE 618

Coure Inforamtion

Instructor Dr. Weiwen Jiang
E-Mail 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
E-Mail 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.

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

Schedule and Documents

[Syllabi]

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]

Presentation and Final Project Signup

[Form]

Final Project Examples

[Report]

[Slides]