Instructor

Sheldon Tan (stan@ece.ucr.edu)

Office Hours: Thursday 3:00 to 4:00pm (better by appointment).

Office: WCH 424

Lecture

Wed: 12:40pm to 2:00pm

Watkins Hall Room 1117

Teaching Assistants

Zeyu Sun (zsun007@ucr.edu)

Office Hour: Tuesday 11:00am to 12:00 p.m (TA will attend each course, so better by appointment right after class)

TA Office Room: TBA

Prerequisite

TBD

Course Description

The course will introduce the advanced topics in modern VLSI IC design techniques and methodologies specially for emerging applications emerging applications such as machine/deep learning, quantum/Ising computing, cyber and hardware security.

Course Background and Description

The first working silicon transistor was invented at Bell lab in 1954 by Morris Tanenbaum and commercially produced by Texas Instrument in 1954 and it has been 62th anniversary of the invention. Today's integrated circuit (IC) becomes a part of every aspect of our daily lives. This course will cover many advanced VLSI design techniques and methodologies ranging from the VLSI reliability, VLSI thermal/power aware design and management for IoTs, Advanced VLSI modeling and simulation techniques, and design techniques for many emerging applications such as machine/deep learning, quantum/Ising computing, cyber and hardware security. This course has a large emphasis paper survey and presentations of many important techniques.

Who can take the course?

Both EE and CS undergraduate and graduate students are welcome as VLSI design are fundamental knowledge and skills for hardware implementation of today's complicated systems.

Course Topics and calendars

1. 1. Electromigration modeling and analysis techniques
2. 2. EM-aware optimization and management at the circuit and system levels
3. 3. Advanced circuit simulation and modeling techniques
4. 4. Thermal modeling and analysis techniques
5. 5. Dynamic thermal/power/reliability management and optimization
6. 6. Power delivery network and decoupling
7. 7. Emerging adiabatic Ising computing, approximate and stochastic computing
8. 8. Hardware security and mitigation techniques
9. 9. VLSI architecture and circuit design for machine/deep learning

Reference book

Lecture notes and related papers.

Grading

Paper survey and presentations : 50%

Final project, project report and project presentation: 50%

All of them will be graded on the scale of 0 to 100 with 100 being the maximum score.

Project

Each student (can form a team with no more than 2 people) need to work on a project in this course. The topics need to be approved by instructor.

VLSI Design Tutorial

https://github.com/sheldonucr/ee260_lab

Assignment

Home works assignment will be issued through iLearn