COMP_ENG 393, 493: Advanced Low Power Digital and Mixed-signal Integrated Circuit Design

This course is not currently offered.


Basic knowledge in electronic circuit design.


Integrated circuits (IC) serve as the backbone of any information system and mobile devices.  This course provides an in-depth review of the advanced technology in integrated circuit design targeting low power mobile devices or emerging wearable biomedical systems.  Special focuses will be given to ultra-low power circuit design, error resilient circuit design, power management circuits and basic design of analog mixed-signal circuit.  Following a seminar format, detailed case study on circuit design techniques used by leading industrial players, e.g. Intel, IBM, Qualcomm etc. will be discussed in the class.

REQUIRED TEXTBOOKS: Not required. Materials will be distributed before or during the classes. 


  1. "CMOS VLSI Design: A Circuits and Systems Perspective" by Neil Weste and David Harris; 4th edition
  2. Jan M. Rabaey, Anantha Chandrakasan, Borivoje Nikolic, Digital Integrated Circuits (2nd Edition), Prentice Hall, 2003.
  3. Behzad Razavi, Design of Analog CMOS Integrated Circuits, McGraw-Hill Education, 2000.


COURSE GOALS: This course is intended to provide deeper understanding on advanced circuit technology in designing modern low power ICs.   After taking this course, the students will be able to design novel circuits and solve practical design challenges faced by current IC industry. This course serves as a jump-start for students who are interested in participating in further research or jobs in the area of integrated circuit design.



  • Overview on the development and growing trend of low power electronics;
  • Case study of ICs developed by Intel, IBM, TI, Qualcomm, etc.;
  • Advanced CMOS device development below 28nm and process challenges;
  • Design of ultra-low power near-threshold digital system and error-resilient digital circuits;
  • Advanced adaptive on-chip power/clock management techniques for mobile devices;
  • Low power design of energy harvesting and biomedical system;
  • IC Chips for Machine Learning, Neuromorphic design and AI;
  • Basic CMOS analog IC design and small-signal analysis;
  • Design of analog and mixed-signal building blocks: advanced on-chip voltage regulators; digital phase-locked loop (PLL);

PROJECTS: The students will work in a group to perform a project on a selected topic.  A written report and an oral presentation are needed at the end of the course.


  • Homework/Lab/Quiz: None; (small practice homework may apply)
  • Project/Presentation: 100%;
  • Final Exam – None

Who should take and how this course is compared with 391 or 303:

This course is advanced topic in IC design and targets at graduate or senior undergraduate students.  While 303 and 391 provides more basic training on how to design an integrated circuits, this course provides advanced circuit techniques and discusses many practical design issues.  This course will adapt to an open discussion environment where students learn through a lot of real circuit examples and projects.   

Students who are working on or plan to work on areas related to microprocessor design, computer architectures, design automation, semiconductor devices, low power embedded systems are highly encouraged to take this course.


  1. Ultra-low voltage processor design for biomedical applications;
  2. Error resilient digital circuits for energy efficient computing;
  3. Neural network accelerator design for machine learning based facial recognition;
  4. Energy harvesting circuit design using ambient power resources, e.g. solar, thermal, wireless;
  5. Circuits for energy efficient stochastic computing;
  6. On-chip sensor design for efficient voltage, process and temperature tracking;
  7. Advanced highly efficient power regulators for ultra-dynamic voltage scaling;
  8. Resonance based energy efficient circuit design;
  9. Ultra-low power analog/mixed-signal circuits for biomedical signal processing;
  10. IC design using emerging semiconductor devices, e.g. Carbon-nanotube FETs;
  11. Proposed topics from students based on their own research interests;