Tutorial Talk 1
Recent Advances in CMOS Temperature sensors
Tsinghua University
Temperature sensors are widely used in many applications to monitor and control physical, chemical, and biological processes. After decades of development, temperature sensors based on CMOS technologies have gained great success and popularity. These sensors are becoming smaller, more accurate, and more energy-efficient; their detection range is increasing, and they are becoming easier to calibrate and use. This tutorial will first review the sensing principles of different types of CMOS temperature sensors (BJT/MOSFET/resistor/thermal-diffusivity). Then, performance metrics and challenging temperature-sensing applications will be introduced. Next, the state-of-the-art sensors and the associated techniques will be elaborated. Finally, the tutorial will be summarized, and an outlook will be given.
Sining Pan received the B.Sc. degree in electronic engineering from Tsinghua University, Beijing, China, in 2013, and the M.Sc. And Ph.D. degrees (cum laude) in electrical engineering from the Delft University of Technology, Delft, The Netherlands, in 2016 and 2021, respectively. He was a Post-Doctoral Researcher with the Electronic Instrumentation Laboratory, Delft University of Technology. In 2022, he joined the School of Integrated Circuits, Tsinghua University, as an Assistant Professor. He has authored and coauthored over 30 technical articles, including 13 from ISSCC and 10 from IEEE JSSC. His research interests include smart sensors, CMOS frequency references, and Delta–Sigma modulators.
Dr. Pan was a recipient of the ADI Outstanding Student Designer Award in 2019 and the IEEE SSCS Predoctoral Achievement Award in 2020. He serves as a Technical Committee Member for A-SSCC.
Tutorial Talk 2
Mechanisms for Accelerating ADC Speed: Quantization Shortcuts
University of Macau
Accelerating the ADC speed purely replies on lithography scaling has come to its practical end. Classic high-speed ADC architectures, such as Flash and Pipeline, inevitably exhibit a suboptimal energy efficiency when designed with conventional circuits and sized up the critical components merely in a brute force manner. Alternatively, researchers are pursuing various mechanisms to shortcut the quantization process. Examples include exploiting different operational domains, employing asynchronous, pipelined, and parallel processing schemes. Contemporary state-of-the-art designs often incorporate multiple of these mechanisms to facilitate breakthroughs in speed while simultaneously retaining outstand energy efficiency. This tutorial systematically identifies and categories these advanced techniques, delves into their core mechanisms, and clarify the widely misunderstood concept of metastability exploitation.
Chi-Hang Chan received the B.S. degree in electrical engineering from University of Washington, Seattle, USA, in 2008, the M.S. and Ph.D. degree from the University of Macau, Macao, China, in 2012 and 2015, respectively. He was a special scientist at the University of California, Los Angeles, USA, in 2016, working high performance analog-digital converter (ADC). Prof. Chan is currently an Associate Professor at the University of Macau, Macao, China. His research interests include high-speed Nyquist, wideband oversampling ADCs, ADC calibrations, ring oscillator-based PLL, and mixed-signal circuits. He has published 18 ISSCC, 23 JSSC papers. He is the recipient of the Solid-State-Circuit-Society (SSCS) Pre-doctoral Achievement Award, 2015. He serves as a data converter subcommittee TPC member of IEEE A-SSCC 2023 and 2024.
Tutorial Talk 3
ASIC Hardware Solvers for Compute-Intensive Optimization Problems
UC Santa Barbara
Recently, there has been ever-increasing interest in developing alternative computing paradigms for complicated combinatorial optimization and decision problems with applications in finance, drug discovery, machine learning, and resource optimizations. The problems are highly compute-intensive and, hence, hard to solve with classical hardware with limited computing resources. The Ising machine is one of the alternative paradigms to solve combinatorial optimization problems (COPs) by searching the ground state of the Ising model implemented as a network of artificial spins in various hardware technologies, such as the ASIC implementations using CMOS technologies. Besides the Ising machine, recent hardware solvers (e.g., SAT solver) have been dedicated for solving specific problems, such as Boolean Satisfiability. This tutorial will introduce the implementations of recent ASIC hardware solvers, including the Ising machine and SAT solvers, focusing on their circuit-level implementations and discussing challenges, opportunities, and applications.
Bongjin Kim received the B.S. and M.S. degrees in Electrical Engineering from POSTECH, South Korea, in 2004 and 2006, respectively, and the Ph.D. degree from the University of Minnesota, MN, USA, in 2014. He was a high-speed mixed-signal circuit designer at Samsung Electronics from 2006 to 2010. While pursuing a Ph.D., he worked as a research intern at Texas Instruments, IBM TJ Watson Research, and Rambus. After Ph.D., he was a research staff at Rambus and a postdoc fellow at Stanford University. In 2017, he joined NTU, Singapore, as an Assistant Professor in the School of EEE. After 3 years at NTU, he joined ECE at the UC Santa Barbara. His research interests include VLSI circuit/chip designs for next-generation compute and communications, ASIC hardware accelerators for compute-intensive problems in broader applications of AI and ML. Prof. Kim received the NSF CAREER award. He is an Associate Editor of the IEEE Solid-State Circuits Letter and a TPC member of the IEEE CICC and ESSERC.
Tutorial Talk 4
THz RF Circuits
National Taiwan University
THz technology has been considered a potential candidate for the 6G wireless communication systems because of its ability to provide communication speeds of over 100 Gb/s through broad spectrums at THz frequencies. THz technology can also be used for sensing applications such as non-invasive biomedical imaging, concealed weapons and explosives detection, and semiconductor wafer inspection. Compared to optical methods, THz electronics offer advantages such as low cost, compactness, high integration, and high yield for mass production. However, designing THz electronics is challenging due to low supply voltages and limited transistor speeds. This tutorial delves into the design challenges of THz electronics using CMOS technologies, discusses layout optimization using electromagnetic simulations to improve transistor speed, and demonstrates powerful reciprocal embedding design techniques for the realization of sub-THz and THz amplifiers and oscillators operating near the maximum oscillation frequency fmax.
Chun-Hsing Li received the B.S. degree in electrophysics and the M.S. and Ph.D. degrees in electronics engineering from National Chiao Tung University, Hsinchu, Taiwan, in 2005, 2007, and 2013, respectively. In 2014, he joined MediaTek, Hsinchu, Taiwan, as a Senior Engineer. In 2014 and 2018, he was with the Department of Electrical Engineering, National Central University, Jhongli, Taiwan, and the Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan, respectively, as an Assistant Professor. He is currently an Associate Professor at the Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan. His current research interests include RF, millimeter-wave, and terahertz integrated circuit and system design. Dr. Li was a recipient of the Excellence in Teaching Award, National Taiwan University 2023.