Accelerated Extraction of Parasitic Capacitance in Metal Interconnects using Floating Random Walk Method

Authors

  • Dongyan Zhao State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China
  • Yanning Chen State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China
  • Fang Liu State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China
  • Yang Zhao State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China
  • Yali Shao State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China
  • Dong Zhang State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China
  • Yucheng Pan School of Electronics and Information Technology Sun Yat-sen University, 510006, China
  • Xiangyu Meng School of Electronics and Information Technology Sun Yat-sen University, 510006, China

DOI:

https://doi.org/10.13052/2024.ACES.J.391105

Keywords:

Capacitance extraction, electromagnetic analysis, floating random walk, interconnects

Abstract

This paper presents a novel and efficient approach for the rapid extraction of parasitic capacitance in metal interconnects of large-scale integrated circuit (IC) layouts. By conducting detailed electromagnetic field simulations, we propose a streamlined method that significantly reduces both computational complexity and runtime, making the extraction process more efficient. At the heart of this approach is the use of the floating random walk (FRW) algorithm, which precisely estimates both self-capacitance and mutual capacitance of conductors. A distinguishing feature of this method is the incorporation of error thresholds, which provide a dynamic mechanism to adjust the trade-off between extraction speed and accuracy. This flexibility allows the method to adapt to varying layout complexities while maintaining a high level of precision. Experimental results reveal that, compared to traditional electromagnetic simulation tools such as ANSYS Maxwell, the proposed method achieves up to 120 times faster capacitance extraction, with accuracy deviations containedwithin 20%.

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Author Biographies

Dongyan Zhao, State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China

Dongyan Zhao received the B.S. degree and the M.S. degree in mechanical manufacturing from Shanghai Jiao Tong University in 1992 and 1998, respectively. Zhao is professor senior engineer, expert obtaining the special allowance of State Council, IEEE Senior member. Zhao is general manager of Beijing Smartchip Microelectronics Technology Co. Ltd, established the first chip R & D team in China’s power industry, built the largest industrial chip design enterprise in China. Zhao was duly elected a chief expert of State Grid Corporation of China in 2022.

Yanning Chen, State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China

Yanning Chen received the B.S. degree in computer science from Capital Normal University in 2002 and received the M.S. degree in electronic and communication engineering from Beijing University of Posts and Telecommunications in 2018. She is senior engineer, director of Research and Development center, Beijing Smartchip Microelectronics Technology Co. Ltd. She has significantly contributed to industrial chip reliability by addressing key technical challenges, developing technical standards, and establishing a quality assurance system for industrial chips.

Fang Liu, State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China

Fang Liu received the Ph.D. degree from Tianjin University, Tianjin, China, in 2010. In 2015, she joined Beijing Smartchip Microelectronics Technology Co. Ltd., Beijing, China. Her current research interests include reliability of integrated circuits and semiconductor devices.

Yang Zhao, State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China

Yang Zhao Senior Engineer, manager of R&D Department of BeijingSmartchip Microelectronics Technology Co. Ltd. He has long beenengaged in the technical work ofindustrial chip testing and verification. He has more than 10 years of technical experience in the fields of IC-EMC, IC failure analysis and reliability. He is mainly responsible for the monitoring and analysis of the electric power field environment and the formulation of the related technical standards for the chips used in the electric power terminal. He has participated in the formulation /revision standard for more than 10 items, published six articles and 13 patents.

Yali Shao, State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China

Yali Shao received the B.S. and M.S. degrees in electronic engineering from Zhejiang University, Hangzhou, China, in 2008 and 2011, respectively. She was in Texas Instruments from 2011 to 2017, and then in Analog Devices Inc. from 2017 to 2021. She current is in Beijing Smartchip Microelectronics Technology Co. Ltd. since 2021. Her research interests include analog IC design (Power IC, Driver IC, Isolation IC, and ADC IC), analog mixed-signal design and automation, process and device basic IP, such as OTP, IO, ESD, STD.

Dong Zhang, State Grid Key Laboratory of Power Industrial Chip Reliability Technology Beijing Smartchip Microelectronics Technology Co. Ltd., 100192, China

Dong Zhang received the B.S degree in applied physics from Lanzhou University of Technology, Lanzhou, China, in 2008. He then worked at RFMD (Beijing) where he was engaged in IC testing, reliability and failure analysis. In 2011, he joined Beijing Smartchip Microelectronics Technology Co. Ltd. and is responsible for analog IC automated design related work. His current research interests include analog circuit sizing and layout automation.

Yucheng Pan, School of Electronics and Information Technology Sun Yat-sen University, 510006, China

Yucheng Pan received his B.S. degree from Sun Yat-sen University, Guangdong, China, in 2022. He is currently a second-year graduate student at Sun Yat-sen University. His research interests include EDA technology for analog integrated circuits, with a particular focus on analog integrated circuit layout and routing.

Xiangyu Meng, School of Electronics and Information Technology Sun Yat-sen University, 510006, China

Xiangyu Meng received the B.Sc. and Ph.D. degrees in electrical engineering from Tsinghua University, Beijing, China, in 2011 and 2017, respectively. From 2017 to 2018, he was a Post-Doctoral Fellow with the Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong. He is currently an Associate Professor with the School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China. His research interests include analog and RF IC design automation.

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Published

2024-11-30

How to Cite

[1]
D. . Zhao, “Accelerated Extraction of Parasitic Capacitance in Metal Interconnects using Floating Random Walk Method”, ACES Journal, vol. 39, no. 11, pp. 970–979, Nov. 2024.

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