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11 results on '"Liu, Juzheng"'

1. A Memristor-Based Analog Accelerator for Solving Quadratic Programming Problems

Author

Cheng, Hsiang-Chun, primary, Su, Shiyu, additional, Palaria, Mayank, additional, Zhang, Qiaochu, additional, Yang, Ce, additional, Hossain, Sushmit, additional, Bena, Ryan, additional, Chen, Buyun, additional, Liu, Zerui, additional, Liu, Juzheng, additional, Rasul, Rezwan, additional, Nguyen, Quan, additional, Wu, Wei, additional, and Chen, Mike Shuo-Wei, additional

Published
2023
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2. Analog/Mixed-Signal Circuit Synthesis Enabled by the Advancements of Circuit Architectures and Machine Learning Algorithms

Author

Su, Shiyu, Zhang, Qiaochu, Hassanpourghadi, Mohsen, Liu, Juzheng, Rasul, Rezwan A, and Chen, Mike Shuo-Wei

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Emerging Technologies (cs.ET), Hardware_INTEGRATEDCIRCUITS, FOS: Electrical engineering, electronic engineering, information engineering, Computer Science - Emerging Technologies, Hardware_PERFORMANCEANDRELIABILITY, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control, Hardware_LOGICDESIGN, Machine Learning (cs.LG)
Abstract

Analog mixed-signal (AMS) circuit architecture has evolved towards more digital friendly due to technology scaling and demand for higher flexibility/reconfigurability. Meanwhile, the design complexity and cost of AMS circuits has substantially increased due to the necessity of optimizing the circuit sizing, layout, and verification of a complex AMS circuit. On the other hand, machine learning (ML) algorithms have been under exponential growth over the past decade and actively exploited by the electronic design automation (EDA) community. This paper will identify the opportunities and challenges brought about by this trend and overview several emerging AMS design methodologies that are enabled by the recent evolution of AMS circuit architectures and machine learning algorithms. Specifically, we will focus on using neural-network-based surrogate models to expedite the circuit design parameter search and layout iterations. Lastly, we will demonstrate the rapid synthesis of several AMS circuit examples from specification to silicon prototype, with significantly reduced human intervention., Comment: PREPRINT - accepted at IEEE/ACM Asia and South Pacific Design Automation Conference (ASP-DAC), 2022

Published
2022

6. A 10-GS/s 8-bit 2850-μm 2 Two-Step Time-Domain ADC With Speed and Efficiency Enhanced by the Delay-Tracking Pipelined-SAR TDC.

Author

Liu, Juzheng, Hassanpourghadi, Mohsen, and Chen, Mike Shuo-Wei

Subjects
SUCCESSIVE approximation analog-to-digital converters, TIME-digital conversion, ANALOG-to-digital converters, NYQUIST frequency, SIGNAL-to-noise ratio, COMPUTER architecture
Abstract

This article presents an 8-bit time-domain analog-to-digital converter (ADC) achieving ten-GS/s conversion speed with only two time-interleaved (TI) channels. A successive approximation register (SAR) time-to-digital converter (TDC) is implemented for the subpicosecond resolution time quantization with high power/area efficiency and low jitter. The throughput of the SAR TDC is enhanced by a unique delay-tracking pipelining technique to enable a 5-GS/s single-channel conversion. On the circuit level, the reference time generation for the SAR TDC is realized by the proposed selective delay tuning (SDT) cell for high efficiency and small reference time variation. Fabricated in the 14-nm FinFet CMOS technology, this ADC achieves a 37.2-dB signal-to-noise and distortion ratio (SNDR) and a 50.6-dB spurious-free dynamic range (SFDR) at the Nyquist input frequency, leading to a 24.8-fJ/conv-step Walden figure of merit with an active area of only 2850 $\mu \text{m}^{2}$. [ABSTRACT FROM AUTHOR]

Published
2022
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7. From Specification to Silicon: Towards Analog/Mixed-Signal Design Automation using Surrogate NN Models with Transfer Learning

Author

Liu, Juzheng, primary, Su, Shiyu, additional, Madhusudan, Meghna, additional, Hassanpourghadi, Mohsen, additional, Saunders, Samuel, additional, Zhang, Qiaochu, additional, Rasul, Rezwan, additional, Li, Yaguang, additional, Hu, Jiang, additional, Sharma, Arvind Kumar, additional, Sapatnekar, Sachin S., additional, Harjani, Ramesh, additional, Levi, Anthony, additional, Gupta, Sandeep, additional, and Chen, Mike Shuo-Wei, additional

Published
2021
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11. Study on mechanism of conducting and switching properties of Cu-TCNQ

Author

Wei Yu, Gu Zhongze, and Liu Juzheng

Subjects
Organic semiconductor, symbols.namesake, Materials science, Condensed matter physics, Band gap, Electrical resistivity and conductivity, Fermi level, symbols, Conductivity, Thermal conduction, Semimetal, Quasi Fermi level
Abstract

This paper outlines the band, conducting mechanism and switching effect of Cu-TCNQ. Cu-TCNQ belongs to trap controlled band conduction, it's conductivity is greatly affected by the overlap of neighboring molecular frontier orbitals whose change triggers off the switching phenomena of Cu-TCNQ.

Published
1992

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