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Dive into the research topics where Yuangang Wang is active.

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Featured researches published by Yuangang Wang.


international symposium on low power electronics and design | 2015

An energy efficient and low cross-talk CMOS sub-THz I/O with surface-wave modulator and interconnect

Yuan Liang; Hao Yu; Junfeng Zhao; Wei Yang; Yuangang Wang

Free-space EM-wave based GHz interconnect has significant loss and crosstalk that cannot be deployed as low-power and dense I/Os for future network-on-chip (NoC) integration of many-core and memory. This paper proposes an energy-efficient and low-crosstalk sub-THz (0.1T-1T) I/O with use of surface-wave based modulator and interconnects in CMOS. By introducing sub-wavelength periodical corrugation structure onto transmission line, the surface-wave is established to propagate signal that is strongly localized on surface of top-layer metal wire, which results in low coupling into lossy substrate and neighboring metal wires. As such, significant power saving and cross-talk reduction can be observed with high communication bandwidth. In addition, a high on/off-ratio surface-wave modulator is also proposed to support on-chip THz communication. As designed in 65nm CMOS, the results have shown that the proposed surface-wave I/O interface achieves 25Gbps data rate and 0.016pJ/bit/mm energy efficiency at 140GHz carrier frequency over 20mm surface-wave channels. They can be placed with 2.4μm channel spacing and a -20dB crosstalk ratio. The surface-wave modulator also achieves significant reduction of radiation loss with 23dB extinction ratio.


international symposium on low power electronics and design | 2017

An energy-efficient and high-throughput bitwise CNN on sneak-path-free digital ReRAM crossbar

Leibin Ni; Zichuan Liu; Wenhao Song; Jianhua Yang; Hao Yu; Kanwen Wang; Yuangang Wang

Convolutional neural network (CNN) based machine learning requires a highly parallel as well as low power consumption (including leakage power) hardware accelerator. In this paper, we will present a digital ReRAM crossbar based CNN accelerator that can achieve significantly higher throughput and lower power consumption than state-of-arts. The CNN is trained with binary constraints on both weights and activations such that all operations become bitwise. With further use of 1-bit comparator, the bitwise CNN model can be naturally realized on a digital ReRAM-crossbar device. A novel sneak-path-free ReRAM-crossbar is further utilized for large-scale realization. Simulation experiments show that the bitwise CNN accelerator on the digital ReRAM crossbar achieves 98.3% and 91.4% accuracy on MNIST and CIFAR-10 benchmarks, respectively. Moreover, it has a peak throughput of 792GOPS at the power consumption of 6.3mW, which is 18.86 times higher throughput and 44.1 times lower power than CMOS CNN (non-binary) accelerators.


international microwave symposium | 2015

A 60GHz digitally-assisted power amplifier with 17.2dBm P sat , 11.3% PAE in 65nm CMOS

Yuan Liang; Nan Li; Fei Wei; Hao Yu; Xiuping Li; Junfeng Zhao; Wei Yang; Yuangang Wang

A digitally-assisted CMOS 60GHz PA is reported with high output power and improved power efficiency during power back-off. To combine large number of CMOS power transistors within compact area, a 2D distributed in-phase power combiner is utilized. Moreover, digitally-assisted self-tuning biasing is introduced for power back-off efficiency improvement, where DC power is reduced along with output power. One digitally-assisted 4-way power-combined PA prototype was implemented in 65nm CMOS process with measured output power of 17.2dBm, PAE of 11.3%, and up to 170~190% efficiency improvement during power back-off for the entire 7GHz band at 60GHz.


IEEE Transactions on Nanotechnology | 2017

A highly-parallel and energy-efficient 3D multi-layer CMOS-RRAM accelerator for tensorized neural network

Hantao Huang; Leibin Ni; Kanwen Wang; Yuangang Wang; Hao Yu


Archive | 2016

Information Storage Apparatus and Method

Yinyin Lin; Yarong Fu; Kai Yang; Wei Yang; Yuangang Wang; Junfeng Zhao


IEEE Transactions on Nanotechnology | 2018

A Highly Parallel and Energy Efficient Three-Dimensional Multilayer CMOS-RRAM Accelerator for Tensorized Neural Network

Hantao Huang; Leibin Ni; Kanwen Wang; Yuangang Wang; Hao Yu


Archive | 2017

MAGNETIC STORAGE APPARATUS AND INFORMATION STORAGE METHOD USING SAME

Kai Yang; Junfeng Zhao; Yuangang Wang; Wei Yang; Yinyin Lin; Yarong Fu


Archive | 2017

Write Apparatus and Magnetic Memory

Yarong Fu; Junfeng Zhao; Yuangang Wang; Wei Yang; Yinyin Lin; Kai Yang


Archive | 2015

Write device and magnetic memory

Yarong Fu; Junfeng Zhao; Yuangang Wang; Wei Yang; Yinyin Lin; Kai Yang


Archive | 2015

Magnetic storage device and information storage method using same

Kai Yang; Junfeng Zhao; Yuangang Wang; Wei Yang; Yinyin Lin; Yarong Fu

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Hao Yu

Nanyang Technological University

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Leibin Ni

Nanyang Technological University

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Hantao Huang

Nanyang Technological University

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Yuan Liang

Nanyang Technological University

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