Ming Cheng (成铭)


Ming Cheng received M.S. degree in the Department of Electronic Engineering, Tsinghua University, Beijing, China. He is currently working in NVIDIA, Shanghai.

Contact

Address: 4-205,Rohm Building,Tsinghua University,Beijing,China
Email: cNOSPAMMINGhengm15☺mails·tsinghua·edu·cn
Phone: 13051317738

Selected Publications


Journal Articles

  • Ming Cheng, Lixue Xia, Zhenhua Zhu, Yi Cai, Yuan Xie, Yu Wang, Huazhong Yang, TIME: A Training-in-memory Architecture for RRAM-based Deep Neural Networks , to appear in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2019. pdf

Conference Papers

  • Yi Cai, Tianqi Tang, Lixue Xia, Ming Cheng, Zhenhua Zhu, Yu Wang, Huazhong Yang, Training Low Bitwidth Convolutional Neural Networks on RRAM , in Proceedings of the 23rd Asia and South Pacific Design Automation Conference (ASP-DAC), 2018, pp.117-122. pdf
  • Jilan Lin, Lixue Xia, Zhenhua Zhu, Hanbo Sun, Yi Cai, Hui Gao, Ming Cheng, Xiaoming Chen, Yu Wang and Huazhong Yang, Rescuing Memristor-based Computing with Non-linear Resistance Levels , in DATE 2018, 2018, pp.407-412. pdf
  • Wenqin Huangfu, Lixue Xia, Ming Cheng, Xilin Yin, Tianqi Tang, Boxun Li, Krishnendu Chakrabarty, Yuan Xie, Yu Wang, Huazhong Yang, Computation-Oriented Fault-Tolerance Schemes for RRAM Computing Systems , in Proceedings of the 22nd Asia and South Pacific Design Automation Conference (ASP-DAC), 2017, pp.794-799. pdf slide
  • Ming Cheng, Lixue Xia, Zhenhua Zhu, Yi Cai, Yuan Xie, Yu Wang, Huazhong Yang, TIME:A Training-in-memory Architecture for Memristor-based Deep Neural Network , in Design Automation Conference (DAC), 2017, pp.26:1-26:6. pdf slide
  • Fang Su, Wei-Hao Chen, Lixue Xia, Chieh-Pu Lo, Tianqi Tang, Zhibo Wang, Kuo-Hsiang Hsu, Ming Cheng, Jun-Yi Li, Yuan Xie, Yu Wang, Meng-Fan Chang, Huazhong Yang, Yongpan Liu, A 462GOPs/J RRAM-Based Nonvolatile Intelligent Processor for Energy Harvesting IoE System Featuring Nonvolatile Logics and Processing-In-Memory , in IEEE Symposium on VLSI Circuits (VLSIC), 2017. pdf
  • Yu Wang, Lixue Xia, Ming Cheng, Tianqi Tang, Boxun Li, Huazhong Yang, RRAM Based Learning Acceleration , in Compliers, Architectures, and Sythesis of Embedded Systems (CASES) invited talk, 2016, pp.1-2. pdf
  • Lixue Xia, Tianqi Tang, Wenqin Huangfu, Ming Cheng, Xiling Yin, Boxun Li, Yu Wang, Huazhong Yang, Switched by Input: Power Efficient Structure for RRAM-based Convolutional Neural Network , in Design Automation Conference (DAC), 2016, pp.125:1-125:6. pdf slide
  • Yu Wang, Lixue Xia, Tianqi Tang, Boxun Li, Song Yao, Ming Cheng, Huazhong Yang, Low Power Convolutional Neural Networks on a Chip , in ISCAS, 2016, pp.129-132. pdf slide

copyright 2019 © NICS Lab of Tsinghua University