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2020 – today
- 2023
[j9]Zhenhua Zhu, Hanbo Sun, Tongxin Xie, Yu Zhu, Guohao Dai
, Lixue Xia, Dimin Niu, Xiaoming Chen, Xiaobo Sharon Hu, Yu Cao, Yuan Xie, Huazhong Yang, Yu Wang:
MNSIM 2.0: A Behavior-Level Modeling Tool for Processing-In-Memory Architectures. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(11): 4112-4125 (2023)- 2021
- [c28]Shiqing Fan, Yi Rong, Chen Meng, Zongyan Cao, Siyu Wang, Zhen Zheng, Chuan Wu, Guoping Long, Jun Yang, Lixue Xia, Lansong Diao, Xiaoyong Liu, Wei Lin:
DAPPLE: a pipelined data parallel approach for training large models. PPoPP 2021: 431-445 - 2020
- [j8]Yi Cai, Tianqi Tang, Lixue Xia, Boxun Li, Yu Wang, Huazhong Yang:
Low Bit-Width Convolutional Neural Network on RRAM. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(7): 1414-1427 (2020) - [j7]Yi Cai, Yujun Lin, Lixue Xia, Xiaoming Chen, Song Han, Yu Wang, Huazhong Yang:
Long Live TIME: Improving Lifetime and Security for NVM-Based Training-in-Memory Systems. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(12): 4707-4720 (2020) - [j6]Mengyun Liu, Lixue Xia, Yu Wang, Krishnendu Chakrabarty:
Algorithmic Fault Detection for RRAM-based Matrix Operations. ACM Trans. Design Autom. Electr. Syst. 25(3): 29:1-29:31 (2020) - [c27]Zhenhua Zhu, Hanbo Sun, Kaizhong Qiu, Lixue Xia, Gokul Krishnan, Guohao Dai, Dimin Niu, Xiaoming Chen, Xiaobo Sharon Hu, Yu Cao, Yuan Xie, Yu Wang, Huazhong Yang:
MNSIM 2.0: A Behavior-Level Modeling Tool for Memristor-based Neuromorphic Computing Systems. ACM Great Lakes Symposium on VLSI 2020: 83-88 - [i1]Shiqing Fan, Yi Rong, Chen Meng, Zongyan Cao, Siyu Wang, Zhen Zheng, Chuan Wu, Guoping Long, Jun Yang, Lixue Xia, Lansong Diao, Xiaoyong Liu, Wei Lin:
DAPPLE: A Pipelined Data Parallel Approach for Training Large Models. CoRR abs/2007.01045 (2020)
2010 – 2019
- 2019
- [j5]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. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38(5): 834-847 (2019) - [j4]Lixue Xia, Mengyun Liu, Xuefei Ning, Krishnendu Chakrabarty, Yu Wang:
Fault-Tolerant Training Enabled by On-Line Fault Detection for RRAM-Based Neural Computing Systems. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38(9): 1611-1624 (2019) - [c26]Lixue Xia, Lansong Diao, Zhao Jiang, Hao Liang, Kai Chen, Li Ding, Shunli Dou, Zibin Su, Meng Sun, Jiansong Zhang, Wei Lin:
PAI-FCNN: FPGA Based Inference System for Complex CNN Models. ASAP 2019: 107-114 - [c25]Mengyun Liu, Lixue Xia, Yu Wang, Krishnendu Chakrabarty:
Fault tolerance in neuromorphic computing systems. ASP-DAC 2019: 216-223 - [c24]Zhenhua Zhu, Hanbo Sun, Yujun Lin, Guohao Dai, Lixue Xia, Song Han, Yu Wang, Huazhong Yang:
A Configurable Multi-Precision CNN Computing Framework Based on Single Bit RRAM. DAC 2019: 56 - [c23]Lansong Diao, Zhao Jiang, Hao Liang, Chang'an Ye, Kai Chen, Li Ding, Shunli Dou, Meng Sun, Lixue Xia, Jiansong Zhang, Wei Lin:
PAI-FCNN: FPGA Based CNN Inference System. FPGA 2019: 184 - [c22]Jiansong Zhang, Lixue Xia, Zhao Jiang, Hao Liang, Jiaoyan Chen, Shouda Liu, Wei Lin, Yuan Xie:
Ouroboros: An Inference Engine for Deep Learning Based TTS on Embedded Devices. Hot Chips Symposium 2019: 1-28 - 2018
- [j3]Lixue Xia, Wenqin Huangfu, Tianqi Tang, Xiling Yin, Krishnendu Chakrabarty, Yuan Xie, Yu Wang, Huazhong Yang:
Stuck-at Fault Tolerance in RRAM Computing Systems. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(1): 102-115 (2018) - [j2]Lixue Xia, Boxun Li, Tianqi Tang, Peng Gu, Pai-Yu Chen, Shimeng Yu, Yu Cao, Yu Wang, Yuan Xie, Huazhong Yang:
MNSIM: Simulation Platform for Memristor-Based Neuromorphic Computing System. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(5): 1009-1022 (2018) - [c21]Yi Cai, Tianqi Tang, Lixue Xia, Ming Cheng, Zhenhua Zhu, Yu Wang, Huazhong Yang:
Training low bitwidth convolutional neural network on RRAM. ASP-DAC 2018: 117-122 - [c20]Yi Cai, Yujun Lin, Lixue Xia, Xiaoming Chen, Song Han, Yu Wang, Huazhong Yang:
Long live TIME: improving lifetime for training-in-memory engines by structured gradient sparsification. DAC 2018: 107:1-107:6 - [c19]Jilan Lin, Lixue Xia, Zhenhua Zhu, Hanbo Sun, Yi Cai, Hui Gao, Ming Cheng, Xiaoming Chen, Yu Wang, Huazhong Yang:
Rescuing memristor-based computing with non-linear resistance levels. DATE 2018: 407-412 - [c18]Keni Qiu, Weiwen Chen, Yuanchao Xu, Lixue Xia, Yu Wang, Zili Shao:
A peripheral circuit reuse structure integrated with a retimed data flow for low power RRAM crossbar-based CNN. DATE 2018: 1057-1062 - [c17]Mengyun Liu, Lixue Xia, Yu Wang, Krishnendu Chakrabarty:
Design of fault-tolerant neuromorphic computing systems. ETS 2018: 1-9 - [c16]Zhenhua Zhu, Jilan Lin, Ming Cheng, Lixue Xia, Hanbo Sun, Xiaoming Chen, Yu Wang, Huazhong Yang:
Mixed size crossbar based RRAM CNN accelerator with overlapped mapping method. ICCAD 2018: 69 - [c15]Mengyun Liu, Lixue Xia, Yu Wang, Krishnendu Chakrabarty:
Fault Tolerance for RRAM-Based Matrix Operations. ITC 2018: 1-10 - [c14]Yuanhui Ni, Keni Qiu, Weiwen Chen, Lixue Xia, Yu Wang:
Low power driven loop tiling for RRAM crossbar-based CNN. SAC 2018: 375-380 - 2017
- [c13]Tianqi Tang, Lixue Xia, Boxun Li, Yu Wang, Huazhong Yang:
Binary convolutional neural network on RRAM. ASP-DAC 2017: 782-787 - [c12]Wenqin Huangfu, Lixue Xia, Ming Cheng, Xiling Yin, Tianqi Tang, Boxun Li, Krishnendu Chakrabarty, Yuan Xie, Yu Wang, Huazhong Yang:
Computation-oriented fault-tolerance schemes for RRAM computing systems. ASP-DAC 2017: 794-799 - [c11]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 Networks. DAC 2017: 26:1-26:6 - [c10]Lixue Xia, Mengyun Liu, Xuefei Ning, Krishnendu Chakrabarty, Yu Wang:
Fault-Tolerant Training with On-Line Fault Detection for RRAM-Based Neural Computing Systems. DAC 2017: 33:1-33:6 - 2016
- [j1]Lixue Xia, Peng Gu, Boxun Li, Tianqi Tang, Xiling Yin, Wenqin Huangfu, Shimeng Yu, Yu Cao, Yu Wang, Huazhong Yang:
Technological Exploration of RRAM Crossbar Array for Matrix-Vector Multiplication. J. Comput. Sci. Technol. 31(1): 3-19 (2016) - [c9]Yu Wang, Lixue Xia, Ming Cheng, Tianqi Tang, Boxun Li, Huazhong Yang:
RRAM based learning acceleration. CASES 2016: 9:1-9:2 - [c8]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. DAC 2016: 125:1-125:6 - [c7]Lixue Xia, Boxun Li, Tianqi Tang, Peng Gu, Xiling Yin, Wenqin Huangfu, Pai-Yu Chen, Shimeng Yu, Yu Cao, Yu Wang, Yuan Xie, Huazhong Yang:
MNSIM: Simulation platform for memristor-based neuromorphic computing system. DATE 2016: 469-474 - [c6]Xiaoming Chen, Lixue Xia, Yu Wang, Huazhong Yang:
Sparsity-oriented sparse solver design for circuit simulation. DATE 2016: 1580-1585 - [c5]Yu Wang, Lixue Xia, Tianqi Tang, Boxun Li, Song Yao, Ming Cheng, Huazhong Yang:
Low power Convolutional Neural Networks on a chip. ISCAS 2016: 129-132 - 2015
- [c4]Lixue Xia, Rong Luo, Bin Zhao, Yu Wang, Huazhong Yang:
An accurate and low-cost PM2.5 estimation method based on Artificial Neural Network. ASP-DAC 2015: 190-195 - [c3]Boxun Li, Lixue Xia, Peng Gu, Yu Wang, Huazhong Yang:
Merging the interface: power, area and accuracy co-optimization for RRAM crossbar-based mixed-signal computing system. DAC 2015: 13:1-13:6 - [c2]Tianqi Tang, Lixue Xia, Boxun Li, Rong Luo, Yiran Chen, Yu Wang, Huazhong Yang:
Spiking neural network with RRAM: can we use it for real-world application? DATE 2015: 860-865 - [c1]Yu Wang, Tianqi Tang, Lixue Xia, Boxun Li, Peng Gu, Huazhong Yang, Hai Li, Yuan Xie:
Energy Efficient RRAM Spiking Neural Network for Real Time Classification. ACM Great Lakes Symposium on VLSI 2015: 189-194
Coauthor Index
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