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一作/通讯作者论文
[1] Bing Li, Ying Wang , Yiran Chen, Hit-M: High-Throughput ReRAM-based PIM for Multi-Modal Neural Networks, to appear in 2020 International Conference On Computer Aided Design. (EI, CCF B 类)
[2] Songyun Qu, Bing Li, Ying Wang, Dawen Xu, Xiandong Zhao, Lei Zhang. RaQu: An automatic high-utilization CNN quantization and mapping framework for general-purpose RRAM Accelerator, 2020 Design Automation Conference (共一，CCF A)
[3] Ziru Li, Bing Li, Zichen Fan, and Hai Li. RED: an ReRAM-based Efficient Accelerator for Deconvolutional Computation. in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, doi: 10.1109/TCAD.2020.2981055. (通讯作者，CCF A， SCI中科院JCR 二区)
[4] Bing Li, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty, Hai Li. 3D-ReG: A 3D ReRAM-based Heterogeneous Architecture for Training Deep Neural Networks, ACM Journal on Emerging Technologies in Computing Systems 16 (2), 1-24, 2020 (SCI, 影响因子: 1.672)
[5] Bing Li, Mengjie Mao, Xiaoxiao Liu, Tao Liu, Zihao Liu, Wujie Wen, Yiran Chen and Hai Li. Thread Batching for High-performance Energy-efficient GPU Memory Design, ACM Journal on Emerging Technologies in Computing Systems. 15(4): 39:1-39:21 (2019). DOI:https://doi.org/10.1145/3330152. (SCI, 影响因子: 1.672)
[6] Qilin Zheng, Jian Kang, Zongwei Wang, Yimao Cai, Ru Huang, Bing Li, Yiran Chen and Hai Li. Enhance the Robustness to Time Dependent Variability of ReRAM-Based Neuromorphic Computing Systems with Regularization and 2R Synapse, in 2019 IEEE International Symposium on Circuits and Systems (ISCAS), Sapporo, Japan, 2019, 26-29 May, pp. 1-5. doi: 10.1109/ISCAS.2019.8702756 (共一)
[7] Bing Li, Bonan Yan, Hai Helen Li. An Overview of In-memory Processing with Emerging Non-volatile Memory for Data-intensive Applications, In Proceedings of the 2019 on Great Lakes Symposium on VLSI (GLSVLSI '19). ACM, New York, NY, USA, 381-386. DOI: https://doi.org/10.1145/3299874.3319452
[8] Bing Li, Bonan Yan, Chenchen Liu, Hai Helen Li. Build Reliable and Efficient Neuromorphic Design with Memristor Technology, in 24th Asia and South Pacific Design Automation Conference (ASP-DAC), 2019, pp. 224-229. (EI)
[9] Zichen Fan, Ziru Li, Bing Li, Hai Li. RED: A ReRAM-based Deconvolution Accelerator, in Design, in Automation & Test in Europe Conference & Exhibition (DATE), 2019, pp. 1763-1768. (共一及通信作者, EI, CCF B类)
[10] Bing Li, Fan Chen, Wang Kang, Weisheng Zhao, Yiran Chen and Hai Helen Li. Design and Data Management for Magnetic Racetrack Memory, in 2018 IEEE International Symposium on Circuits and Systems (ISCAS), 2018, pp 1-4.
[11] Bing Li, Linghao Song, Fan Chen, Xuehai Qian, Yiran Chen, Hai Helen Li. ReRAM-based accelerator for deep learning, in Design, Automation & Test in Europe Conference & Exhibition (DATE), 2018, pp 815-820. (EI, CCF B类)
[12] Bing Li, Wei Wen, Jiachen Mao, Sicheng Li, Yiran Chen, Hai Helen Li. Running sparse and low-precision neural network: When algorithm meets hardware, in 23th Asia and South Pacific Design Automation Conference (ASP-DAC), 2018, pp 534-539. (EI)
[13] Bing Li, Yu Hu, Ying Wang, Jing Ye, and Xiaowei Li. Power-Utility-Driven Write Management for MLC PCM. ACM Journal on Emerging Technologies in Computing Systems (JETC) 13.3 (2017): 50. (SCI, 影响因子: 1.672)
[14] Bing Li, ShuChang Shan, Yu Hu, Xiaowei Li. A Dynamic Adjustment Design for Hybrid Fault Tolerant Code in Memory System (面向内存的混合容错编码动态调节设计), in Journal of Computer-Aided Design & Computer Graphics (JCAD, 计算机辅助设计与图形学学报), Volume 26 Issue 9, September 2014. (EI, 中文核心期刊)
[15] Bing Li, Yu Hu, Xiaowei Li, Short-SET: An energy-efficient write scheme for MLC PCM, in IEEE Non-Volatile Memory Systems and Applications Symposium (NVMSA), 2014, pp. 1-6. (EI)
[16] Bing Li, ShuChang Shan, Yu Hu, Xiaowei Li. Partial-SET: Write speedup of PCM main memory, in Design, Automation & Test in Europe Conference & Exhibition (DATE), 2014, pp. 1-4. (EI, CCF B类)
[17] Bing Li, ShuChang Shan, Yu Hu, Xiaowei Li. Tolerating Noise in MLC PCM with Multi-Bit Error Correction Code, in 19th Pacific Rim International Symposium on Dependable Computing (PRDC), 2013, pp. 226-231. (EI)
合作论文(按对论文的贡献程度排名)
[1] Ying Wang, Bing Li, Mengdi Wang, Huawei Li, and Xiaowei Li, An Energy-Efficient Many-Core Accelerator Design for On-Chip Deep Reinforcement Learning, to appear in 2020 International Conference On Computer Aided Design.
[2] Bonan Yan, Bing Li, Ximing Qiao, Cheng-Xin Xue, Meng-Fan Chang, Yiran Chen, and Hai (Helen) Li. RRAM based In-Memory Computing: From Device and Large-Scale Integration System Perspectives, in Advanced Intelligent Systems.
[3] Chunpeng Wu, Ang Li, Bing Li, and Yiran Chen. Efficiently Learning a Robust Self-Driving Model with Neuron Coverage Aware Adaptive Filter Reuse, in 2019 IEEE International Workshop on Signal Processing Systems (SiPS).
[4] Xuyang Guo, Yuanjun Huang, Hsin-pai Cheng, Bing Li, Wei Wen, Siyuan Ma, Hai Li, Yiran Chen. Exploration of Automatic Mixed-Precision Search for Deep Neural Networks. 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), Hsinchu, Taiwan, 2019, pp. 276-278.
[5] Biresh Kumar Joardar, Bing Li, Janardhan Rao Doppa, Hai Li, Partha Pratim Pande, Krishnendu Chakrabarty. "REGENT: A Heterogeneous ReRAM/GPU-based Architecture Enabled by NoC for Training CNNs". to appear in Design, Automation & Test in Europe Conference & Exhibition (DATE), 2019. (EI, CCF B类)
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