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ORCIDBing Li 0017
Person information
- affiliation: Duke University, Durham, NC, USA
- affiliation (former): Chinese Academy of Sciences, Institute of Computing Technology, Key Laboratory of Computer System and Architecture, Beijing, China
Other persons with the same name
- Bing Li — disambiguation page
- Bing Li 0001
![[0000-0002-5888-6735]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-5888-6735")
— Chinese Academy of Sciences, Institute of Automation, National Laboratory of Pattern Recognition, Beijing, China (and 1 more) - Bing Li 0002 — Agency for Science, Technology and Research, A*STAR, Centre for Frontier AI Research, Singapore (and 2 more)
- Bing Li 0003 — Chongqing Jiaotong University, College of Sciences, China
- Bing Li 0004 — Shenzhen University, China (and 3 more)
- Bing Li 0005 — Technical University of Munich, Institute for Electronic Design Automation, Germany
- Bing Li 0006 — Hefei University of Technology, School of Electrical and Automation Engineering, China (and 1 more)
- Bing Li 0007 — Wuhan University of Technology, School of Economics, China (and 1 more)
- Bing Li 0008 — Clemson University, Department of Automotive Engineering, SC, USA (and 2 more)
- Bing Li 0009 — University of Virginia, Charlottesville, VA, USA
- Bing Li 0010 — Wuhan University, School of Computer / State Key Lab of Software Engineering, China (and 1 more)
- Bing Li 0011 — Shenzhen University, College of Electronic Science and Technology, China (and 1 more)
- Bing Li 0012 — Georgia State University, Department of Computer Science, Atlanta, GA, USA
- Bing Li 0013 — ETH Zurich, Department of Mechanical and Process Engineering, Reliability and Risk Engineering Laboratory, Switzerland
- Bing Li 0014 — Qilu University of Technology (Shandong Academy of Sciences), School of Information, Jinan, China
- Bing Li 0015 — Harbin Institute of Technology, Department of Mechanical Engineering and Automation, Shenzhen, China (and 1 more)
- Bing Li 0016 — Southwest Jiaotong University, School of Electrical Engineering, Chengdu, China (and 2 more)
- Bing Li 0018 — Lanzhou University, School of Information Science and Engineering, China
- Bing Li 0019 — Arizona State University, Tempe, USA
- Bing Li 0020 — Yunnan Minzu University, School of Mathematics and Computer Science, China
- Bing Li 0021 — Jilin University, College of Computer Science and Technology, Changchun, China
- Bing Li 0022 — Xi'an Jiaotong University, Institute of Microelectronics, China
- Bing Li 0023 — Xi'an Jiaotong University, State Key Laboratory for Manufacturing Systems Engineering, China
- Bing Li 0024 — King Abdullah University of Science and Technology, Visual Computing Center, Thuwal, Saudi Arabia (and 2 more)
- Bing Li 0025 — Tongji University, School of Software Engineering, Shanghai, China (and 1 more)
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2020 – today
- 2024
[j10]Yintao He, Bing Li, Ying Wang, Cheng Liu, Huawei Li, Xiaowei Li:
A Task-Adaptive In-Situ ReRAM Computing for Graph Convolutional Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(9): 2635-2646 (2024)- [c26]Songyun Qu, Shixin Zhao, Bing Li, Yintao He, Xuyi Cai, Lei Zhang, Ying Wang:
CIM-MLC: A Multi-level Compilation Stack for Computing-In-Memory Accelerators. ASPLOS (2) 2024: 185-200 - [c25]Yibo Du, Ying Wang, Bing Li, Fuping Li, Shengwen Liang, Huawei Li, Xiaowei Li, Yinhe Han:
Chiplever: Towards Effortless Extension of Chiplet-based System for FHE. DAC 2024: 243:1-243:6 - [i6]Songyun Qu, Shixin Zhao, Bing Li, Yintao He, Xuyi Cai, Lei Zhang, Ying Wang:
CIM-MLC: A Multi-level Compilation Stack for Computing-In-Memory Accelerators. CoRR abs/2401.12428 (2024) - [i5]Yilun Zhao, Bingmeng Wang, Wenle Jiang, Xiwei Pan, Bing Li, Yinhe Han, Ying Wang:
SuperEncoder: Towards Universal Neural Approximate Quantum State Preparation. CoRR abs/2408.05435 (2024) - 2023
- [j9]Hao Lv, Bing Li, Lei Zhang, Cheng Liu, Ying Wang:
Variation Enhanced Attacks Against RRAM-Based Neuromorphic Computing System. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(5): 1588-1596 (2023) - [j8]Songyun Qu, Bing Li, Shixin Zhao, Lei Zhang, Ying Wang:
A Coordinated Model Pruning and Mapping Framework for RRAM-Based DNN Accelerators. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(7): 2364-2376 (2023) - [c24]Yanjun Li, Chunshan Zu, Bingqian Wang, Zhenhua Zhu, Yaojun Zhang, Ran Duan, Bing Li, Bonan Yan:
SRAM-Based Processing-In-Memory Design with Kullback-Leibler Divergence-Based Dynamic Precision Quantization. ACM Great Lakes Symposium on VLSI 2023: 189-192 - [c23]Yilun Zhao, Yu Chen, He Li, Ying Wang, Kaiyan Chang, Bingmeng Wang, Bing Li, Yinhe Han:
Full State Quantum Circuit Simulation Beyond Memory Limit. ICCAD 2023: 1-9 - [i4]Hao Lv, Bing Li, Lei Zhang, Cheng Liu, Ying Wang:
Variation Enhanced Attacks Against RRAM-based Neuromorphic Computing System. CoRR abs/2302.09902 (2023) - 2022
- [j7]Bing Li, Songyun Qu, Ying Wang:
An Automated Quantization Framework for High-Utilization RRAM-Based PIM. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(3): 583-596 (2022) - [c22]Yintao He, Songyun Qu, Ying Wang, Bing Li, Huawei Li, Xiaowei Li:
InfoX: an energy-efficient ReRAM accelerator design with information-lossless low-bit ADCs. DAC 2022: 97-102 - [c21]Bing Li, Hao Lv, Ying Wang, Yiran Chen:
Security Threat to the Robustness of RRAM-based Neuromorphic Computing System. iSES 2022: 267-271 - 2021
- [c20]Hao Lv, Bing Li, Ying Wang, Cheng Liu, Lei Zhang:
VADER: Leveraging the Natural Variation of Hardware to Enhance Adversarial Attack. ASP-DAC 2021: 487-492 - [c19]Songyun Qu, Bing Li, Ying Wang, Lei Zhang:
ASBP: Automatic Structured Bit-Pruning for RRAM-based NN Accelerator. DAC 2021: 745-750 - [c18]Mengdi Wang, Bing Li, Ying Wang, Cheng Liu, Xiaohan Ma, Xiandong Zhao, Lei Zhang:
MT-DLA: An Efficient Multi-Task Deep Learning Accelerator Design. ACM Great Lakes Symposium on VLSI 2021: 1-8 - [c17]Chengsi Gao, Bing Li, Ying Wang, Weiwei Chen, Lei Zhang:
Tenet: A Neural Network Model Extraction Attack in Multi-core Architecture. ACM Great Lakes Symposium on VLSI 2021: 21-26 - [c16]Farzaneh Zokaee, Bing Li, Fan Chen:
FeFET-based Process-in-Memory Architecture for Low-Power DNN Training. NANOARCH 2021: 1-6 - 2020
- [j6]Bing Li, Janardhan Rao Doppa, Partha Pratim Pande, Krishnendu Chakrabarty, Joe X. Qiu, Hai (Helen) Li:
3D-ReG: A 3D ReRAM-based Heterogeneous Architecture for Training Deep Neural Networks. ACM J. Emerg. Technol. Comput. Syst. 16(2): 20:1-20:24 (2020) - [j5]Ziru Li, Bing Li, Zichen Fan, Hai Li:
RED: A ReRAM-Based Efficient Accelerator for Deconvolutional Computation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(12): 4736-4747 (2020) - [c15]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. DAC 2020: 1-6 - [c14]Ying Wang, Mengdi Wang, Bing Li, Huawei Li, Xiaowei Li:
A Many-Core Accelerator Design for On-Chip Deep Reinforcement Learning. ICCAD 2020: 46:1-46:7 - [c13]Bing Li, Ying Wang, Yiran Chen:
HitM: High-Throughput ReRAM-based PIM for Multi-Modal Neural Networks. ICCAD 2020: 105:1-105:7
2010 – 2019
- 2019
- [j4]Bonan Yan, Bing Li, Ximing Qiao, Cheng-Xin Xue, Meng-Fan Chang, Yiran Chen, Hai Helen Li:
Resistive Memory-Based In-Memory Computing: From Device and Large-Scale Integration System Perspectives. Adv. Intell. Syst. 1(7): 1900068 (2019) - [j3]Qingli Guo, Jing Ye, Bing Li, Yu Hu, Xiaowei Li, Yazhu Lan, Guohe Zhang:
PUFPass: A password management mechanism based on software/hardware codesign. Integr. 64: 173-183 (2019) - [j2]Bing Li, Mengjie Mao, Xiaoxiao Liu, Tao Liu, Zihao Liu, Wujie Wen, Yiran Chen, Hai (Helen) Li:
Thread Batching for High-performance Energy-efficient GPU Memory Design. ACM J. Emerg. Technol. Comput. Syst. 15(4): 39:1-39:21 (2019) - [c12]Xuyang Guo, Yuanjun Huang, Hsin-Pai Cheng, Bing Li, Wei Wen, Siyuan Ma, Hai Helen Li, Yiran Chen:
Exploration of Automatic Mixed-Precision Search for Deep Neural Networks. AICAS 2019: 276-278 - [c11]Bing Li, Bonan Yan, Chenchen Liu, Hai (Helen) Li:
Build reliable and efficient neuromorphic design with memristor technology. ASP-DAC 2019: 224-229 - [c10]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. DATE 2019: 522-527 - [c9]Zichen Fan, Ziru Li, Bing Li, Yiran Chen, Hai Helen Li:
RED: A ReRAM-based Deconvolution Accelerator. DATE 2019: 1763-1768 - [c8]Bing Li, Bonan Yan, Hai Li:
An Overview of In-memory Processing with Emerging Non-volatile Memory for Data-intensive Applications. ACM Great Lakes Symposium on VLSI 2019: 381-386 - [c7]Qilin Zheng, Jian Kang, Zongwei Wang, Yimao Cai, Ru Huang, Bing Li, Yiran Chen, Hai Helen Li:
Enhance the Robustness to Time Dependent Variability of ReRAM-Based Neuromorphic Computing Systems with Regularization and 2R Synapse. ISCAS 2019: 1-5 - [i3]Bing Li, Mengjie Mao, Xiaoxiao Liu, Tao Liu, Zihao Liu, Wujie Wen, Yiran Chen, Hai Helen Li:
Thread Batching for High-performance Energy-efficient GPU Memory Design. CoRR abs/1906.05922 (2019) - [i2]Bing Li, Bonan Yan, Hai Li:
An Overview of In-memory Processing with Emerging Non-volatile Memory for Data-intensive Applications. CoRR abs/1906.06603 (2019) - [i1]Zichen Fan, Ziru Li, Bing Li, Yiran Chen, Hai Helen Li:
RED: A ReRAM-based Deconvolution Accelerator. CoRR abs/1907.02987 (2019) - 2018
- [c6]Bing Li, Wei Wen, Jiachen Mao, Sicheng Li, Yiran Chen, Hai Helen Li:
Running sparse and low-precision neural network: When algorithm meets hardware. ASP-DAC 2018: 534-539 - [c5]Bing Li, Linghao Song, Fan Chen, Xuehai Qian, Yiran Chen, Hai Helen Li:
ReRAM-based accelerator for deep learning. DATE 2018: 815-820 - [c4]Bing Li, Fan Chen, Wang Kang, Weisheng Zhao, Yiran Chen, Hai Li:
Design and Data Management for Magnetic Racetrack Memory. ISCAS 2018: 1-4 - 2017
- [j1]Bing Li, Yu Hu, Ying Wang, Jing Ye, Xiaowei Li:
Power-Utility-Driven Write Management for MLC PCM. ACM J. Emerg. Technol. Comput. Syst. 13(3): 50:1-50:22 (2017) - 2014
- [c3]Bing Li, Shuchang Shan, Yu Hu, Xiaowei Li:
Partial-SET: Write speedup of PCM main memory. DATE 2014: 1-4 - [c2]Bing Li, Yu Hu, Xiaowei Li:
Short-SET: An energy-efficient write scheme for MLC PCM. NVMSA 2014: 1-6 - 2013
- [c1]Bing Li, Shuchang Shan, Yu Hu, Xiaowei Li:
Tolerating Noise in MLC PCM with Multi-Bit Error Correction Code. PRDC 2013: 226-231
Coauthor Index
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last updated on 2024-12-26 01:53 CET by the dblp team
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