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ORCIDJinming Lu
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Journal Articles
- 2026
[j12]Jiayi Tian
, Jinming Lu, Hai Li, Xiangwei Wang, Cong Callie Hao, Ian A. Young, Zheng Zhang:
Ultra Memory-Efficient On-FPGA Training of Transformers via Tensor-Compressed Optimization. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 45(3): 1352-1365 (2026)- [j11]Hui Wang, Jinming Lu, Rui Ding, Weize Ma, Zhongfeng Wang, Jun Lin:
WiFlow: A Precision-Scalable DNN Training Accelerator Through Winograd Algorithm and Dataflow Co-Design. IEEE Trans. Circuits Syst. I Regul. Pap. 73(4): 2659-2672 (2026) - 2025
- [j10]Jinhong Lv, Yangyang Xu, Mengzhu Jiang, Yuanhao Lv, Jialu Sun, Jinming Lu, Lina Wang, Hongru Wang:
A DeepSeek-powered locally deployed closed-loop system for enhancing quality control in electronic nursing documentation: development and clinical validation. J. Am. Medical Informatics Assoc. 32(10): 1526-1532 (2025) - 2024
- [j9]Jinming Lu, Hui Wang, Jun Lin, Zhongfeng Wang:
WinTA: An Efficient Reconfigurable CNN Training Accelerator With Decomposition Winograd. IEEE Trans. Circuits Syst. I Regul. Pap. 71(2): 634-645 (2024) - 2023
- [j8]Jinming Lu, Ewald A. Werner:
Cathode Shape Design for Steady-State Electrochemical Machining. Algorithms 16(2): 67 (2023) - [j7]Jinming Lu, Chao Ni, Zhongfeng Wang:
ETA: An Efficient Training Accelerator for DNNs Based on Hardware-Algorithm Co-Optimization. IEEE Trans. Neural Networks Learn. Syst. 34(10): 7660-7674 (2023) - [j6]Haikuo Shao, Jinming Lu, Meiqi Wang, Zhongfeng Wang:
An Efficient Training Accelerator for Transformers With Hardware-Algorithm Co-Optimization. IEEE Trans. Very Large Scale Integr. Syst. 31(11): 1788-1801 (2023) - 2022
- [j5]Jinming Lu, Jian Huang, Zhongfeng Wang:
THETA: A High-Efficiency Training Accelerator for DNNs With Triple-Side Sparsity Exploration. IEEE Trans. Very Large Scale Integr. Syst. 30(8): 1034-1046 (2022) - 2021
- [j4]Jinming Lu, Chao Fang, Mingyang Xu, Jun Lin, Zhongfeng Wang:
Evaluations on Deep Neural Networks Training Using Posit Number System. IEEE Trans. Computers 70(2): 174-187 (2021) - 2019
- [j3]Siyuan Lu, Jinming Lu, Jun Lin, Zhongfeng Wang:
A Hardware-Oriented and Memory-Efficient Method for CTC Decoding. IEEE Access 7: 120681-120694 (2019) - [j2]Meiqi Wang, Zhisheng Wang, Jinming Lu, Jun Lin, Zhongfeng Wang:
E-LSTM: An Efficient Hardware Architecture for Long Short-Term Memory. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(2): 280-291 (2019) - 2018
- [j1]Jianwei Feng, Junsheng Dai, Jinming Lu, Xizhe Li:
Quantitative Prediction of 3-D Multiple Parameters of Tectonic Fractures in Tight Sandstone Reservoirs Based on Geomechanical Method. IEEE Access 6: 39096-39116 (2018)
Conference and Workshop Papers
- 2026
- [c13]Jiayi Tian, Ryan Solgi, Jinming Lu, Yifan Yang, Hai Li, Zheng Zhang:
FLAT-LLM: Fine-grained Low-rank Activation Space Transformation for Large Language Model Compression. EACL (Findings) 2026: 2988-3002 - [c12]Hui Wang, Weize Ma, Jinming Lu, Jun Lin:
HoloLUT: An Efficient LUT-Based Engine via Holistic Data Processing for Low-bit LLM Inference. ACM Great Lakes Symposium on VLSI 2026: 109-114 - 2025
- [c11]Jinming Lu, Minghao She, Wendong Mao, Zhongfeng Wang:
CDM-QTA: Quantized Training Acceleration for Efficient LoRA Fine-Tuning of Diffusion Model. ISCAS 2025: 1-5 - 2023
- [c10]Mingming Zhang, Liu Jie, Jinming Lu:
Data Analysis for Machine Sound Detection: Challenges, Methods, and Future Trends. CISP-BMEI 2023: 1-5 - [c9]Hui Wang, Jinming Lu, Jun Lin, Zhongfeng Wang:
An FPGA-Based Reconfigurable CNN Training Accelerator Using Decomposable Winograd. ISVLSI 2023: 1-6 - 2022
- [c8]Mingyang Xu, Jinming Lu, Zhongfeng Wang, Jun Lin:
An Efficient CNN Training Accelerator Leveraging Transposable Block Sparsity. AICAS 2022: 230-233 - [c7]Jian Huang, Jinming Lu, Zhongfeng Wang:
An Efficient Hardware Architecture for DNN Training by Exploiting Triple Sparsity. ISCAS 2022: 2802-2805 - 2021
- [c6]Tongtong Yin, Wendong Mao, Jinming Lu, Zhongfeng Wang:
A Reconfigurable Accelerator for Generative Adversarial Network Training Based on FPGA. ISVLSI 2021: 144-149 - [c5]Haikuo Shao, Jinming Lu, Jun Lin, Zhongfeng Wang:
An FPGA-Based Reconfigurable Accelerator for Low-Bit DNN Training. ISVLSI 2021: 254-259 - 2020
- [c4]Chao Ni, Jinming Lu, Jun Lin, Zhongfeng Wang:
LBFP: Logarithmic Block Floating Point Arithmetic for Deep Neural Networks. APCCAS 2020: 201-204 - [c3]Jinming Lu, Jun Lin, Zhongfeng Wang:
A Reconfigurable DNN Training Accelerator on FPGA. SiPS 2020: 1-6 - 2019
- [c2]Siyuan Lu, Jinming Lu, Jun Lin, Zhongfeng Wang, Li Du:
A Low-Latency and Low-Complexity Hardware Architecture for CTC Beam Search Decoding. SiPS 2019: 352-357 - [c1]Jinming Lu, Siyuan Lu, Zhisheng Wang, Chao Fang, Jun Lin, Zhongfeng Wang, Li Du:
Training Deep Neural Networks Using Posit Number System. SoCC 2019: 62-67
Informal and Other Publications
- 2025
- [i8]Jiayi Tian, Jinming Lu, Hai Li, Xiangwei Wang, Cong Hao, Ian A. Young, Zheng Zhang:
Ultra Memory-Efficient On-FPGA Training of Transformers via Tensor-Compressed Optimization. CoRR abs/2501.06663 (2025) - [i7]Jinming Lu, Jiayi Tian, Hai Li, Ian A. Young, Zheng Zhang:
FETTA: Flexible and Efficient Hardware Accelerator for Tensorized Neural Network Training. CoRR abs/2504.06474 (2025) - [i6]Jinming Lu, Minghao She, Wendong Mao, Zhongfeng Wang:
CDM-QTA: Quantized Training Acceleration for Efficient LoRA Fine-Tuning of Diffusion Model. CoRR abs/2504.07998 (2025) - [i5]Jiayi Tian, Ryan Solgi, Jinming Lu, Yifan Yang, Hai Li, Zheng Zhang:
FLAT-LLM: Fine-grained Low-rank Activation Space Transformation for Large Language Model Compression. CoRR abs/2505.23966 (2025) - [i4]Jinsong Zhang, Minghe Li, Jiayi Tian, Jinming Lu, Zheng Zhang:
Comprehensive Design Space Exploration for Tensorized Neural Network Hardware Accelerators. CoRR abs/2511.17971 (2025) - [i3]Jinming Lu, Jiayi Tian, Yequan Zhao, Hai Li, Zheng Zhang:
Tensor-Compressed and Fully-Quantized Training of Neural PDE Solvers. CoRR abs/2512.09202 (2025) - 2019
- [i2]Siyuan Lu, Jinming Lu, Jun Lin, Zhongfeng Wang:
A Hardware-Oriented and Memory-Efficient Method for CTC Decoding. CoRR abs/1905.03175 (2019) - [i1]Jinming Lu, Siyuan Lu, Zhisheng Wang, Chao Fang, Jun Lin, Zhongfeng Wang, Li Du:
Training Deep Neural Networks Using Posit Number System. CoRR abs/1909.03831 (2019)
Coauthor Index
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last updated on 2026-06-26 02:24 CEST by the dblp team
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