Jinming Lu

According to our database, Jinming Lu authored at least 19 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

WinTA: An Efficient Reconfigurable CNN Training Accelerator With Decomposition Winograd.

Jinming Lu, Hui Wang, Jun Lin, Zhongfeng Wang

IEEE Trans. Circuits Syst. I Regul. Pap., February, 2024

2023

An Efficient Training Accelerator for Transformers With Hardware-Algorithm Co-Optimization.

Haikuo Shao, Jinming Lu, Meiqi Wang, Zhongfeng Wang

IEEE Trans. Very Large Scale Integr. Syst., November, 2023

ETA: An Efficient Training Accelerator for DNNs Based on Hardware-Algorithm Co-Optimization.

Jinming Lu, Chao Ni, Zhongfeng Wang

IEEE Trans. Neural Networks Learn. Syst., October, 2023

Cathode Shape Design for Steady-State Electrochemical Machining.

Jinming Lu, Ewald A. Werner

Algorithms, February, 2023

An FPGA-Based Reconfigurable CNN Training Accelerator Using Decomposable Winograd.

Hui Wang, Jinming Lu, Jun Lin, Zhongfeng Wang

Proceedings of the IEEE Computer Society Annual Symposium on VLSI, 2023

Data Analysis for Machine Sound Detection: Challenges, Methods, and Future Trends.

Mingming Zhang, Liu Jie, Jinming Lu

Proceedings of the 16th International Congress on Image and Signal Processing, 2023

2022

THETA: A High-Efficiency Training Accelerator for DNNs With Triple-Side Sparsity Exploration.

Jinming Lu, Jian Huang, Zhongfeng Wang

IEEE Trans. Very Large Scale Integr. Syst., 2022

An Efficient Hardware Architecture for DNN Training by Exploiting Triple Sparsity.

Jian Huang, Jinming Lu, Zhongfeng Wang

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

An Efficient CNN Training Accelerator Leveraging Transposable Block Sparsity.

Mingyang Xu, Jinming Lu, Zhongfeng Wang, Jun Lin

Proceedings of the 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2022

2021

Evaluations on Deep Neural Networks Training Using Posit Number System.

Jinming Lu, Chao Fang, Mingyang Xu, Jun Lin, Zhongfeng Wang

IEEE Trans. Computers, 2021

A Reconfigurable Accelerator for Generative Adversarial Network Training Based on FPGA.

Tongtong Yin, Wendong Mao, Jinming Lu, Zhongfeng Wang

Proceedings of the IEEE Computer Society Annual Symposium on VLSI, 2021

An FPGA-Based Reconfigurable Accelerator for Low-Bit DNN Training.

Haikuo Shao, Jinming Lu, Jun Lin, Zhongfeng Wang

Proceedings of the IEEE Computer Society Annual Symposium on VLSI, 2021

2020

A Reconfigurable DNN Training Accelerator on FPGA.

Jinming Lu, Jun Lin, Zhongfeng Wang

Proceedings of the IEEE Workshop on Signal Processing Systems, 2020

LBFP: Logarithmic Block Floating Point Arithmetic for Deep Neural Networks.

Chao Ni, Jinming Lu, Jun Lin, Zhongfeng Wang

Proceedings of the 2020 IEEE Asia Pacific Conference on Circuits and Systems, 2020

2019

E-LSTM: An Efficient Hardware Architecture for Long Short-Term Memory.

Meiqi Wang, Zhisheng Wang, Jinming Lu, Jun Lin, Zhongfeng Wang

IEEE J. Emerg. Sel. Topics Circuits Syst., 2019

A Hardware-Oriented and Memory-Efficient Method for CTC Decoding.

Siyuan Lu, Jinming Lu, Jun Lin, Zhongfeng Wang

IEEE Access, 2019

Training Deep Neural Networks Using Posit Number System.

Jinming Lu, Siyuan Lu, Zhisheng Wang, Chao Fang, Jun Lin, Zhongfeng Wang, Li Du

Proceedings of the 32nd IEEE International System-on-Chip Conference, 2019

A Low-Latency and Low-Complexity Hardware Architecture for CTC Beam Search Decoding.

Siyuan Lu, Jinming Lu, Jun Lin, Zhongfeng Wang, Li Du

Proceedings of the 2019 IEEE International Workshop on Signal Processing Systems, 2019

2018

Quantitative Prediction of 3-D Multiple Parameters of Tectonic Fractures in Tight Sandstone Reservoirs Based on Geomechanical Method.

Jianwei Feng, Junsheng Dai, Jinming Lu, Xizhe Li

IEEE Access, 2018