Fengbin Tu

2.0k citations
68 papers · 1.4k · h-index 19

Impact in

Papers in

Co-authors
Shouyi Yin (46 shared papers)Leibo Liu (33 shared papers)Shaojun Wei (39 shared papers)Peng Ouyang (11 shared papers)Shibin Tang (5 shared papers)Yuan Xie (17 shared papers)Yufei Ding (11 shared papers)Yiqi Wang (17 shared papers)
Journals
IEEE Journal of Solid-State Circuits (8 papers)IEEE Transactions on Circuits and Systems I Regular Papers (6 papers)IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (5 papers)IEEE Transactions on Computers (2 papers)Journal of Semiconductors (2 papers)
Partner nations
ChinaHong KongUnited States

In The Last Decade

Fengbin Tu

60 papers receiving 1.4k citations

Peers

Fengbin Tu
Comparison fields: 5 of 82
  • Hardware and Architecture 286
  • Computational Mathematics 22
  • Computer Vision and Pattern Recognition 586
  • Electrical and Electronic Engineering 872
  • Artificial Intelligence 423
Replace Jinmook Lee with:
Jinmook Lee South Korea
Liqiang He China
Antonio Puglielli United States
Yijin Guan China
Debbie Marr United States
Peng Ouyang China
Naveen Suda United States
Hiroki Nakahara Japan
Fengbin Tu relative to Jinmook Lee South Korea Jinmook Lee's profile →
Citations per field
00.5×2×4×5.5×
Jinmook Lee · 1×
Citations per year

Countries citing papers authored by Fengbin Tu

Since Specialization
Citations

This map shows the geographic impact of Fengbin Tu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Fengbin Tu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fengbin Tu more than expected).

Fields of papers citing papers by Fengbin Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fengbin Tu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Fengbin Tu. The network helps show where Fengbin Tu may publish in the future.

Co-authors

The 25 scholars most cited alongside Fengbin Tu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fengbin Tu Line = papers co-authored together Fengbin Tu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Convolutional Neural Network Architecture With Reconfigurable Computation Patterns
IEEE Transactions on Very Large Scale Integration (VLSI) Systems ·Fengbin Tu, Shouyi Yin, Peng Ouyang, Shibin Tang, Leibo Liu, Shaojun Wei
2017255
2
A High Energy Efficient Reconfigurable Hybrid Neural Network Processor for Deep Learning Applications
IEEE Journal of Solid-State Circuits ·Shouyi Yin, Peng Ouyang, Shibin Tang, Fengbin Tu, Xiudong Li, Shixuan Zheng, Tianyi Lu, Jiangyuan Gu, Leibo Liu, Shaojun Wei
2017174
3
A 28nm 29.2TFLOPS/W BF16 and 36.5TOPS/W INT8 Reconfigurable Digital CIM Processor with Unified FP/INT Pipeline and Bitwise In-Memory Booth Multiplication for Cloud Deep Learning Acceleration
2022 IEEE International Solid- State Circuits Conference (ISSCC) ·Fengbin Tu, Yiqi Wang, Zihan Wu, Ling Liang, Yufei Ding, Bongjin Kim, Leibo Liu, Shaojun Wei, Yuan Xie, Shouyi Yin
202294
4
DOTA: detect and omit weak attentions for scalable transformer acceleration
Rare & Special e-Zone (The Hong Kong University of Science and Technology) ·Zheng Qu, Liu Liu, Fengbin Tu, Zhaodong Chen, Yufei Ding, Yuan Xie
202277
5
A 1.06-to-5.09 TOPS/W reconfigurable hybrid-neural-network processor for deep learning applications
Rare & Special e-Zone (The Hong Kong University of Science and Technology) ·Shouyi Yin, Peng Ouyang, Shibin Tang, Fengbin Tu, Xiudong Li, Leibo Liu, Shaojun Wei
201771
6
RANA: Towards Efficient Neural Acceleration with Refresh-Optimized Embedded DRAM
Rare & Special e-Zone (The Hong Kong University of Science and Technology) ·Fengbin Tu, Weiwei Wu, Shouyi Yin, Leibo Liu, Shaojun Wei
201859
7
A High Throughput Acceleration for Hybrid Neural Networks With Efficient Resource Management on FPGA
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ·Shouyi Yin, Shibin Tang, Xinhan Lin, Peng Ouyang, Fengbin Tu, Leibo Liu, Shaojun Wei
201843
8
A 28nm 15.59µJ/Token Full-Digital Bitline-Transpose CIM-Based Sparse Transformer Accelerator with Pipeline/Parallel Reconfigurable Modes
2022 IEEE International Solid- State Circuits Conference (ISSCC) ·Fengbin Tu, Zihan Wu, Yiqi Wang, Ling Liang, Liu Liu, Yufei Ding, Leibo Liu, Shaojun Wei, Yuan Xie, Shouyi Yin
202243
9
ReDCIM: Reconfigurable Digital Computing- In -Memory Processor With Unified FP/INT Pipeline for Cloud AI Acceleration
IEEE Journal of Solid-State Circuits ·Fengbin Tu, Yiqi Wang, Zihan Wu, Ling Liang, Yufei Ding, Bongjin Kim, Leibo Liu, Shaojun Wei, Yuan Xie, Shouyi Yin
202241
10
TranCIM: Full-Digital Bitline-Transpose CIM-based Sparse Transformer Accelerator With Pipeline/Parallel Reconfigurable Modes
IEEE Journal of Solid-State Circuits ·Fengbin Tu, Zihan Wu, Yiqi Wang, Ling Liang, Liu Liu, Yufei Ding, Leibo Liu, Shaojun Wei, Yuan Xie, Shouyi Yin
202239
11
Evolver: A Deep Learning Processor With On-Device Quantization–Voltage–Frequency Tuning
IEEE Journal of Solid-State Circuits ·Fengbin Tu, Weiwei Wu, Yang Wang, Hongjiang Chen, Feng Xiong, Man Shi, Ning Li, Jinyi Deng, Tianbao Chen, Leibo Liu, Shaojun Wei, Yuan Xie, Shouyi Yin
202039
12
H2Learn: High-Efficiency Learning Accelerator for High-Accuracy Spiking Neural Networks
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ·Ling Liang, Zheng Qu, Zhaodong Chen, Fengbin Tu, Yujie Wu, Lei Deng, Guoqi Li, Peng Li, Yuan Xie
202132
13
GNA: Reconfigurable and Efficient Architecture for Generative Network Acceleration
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ·Jiale Yan, Shouyi Yin, Fengbin Tu, Leibo Liu, Shaojun Wei
201832
14
AEPE: An area and power efficient RRAM crossbar-based accelerator for deep CNNs
Rare & Special e-Zone (The Hong Kong University of Science and Technology) ·Shibin Tang, Shouyi Yin, Shixuan Zheng, Peng Ouyang, Fengbin Tu, Leiyue Yao, JinZhou Wu, Wenming Cheng, Leibo Liu, Shaojun Wei
201731
15
20.2 A 28nm 74.34TFLOPS/W BF16 Heterogenous CIM-Based Accelerator Exploiting Denoising-Similarity for Diffusion Models
Rare & Special e-Zone (The Hong Kong University of Science and Technology) ·Ruiqi Guo, Lei Wang, Xiaofeng Chen, Hao Sun, Zhiheng Yue, Yubin Qin, Huiming Han, Yang Wang, Fengbin Tu, Shaojun Wei, Hu Yang, Shouyi Yin
202422
16
Dynamic Sparse Attention for Scalable Transformer Acceleration
IEEE Transactions on Computers ·Liu Liu, Zheng Qu, Zhaodong Chen, Fengbin Tu, Yufei Ding, Yuan Xie
202221
17
16.4 TensorCIM: A 28nm 3.7nJ/Gather and 8.3TFLOPS/W FP32 Digital-CIM Tensor Processor for MCM-CIM-Based Beyond-NN Acceleration
Rare & Special e-Zone (The Hong Kong University of Science and Technology) ·Fengbin Tu, Yiqi Wang, Zihan Wu, Weiwei Wu, Leibo Liu, Yang Hu, Shaojun Wei, Shouyi Yin
202321
18
16.1 MuITCIM: A 28nm $2.24 \mu\mathrm{J}$/Token Attention-Token-Bit Hybrid Sparse Digital CIM-Based Accelerator for Multimodal Transformers
Rare & Special e-Zone (The Hong Kong University of Science and Technology) ·Fengbin Tu, Zihan Wu, Yiqi Wang, Weiwei Wu, Leibo Liu, Yang Hu, Shaojun Wei, Shouyi Yin
202321
19
DUET: Boosting Deep Neural Network Efficiency on Dual-Module Architecture
Rare & Special e-Zone (The Hong Kong University of Science and Technology) ·Liu Liu, Zheng Qu, Lei Deng, Fengbin Tu, Shuangchen Li, Xing Hu, Zhenyu Gu, Yufei Ding, Yuan Xie
202019
20
SDP: Co-Designing Algorithm, Dataflow, and Architecture for In-SRAM Sparse NN Acceleration
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ·Fengbin Tu, Yiqi Wang, Ling Liang, Yufei Ding, Leibo Liu, Shaojun Wei, Shouyi Yin, Yuan Xie
202218

About Fengbin Tu

Fengbin Tu is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Hardware and Architecture and Computer Networks and Communications, having authored 68 papers that have together received 1.4k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (28 papers), Advanced Neural Network Applications (26 papers), Ferroelectric and Negative Capacitance Devices (18 papers), Parallel Computing and Optimization Techniques (14 papers), Advanced Data Storage Technologies (11 papers), CCD and CMOS Imaging Sensors (9 papers), Embedded Systems Design Techniques (5 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Hardware and Architecture (286 citations), Computational Mathematics (22 citations), Computer Vision and Pattern Recognition (586 citations), Electrical and Electronic Engineering (872 citations) and Artificial Intelligence (423 citations). Fengbin Tu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Shouyi Yin, Leibo Liu, Shaojun Wei, Peng Ouyang, Shibin Tang, Yuan Xie, Yufei Ding, Yiqi Wang, Zihan Wu and Liu Liu. Their work appears in journals such as IEEE Journal of Solid-State Circuits, IEEE Transactions on Circuits and Systems I Regular Papers, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on Computers and Journal of Semiconductors.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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