Fangxin Liu

According to our database, Fangxin Liu authored at least 40 papers between 2017 and 2024.

Collaborative distances:

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

2024

SPARK: Scalable and Precision-Aware Acceleration of Neural Networks via Efficient Encoding.

Fangxin Liu, Ning Yang, Haomin Li, Zongwu Wang, Zhuoran Song, Songwen Pei, Li Jiang

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2024

2023

A Point Cloud Video Recognition Acceleration Framework Based on Tempo-Spatial Information.

Zhuoran Song, Wanzhen Liu, Tao Yang, Fangxin Liu, Naifeng Jing, Xiaoyao Liang

IEEE Trans. Parallel Distributed Syst., December, 2023

DVHN: A Deep Hashing Framework for Large-Scale Vehicle Re-Identification.

Yongbiao Chen, Sheng Zhang, Fangxin Liu, Chenggang Wu, Kaicheng Guo, Zhengwei Qi

IEEE Trans. Intell. Transp. Syst., September, 2023

DTATrans: Leveraging Dynamic Token-Based Quantization With Accuracy Compensation Mechanism for Efficient Transformer Architecture.

Tao Yang, Fei Ma, Xiaoling Li, Fangxin Liu, Yilong Zhao, Zhezhi He, Li Jiang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., February, 2023

PASGCN: An ReRAM-Based PIM Design for GCN With Adaptively Sparsified Graphs.

Tao Yang, Dongyue Li, Fei Ma, Zhuoran Song, Yilong Zhao, Jiaxi Zhang, Fangxin Liu, Li Jiang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023

SoBS-X: Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural Network Accelerator.

Fangxin Liu, Zongwu Wang, Yongbiao Chen, Zhezhi He, Tao Yang, Xiaoyao Liang, Li Jiang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023

PSQ: An Automatic Search Framework for Data-Free Quantization on PIM-based Architecture.

Fangxin Liu, Ning Yang, Li Jiang

Proceedings of the 41st IEEE International Conference on Computer Design, 2023

HyperNode: An Efficient Node Classification Framework Using HyperDimensional Computing.

Haomin Li, Fangxin Liu, Yichi Chen, Li Jiang

Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023

PIMPR: PIM-based Personalized Recommendation with Heterogeneous Memory Hierarchy.

Tao Yang, Hui Ma, Yilong Zhao, Fangxin Liu, Zhezhi He, Xiaoli Sun, Li Jiang

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

SIMSnn: A Weight-Agnostic ReRAM-based Search-In-Memory Engine for SNN Acceleration.

Fangxin Liu, Wenbo Zhao, Zongwu Wang, Xiaokang Yang, Li Jiang

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

HyperAttack: An Efficient Attack Framework for HyperDimensional Computing.

Fangxin Liu, Haoming Li, Yongbiao Chen, Tao Yang, Li Jiang

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

IVQ: In-Memory Acceleration of DNN Inference Exploiting Varied Quantization.

Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yilong Zhao, Tao Yang, Yiran Chen, Li Jiang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

RePAST: A ReRAM-based PIM Accelerator for Second-order Training of DNN.

Yilong Zhao, Li Jiang, Mingyu Gao, Naifeng Jing, Chengyang Gu, Qidong Tang, Fangxin Liu, Tao Yang, Xiaoyao Liang

CoRR, 2022

A systematic study on benchmarking AI inference accelerators.

Zihan Jiang, Jiansong Li, Fangxin Liu, Wanling Gao, Lei Wang, Chuanxin Lan, Fei Tang, Lei Liu, Tao Li

CCF Trans. High Perform. Comput., 2022

L3E-HD: A Framework Enabling Efficient Ensemble in High-Dimensional Space for Language Tasks.

Fangxin Liu, Haomin Li, Xiaokang Yang, Li Jiang

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval.

Yongbiao Chen, Sheng Zhang, Fangxin Liu, Zhigang Chang, Mang Ye, Zhengwei Qi

Proceedings of the ICMR '22: International Conference on Multimedia Retrieval, Newark, NJ, USA, June 27, 2022

Supervised Contrastive Vehicle Quantization for Efficient Vehicle Retrieval.

Yongbiao Chen, Kaicheng Guo, Fangxin Liu, Yusheng Huang, Zhengwei Qi

Proceedings of the ICMR '22: International Conference on Multimedia Retrieval, Newark, NJ, USA, June 27, 2022

Randomize and Match: Exploiting Irregular Sparsity for Energy Efficient Processing in SNNs.

Fangxin Liu, Zongwu Wang, Wenbo Zhao, Yongbiao Chen, Tao Yang, Xiaokang Yang, Li Jiang

Proceedings of the IEEE 40th International Conference on Computer Design, 2022

DynSNN: A Dynamic Approach to Reduce Redundancy in Spiking Neural Networks.

Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Fei Dai

Proceedings of the IEEE International Conference on Acoustics, 2022

DTQAtten: Leveraging Dynamic Token-based Quantization for Efficient Attention Architecture.

Tao Yang, Dongyue Li, Zhuoran Song, Yilong Zhao, Fangxin Liu, Zongwu Wang, Zhezhi He, Li Jiang

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

Self-Terminating Write of Multi-Level Cell ReRAM for Efficient Neuromorphic Computing.

Zongwu Wang, Zhezhi He, Rui Yang, Shiquan Fan, Jie Lin, Fangxin Liu, Yueyang Jia, Chenxi Yuan, Qidong Tang, Li Jiang

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

SATO: spiking neural network acceleration via temporal-oriented dataflow and architecture.

Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Tao Yang, Zhezhi He, Xiaokang Yang, Li Jiang

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

EBSP: evolving bit sparsity patterns for hardware-friendly inference of quantized deep neural networks.

Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Zhezhi He, Naifeng Jing, Xiaoyao Liang, Li Jiang

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

PIM-DH: ReRAM-based processing-in-memory architecture for deep hashing acceleration.

Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Zhezhi He, Rui Yang, Qidong Tang, Tao Yang, Cheng Zhuo, Li Jiang

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

HAWIS: Hardware-Aware Automated WIdth Search for Accurate, Energy-Efficient and Robust Binary Neural Network on ReRAM Dot-Product Engine.

Qidong Tang, Zhezhi He, Fangxin Liu, Zongwu Wang, Yiyuan Zhou, Yinghuan Zhang, Li Jiang

Proceedings of the 27th Asia and South Pacific Design Automation Conference, 2022

SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks.

Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Li Jiang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

BISWSRBS: A Winograd-based CNN Accelerator with a Fine-grained Regular Sparsity Pattern and Mixed Precision Quantization.

Tao Yang, Zhezhi He, Tengchuan Kou, Qingzheng Li, Qi Han, Haibao Yu, Fangxin Liu, Yun Liang, Li Jiang

ACM Trans. Reconfigurable Technol. Syst., 2021

SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network.

Fangxin Liu, Wenbo Zhao, Yilong Zhao, Zongwu Wang, Tao Yang, Zhezhi He, Naifeng Jing, Xiaoyao Liang, Li Jiang

CoRR, 2021

Improving Neural Network Efficiency via Post-training Quantization with Adaptive Floating-Point.

Fangxin Liu, Wenbo Zhao, Zhezhi He, Yanzhi Wang, Zongwu Wang, Changzhi Dai, Xiaoyao Liang, Li Jiang

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network.

Fangxin Liu, Wenbo Zhao, Zhezhi He, Zongwu Wang, Yilong Zhao, Tao Yang, Jingnai Feng, Xiaoyao Liang, Li Jiang

Proceedings of the 39th IEEE International Conference on Computer Design, 2021

Bit-Transformer: Transforming Bit-level Sparsity into Higher Preformance in ReRAM-based Accelerator.

Fangxin Liu, Wenbo Zhao, Zhezhi He, Zongwu Wang, Yilong Zhao, Yongbiao Chen, Li Jiang

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021

IM3A: Boosting Deep Neural Network Efficiency via In-Memory Addressing-Assisted Acceleration.

Fangxin Liu, Wenbo Zhao, Zongwu Wang, Tao Yang, Li Jiang

Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021

PIMGCN: A ReRAM-Based PIM Design for Graph Convolutional Network Acceleration.

Tao Yang, Dongyue Li, Yibo Han, Yilong Zhao, Fangxin Liu, Xiaoyao Liang, Zhezhi He, Li Jiang

Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

2020

AUSN: Approximately Uniform Quantization by Adaptively Superimposing Non-uniform Distribution for Deep Neural Networks.

Fangxin Liu, Wenbo Zhao, Yanzhi Wang, Changzhi Dai, Li Jiang

CoRR, 2020

Characterizing the I/O Pipeline in the Deployment of CNNs on Commercial Accelerators.

Jiansong Li, Zihan Jiang, Fangxin Liu, Xiao Dong, Guangli Li, Xueying Wang, Wei Cao, Lei Liu, Yanzhi Wang, Tao Li, Xiaobing Feng

Proceedings of the IEEE International Conference on Parallel & Distributed Processing with Applications, 2020

2019

ExploreBP: A Simulation Tool for Mobile Browser Energy Optimization.

Jin Zhang, Xin Wei, Zhen Liu, Fangxin Liu, Tao Li, Tingjuan Lu, Xiaoli Gong

Proceedings of the Simulation Tools and Techniques - 11th International Conference, 2019

LHC: A Low-Power Heterogeneous Computing Method on Neural Network Accelerator.

Fangxin Liu, Kunpeng Xie, Cheng Gong, Shusheng Liu, Ye Lu, Tao Li

Proceedings of the 25th IEEE International Conference on Parallel and Distributed Systems, 2019

2018

Dynamic Obstacle Avoidance Planning Algorithm for UAV Based on Dubins Path.

Na Wang, Fei Dai, Fangxin Liu, Guomin Zhang

Proceedings of the Algorithms and Architectures for Parallel Processing, 2018

UAV 3D Mobility Model Oriented to Dynamic and Uncertain Environment.

Na Wang, Nan Di, Fei Dai, Fangxin Liu

Proceedings of the Algorithms and Architectures for Parallel Processing, 2018

2017

A mechanism of topology optimization for underwater acoustic sensor networks based on autonomous underwater vehicles.

Ming He, Fangxin Liu, Zhuang Miao, Huan Zhou, Qiuli Chen

Int. J. Distributed Sens. Networks, 2017