Fangxin Liu

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 51

Top Topics

Simulation Tool

Uniform Quantization

Memory Hierarchy

Top Venues

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

Publications

Fangxin Liu, Haomin Li, Ning Yang, Zongwu Wang, Tao Yang, Li Jiang
TEAS: Exploiting Spiking Activity for Temporal-wise Adaptive Spiking Neural Networks. ASPDAC (2024)
Jiahao Sun, Fangxin Liu, Yijian Zhang, Li Jiang, Rui Yang
RTSA: An RRAM-TCAM based In-Memory-Search Accelerator for Sub-100 µs Collision Detection. DATE (2024)
Shiyuan Huang, Fangxin Liu, Tian Li, Zongwu Wang, Haomin Li, Li Jiang
TSTC: Enabling Efficient Training via Structured Sparse Tensor Compilation. ASPDAC (2024)
Fangxin Liu, Ning Yang, Haomin Li, Zongwu Wang, Zhuoran Song, Songwen Pei, Li Jiang
SPARK: Scalable and Precision-Aware Acceleration of Neural Networks via Efficient Encoding. HPCA (2024)
Zhuoran Song, Chunyu Qi, Fangxin Liu, Naifeng Jing, Xiaoyao Liang
CMC: Video Transformer Acceleration via CODEC Assisted Matrix Condensing. ASPLOS (2) (2024)
Haomin Li, Fangxin Liu, Yichi Chen, Li Jiang
HyperFeel: An Efficient Federated Learning Framework Using Hyperdimensional Computing. ASPDAC (2024)
Yilong Zhao, Mingyu Gao, Fangxin Liu, Yiwei Hu, Zongwu Wang, Han Lin, Jin Li, He Xian, Hanlin Dong, Tao Yang, Naifeng Jing, Xiaoyao Liang, Li Jiang
UM-PIM: DRAM-based PIM with Uniform & Shared Memory Space. ISCA (2024)
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Xiaoyao Liang, Li Jiang
ERA-BS: Boosting the Efficiency of ReRAM-Based PIM Accelerator With Fine-Grained Bit-Level Sparsity. IEEE Trans. Computers 73 (9) (2024)
Fangxin Liu, Haomin Li, Ning Yang, Yichi Chen, Zongwu Wang, Tao Yang, Li Jiang
PAAP-HD: PIM-Assisted Approximation for Efficient Hyper-Dimensional Computing. ASPDAC (2024)
Xueyuan Liu, Zhuoran Song, Xiang Liao, Xing Li, Tao Yang, Fangxin Liu, Xiaoyao Liang
Sava: A Spatial- and Value-Aware Accelerator for Point Cloud Transformer. DATE (2024)
Zhuoran Song, Wanzhen Liu, Tao Yang, Fangxin Liu, Naifeng Jing, Xiaoyao Liang
A Point Cloud Video Recognition Acceleration Framework Based on Tempo-Spatial Information. IEEE Trans. Parallel Distributed Syst. 34 (12) (2023)
Tao Yang, Hui Ma, Yilong Zhao, Fangxin Liu, Zhezhi He, Xiaoli Sun, Li Jiang
PIMPR: PIM-based Personalized Recommendation with Heterogeneous Memory Hierarchy. DATE (2023)
Haomin Li, Fangxin Liu, Yichi Chen, Li Jiang
HyperNode: An Efficient Node Classification Framework Using HyperDimensional Computing. ICCAD (2023)
Tao Yang, Dongyue Li, Fei Ma, Zhuoran Song, Yilong Zhao, Jiaxi Zhang, Fangxin Liu, Li Jiang
PASGCN: An ReRAM-Based PIM Design for GCN With Adaptively Sparsified Graphs. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42 (1) (2023)
Yongbiao Chen, Sheng Zhang, Fangxin Liu, Chenggang Wu, Kaicheng Guo, Zhengwei Qi
DVHN: A Deep Hashing Framework for Large-Scale Vehicle Re-Identification. IEEE Trans. Intell. Transp. Syst. 24 (9) (2023)
Fangxin Liu, Ning Yang, Li Jiang
PSQ: An Automatic Search Framework for Data-Free Quantization on PIM-based Architecture. ICCD (2023)
Tao Yang, Fei Ma, Xiaoling Li, Fangxin Liu, Yilong Zhao, Zhezhi He, Li Jiang
DTATrans: Leveraging Dynamic Token-Based Quantization With Accuracy Compensation Mechanism for Efficient Transformer Architecture. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42 (2) (2023)
Fangxin Liu, Haoming Li, Yongbiao Chen, Tao Yang, Li Jiang
HyperAttack: An Efficient Attack Framework for HyperDimensional Computing. DAC (2023)
Fangxin Liu, Zongwu Wang, Yongbiao Chen, Zhezhi He, Tao Yang, Xiaoyao Liang, Li Jiang
SoBS-X: Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural Network Accelerator. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42 (1) (2023)
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Xiaokang Yang, Li Jiang
SIMSnn: A Weight-Agnostic ReRAM-based Search-In-Memory Engine for SNN Acceleration. DATE (2023)
Zongwu Wang, Zhezhi He, Rui Yang, Shiquan Fan, Jie Lin, Fangxin Liu, Yueyang Jia, Chenxi Yuan, Qidong Tang, Li Jiang
Self-Terminating Write of Multi-Level Cell ReRAM for Efficient Neuromorphic Computing. DATE (2022)
Fangxin Liu, Zongwu Wang, Wenbo Zhao, Yongbiao Chen, Tao Yang, Xiaokang Yang, Li Jiang
Randomize and Match: Exploiting Irregular Sparsity for Energy Efficient Processing in SNNs. ICCD (2022)
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Zhezhi He, Naifeng Jing, Xiaoyao Liang, Li Jiang
EBSP: evolving bit sparsity patterns for hardware-friendly inference of quantized deep neural networks. DAC (2022)
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Tao Yang, Zhezhi He, Xiaokang Yang, Li Jiang
SATO: spiking neural network acceleration via temporal-oriented dataflow and architecture. DAC (2022)
Fangxin Liu, Haomin Li, Xiaokang Yang, Li Jiang
L3E-HD: A Framework Enabling Efficient Ensemble in High-Dimensional Space for Language Tasks. SIGIR (2022)
Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Li Jiang
SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks. AAAI (2022)
Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Zhezhi He, Rui Yang, Qidong Tang, Tao Yang, Cheng Zhuo, Li Jiang
PIM-DH: ReRAM-based processing-in-memory architecture for deep hashing acceleration. DAC (2022)
Yongbiao Chen, Kaicheng Guo, Fangxin Liu, Yusheng Huang, Zhengwei Qi
Supervised Contrastive Vehicle Quantization for Efficient Vehicle Retrieval. ICMR (2022)
Zihan Jiang, Jiansong Li, Fangxin Liu, Wanling Gao, Lei Wang, Chuanxin Lan, Fei Tang, Lei Liu, Tao Li
A systematic study on benchmarking AI inference accelerators. CCF Trans. High Perform. Comput. 4 (2) (2022)
Tao Yang, Dongyue Li, Zhuoran Song, Yilong Zhao, Fangxin Liu, Zongwu Wang, Zhezhi He, Li Jiang
DTQAtten: Leveraging Dynamic Token-based Quantization for Efficient Attention Architecture. DATE (2022)
Qidong Tang, Zhezhi He, Fangxin Liu, Zongwu Wang, Yiyuan Zhou, Yinghuan Zhang, Li Jiang
HAWIS: Hardware-Aware Automated WIdth Search for Accurate, Energy-Efficient and Robust Binary Neural Network on ReRAM Dot-Product Engine. ASP-DAC (2022)
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yilong Zhao, Tao Yang, Yiran Chen, Li Jiang
IVQ: In-Memory Acceleration of DNN Inference Exploiting Varied Quantization. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41 (12) (2022)
Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Fei Dai
DynSNN: A Dynamic Approach to Reduce Redundancy in Spiking Neural Networks. ICASSP (2022)
Yongbiao Chen, Sheng Zhang, Fangxin Liu, Zhigang Chang, Mang Ye, Zhengwei Qi
TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval. ICMR (2022)
Yilong Zhao, Li Jiang, Mingyu Gao, Naifeng Jing, Chengyang Gu, Qidong Tang, Fangxin Liu, Tao Yang, Xiaoyao Liang
RePAST: A ReRAM-based PIM Accelerator for Second-order Training of DNN. CoRR (2022)
Fangxin Liu, Wenbo Zhao, Zongwu Wang, Tao Yang, Li Jiang
IM3A: Boosting Deep Neural Network Efficiency via In-Memory Addressing-Assisted Acceleration. ACM Great Lakes Symposium on VLSI (2021)
Fangxin Liu, Wenbo Zhao, Yilong Zhao, Zongwu Wang, Tao Yang, Zhezhi He, Naifeng Jing, Xiaoyao Liang, Li Jiang
SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network. CoRR (2021)
Fangxin Liu, Wenbo Zhao, Zhezhi He, Yanzhi Wang, Zongwu Wang, Changzhi Dai, Xiaoyao Liang, Li Jiang
Improving Neural Network Efficiency via Post-training Quantization with Adaptive Floating-Point. ICCV (2021)
Tao Yang, Zhezhi He, Tengchuan Kou, Qingzheng Li, Qi Han, Haibao Yu, Fangxin Liu, Yun Liang, Li Jiang
BISWSRBS: A Winograd-based CNN Accelerator with a Fine-grained Regular Sparsity Pattern and Mixed Precision Quantization. ACM Trans. Reconfigurable Technol. Syst. 14 (4) (2021)
Fangxin Liu, Wenbo Zhao, Zhezhi He, Zongwu Wang, Yilong Zhao, Yongbiao Chen, Li Jiang
Bit-Transformer: Transforming Bit-level Sparsity into Higher Preformance in ReRAM-based Accelerator. ICCAD (2021)
Fangxin Liu, Wenbo Zhao, Zhezhi He, Zongwu Wang, Yilong Zhao, Tao Yang, Jingnai Feng, Xiaoyao Liang, Li Jiang
SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network. ICCD (2021)
Yongbiao Chen, Sheng Zhang, Fangxin Liu, Chenggang Wu, Kaicheng Guo, Zhengwei Qi
DVHN: A Deep Hashing Framework for Large-scale Vehicle Re-identification. CoRR (2021)
Yongbiao Chen, Sheng Zhang, Fangxin Liu, Zhigang Chang, Mang Ye, Zhengwei Qi
TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval. CoRR (2021)
Tao Yang, Dongyue Li, Yibo Han, Yilong Zhao, Fangxin Liu, Xiaoyao Liang, Zhezhi He, Li Jiang
PIMGCN: A ReRAM-Based PIM Design for Graph Convolutional Network Acceleration. DAC (2021)
Jiansong Li, Zihan Jiang, Fangxin Liu, Xiao Dong, Guangli Li, Xueying Wang, Wei Cao, Lei Liu, Yanzhi Wang, Tao Li, Xiaobing Feng
Characterizing the I/O Pipeline in the Deployment of CNNs on Commercial Accelerators. ISPA/BDCloud/SocialCom/SustainCom (2020)
Fangxin Liu, Wenbo Zhao, Yanzhi Wang, Changzhi Dai, Li Jiang
AUSN: Approximately Uniform Quantization by Adaptively Superimposing Non-uniform Distribution for Deep Neural Networks. CoRR (2020)
Fangxin Liu, Kunpeng Xie, Cheng Gong, Shusheng Liu, Ye Lu, Tao Li
LHC: A Low-Power Heterogeneous Computing Method on Neural Network Accelerator. ICPADS (2019)
Jin Zhang, Xin Wei, Zhen Liu, Fangxin Liu, Tao Li, Tingjuan Lu, Xiaoli Gong
ExploreBP: A Simulation Tool for Mobile Browser Energy Optimization. SimuTools (2019)
Na Wang, Nan Di, Fei Dai, Fangxin Liu
UAV 3D Mobility Model Oriented to Dynamic and Uncertain Environment. ICA3PP (3) (2018)
Na Wang, Fei Dai, Fangxin Liu, Guomin Zhang
Dynamic Obstacle Avoidance Planning Algorithm for UAV Based on Dubins Path. ICA3PP (2) (2018)
Ming He, Fangxin Liu, Zhuang Miao, Huan Zhou, Qiuli Chen
A mechanism of topology optimization for underwater acoustic sensor networks based on autonomous underwater vehicles. Int. J. Distributed Sens. Networks 13 (1) (2017)