CV

Education

Research experience

Publications

ASP-DAC 2024 NeuronQuant: Accurate and Efficient Post-Training Quantization for Spiking Neural Networks
Haomin Li=, Fangxin Liu=, Zewen Sun, Zongwu Wang, Shiyuan Huang, Ning Yang, and Li Jiang
30th Asia and South Pacific Design Automation Conference


MICRO 2024 COMPASS: SRAM-Based Computing-in-Memory SNN Accelerator with Adaptive Spike Speculation
Zongwu Wang, Fangxin Liu, Ning Yang, Shiyuan Huang, Haomin Li, and Li Jiang
57th IEEE/ACM International Symposium on Microarchitecture


TPDS 2024 Exploiting Temporal-Unrolled Parallelism for Energy-Efficient SNN Acceleration
Fangxin Liu, Zongwu Wang, Wenbo Zhao, Ning Yang, Yongbiao Chen, Shiyuan Huang, Haomin Li, Tao Yang, Songwen Pei, Xiaoyao Liang, and Li Jiang
IEEE Transactions on Parallel and Distributed Systems


DAC 2024 INSPIRE: Accelerating Deep Neural Networks via Hardware-friendly Index-Pair Encoding
Fangxin Liu, Ning Yang, Zhiyan Song, Zongwu Wang, Haomin Li, Shiyuan Huang, Zhuoran Song, Songwen Pei, and Li Jiang
61th Design Automation Conference


DAC 2024 EOS: An Energy-Oriented Attack Framework for Spiking Neural Networks
Ning Yang, Fangxin Liu, Zongwu Wang, Haomin Li, Zhuoran Song, Songwen Pei, and Li Jiang
61th Design Automation Conference


DAC 2024 DEFA: Efficient Deformable Attention Acceleration via Pruning-Assisted Grid-Sampling and Multi-Scale Parallel Processing
Yansong Xu, Dongxu Lyu, Zhenyu Li, Yuzhou Chen, Zilong Wang, Gang Wang, Zhican Wang, Haomin Li, and Guanghui He
61th Design Automation Conference


HPCA 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, and Li Jiang
30th International Symposium on High-Performance Computer Architecture


ASP-DAC 2024 PAAP-HD: PIM-Assisted Approximation for Efficient Hyper-Dimensional Computing
Fangxin Liu=, Haomin Li=, Ning Yang, Yichi Chen, Zongwu Wang, Tao Yang, and Li Jiang
29th Asia and South Pacific Design Automation Conference


ASP-DAC 2024 TEAS: Exploiting Spiking Activity for Temporal-wise Adaptive Spiking Neural Networks
Fangxin Liu=, Haomin Li=, Ning Yang, Zongwu Wang, Tao Yang, and Li Jiang
29th Asia and South Pacific Design Automation Conference


ASP-DAC 2024 TSTC: Enabling Efficient Training via Structured Sparse Tensor Compilation
Shiyuan Huang=, Fangxin Liu=, Tian Li, Zongwu Wang, Haomin Li, and Li Jiang
29th Asia and South Pacific Design Automation Conference


ASP-DAC 2024 HyperFeel: An Efficient Federated Learning Framework Using Hyperdimensional Computing
Haomin Li=, Fangxin Liu=, Yichi Chen, and Li Jiang
29th Asia and South Pacific Design Automation Conference


ICCAD 2023 HyperNode: An Efficient Node Classification Framework Using HyperDimensional Computing
Haomin Li=, Fangxin Liu=, Yichi Chen, and Li Jiang
42th IEEE/ACM International Conference on Computer-Aided Design


DAC 2023 HyperAttack: An Efficient Attack Framework for HyperDimensional Computing
Fangxin Liu=, Haomin Li=, Yongbiao Chen, Tao Yang, and Li Jiang </span>
60th Design Automation Conference


SIGIR 2022 L3E-HD: A Framework Enabling Efficient Ensemble in High-Dimensional Space for Language Tasks
Fangxin Liu, Haomin Li, Xiaokang Yang, and Li Jiang
45th International ACM SIGIR Conference on Research and Development in Information Retrieval

code


Genomics 2021 DeepSE: Detecting super-enhancers among typical enhancers using only sequence feature embeddings
Qiao-Ying Ji, Xiu-Jun Gong, Haomin Li, and Pu-Feng Du
Genomics, 113(6): 4052-4060.