Shanghai Qi Zhi Institute PI, Professor at Shanghai Jiao Tong University.
Jiang Li obtained a Bachelor's degree in Computer Science and Technology from Shanghai Jiao Tong University in 2007 and a Ph.D. in Computer Science and Engineering from the Chinese University of Hong Kong in 2013. In 2013, he went to Duke University as a visiting scholar in the Department of Electrical and Computer Engineering (ECE). His research focuses on chip design, electronic design automation (EDA), computer architecture, and the enhancement of chip and hardware system performance and reliability based on machine learning algorithms.
Storage-Computing Integrated Architecture
Key scientific issues and technical challenges in building a non-von Neumann system architecture for in-storage computing, breaking through the memory wall bottleneck.
High-Performance AI Systems
Design and optimization of cross-layer collaboration between algorithms, encoding/decoding, compilation, and architecture, to address the computational power, memory access, and communication bottlenecks of large models.
32. Haomin Li, Fangxin Liu, Yichi Chen and Li Jiang, HyperNode: An Efficient Node Classification Framework Using HyperDimensional Computing, ICCD, 2023 查看PDF
31. Fangxin Liu, Ning Yang and Li Jiang, PSQ: An Automatic Search Framework for Data-Free Quantization on PIM-based Architecture, ICCD, 2023 查看PDF
30. Fangxin Liu, HaominLi, Yongbiao Chen, TaoYang and Li Jiang, HyperAttack: An Effcient Attack Framework for HyperDimensional Computing, DAC, 2023 查看PDF
29. Tao Yang, YiyuanZhou, QidongTang, FengXu, HuiMa, JieruZhao and Li Jiang, SpM
MPlu: A Compiler Plug-in with Sparse IR for Efficient Sparse Matrix Multiplication, DAC, 2023 查看PDF
28. Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Xiaoyao Liang and Li Jiang, ERA-BS: Boosting the Efficiency of ReRAM-based PIM Accelerator with Fine-Grained Bit-Level Sparsity, IEEE Transactions on Computers , 2023 查看PDF
27. Fangxin Liu, Wenbo Zhao, Zongwu Wang, XiaokangYang and Li Jiang, SIMSnn:A Weight-Agnostic ReRAM-based Search-In-Memory Engine for SNN Acceleration, DATE, 2023 查看PDF
26. Tao Yang, HuiMa, Yilong Zhao, Fangxin Liu, Zhezhi He, Xiaoli Sun and Li Jiang, PIMPR:PIM-based Personalized Recommendation with Heterogeneous Memory Hierarchy, DATE, 2023 查看PDF
25. Tao Yang, Dongyue Li, Fei Ma, Zhuoran Song, Yilong Zhao, Jiaxi Zhang, Fangxin Liu and Li Jiang, PASGCN: An ReRAM-Based PIM Design for GCN With Adaptively Sparsified Graphs., TCAD, 2023 查看PDF
24. Fangxin Liu, Zongwu Wang, Yongbiao Chen, Zhezhi He, Tao Yang, Xiaoyao Liang and Li Jiang, SoBS-X: Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural Network Accelerator, TCAD, 2023 查看PDF
23. Yanan Sun, Chang Ma, Zhi Li, Yilong Zhao, Jiachen Jiang, Weikang Qian, Rui Yang, Zhezhi He, Unary Coding and Variation-Aware Optimal Mapping Scheme for Reliable ReRAM-based Neuromorphic Computing, (TCAD) IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2021 查看PDF
22. 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) in ACM/IEEE Design Automation Conference, 2021 查看PDF
21. Yilong Zhao, Zhezhi He, Naifeng Jing, Xiaoyao Liang, Li Jiang, Re2PIM: A Reconfigurable ReRAM-based PIM Design for Variable-sized Vector-Matrix Multiplication, (GLSVLSI) in ACM Great Lakes Symposium on VLS , 2021 查看PDF
20. Fangxin Liu, Wenbo Zhao, Zongwu Wang, Tao Yang, Li Jiang, IM3A: Boosting Deep Neural Network Efficiency via In-Memory Addressing-Assisted Acceleration, (GLSVLSI) in ACM Great Lakes Symposium on VLSI, 2021 查看PDF
19. Zhuoran Song, Dongyue Li, Zhezhi He, Xiaoyao Liang, Li Jiang, ReRAM-Sharing: Fine-Grained Weight Sharing for ReRAM-Based Deep Neural Network Accelerator, (ISCAS) in International Symposium on Circuits and Systems , 2021 查看PDF
18. Xingyi Wang, Yu Li, Yiquan Chen, Shiwen Wang, Yin Du, Cheng He, YuZhong Zhang, Pinan Chen, Xin Li, Wenjun Song, Qiang xu, Li Jiang, On Workload-Aware DRAM Failure Prediction in Large-Scale Data Centers, (VTS) in IEEE VLSI Test Symposium, 2021 查看PDF
17. 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)International Conference on Computer-Aided Design, 2021 查看PDF
16. 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)International Conference on Computer Vision, 2021 查看PDF
15. Dongyue Li,Tao Yang,Lun Du,Zhezhi He,Li Jiang, AdaptiveGCN: Efficient GCN Through Adaptively Sparsifying Graphs, (CIKM)International Conference on Information and Knowledge Management, 2021 查看PDF
14. Hanchen Guo, Zhehan Lin, Yunfei Gu, Chentao Wu*, Li Jiang*, Jie Li, Guangtao Xue, Minyi Guo, Lazy-WL: A Wear-aware Load Balanced Data Redistribution Method for Efficient SSD Array Scaling, (CLUSTER)IEEE International Conference on Cluster Computing, 2021 查看PDF
13. Fangxin Liu, Wenbo Zhao, Zhezhi He, Zongwu Wang, Yilong Zhao, Tao Yang, Xiaoyao Liang, Naifeng Jing and Li Jiang, SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network, (ICCD)International Conference on Computer Design, 2021 查看PDF
12. Fangxin Liu, Wenbo Zhao, Zongwu Wang,Qidong Tang, Yongbiao Chen,Zhezhi He,Naifeng Jing,Xiaoyang Liang and Li Jiang, EBSP: Evolving Bit Sparsity Patterns for Hardware-Friendly Inference of Quantized Deep Neural Networks, (DAC) in ACM/IEEE Design Automation Conference, 2022 查看PDF
11. Fangxin Liu, Wenbo Zhao,Yongbiao Chen,Zongwu Wang,Zhezhi He,Rui Yang,Qidong Tang, Tao Yang,Cheng Zhuo and Li Jiang, PIM-DH: ReRAM-based Processing-in-Memory Architecture for Deep Hashing Acceleration, (DAC) in ACM/IEEE Design Automation Conference, 2022 查看PDF
10. Fangxin Liu，Wenbo Zhao, Zongwu Wang,Yongbiao Chen,Li Jiang, SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks, AAAI Conference on Artificial Intelligence, 2022 查看PDF
9. Tao Yang, Dongyue Li, Zhuoran Song, Yilong Zhao, Fangxin Liu, Zongwu Wang, Zhezhi He and Li Jiang, DTQAtten: Leveraging Dynamic Token-based Quantization for Efficient Attention Architecture, (DATE)Design, Automation & Test in Europe Conference & Exhibition, 2022 查看PDF
8. Tao Yang，Dongyue Li，Fei Ma，Zhuoran Song，Yilong Zhao，Jiaxi Zhang，Fangxin Liu and Li Jiang, PASGCN: An ReRAM-Based PIM Design for GCN with Adaptively Sparsified Graphs, （TCAD）IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022 查看PDF
7. Zongwu Wang,Zhezhi He, Rui Yang,Shiquan Fan，Jie Lin, Fangxin Liu，Yueyang Jia, Chenxi Yuan，Qidong Tang and Li Jiang, Self-Terminating Write of Multi-Level Cell ReRAM for Efficient Neuromorphic Computing, (DATE)Design, Automation & Test in Europe Conference & Exhibition, 2022 查看PDF
6. Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Tao Yang and Li Jiang, SSTDP: Supervised Spike Timing Dependent Plasticity for Efficient Spiking Neural Network Training, Frontiers in Neuroscience, section Neuromorphic Engineering, 2022 查看PDF
5. 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)27th Asia and South Pacific Design Automation Conference, 2022 查看PDF
4. Fangxin Liu, Wenbo Zhao, Zongwu Wang, Yongbiao Chen, Tao Yang, Zhezhi He, Xiaokang Yang and Li Jiang, SATO: Spiking Neural Network Acceleration via Temporal-Oriented Dataflow and Architecture, (DAC) in ACM/IEEE Design Automation Conference, 2022 查看PDF
3. Fangxin Liu，Haomin Li，Xiaokang Yang，Li Jiang, L3E-HD: A Framework Enabling Efficient Ensemble in High-Dimensional Space for Language Tasks, (SIGIR)International Conference on Research and Development in Information Retrieval, 2022 查看PDF
2. Fangxin Liu, Zongwu Wang,Wenbo Zhao, Yongbiao Chen, Xiaokang Yang and Li Jiang, Randomize and Match: Exploiting Irregular Sparsity for Energy Efficient Processing in SNNs, IEEE International Conference on Computer Design (ICCD), 2022 查看PDF
1. Tao Yang,Hui Ma,Xiaoling Li,Fangxin Liu,Yilong Zhao,Zhezhi He and Li Jiang, DTATrans: Leveraging Dynamic Token-basedQuantization with Accuracy Compensation Mechanism for Efficien tTranformer Architecture, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems(TCAD), 2022 查看PDF
