Mingyu Yan

Mingyu Yan

Associate Professor at the Institute of Computing Technology of Chinese Academy of Sciences

Selected Publications

Journal Papers

  1. [PIEEE 2023] Haiyang Lin, Mingyu Yan✉️, Xiaochun Ye, Dongrui Fan, Shirui Pan, Wenguang Chen, and Yuan Xie. “A Comprehensive Survey on Distributed Training of Graph Neural Networks.” Proceedings of the IEEE (PIEEE), 2023.
  2. [IEEE TPDS 2024] Runzhen Xue, Dengke Han, Mingyu Yan✉️, Mo Zou, Xiaocheng Yang, Duo Wang, Wenming Li, Zhimin Tang, John Kim, Xiaochun Ye, and Dongrui Fan. “HiHGNN: Accelerating HGNNs through Parallelism and Data Reusability Exploitation.”, IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), 2024.
  3. [IEEE TC 2022] Gongjian Sun, Mingyu Yan✉️, Duo Wang, Han Li, Wenming Li, Xiaochun Ye, Dongrui Fan, and Yuan Xie. “Multi-Node Acceleration for Large-Scale GCNs.” IEEE Transactions on Computers (IEEE TC), 2022
  4. [IEEE TCAD 2025] Runzhen Xue, Mingyu Yan✉️, Dengke Han, Ziheng Xiao, Zhimin Tang, Xiaochun Ye, Dongrui Fan. “SiHGNN: Leveraging Properties of Semantic Graphs for Efficient HGNN Acceleration.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD), 2025.
  5. [IEEE TCAD 2024] Duo Wang, Mingyu Yan✉️, Yihan Teng, Dengke Han, Xin Liu, Wenming Li, Xiaochun Ye, and Dongrui Fan. “MoDSE: A High-Accurate Multi-Objective Design Space Exploration Framework for CPU Microarchitectures.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD), 2024.
  6. [ACM TACO 2024] Dengke Han, Mingyu Yan✉️, Xiaochun Ye, and Dongrui Fan. “Characterizing and Understanding HGNN Training on GPUs.” ACM Transactions on Architecture and Code Optimization (ACM TACO), 2024.
  7. [IEEE TPDS 2025] Meng Wu, Mingyu Yan✉️, Wenming Li, Xiaochun Ye, Dongrui Fan, and Yuan Xie. “Survey on Characterizing and Understanding GNNs from a Computer Architecture Perspective.”, IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), 2025.
  8. [Neural Networks 2024] Xin Liu, Xunbin Xiong, Mingyu Yan✉️, Runzhen Xue, Shirui Pan, Songwen Pei, Lei Deng, Xiaochun Ye, and Dongrui Fan. “DropNaE: Alleviating Irregularity for Large-scale Graph Representation Learning.” Neural Networks, 2024.
  9. [IEEE/CAA JAS 2022] Xin Liu, Mingyu Yan✉️, Lei Deng, Guoqi Li, Xiaochun Ye, and Dongrui Fan. “Sampling Methods for Efficient Training of Graph Convolutional Networks: A Survey.” IEEE/CAA Journal of Automatica Sinica (IEEE/CAA JAS), 2022.
  10. [NCE 2022] Xin Liu, Mingyu Yan✉️, Lei Deng, Yujie Wu, De Han, Guoqi Li, Xiaochun Ye, and Dongrui Fan. “General Spiking Neural Network Framework for The Learning Trajectory from A Noisy Mmwave Radar.” Neuromorphic Computing and Engineering (NCE), 2022.
  11. [IEEE CAL 2022] Haiyang Lin, Mingyu Yan✉️, Xiaocheng Yang, Mo Zou, Wenming Li, Xiaochun Ye, and Dongrui Fan. “Characterizing and Understanding Distributed GNN Training on GPUs.” IEEE Computer Architecture Letters (IEEE CAL), 2022.
  12. [IEEE CAL 2022] Mingyu Yan, Mo Zou, Xiaocheng Yang, Wenming Li, Xiaochun Ye, Dongrui Fan, Yuan Xie. “Characterizing and Understanding HGNNs on GPUs.” IEEE Computer Architecture Letters (IEEE CAL), 2022.
  13. [IEEE CAL 2022] Han Li, Mingyu Yan✉️, Xiaocheng Yang, Lei Deng, Wenming Li, Xiaochun Ye, Dongrui Fan, and Yuan Xie. “Hardware Acceleration for GCNs via Bidirectional Fusion.” IEEE Computer Architecture Letters (IEEE CAL), 2021.
  14. [IEEE TCAD 2021] Xiaobing Chen, Yuke Wang, Xinfeng Xie, Xing Hu, Abanti Basak, Ling Liang, Mingyu Yan, Lei Deng, Yufei Ding, Zidong Du, and Yuan Xie. “Rubik: A Hierarchical Architecture for Efficient Graph Neural Network Training.” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD), 2021.
  15. [IEEE JSTSP 2021] Ling Liang, Jianyu Xu, Lei Deng, Mingyu Yan, Xing Hu, Zheng Zhang, Guoqi Li, and Yuan Xie. “Fast Search of the Optimal Contraction Sequence in Tensor Networks.” IEEE Journal of Selected Topics in Signal Processing (IEEE JSTSP), 2021.
  16. [IEEE CAL 2020] Mingyu Yan, Zhaodong Chen, Lei Deng, Xiaochun Ye, Zhimin Zhang, Dongrui Fan, Yuan Xie. “Characterizing and Understanding GCNs on GPU.” IEEE Computer Architecture Letters (IEEE CAL), 2020.

Conference Papers

  1. [HPCA’20] Mingyu Yan, Lei Deng, Xing Hu, Ling Liang, Yujing Feng, Xiaochun Ye, Zhimin Zhang, Dongrui Fan, and Yuan Xie. “HyGCN: A GCN Accelerator with Hybrid Architecture.” in the 26th IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2020.
  2. [MICRO’19] Mingyu Yan, Xing Hu, Shuangchen Li, Abanti Basak, Han Li, Xin Ma, Itir Akgun, Yujing Feng, Peng Gu, Lei Deng, Xiaochun Ye, Zhimin Zhang, Dongrui Fan, and Yuan Xie. “Alleviating Irregularity in Graph Analytics Acceleration: a Hardware/Software Co-Design Approach.” in Proceedings of the 52nd IEEE/ACM International Symposium on Microarchitecture (MICRO), 2019.
  3. [DAC’25] Runzhen Xue, Hao Wu, Mingyu Yan✉️, Ziheng Xiao, Xiaochun Ye and Dongrui Fan. “MetaDSE: A Few-Shot Meta-Learning Framework for Cross-Workload CPU Design Space Exploration.” in 62nd ACM/IEEE Design Automation Conference (DAC), 2025.
  4. [DAC’24] Runzhen Xue, Mingyu Yan✉️, Dengke Han, Yihan Teng, Zhimin Tang, Xiaochun Ye, and Dongrui Fan. “GDR-HGNN: A Heterogeneous Graph Neural Networks Accelerator with Graph Decoupling and Recouping.” in 61th ACM/IEEE Design Automation Conference (DAC), 2024.
  5. [DAC’23] Duo Wang, Mingyu Yan✉️, Xin Liu, Mo Zou, Tianyu Liu, Wenming Li, Xiaochun Ye, and Dongrui Fan. “A High-accurate Multi-objective Exploration Framework for Design Space of CPU.” in 60th ACM/IEEE Design Automation Conference (DAC), 2023.
  6. [DAC’22] Haiyang Lin, Mingyu Yan✉️, Duo Wang, Mo Zuo, Fengbin Tu, Xiaochun Ye, Dongrui Fan, and Yuan Xie. “Alleviating Datapath Conflicts and Design Centralization in Graph Analytics Acceleration.” in the 59th Design Automation Conference (DAC), 2022.
  7. [AAAI’23] Xiaocheng Yang, Mingyu Yan✉️, Shirui Pan, Xiaochun Ye, and Dongrui Fan. “Simple and Efficient Heterogeneous Graph Neural Network.” in AAAI Conference on Artificial Intelligence (AAAI), 2023.
  8. [IJCAI’22] Xin Liu, Mingyu Yan✉️, Lei Deng, Guoqi Li, Xiaochun Ye, Dongrui Fan, Shirui Pan, and Yuan Xie. “Survey on Graph Neural Network Acceleration: An Algorithmic Perspective.” in Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI), 2022.
  9. [ICCAD’23] Duo Wang, Mingyu Yan✉️, Yihan Teng, Dengke Han, Haoran Dang, Xiaochun Ye, and Dongrui Fan. “A Transfer Learning Framework for High-Accurate Cross-Workload Design Space Exploration of CPU.” in IEEE/ACM International Conference on Computer Aided Design (ICCAD), 2023.
  10. [ECML-PKDD’22] Xin Liu, Mingyu Yan✉️, Shuhan Song, Zhengyang Lv, Wenming Li, Guangyu Sun, Xiaochun Ye, and Dongrui Fan.”GNNSampler: Bridging the Gap between Sampling Algorithms of GNN and Hardware.” in the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2022.
  11. [ICCAD’20] Zhaodong Chen, Mingyu Yan, Maohua Zhu, Lei Deng, Guoqi Li, Shuangchen Li, and Yuan Xie. “fuseGNN: Accelerating Graph Convolutional Neural Network Training on GPGPU.” in Proceedings of International Conference on Computer Aided Design (ICCAD), 2020.
  12. [DATE’25] Gongjian Sun, Mingyu Yan✉️, Dengke Han, Runzhen Xue, Xiaochun Ye, and Dongrui Fan. “LiGNN: Accelerating GNN Training through Locality-aware Dropout.” in Proceedings of Design Automation and Test in Europe Conference (DATE), 2025.
  13. [Euro-Par’24] Dengke Han, Meng Wu, Runzhen Xue, Mingyu Yan✉️, Xiaochun Ye, and Dongrui Fan. “ADE-HGNN: Accelerating HGNNs through Attention Disparity Exploitation.” in Proceedings of European Conference on Parallel Processing (Euro-Par), 2024.
  14. [Euro-Par’24] Haoran Dang, Meng Wu, Mingyu Yan✉️, Xiaochun Ye, and Dongrui Fan. “GDL-GNN: Applying GPU Dataloading of Large Datasets for Graph Neural Network Inference.” in Proceedings of European Conference on Parallel Processing (Euro-Par), 2024.
  15. [Euro-Par’24] Yuxiang Zhang, Xin Liu, Meng Wu, Wei Yan, Mingyu Yan✉️, Xiaochun Ye, and Dongrui Fan. “Disttack: Graph Adversarial Attacks Toward Distributed GNN Training.” in Proceedings of European Conference on Parallel Processing (Euro-Par), 2024.