Hygcn: A gcn accelerator with hybrid architecture M Yan, L Deng, X Hu, L Liang, Y Feng, X Ye, Z Zhang, D Fan, Y Xie 2020 IEEE International Symposium on High Performance Computer Architecture …, 2020 | 309 | 2020 |

Sampling methods for efficient training of graph convolutional networks: A survey X Liu, M Yan, L Deng, G Li, X Ye, D Fan IEEE/CAA Journal of Automatica Sinica 9 (2), 205-234, 2021 | 96 | 2021 |

Alleviating irregularity in graph analytics acceleration: A hardware/software co-design approach M Yan, X Hu, S Li, A Basak, H Li, X Ma, I Akgun, Y Feng, P Gu, L Deng, ... Proceedings of the 52nd Annual IEEE/ACM International Symposium on …, 2019 | 89* | 2019 |

Simple and efficient heterogeneous graph neural network X Yang, M Yan, S Pan, X Ye, D Fan Proceedings of the AAAI conference on artificial intelligence 37 (9), 10816 …, 2023 | 76 | 2023 |

Characterizing and understanding GCNs on GPU M Yan, Z Chen, L Deng, X Ye, Z Zhang, D Fan, Y Xie IEEE Computer Architecture Letters 19 (1), 22-25, 2020 | 61 | 2020 |

Rubik: A hierarchical architecture for efficient graph neural network training X Chen, Y Wang, X Xie, X Hu, A Basak, L Liang, M Yan, L Deng, Y Ding, ... IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2021 | 58* | 2021 |

Survey on graph neural network acceleration: An algorithmic perspective X Liu, M Yan, L Deng, G Li, X Ye, D Fan, S Pan, Y Xie Proceedings of the Thirty-First International Joint Conference on Artificial …, 2022 | 36 | 2022 |

fuseGNN: Accelerating graph convolutional neural network training on GPGPU Z Chen, M Yan, M Zhu, L Deng, G Li, S Li, Y Xie Proceedings of the 39th International Conference on Computer-Aided Design, 1-9, 2020 | 20 | 2020 |

A comprehensive survey on distributed training of graph neural networks H Lin, M Yan, X Ye, D Fan, S Pan, W Chen, Y Xie Proceedings of the IEEE, 2023 | 17 | 2023 |

Fast search of the optimal contraction sequence in tensor networks L Liang, J Xu, L Deng, M Yan, X Hu, Z Zhang, G Li, Y Xie IEEE Journal of Selected Topics in Signal Processing 15 (3), 574-586, 2021 | 13 | 2021 |

Characterizing and understanding HGNNs on GPUs M Yan, M Zou, X Yang, W Li, X Ye, D Fan, Y Xie IEEE Computer Architecture Letters 21 (2), 69-72, 2022 | 11 | 2022 |

GNNSampler: Bridging the gap between sampling algorithms of GNN and hardware X Liu, M Yan, S Song, Z Lv, W Li, G Sun, X Ye, D Fan Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 10 | 2022 |

General spiking neural network framework for the learning trajectory from a noisy mmwave radar X Liu, M Yan, L Deng, Y Wu, D Han, G Li, X Ye, D Fan Neuromorphic Computing and Engineering 2 (3), 034013, 2022 | 8 | 2022 |

Characterizing and understanding distributed GNN training on GPUs H Lin, M Yan, X Yang, M Zou, W Li, X Ye, D Fan IEEE Computer Architecture Letters 21 (1), 21-24, 2022 | 8 | 2022 |

Multi-node acceleration for large-scale GCNs G Sun, M Yan, D Wang, H Li, W Li, X Ye, D Fan, Y Xie IEEE Transactions on Computers 71 (12), 3140-3152, 2022 | 6 | 2022 |

Hardware acceleration for GCNs via bidirectional fusion H Li, M Yan, X Yang, L Deng, W Li, X Ye, D Fan, Y Xie IEEE Computer Architecture Letters 20 (1), 66-4, 2021 | 6 | 2021 |

HiHGNN: Accelerating HGNNs through Parallelism and Data Reusability Exploitation R Xue, D Han, M Yan, M Zou, X Yang, D Wang, W Li, Z Tang, J Kim, X Ye, ... IEEE Transactions on Parallel and Distributed Systems, 2024 | 3 | 2024 |

A Survey of Graph Pre-processing Methods: From Algorithmic to Hardware Perspectives Z Lv, M Yan, X Liu, M Dong, X Ye, D Fan, N Sun arXiv preprint arXiv:2309.07581, 2023 | 3 | 2023 |

A high-accurate multi-objective ensemble exploration framework for design space of CPU microarchitecture D Wang, M Yan, Y Teng, D Han, X Ye, D Fan Proceedings of the Great Lakes Symposium on VLSI 2023, 379-383, 2023 | 3 | 2023 |

RISC-NN: Use RISC, NOT CISC as neural network hardware infrastructure T Xiang, L Zhang, S An, X Ye, M Zhang, Y Liu, M Yan, D Wang, H Zhang, ... arXiv preprint arXiv:2103.12393, 2021 | 3 | 2021 |