News

📝 HiHGNN，a hardware accelerator for heterogeneous graph neural networks has been accepted by IEEE TPDS.

[TPDS 2024] “HiHGNN: Accelerating HGNNs through Parallelism and Data Reusability Exploitation.”, IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), 2024.

📝 GDR-HGNN, a hardware accelerator for heterogeneous graph neural networks has been accepted by DAC’24.

[DAC’24] “GDR-HGNN: A Heterogeneous Graph Neural Networks Accelerator with Graph Decoupling and Recouping.” in 61th ACM/IEEE Design Automation Conference (DAC), 2024.

🧐Mingyu Yan was invited to serve as the EPC member of MICRO 2024.

📝 A comprehensive survey on distributed training of graph neural networks has been accepted by Proceedings of the IEEE.

📝 Extension design of MoDSE has been accepted by IEEE TCAD.

[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.

🧐Mingyu Yan was invited to serve as the TPC member of Survey Track in IJCAI 2024.

🧐Mingyu Yan was invited to serve as the TPC member of ICS 2024.

🧐Mingyu Yan was invited to serve as the ERC member of ISCA 2024.

🧐Mingyu Yan was invited to serve as the TPC member of HPCA 2024.

📝 MoDSE, a multi-objective exploration framework for design space of CPU has been accepted by DAC’23.

📝 TrEnDSE, a transfer learning framework for cross-Workload design space exploration of CPU has been accepted by ICCAD’23.

[ICCAD’23] “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.

📝 SeHGNN, a simple and efficient heterogeneous graph neural network has been accepted by AAAI’23.

[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.
Open Source: https://github.com/ICT-GIMLab/SeHGNN

🏆SeHGNN has ranked #1 in the leaderboard for node property prediction (ogbn-mag) on Open Graph Benchmark.

🏆Mingyu Yan has been selected for the member of Youth Innovation Promotion Association of Chinese Academy of Sciences (2023)

🏆Mingyu Yan has been awarded the Outstanding Doctoral Dissertation Award of China Computer Federation (2022).

📝MultiGCN, a multi-node hardware accelerator for graph convolutional networks has been accepted by IEEE TC.

[IEEE TC 2022] “Multi-Node Acceleration for Large-Scale GCNs.” IEEE Transactions on Computers (IEEE TC), 2022

🏆Mingyu Yan has been selected for Young Talent Development Program of China Computer Federation (2022).

📝 HiGraph, a graph analytics hardware accelerator has been accepted by DAC’22.

📝 A survey on graph neural network acceleration from an algorithmic perspective has been accepted by IJCAI’22.

[IJCAI’22] “Survey on Graph Neural Network Acceleration: An Algorithmic Perspective.” in Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI), 2022.

📝 A survey on sampling methods for efficient training of graph convolutional networks has been accepted by IEEE/CAA JAS.

[IEEE/CAA JAS 2022] “Sampling Methods for Efficient Training of Graph Convolutional Networks: A Survey.” IEEE/CAA Journal of Automatica Sinica (IEEE/CAA JAS), 2022.

🏆Mingyu Yan has been selected for the Special Research Assistant Grant Program of Chinese Academy of Sciences (2021).

🏆Mingyu Yan has been awarded the first prize in the Beijing Science and Technology Award (Technological Invention) (2020).

📝 HyGCN, a hardware accelerator for graph convolutional networks has been accepted by HPCA’20.

[HPCA’20] “HyGCN: A GCN Accelerator with Hybrid Architecture.” in the 26th IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2020.

📝 GraphDynS, a hardware accelerator for graph analytics has been accepted by MICRO’19.

[MICRO’19] “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.