Efficient message passing architecture for GCN training on HBM-based FPGAs with orthogonal topology on-chip networks

Qizhe WU , Letian ZHAO , Huawen LIANG , Jinyi ZHOU , Xiaotian WANG , Xi JIN

Front. Comput. Sci. ›› 2026, Vol. 20 ›› Issue (5) : 2005106

PDF (879KB)
Front. Comput. Sci. ›› 2026, Vol. 20 ›› Issue (5) : 2005106 DOI: 10.1007/s11704-025-41218-2
Architecture
LETTER

Efficient message passing architecture for GCN training on HBM-based FPGAs with orthogonal topology on-chip networks

Author information +
History +
PDF (879KB)

Graphical abstract

Cite this article

Download citation ▾
Qizhe WU, Letian ZHAO, Huawen LIANG, Jinyi ZHOU, Xiaotian WANG, Xi JIN. Efficient message passing architecture for GCN training on HBM-based FPGAs with orthogonal topology on-chip networks. Front. Comput. Sci., 2026, 20(5): 2005106 DOI:10.1007/s11704-025-41218-2

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Yang H. AliGraph: a comprehensive graph neural network platform. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2019, 3165−3166

[2]

Zhou Z, Shi B, Zhang Z, Guan Y, Sun G, Luo G. BlockGNN: towards efficient GNN acceleration using block-circulant weight matrices. In: Proceedings of the 58th ACM/IEEE Design Automation Conference (DAC). 2021, 1009−1014

[3]

Zhang B, Kannan R, Prasanna V. BoostGCN: a framework for optimizing GCN inference on FPGA. In: Proceedings of the IEEE 29th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM). 2021, 29−39

[4]

Li J, Louri A, Karanth A, Bunescu R. GCNAX: a flexible and energy-efficient accelerator for graph convolutional neural networks. In: Proceedings of 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA). 2021, 775−788

[5]

Lin Y C, Zhang B, Prasanna V. HP-GNN: generating high throughput GNN training implementation on CPU-FPGA heterogeneous platform. In: Proceedings of 2022 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays. 2022, 123−133

RIGHTS & PERMISSIONS

Higher Education Press

AI Summary AI Mindmap
PDF (879KB)

Supplementary files

Highlights

236

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/