Characterizing and Understanding HGNN Training on GPUs

doi:10.1145/3703356

	Characterizing and Understanding HGNN Training on GPUs
	Han, Dengke 1,2; Yan, Mingyu 1,2; Ye, Xiaochun 1,2; Fan, Dongrui 1,2
	2025-03-01
发表期刊	ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION
ISSN	1544-3566
卷号	22 期号:1 页码:25
摘要	Owing to their remarkable representation capabilities for heterogeneous graph data, Heterogeneous Graph Neural Networks (HGNNs) have been widely adopted in many critical real-world domains such as recommendation systems and medical analysis. Prior to their practical application, identifying the optimal HGNN model parameters tailored to specific tasks through extensive training is a time-consuming and costly process. To enhance the efficiency of HGNN training, it is essential to characterize and analyze the execution semantics and patterns within the training process to identify performance bottlenecks. In this study, we conduct a comprehensive quantification and in-depth analysis of two mainstream HGNN training scenarios, including single-GPU and multi-GPU distributed training. Based on the characterization results, we reveal the performance bottlenecks and their underlying causes in different HGNN training scenarios and propose optimization guidelines from both software and hardware perspectives.
关键词	Heterogeneous graph neural networks graph neural networks training characterization quantitative analysis optimization guidelines
DOI	10.1145/3703356
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program[2022YFB4501400] ; National Natural Science Foundation of China[62202451] ; CAS Project for Young Scientists in Basic Research[YSBR-029] ; CAS Project for Youth Innovation Promotion Association
WOS研究方向	Computer Science
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods
WOS记录号	WOS:001470292900008
出版者	ASSOC COMPUTING MACHINERY
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/40609
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Yan, Mingyu
作者单位	1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Processors, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Han, Dengke,Yan, Mingyu,Ye, Xiaochun,et al. Characterizing and Understanding HGNN Training on GPUs[J]. ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION,2025,22(1):25.
APA	Han, Dengke,Yan, Mingyu,Ye, Xiaochun,&Fan, Dongrui.(2025).Characterizing and Understanding HGNN Training on GPUs.ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION,22(1),25.
MLA	Han, Dengke,et al."Characterizing and Understanding HGNN Training on GPUs".ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION 22.1(2025):25.