swPredictor: A data-driven performance model for distributed data parallelism training on large-scale HPC clusters

ZhuXianyuWuRuohanChenJunshiAnHong

高性能计算与并行算法方向论文：swPredictor: A data-driven performance model for distributed data parall

◫预览 PDFPreview PDF ↓下载 PDFDownload PDF ↗在线页面Official page ◇DOI

内容导读Reading note

分类与摘要Category & abstract

关注大规模并行算法、超算平台和性能优化，是 HPC 方向的重要条目。

Evidence note

llelism training on large-scale HPC clusters Xianyu Zhu a , Ruohan Wu a , Junshi Chen a,b ,∗, Hong An a,b a University of Science and Technology of China, Hefei, Anhui, China b Laoshan Laboratory, Qingdao, China A R T I C L E I N F O Keywords: High-performance computing Performance modeling Deep learning Distributed training A B S T R A C T Given the complexity of heterogeneous architectures and multi-node col || llelism training on large-scale HPC clusters Xianyu Zhu a , Ruohan Wu a , Junshi Chen a,b ,∗, Hong An a,b a University of Science and Technology of China, Hefei, Anhui, China b Laoshan Laboratory, Qingdao, China A R T I C L E I N F O Keywords: High-performance computing Performance modeling Deep learning Distributed training A B S T R A C T Given the complexity of heterogeneous architectures and mul || pported by the Chinese Academy of Sciences (Strategic Priority Research Program, China), Grant (XDB0500102). And this work is financially supported by Laoshan Laboratory (China) (LSKJ202300305). We would like to thank Ziyue You from the University of Edinburgh, Shengtao Xue from the Northwest A&F University and Jiahao Huang from the National University of Singapore, for their valuable feedback and assistanc || pported by the Chinese Academy of Sciences (Strategic Priority Research Program, China), Grant (XDB0500102). And this work is financially supported by Laoshan Laboratory (China) (LSKJ202300305). We would like to thank Ziyue You from the University of Edinburgh, Shengtao Xue from the Northwest A&F University and Jiahao Huang from the National University of Singapore, for their valuable feedback and

Metadata

完整论文信息Full record

title: swPredictor: A data-driven performance model for distributed data parallelism training on large-scale HPC clusters
title_zh: 待补充
abstract: 待补充
abstract_zh: 待补充
keywords: HPC, Distributed, 学位认定 B, CCF B
year: 2025
published_date: 待补充
online_date: 待补充
paper_type: Journal
publication_status: Published
volume: 待补充
issue: 待补充
pages: 待补充
article_number: 待补充
publisher: 待补充
doi: 10.1016/j.peva.2025.102530
research_area: 高性能计算与并行算法
tags: HPC, Distributed, 学位认定 B, CCF B
category: 高性能计算与并行算法
summary: 关注大规模并行算法、超算平台和性能优化，是 HPC 方向的重要条目。
authors: Zhu, Xianyu, Wu, Ruohan, Chen, Junshi, An, Hong
corresponding_authors: 否
affiliations: 待补充
funding: 崂山实验室项目

Research area

高性能计算与并行算法

Citation

Zhu, Xianyu; Wu, Ruohan; Chen, Junshi; An, Hong，swPredictor: A data-driven performance model for distributed data parallelism training on large-scale HPC clusters，PERFORMANCE EVALUATION，VOL170，November ,2025 （CCF B）

BibTeX

@article{acsa2025_4,
  title = {swPredictor: A data-driven performance model for distributed data parallelism training on large-scale HPC clusters},
  year = {2025},
  doi = {10.1016/j.peva.2025.102530}
}