图计算体系结构和系统软件关键技术综述
Review of Key Technologies in Graph Processing Architectures and Systems Software
张宇 1姜新宇 1余辉 1赵进 1齐豪 1廖小飞 1金海 1王彪 2余婷2
作者信息
- 1. 大数据技术与系统国家地方联合工程研究中心(华中科技大学) 武汉 430074;服务计算技术与系统教育部重点实验室(华中科技大学) 武汉 430074;集群与网格计算湖北省重点实验室(华中科技大学) 武汉 430074;华中科技大学计算机科学与技术学院 武汉 430074
- 2. 之江实验室 杭州 311121
- 折叠
摘要
图计算作为分析事物之间关联关系的重要工具,近年来已成为各国政府及公司争夺的关键技术.学术界和工业界在图计算体系结构和系统软件关键技术方面取得了一定进展.然而,现实场景图计算大多具有动态变化、应用需求复杂多样等特征.这给图计算在基础理论、体系架构和系统软件关键技术方面提出了新的需求,同时也带来了新的挑战.为应对这些挑战,科研人员提出了一系列图计算系统或图计算加速器,通过高性能计算、并行计算等技术来优化图计算过程.综述国内外图计算体系结构和系统软件关键技术的研究发展现状,对国内外研究的最新进展进行归纳、比较和分析,并结合国家发展战略和重大应用需求,选取与我国国计民生密切相关的领域,从典型应用分析总结图计算相关技术的行业进展.最后,就未来的技术挑战和研究方向进行展望.
Abstract
In recent years,some progress has been made in the key technologies of the architecture and systems software for graph processing.Large-scale graph processing has also been widely used in many fields,including scientific computing,machine learning,social networks,intelligent transportation,bioinformatics,etc.However,most real-world graph computations have characteristics such as dynamic changes and complex and diverse application requirements.This poses new demands and challenges for graph processing in terms of basic theory,architecture,and key technologies of systems software.To address these challenges,researchers have proposed a series of graph processing systems and accelerators,which optimize the graph processing process through technologies such as high-performance computing and parallel computing.Furthermore,in order to meet the demands of practical application scenarios,various graph processing frameworks and algorithms are constantly being innovated and optimized,thus enhancing the practical value of graph processing in terms of processing large-scale graph data and improving computational efficiency.We review the research and development status of key technologies in graph processing architecture and systems software,and summarize,compare,analyze the latest progress of research at home and abroad,and select fields closely related to national economy and people's livelihood in combination with national development strategies and major application requirements.The industry progress of graph processing-related technologies is analyzed and summarized from typical applications.Finally,the future technical challenges and research directions are prospected.
关键词
图计算/体系结构/系统软件/图遍历/图挖掘/图神经网络/单机系统/分布式系统/加速器/行业应用Key words
graph processing/architecture/systems software/graph traversal/graph mining/graph neural network/single machine system/distributed system/accelerator/industry applications引用本文复制引用
基金项目
国家重点研发计划(2022YFB2404202)
国家自然科学基金(62072193)
之江实验室开放基金(2021KD0AB01)
之江实验室重大科研项目(2022PI0AC03)
出版年
2024
NETL
NSTL
万方数据