之江实验室图计算研究中心/华中科技大学计算机科学与技术学院助理研究员，2022年9月在华中科技大学获得计算机系统结构博士学位，入选第九届中国科协青年人才托举工程，博士论文入选2023年度“CCF优秀博士学位论文激励计划”和2023年度“CCF体系结构优秀博士学位论文激励计划”。主要研究面向图计算的高性能体系结构和系统软件，相关成果在ISCA、SC、Eurosys、DAC、ACM TOS/TACO、IEEE TC/TKDE/TBD等会议和期刊上发表或录用学术论文20余篇，入选CCF A类期刊IEEE TC的Featured Paper of the Month等，研发的图计算引擎在图计算性能权威榜单Green Graph 500和Graph 500排名中多次位列第一，获第七届“互联网+”产业命题赛道全国金奖、第十三届“挑战杯”中国大学生创业计划竞赛全国金奖和2023年中国国际大学生创新大赛全国金奖，目前正在主持CCF-蚂蚁科研基金、之江实验室青年基金和第5批博士后特别资助（站前）等。
🔥 News
- 2024.02: 🎉🎉 Our papers “CDA-GNN: A Chain-driven Accelerator for Efficient Asynchronous Graph Neural Network” and “RTGA: A Redundancy-free Accelerator for High-Performance Temporal Graph Neural Network Inference” are accepted by DAC 2024!
- 2024.02: 🎉🎉 Our paper “LSGraph: A Locality-centric High-performance Streaming Graph Engine” is accepted by EuroSys 2024!
- 2024.01: 🎉🎉 Our paper “Computing Power Networking Meets Blockchain: A Reputation-enhanced Trading Framework for Decentralized IoT Cloud Services” is accepted by IoT!
- 2023.08: 🎉🎉 Our paper “RACE: An Efficient Redundancy-aware Accelerator for Dynamic Graph Neural Network” is accepted by ACM TACO!
- 2023.05: 🎉🎉 Our paper “GraphTune: An Efficient Dependency-Aware Substrate to Alleviate Irregularity in Concurrent Graph Processing” is accepted by ACM TACO!
- 2023.02: 🎉🎉 Our papers “SaGraph: A Similarity-aware Hardware Accelerator for Temporal Graph Processing” and “PSMiner: A Pattern-Aware Accelerator for High-Performance Streaming Graph Pattern Mining” are accepted by DAC 2023!
📝 Publications
- [Eurosys] Hao Qi, Yiyang Wu, Ligang He, Yu Zhang, Kang Luo, Minzhi Cai, Hai Jin, Zhan Zhang, Jin Zhao. LSGraph: A Locality-centric High-performance Streaming Graph Engine. In Proceedings of the 18th European Conference on Computer Systems (EuroSys’24), 1-17, 2024. (To appear)
- [DAC] Hui Yu, Yu Zhang, Ligang He, Donghao He, Qikun Li, Jin Zhao, Xiaofei Liao, Hai Jin, Lin Gu and Haikun Liu. CDA-GNN: A Chain-driven Accelerator for Efficient Asynchronous Graph Neural Network. In Proceedings of the 61st ACM/IEEE Design Automation Conference (DAC’24), 1-6, 2024. (To appear)
- [DAC] Hui Yu, Yu Zhang, Andong Tan, Chenze Lu, Jin Zhao, Xiaofei Liao, Hai Jin and Haikun Liu. RTGA: A Redundancy-free Accelerator for High-Performance Temporal Graph Neural Network Inference. In Proceedings of the 61st ACM/IEEE Design Automation Conference (DAC’24), 1-6, 2024. (To appear)
- [DAC] Jin Zhao, Yu Zhang, Jian Cheng, Yiyang Wu, Chuyue Ye, Hui Yu, Zhiying Huang, Hai Jin, Xiaofei Liao, Lin Gu, Haikun Liu. SaGraph: A Similarity-aware Hardware Accelerator for Temporal Graph Processing. In Proceedings of the 60th Design Automation Conference, 2023.
- [DAC] Hao Qi, Yu Zhang, Ligang He, Kang Luo, Jun Huang, Haoyu Lu, Jin Zhao, Hai Jin. PSMiner: A Pattern-Aware Accelerator for High-Performance Streaming Graph Pattern Mining. In Proceedings of the 60th Design Automation Conference, 2023.
- [ISCA] Jin Zhao, Yun Yang, Yu Zhang, Xiaofei Liao, Lin Gu, Ligang He, Bingsheng He, Hai Jin, Haikun Liu, Xinyu Jiang, Hui Yu. TDGraph: A Topology-Driven Accelerator for High-Performance Streaming Graph Processing. In Proceedings of the 2022 IEEE/ACM International Symposium on Computer Architecture, 2022.
- [SC] Jin Zhao, Yu Zhang, Xiaofei Liao, Ligang He, Bingsheng He, Hai Jin, Haikun Liu. LCCG: A Locality-centric Hardware Accelerator for High Throughput of Concurrent Graph Processing. In Proceedings of the 2021 International Conference for High Performance Computing, Networking, Storage, and Analysis, 2021.
- [SC] Jin Zhao, Yu Zhang, Xiaofei Liao, Ligang He, Bingsheng He, Hai Jin, Haikun Liu, Yicheng Chen. GraphM: An Efficient Storage System for High Throughput of Concurrent Graph Analytics. In Proceedings of the 2019 International Conference for High Performance Computing, Networking, Storage, and Analysis, 2019.
- [IoT] Li Lin, Jiapeng Wu, Zhi Zhou, Jin Zhao (Corresponding author), Peng Li, Jinbo Xiong. Computing Power Networking Meets Blockchain: A Reputation-enhanced Trading Framework for Decentralized IoT Cloud Services. IEEE Internet of Things Journal, 2024.
- [TACO] Jin Zhao, Yu Zhang, Ligang He, Qikun Li, Xiang Zhang, Hui Yu, Xiaofei Liao, Hai Jin, Lin Gu, Haikun Liu, Bingsheng He, Ji Zhang, Xianzheng Song, Lin Wang, Jun Zhuo. GraphTune: An Efficient Dependency-Aware Substrate to Alleviate Irregularity in Concurrent Graph Processing. ACM Transactions on Architecture and Code Optimization, 2023.
- [TACO] Hui Yu, Yu Zhang, Jin Zhao, Yujian Liao, Zhiying Huang, Donghao He, Lin Gu, Hai Jin, Xiaofei Liao, Haikun Liu. RACE: An Efficient Redundancy-aware Accelerator for Dynamic Graph Neural Network. ACM Transactions on Architecture and Code Optimization, 2023.
- [TC] Xiaofei Liao, Jin Zhao, Yu Zhang, Bingsheng He, Ligang He, Hai Jin, Lin Gu. A Structure-aware Storage Optimization for Out-of-Core Concurrent Graph Processing. IEEE Transactions on Computer
Featured Paper of the Month, 2022. - [TC] Hai Jin, Dan Chen, Long Zheng, Yu Huang, Pengcheng Yao, Jin Zhao, Xiaofei Liao, Wenbin Jiang. Accelerating Graph Convolutional Networks Through a PIM-Accelerated Approach. IEEE Transactions on Computers, 2023.
- [TKDE] Yu Zhang, Yuxuan Liang, Jin Zhao, Fubing Mao, Lin Gu, Xiaofei Liao, Hai Jin, Haikun Liu, Song Guo, Yangqing Zeng, Hang Hu. EGraph: efficient concurrent GPU-based dynamic graph processing. IEEE Transactions on Knowledge and Data Engineering, 2023.
- [JCST] Hui Yu, Xinyu Jiang, Jin Zhao, Hao Qi, Yu Zhang, Xiaofei Liao, Haikun Liu, Fubing Mao, Hai Jin. Toward High-Performance Delta-Based Iterative Processing with a Group-Based Approach. Journal of Computer Science and Technology, 2022.
- [Intelligent Computing] Hai Jin, Hao Qi, Jin Zhao, Xinyu Jiang, Yu Huang, Chuangyi Gui, Qinggang Wang, Xinyang Shen, Yi Zhang, Ao Hu, Dan Chen, Chaoqiang Liu, Haifeng Liu, Haiheng He, Xiangyu Ye, Runze Wang, Jingrui Yuan, Pengcheng Yao, Yu Zhang, Long Zheng, Xiaofei Liao. Software Systems Implementation and Domain-Specific Architectures towards Graph Analytics. Intelligent Computing, 2022.
- [TBD] Beibei Si, Yuxuan Liang, Jin Zhao, Yu Zhang, Xiaofei Liao, Hai Jin, Haikun Liu, Lin Gu. GGraph: An Efficient Structure-aware Approach for Iterative Graph Processing. IEEE Transactions on Big Data, 2022.
- [TOS] Yu Zhang, Jin Zhao, Xiaofei Liao, Hai Jin, Lin Gu, Haikun Liu, Bingsheng He, Ligang He. CGraph: A Distributed Storage and Processing System for Concurrent Iterative Graph Analysis Jobs. ACM Transactions on Storage, 2019.
- [中国科学: 信息科学] 赵进, 姜新宇, 张宇, 廖小飞, 金海, 刘海坤, 杨赟, 张吉, 王彪, 余婷. 一种高效的面向高并发图分析任务的存储系统. 中国科学: 信息科学, 2022.
- [中国科学: 信息科学] 杨赟, 余辉, 赵进, 张宇, 廖小飞, 姜新宇, 刘海坤, 毛伏兵, 张吉, 王彪. 面向动态有向图的单调图算法硬件加速机制. 中国科学: 信息科学, 2023.
- [中国科学:信息科学] 毛伏兵, 彭达, 张宇, 廖小飞, 姜新宇,杨赟, 金海, 赵进, 刘海坤, 王柳峥. 图计算在ATPG中的应用探究. 中国科学: 信息科学, 2023.
- [中国科学:信息科学] 廖小飞, 陈意诚, 张宇, 金海, 刘海坤, 赵进. 一种高效的面向动态有向图的增量强连通分量算法. 中国科学:信息科学, 2019.
🎖 Honors and Awards
- 2023年度“CCF优秀博士学位论文激励计划”
- 2023年中国国际大学生创新大赛全国金奖
- 2023年“CCF体系结构优秀博士学位论文激励计划”
- 2023年获得第十三届“挑战杯”中国大学生创业计划竞赛全国金奖
- 2022年在图学习“国际开放图基准数据集挑战赛”的链接属性预测赛道预测精度排名全球第一
- 2022/2023年在第24、25和26届Graph 500排名中，SSSP性能蝉联全球第一、BFS性能全球第二（国内第一）
- 2022年入选第八届“长江学子”开拓创新类
- 2021年获得国家奖学金、达梦奖学金、华为奖学金、腾讯奖学金
- 2021年获得第七届中国国际“互联网+”大学生创新创业大赛全国金奖
- 2021年在第18届Green Graph 500排名中，性能功耗比全球第一
📖 Educations
- 2017.09-2022.08，华中科技大学，计算机软件与理论，计算机科学与计算学院，博士 （导师：廖小飞教授）
- 2013.09-2017.06，中国地质大学(武汉)，信息安全，计算机学院，学士
💬 Invited Talks
- 2023.09, A Joint Workshop on Hot Topics on Big data and AI，“High-performance Graph Processing over Streaming Graphs”.
- 2023.08, HPC China 2023 “第二届高性能图计算优化技术” 论坛，报告：动态图计算优化技术研究.
- 2023.08, CCFSys 2023 “高性能图计算体系结构和系统软件” 论坛，论坛主席.
- 2022.12, CNCC 2022 “面向复杂图计算应用的新型高能效体系结构” 论坛，报告：拓扑驱动的动态图计算硬件加速机制研究.
- 2022.06, 鲲鹏开发者峰会 2022，报告：基于鲲鹏BoostKit，打造全球领先的图计算系统.
- 2019.08, HPC China 2019 “ 第五届HPC Plus论坛”，报告：面向并发图计算任务的存储系统.
💻 Internships
- 2019.05-2019.09，新加坡国立大学（导师：何丙胜教授），新加坡.
📝 Projects
- CCF-蚂蚁科研基金（主持） 高性能分布式图神经网络系统优化技术研究（No.RF20220211）
- 之江实验室青年基金 （主持）图结构感知的高性能图处理优化技术研究（No.K2023PI0AA01）
- 博士后特别资助（站前）（主持）高性能动态图处理系统关键技术研究（No.2023TQ0325）
- 国家重点研发计划项目（核心骨干）面向图计算的通用计算机技术与系统（No.2018YFB1003500）
- 国家自然科学基金重点项目 （核心骨干） 面向大数据高效处理的体系结构与关键技术（No. 61832006）
- 国家自然科学基金 （核心骨干） 关联性感知的并发图计算系统优化机制研究 (No.6170050426)
- 国家自然科学基金 （核心骨干） 面向高并发图分析服务的运行时系统关键技术研究 (No.6207050010)
- 之江实验室开放课题 （核心骨干） 面向高并发图分析服务的运行时系统关键技术研究（No.2021KD0AB01）
- 之江实验室重大项目 （核心骨干） 高并发分布式图计算系统（No.2022PI0AC03）
- 华为联合实验室项目 （核心骨干） 异步动态图计算加速器设计（No.YBN2021035018A5）
- 华为联合实验室项目 （核心骨干） 面向大规模图分析和图神经网络的高性能统一计算框架（No.YBN2021035018A6）
- 华为海思项目 （核心骨干） 图计算在ATPG中的应用探索（No.YBN2020115040）