| Neutronstar: distributed GNN training with hybrid dependency management Q Wang, Y Zhang, H Wang, C Chen, X Zhang, G Yu Proceedings of the 2022 International Conference on Management of Data, 1301 …, 2022 | 48 | 2022 |
| Automating incremental and asynchronous evaluation for recursive aggregate data processing Q Wang, Y Zhang, H Wang, L Geng, R Lee, X Zhang, G Yu Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 24 | 2020 |
| 区块链系统的数据存储与查询技术综述 (Survey of Data Storage and Query Techniques in Blockchain Systems) Q Wang, P He, T Nie, D Shen, G Yu 计算机科学, 2018 | 17 | 2018 |
| Hongtu: Scalable full-graph GNN training on multiple gpus Q Wang, Y Chen, WF Wong, B He Proceedings of the ACM on Management of Data 1 (4), 1-27, 2023 | 13 | 2023 |
| HyTGraph: GPU-Accelerated Graph Processing with Hybrid Transfer Management Q Wang, X Ai, Y Zhang, J Chen, G Yu 2023 IEEE 39th International Conference on Data Engineering (ICDE), 558-571, 2023 | 12 | 2023 |
| 区块链系统的数据存储与查询技术综述 王千阁， 何蒲， 聂铁铮， 申德荣， 于戈 计算机科学 45 (12), 12-18, 2018 | 11 | 2018 |
| Comprehensive evaluation of gnn training systems: A data management perspective H Yuan, Y Liu, Y Zhang, X Ai, Q Wang, C Chen, Y Gu, G Yu arXiv preprint arXiv:2311.13279, 2023 | 8 | 2023 |
| Ragraph: A region-aware framework for geo-distributed graph processing F Yao, Q Tao, W Yu, Y Zhang, S Gong, Q Wang, G Yu, J Zhou Proceedings of the VLDB Endowment 17 (3), 264-277, 2023 | 8 | 2023 |
| NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments X Ai, Q Wang, C Cao, Y Zhang, C Chen, H Yuan, Y Gu, G Yu arXiv preprint arXiv:2311.13225, 2023 | 7 | 2023 |
| NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams C Chen, D Gao, Y Zhang, Q Wang, Z Fu, X Zhang, J Zhu, Y Gu, G Yu arXiv preprint arXiv:2312.02473, 2023 | 5 | 2023 |
| 大规模图神经网络系统综述 赵港， 王千阁， 姚烽， 张岩峰， 于戈 软件学报 33 (1), 150-170, 2021 | 5 | 2021 |
| Hongtu: Scalable full-graph gnn training on multiple gpus (via communication-optimized cpu data offloading) Q Wang, Y Chen, WF Wong, B He arXiv preprint arXiv:2311.14898, 2023 | 4 | 2023 |
| Unified-memory-based hybrid processing for partition-oriented subgraph matching on GPU J Chen, Q Wang, Y Gu, C Li, G Yu World Wide Web, 1-26, 2022 | 3 | 2022 |
| Partition-oriented subgraph matching on gpu J Chen, Y Gu, Q Wang, C Li, G Yu Web and Big Data: 4th International Joint Conference, APWeb-WAIM 2020 …, 2020 | 3 | 2020 |
| BG3: A Cost Effective and I/O Efficient Graph Database in Bytedance W Zhang, C Chen, Q Wang, W Wang, S Yang, B Zhou, H Zhu, C Chen, ... Companion of the 2024 International Conference on Management of Data, 360-372, 2024 | 2 | 2024 |
| Distributed graph processing: techniques and systems Y Zhang, Q Wang, S Gong Web and Big Data. APWeb-WAIM 2020 International Workshops: KGMA 2020 …, 2021 | 1 | 2021 |
| Towards Communication-Efficient Out-of-Core Graph Processing on the GPU Q Wang, X Ai, Y Yan, S Gong, Y Zhang, J Chen, G Yu IEEE Transactions on Parallel and Distributed Systems, 2025 | | 2025 |
| NeutronSketch: An in-depth exploration of redundancy in large-scale graph neural network training Y Liu, Y Zhang, Q Wang, H Yuan, X Ai, G Yu Knowledge-Based Systems 309, 112786, 2025 | | 2025 |
| Towards Efficient Graph Processing in Geo-Distributed Data Centers F Yao, Q Tao, S Lin, Y Zhang, W Yu, S Gong, Q Wang, G Yu, J Zhou IEEE Transactions on Parallel and Distributed Systems, 2024 | | 2024 |
Yanfeng ZhangNortheastern University, ChinaDirección de correo verificada de cc.neu.edu.cn
