Da Zheng
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Deep graph library: A graph-centric, highly-performant package for graph neural networks
M Wang, D Zheng, Z Ye, Q Gan, M Li, X Song, J Zhou, C Ma, L Yu, Y Gai, ...
arXiv preprint arXiv:1909.01315, 2019
Deep graph library: Towards efficient and scalable deep learning on graphs
MY Wang
ICLR workshop on representation learning on graphs and manifolds, 2019
{FlashGraph}: Processing {Billion-Node} graphs on an array of commodity {SSDs}
D Zheng, D Mhembere, R Burns, J Vogelstein, CE Priebe, AS Szalay
13th USENIX Conference on File and Storage Technologies (FAST 15), 45-58, 2015
Distdgl: distributed graph neural network training for billion-scale graphs
D Zheng, C Ma, M Wang, J Zhou, Q Su, X Song, Q Gan, Z Zhang, ...
In 2020 IEEE/ACM 10th Workshop on Irregular Applications: Architectures and …, 2020
Dgl-ke: Training knowledge graph embeddings at scale
D Zheng, X Song, C Ma, Z Tan, Z Ye, J Dong, H Xiong, Z Zhang, ...
Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020
Drkg-drug repurposing knowledge graph for covid-19
VN Ioannidis, X Song, S Manchanda, M Li, X Pan, D Zheng, X Ning, ...
arXiv preprint arXiv:2010.09600, 2020
Featgraph: A flexible and efficient backend for graph neural network systems
Y Hu, Z Ye, M Wang, J Yu, D Zheng, M Li, Z Zhang, Z Zhang, Y Wang
SC20: International Conference for High Performance Computing, Networking …, 2020
Tgl: A general framework for temporal gnn training on billion-scale graphs
H Zhou, D Zheng, I Nisa, V Ioannidis, X Song, G Karypis
arXiv preprint arXiv:2203.14883, 2022
Toward millions of file system IOPS on low-cost, commodity hardware
D Zheng, R Burns, AS Szalay
Proceedings of the international conference on high performance computing …, 2013
Few-shot link prediction via graph neural networks for covid-19 drug-repurposing
VN Ioannidis, D Zheng, G Karypis
arXiv preprint arXiv:2007.10261, 2020
Collective multi-type entity alignment between knowledge graphs
Q Zhu, H Wei, B Sisman, D Zheng, C Faloutsos, XL Dong, J Han
Proceedings of The Web Conference 2020, 2241-2252, 2020
Supervised dimensionality reduction for big data
JT Vogelstein, EW Bridgeford, M Tang, D Zheng, C Douville, R Burns, ...
Nature communications 12 (1), 2872, 2021
Distributed hybrid cpu and gpu training for graph neural networks on billion-scale heterogeneous graphs
D Zheng, X Song, C Yang, D LaSalle, G Karypis
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
A parallel page cache: IOPS and caching for multicore systems
D Zheng, R Burns, AS Szalay
Proceedings of the 4th USENIX conference on Hot Topics in Storage and File …, 2012
Global neighbor sampling for mixed CPU-GPU training on giant graphs
J Dong, D Zheng, LF Yang, G Karypis
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
Semi-external memory sparse matrix multiplication for billion-node graphs
D Zheng, D Mhembere, V Lyzinski, JT Vogelstein, CE Priebe, R Burns
IEEE Transactions on Parallel and Distributed Systems 28 (5), 1470-1483, 2016
Traversenet: Unifying space and time in message passing for traffic forecasting
Z Wu, D Zheng, S Pan, Q Gan, G Long, G Karypis
IEEE Transactions on Neural Networks and Learning Systems, 2022
Scalable graph neural networks with deep graph library
D Zheng, M Wang, Q Gan, X Song, Z Zhang, G Karypis
Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021
Automatic parallelization of array-oriented programs for a multi-core machine
WM Ching, D Zheng
International Journal of Parallel Programming 40 (5), 514-531, 2012
Learning over families of sets-hypergraph representation learning for higher order tasks
B Srinivasan, D Zheng, G Karypis
Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021
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