publications

2024

1. arxiv

   GeoT: Tensor Centric Library for Graph Neural Network via Efficient Segment Reduction on GPU

   Zhongming Yu, Genghan Zhang, Hanxian Huang, and 2 more authors

   arXiv preprint arXiv:2404.03019, 2024

   Code

2023

1. www

   Cogdl: A comprehensive library for graph deep learning

   Yukuo Cen, Zhenyu Hou, Yan Wang, and 8 more authors

   In Proceedings of the ACM Web Conference 2023, 2023

   Bib HTML Code

   @inproceedings{cen2023cogdl,
     title = {Cogdl: A comprehensive library for graph deep learning},
     author = {Cen, Yukuo and Hou, Zhenyu and Wang, Yan and Chen, Qibin and Luo, Yizhen and Yu, Zhongming and Zhang, Hengrui and Yao, Xingcheng and Zeng, Aohan and Guo, Shiguang and others},
     booktitle = {Proceedings of the ACM Web Conference 2023},
     pages = {747--758},
     year = {2023},
   }

2. mlsys

   HyperGef: A Framework Enabling Efficient Fusion for Hypergraph Neural Network on GPUs

   Zhongming Yu, Guohao Dai, Shang Yang, and 6 more authors

   Proceedings of Machine Learning and Systems, 2023

   Bib HTML Code

   @article{yu2023hypergef,
     title = {HyperGef: A Framework Enabling Efficient Fusion for Hypergraph Neural Network on GPUs},
     author = {Yu, Zhongming and Dai, Guohao and Yang, Shang and Zhang, Genghan and Zhang, Hengrui and Zhu, Feiwen and Yang, June and Zhao, Jishen and Wang, Yu},
     journal = {Proceedings of Machine Learning and Systems},
     volume = {5},
     year = {2023},
   }

3. cvpr

   TorchSparse++: Efficient Point Cloud Engine

   Haotian Tang, Shang Yang, Zhijian Liu, and 6 more authors

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

   Poster

   Bib HTML Code

   @inproceedings{tang2023torchsparse++,
     title = {TorchSparse++: Efficient Point Cloud Engine},
     author = {Tang, Haotian and Yang, Shang and Liu, Zhijian and Hong, Ke and Yu, Zhongming and Li, Xiuyu and Dai, Guohao and Wang, Yu and Han, Song},
     booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
     pages = {202--209},
     note = {Poster},
     year = {2023},
   }

4. mlsys

   Exploiting Hardware Utilization and Adaptive Dataflow for Efficient Sparse Convolution in 3D Point Clouds

   Ke Hong*, Zhongming Yu*, Guohao Dai, and 4 more authors

   Proceedings of Machine Learning and Systems, 2023

   * stands for equal contribution

   Bib HTML Code

   @article{hong2023exploiting,
     title = {Exploiting Hardware Utilization and Adaptive Dataflow for Efficient Sparse Convolution in 3D Point Clouds},
     author = {Hong*, Ke and Yu*, Zhongming and Dai, Guohao and Yang, Xinhao and Lian, Yaoxiu and Xu, Ningyi and Wang, Yu},
     journal = {Proceedings of Machine Learning and Systems},
     volume = {5},
     note = {* stands for equal contribution},
     year = {2023},
   }

2022

1. mlsys

   Understanding gnn computational graph: A coordinated computation, io, and memory perspective

   Hengrui Zhang*, Zhongming Yu*, Guohao Dai, and 4 more authors

   Proceedings of Machine Learning and Systems, 2022

   * stands for equal contribution

   Bib HTML Code

   @article{zhang2022understanding,
     title = {Understanding gnn computational graph: A coordinated computation, io, and memory perspective},
     author = {Zhang*, Hengrui and Yu*, Zhongming and Dai, Guohao and Huang, Guyue and Ding, Yufei and Xie, Yuan and Wang, Yu},
     journal = {Proceedings of Machine Learning and Systems},
     note = {* stands for equal contribution},
     volume = {4},
     pages = {467--484},
     year = {2022},
   }

2. arxiv

   Benchmarking GNN-Based Recommender Systems on Intel Optane Persistent Memory

   Yuwei Hu, Jiajie Li, Zhongming Yu, and 1 more author

   arXiv preprint arXiv:2207.11918, 2022

   Bib HTML

   @article{hu2022benchmarking,
     title = {Benchmarking GNN-Based Recommender Systems on Intel Optane Persistent Memory},
     author = {Hu, Yuwei and Li, Jiajie and Yu, Zhongming and Zhang, Zhiru},
     journal = {arXiv preprint arXiv:2207.11918},
     year = {2022},
   }

2021

1. iccd

   Exploiting Online Locality and Reduction Parallelism for Sampled Dense Matrix Multiplication on GPUs

   Zhongming Yu, Guohao Dai, Guyue Huang, and 2 more authors

   In 2021 IEEE 39th International Conference on Computer Design (ICCD), 2021

   Bib HTML Code

   @inproceedings{yu2021exploiting,
     title = {Exploiting Online Locality and Reduction Parallelism for Sampled Dense Matrix Multiplication on GPUs},
     author = {Yu, Zhongming and Dai, Guohao and Huang, Guyue and Wang, Yu and Yang, Huazhong},
     booktitle = {2021 IEEE 39th International Conference on Computer Design (ICCD)},
     pages = {567--574},
     year = {2021},
     organization = {IEEE}
   }