| Machine learning for electronic design automation: A survey G Huang, J Hu, Y He, J Liu, M Ma, Z Shen, J Wu, Y Xu, H Zhang, K Zhong, ... ACM Transactions on Design Automation of Electronic Systems (TODAES) 26 (5 …, 2021 | 197 | 2021 |
| Understanding gnn computational graph: A coordinated computation, io, and memory perspective H Zhang, Z Yu, G Dai, G Huang, Y Ding, Y Xie, Y Wang Proceedings of Machine Learning and Systems 4, 467-484, 2022 | 35 | 2022 |
| Cogdl: A comprehensive library for graph deep learning Y Cen, Z Hou, Y Wang, Q Chen, Y Luo, Z Yu, H Zhang, X Yao, A Zeng, ... Proceedings of the ACM Web Conference 2023, 747-758, 2023 | 11 | 2023 |
| Heuristic adaptability to input dynamics for spmm on gpus G Dai, G Huang, S Yang, Z Yu, H Zhang, Y Ding, Y Xie, H Yang, Y Wang Proceedings of the 59th ACM/IEEE Design Automation Conference, 595-600, 2022 | 10 | 2022 |
| Hypergef: A framework enabling efficient fusion for hypergraph neural network on gpus Z Yu, G Dai, S Yang, G Zhang, H Zhang, F Zhu, J Yang, J Zhao, Y Wang Proceedings of Machine Learning and Systems 5, 2023 | 3 | 2023 |
| A Hardware Evaluation Framework for Large Language Model Inference H Zhang, A Ning, R Prabhakar, D Wentzlaff arXiv preprint arXiv:2312.03134, 2023 | | 2023 |
