Dimmining: pruning-efficient and parallel graph mining on near-memory-computing G Dai, Z Zhu, T Fu, C Wei, B Wang, X Li, Y Xie, H Yang, Y Wang Proceedings of the 49th Annual International Symposium on Computer …, 2022 | 29 | 2022 |
An efficient accelerator for point-based and voxel-based point cloud neural networks X Yang, T Fu, G Dai, S Zeng, K Zhong, K Hong, Y Wang 2023 60th ACM/IEEE Design Automation Conference (DAC), 1-6, 2023 | 4 | 2023 |
FlightLLM: Efficient Large Language Model Inference with a Complete Mapping Flow on FPGAs S Zeng, J Liu, G Dai, X Yang, T Fu, H Wang, W Ma, H Sun, S Li, Z Huang, ... Proceedings of the 2024 ACM/SIGDA International Symposium on Field …, 2024 | 2 | 2024 |
A Survey on Efficient Inference for Large Language Models Z Zhou, X Ning, K Hong, T Fu, J Xu, S Li, Y Lou, L Wang, Z Yuan, X Li, ... arXiv preprint arXiv:2404.14294, 2024 | 1 | 2024 |
Desco: Towards generalizable and scalable deep subgraph counting T Fu, C Wei, Y Wang, R Ying Proceedings of the 17th ACM International Conference on Web Search and Data …, 2024 | 1 | 2024 |
LessMine: Reducing Sample Space and Data Access for Dense Pattern Mining T Fu, Z Wan, G Dai, Y Wang, H Yang 2020 IEEE High Performance Extreme Computing Conference (HPEC), 1-7, 2020 | 1 | 2020 |
Representation Learning for Frequent Subgraph Mining R Ying, T Fu, A Wang, J You, Y Wang, J Leskovec arXiv preprint arXiv:2402.14367, 2024 | | 2024 |
CLAP: Locality Aware and Parallel Triangle Counting with Content Addressable Memory T Fu, C Wei, Z Zhu, S Yang, Z Yu, G Dai, H Yang, Y Wang 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1-6, 2023 | | 2023 |
SemSA: Semantic Sparse Attention is hidden in Large Language Models. T Fu, X Ning, B Chen, T Wu, G Zhang, G Dai, H Yang, Y Wang | | |