| 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 | 422 | 2021 |
| GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks G Huang, G Dai, W Yu, Y Huazhong Proceedings of the International Conference for High Performance Computing …, 2020 | 198 | 2020 |
| {TC-GNN}: Bridging Sparse {GNN} Computation and Dense Tensor Cores on {GPUs} Y Wang, B Feng, Z Wang, G Huang, Y Ding 2023 USENIX Annual Technical Conference (USENIX ATC 23), 149-164, 2023 | 90 | 2023 |
| 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 | 81 | 2022 |
| Lightseq2: Accelerated training for transformer-based models on gpus X Wang, Y Wei, Y Xiong, G Huang, X Qian, Y Ding, M Wang, L Li SC22: International Conference for High Performance Computing, Networking …, 2022 | 49 | 2022 |
| Mixdq: Memory-efficient few-step text-to-image diffusion models with metric-decoupled mixed precision quantization T Zhao, X Ning, T Fang, E Liu, G Huang, Z Lin, S Yan, G Dai, Y Wang European Conference on Computer Vision, 285-302, 2024 | 35 | 2024 |
| 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 | 35 | 2022 |
| Alcop: Automatic load-compute pipelining in deep learning compiler for ai-gpus G Huang, Y Bai, L Liu, Y Wang, B Yu, Y Ding, Y Xie Proceedings of Machine Learning and Systems 5, 680-694, 2023 | 30 | 2023 |
| Shfl-BW: accelerating deep neural network inference with tensor-core aware weight pruning G Huang, H Li, M Qin, F Sun, Y Ding, Y Xie Proceedings of the 59th ACM/IEEE Design Automation Conference, 1153-1158, 2022 | 22 | 2022 |
| RM-STC: Row-Merge Dataflow Inspired GPU Sparse Tensor Core for Energy-Efficient Sparse Acceleration G Huang, Z Wang, PA Tsai, C Zhang, Y Ding, Y Xie Proceedings of the 56th Annual IEEE/ACM International Symposium on …, 2023 | 20 | 2023 |
| Exploiting Online Locality and Reduction Parallelism for Sampled Dense Matrix Multiplication on GPUs Z Yu, G Dai, G Huang, Y Wang, H Yang 2021 IEEE 39th International Conference on Computer Design (ICCD), 567-574, 2021 | 14 | 2021 |
| {OPER}:{Optimality-Guided} Embedding Table Parallelization for Large-scale Recommendation Model Z Wang, Y Wang, B Feng, G Huang, D Mudigere, B Muthiah, A Li, Y Ding 2024 USENIX Annual Technical Conference (USENIX ATC 24), 667-682, 2024 | 5 | 2024 |
| Efficient Sparse Matrix Kernels based on Adaptive Workload-Balancing and Parallel-Reduction G Huang, G Dai, Y Wang, Y Ding, Y Xie arXiv preprint arXiv:2106.16064, 2021 | 5 | 2021 |
| Enabling Efficient Sparse Multiplications on GPUs with Heuristic Adaptability J Xu, S Huang, J Li, G Huang, Y Xie, Y Wang, G Dai IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2024 | 3 | 2024 |
| Low-power in-pixel buffer circuit for smart image sensor Q Li, H Zhu, G Huang, Z Yu, F Qiao, Q Wei, X Liu, H Yang Sensor Review 40 (5), 585-590, 2020 | 1 | 2020 |
| TRACI: Network Acceleration of Input-Dynamic Communication for Large-Scale Deep Learning Recommendation Model G Huang, H Li, L Qin, J Huang, Y Kang, Y Ding, Y Xie Proceedings of the 52nd Annual International Symposium on Computer …, 2025 | | 2025 |
| {GMI-DRL}: Empowering {Multi-GPU}{DRL} with {Adaptive-Grained} Parallelism Y Wang, B Feng, Z Wang, G Huang, TT Geng, A Li, Y Ding 2025 USENIX Annual Technical Conference (USENIX ATC 25), 89-103, 2025 | | 2025 |
| Warp execution method and associated GPU Y Gao, F Sun, H Li, G Huang, C Zhang, R Zhong US Patent 12,100,064, 2024 | | 2024 |
| High-Performance Deep Learning Systems via DL Sparsity and DL Compiler G Huang University of California, Santa Barbara, 2024 | | 2024 |
| Systems and methods for neural network training with weight sparsity F Sun, M Qin, H Li, G Zhu, Y Gao, G Huang, Y Zhang US Patent App. 17/866,194, 2023 | | 2023 |
Yu Wang (汪玉)Department of Electronic Engineering, Tsinghua University, ChinaVerified email at mail.tsinghua.edu.cn
