| Cityflow: A multi-agent reinforcement learning environment for large scale city traffic scenario H Zhang, S Feng, C Liu, Y Ding, Y Zhu, Z Zhou, W Zhang, Y Yu, H Jin, Z Li The World Wide Web Conference, 3620-3624, 2019 | 417 | 2019 |
| GAN Compression: Efficient Architectures for Interactive Conditional GANs M Li, J Lin, Y Ding, Z Liu, JY Zhu, S Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 319 | 2020 |
| IOS: Inter-Operator Scheduler for CNN Acceleration Y Ding, L Zhu, Z Jia, G Pekhimenko, S Han Proceedings of Machine Learning and Systems 3, 2021 | 95 | 2021 |
| Hidet: Task-Mapping Programming Paradigm for Deep Learning Tensor Programs Y Ding, CH Yu, B Zheng, Y Liu, Y Wang, G Pekhimenko Proceedings of the 28th ACM International Conference on Architectural …, 2023 | 59 | 2023 |
| Grape: Practical and Efficient Graphed Execution for Dynamic Deep Neural Networks on GPUs B Zheng, CH Yu, J Wang, Y Ding, Y Liu, Y Wang, G Pekhimenko Proceedings of the 56th Annual IEEE/ACM International Symposium on …, 2023 | 8 | 2023 |
| Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation Y Ding, B Hou, X Zhang, A Lin, T Chen, CH Yu, Y Wang, G Pekhimenko Proceedings of the 31st ACM International Conference on Architectural …, 2026 | 5* | 2026 |
| LoRAFusion: Efficient LoRA Fine-Tuning for LLMs Z Zhu, Q Su, Y Ding, K Song, S Wang, G Pekhimenko arXiv preprint arXiv:2510.00206, 2025 | | 2025 |
| Aegis: Taxonomy and Optimizations for Overcoming Agent-Environment Failures in LLM Agents K Song, A Jayarajan, Y Ding, Q Su, Z Zhu, S Liu, G Pekhimenko arXiv preprint arXiv:2508.19504, 2025 | | 2025 |
| Hexcute: A Tile-based Programming Language with Automatic Layout and Task-Mapping Synthesis X Zhang, Y Ding, Y Hu, G Pekhimenko arXiv preprint arXiv:2504.16214, 2025 | | 2025 |
Gennady PekhimenkoUniversity of TorontoVerified email at cs.toronto.edu
