Publications

Yi Zhai, Sijia Yang, Keyu Pan, Renwei Zhang, Shuo Liu, Chao Liu, Zichun Ye, Jianmin Ji, Jie Zhao, Yu Zhang, Yanyong Zhang (2024). Enabling Tensor Language Model to Assist in Generating High-Performance Tensor Programs for Deep Learning. In OSDI 2024.

Jinchen Xu, Mengqi Cui, Fei Li, Zuoyan Zhang, Hongru Yang, Bei Zhou, Jie Zhao (2024). Arfa: an Agile Regime-based Floating-point Optimization Approach for Rounding Errors. In ISSTA 2024.

Jinchen Xu, Guanghui Song, Bei Zhou, Fei Li, Jiangwei Hao, Jie Zhao (2024). A Holistic Approach to Automatic Mixed-Precision Code Generation and Tuning for Affine Programs. In PPoPP 2024.

PDF Cite Code Dataset

Jie Zhao, Jinchen Xu, Peng Di, Wang Nie, Jiahui Hu, Yanzhi Yi, Sijia Yang, Zhen Geng, Renwei Zhang, Bojie Li, Zhiliang Gan, Xuefeng Jin (2024). Modeling the Interplay between Loop Tiling and Fusion in Optimizing Compilers Using Affine Relations. ACM Transactions on Computer Systems.

Yijin Li, Jiacheng Zhao, Qianqi Sun, Haohui Mai, Lei Chen, Wanlu Cao, Yanfan Chen, Zhicheng Li, Ying Liu, Xinyuan Zhang, Xiyu Shi, Jie Zhao, Jingling Xue, Huimin Cui, Xiaobing Feng (2023). SIRIUS: Harvesting Whole-Program Optimization Opportunities for DNNs. In MLSys 2023.

Zuoyan Zhang, Bei Zhou, Jiangwei Hao, Hongru Yang, Mengqi Cui, Yuchang Zhou, Guanghui Song, Fei Li, Jinchen Xu, Jie Zhao (2023). Eiffel: Inferring Input Ranges of Significant Floating-point Errors via Polynomial Extrapolation. In ASE 2023.

Jie Zhao, Xiong Gao, Ruijie Xia, Zhaochuang Zhang, Deshi Chen, Lei Chen, Renwei Zhang, Zhen Geng, Bin Cheng, Xuefeng Jin (2023). Apollo: Automatic Partition-based Operator Fusion through Layer by Layer Optimization. In MLSys 2022.

Jie Zhao, Siyuan Feng, Xiaoqiang Dan, Fei Liu, Chengke Wang, Sheng Yuan, Wenyuan Lv, Qikai Xie (2023). Effectively Scheduling Computational Graphs of Deep Neural Networks toward Their Domain-Specific Accelerators. In OSDI 2023.

Jie Zhao, Cédric Bastoul, Yanzhi Yi, Jiahui Hu, Wang Nie, Renwei Zhang, Zhen Geng, Chong Li, Thibaut Tachon, Zhiliang Gan (2022). Parallelizing Neural Network Models Effectively on GPU by Implementing Reductions Atomically. In PACT 2022.

Xiaohan Tao, Yu Zhu, Boyang Wang, Jinlong Xu, Jianmin Pang, Jie Zhao (2022). Automatically Generating High-performance Matrix Multiplication Kernels on the Latest Sunway Processor. In ICPP 2022.

Jie Zhao, Bojie Li, Wang Nie, Zhen Geng, Renwei Zhang, Xiong Gao, Bin Cheng, Chen Wu, Yun Cheng, Zheng Li, Peng Di, Kun Zhang, Xuefeng Jin (2021). AKG: automatic kernel generation for neural processing units using polyhedral transformations. In PLDI 2021.

Jie Zhao, Peng Di (2020). Optimizing the Memory Hierarchy by Compositing Automatic Transformations on Computations and Data. In MICRO 2020.

Jie Zhao, Albert Cohen (2019). Flextended Tiles: A Flexible Extension of Overlapped Tiles for Polyhedral Compilation. In TACO 2019.

Jie Zhao, Michael Kruse, Albert Cohen (2018). A polyhedral compilation framework for loops with dynamic data-dependent bounds. In CC 2018.