A Nonlinear Array Subscripts Dependence Test. - Jie Zhao 002; Rongcai Zhao; Han Lin (HPCC-ICESS, 2012)

A Nested Loop Fusion Algorithm Based on Cost Analysis. - Jie Zhao 002; Rongcai Zhao; Yao Yuan (HPCC-ICESS, 2012)

A Max-Plus Algebra Approach for Network-on-Chip End-to-End Delay Estimation. - Baoliang Li; Jie Zhao 002; Junhui Wang; Wenhua Dou (SKG, 2012)

QP test: a dependence test for quadratic array subscripts. - Jie Zhao 002; Rongcai Zhao; Lin Han; Jinlong Xu (IET Softw., 2013)

An improved nonlinear data dependence test. - Jie Zhao 002; Rongcai Zhao; Xi Chen; Bo Zhao 010 (J. Supercomput., 2015)

Code Generation for Distributed-Memory Architectures. - Jie Zhao 002; Rongcai Zhao; Jinchen Xu (Comput. J., 2016)

Identifying superword level parallelism with extended directed dependence graph reachability. - Jie Zhao 002; Rongcai Zhao (Sci. China Inf. Sci., 2017)

A polyhedral compilation framework for loops with dynamic data-dependent bounds. - Jie Zhao 002; Michael Kruse; Albert Cohen 001 (CC, 2018)

A Practical and Aggressive Loop Fission Technique. - Bo Zhao 010; Yingying Li; Lin Han; Jie Zhao 002; Wei Gao 011; Rongcai Zhao; Ramin Yahyapour (ICA3PP (Workshops), 2018)

K-DT: a formal system for the evaluation of linear data dependence testing techniques. - Jie Zhao 002; Rongcai Zhao (J. Supercomput., 2018)

A Combined Language and Polyhedral Approach for Heterogeneous Parallelism. (Une Approche Combinée Langage-Polyédrique pour la Programmation Parallèle Hétérogène). - Jie Zhao 002 (2018)

WCCV: improving the vectorization of IF-statements with warp-coherent conditions. - Huihui Sun; Florian Fey; Jie Zhao 002; Sergei Gorlatch (ICS, 2019)

Optimizing the Memory Hierarchy by Compositing Automatic Transformations on Computations and Data. - Jie Zhao 002; Peng Di (MICRO, 2020)

Flextended Tiles: A Flexible Extension of Overlapped Tiles for Polyhedral Compilation. - Jie Zhao 002; Albert Cohen 001 (ACM Trans. Archit. Code Optim., 2020)

AKG: automatic kernel generation for neural processing units using polyhedral transformations. - Jie Zhao 002; Bojie Li; Wang Nie; Zhen Geng; Renwei Zhang; Xiong Gao; Bin Cheng; Chen Wu; Yun Cheng; Zheng Li; Peng Di; Kun Zhang; et al. (PLDI, 2021)

OneFlow: Redesign the Distributed Deep Learning Framework from Scratch. - Jinhui Yuan; Xinqi Li; Cheng Cheng; Juncheng Liu; Ran Guo; Shenghang Cai; Chi Yao; Fei Yang; Xiaodong Yi 001; Chuan Wu 001; Haoran Zhang; Jie Zhao 002 (CoRR, 2021)

Parallelizing Neural Network Models Effectively on GPU by Implementing Reductions Atomically. - Jie Zhao 002; Cédric Bastoul; Yanzhi Yi; Jiahui Hu; Wang Nie; Renwei Zhang; Zhen Geng; Chong Li 003; Thibaut Tachon; Zhiliang Gan (PACT, 2022)

Automatically Generating High-performance Matrix Multiplication Kernels on the Latest Sunway Processor. - Xiaohan Tao; Yu Zhu; Boyang Wang; Jinlong Xu; Jianmin Pang; Jie Zhao 002 (ICPP, 2022)

Apollo: Automatic Partition-based Operator Fusion through Layer by Layer Optimization. - Jie Zhao 002; Xiong Gao; Ruijie Xia; Zhaochuang Zhang; Deshi Chen; Lei Chen; Renwei Zhang; Zhen Geng; Bin Cheng; Xuefeng Jin (MLSys, 2022)

Eiffel: Inferring Input Ranges of Significant Floating-point Errors via Polynomial Extrapolation. - Zuoyan Zhang; Bei Zhou; Jiangwei Hao; Hongru Yang; Mengqi Cui; Yuchang Zhou; Guanghui Song; Fei Li 045; Jinchen Xu; Jie Zhao 002 (ASE, 2023)

SIRIUS: Harvesting Whole-Program Optimization Opportunities for DNNs. - Yijin Li; Jiacheng Zhao; Qianqi Sun; Haohui Mai; Lei Chen; Wanlu Cao; Yanfan Chen; Zhicheng Li; Ying Liu 055; Xinyuan Zhang; Xiyu Shi; Jie Zhao 002; et al. (MLSys, 2023)

Effectively Scheduling Computational Graphs of Deep Neural Networks toward Their Domain-Specific Accelerators. - Jie Zhao 002; Siyuan Feng; Xiaoqiang Dan; Fei Liu; Chengke Wang; Sheng Yuan; Wenyuan Lv; Qikai Xie (OSDI, 2023)

Modeling the Interplay between Loop Tiling and Fusion in Optimizing Compilers Using Affine Relations. - Jie Zhao 002; Jinchen Xu; Peng Di; Wang Nie; Jiahui Hu; Yanzhi Yi; Sijia Yang; Zhen Geng; Renwei Zhang; Bojie Li; Zhiliang Gan; Xuefeng Jin (ACM Trans. Comput. Syst., 2023)

Arfa: An Agile Regime-Based Floating-Point Optimization Approach for Rounding Errors. - Jinchen Xu; Mengqi Cui; Fei Li 045; Zuoyan Zhang; Hongru Yang; Bei Zhou; Jie Zhao 002 (ISSTA, 2024)

Enabling Tensor Language Model to Assist in Generating High-Performance Tensor Programs for Deep Learning. - Yi Zhai; Sijia Yang; Keyu Pan; Renwei Zhang; Shuo Liu; Chao Liu; Zichun Ye; Jianmin Ji; Jie Zhao 002; Yu Zhang 086; Yanyong Zhang (OSDI, 2024)

A Holistic Approach to Automatic Mixed-Precision Code Generation and Tuning for Affine Programs. - Jinchen Xu; Guanghui Song; Bei Zhou; Fei Li 045; Jiangwei Hao; Jie Zhao 002 (PPoPP, 2024)

Optimizing Deep Learning Inference Efficiency through Block Dependency Analysis. - Zhanyuan Di; Leping Wang; En Shao; Zhaojia Ma; Ziyi Ren; Feng Hua; Lixian Ma; Jie Zhao 002; Guangming Tan; Ninghui Sun (ASPLOS (2), 2025)

Post-Link Outlining for Code Size Reduction. - Shaobai Yuan; Jihong He; Yihui Xie; Feng Wang 050; Jie Zhao 002 (CC, 2025)

Magneto: Accelerating Parallel Structures in DNNs via Co-Optimization of Operators. - Zhanyuan Di; Leping Wang; Ziyi Ren; En Shao; Jie Zhao 002; Siyuan Feng; Dingwen Tao; Guangming Tan; Ninghui Sun (PPoPP, 2025)