Benchmarking Deep Learning Frameworks with FPGA-suitable Models on a Traffic Sign Dataset. - Zhongyi Lin; Jeffrey M. Ota; John D. Owens; Pinar Muyan-Özçelik (Intelligent Vehicles Symposium, 2018)

Accelerating DNN Inference with GraphBLAS and the GPU. - Xiaoyun Wang; Zhongyi Lin; Carl Yang 002; John D. Owens (HPEC, 2019)

Benchmarking Deep Learning Frameworks and Investigating FPGA Deployment for Traffic Sign Classification and Detection. - Zhongyi Lin; Matthew Yih; Jeffrey M. Ota; John D. Owens; Pinar Muyan-Özçelik (IEEE Trans. Intell. Veh., 2019)

Towards Flexible and Compiler-Friendly Layer Fusion for CNNs on Multicore CPUs. - Zhongyi Lin; Evangelos Georganas; John D. Owens (Euro-Par, 2021)

Research on Optimization of Urban Public Transport Network Based on Complex Network Theory. - Zhongyi Lin; Yang Cao; Huasheng Liu; Jin Li; Shuzhi Zhao (Symmetry, 2021)

Building a Performance Model for Deep Learning Recommendation Model Training on GPUs. - Zhongyi Lin; Louis Feng; Ehsan K. Ardestani; Jaewon Lee; John Lundell; Changkyu Kim; Arun Kejariwal; John D. Owens (HIPC, 2022)

Mystique: Enabling Accurate and Scalable Generation of Production AI Benchmarks. - Mingyu Liang; Wenyin Fu; Louis Feng; Zhongyi Lin; Pavani Panakanti; Shengbao Zheng; Srinivas Sridharan 002; Christina Delimitrou (ISCA, 2023)

Mystique: Accurate and Scalable Production AI Benchmarks Generation. - Mingyu Liang; Wenyin Fu; Louis Feng; Zhongyi Lin; Pavani Panakanti; Srinivas Sridharan; Christina Delimitrou (CoRR, 2023)

Performance Modeling and Optimization for Machine Learning Workloads - Zhongyi Lin (2023)

Towards Universal Performance Modeling for Machine Learning Training on Multi-GPU Platforms. - Zhongyi Lin; Ning Sun; Pallab Bhattacharya; Xizhou Feng; Louis Feng; John D. Owens (IEEE Trans. Parallel Distributed Syst., 2025)