Zhongyi Lin

According to our database, Zhongyi Lin authored at least 10 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

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

CoRR, 2024

2023

Performance Modeling and Optimization for Machine Learning Workloads

Zhongyi Lin

PhD thesis, 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

Mystique: Enabling Accurate and Scalable Generation of Production AI Benchmarks.

Mingyu Liang, Wenyin Fu, Louis Feng, Zhongyi Lin, Pavani Panakanti, Shengbao Zheng, Srinivas Sridharan, Christina Delimitrou

Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023

2022

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

Proceedings of the 29th IEEE International Conference on High Performance Computing, 2022

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

Towards Flexible and Compiler-Friendly Layer Fusion for CNNs on Multicore CPUs.

Zhongyi Lin, Evangelos Georganas, John D. Owens

Proceedings of the Euro-Par 2021: Parallel Processing, 2021

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

Accelerating DNN Inference with GraphBLAS and the GPU.

Xiaoyun Wang, Zhongyi Lin, Carl Yang, John D. Owens

Proceedings of the 2019 IEEE High Performance Extreme Computing Conference, 2019

2018

Benchmarking Deep Learning Frameworks with FPGA-suitable Models on a Traffic Sign Dataset.

Zhongyi Lin, Jeffrey M. Ota, John D. Owens, Pinar Muyan-Özçelik

Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018