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ORCIDZhongyi Lin
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2020 – today
- 2024
[i3]Zhongyi Lin, Ning Sun, Pallab Bhattacharya, Xizhou Feng, Louis Feng, John D. Owens:
Towards Universal Performance Modeling for Machine Learning Training on Multi-GPU Platforms. CoRR abs/2404.12674 (2024)- 2023
- [b1]Zhongyi Lin:
Performance Modeling and Optimization for Machine Learning Workloads. University of California, Davis, USA, 2023 - [c6]Mingyu Liang
, Wenyin Fu, Louis Feng, Zhongyi Lin, Pavani Panakanti, Shengbao Zheng, Srinivas Sridharan, Christina Delimitrou:
Mystique: Enabling Accurate and Scalable Generation of Production AI Benchmarks. ISCA 2023: 37:1-37:13 - [i2]Mingyu Liang, Wenyin Fu, Louis Feng, Zhongyi Lin, Pavani Panakanti, Srinivas Sridharan, Christina Delimitrou:
Mystique: Accurate and Scalable Production AI Benchmarks Generation. CoRR abs/2301.04122 (2023) - 2022
- [c5]Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens:
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs. HIPC 2022: 48-58 - [c4]Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens:
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs. ISPASS 2022: 227-229 - [i1]Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens:
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs. CoRR abs/2201.07821 (2022) - 2021
- [j2]Zhongyi Lin, Yang Cao, Huasheng Liu, Jin Li, Shuzhi Zhao:
Research on Optimization of Urban Public Transport Network Based on Complex Network Theory. Symmetry 13(12): 2436 (2021) - [c3]Zhongyi Lin, Evangelos Georganas, John D. Owens:
Towards Flexible and Compiler-Friendly Layer Fusion for CNNs on Multicore CPUs. Euro-Par 2021: 232-248
2010 – 2019
- 2019
- [j1]Zhongyi Lin, Matthew Yih, Jeffrey M. Ota, John D. Owens, Pinar Muyan-Özçelik:
Benchmarking Deep Learning Frameworks and Investigating FPGA Deployment for Traffic Sign Classification and Detection. IEEE Trans. Intell. Veh. 4(3): 385-395 (2019) - [c2]Xiaoyun Wang, Zhongyi Lin, Carl Yang, John D. Owens:
Accelerating DNN Inference with GraphBLAS and the GPU. HPEC 2019: 1-6 - 2018
- [c1]Zhongyi Lin, Jeffrey M. Ota, John D. Owens, Pinar Muyan-Özçelik:
Benchmarking Deep Learning Frameworks with FPGA-suitable Models on a Traffic Sign Dataset. Intelligent Vehicles Symposium 2018: 1197-1203
Coauthor Index
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