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Junjie Bai
Junjie Bai
Alibaba
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Year
Pytorch: An imperative style, high-performance deep learning library
A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
Advances in neural information processing systems 32, 2019
513782019
Onnx: Open neural network exchange
J Bai, F Lu, K Zhang
GitHub repository, 2017
4522017
PyTorch: An Imperative Style, High-Performance Deep Learning Library. arXiv e-prints: p
A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
arXiv preprint arXiv:1912.01703, 2019
1132019
PyTorch: an imperative style, high-performance deep learning library, December 2019
A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
URL http://arxiv. org/abs/1912.01703, 1912
411912
DISC: A dynamic shape compiler for machine learning workloads
K Zhu, WY Zhao, Z Zheng, TY Guo, PZ Zhao, JJ Bai, J Yang, XY Liu, ...
Proceedings of the 1st Workshop on Machine Learning and Systems, 89-95, 2021
302021
Distrifusion: Distributed parallel inference for high-resolution diffusion models
M Li, T Cai, J Cao, Q Zhang, H Cai, J Bai, Y Jia, K Li, S Han
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
282024
Parameter-efficient sparsity for large language models fine-tuning
Y Li, F Luo, C Tan, M Wang, S Huang, S Li, J Bai
arXiv preprint arXiv:2205.11005, 2022
232022
Bladedisc: Optimizing dynamic shape machine learning workloads via compiler approach
Z Zheng, Z Pan, D Wang, K Zhu, W Zhao, T Guo, X Qiu, M Sun, J Bai, ...
Proceedings of the ACM on Management of Data 1 (3), 1-29, 2023
112023
Recom: A compiler approach to accelerating recommendation model inference with massive embedding columns
Z Pan, Z Zheng, F Zhang, R Wu, H Liang, D Wang, X Qiu, J Bai, W Lin, ...
Proceedings of the 28th ACM International Conference on Architectural …, 2023
62023
MonoNN: Enabling a New Monolithic Optimization Space for Neural Network Inference Tasks on Modern GPU-Centric Architectures
D Zhuang, Z Zheng, H Xia, X Qiu, J Bai, W Lin
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Articles 1–10