1

Communication-Efficient Model Parallelism for Distributed In-situ Transformer Inference
Transformer models have shown significant success in a wide range of tasks. Meanwhile, massive resources required by its inference …
Yuanxin Wei, Shengyuan Ye, Jiazhi Jiang, Xu Chen, Dan Huang, Jiangsu Du, Yutong Lu
Nov 12, 2023
Paper
Communication-Efficient Model Parallelism for Distributed In-situ Transformer Inference
Transformer models have shown significant success in a wide range of tasks. Meanwhile, massive resources required by its inference …
Yuanxin Wei, Shengyuan Ye, Jiazhi Jiang, Xu Chen, Dan Huang, Jiangsu Du, Yutong Lu
Cite Paper
Communication-Efficient Model Parallelism for Distributed In-situ Transformer Inference
Eco-FL: Adaptive Federated Learning with Efficient Edge Collaborative Pipeline Training
Federated Learning (FL) has been a promising paradigm in distributed machine learning that enables in-situ model training and global …
Shengyuan Ye, Liekang Zeng, Qiong Wu, Ke Luo, Qingze Fang, Xu Chen
Jun 18, 2022
Paper Code Slides Videos
Eco-FL: Adaptive Federated Learning with Efficient Edge Collaborative Pipeline Training
Federated Learning (FL) has been a promising paradigm in distributed machine learning that enables in-situ model training and global …
Shengyuan Ye, Liekang Zeng, Qiong Wu, Ke Luo, Qingze Fang, Xu Chen
Cite Paper Code Slides Videos
Eco-FL: Adaptive Federated Learning with Efficient Edge Collaborative Pipeline Training