most citedAsteroid: Resource-Efficient Hybrid Pipeline Parallelism for Collaborative DNN Training on Heterogeneous Edge Devices

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cs.DC2024★ 1 cited

Asteroid: Resource-Efficient Hybrid Pipeline Parallelism for Collaborative DNN Training on Heterogeneous Edge Devices

Shengyuan Ye, Liekang Zeng, Xiaowen Chu +2

On-device Deep Neural Network (DNN) training has been recognized as crucial for privacy-preserving machine learning at the edge. However, the intensive training workload and limite…

cs.DC2024

Resource-Efficient Personal Large Language Models Fine-Tuning with Collaborative Edge Computing

Shengyuan Ye, Bei Ouyang, Tianyi Qian +6

Large language models (LLMs) have unlocked a plethora of powerful applications at the network edge, such as intelligent personal assistants. Data privacy and security concerns have…