3 papers
cs.LG2025
EdgeMoE: Empowering Sparse Large Language Models on Mobile Devices
Rongjie Yi, Liwei Guo, Shiyun Wei +3
Large language models (LLMs) such as GPTs and Mixtral-8x7B have revolutionized machine intelligence due to their exceptional abilities in generic ML tasks. Transiting LLMs from dat…
cs.LG2024
FedMoE: Personalized Federated Learning via Heterogeneous Mixture of Experts
Hanzi Mei, Dongqi Cai, Ao Zhou +2
As Large Language Models (LLMs) push the boundaries of AI capabilities, their demand for data is growing. Much of this data is private and distributed across edge devices, making F…
cs.DC2024
More is Different: Prototyping and Analyzing a New Form of Edge Server with Massive Mobile SoCs
Li Zhang, Zhe Fu, Boqing Shi +7
Huge energy consumption poses a significant challenge for edge clouds. In response to this, we introduce a new type of edge server, namely SoC Cluster, that orchestrates multiple l…