As a key 5G enabler, edge computing locates resources near users to enable low-latency services, and microservices architecture (MSA) decomposes monolithic services into microservices, easing deployment and scaling of mission-critical applications with high reliability requirements. Existing studies on microservice bac...
Yue Zeng, Jun-Long Zhou, Lin-Hui Wang et al.· IEEE transactions on compute...· 0 citations
Chameleon is a synchronous and adaptive bidirectional pipeline framework that achieves high throughput in dynamic and heterogeneous edge systems, and incorporates a hardware-aware throughput model to capture pipeline stage performance on heterogeneous devices.
Tao Liu, Xiang-Peng Hou, Li-Ying Li et al.· Proceedings of the Internati...· 0 citations
The shift of deep learning (DL) from the cloud to the edge introduces a critical systems challenge: enabling efficient and stable distributed training under dynamic and heterogeneous conditions. Pipeline parallelism is crucial for training throughput, but existing frameworks, designed for cloud servers, incur high over...
Tao Liu, Xiang-Peng Hou, Li-Ying Li et al.· Proceedings of the Internati...· 0 citations
FeDiSyn is proposed, a unified framework that holistically considers the interplay between pre-training and FedFT to minimize the overall LVM training time and introduces a scaling law for FedFT pre-training to determine the optimal number of synthetic images, balancing pre-training benefit against generation/pre-train...
Qianpiao Ma, Xiaozhu Song, Junlong Zhou et al.· 0 citations
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