204 citations · 388 across the 43 of their papers we have counts for
7 papers · 1 filter
Breaking the Memory Wall for Heterogeneous Federated Learning via Model Splitting
Chunlin Tian, Li Li, Kahou Tam +2
Federated Learning (FL) enables multiple devices to collaboratively train a shared model while preserving data privacy. Ever-increasing model complexity coupled with limited memory…
Heterogeneity-Aware Memory Efficient Federated Learning via Progressive Layer Freezing
Wu Yebo, Li Li, Tian Chunlin +4
In this paper, we propose SmartFreeze, a framework that effectively reduces the memory footprint by conducting the training in a progressive manner. Instead of updating the full mo…
Bridging Memory Gaps: Scaling Federated Learning for Heterogeneous Clients
Yebo Wu, Jingguang Li, Chunlin Tian +3
Federated Learning (FL) enables multiple clients to collaboratively train a shared model while preserving data privacy. However, the high memory demand during model training severe…
Breaking the Memory Wall for Heterogeneous Federated Learning via Progressive Training
Yebo Wu, Li Li, Chengzhong Xu
This paper presents ProFL, a new framework that effectively addresses the memory constraints in FL. Rather than updating the full model during local training, ProFL partitions the…
ChainsFormer: A Chain Latency-aware Resource Provisioning Approach for Microservices Cluster
Chenghao Song, Minxian Xu, Kejiang Ye +4
The trend towards transitioning from monolithic applications to microservices has been widely embraced in modern distributed systems and applications. This shift has resulted in th…
Practice of Alibaba Cloud on Elastic Resource Provisioning for Large-scale Microservices Cluster
Minxian Xu, Lei Yang, Yang Wang +6
Cloud-native architecture is becoming increasingly crucial for today's cloud computing environments due to the need for speed and flexibility in developing applications. It utilize…
An Optimal Fully Distributed Algorithm to Minimize the Resource Consumption of Cloud Applications
Nikos Tziritas, Samee Ullah Khan, Cheng-Zhong Xu +1
According to the pay-per-use model adopted in clouds, the more the resources consumed by an application running in a cloud computing environment, the greater the amount of money th…