2 papers
cs.DC2025
Resource Heterogeneity-Aware and Utilization-Enhanced Scheduling for Deep Learning Clusters
Abeda Sultana, Nabin Pakka, Fei Xu +3
Scheduling deep learning (DL) models to train on powerful clusters with accelerators like GPUs and TPUs, presently falls short, either lacking fine-grained heterogeneity awareness…
cs.DC2025
SEAFL: Enhancing Efficiency in Semi-Asynchronous Federated Learning through Adaptive Aggregation and Selective Training
Md Sirajul Islam, Sanjeev Panta, Fei Xu +3
Federated Learning (FL) is a promising distributed machine learning framework that allows collaborative learning of a global model across decentralized devices without uploading th…