4 papers
Weaver: A System for AI-RAN Compute Sharing with Foundation Model Training
Leyang Xue, Tianxin Wang, Xin Zhe Khooi +6
The emergence of AI-RAN infrastructure, which equips cell sites with GPU-accelerated hardware, creates an opportunity to colocate non-RAN workloads with primary RAN processing. We…
TUBO: A Tailored ML Framework for Reliable Network Traffic Forecasting
Zhihang Yuan, Leyang Xue, Waleed Ahsan +1
Traffic forecasting based network operation optimization and management offers enormous promise but also presents significant challenges from traffic forecasting perspective. While…
On Harnessing Idle Compute at the Edge for Foundation Model Training
Leyang Xue, Meghana Madhyastha, Myungjin Lee +3
The foundation-model ecosystem remains highly centralized because training requires immense compute resources and is therefore largely limited to large cloud operators. Edge-assist…
Towards Decentralized and Sustainable Foundation Model Training with the Edge
Leyang Xue, Meghana Madhyastha, Randal Burns +2
Foundation models are at the forefront of AI research, appealing for their ability to learn from vast datasets and cater to diverse tasks. Yet, their significant computational dema…