240 citations · 571 across the 28 of their papers we have counts for
5 papers · 1 filter
Venn: Resource Management for Collaborative Learning Jobs
Jiachen Liu, Fan Lai, Ding Ding +2
In recent years, collaborative learning (CL) has emerged as a promising approach for machine learning (ML) and data science across distributed edge devices. As the deployment of CL…
Oobleck: Resilient Distributed Training of Large Models Using Pipeline Templates
Insu Jang, Zhenning Yang, Zhen Zhang +2
Oobleck enables resilient distributed training of large DNN models with guaranteed fault tolerance. It takes a planning-execution co-design approach, where it first generates a set…
Memory Disaggregation: Advances and Open Challenges
Hasan Al Maruf, Mosharaf Chowdhury
Compute and memory are tightly coupled within each server in traditional datacenters. Large-scale datacenter operators have identified this coupling as a root cause behind fleet-wi…
Chasing Low-Carbon Electricity for Practical and Sustainable DNN Training
Zhenning Yang, Luoxi Meng, Jae-Won Chung +1
Deep learning has experienced significant growth in recent years, resulting in increased energy consumption and carbon emission from the use of GPUs for training deep neural networ…
FLINT: A Platform for Federated Learning Integration
Ewen Wang, Ajay Kannan, Yuefeng Liang +2
Cross-device federated learning (FL) has been well-studied from algorithmic, system scalability, and training speed perspectives. Nonetheless, moving from centralized training to c…