1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.DC2026
FEPLB: Exploiting Copy Engines for Nearly Free MoE Load Balancing in Distributed Training
Shuyao Qi, Haoyuan Liu, Shizhen Zhao
Fine-grained, per-micro-batch load balancing is essential for efficient Mixture-of-Experts (MoE) training, yet every prior dynamic scheduling scheme pays for it with extra communic…
cs.DC2023★ 1 cited
Isolated Scheduling for Distributed Training Tasks in GPU Clusters
Xinchi Han, Weihao Jiang, Peirui Cao +5
Distributed machine learning (DML) technology makes it possible to train large neural networks in a reasonable amount of time. Meanwhile, as the computing power grows much faster t…