Scaling MoE reinforcement learning on Amazon EKS with EFA and DeepEP boosts throughput by 40%
Scaling MoE reinforcement learning on Amazon EKS with EFA and DeepEP with 40% more throughput
What happened
AWS presents an architecture for scaling MoE reinforcement-learning training on Amazon EKS with EFA and DeepEP, improving throughput by 40%. It addresses resource contention between rollout generation and policy training in large-scale RL workloads such as RLHF and GRPO, high-throughput communication across hundreds of accelerators, and the cross-node all-to-all overhead introduced by Expert Parallelism.
Open sourceDeployment engineeringData and trainingTutorials#Tutorials and practice#Deployment and engineering#Data and training#Open-source ecosystem
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