Scaling MoE reinforcement learning on Amazon EKS with EFA and DeepEP with 40% more throughput

Amazon Web Services · 2 weeks ago · 42

Amazon EKS, EFA, and DeepEP were used to scale post-training MoE reinforcement learning workloads by orchestrating rollout generation and tightly coupled policy training across heterogeneous nodes. DeepEP v2 native EFA support delivered 40% more throughput by replacing standard all-to-all expert-parallel communication with dispatch and combine kernels over libfabric and EFA. This shifts the bottleneck from expert-parallel inter-node communication to a more balanced end-to-end pipeline, improving rollout generation capacity and keeping training workers from idling.