AWS Machine Learning Blog· Ashvin Nihalani·· 2026-09-26
Scaling MoE reinforcement learning on Amazon EKS with EFA and DeepEP with 40% more throughput
Scaling MoE reinforcement learning on Amazon EKS with EFA and DeepEP with 40% more throughput
AI summary
Learn how to scale Mixture-of-Experts (MoE) reinforcement learning on Amazon EKS using Elastic Fabric Adapter (EFA) and DeepEP. This post presents an architecture that combines Amazon EKS, EFA, and Amazon S3 and increased aggregate reinforcement learning rollout throughput by 40% for large-scale RLHF and GRPO training.
Selection record
Threshold 60Official, first-handFirst 31Second 34
Not admittedSum of both 65 < twice the threshold 120
- Source tier
- Official, first-hand; this tier's threshold is 60
- Pre-filter
- passed：MoE强化学习训练与DeepEP优化，实质AI技术
A model scores each item twice, independently, against one written standard, out of 100. An item is admitted only when the two scores add up to twice the threshold. The threshold is set per source tier.
Source: AWS Machine Learning Blog · aws.amazon.com