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AWS details distributed PyTorch training with Ray Train DLCs and EFA on EKS

AWS published a guide on running distributed PyTorch training on Amazon EKS using Ray Train Deep Learning Containers and Elastic Fabric Adapter.

AWS details distributed PyTorch training with Ray Train DLCs and EFA on EKS — image from AWS
Image: AWS

Summary

AWS published a walkthrough on running distributed PyTorch training on Amazon EKS using Ray Train Deep Learning Containers and Elastic Fabric Adapter. The guide demonstrates fine-tuning Qwen2.5-1.5B with PyTorch FSDP across eight NVIDIA L4 GPUs on two g6.12xlarge instances without building custom container images.

What changed

  • AWS highlighted the Ray Train Deep Learning Container that packages PyTorch, CUDA, NCCL, and EFA libraries.
  • KubeRay manages Ray head and worker pods across Amazon EKS nodes using a single container image.
  • Training scripts scale dynamically by reading the cluster GPU count at runtime.

Availability

Available now

“The Ray Train Deep Learning Container (DLC) is that image, built by AWS.”

Founder takeaway

Developers running distributed PyTorch training on AWS can use prebuilt Ray Train Deep Learning Containers to avoid managing custom CUDA and EFA container stacks.

Source

AWSDistributed training with Ray Train DLCs and EFA on EKS | Amazon Web Services

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