Distributed training with Ray Train and EFA on EKS
In brief
- The Ray Train container provides a ready-to-use CUDA-through-EFA stack.
- Sample shows distributed fine-tuning of Qwen2.5-1.5B across 8 GPUs with PyTorch FSDP.
- Deployment on two g6.12xlarge EKS instances without image modification.
Amazon Web Services describes how to use the Ray Train container to fine-tune the Qwen2.5-1.5B model in distributed mode across eight GPUs with PyTorch FSDP. The sample relies on two EFA-enabled g6.12xlarge instances running on Amazon EKS, using the published Docker image without modification according to the announcement.
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