The example assigns prefill to one node and decode to another, with both behind one OpenAI-compatible endpoint. The container bundles Ray Serve LLM, NVIDIA Inference Transfer Library, and Elastic Fabric Adapter. AWS says the setup can address models too large for one GPU, throughput needs beyond one replica, or workloads that benefit from separating inference phases. The article presents a configuration walkthrough and accompanying code repository; the supplied source does not establish a benchmark result or independent performance comparison.
Raw SignalOct 12, 20261 min read1 source
Run multi-node inference workloads using Ray LLM Deep Learning Containers
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AWS published a deployment guide for serving one large language model across two GPU nodes on Amazon EKS using its multi-node Ray LLM Deep Learning Containers.