[Misc] Adding script to setup ray for multi-node vllm deployments

[Edwinhr716]

FIX #8302 (link existing issues this PR will resolve)

This script only starts the ray workers, and stalls until all ray workers have been started. It doesn't start up the vllm server itself. The expected command would be

/vllm-workspace/examples/online-serving/multi-node-serving.sh leader --ray_cluster_size=<number-of-nodes>; 
python3 -m vllm.entrypoints.openai.api_server --port 8080 --model meta-llama/Meta-Llama-3.1-405B-Instruct --tensor-parallel-size 8 --pipeline_parallel_size 2

Unlike run_cluster.sh this script doesn't launch docker, instead assumes that the image is already running, making it compatible with Kubernetes.

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[ahg-g]

This is not LWS specific, it is useful for any multi-node vllm deployment

[ahg-g]

suggest to name the file multi-node-serving.sh

[Edwinhr716]

Changed

[ahg-g]

Can you please show an example? I want to make sure we support setting any vllm backend flag

[Edwinhr716]

it would be very similar to how we currently do it in the LWS repo:

command:
- sh
- -c
- "/vllm-workspace/examples/online-serving/multi-node-serving.sh leader --ray_cluster_size=$(LWS_GROUP_SIZE); 
python3 -m vllm.entrypoints.openai.api_server --port 8080 --model meta-llama/Meta-Llama-3.1-405B-Instruct --tensor-parallel-size 8 --pipeline_parallel_size 2"

[ahg-g]

@robertgshaw2-redhat do you have a minute to look into this one? It will allow us to easily launch multi-node inference workloads, see examples at https://github.com/kubernetes-sigs/lws/tree/main/docs/examples/vllm

[ahg-g]

@robertgshaw2-redhat do you have a minute to look into this one? It will allow us to easily launch multi-node inference workloads, see examples at https://github.com/kubernetes-sigs/lws/tree/main/docs/examples/vllm

Right now we have to-rebuild the container to include this script, but it would be great to have it embedded in the main vllm container.

[robertgshaw2-redhat]

@ahg-g - I can approve but I don't really have the context to give a detailed review since this is outside my area of expertise. Can you let me know when its good to go from your POV?

Thanks!

[ahg-g]

It is good to go now,

@ahg-g - I can approve but I don't really have the context to give a detailed review since this is outside my area of expertise. Can you let me know when its good to go from your POV?

Thanks!

Thanks! it is good to go.
/lgtm

[ahg-g]

@robertgshaw2-redhat this one ready.