From 1ddb879e0eb37607f3f9cfea29e2de5484bd490e Mon Sep 17 00:00:00 2001 From: Junjie Tang Date: Mon, 23 Sep 2024 12:33:41 +0200 Subject: [PATCH] remove the old readme and add a blog later --- manifests/fine-tuning-6B/README.md | 90 ------------------ .../fine-tuning-6B/docs/ray-dashboard.png | Bin 199471 -> 0 bytes .../docs/ray-on-eks-architecture.jpg | Bin 597890 -> 0 bytes 3 files changed, 90 deletions(-) delete mode 100644 manifests/fine-tuning-6B/README.md delete mode 100644 manifests/fine-tuning-6B/docs/ray-dashboard.png delete mode 100644 manifests/fine-tuning-6B/docs/ray-on-eks-architecture.jpg diff --git a/manifests/fine-tuning-6B/README.md b/manifests/fine-tuning-6B/README.md deleted file mode 100644 index d4292997..00000000 --- a/manifests/fine-tuning-6B/README.md +++ /dev/null @@ -1,90 +0,0 @@ -# How to fine tune a 6B LLM on Ray on Amazon Elastic Kubernetes Service - -## Description - -The manifest `manifests/fine-tuning-6B/deployment.yaml` deploys Ray on Amazon EKS. - -It provisions an [Amazon EKS](https://docs.aws.amazon.com/eks/latest/userguide/what-is-eks.html) cluster with 2 node groups: -Core (CPU) and Workload (GPU) and deploys [KubeRay](https://github.com/ray-project/kuberay) Ray Operator, and a Ray Cluster -with autoscaling and mounted high-performance [Amazon FSx for Lustre](https://docs.aws.amazon.com/fsx/latest/LustreGuide/what-is.html) -file system. Additionally, a custom Ray container image is supported. - -### Architecture - -![Ray on Amazon EKS Architecture](docs/ray-on-eks-architecture.jpg "Ray on Amazon EKS Architecture") - -### Modules Inventory - -- [Ray Operator Module](modules/eks/ray-operator/README.md) -- [Ray Cluster Module](modules/eks/ray-cluster/README.md) -- [Ray Image Module](modules/eks/ray-image/README.md) -- [EKS Module](https://github.com/awslabs/idf-modules/tree/main/modules/compute/eks) -- [FSx for Lustre Module](https://github.com/awslabs/idf-modules/tree/main/modules/storage/fsx-lustre) -- [FSx for Lustre on EKS Integration Module](https://github.com/awslabs/idf-modules/tree/main/modules/integration/fsx-lustre-on-eks) -- [Networking Module](https://github.com/awslabs/idf-modules/tree/main/modules/network/basic-cdk) -- [ECR Module](https://github.com/awslabs/idf-modules/tree/main/modules/storage/ecr) -- [Buckets Module](https://github.com/awslabs/idf-modules/tree/main/modules/storage/buckets) - -## Deployment - -For deployment instructions, please refer to [DEPLOYMENT.MD](https://github.com/awslabs/aiops-modules/blob/main/DEPLOYMENT.md). - -## User Guide - -### Submitting Jobs - -After deploying the manifest, follow the steps below to submit a job to the cluster. - -1. Connect to EKS cluster -``` -aws eks update-kubeconfig --region us-east-1 --name eks-cluster-xxx -``` - -2. Check that Ray cluster and operator pods are running: - -``` -kubectl get pods --all-namespaces - -NAMESPACE NAME READY STATUS RESTARTS AGE -... -ray kuberay-operator-... 1/1 Running 0 11m -ray ray-cluster-kuberay-head-... 1/1 Running 0 11m -ray ray-cluster-kuberay-worker-workergroup-... 1/1 Running 0 11m -ray ray-cluster-kuberay-worker-workergroup-... 1/1 Running 0 11m -``` - -3. Check Ray service is running: - -``` -kubectl get services -n ray - -NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE -kuberay-head-svc ClusterIP ... 10001/TCP,8265/TCP,8080/TCP,6379/TCP,8000/TCP 64s -kuberay-operator ClusterIP ... 8080/TCP 6m3s -``` - -4. Get Ray service endpoint: - -``` -kubectl get endpoints -n ray - -NAME ENDPOINTS AGE -kuberay-head-svc ...:8080,...:10001,...:8000 + 2 more... 98s -kuberay-operator ...:8080 6m37s -``` - -5. Set up port forwarding: - -``` -kubectl port-forward -n ray --address 0.0.0.0 service/kuberay-head-svc 8265:8265 -``` - -6. Submit the job: - -``` -ray job submit --address http://localhost:8265 --working-dir="." -- python scripts/training-6B.py -``` - -9. 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