Merge pull request #70 from AI-Hypercomputer/bvandermoon-recipes

Use public GCP documentation to create v6e clusters

Author: bvandermoon

training/trillium/XPK_README.md

@@ -33,89 +33,8 @@ steps, you must use the same one to run the steps in the [MAXTEXT_README](MAXTEX
 as well as your relevant tpu-recipe workloads.
 
 ## GKE Cluster Creation 
-1. Specify your TPU GKE cluster configs.
-```shell
-export CLUSTER_NAME=v6e-demo #<your_cluster_name>
-export NETWORK_NAME=${CLUSTER_NAME}-only-mtu9k
-export NETWORK_FW_NAME=${NETWORK_NAME}-only-fw
-export CLUSTER_ARGUMENTS="--network=${NETWORK_NAME} --subnetwork=${NETWORK_NAME}"
-export TPU_TYPE=v6e-256 #<your TPU Type>
-export NUM_SLICES=1 #<number of TPU node-pools you want to create>
-export ZONE=<compute_zone>
-export REGION=<compute_region>
-```
-
-2. Create the network and firewall for this cluster if it doesn’t exist yet.
-```shell
-NETWORK_NAME_1=${CLUSTER_NAME}-mtu9k-1-${ZONE}
-NETWORK_FW_NAME_1=${NETWORK_NAME_1}-fw-1-${ZONE}
-
-# Use a custom network for better performance as well as avoid the default network to be overloaded.
-gcloud compute networks create ${NETWORK_NAME_1} --mtu=8896 --project=${PROJECT} --subnet-mode=auto --bgp-routing-mode=regional
-gcloud compute firewall-rules create ${NETWORK_FW_NAME_1} --network ${NETWORK_NAME_1} --allow tcp,icmp,udp --project=${PROJECT}
-
-# Secondary subnet for multinic experience. Need custom ip routing to be different from first network’s subnet.
-export NETWORK_NAME_2=${CLUSTER_NAME}-privatenetwork-2-${ZONE}
-export SUBNET_NAME_2=${CLUSTER_NAME}-privatesubnet-2-${ZONE}
-export FIREWALL_RULE_NAME=${CLUSTER_NAME}-privatefirewall-2-${ZONE}
-export ROUTER_NAME=${CLUSTER_NAME}-network-2-${ZONE}
-export NAT_CONFIG=${CLUSTER_NAME}-natconfig-2-${ZONE}
-
-gcloud compute networks create "${NETWORK_NAME_2}" --mtu=8896 --bgp-routing-mode=regional --subnet-mode=custom --project=$PROJECT
-gcloud compute networks subnets create "${SUBNET_NAME_2}" --network="${NETWORK_NAME_2}" --range=10.10.0.0/18 --region="${REGION}" --project=$PROJECT
-gcloud compute firewall-rules create "${FIREWALL_RULE_NAME}" --network "${NETWORK_NAME_2}" --allow tcp,icmp,udp --project="${PROJECT}"
-gcloud compute routers create "${ROUTER_NAME}" \
-  --project="${PROJECT}" \
-  --network="${NETWORK_NAME_2}" \
-  --region="${REGION}"
-gcloud compute routers nats create "${NAT_CONFIG}" \
-  --router="${ROUTER_NAME}" \
-  --region="${REGION}" \
-  --auto-allocate-nat-external-ips \
-  --nat-all-subnet-ip-ranges \
-  --project="${PROJECT}" \
-  --enable-logging
-```
-
-3. Create GKE cluster with TPU node-pools
-```shell
-export CLUSTER_ARGUMENTS="--enable-dataplane-v2 --enable-ip-alias --enable-multi-networking --network=${NETWORK_NAME_1} --subnetwork=${NETWORK_NAME_1}"
-
-export NODE_POOL_ARGUMENTS="--additional-node-network network=${NETWORK_NAME_2},subnetwork=${SUBNET_NAME_2}"
-
-python3 xpk.py cluster create --cluster $CLUSTER_NAME --cluster-cpu-machine-type=n1-standard-8 --num-slices=$NUM_SLICES --tpu-type=$TPU_TYPE --zone=$ZONE  --project=$PROJECT --on-demand --custom-cluster-arguments="${CLUSTER_ARGUMENTS}" --custom-nodepool-arguments="${NODE_POOL_ARGUMENTS}" --create-vertex-tensorboard
-```
-
-  * Noted: TPU has `reserved`, `on-demand`, `spot` quota. This example used the `on-demand` quota. If you have the reserved or spot quota, please refer to this [link](https://github.com/google/xpk?tab=readme-ov-file#cluster-create).
-  * If you want to check what quota you have, please refer to this [link](https://cloud.google.com/kubernetes-engine/docs/how-to/tpus#ensure-quota).
-  * You should be able to see your GKE cluster similar to this once it is created successfully:![image](https://github.com/user-attachments/assets/60743411-5ee5-4391-bb0e-7ffba4d91c1d)
-
-4. Performance Daemonset 
-```shell
-kubectl apply -f https://raw.githubusercontent.com/GoogleCloudPlatform/ai-on-gke/9ff340f07f70be0130454f9e7238551587242b75/scripts/network-setup/v6e-network-optimization.yaml
-```
-
-5. Test your GKE cluster to make sure it is usable
-```shell
-python3 xpk.py workload create \
---cluster ${CLUSTER_NAME} \
---workload hello-world-test \
---tpu-type=${TPU_TYPE} \
---num-slices=${NUM_SLICES} \
---command "echo Hello World"
-```
-* You should be able to to see results like this: ![image](https://github.com/user-attachments/assets/c33010a6-e109-411e-8fb5-afb4edb3fa72)
-
-6. You can also check your workload status with the following command:
-```shell
-python3 xpk.py workload list --cluster ${CLUSTER_NAME}
-```
-7. For more information about XPK, please refer to this [link](https://github.com/google/xpk).
-
-## GKE Cluster Deletion
-You can use the following command to delete GKE cluster:
-```shell
-export CLUSTER_NAME=v6e-demo #<your_cluster_name>
+Trillium GKE clusters can be [created](https://cloud.google.com/tpu/docs/v6e-intro#create_an_xpk_cluster_with_multi-nic_support) and 
+[deleted](https://cloud.google.com/tpu/docs/v6e-intro#delete_xpk_cluster) by following the public GCP documentation.
 
-python3 xpk.py cluster delete --cluster $CLUSTER_NAME
-```
+> Note: in order to run the training and microbenchmarks tpu-recipes, you should not need to run sections outside of 
+`Create an XPK cluster with multi-NIC support` when creating your cluster. You can skip the following sections like `Framework setup`.