Google Cloud Deployment
Requirements
The requirements for running Omniverse Isaac Sim on Google Cloud are:
A Google Cloud account with Compute Engine access that is able to create a Virtual Machine with GPU support.
A GCP virtual machine with the following recommended specifications:
GPU: nvidia-tesla-t4
Machine type: n1-standard-8 or better
Image: Ubuntu 22.04 LTS
GPU: nvidia-l4
Machine type: g2-standard-4 or better
Image: Ubuntu 22.04 LTS
Setup
To launch the GCP virtual machine, use the following steps:
Search for GPU Zones with the NVIDIA T4 ot L4 GPU model.
Create a Default VPC network.
Setup SSH connection to VM instances using a browser.
Follow the steps in Launch Cloud Shell to start Cloud Shell session on GCP.
Run the following command in the Cloud Shell session session to create a VM. Replace <project_name> and <instance_name>. The zone is set to us-central1-a, in this example, but can be replaced with the zones from step 1.
$ gcloud compute \ --project "<project_name>" \ instances create "<instance_name>" \ --zone "us-central1-a" \ --machine-type "n1-standard-8" \ --subnet "default" \ --metadata="install-nvidia-driver=True" \ --maintenance-policy "TERMINATE" \ --accelerator type=nvidia-tesla-t4,count=1 \ --image "ubuntu-2204-jammy-v20230919" \ --image-project "ubuntu-os-cloud" \ --boot-disk-size "100" \ --boot-disk-type "pd-ssd"
$ gcloud compute \ --project "<project_name>" \ instances create "<instance_name>" \ --zone "us-central1-a" \ --machine-type "g2-standard-4" \ --subnet "default" \ --metadata="install-nvidia-driver=True" \ --maintenance-policy "TERMINATE" \ --accelerator type=nvidia-l4,count=1 \ --image "ubuntu-2204-jammy-v20230919" \ --image-project "ubuntu-os-cloud" \ --boot-disk-size "100" \ --boot-disk-type "pd-ssd"
Follow the steps in Connect to Linux VMs using Google tools to connect to the VM.
Follow the steps in Install NVIDIA driver.
$ curl https://raw.githubusercontent.com/GoogleCloudPlatform/compute-gpu-installation/main/linux/install_gpu_driver.py --output install_gpu_driver.py $ sudo python3 install_gpu_driver.py
See Container Installation to install the Docker and NVIDIA Container Toolkit.
Proceed to Container Deployment.