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USD Search API Quick setup

USD Search API Quick setup

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Description
Quick setup guide for USD Search API
Publisher
NVIDIA
Latest Version
1.1.0
Modified
March 7, 2025
Compressed Size
66.03 KB

Collection of helper scripts for USD Search API deployment

A collection of helper scripts that simplify the process of setting up USD Search API on a kubernetes cluster.

Packages and Access

Install the NGC CLI tool. Please refer to this guide for more details.

Generate your NGC helm and container registry API Key. See onboarding guide here. This step could be skipped if the API Key was generated before.

Fetch the latest resource from the NGC registry by using the Download button in the top right corner of the page and selecting the preferred download method. Below you can find a sample command that uses NGC CLI for downloading:

ngc registry resource download-version "nvidia/usdsearch/usdsearch_quick_setup:1.1.0"

Quick Setup Helper Scripts

Important: A fully functional Kubernetes environment with GPU operator, CSI & CNI providers is required. While the helper scripts can attempt to create a DEMO environment, we cannot guarantee the results.

USD Search API installer for AWS S3 buckets

The aws_s3.sh helper script simplifies deployment of USD Search API, when installing it for processing an AWS S3 bucket. In order to get started - simply run the script as follows:

bash ./aws_s3.sh

and follow the instructions to provide all the required information.

USD Search API installer for Omniverse Nucleus servers

The nucleus.sh helper script simplifies deployment of USD Search API, when installing it for processing an Omniverse Nucleus server. In order to get started - simply run the script as follows:

bash ./nucleus.sh

and follow the instructions to provide all the required information.

FAQ

NVIDIA GPU operator failing due to version mismatch

In case NVIDIA drivers have already been installed on the host machine it could happen that the version of nvidia container runtime installed by microk8s does not match the driver version. This could result in GPU-operator pods not starting up properly.

To overcome this issue, make sure that NVIDIA Container toolkit is installed and then install NVIDIA GPU operator as follows:

sudo microk8s disable nvidia
helm repo add nvidia https://helm.ngc.nvidia.com/nvidia
helm repo update
helm install --wait --create-namespace -n gpu-operator gpu-operator nvidia/gpu-operator -f ./gpu-operator/microk8s-config.yaml  --version v23.9.2