Prerequisites#

This section covers the prerequisites for deploying and using the Warehouse Blueprint.

Hardware Requirements#

The Warehouse Blueprint has been validated and tested on the following NVIDIA GPUs:

  • NVIDIA RTX PRO 6000 Blackwell

  • NVIDIA H100 (NVL, SXM HBM3)

  • NVIDIA RTX A6000 ADA

  • NVIDIA RTX A6000

  • NVIDIA L40S

  • NVIDIA L4

  • NVIDIA IGX-THOR

  • NVIDIA DGX-SPARK

Software Requirements#

The following software must be installed on your system:

  • OS:

    • x86 hosts: Ubuntu 24.04

    • DGX-SPARK: DGX OS 7.4.0

    • IGX-THOR: Jetson Linux BSP (Rel 38.5)

  • NVIDIA Driver:

    • 580.105.08 (x86 hosts with Ubuntu 24.04)

    • 580.95.05 (DGX-SPARK)

    • 580.00 (IGX-THOR)

  • NVIDIA Fabric Manager: 580.105.08 (for H100 SXM HBM3 to run local LLM) - See Installation Guide

  • NVIDIA Container Toolkit: 1.17.8+

  • Docker: 27.2.0+

  • Docker Compose: v2.29.0+

  • NGC CLI: 4.10.0+

Note

For detailed installation instructions for the software requirements listed above, see the Appendix:

Runtime Environment Settings#

Linux Kernel Settings#

# Ensure the sysctl.d directory exists
sudo mkdir -p /etc/sysctl.d

# Write VSS kernel settings to 99-vss.conf (persistent across reboots)
sudo bash -c "printf '%s\n' \
  'net.ipv6.conf.all.disable_ipv6 = 1' \
  'net.ipv6.conf.default.disable_ipv6 = 1' \
  'net.ipv6.conf.lo.disable_ipv6 = 1' \
  'net.core.rmem_max = 5242880' \
  'net.core.wmem_max = 5242880' \
  'net.ipv4.tcp_rmem = 4096 87380 16777216' \
  'net.ipv4.tcp_wmem = 4096 65536 16777216' \
  > /etc/sysctl.d/99-vss.conf"

# Reload sysctl to apply the new settings
sudo sysctl --system

Cache cleaner (only on DGX-SPARK, IGX-THOR)#

Run the cache cleaner script for DGX SPARK and Jetson Thor.

Create the cache cleaner script at /usr/local/bin/sys-cache-cleaner.sh:

sudo tee /usr/local/bin/sys-cache-cleaner.sh << 'EOF'
#!/bin/bash
# Exit immediately if any command fails
set -e

# Disable hugepages
echo "disable vm/nr_hugepage"
echo 0 | tee /proc/sys/vm/nr_hugepages

# Notify that the cache cleaner is running
echo "Starting cache cleaner - Running"
echo "Press Ctrl + C to stop"
# Repeatedly sync and drop caches every 3 seconds
while true; do
     sync && echo 3 | tee /proc/sys/vm/drop_caches > /dev/null
     sleep 3
done
EOF

sudo chmod +x /usr/local/bin/sys-cache-cleaner.sh

Running in the background#

sudo -b /usr/local/bin/sys-cache-cleaner.sh

Note

The above runs the cache cleaner in the current session only; it does not persist across reboots. To have the cache cleaner run across reboots, create a systemd service instead.

VIC clocks (IGX-THOR only)#

For IGX Thor, VIC clocks need to be boosted for best performance and latency. Run the following before deployment:

sudo nvpmodel -m 0
sudo jetson_clocks
sudo su
# Run the following in the root shell (after sudo su):
echo performance > /sys/class/devfreq/8188050000.vic/governor

Minimum System Requirements#

The following requirements ensure reliable performance for real-time video analytics workloads, including GPU-accelerated inference, video decoding, and data streaming. These specifications support processing multiple camera streams simultaneously while maintaining low latency for analytics and alerting.

  • 18 core CPU (x86 systems)

  • 128 GB RAM

  • 1 TB SSD

  • 1 × 1 Gbps network interface

NGC API Key Access#

To deploy the Warehouse Blueprint, you need an NGC API key with access to the required resources.

Create an NVIDIA NGC Account#

  1. Go to https://ngc.nvidia.com

  2. Click Sign up if you don’t have an account, or Sign in if you do

  3. Complete the registration process with your email address

Generate an API Key#

  1. Once logged in, click on your username in the top right corner

  2. Select Setup from the dropdown menu

  3. Navigate to API Keys under the Keys/Secrets section

  4. Click Generate API Key

  5. Click Generate Personal Key (available at both the top-center and top-right of the page)

  6. Provide a descriptive name for your API key (e.g., “Warehouse Blueprint Development”)

  7. Select NGC Catalog for Key Permissions

  8. Click Generate Personal Key

  9. Copy the generated API key immediately - you won’t be able to see it again

  10. Store it securely in a password manager or encrypted file

Note

Keep your NGC API key secure and never commit it to version control systems.

Verify Your NGC Access#

To verify your NGC key has the correct permissions:

# Set your NGC API key
export NGC_CLI_API_KEY='your_ngc_api_key'

# Test access to the required resources
ngc registry resource list "nvidia/vss-warehouse/*"
ngc registry resource list "nvidia/vss-core/*"

# Test access to the required images
ngc registry image list "nvidia/vss-core/*"

If you encounter permission errors, contact NVIDIA support for assistance.

Google Maps API Key#

The Video-Analytics-UI map view functionality requires a Google Maps API key.

You can obtain a Google Maps API key by following the create API key instructions.

Note

For production deployments, ensure you configure appropriate API key restrictions and usage limits.

Prerequisite Software Installation Guide#

Install NVIDIA Driver#

NVIDIA Driver version 580.105.08 is required.

You can download the driver directly from: https://www.nvidia.com/en-us/drivers/details/257738/

For detailed installation instructions, refer to the official NVIDIA Driver Installation Guide: https://docs.nvidia.com/datacenter/tesla/driver-installation-guide/index.html

You can also browse drivers for your specific GPU and platform from the NVIDIA Driver Downloads page: https://www.nvidia.com/Download/index.aspx

Note

After installation, verify the driver is correctly installed by running nvidia-smi to confirm the driver version and GPU detection.

Note

NVIDIA Fabric Manager Requirement

NVIDIA Fabric Manager is required on systems with multiple GPUs that are connected using NVLink or NVSwitch technology. This typically applies to:

  • Multi-GPU systems with NVLink bridges (e.g., DGX systems, HGX platforms)

  • Systems with NVSwitch fabric interconnects

  • Hosts running NVIDIA H100, A100, V100, or other datacenter GPUs with NVLink

Fabric Manager is not required for:

  • Single GPU systems

  • Multi-GPU systems without NVLink/NVSwitch (PCIe-only configurations)

For installation instructions, refer to the official NVIDIA Fabric Manager documentation:

Verify Fabric Manager status after installation:

sudo systemctl status nvidia-fabricmanager

Install Docker#

Docker version 27.2.0+ is recommended. Follow the guide here for installing Docker: https://docs.docker.com/engine/install/ubuntu/

Run docker without sudo#

After installation, complete the Linux post-installation steps so that Docker can run without sudo. See Linux post-installation steps for Docker Engine.

Configure Docker#

After installing Docker, you must configure it to use the cgroupfs cgroup driver.

Edit the Docker daemon configuration file:

Add or verify the following entry in /etc/docker/daemon.json:

"exec-opts": ["native.cgroupdriver=cgroupfs"]

This configuration must be included within the JSON object. For example:

{
    "exec-opts": ["native.cgroupdriver=cgroupfs"]
}

If your /etc/docker/daemon.json already contains other settings, ensure this entry is added to the existing configuration.

Apply the configuration:

After editing the daemon configuration, restart Docker to apply the changes:

sudo systemctl daemon-reload
sudo systemctl restart docker

Note

Restarting Docker will temporarily stop all running containers. Plan accordingly if you have containers running.

Install Docker Compose#

Docker Compose v2.29.0 or later is required. Docker Compose v2 is typically installed as a plugin with modern Docker installations.

Verify if Docker Compose is already installed:

docker compose version

If not installed, install Docker Compose plugin:

sudo apt update
sudo apt install docker-compose-plugin

Verify installation:

docker compose version

Note

Docker Compose v2 uses the command docker compose (without hyphen) instead of the older docker-compose command.

Install NVIDIA Container Toolkit#

The NVIDIA Container Toolkit is required to run the NVIDIA containers. Follow the guide here for installing the NVIDIA Container Toolkit: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html

Install NGC CLI#

NGC CLI version 4.10.0 or later is required to download blueprints and authenticate with NGC resources.

Download and install NGC CLI:

For ARM64 Linux:

curl -sLo "/tmp/ngccli.zip" https://api.ngc.nvidia.com/v2/resources/nvidia/ngc-apps/ngc_cli/versions/4.10.0/files/ngccli_arm64.zip

For AMD64 Linux:

curl -sLo "/tmp/ngccli.zip" https://api.ngc.nvidia.com/v2/resources/nvidia/ngc-apps/ngc_cli/versions/4.10.0/files/ngccli_linux.zip

After downloading, install NGC CLI:

sudo mkdir -p /usr/local/bin
sudo unzip -qo /tmp/ngccli.zip -d /usr/local/lib
sudo chmod +x /usr/local/lib/ngc-cli/ngc
sudo ln -sfn /usr/local/lib/ngc-cli/ngc /usr/local/bin/ngc

Verify installation:

ngc --version

Configure NGC CLI with your API key:

ngc config set

When prompted, enter your NGC API key. For information on obtaining an NGC API key, see the NGC API Key Access section.

Note

For the latest version of NGC CLI, visit the NGC CLI downloads page: https://ngc.nvidia.com/setup/installers/cli

Setup DGX-SPARK#

For setup instructions, see the DGX Spark User Guide.

Setup installs DGX OS (including the NVIDIA driver), Docker with NVIDIA Container Toolkit integration, and NGC access.

Note

Setup IGX-THOR#

For IGX Thor, the IGX 2.0 GA ISO and Jetson BSP r38.5 are required. Set up Jetson BSP Rel 38.5 instructions are coming soon.

Steps: - Setup installs Jetson Linux BSP (including the NVIDIA driver). - Install JetPack after the BSP is in place (for CUDA and other components), as described in the user guide.

Note