Holoscan Debian/apt Installation

Holoscan Debian/​apt Installation

Purpose

Install the Holoscan SDK C++ runtime + headers on Ubuntu using NVIDIA's apt repo, selecting the right holoscan-cuda-* package for the host's CUDA driver and verifying with the bundled C++ examples.

Prerequisites

• Ubuntu x86_64 (22.04 / 24.04) or ARM64 (Jetson / IGX) with an NVIDIA GPU and working driver (nvidia-smi).
• sudo and network access to developer.download.nvidia.com and docs.nvidia.com.
• cuda-keyring package (Step 2 installs it if missing).

Limitations

• No Python bindings from apt — pair with /​holoscan-install-wheel if the user needs Python.
• Ubuntu-only. Other distros must use the container or wheel install.
• Package variant must match the host CUDA driver (holoscan-cuda-12 vs holoscan-cuda-13); wrong variant → "CUDA driver version is insufficient".

Step 0: Consult the Official Install Instructions

Fetch the Debian/​apt section of https://docs.nvidia.com/holoscan/sdk-user-guide/sdk_installation.html before installing. Extract:

• Exact package names (holoscan-cuda-12, holoscan-cuda-13, holoscan)
• Supported Ubuntu versions
• The cuda-keyring URL for the right distro

If the doc disagrees with anything below, the doc wins.

Determine OS version and CUDA variant if not already known — run in parallel:

lsb_release -a 2>/​dev/​null || cat /​etc/​os-release
nvidia-smi 2>&1 | head -5

CUDA variant rule — pick the apt package:

Step 1: Prerequisites Check

dpkg -l | grep cuda-keyring
dpkg -l | grep -E "holoscan-cuda-(12|13)|^ii  holoscan "
apt-cache show holoscan-cuda-13 holoscan-cuda-12 2>/​dev/​null | grep -E "^(Package|Version)"

Decision rules based on what Step 1 found:

• Skip the keyring step if cuda-keyring is already installed.
• Skip apt-get update if the repo is already configured and the package is visible in apt-cache show.
• Skip Step 2 entirely and proceed directly to Step 3 if the correct package variant is already installed (e.g. holoscan-cuda-12 when targeting cu12).

Step 2: Install

Skip this step if the package is already installed (detected in Step 1) or if user is on IGX platform.

# If cuda-keyring missing (adjust ubuntu2204/​ubuntu2404 as needed) and not on IGX platform:
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb && sudo apt-get update

sudo apt-get install -y holoscan-cuda-12   # or holoscan-cuda-13

Step 3: Verify

Set the env once for the rest of this step, then run the three C++ checks:

HS=/​opt/​nvidia/​holoscan
export LD_LIBRARY_PATH=$HS/​lib
export HOLOSCAN_INPUT_PATH=$HS/​data
ulimit -s 32768

ls $HS/​examples/​{hello_world,tensor_interop,video_replayer}/

# hello_world — expected: "Hello World!"
$HS/​examples/​hello_world/​cpp/​hello_world

# tensor_interop — expected: tensors doubling each pass, "Graph execution finished."
# If "CUDA driver version is insufficient": swap package variant:
#   sudo apt-get remove -y holoscan-cuda-13 && sudo apt-get install -y holoscan-cuda-12
$HS/​examples/​tensor_interop/​cpp/​tensor_interop

# video_replayer (10 frames, headless) — expected: Vulkan selects NVIDIA GPU, "Graph execution finished."
# Always run headless: works with or without a display, avoids GUI failure modes over SSH.
ls $HS/​data/​racerx 2>/​dev/​null || sudo $HS/​examples/​download_example_data
python3 -c "
c=open('$HS/​examples/​video_replayer/​cpp/​video_replayer.yaml').read()
c=c.replace('count: 0','count: 10').replace('repeat: true','repeat: false').replace('realtime: true','realtime: false')
c=c.replace('  width: 854','  headless: true\n  width: 854')
open('/​tmp/​vr.yaml','w').write(c)"
$HS/​examples/​video_replayer/​cpp/​video_replayer --config /​tmp/​vr.yaml

Step 4: Give the User the Reusable Env Snippet

Once verified, share this snippet with user and suggest adding it to their shell startup file (e.g., ~/​.bashrc) if they want it to persist across sessions:

export LD_LIBRARY_PATH=/​opt/​nvidia/​holoscan/​lib:${LD_LIBRARY_PATH}
export HOLOSCAN_INPUT_PATH=/​opt/​nvidia/​holoscan/​data
ulimit -s 32768

Then offer next steps:

• Add Python support: /​holoscan-install-wheel
• Explore examples: ls /​opt/​nvidia/​holoscan/​examples/
• Walk through a specific example: /​explain-example
• Start building a custom Holoscan application

Troubleshooting

• python3 -c "import holoscan" fails after apt install. Expected — the Debian package has been C++ only since v3.0.0. Run /​holoscan-install-wheel to add Python bindings.
• "CUDA driver version is insufficient" when running an example. Wrong package variant. Re-check nvidia-smi CUDA Version and swap variants: sudo apt-get remove -y holoscan-cuda-13 && sudo apt-get install -y holoscan-cuda-12 (or vice versa).
• E: Unable to locate package holoscan-cuda-12. cuda-keyring not installed or repo not yet pulled. Run the keyring + apt-get update block in Step 2 (adjust ubuntu2204/ubuntu2404 to match the host).
• Segmentation fault when launching an example. ulimit -s 32768 not set in the current shell. Prepend it to the command (Step 3 pattern).
• error while loading shared libraries: libholoscan_core.so. LD_LIBRARY_PATH is unset. Use the env snippet from Step 4 — export LD_LIBRARY_PATH=/​opt/​nvidia/​holoscan/​lib.
• video_replayer can't find data. Set HOLOSCAN_INPUT_PATH=/​opt/​nvidia/​holoscan/​data, or run sudo /​opt/​nvidia/​holoscan/​examples/​download_example_data to fetch the racerx dataset.