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holoscan-install-source

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Build the Holoscan SDK from source using its in-tree Docker-based build script, producing a local install tree for CMake-based applications.

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Updated time September 25, 2026

Holoscan SDK — Build from Source

Purpose

Build the Holoscan SDK from the nvidia-holoscan/holoscan-sdk source tree using its ./run script (which builds inside a Docker container), producing a local install tree consumable as a CMake dependency.

Prerequisites

  • Linux host with NVIDIA GPU + driver (nvidia-smi).
  • git, Docker with NVIDIA Container Toolkit (docker run --gpus all works), and docker-buildx-plugin.
  • ~20 GB free disk for the build container + build/install trees.
  • 10–30 min for a clean first build.

Limitations

  • Only recommended when published packages (Conda / container / apt / wheel) don't fit — debug symbols, custom CMake options, or unsupported configs.
  • Still requires Docker — the ./run script builds inside a container; this is not a true bare-metal build.
  • Cross-compiling to aarch64 needs qemu-user-static on the host.

Step 0: Consult the Official Install Instructions

Always fetch the "Build from Source" section of https://docs.nvidia.com/holoscan/sdk-user-guide/sdk_installation.html (and the linked GitHub README.md / DEVELOP.md for the chosen tag) before building. Extract: required ./run flags for the target architecture and CUDA major, supported branches/tags, any Dockerfile patches called out for the release, and the test names recommended for verification. If the doc disagrees with anything below, the doc wins.

Step 1: Prerequisites

Check that git and Docker (with GPU passthrough) are available:

git --version
docker --version
docker run --rm --gpus all ubuntu:22.04 nvidia-smi
  • If Docker is missing → help install from https://docs.docker.com/engine/install/
  • If GPU passthrough fails → install NVIDIA Container Toolkit:
    curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
    curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \
      | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \
      | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
    sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
    sudo nvidia-ctk runtime configure --runtime=docker && sudo systemctl restart docker
    
  • If Docker buildx is missing: sudo apt-get install docker-buildx-plugin

Step 2: Clone the Repository

Clone repo to ~/holoscan/holoscan-sdk if needed

mkdir -p ~/holoscan/
git clone https://github.com/nvidia-holoscan/holoscan-sdk.git
cd ~/holoscan/holoscan-sdk

To build a specific release tag (recommended for stability):

git tag | grep -E '^v[0-9]' | sort -V | tail -5   # list recent tags
git checkout v                             # e.g. v4.1.0

Step 3: Build

The ./run build script handles container creation, CMake configuration, compilation, and install in one step. Warn the user this takes 10–30 minutes on first run (downloads base image + compiles).

./run build

Common options:

Flag Purpose
--type debug Debug build (symbols, no optimization)
--type RelWithDebInfo Release + debug symbols
--arch aarch64 Cross-compile for ARM64 (needs sudo apt install qemu-user-static)
--gpu igpu iGPU build for Jetson/IGX
--dryrun Preview commands without executing

If CMake cache errors occur after changing options:

./run clear_cache && ./run build

Output lands in these folders, and can be retrieved with ./run get_build_dir and ./run get_install_dir

  • Build dir: build-cu-/
  • Install dir: install-cu-/.

Step 4: Run Tests

Run the following tests

  • EXAMPLE_CPP_HELLO_WORLD_TEST
  • EXAMPLE_PYTHON_HELLO_WORLD_TEST
  • EXAMPLE_CPP_TENSOR_INTEROP_TEST
  • EXAMPLE_PYTHON_TENSOR_INTEROP_TEST
  • EXAMPLE_CPP_VIDEO_REPLAYER_TEST
  • EXAMPLE_PYTHON_VIDEO_REPLAYER_TEST
./run test

To run all six required tests at once, use a single-quoted regex (the | must be quoted to prevent bash from treating it as a pipe):

./run test --options "-R 'EXAMPLE_CPP_HELLO_WORLD_TEST|EXAMPLE_PYTHON_HELLO_WORLD_TEST|EXAMPLE_CPP_TENSOR_INTEROP_TEST|EXAMPLE_PYTHON_TENSOR_INTEROP_TEST|EXAMPLE_CPP_VIDEO_REPLAYER_TEST|EXAMPLE_PYTHON_VIDEO_REPLAYER_TEST' --output-on-failure"

Run a specific test by name or regex:

./run test --name 
./run test --options "-R '' --output-on-failure"
./run test --verbose

Important: Always single-quote the regex string when it contains | — without quotes, bash interprets | as a pipe and the command fails with command not found.

Expected: all tests pass. Note any failures and report them to the user before continuing.

Step 5: Point Applications at the Install Tree

Once built, applications can use the install tree as a CMake dependency. Give the user this path:

/path/to/holoscan-sdk/install-cu-/

They can set Holoscan_ROOT or CMAKE_PREFIX_PATH to this directory when building their own applications.

Troubleshooting

Symptom Fix
bash: : command not found when running tests The regex contains | — wrap it in single quotes: --options "-R ''"
CMake cache errors after option change ./run clear_cache && ./run build
Docker buildx not found sudo apt-get install docker-buildx-plugin
GPU not visible inside build container Verify NVIDIA Container Toolkit and re-run sudo nvidia-ctk runtime configure --runtime=docker
Cross-compile fails (aarch64) Install qemu: sudo apt-get install qemu-user-static
View on GitHub
---
name: holoscan-install-source
description: Build the Holoscan SDK from source using its in-tree Docker-based build script, producing a local install tree for CMake-based applications.
license: Apache-2.0
---

# Holoscan SDK — Build from Source

## Purpose

Build the Holoscan SDK from the `nvidia-holoscan/holoscan-sdk` source tree using its `./run` script (which builds inside a Docker container), producing a local install tree consumable as a CMake dependency.

## Prerequisites

- Linux host with NVIDIA GPU + driver (`nvidia-smi`).
- `git`, Docker with NVIDIA Container Toolkit (`docker run --gpus all` works), and `docker-buildx-plugin`.
- ~20 GB free disk for the build container + build/install trees.
- 10–30 min for a clean first build.

## Limitations

- Only recommended when published packages (Conda / container / apt / wheel) don't fit — debug symbols, custom CMake options, or unsupported configs.
- Still requires Docker — the `./run` script builds inside a container; this is not a true bare-metal build.
- Cross-compiling to aarch64 needs `qemu-user-static` on the host.

## Step 0: Consult the Official Install Instructions

Always fetch the "Build from Source" section of `https://docs.nvidia.com/holoscan/sdk-user-guide/sdk_installation.html` (and the linked GitHub `README.md` / `DEVELOP.md` for the chosen tag) before building. Extract: required `./run` flags for the target architecture and CUDA major, supported branches/tags, any Dockerfile patches called out for the release, and the test names recommended for verification. If the doc disagrees with anything below, the doc wins.

## Step 1: Prerequisites

Check that git and Docker (with GPU passthrough) are available:

```bash
git --version
docker --version
docker run --rm --gpus all ubuntu:22.04 nvidia-smi
```

- If Docker is missing → help install from https://docs.docker.com/engine/install/
- If GPU passthrough fails → install NVIDIA Container Toolkit:
  ```bash
  curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
  curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \
    | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \
    | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
  sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
  sudo nvidia-ctk runtime configure --runtime=docker && sudo systemctl restart docker
  ```
- If Docker buildx is missing: `sudo apt-get install docker-buildx-plugin`

## Step 2: Clone the Repository

Clone repo to ~/holoscan/holoscan-sdk if needed

```bash
mkdir -p ~/holoscan/
git clone https://github.com/nvidia-holoscan/holoscan-sdk.git
cd ~/holoscan/holoscan-sdk
```

To build a specific release tag (recommended for stability):

```bash
git tag | grep -E '^v[0-9]' | sort -V | tail -5   # list recent tags
git checkout v<VERSION>                             # e.g. v4.1.0
```

## Step 3: Build

The `./run build` script handles container creation, CMake configuration, compilation, and install in one step. Warn the user this takes **10–30 minutes** on first run (downloads base image + compiles).

```bash
./run build
```

Common options:

| Flag | Purpose |
|------|---------|
| `--type debug` | Debug build (symbols, no optimization) |
| `--type RelWithDebInfo` | Release + debug symbols |
| `--arch aarch64` | Cross-compile for ARM64 (needs `sudo apt install qemu-user-static`) |
| `--gpu igpu` | iGPU build for Jetson/IGX |
| `--dryrun` | Preview commands without executing |

If CMake cache errors occur after changing options:

```bash
./run clear_cache && ./run build
```

Output lands in these folders, and can be retrieved with `./run get_build_dir` and `./run get_install_dir`
* Build dir: `build-cu<N>-<arch>/`
* Install dir: `install-cu<N>-<arch>/`.

## Step 4: Run Tests

Run the following tests
* EXAMPLE_CPP_HELLO_WORLD_TEST
* EXAMPLE_PYTHON_HELLO_WORLD_TEST
* EXAMPLE_CPP_TENSOR_INTEROP_TEST
* EXAMPLE_PYTHON_TENSOR_INTEROP_TEST
* EXAMPLE_CPP_VIDEO_REPLAYER_TEST
* EXAMPLE_PYTHON_VIDEO_REPLAYER_TEST

```bash
./run test
```

To run all six required tests at once, use a single-quoted regex (the `|` must be quoted to prevent bash from treating it as a pipe):

```bash
./run test --options "-R 'EXAMPLE_CPP_HELLO_WORLD_TEST|EXAMPLE_PYTHON_HELLO_WORLD_TEST|EXAMPLE_CPP_TENSOR_INTEROP_TEST|EXAMPLE_PYTHON_TENSOR_INTEROP_TEST|EXAMPLE_CPP_VIDEO_REPLAYER_TEST|EXAMPLE_PYTHON_VIDEO_REPLAYER_TEST' --output-on-failure"
```

Run a specific test by name or regex:

```bash
./run test --name <test_name>
./run test --options "-R '<regex>' --output-on-failure"
./run test --verbose
```

**Important:** Always single-quote the regex string when it contains `|` — without quotes, bash interprets `|` as a pipe and the command fails with `command not found`.

Expected: all tests pass. Note any failures and report them to the user before continuing.

## Step 5: Point Applications at the Install Tree

Once built, applications can use the install tree as a CMake dependency. Give the user this path:

```
/path/to/holoscan-sdk/install-cu<N>-<arch>/
```

They can set `Holoscan_ROOT` or `CMAKE_PREFIX_PATH` to this directory when building their own applications.

## Troubleshooting

| Symptom | Fix |
|---------|-----|
| `bash: <TEST_NAME>: command not found` when running tests | The regex contains `\|` — wrap it in single quotes: `--options "-R '<regex>'"` |
| CMake cache errors after option change | `./run clear_cache && ./run build` |
| Docker buildx not found | `sudo apt-get install docker-buildx-plugin` |
| GPU not visible inside build container | Verify NVIDIA Container Toolkit and re-run `sudo nvidia-ctk runtime configure --runtime=docker` |
| Cross-compile fails (aarch64) | Install qemu: `sudo apt-get install qemu-user-static` |

Install holoscan-install-source

Download and extract the skill files to your .claude/skills/ directory.

Download ZIP

Clone the repository and copy the skill files to your project.

git clone https://github.com/NVIDIA/skills/tree/main/skills/holoscan-install-source # Copy SKILL.md to your .claude/skills/ directory

Copy Copy
Quick Setup: Copy the skill folder to .claude/skills/ Claude will automatically detect and use the skill
Repository NVIDIA/skills

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