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Holoscan Conda Installation

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Effortlessly install the Holoscan SDK in a Conda environment.

by nvidia2.8k stars on nvidia/skills
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Updated Aug 7, 2026
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What Holoscan Conda Installation does

The Holoscan Conda Installation skill provides a streamlined method for setting up the Holoscan SDK (version 4.3 or higher) within a Conda environment on Linux x86_64 systems equipped with an NVIDIA GPU and CUDA 13. This skill is essential for developers and data scientists who need to leverage the capabilities of the Holoscan SDK for high-performance applications in areas such as real-time data processing and AI-driven workloads. By using this skill, users can ensure that they are installing the correct packages and dependencies, reducing the likelihood of compatibility issues.

The installation process begins with checking prerequisites, including the presence of Conda and the correct CUDA driver. If Conda is not installed, the skill will automatically install Miniforge, which is preferred for managing Conda environments. Users are guided through creating a dedicated Conda environment and installing the necessary packages, including the Holoscan Python bindings, C++ development headers, and required RAPIDS libraries. This ensures that all components are correctly configured for optimal performance.

Additionally, the skill emphasizes the importance of consulting the official NVIDIA documentation to verify package names and installation instructions, as these can change between SDK releases. Users are also reminded to set appropriate system limits to prevent potential segmentation faults during runtime. The skill provides clear instructions for running tests to validate the installation, ensuring that users can quickly verify their setup and begin developing applications using the Holoscan SDK.

Overall, this skill is tailored for developers and data scientists who require a reliable installation method for the Holoscan SDK in their Conda environments, facilitating the development of advanced applications in high-performance computing environments.

When to use it

Use this skill when you need to install the Holoscan SDK in a Conda environment on a Linux x86_64 system with an NVIDIA GPU and CUDA 13.

When not to use it

This skill is not suitable for systems running CUDA 12 or for architectures other than Linux x86_64.

What you can build with it

Setting Up a New Development Environment

Quickly install the Holoscan SDK in a fresh Conda environment to start developing high-performance applications.

Transitioning to CUDA 13

Easily migrate your existing projects to use the latest Holoscan SDK with CUDA 13 support.

Verifying Installation for Testing

Run the provided tests to ensure that your Holoscan SDK installation is functioning correctly before starting development.

How to install Holoscan Conda Installation

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1. Install with the skills CLI

npx skills add nvidia/skills/holoscan-install-conda --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by nvidia

Holoscan Conda Installation

Purpose

Install the Holoscan SDK (Python runtime and/or C++ dev headers) into a Conda environment on Linux x86_64, using conda-forge + rapidsai with a correctly pinned CUDA metapackage.

Prerequisites

  • Linux x86_64 with an NVIDIA GPU and CUDA 13 driver (check nvidia-smi).
  • conda (Miniforge preferred). Step 1 installs it if missing.
  • Network access to conda-forge, rapidsai, and docs.nvidia.com.

Limitations

  • CUDA 13 only (since v4.3.0 — earlier releases were CUDA 12). If the user has a CUDA 12 driver, redirect to /holoscan-install-container or /holoscan-install-wheel instead.
  • Linux x86_64 only — no aarch64/iGPU support on conda-forge.
  • ulimit -s 32768 is recommended in every shell that runs Holoscan — without it, some apps may segfault.

Step 0: Consult the Official Install Instructions

Always fetch the current Conda section of https://docs.nvidia.com/holoscan/sdk-user-guide/sdk_installation.html before installing — package names, channel selection, and the runtime/dev split can change between releases. Specifically extract:

  • The exact runtime package name (e.g. holoscan for Python bindings).
  • The C++ dev package name and whether the user needs it. As of v4.1.0, libholoscan-dev is a separate package containing headers and CMake config — install it whenever the user wants to develop C++ apps. Without it, find_package(holoscan) fails and there are no headers to #include.
  • Supported Python versions for the current release (3.10–3.13 for v4.3).
  • The current cuda-version pin (v4.3 → 13).

rmm and ucxx are distributed via the rapidsai channel; holoscan, libholoscan, and libholoscan-dev come from conda-forge.

If the doc disagrees with anything below, the doc wins — update the install commands accordingly and tell the user.

Step 1: Prerequisites Check

conda --version 2>&1
nvidia-smi 2>&1 | head -5

If conda is not found, install Miniforge silently (preferred over Miniconda for conda-forge):

wget -q https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh -O /tmp/Miniforge3.sh
bash /tmp/Miniforge3.sh -b -p ~/miniforge3
source ~/miniforge3/etc/profile.d/conda.sh
conda --version

The -b flag installs non-interactively without modifying .bashrc. Users must source ~/miniforge3/etc/profile.d/conda.sh in each new shell (or add it to their shell RC file) to make conda available.

Step 2: Create Environment and Install

Package roles

  • libholoscan — C++ runtime symbols (libholoscan_core.so). Auto-pulled as a dependency.
  • holoscan — Python bindings.
  • libholoscan-dev — C++ headers, libholoscan_core.so symlink, and holoscan-config.cmake for find_package(holoscan).
  • rmm — RAPIDS Memory Manager (rapidsai channel). Undeclared runtime dep of holoscan; import holoscan fails without it.
  • ucxx — UCX Python bindings (rapidsai channel), needed for distributed/multi-process apps.
  • cuda-version=13 — pins the CUDA 13 metapackage so the solver picks compatible CUDA runtime libs.

Create the environment first:

source ~/miniforge3/etc/profile.d/conda.sh   # if conda not yet on PATH
conda create -n holoscan python=3.13 -y
conda activate holoscan

Then pick one of the variants below based on the user's goal.

Pick the packages for the user's goal — Python-only needs holoscan, C++ dev needs libholoscan-dev, both works for combined use:

conda install <packages> rmm ucxx cuda-version=13 -c rapidsai -c conda-forge -y

For C++ development, also install the toolchain:

conda install -c conda-forge cxx-compiler cmake ninja -y

Verify Python installs with python3 -c "import holoscan; print(holoscan.__version__)". Verify C++ dev installs with ls "$CONDA_PREFIX/include/holoscan".

Step 3: Run Python Tests

ulimit -s 32768 is recommended — without it, some Holoscan apps may segfault on startup.

video_replayer is a display app that loops forever by default. Always patch its YAML to stop after 10 frames (count: 10, repeat: false, realtime: false) and to run headless (headless: true) — headless works with or without a display attached and avoids GUI failure modes over SSH, so we don't branch on $DISPLAY.

Download scripts and YAML configs, patch the YAML, then run:

source ~/miniforge3/etc/profile.d/conda.sh
conda activate holoscan
ulimit -s 32768

SDK_VER=$(python3 -c "import holoscan; print(holoscan.__version__)")
BASE="https://raw.githubusercontent.com/nvidia-holoscan/holoscan-sdk/v${SDK_VER}/examples"

curl -fsSL "${BASE}/hello_world/python/hello_world.py"         -o /tmp/hs_hello_world.py
curl -fsSL "${BASE}/video_replayer/python/video_replayer.py"   -o /tmp/hs_video_replayer.py
curl -fsSL "${BASE}/video_replayer/python/video_replayer.yaml" -o /tmp/video_replayer.yaml

# Patch video_replayer.yaml — 10 frames, headless.
python3 -c "
c = open('/tmp/video_replayer.yaml').read()
c = c.replace('count: 0', 'count: 10')
c = c.replace('repeat: true', 'repeat: false')
c = c.replace('realtime: true', 'realtime: false')
c = c.replace('  width: 854', '  headless: true\n  width: 854')
open('/tmp/video_replayer.yaml', 'w').write(c)"

# hello_world — no display, no data needed; expected: "Hello World!"
python3 /tmp/hs_hello_world.py

# video_replayer — needs racerx data; expected: frames rendered, "Graph execution finished."
HOLOSCAN_INPUT_PATH=/path/to/holoscan/data python3 /tmp/hs_video_replayer.py

HOLOSCAN_INPUT_PATH must point to the directory containing a racerx/ subdirectory. If the user has the SDK source repo that is ~/repos/holoscan-sdk/data; otherwise download with the download_ngc_data script from the Debian or source install tree.

Step 4: Remind the User

They must do the following in each new shell session:

source ~/miniforge3/etc/profile.d/conda.sh   # if Miniforge was installed with -b
conda activate holoscan
ulimit -s 32768   # recommended — prevents segfaults in some apps

Consider adding these lines to ~/.bashrc or ~/.zshrc to avoid repeating them.

Then offer next steps:

  • Explore C++ and Python examples at https://github.com/nvidia-holoscan/holoscan-sdk/tree/v<VERSION>/examples
  • Walk through a specific example: /explain-example
  • Start building a custom Holoscan application

Troubleshooting

  • ImportError: librmm.so: cannot open shared object file. rmm was not installed. Re-run the Step 2 conda install line — rmm is an undeclared runtime dependency of holoscan.
  • Solver picks an older holoscan build than expected. Channel order may be wrong. Use -c rapidsai -c conda-forge (rapidsai first) — that's the order in the official install command, and under strict channel priority a conda-forge-first ordering can lock the solver to an older holoscan build.
  • Segmentation fault on app startup. Set ulimit -s 32768 in the current shell before running any Holoscan app. Not all apps trip this, but the larger stack avoids the failure mode.
  • find_package(holoscan) fails when building C++ apps. Install libholoscan-dev (headers + CMake config are in a separate package since v4.1.0).
  • conda: command not found in a new shell. Miniforge was installed with -b and did not patch .bashrc. Run source ~/miniforge3/etc/profile.d/conda.sh or add it to your shell RC file.

Frequently asked questions about Holoscan Conda Installation

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