
Holoscan Conda Installation
OfficialFreeEffortlessly install the Holoscan SDK in a Conda environment.
Free · Opens the source repo
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
View source1. Install with the skills CLI
npx skills add nvidia/skills/holoscan-install-conda --agent claude-code2. 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 nvidiaHoloscan 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-containeror/holoscan-install-wheelinstead. - Linux x86_64 only — no aarch64/iGPU support on conda-forge.
ulimit -s 32768is 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.
holoscanfor Python bindings). - The C++ dev package name and whether the user needs it. As of v4.1.0,
libholoscan-devis 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-versionpin (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.sosymlink, andholoscan-config.cmakeforfind_package(holoscan).rmm— RAPIDS Memory Manager (rapidsai channel). Undeclared runtime dep ofholoscan;import holoscanfails 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.rmmwas not installed. Re-run the Step 2conda installline —rmmis an undeclared runtime dependency ofholoscan.- Solver picks an older
holoscanbuild 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 olderholoscanbuild. - Segmentation fault on app startup. Set
ulimit -s 32768in 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. Installlibholoscan-dev(headers + CMake config are in a separate package since v4.1.0).conda: command not foundin a new shell. Miniforge was installed with-band did not patch.bashrc. Runsource ~/miniforge3/etc/profile.d/conda.shor add it to your shell RC file.
Frequently asked questions about Holoscan Conda Installation
Similar skills
Spring Boot Testing
Master testing techniques for Spring Boot 4 applications.
GitHub Issues
Manage GitHub issues efficiently with MCP tools.
Geofeed Tuner
Optimize your IP geolocation feeds in CSV format.
Batch Files
Master Windows batch scripting for automation and task management.
Adobe Illustrator Scripting
Automate your Illustrator workflows with ExtendScript.
Plugin Structure
Create and organize Claude Code plugins effectively.
