Holoscan Install Conda

Install Holoscan SDK v4.3+ via Conda in a CUDA 13 environment. Use for Conda installs; redirect CUDA 12 hosts to container/wheel.

Published by @NVIDIA·0 agent reads / 30d·0 saves·

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.

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