Holoscan Install Conda

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".