holoscan-install-debian

Holoscan 5.x Debian Installation

Release and platform checks

This skill targets Holoscan SDK 5.x. Select the requested 5.x release before choosing artifacts. Read its release notes and the matching SDK installation guide. Select the 5.x documentation version; an unversioned page may describe 4.x. For an unreleased checkout, use its docs/sdk_installation.mdx and DEVELOP.md. Early Access binary commands describe planned artifacts, so confirm publication for the exact release before installing. If unavailable, explain that status and offer holoscan-install-source; keep the requested 5.x version.

The 5.0 artifact set targets CUDA 13 and dGPU systems on x86_64 or arm64. Native packages use Ubuntu 24.04; wheels use glibc 2.39 and regular CPython 3.12–3.14. Check the selected release for changes to that matrix. There is no CUDA 12 variant or separate Tegra/iGPU artifact in this set. A driver reporting CUDA 12 support needs a compatibility assessment or driver upgrade before a CUDA 13 installation; the nvidia-smi CUDA field is a driver capability, not the installed toolkit version. Never infer compatibility from that field alone.

Select packages and inspect availability

This path supplies C++ libraries, headers, CMake configuration, and C++ examples under /usr. Python bindings use holoscan-install-wheel separately. Support in the planned artifact set is Ubuntu 24.04 x86_64 and SBSA arm64; SBSA does not imply Tegra/iGPU support.

Goal	Package
Full SDK	holoscan
Core libraries only	holoscan-core
Optional modules	holoscan-vision, holoscan-visualization, holoscan-inference

Inspect /etc/os-release, uname -m, nvidia-smi, and existing packages. Use the release-specific network/local installer from Holoscan Downloads to configure the CUDA APT repository when needed. Choose ubuntu2404/x86_64 or ubuntu2404/sbsa as appropriate; use the published release-specific installer instructions and package names.

After repository setup is authorized, refresh metadata and inspect candidates:

sudo apt update
apt-cache policy holoscan holoscan-core holoscan-vision holoscan-visualization holoscan-inference
apt-cache madison holoscan holoscan-core

Choose the exact APT version corresponding to the requested 5.x release. A candidate from 4.x is not an available 5.x package. Keep every optional module on the same Core release. Preview dependency changes before installing:

# APT_VERSION is the exact available 5.x Debian version, including its revision.
apt-get --simulate install "holoscan=${APT_VERSION}"

For Core-only, substitute holoscan-core. Add selected optional module packages with their matching versions. Review the simulated transaction for removals or an existing 4.x installation before applying it. If simulation fails or proposes changes outside the requested scope, stop and report the failing command/output or conflicting changes. Resolve the conflict or obtain authorization for the expanded scope before installing. An existing 4.x installation alone does not block an upgrade the user requested.

After the simulated transaction is acceptable, install the selected package set:

sudo apt install "holoscan=${APT_VERSION}"

Verify C++ support

dpkg-query -W 'holoscan*'
dpkg -L holoscan-core-cuda-13

The unsuffixed component packages select CUDA 13 native packages, such as holoscan-core-cuda-13; inspect their installed versions and file lists. Use the package file list to locate the installed hello_world/cpp/hello_world and hello_core/cpp/hello_core executables under the system library hierarchy. Run them and expect Hello Holoscan! and holoscan core sample complete. Use the installed hello_world source and its CMakeLists.txt for a small consumer build in a user-writable build directory; verify find_package(holoscan) and the holoscan::core target. Check that cmake --version reports 4.0 or newer first; Ubuntu 24.04's default CMake 3.28 cannot configure the consumer. Inspect package contents rather than exporting the old /opt/nvidia/holoscan/lib path. Record missing example packages as a verification gap.

Core declares CUDA development dependencies; Vision supplies its CV-CUDA runtime, and Inference recommends TensorRT 10 runtime libraries. Check the application's selected modules and dependencies before claiming full support. Report installed package versions, C++ checks, and any untested GPU/module paths. If Python import is requested, explain the C++/Python package split and use the wheel workflow with the same SDK release.