stornic56/openvino-runtime-simple-installer
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update openvino + neo + igc

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- Real update capability (derived INSTALL_DIR, replace policy, stable symlink)
- Mesa >= 25.2 transition fix on Debian 13 (mesa-va-drivers/vdpau)
- Robustness: SIGPIPE fixes, dead repair code, EOF stdin, unbound vars,
  trap cleanup (modules + --install), strict booleans, set -euo pipefail in deps/
- Ubuntu 22.04 doc alignment
- Validated end-to-end on Debian 13 + Arc B580 (clinfo 26.31, vainfo iHD OK)"
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stornic56
2026-09-17 15:52:45 -05:00
committed by GitHub
parent 3b0c2051f1
commit ae66af419f
7 changed files with 282 additions and 258 deletions
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README.md
+25 -16
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@@ -4,10 +4,11 @@ This project repository provides a comprehensive automated installation and conf
## Supported Operating Systems
* Debian 13
* Ubuntu 24.04
* Ubuntu 26.04
* Fedora 43
* Debian 13
* Ubuntu 22.04
* Ubuntu 24.04
* Ubuntu 26.04
* Fedora 43
---
@@ -16,7 +17,9 @@ This project repository provides a comprehensive automated installation and conf
The installer scripts are designed to be executed as a root user (`sudo`). Ensure all necessary system dependencies (such as `git`, `wget`, and the respective package managers like `dpkg`/`dnf`) exist before execution.
### Setup & Clone Repository
First, clone the repository from GitHub:
```bash
# 1. Clone the installer repository
git clone https://github.com/stornic56/openvino-runtime-simple-installer
@@ -27,7 +30,9 @@ chmod +x main.sh
```
### Execution
Execute the primary installation script using elevated privileges (root access is mandatory):
```bash
sudo ./main.sh
```
@@ -37,19 +42,21 @@ sudo ./main.sh
The execution of `main.sh` automatically handles OS detection and conditionally installs components based on hardware presence, ensuring a fully configured inference pipeline:
**Core Runtime & Libraries:**
* **OpenVINO Toolkit 2026.0:** The complete runtime package is downloaded from the official OpenVINO repository (`https://storage.openvinotoolkit.org/repositories/openvino/packages/2026.0/linux`) and installed under `/opt/intel/openvino_2026`. It is the same version used in llama.cpp in its builds.
* **System Dependencies:** Required libraries, including `cmake`, Python 3 (with version-specific dependencies like `libpython3.13` for Debian 13 or `libpython3.13` for Ubuntu 26.04), GCC compilers (`g++`), NumPy bindings, and standard development tools are installed via system package managers (`apt`/`dnf`).
* **OpenVINO Toolkit 2026.3.1:** The complete runtime package is downloaded from the official OpenVINO repository (`https://storage.openvinotoolkit.org/repositories/openvino/packages/2026.3.1/linux`) and installed under `/opt/intel/openvino_2026`. It is the same version used in llama.cpp in its builds.
* **System Dependencies:** Required libraries, including `cmake`, Python 3 (with version-specific dependencies like `libpython3.13` for Debian 13 or `libpython3.13` for Ubuntu 26.04), GCC compilers (`g++`), NumPy bindings, and standard development tools are installed via system package managers (`apt`/`dnf`).
**Hardware Acceleration & Drivers (NEO):**
* **Intel Compute Runtime NEO:** If an Intel GPU is detected, the respective module script installs critical proprietary drivers:
* `intel-igc-core`: Graphics Compiler core components.
* `intel-igc-opencl`: OpenCL interface libraries for graphics compilation.
* `intel-ocloc`/`libze-intel-gpu1`: Compute Runtime interfaces and GPU acceleration layers (OpenCL/oneAPI).
* **Multimedia Support:** Installation of `mesa-va-drivers`, `vainfo`, and related packages to ensure Video Acceleration API support, crucial for media inference tasks.
* **Intel Compute Runtime NEO (26.31.39395.13):** If an Intel GPU is detected, the respective module script installs critical proprietary drivers:
* `intel-igc-core` (2.40.13): Graphics Compiler core components.
* `intel-igc-opencl` (2.40.13): OpenCL interface libraries for graphics compilation.
* `intel-ocloc`/`libze-intel-gpu1`: Compute Runtime interfaces and GPU acceleration layers (OpenCL/oneAPI).
* **Multimedia Support:** Installation of `mesa-va-drivers`, `vainfo`, and related packages to ensure Video Acceleration API support, crucial for media inference tasks.
**Environment Configuration:**
* User permissions are configured by adding the executing user (`$SUDO_USER`) to the system groups `render` and `video` to allow proper GPU access post-installation.
* User permissions are configured by adding the executing user (`$SUDO_USER`) to the system groups `render` and `video` to allow proper GPU access post-installation.
## After Installation
@@ -66,8 +73,10 @@ clinfo | grep -i "device name"
4. Check video acceleration
vainfo
```
## Note:
## Note
Users should reference the following official projects:
- Llamacpp: [Official Repository Link](https://github.com/ggml-org/llama.cpp) and [OpenvinoBackend](https://github.com/ggml-org/llama.cpp/blob/master/docs/backend/OPENVINO.md)
- OpenVino Toolkit: [Docs](https://docs.openvino.ai/2026/get-started/install-openvino/install-openvino-archive-linux.html) and [github](https://github.com/openvinotoolkit/openvino)
- Intel NEO Drivers: [Intel Compute Runtime](https://github.com/intel/compute-runtime)
* Llamacpp: [Official Repository Link](https://github.com/ggml-org/llama.cpp) and [OpenvinoBackend](https://github.com/ggml-org/llama.cpp/blob/master/docs/backend/OPENVINO.md)
* OpenVino Toolkit: [Docs](https://docs.openvino.ai/2026/get-started/install-openvino/install-openvino-archive-linux.html) and [github](https://github.com/openvinotoolkit/openvino)
* Intel NEO Drivers: [Intel Compute Runtime](https://github.com/intel/compute-runtime)