Prebuilt official ONNX Runtime GPU 1.26.0 libraries that re-enable CUDA acceleration for the current ONNX-backed DeepSNR PixInsight module on Linux — including Blackwell (RTX 50-series). No fork, no source build.
What's in the bundle
ort-gpu-1.26.0-linux-x86_64.tar.gz contains the three libraries StarNet's Linux package omits, extracted unmodified from the official onnxruntime-gpu 1.26.0 PyPI wheel:
libonnxruntime.so.1.26.0libonnxruntime_providers_shared.solibonnxruntime_providers_cuda.so
plus ONNX Runtime's LICENSE and a PROVENANCE.txt recording the source wheel's sha256 so anyone can reproduce and diff it.
Do you need to download this?
Most people don't — install-deepsnr-gpu.sh fetches the same libraries from PyPI for you (integrity-checked, no pip required). This bundle is for systems without python3, or anyone who prefers grabbing a checked artifact from here.
Verified
- glibc symbol floor ≤ 2.28 → x86_64 Debian 10+ (incl. 13 "trixie"), Ubuntu 20.04+, RHEL/AlmaLinux/Rocky 8+, Fedora, Arch, openSUSE.
- Loads on Debian 13 and AlmaLinux 8 containers; CPU inference of the DeepSNR model verified inside Debian 13.
- GPU end-to-end confirmed in PixInsight on an RTX 5080 / Fedora 44 (~136× per tile vs CPU).
Requirements / scope
NVIDIA GPU + driver, CUDA 12.x runtime, cuDNN 9 for CUDA 12. Without them DeepSNR still runs on CPU — the module announces the fallback itself in the process console. NVIDIA only: AMD is blocked at the vendor level, since the signed DeepSNR module registers ONNX Runtime's CUDA execution provider specifically.
Other PixInsight AI tools?
RC Astro's NoiseXTerminator / StarXTerminator / BlurXTerminator use TensorFlow today, not ONNX — so these libraries don't accelerate them yet. The developer has confirmed a move to ONNX+CUDA on Linux in a future version, at which point the same drop-in will cover them too. For GPU acceleration of the TensorFlow-based RC Astro tools right now, see the companion project: pixinsight-blackwell-tensorflow.
Verify the download:
sha256sum -c ort-gpu-1.26.0-linux-x86_64.tar.gz.sha256
See the README for full install steps.