v0.14.0 Beta

CV-CUDA v0.14.0 includes the following changes:

Full Changelog: https://github.com/CVCUDA/CV-CUDA/compare/v0.13.0-beta...v0.14.0-beta

New Features

• Added support for SBSA ARM/Grace cuda 12, including ManyLinux2014-compliant Python wheel generation
• We do not provide SBSA-compatible aarch64_cu11 packages yet, this will be addressed in an upcoming release
• aarch64_cu12 packages distributed on Github and Pypi are the SBSA-compatible ones. Jetson builds can be found in explicitly named "Jetson" archives in Github release assets.
• Added support for compiling NVCV on QNX
• Added support for VYUY and YUV8p formats in NVCV
• Improved test coverage for NVCV and operators
• Minor corrections to documentation

Bug Fixes

• Made Python cache thread-local to avoid race conditions and potential crashes in Python gilless multithreaded setups

Compatibility and Known Limitations

• Starting with v0.14, aarch64_cu12 packages (deb, tar.xz or wheels) distributed on Github (release "assets") and Pypi are the SBSA-compatible ones. Jetson builds (deb, tar.xz, whl) can be found in explicitly named "Jetson" archives in Github release assets.
• We do not provide SBSA-compatible aarch64_cu11 packages yet, this will be addressed in an upcoming release.

For the full list, see the main README on CV-CUDA GitHub.

License

CV-CUDA is licensed under the Apache 2.0 license.

Resources

1. CV-CUDA GitHub
2. CV-CUDA Increasing Throughput and Reducing Costs for AI-Based Computer Vision with CV-CUDA
3. NVIDIA Announces Microsoft, Tencent, Baidu Adopting CV-CUDA for Computer Vision AI
4. CV-CUDA helps Tencent Cloud audio and video PaaS platform achieve full-process GPU acceleration for video enhancement AI

Acknowledgements

CV-CUDA is developed jointly by NVIDIA and the ByteDance Machine Learning team.