v0.13.0-beta

Release Highlights

CV-CUDA v0.13.0 includes ManyLinux 2014 compliant wheels alongside the following changes:​

  • New Features:​

    • Added Python wheel generation compliant with ManyLinux 2014 and PyPI standards.

      • The multiple python version wheels are now unified into a single wheel file per CUDA version​.

      • Included scripts to build two ManyLinux 2014 Docker images (CUDA 11, CUDA 12) for build, and four Ubuntu images (20.04 and 22.04 x CUDA 11, CUDA 12) for testing.

      • Python wheels must be built within the ManyLinux 2014 docker images to guarantee ManyLinux2014 compliance.

  • Bug Fixes:​

    • Upgraded pybind11 to version 2.13.6 for improved compatibility and functionality.​

      • Resolved Python ABI compatibility issues present in previous versions by upgrading pybind11 reported in previous versions.​

Compatibility and Known Limitations

For the full list, see 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.