CV-CUDA Release v0.13.0

[milesp-nvidia]

v0.13.0 Beta

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

Full Changelog: v0.12.0-beta...v0.13.0-beta

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 ManyLinux 2014 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.

Compatibility and Known Limitations

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.

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This discussion was created from the release CV-CUDA Release v0.13.0.