v0.16.0-beta

Release Highlights

CV-CUDA v0.16.0 includes the following changes:​

• New Features and Enhancements:​

  • Added support for Python 3.14​, CUDA 13, GCC-12 to GCC-14 and Blackwell GPU architecture, including Jetson Thor

  • Improved documentation, samples and framework interoperability examples

  • Added new multi-architecture (x86_64, aarch64) Docker images for building (ManyLinux-based) and developing CV-CUDA (Ubuntu-based)

  • Improved Python wheels generation and packaging​

• Bug Fixes:

  • Fixed Coverity security findings​

• Deprecated Features:

  • Dropped official support for CUDA 11

  • Dropped official support for CUDA Compute Capability SM7 (Volta architecture)

  • Dropped official support for Ubuntu 20.04

  • Dropped official support for Python 3.8

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. Optimizing Microsoft Bing Visual Search with NVIDIA Accelerated Libraries

3. Accelerating AI Pipelines: Boosting Visual Search Efficiency

4. Optimize Short-Form Video Processing Toward the Speed of Light

5. CV-CUDA Increasing Throughput and Reducing Costs for AI-Based Computer Vision with CV-CUDA

6. NVIDIA Announces Microsoft, Tencent, Baidu Adopting CV-CUDA for Computer Vision AI

7. CV-CUDA helps Tencent Cloud audio and video PaaS platform achieve full-process GPU acceleration for video enhancement AI

Acknowledgements

CV-CUDA originated as a collaborative effort between NVIDIA and the ByteDance Machine Learning team.