.. # SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. .. _v0.16.0-beta: 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, :doc:`samples <../samples>` and :doc:`framework interoperability <../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.