performance improvements
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RTX 5090 CuPy Setup: Blackwell Architecture & CUDA 13.1
Read Full Article: RTX 5090 CuPy Setup: Blackwell Architecture & CUDA 13.1![[D] RTX 5090 / 50-series CuPy setup (Blackwell architecture, CUDA 13.1 required)](https://www.tweakedgeek.com/wp-content/uploads/2026/01/featured-article-9252-300x171.png)
Users experiencing issues with CuPy on RTX 5090, 5080, or 5070 GPUs should note that the new Blackwell architecture requires CUDA 13.1 for compatibility. Pre-built CuPy wheels do not support the compute capability of these GPUs, necessitating a build from source. After uninstalling existing CuPy versions, install the CUDA Toolkit 13.1 and then CuPy without binaries. For Windows users, ensure the correct path is added to the system PATH. Proper configuration can lead to significant performance improvements, such as a 21× speedup in physics simulations compared to CPU processing. This matters because it highlights the importance of proper software setup to fully utilize the capabilities of new hardware.
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OpenCV 4.13: Enhanced AVX-512 and CUDA 13 Support
Read Full Article: OpenCV 4.13: Enhanced AVX-512 and CUDA 13 Support
OpenCV 4.13 introduces enhanced support for AVX-512, a set of instructions that can significantly boost performance on compatible hardware, making it more efficient for tasks such as image processing. The update also includes support for CUDA 13, enabling better integration with NVIDIA's latest GPU technologies, which is crucial for accelerating computer vision applications. Additionally, the release brings a variety of other improvements and new features, including bug fixes and optimizations, to further enhance the library's capabilities. These advancements are important as they enable developers to leverage cutting-edge hardware and software optimizations for more efficient and powerful computer vision solutions.