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Source channel @githubtrending · Post #14985 · Jul 22

#c_lang#cuda#cuda_driver_api#cuda_kernels#cuda_opengl You can use the CUDA Samples from NVIDIA to learn and test CUDA Toolkit 12.9 features by downloading them from GitHub or as a ZIP file. These samples show how to use CUDA for GPU programming, including utilities, concepts, libraries, and performance optimization. You build them with CMake on Linux, Windows, or Tegra devices, and can run tests automatically with a provided Python script. This helps you understand CUDA programming, debug GPU code, and optimize your applications for better performance on NVIDIA GPUs. It’s a practical way to develop and improve GPU-accelerated software efficiently. https://github.com/NVIDIA/cuda-samples

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@libreware · Post #1056 · 03/16/2022, 10:06 PM

https://wikiless.org A free open source alternative Wikipedia front-end focused on privacy The source is available at Codeberg https://codeberg.org/orenom/wikiless All requests go through Wikiless, your browser never talks to Wikipedia No JavaScript or ads Self-hostable #wikipedia#wikiless