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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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@githubtrending · Post #14971 · 07/17/2025, 12:30 PM

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#ruby#api_documentation#app#devdocs#developer_tools#docs#documentation#documentation_tool#hacktoberfest#offline#pwa DevDocs is a free, fast, and easy-to-use web app that lets you quickly search and browse official API documentation for many programming languages and tools all in one place. It works offline, has a clean interface, supports keyboard shortcuts, dark mode, and mobile use. You can access over 100 documentations like HTML, CSS, JavaScript, and more without switching tabs or searching Google repeatedly. It saves time by providing instant search results and keeps everything organized, making coding and learning more efficient and enjoyable. You can use it online or run it locally with Docker for even faster access[1][2][3][5]. https://github.com/freeCodeCamp/devdocs

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