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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 #15247 · 10/25/2025, 12:30 PM

#cmake#audio#ios#linux#macos#plugins#sdk#vst3#win32 VST 3 is an improved version of the VST audio plug-in interface. It offers several benefits, including better performance by only processing audio when needed, dynamic input/output configurations, and precise automation. Users can also enjoy a more organized interface and support for advanced audio features like 3D sound. These improvements make it easier for developers to create plugins and for users to work with them in digital audio workstations (DAWs), enhancing overall audio production efficiency. https://github.com/steinbergmedia/vst3sdk