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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 #15208 · 10/09/2025, 02:00 PM

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#go#archival#data_archiving#data_import#family_history#self_hosted#timeline Timelinize helps you organize your personal data from different sources like photos, messages, and social media into a single timeline on your computer. This keeps your data private and under your control, unlike cloud services. You can import data from many places, view it on a map, and see conversations across different platforms. It's like having a personal journal that you can add to and keep forever, without relying on companies to store it for you. This way, you can keep your memories safe and easily look back at them whenever you want. https://github.com/timelinize/timelinize

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