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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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@googlefactss · Post #40365 · 12/19/2025, 09:21 PM

When the chat reaches 4,000 members or the channel 90,000, 10 group members will be allowed to create a post each, about a sfw topic of their own chosing. You must give @googlefactss permission to use your post and add it to the channel, with or without your username. More details will come after we hit these numbers. Invite friends, family, and coworkers to join. Do not spam/send links without permission of the place you send them in!! Our group links are: Main channel https://t.me/googlefactss Group: https://t.me/googlefactssgroup @googlefactss📢👥 #Community#Permission#Posts#Growth#KeepTrackOfThisPost