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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 #1185 · 09/26/2023, 11:04 PM
Meshenger is a P2P Android phone app that started out as a demo for community mesh networks. Meshenger started out as an idea to promote off the grid mesh networks and has now reached its initial goal. In this talk I will talk about the idea behind it, the story how it came to be and of course how it works. https://media.ccc.de/v/camp2023-57107-meshenger #P2P#Meshenger#Mesh#MeshNetwork#ChaosComputerClubBerlin #CCCde