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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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@emagzinewspars · Post #9561 · 11/17/2025, 03:17 AM

#The_Science🇺🇸📕[PDF]⬇️ 13 #November2025 #Weekly_Magazines For learning, for free(dom). @backupofmagazines This issue dives into breakthroughs reshaping biology and energy as researchers confront rising geopolitical limits. From #AI-driven epigenetics to #SyntheticBiology advances, the issue tracks how innovation pushes ahead despite tensions over China-US research ties. New micro-robots navigating the bloodstream and faster-charging batteries highlight a surge in #DeepTech momentum. Climate resilience, #PandemicPreparedness, and EU chemical reforms underscore global policy stakes. Studies on dog domestication, brown dwarfs, and marine recovery after extinction broaden the scientific lens. A reminder that #ScienceMatters even as politics shift—innovation continues to define our shared future. #TechNews#GlobalTrends#ResearchUpdates