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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 #9490 · 11/06/2025, 07:04 AM

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#Beijing_Review🇨🇳📕[PDF]⬇️ 6 #November2025 #Weekly_Magazines For learning, for free(dom). @backupofmagazines Beijing Review spotlights China’s #15thFiveYearPlan and its vision for a coordinated, green, and globally inclusive future. The issue unpacks Xi–Trump #Summit diplomacy in Busan, China’s push for #GenderEquality partnerships, and #RCEP as an engine for regional #Integration. Articles explore how strategic planning drives #Sustainability and global development under the banner of #Modernization. From energy transition to cyberspace security, the issue portrays a confident China charting a course for shared growth and stability. #China#GlobalGovernance#Sustainability#FiveYearPlan#RCEP#XiTrumpMeeting#ClimateAction#DigitalFuture#GenderEquality#AsiaPacific

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