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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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djangoproject

@djangoproject · Post #550 · 01/15/2018, 07:05 AM

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http://www.wikipython.com/other-concepts/anatomy-of-a-class/ It seems obvious, but note that you must define a class before you use it. When you create a #class, it establishes its own namespace and all its own local variables (except global definitions) exist only inside that #namespace. They do not interact with other variables of the same name outside it. This leads us to one very important “feature” of classes that you need to know. If you use the same word to designate some specific value both inside and outside the class blueprint, the instance value will take precedence when you try to use that value. #learn

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