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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
Search: #interpreter
@djangoproject · Post #156 · 09/06/2016, 01:43 AM
https://wiki.python.org/moin/GlobalInterpreterLock In #CPython, the #global#interpreter lock, or #GIL, is a mutex that prevents multiple native #threads from executing Python bytecodes at once. This lock is necessary mainly because CPython's memory management is not thread-safe. (However, since the GIL exists, other features have grown to depend on the guarantees that it enforces.)
@djangoproject · Post #159 · 09/12/2016, 05:37 PM
https://docs.python.org/3/library/atexit.html The #atexit module defines #functions to #register and #unregister cleanup functions. Functions thus registered are automatically executed upon normal interpreter termination. atexit runs these functions in the reverse order in which they were registered; if you register A, B, and C, at #interpreter#termination time they will be run in the order C, B, A.