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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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@dooooshno · Post #921 · 03/28/2024, 02:15 PM
Пришло время! Я работаю саунд продюссером, SFX, игры, реклама и участие в создании архитектуры проекта #musicproduction#sounddesign#composer#soundegineer И конечно свожу треки, очень красиво и главное бережно к артисту и его душевной организации) Если вам или кому-то из ваших друзей/знакомых нужен такой специалист – Смело пишите , отправляйте ему это сообщение 💼Портфолио: http://leonovaportfolio.tilda.ws/page44575443.html
@djangoproject · Post #535 · 12/28/2017, 10:12 AM
https://docs.pipenv.org/ #Pipenv — the officially recommended #Python#packaging tool from Python.org, free (as in freedom). Pipenv is a tool that aims to bring the best of all packaging worlds (#bundler, #composer, #npm, #cargo, #yarn, etc.) to the Python world. #Windows is a first–class citizen, in our world. It automatically creates and manages a #virtualenv for your projects, as well as adds/removes #packages from your #Pipfile as you install/uninstall packages. It also generates the ever–important Pipfile.lock, which is used to produce deterministic builds.