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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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Host Testing and evaluation

@HostEvaluate · Post #801 · 07/25/2022, 02:31 AM

#Marbell#CH Host Provider: Marbell Location: Zurich, Switzerland Specification: 2vCore | 2GB RAM | 120GB SSD | 1TB @ 1Gbps | ~$3.90 / Mo Test IP: 185.203.41.129 https://paste.red/p/eb86d0e3ca29 匿名投稿。储存空间挺大的 m247 机房机器。他们家声称保证 100% uptime.

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