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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 #699 · 11/30/2020, 08:22 AM

#CHI#US#HostHatch HostProvider: HostHatch Specification: 1vCore | 3G RAM | 3T Storage Network: 10T @ 1Gbps Looking glass: lg.chi.hosthatch.com Price: $84 / Year https://paste.ubuntu.com/p/nfQwvFJ7MT/ 感谢群友 @fling4you 的投稿. 这是 hosthatch 19 年黑五的 offer. 机器性能中上, 性价比不错.