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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 #863 · 04/08/2023, 08:40 AM

#Oneprovider#OneCloud#KR#ICN Host Provider: OneCloud Location: Seoul, Republic of Korea Specification: 1vCore | 1GB RAM | 30GB SSD | 1.5TB @ 1Gbps | $8 / Mo Test IP: 223.165.5.1/24 自己试吧 机器性能给人一种大树挂辣椒的感觉。上游 Ehostict 啥都不解锁。三网 SK 延迟很低但我这没速度,估计是 UDP 会被恰,也可能存粹是太挤了。 https://paste.red/p/b7cb8bcc973b