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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 #853 · 01/18/2023, 12:02 PM

#misaka#DE#BER Host Provider: Misaka Network Location: Berlin, Germany Specification: 1vCore(Xeon Skylake) | 512MB RAM | 10GB NVMe | 512GB Traffic | $10.5 / Mo Test IP: 45.131.71.128 MTR: https://ping.sx/mtr?p=misaka-ber02-s2c 感谢商家提供的测试机。这款是 Misaka 新上的柏林机器,带 CN2 优化。应该会有活动的。这个 CN2 是从他们俄罗斯牵过去的,延迟比咸鱼云的法兰克福要低些。国际目前只有 retn, 后面会加 lumen, 具体啥时候加上就不得而知了。去往西欧延迟更低的一个选择。机器性能可以,本地带宽应该是 10Gbps? BerlinCN2Launch 年付 30off, 限 CN2 产品 https://paste.red/p/c20e1103c9f5