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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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AIGC

@aigcrubbish · Post #158 · 01/27/2026, 05:06 PM

[$] Implicit arguments for BPF kfuncs Linux 内核的 kfunc 机制允许 BPF 程序直接调用内核函数。目前内核中有超过 300 个 kfunc,功能涵盖字符串处理(如 `bpf_strnlen()`)到自定义调度器(如 `scx_bpf_kick_cpu()`)等。 有时,这些 kfunc 需要访问 BPF 程序无法直接获取的上下文信息,因此无法通过参数传递。Ihor Solodrai 提交的“隐式参数”补丁集旨在解决这个问题,它允许 kfunc 隐式地接收额外的上下文参数。 原文链接:https://lwn.net/Articles/1055559/ #Linux#内核#BPF#kfunc #AIGC Read more