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Source channel @githubtrending · Post #14985 · Jul 22

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#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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@bcd8888 · Post #1546 · 08/07/2025, 01:25 PM

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@tribebrook · Post #469 · 10/04/2025, 03:47 PM

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#Mac#清理#GitHub#CleanMyMac#Lemon 🦡 像鼹鼠一样深入挖掘来清理您的 Mac 一；亮点 🐦深度系统清理- 一次性删除隐藏的缓存、日志和临时文件 📦彻底卸载- 清理了 22 个以上位置，而标准卸载只有 1 个，优于 CleanMyMac/Lemon ⚡️快速且轻量- 基于终端，零膨胀，带分页的箭头键导航 🧹海量空间恢复- 回收 100GB 以上的浪费磁盘空间 二；安装 curl -fsSL curl -fsSL https://raw.githubusercontent.com/tw93/mole/main/install.sh | bash 或者通过 Homebrew： brew install tw93/tap/mole GitHub地址：官方 🔔提示：限免，兑换码具有时效性，打开本频道通知，第一时间获取全网资讯！！！ 🏠本消息Via：小小溪 📰群组：homeBrook 📢频道：Home_brook 🤖其他问题（投稿）请Bot：@xia0_bot

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