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Source channel @githubtrending · Post #15007 · Jul 29

#c_lang You can find detailed guides for Linux kernel developers and users in the Documentation/ folder, which includes files in formats like HTML and PDF. To build these documents yourself, use commands like `make htmldocs` or `make pdfdocs`. The documentation covers important topics such as kernel building, running requirements, and upgrade issues. You can also view the latest formatted docs online. Additionally, the kernel source uses a special comment style called kernel-doc to embed documentation directly in the code, making it easier to understand functions and structures. This helps you learn, build, and maintain the Linux kernel more effectively. https://github.com/raspberrypi/linux

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@githubtrending · Post #15271 · 11/05/2025, 12:30 PM

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#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance. https://github.com/PaddlePaddle/Paddle-Lite

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