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Source channel @githubtrending · Post #14714 · May 16

#go#compression#decompression#deflate#go#golang#gzip#snappy#zip#zstandard#zstd The "github.com/klauspost/compress" package offers many fast and efficient compression tools in pure Go, including zstandard, S2 (a faster Snappy replacement), optimized deflate for gzip/zip/zlib, and snappy with better compression and concurrency. It also provides entropy encoders (huff0, FSE), HTTP gzip handlers, and a parallel gzip implementation (pgzip). These tools are drop-in replacements for Go's standard libraries but run about twice as fast, saving time and resources. You can easily add it to your project with `go get`. It supports current and recent Go versions and offers options to disable unsafe code or assembly for compatibility. This package benefits you by improving compression speed and efficiency while maintaining compatibility with standard Go compression APIs, making your applications faster and more resource-friendly. https://github.com/klauspost/compress

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

#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