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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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#go #compression #decompression #deflate #golang #gzip #snappy #zip #zstandard #zstd

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@githubtrending · Post #14659 · 05/01/2025, 03:30 PM

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#cplusplus#arm#convolution#deep_learning#embedded_devices#llm#machine_learning#ml#mnn#transformer#vulkan#winograd_algorithm MNN is a lightweight and efficient deep learning framework that helps run AI models on mobile devices and other small devices. It supports many types of AI models and can handle tasks like image recognition and language processing quickly and locally on your device. This means you can use AI features without needing to send data to the cloud, which improves privacy and speed. MNN is used in many apps, including those from Alibaba, and supports various platforms like Android and iOS. It also helps reduce the size of AI models, making them faster and more efficient. https://github.com/alibaba/MNN

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#cplusplus #arm #convolution #deep_learning #embedded_devices #llm #machine_learning #ml #mnn #transformer #vulkan #winograd_algorithm