7 مستودعات
Best practices and build configurations for creating shared libraries.
Distinguishing note: Focuses on the creation and build-system integration of shared libraries.
Explore 7 awesome GitHub repositories matching operating systems & systems programming · Shared Library Development. Refine with filters or upvote what's useful.
This project is a comprehensive technical knowledge base designed to support developers in mastering systems programming and preparing for technical assessments. It provides a structured collection of fundamental computer science concepts, mapping high-level language constructs to low-level hardware memory layouts, runtime object lifecycles, and system-level operations. The repository distinguishes itself through a hierarchical approach that bridges the gap between theoretical principles and practical implementation. It offers detailed guidance on C++ language mechanisms, standard library usa
Provides guidance on configuring and building shared libraries across different environments.
Zstandard is a lossless data compression library and archive format designed for high compression ratios and fast real-time processing. It functions as a real-time data compressor and multi-threaded compression engine capable of distributing workloads across multiple CPU cores to increase throughput. The system features a dictionary-based compressor that trains on sample data to improve the compression ratio and speed of small files. It also provides long distance pattern matching to identify repeated sequences across large files. The library covers a broad range of capabilities including st
Supports compiling source code into shared or static libraries using a build system to manage dependencies.
This project is a cross-platform machine learning inference engine designed to execute pre-trained models across diverse operating systems and hardware environments. It functions as a standardized execution framework that manages the entire lifecycle of model inference, from loading and graph optimization to hardware-accelerated execution and generative sequence management. The runtime distinguishes itself through a highly modular architecture that decouples model logic from hardware-specific kernels. By utilizing an execution provider abstraction, it enables developers to offload computation
Generates native C++ shared libraries for cross-platform deployment and custom linkage.
Nim is a statically typed, compiled systems programming language designed for high performance and cross-platform development. It translates high-level source code into C, C++, or JavaScript, allowing developers to produce efficient native binaries or web-compatible scripts from a single codebase. The language emphasizes a clean, indentation-based syntax that simplifies code hierarchy while maintaining the power of a full-featured systems language. What distinguishes Nim is its robust metaprogramming framework, which allows developers to inspect, modify, and generate code structures during th
Produces dynamic or static shared libraries to allow integration with external host applications.
Specs is a centralized package metadata repository and distribution service for the Apple platform. It serves as a public index of library specifications, enabling the discovery, resolution, and installation of third-party frameworks for iOS and macOS projects. The project provides a podspec distribution service that hosts and validates library specifications to ensure reproducible dependency resolution. It utilizes a Git-based collection of structured specifications and a REST API to manage library publishing, ownership, and versioning. The system encompasses comprehensive capabilities for
Pulls libraries from specification files hosted at HTTP URLs.
gemma.cpp is a C++ inference engine for Gemma, PaliGemma, and Griffin language models, designed to run directly on-device without Python dependencies. It provides a self-contained runtime that loads quantized model weights and performs text generation on CPU or GPU, along with a model checkpoint converter that transforms PyTorch or Keras checkpoints into a compact binary format for fast loading. The engine supports multiple model architectures, including the Griffin recurrent architecture with gated linear recurrent layers and sliding-window attention for efficient long-sequence handling, as
Compiles the inference engine into a standalone shared library for linking into external CMake projects via FetchContent.
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