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An Open Source Machine Learning Framework for Everyone
Carbon Language's main repository: documents, design, implementation, and related tools. (NOTE: Carbon Language is experimental; see README)
Emscripten: An LLVM-to-WebAssembly Compiler
Parsing gigabytes of JSON per second : used by Facebook/Meta Velox, the Node.js runtime, ClickHouse, WatermelonDB, Apache Doris, Milvus, StarRocks
Filament is a real-time physically based rendering engine for Android, iOS, Windows, Linux, macOS, and WebGL2
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Open3D: A Modern Library for 3D Data Processing
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
FlashMLA: Efficient Multi-head Latent Attention Kernels
A data visualization and analytics component, especially well-suited for large and/or streaming datasets.
The Fastest Distributed Database for Transactional, Analytical, and AI Workloads.
A high-performance distributed file system designed to address the challenges of AI training and inference workloads.
A library for building cross-platform native desktop applications with Node.js and CSS 🚀. React NodeGui : https://react.nodegui.org and Vue NodeGui: https://vue.nodegui.org
Krita is a free and open source cross-platform application that offers an end-to-end solution for creating digital art files from scratch built on the KDE and Qt frameworks.
Portable and lightweight cross-platform desktop application development framework
The JavaScript / Wasm runtime that powers Cloudflare Workers
lightweight, standalone C++ inference engine for Google's Gemma models.
A lightweight library for portable low-level GPU computation using WebGPU.
A machine learning compiler for GPUs, CPUs, and ML accelerators
Universal grid map library for mobile robotic mapping
Go AI program which implements the AlphaGo Zero paper
A minimal WebAssembly virtual DOM to build C++ SPA (Single page applications)
The Haiku operating system. (Pull requests will be ignored; patches may be sent to https://review.haiku-os.org).