C++ 排行榜

Optimized primitives for collective multi-GPU communication

MegEngine 是一个快速、可拓展、易于使用且支持自动求导的深度学习框架

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.

Fast inference engine for Transformer models

Tengine is a lite, high performance, modular inference engine for embedded device

Lightning fast C++/CUDA neural network framework

A lite C++ AI toolkit: 100+ models with MNN, ORT and TRT, including Det, Seg, Stable-Diffusion, Face-Fusion.

Simplify your onnx model

High-performance open-source in-memory graph database for GraphRAG, AI memory, agentic AI, and real-time graph analytics. Cypher-compatible, built in C++.

oneAPI Deep Neural Network Library (oneDNN)

A retargetable MLIR-based machine learning compiler and runtime toolkit.

Turbopilot is an open source large-language-model based code completion engine that runs locally on CPU

a distributed deep learning platform

校招、秋招、春招、实习好项目！带你从零实现一个高性能的深度学习推理库，支持大模型 llama2 、Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library step by step

The official repository for ROOT: analyzing, storing and visualizing big data, scientifically

ONNX-TensorRT: TensorRT backend for ONNX

Open source neural network chess engine with GPU acceleration and broad hardware support.

The Compute Library is a set of computer vision and machine learning functions optimised for both Arm CPUs and GPUs using SIMD technologies.

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.