{"repo":"AlgRUC/JittorGeometric","free":true,"listed":false,"github":"https://github.com/AlgRUC/JittorGeometric","clone":"git clone https://github.com/AlgRUC/JittorGeometric.git","description":"JittorGeometric is a Jittor-based graph machine learning library.","language":"Python","stars":1156,"topics":["graph","jittor","python"],"license":"Apache-2.0","category":"machine-learning","readme_excerpt":"JittorGeometric 2.0 A Comprehensive Graph Machine Learning Library Built on Jittor Documentation • Examples • Installation • Quick Start • Models --- Overview JittorGeometric 2.0 is a state-of-the-art graph machine learning library built on the Jittor framework. As a Chinese-developed deep learning library, JittorGeometric provides comprehensive support for Graph Neural Networks (GNNs) research and applications, featuring enhanced performance, flexibility, and scalability. 🌟 Key Features Core Capabilities - 🚀 JIT Compilation : Leverage Just-In-Time compilation for dynamic code modification without pre-compilation overhead - ⚡ Optimized Sparse Operations : High-performance sparse matrix computations with CuSparse acceleration - 🎯 Comprehensive Model Zoo : 40+ implemented models covering classic, spectral, dynamic, molecular, and transformer-based GNNs - 📊 Rich Dataset Support : Built-in loaders for popular graph datasets (Planetoid, OGB, Reddit, etc.) New in Version 2.0 - 🔄 Distributed Training : Multi-GPU and multi-node training support with MPI - 🌊 Dynamic Graph Processing : Event-based dynamic graph support with parallel processing - 📦 Mini-batch Support : Efficient mini-batch training for large-scale graphs - 🔧 Ascend-GNN : GNN for NPU - 🎛️ Extended Model Categories : Graph transformers, self-supervised learning, and recommendation systems Quick Tour Supported Models JittorGeometric 2.0 includes implementations of 40+ state-of-the-art GNN models: Classic Graph Neu","default_branch":null,"files":null,"tree":[],"storefront":"/r/AlgRUC","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AlgRUC/JittorGeometric/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}