Welcome to cuGraph’s documentation!

RAPIDS cuGraph is a library of graph algorithms that seamlessly integrates into the RAPIDS data science ecosystem and allows the data scientist to easily call graph algorithms using data stored in GPU DataFrames, NetworkX Graphs, or even CuPy or SciPy sparse Matrices.

Contents:

• Basics
  • cuGraph Introduction
  • Vision
  • Terminology
  • Roadmap
  • NetworkX Compatibility and Transition
  • Method Cascading and cuGraph
• Installation
  • Getting cuGraph Packages
  • Building from Source
• Tutorials
  • How To Guides
  • cuGraph Blogs and Presentations
  • Commmunity Resources
• Graph Support
  • Algorithms
  • Compatibility
  • Graph Neural Network Support
  • Data Stores
  • CuGraph Service
• References
  • References
• Developer Resources
  • https://docs.rapids.ai/maintainers
  • API
• Releases
• Python API reference
  • cugraph API Reference
  • pylibcugraph API reference
  • cugraph-dgl API Reference
  • cugraph-pyg API Reference
  • cugraph-service-client API Reference
  • cugraph-service-server API Reference

Indices and tables

• Index

• Search Page