Welcome to RAPIDS Graph documentation#
RAPIDS Graph covers a range of graph libraries and packages, that includes:
cugraph: GPU-accelerated graph algorithms
cugraph-ops: GPU-accelerated GNN aggregators and operators
cugraph-service: multi-user, remote GPU-accelerated graph algorithm service
cugraph-pyg: GPU-accelerated extensions for use with the PyG framework
cugraph-dgl: GPU-accelerated extensions for use with the DGL framework
wholegraph: shared memory-based GPU-accelerated GNN training
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.
Note: We are redoing all of our documents, please be patient as we update the docs and links