RAPIDS cugraph_pyg enables the ability to use cugraph Property Graphs with PyTorch Geometric (PyG). PyG users will have access to cuGraph and cuGraph-Service through the PyG GraphStore, FeatureStore, and Sampler interfaces. Through cugraph_pyg, PyG users have the full power of cuGraph's GPU-accelerated algorithms for graph analytics, such as sampling, centrality computation, and community detection.
The goal of cugraph_pyg is to enable accelerated single-GPU and multi-node, multi-GPU cugraph accelerated graphs to help train large-scale Graph Neural Networks (GNN) on PyG by providing duck-typed drop-in replacements of the GraphStore, FeatureStore, and Sampler interfaces backed by either cuGraph or cuGraph-Service.
Users of cugraph_pyg have the option of installing either the cugraph or cugraph_service_client packages. Only one is required.
G = cuGraph.PropertyGraph()
...
feature_store, graph_store = to_pyg(G)
sampler = CuGraphSampler(
data=(feature_store, graph_store),
shuffle=True,
num_neighbors=[10,25],
batch_size=50,
)
...