awesome-gnn-systems
github.com/ch-wan/awesome-gnn-systems ↗A list of awesome GNN systems.
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Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me gnn inference accelerators resources from awesome-gnn-systems"
Installation instructions →What's inside
Papers
- APA 2020GNN Inference Accelerators
GNN-PIM: A Processing-in-Memory Architecture for Graph Neural Networks
- arXiv 2018GNN Libraries
Relational Inductive Biases, Deep Learning, and Graph Networks
- arXiv 2019GNN Libraries
Fast Graph Representation Learning with PyTorch Geometric
- arXiv 2019GNN Dataloaders
TigerGraph: A Native MPP Graph Database
- arXiv 2019GNN Libraries
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
- arXiv 2020GNN Inference Accelerators
GRIP: A Graph Neural Network Accelerator Architecture
Open Source Libraries
- CogDL: An Extensive Toolkit for Deep Learning on Graphs
- DeepGNN: a Framework for Training Machine Learning Models on Large Scale Graph Data
- DGL: Python Package Built to Ease Deep Learning on Graph
- DIG: A Turnkey Library for Diving into Graph Deep Learning Research
- Euler: A Distributed Graph Deep Learning Framework
- Graph-Learn: An Industrial Graph Neural Network Framework
Showing a sample of 117 resources. View the full list on GitHub →