Awesome Graph Neural Network Systems

A list of awesome systems for graph neural network (GNN). If you have any comment, please create an issue or pull request.

Contents

• Open Source Libraries
• Papers
• Survey Papers
• GNN Libraries
• GNN Kernels
• GNN Compilers
• Distributed GNN Training Systems
• Training Systems for Scaling Graphs
• Quantized GNNs
• GNN Dataloaders
• GNN Training Accelerators
• GNN Inference Accelerators
• Contribute

Open Source Libraries

• PyG: Graph Neural Network Library for PyTorch
• DGL: Python Package Built to Ease Deep Learning on Graph
• Graph Nets: Build Graph Nets in Tensorflow
• Euler: A Distributed Graph Deep Learning Framework
• StellarGraph: Machine Learning on Graphs
• Spektral: Graph Neural Networks with Keras and Tensorflow 2
• PGL: An Efficient and Flexible Graph Learning Framework Based on PaddlePaddle
• CogDL: An Extensive Toolkit for Deep Learning on Graphs
• DIG: A Turnkey Library for Diving into Graph Deep Learning Research
• Jraph: A Graph Neural Network Library in Jax
• Graph-Learn: An Industrial Graph Neural Network Framework
• DeepGNN: a Framework for Training Machine Learning Models on Large Scale Graph Data

Papers

Survey Papers

Venue	Title	Affiliation	Link	Source
CSUR 2024	Distributed Graph Neural Network Training: A Survey	BUPT	[paper]
Proceedings of the IEEE 2023	A Comprehensive Survey on Distributed Training of Graph Neural Networks	Chinese Academy of Sciences	[paper]
arXiv 2023	A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware	UCLA	[paper]
arXiv 2022	Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis	ETHZ	[paper]
CSUR 2022	Computing Graph Neural Networks: A Survey from Algorithms to Accelerators	UPC	[paper]
### GNN Libraries
Venue	Title	Affiliation	Link	Source
:---:	:---:	:---------:	:---:	:----:
JMLR 2021	DIG: A Turnkey Library for Diving into Graph Deep Learning Research	TAMU	[paper]	[code]
arXiv 2021	CogDL: A Toolkit for Deep Learning on Graphs	THU	[paper]	[code]
CIM 2021	Graph Neural Networks in TensorFlow and Keras with Spektral	Università della Svizzera italiana	[paper]	[code]
arXiv 2019	Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks	AWS	[paper]	[code]
VLDB 2019	AliGraph: A Comprehensive Graph Neural Network Platform	Alibaba	[paper]	[code]
arXiv 2019	Fast Graph Representation Learning with PyTorch Geometric	TU Dortmund University	[paper]	[code]
arXiv 2018	Relational Inductive Biases, Deep Learning, and Graph Networks	DeepMind	[paper]	[code]
### GNN Kernels
Venue	Title	Affiliation	Link	Source
:---:	:---:	:---------:	:---:	:----:
MLSys 2022	Understanding GNN Computational Graph: A Coordinated Computation, IO, and Memory Perspective	THU	[paper]	[code]
HPDC 2022	TLPGNN: A Lightweight Two-Level Parallelism Paradigm for Graph Neural Network Computation on GPU	GW	[paper]
IPDPS 2021	FusedMM: A Unified SDDMM-SpMM Kernel for Graph Embedding and Graph Neural Networks	Indiana University Bloomington	[paper]	[code]
SC 2020	GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks	THU	[paper]	[code]
ICCAD 2020	fuseGNN: Accelerating Graph Convolutional Neural Network Training on GPGPU	UCSB	[paper]	[code]
IPDPS 2020	PCGCN: Partition-Centric Processing for Accelerating Graph Convolutional Network	PKU	[paper]
### GNN Compilers
Venue	Title	Affiliation	Link	Source
:---:	:---:	:---------:	:---:	:----:
MLSys 2022	Graphiler: Optimizing Graph Neural Networks with Message Passing Data Flow Graph	ShanghaiTech	[paper]	[code]
EuroSys 2021	Seastar: Vertex-Centric Programming for Graph Neural Networks	CUHK	[paper]
SC 2020	FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems	Cornell	[paper]	[code]
### Distributed GNN Training Systems
Venue	Title	Affiliation	Link	Source
:---:	:---:	:---------:	:---:	:----:
FAST 2025	LeapGNN: Accelerating Distributed GNN Training Leveraging Feature-Centric Model Migration	ZJU	[paper]	[code]
VLDB 2025	NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism	NEU	[paper]	[code]
arXiv 2023	Communication-Free Distributed GNN Training with Vertex Cut	Stanford	[paper]
arXiv 2023	GNNPipe: Accelerating Distributed Full-Graph GNN Training with Pipelined Model Parallelism	Purdue	[paper]
OSDI 2023	MGG: Accelerating Graph Neural Networks with Fine-Grained Intra-Kernel Communication-Computation Pipelining on Multi-GPU Platforms	UCSB	[paper]	[code]![GitHub stars](h