awesome-gnn-systems
A list of awesome GNN systems.
https://github.com/ch-wan/awesome-gnn-systems
Last synced: 6 days ago
JSON representation
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Open Source Libraries
- DGL: Python Package Built to Ease Deep Learning on Graph
- 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 - learn.svg?logo=github&label=Stars)
- DeepGNN: a Framework for Training Machine Learning Models on Large Scale Graph Data
- PyG: Graph Neural Network Library for PyTorch
- Graph Nets: Build Graph Nets in Tensorflow
- Jraph: A Graph Neural Network Library in Jax
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Papers
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Distributed GNN Training Systems
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/iDC-NEU/NeutronStarLite)|
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 25-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 19-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 14-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 274-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 126-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 104-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/PASSIONLab/CAGNET)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 33-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/YukeWang96/MGG_OSDI23)|
- [paper - 145-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/dmlc/dgl/pull/3024)|
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 49-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 115-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/PASSIONLab/CAGNET)|
- [paper - 130-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/dmlc/dgl/tree/master/python/dgl/distributed)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 144-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/uclasystem/dorylus)|
- [paper - 243-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/jiazhihao/ROC)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/iDC-NEU/NeutronTP)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/ISCS-ZJU/LeapGNN-AE)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/RICE-EIC/BNS-GCN)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/RICE-EIC/PipeGCN)|
- [paper - 50-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/Xtra-Computing/G3)|
- [paper - 4-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 118-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/dmlc/dgl/tree/master/python/dgl/distributed)|
- [paper - 76-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/chenzhao/light-dist-gnn)|
- [paper - 26-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/IntelLabs/SAR)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/MortezaRamezani/llcg)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
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Survey Papers
- [paper - 25-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 302-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 67-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 31-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 30-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
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GNN Libraries
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/THUDM/cogdl)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/deepmind/graph_nets)|
- [paper - 110-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/divelab/DIG)|
- [paper - 355-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/alibaba/graph-learn)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/rusty1s/pytorch_geometric)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/danielegrattarola/spektral)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/dmlc/dgl)|
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GNN Kernels
- [paper - 25-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/apuaaChen/gcnLib)|
- [paper - 52-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 28-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/hgyhungry/ge-spmm)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/HipGraph/FusedMM)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/dgSPARSE/dgNN)|
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GNN Compilers
- [paper - 27-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/xiezhq-hermann/graphiler)|
- [paper - 84-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/dglai/FeatGraph)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/dglai/FeatGraph)|
- [paper - 0-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
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Quantized GNNs
- [paper - 32-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 34-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/YukeWang96/SGQuant)|
- [paper - 49-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/YukeWang96/SGQuant)|
- [paper - 56-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/mbahri/binary_gnn)|
- [paper - 55-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/bywmm/Bi-GCN)|
- [paper - 11-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/Lyun-Huang/EPQuant)|
- [paper - 58-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/warai-0toko/Exact)|
- [paper - 42-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/YukeWang96/PPoPP22_QGTC)|
- [paper - 38-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 181-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/camlsys/degree-quant)|
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GNN Dataloaders
- [paper - 29-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 71-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 56-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/MITIBMxGraph/SALIENT)|
- [paper - 34-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/zhiqi-0/PaGraph)|
- [paper - 37-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 81-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 66-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/K-Wu/pytorch-direct_dgl)|
- [paper - 67-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
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GNN Training Accelerators
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GNN Inference Accelerators
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 29-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 4-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 76-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 124-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 254-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 86-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 34-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 167-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 19-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 14-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 27-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 4-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 123-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 14-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 9-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/stonne-simulator/omega)|
- [paper - 11-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 25-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 2-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 13-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 309-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 43-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/RICE-EIC/GCoD)|
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 1-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
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Training Systems for Scaling Graphs
- [paper - 34-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/marius-team/marius)|
- [paper - 29-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/divelab/DIG/tree/dig-stable/dig/lsgraph)|
- [paper - 160-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/rusty1s/pyg_autoscale)|
- [paper - 155-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/YukeWang96/OSDI21_AE)|
- [paper - 75-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
- [paper - 3-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)||
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Categories
Sub Categories
Keywords
deep-learning
8
graph-neural-networks
8
graph
3
machine-learning
3
tensorflow
3
graphs
2
pytorch
2
link-prediction
2
graph-neural-network
2
jax
2
python
2
graph-learning
2
graph-embedding
2
graph-convolutional-networks
2
gcn
2
networkx
1
machine-learning-algorithms
1
interpretability
1
saliency-map
1
heterogeneous-networks
1
graph-machine-learning
1
graph-data
1
graph-analysis
1
geometric-deep-learning
1
data-science
1
random-walk
1
node2vec
1
network-embedding
1
graphsage
1
ggnn
1
sonnet
1
neural-networks
1
graph-networks
1
artificial-intelligence
1
training
1
graphlearn
1
gnn-inference
1
gnn-framework
1
gnn
1
dynamic-graph-service
1
dynamic-graph
1
aligraph
1
self-supervised-learning
1
graph-generation
1
explainable-ml
1
3d-graph
1
node-classification
1
leaderboard
1
graph-classification
1
gnn-model
1