DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks.
Vasimuddin MdSanchit MisraGuixiang MaRamanarayan MohantyEvangelos GeorganasAlexander HeineckeDhiraj D. KalamkarNesreen K. AhmedSasikanth AvanchaPublished in: CoRR (2021)
Keyphrases
- scalable distributed
- neural network
- training process
- training algorithm
- feedforward neural networks
- feed forward neural networks
- neural network training
- pattern recognition
- backpropagation algorithm
- graph representation
- multi layer perceptron
- graph structure
- real world
- graph theory
- training set
- structured data
- connected components
- back propagation
- massive graphs
- recurrent networks
- training patterns
- supervised learning
- random walk
- graph model
- test set
- small scale
- bipartite graph
- file system
- directed graph
- training examples
- graph databases
- training phase
- training samples
- activation function
- online learning
- artificial neural networks
- neural network structure
- genetic algorithm
- multilayer neural network
- self organizing maps