Sequential Aggregation and Rematerialization: Distributed Full-batch Training of Graph Neural Networks on Large Graphs (original) (raw)
Related papers
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks
2021
Scalable Graph Convolutional Network Training on Distributed-Memory Systems
Proceedings of the VLDB Endowment
P3: Distributed Deep Graph Learning at Scale
2021
GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism
arXiv (Cornell University), 2023
Residual convolutional graph neural network with subgraph attention pooling
Tsinghua Science and Technology, 2022
Large-Scale Learnable Graph Convolutional Networks
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
Permutohedral-GCN: Graph Convolutional Networks with Global Attention
ArXiv, 2020
Analyzing the Performance of Graph Neural Networks with Pipe Parallelism
ArXiv, 2020
GDLL: A Scalable and Share Nothing Architecture based Distributed Graph Neural Networks Framework
IEEE Access
Communication-Efficient Sampling for Distributed Training of Graph Convolutional Networks
2021
Enhance Information Propagation for Graph Neural Network by Heterogeneous Aggregations
ArXiv, 2021
ADGraph: Accurate, Distributed Training on Large Graphs
Computer Science & Information Technology (CS & IT) Computer Science Conference Proceedings (CSCP)
G3: When Graph Neural Networks Meet Parallel Graph Processing Systems on GPUs
2020
Simplifying Graph Attention Networks with Source-Target Separation
2020
TF-GNN: Graph Neural Networks in TensorFlow
arXiv (Cornell University), 2022
SIGN: Scalable Inception Graph Neural Networks
Improving Graph Convolutional Networks with Non-Parametric Activation Functions
2018
Efficient scaling of dynamic graph neural networks
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2021
Breaking the Limits of Message Passing Graph Neural Networks
2021
Graph Neural Networks with Composite Kernels
ArXiv, 2020
Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2
Computing Graph Neural Networks: A Survey from Algorithms to Accelerators
ACM Computing Surveys
Graph Attention Multi-Layer Perceptron
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks
ArXiv, 2020
Scaling R-GCN Training with Graph Summarization
2022
Learning Graph Neural Networks with Approximate Gradient Descent
2021
Model Degradation Hinders Deep Graph Neural Networks
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Wide and Deep Graph Neural Networks with Distributed Online Learning
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
Pre-training Graph Neural Networks with Kernels
ArXiv, 2018
Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and Inference
ArXiv, 2019
An Analysis of Attentive Walk-Aggregating Graph Neural Networks
ArXiv, 2021
ArXiv, 2018
Introduction to Graph Neural Networks
Synthesis Lectures on Artificial Intelligence and Machine Learning, 2020
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks
arXiv (Cornell University), 2023
A Comprehensive Survey on Graph Neural Networks
IEEE Transactions on Neural Networks and Learning Systems, 2020