Loading Now

Summary of Graph Neural Network Training Systems: a Performance Comparison Of Full-graph and Mini-batch, by Saurabh Bajaj and Hojae Son and Juelin Liu and Hui Guan and Marco Serafini


Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch

by Saurabh Bajaj, Hojae Son, Juelin Liu, Hui Guan, Marco Serafini

First submitted to arxiv on: 1 Jun 2024

Categories

  • Main: Machine Learning (cs.LG)
  • Secondary: Distributed, Parallel, and Cluster Computing (cs.DC)

     Abstract of paper      PDF of paper


GrooveSquid.com Paper Summaries

GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!

Summary difficulty Written by Summary
High Paper authors High Difficulty Summary
Read the original abstract here
Medium GrooveSquid.com (original content) Medium Difficulty Summary
The paper explores the differences between two methods of training Graph Neural Networks (GNNs): mini-batch training and full-graph training. Two distinct classes of GNN training systems emerged, each optimized for one method, with limited comparison between them. Some prior work justifies its focus on a specific training method by claiming higher accuracy, but the literature lacks complete and consistent evidence.
Low GrooveSquid.com (original content) Low Difficulty Summary
The paper looks at how we train Graph Neural Networks (GNNs) in two different ways: mini-batch training and full-graph training. Because these methods require different tools and tricks, two types of systems for training GNNs were developed. Some people think one way is better than the other because it gets more accurate results. But really, we don’t know which one is best.

Keywords

» Artificial intelligence  » Gnn