Memory Consumption Patterns of LightGCL, SGL, and GCA on Large-Scale Graphs

This report synthesises findings from 1 peer-reviewed paper addressing the following research question: How do the memory consumption patterns of LightGCL, SGL, and GCA differ during training on graphs scaling from 1 million to 20 million nodes. 13 claims were extracted from source literature; 11 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 7.7/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: How do the memory consumption patterns of LightGCL, SGL, and GCA differ during training on graphs scaling from 1 million to 20 million nodes?

Autonomous literature synthesis. Automated review score: 7.7/10. Full text and citation available at Assignee Research.