FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training

Summary: FreshGNN caches historical node embeddings to avoid repeated raw-feature loads in GNN mini-batch training, lowering GPU–CPU traffic. A gradient+staleness policy caches only stable embeddings, yielding 59% fewer memory accesses and 3.4–20.5x speedups on large graphs with <1% accuracy loss. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13389
Venue: VLDB
Year: 2024
Pagerank: 5.5710441e-05
Overall Rank: 5,321 | 62.99%
DOI: 10.14778/3648160.3648184

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
5,136	NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments	2024	VLDB	5.6723526e-05
6,980	OUTRE: An OUT-of-core De-REdundancy GNN Training Framework for Massive Graphs within A Single Machine	2024	VLDB	4.8744298e-05
10,011	A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness	2026	SIGMOD	4.1945683e-05
10,638	Heta: Distributed Training of Heterogeneous Graph Neural Networks	2025	VLDB	4.1945683e-05
10,735	Faster Convergence in Mini-batch Graph Neural Networks Training with Pseudo Full Neighborhood Compensation	2025	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,160	Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks	2022	VLDB	0.00013586221

Semantically Similar Papers

Overall Rank	Paper	Year	Venue	Pagerank
2,400	ByteGNN: Efficient Graph Neural Network Training at Large Scale	2022	VLDB	8.8955105e-05
5,737	Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective	2024	VLDB	5.3480667e-05
3,087	Scalable and Efficient Full-Graph GNN Training for Large Graphs	2023	SIGMOD	7.5939896e-05
7,014	SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement	2024	SIGMOD	4.8616315e-05
7,108	DiskGNN: Bridging I/O Efficiency and Model Accuracy for Out-of-Core GNN Training	2025	SIGMOD	4.8297805e-05
7,545	XGNN: Boosting Multi-GPU GNN Training via Global GNN Memory Store	2024	VLDB	4.714889e-05
10,735	Faster Convergence in Mini-batch Graph Neural Networks Training with Pseudo Full Neighborhood Compensation	2025	VLDB	4.1945683e-05
6,942	Efficient Training of Graph Neural Networks on Large Graphs	2024	VLDB	4.8922884e-05
5,561	Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage Accesses	2024	VLDB	5.4332062e-05
8,363	Eliminating Data Processing Bottlenecks in GNN Training over Large Graphs via Two-level Feature Compression	2024	VLDB	4.5364942e-05