Back to papers
ByteGNN: Efficient Graph Neural Network Training at Large Scale
Summary: ByteGNN enables scalable distributed GNN training with three designs: mini-batch sampling for high parallelism; a two-level scheduler for better resource use; and a GNN-aware partitioner. 3.5–23.8x end-to-end speedups, 2–6x CPU, ~50% network-cost reduction.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 12633
- Venue
- VLDB
- Year
- 2022
- Pagerank
- 8.8869693e-05
- Overall Rank
- 2,399 | 83.33%
- DOI
-
10.14778/3514061.3514069
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 20 of 20 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 5,356 |
NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams |
2024 |
VLDB |
5.5514335e-05 |
| 5,485 |
ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs |
2024 |
VLDB |
5.4817019e-05 |
| 5,746 |
Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective |
2024 |
VLDB |
5.3429324e-05 |
| 7,014 |
SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement |
2024 |
SIGMOD |
4.8570865e-05 |
| 7,286 |
DAHA: Accelerating GNN Training with Data and Hardware Aware Execution Planning |
2024 |
VLDB |
4.7701372e-05 |
| 7,609 |
Systems for Scalable Graph Analytics and Machine Learning: Trends and Methods |
2025 |
VLDB |
4.6921981e-05 |
| 7,924 |
Distributed Graph Embedding with Information-Oriented Random Walks |
2023 |
VLDB |
4.6109814e-05 |
| 8,507 |
Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense |
2024 |
VLDB |
4.4909322e-05 |
| 9,400 |
NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism |
2025 |
VLDB |
4.3399748e-05 |
| 9,596 |
Scalable Graph Convolutional Network Training on Distributed-Memory Systems |
2023 |
VLDB |
4.3150788e-05 |
| 9,787 |
The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format |
2024 |
SIGMOD |
4.2799988e-05 |
| 10,011 |
A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,027 |
NeutronHeter: Optimizing Distributed Graph Neural Network Training for Heterogeneous Clusters |
2026 |
SIGMOD |
4.1905499e-05 |
| 10,310 |
NeutronCloud: Resource-Aware Distributed GNN Training in Fluctuating Cloud Environments |
2026 |
VLDB |
4.1905499e-05 |
| 10,548 |
Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch. |
2025 |
VLDB |
4.1905499e-05 |
| 10,579 |
NeutronTask: Scalable and Efficient Multi-GPU GNN Training with Task Parallelism |
2025 |
VLDB |
4.1905499e-05 |
| 10,646 |
Heta: Distributed Training of Heterogeneous Graph Neural Networks |
2025 |
VLDB |
4.1905499e-05 |
| 10,655 |
Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Study |
2025 |
VLDB |
4.1905499e-05 |
| 10,664 |
Effective and Efficient Distributed Temporal Graph Learning through Hotspot Memory Sharing |
2025 |
VLDB |
4.1905499e-05 |
| 10,977 |
GE2: A General and Efficient Knowledge Graph Embedding Learning System |
2024 |
SIGMOD |
4.1905499e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 10,579 |
NeutronTask: Scalable and Efficient Multi-GPU GNN Training with Task Parallelism |
2025 |
VLDB |
4.1905499e-05 |
| 9,400 |
NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism |
2025 |
VLDB |
4.3399748e-05 |
| 10,310 |
NeutronCloud: Resource-Aware Distributed GNN Training in Fluctuating Cloud Environments |
2026 |
VLDB |
4.1905499e-05 |
| 7,568 |
ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling |
2023 |
SIGMOD |
4.7044808e-05 |
| 10,548 |
Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch. |
2025 |
VLDB |
4.1905499e-05 |
| 10,233 |
Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling |
2026 |
VLDB |
4.1905499e-05 |
| 9,596 |
Scalable Graph Convolutional Network Training on Distributed-Memory Systems |
2023 |
VLDB |
4.3150788e-05 |
| 5,746 |
Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective |
2024 |
VLDB |
5.3429324e-05 |
| 6,944 |
Efficient Training of Graph Neural Networks on Large Graphs |
2024 |
VLDB |
4.8875946e-05 |
| 3,092 |
Scalable and Efficient Full-Graph GNN Training for Large Graphs |
2023 |
SIGMOD |
7.5869574e-05 |