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NeutronTask: Scalable and Efficient Multi-GPU GNN Training with Task Parallelism

Summary: Introduce GNN task parallelism that partitions per-layer training tasks across GPUs (instead of graph partitioning), reducing neighbor replication, enabling intra-GPU shared neighbor-embedding reuse and overlapping subgraph computation. Combine with a task-decoupled training framework that releases intermediate data early to cut memory, enabling billion-scale full-graph multi-GPU training and 1.27×–5.47× speedups over NeutronStar/Sancus on 4×A5000. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13830
Venue
VLDB
Year
2025
Pagerank
4.1945683e-05
Overall Rank
10,570 | 26.47%
DOI
10.14778/3725688.3725700

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Showing 16 of 16 cited papers.

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

Rank Cited Paper Year Venue Pagerank
278 AliGraph: A Comprehensive Graph Neural Network Platform 2019 VLDB 0.00029230623
1,160 Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks 2022 VLDB 0.00013586221
2,400 ByteGNN: Efficient Graph Neural Network Training at Large Scale 2022 VLDB 8.8955105e-05
2,422 DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU 2023 SIGMOD 8.8499665e-05
3,025 NeutronStar: Distributed GNN Training with Hybrid Dependency Management 2022 SIGMOD 7.6906935e-05
3,087 Scalable and Efficient Full-Graph GNN Training for Large Graphs 2023 SIGMOD 7.5939896e-05
4,355 LargeEA: Aligning Entities for Large-scale Knowledge Graphs 2022 VLDB 6.259483e-05
5,136 NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments 2024 VLDB 5.6723526e-05
5,443 Decoupled Graph Neural Networks for Large Dynamic Graphs 2023 VLDB 5.5025808e-05
6,884 Lotan: Bridging the Gap between GNNs and Scalable Graph Analytics Engines 2023 VLDB 4.8955332e-05
6,942 Efficient Training of Graph Neural Networks on Large Graphs 2024 VLDB 4.8922884e-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
7,091 HongTu: Scalable Full-Graph GNN Training on Multiple GPUs 2023 SIGMOD 4.8370645e-05
7,289 DAHA: Accelerating GNN Training with Data and Hardware Aware Execution Planning 2024 VLDB 4.7747168e-05
7,545 XGNN: Boosting Multi-GPU GNN Training via Global GNN Memory Store 2024 VLDB 4.714889e-05
9,395 NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism 2025 VLDB 4.3441378e-05
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Overall Rank Paper Year Venue Pagerank
7,091 HongTu: Scalable Full-Graph GNN Training on Multiple GPUs 2023 SIGMOD 4.8370645e-05
5,737 Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective 2024 VLDB 5.3480667e-05
2,400 ByteGNN: Efficient Graph Neural Network Training at Large Scale 2022 VLDB 8.8955105e-05
5,345 NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams 2024 VLDB 5.5567697e-05
3,087 Scalable and Efficient Full-Graph GNN Training for Large Graphs 2023 SIGMOD 7.5939896e-05
10,027 NeutronHeter: Optimizing Distributed Graph Neural Network Training for Heterogeneous Clusters 2026 SIGMOD 4.1945683e-05
3,025 NeutronStar: Distributed GNN Training with Hybrid Dependency Management 2022 SIGMOD 7.6906935e-05
10,298 NeutronCloud: Resource-Aware Distributed GNN Training in Fluctuating Cloud Environments 2026 VLDB 4.1945683e-05
5,136 NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments 2024 VLDB 5.6723526e-05
9,395 NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism 2025 VLDB 4.3441378e-05