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Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks

Summary: Staleness-aware decentralized GNN training. Sancus bounds embedding staleness with cache-based histories and adaptive skipping, reframing training as sequential matmul with convergence guarantees, yielding up to 74% less communication and 1.86x throughput. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12692
Venue
VLDB
Year
2022
Pagerank
0.00013586221
Overall Rank
1,160 | 91.94%
DOI
10.14778/3538598.3538614

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 30 of 30 citing papers.

Rank Citing Paper Year Venue Pagerank
2,422 DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU 2023 SIGMOD 8.8499665e-05
3,087 Scalable and Efficient Full-Graph GNN Training for Large Graphs 2023 SIGMOD 7.5939896e-05
5,018 DGC: Training Dynamic Graphs with Spatio-Temporal Non-Uniformity using Graph Partitioning by Chunks 2023 SIGMOD 5.7567672e-05
5,136 NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments 2024 VLDB 5.6723526e-05
5,321 FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training 2024 VLDB 5.5710441e-05
5,345 NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams 2024 VLDB 5.5567697e-05
5,475 ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs 2024 VLDB 5.4869706e-05
5,710 DynaHB: A Communication-Avoiding Asynchronous Distributed Framework with Hybrid Batches for Dynamic GNN Training 2024 VLDB 5.3590055e-05
5,737 Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective 2024 VLDB 5.3480667e-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
7,014 SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement 2024 SIGMOD 4.8616315e-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
7,607 Systems for Scalable Graph Analytics and Machine Learning: Trends and Methods 2025 VLDB 4.6967024e-05
8,463 D3-GNN: Dynamic Distributed Dataflow for Streaming Graph Neural Networks 2024 VLDB 4.5052127e-05
9,395 NeutronTP: Load-Balanced Distributed Full-Graph GNN Training with Tensor Parallelism 2025 VLDB 4.3441378e-05
9,596 Scalable Graph Convolutional Network Training on Distributed-Memory Systems 2023 VLDB 4.319218e-05
9,677 Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving 2025 SIGMOD 4.3047774e-05
9,806 The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format 2024 SIGMOD 4.2805224e-05
10,027 NeutronHeter: Optimizing Distributed Graph Neural Network Training for Heterogeneous Clusters 2026 SIGMOD 4.1945683e-05
10,233 Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling 2026 VLDB 4.1945683e-05
10,267 FlareDTDG: Harnessing Temporal Recency for Scalable Discrete-Time Dynamic Graph Training 2026 VLDB 4.1945683e-05
10,298 NeutronCloud: Resource-Aware Distributed GNN Training in Fluctuating Cloud Environments 2026 VLDB 4.1945683e-05
10,506 SWASH: A Flexible Communication Framework with Sliding Window-Based Cache Sharing for Scalable DGNN Training 2025 SIGMOD 4.1945683e-05
10,539 Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch. 2025 VLDB 4.1945683e-05
10,570 NeutronTask: Scalable and Efficient Multi-GPU GNN Training with Task Parallelism 2025 VLDB 4.1945683e-05
10,638 Heta: Distributed Training of Heterogeneous Graph Neural Networks 2025 VLDB 4.1945683e-05
10,647 Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Study 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
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Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

Rank Cited Paper Year Venue Pagerank
4 Pregel: A System for Large-Scale Graph Processing 2010 SIGMOD 0.0019005923
278 AliGraph: A Comprehensive Graph Neural Network Platform 2019 VLDB 0.00029230623
444 Parallelizing Sequential Graph Computations 2017 SIGMOD 0.00022987918
1,103 Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture 2021 VLDB 0.00014025101
1,329 AGL: A Scalable System for Industrial-purpose Graph Machine Learning 2020 VLDB 0.00012561848
1,942 Heterogeneity-aware Distributed Parameter Servers 2017 SIGMOD 0.00010012691
2,177 Accelerating Large Scale Real-Time GNN Inference using Channel Pruning 2021 VLDB 9.359876e-05
3,986 G3: When Graph Neural Networks Meet Parallel Graph Processing Systems on GPUs 2020 VLDB 6.5611714e-05
4,165 Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization 2021 VLDB 6.3921956e-05
4,577 Accelerating Dynamic Graph Analytics on GPUs 2018 VLDB 6.0709631e-05
5,333 Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce 2021 SIGMOD 5.5656575e-05
6,105 GRAPE: Parallelizing Sequential Graph Computations 2017 VLDB 5.2078702e-05
6,566 Reliable Data Distillation on Graph Convolutional Network 2020 SIGMOD 5.0074274e-05
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Overall Rank Paper Year Venue Pagerank
5,321 FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training 2024 VLDB 5.5710441e-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
5,018 DGC: Training Dynamic Graphs with Spatio-Temporal Non-Uniformity using Graph Partitioning by Chunks 2023 SIGMOD 5.7567672e-05
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2,400 ByteGNN: Efficient Graph Neural Network Training at Large Scale 2022 VLDB 8.8955105e-05
9,596 Scalable Graph Convolutional Network Training on Distributed-Memory Systems 2023 VLDB 4.319218e-05
7,566 ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling 2023 SIGMOD 4.7089968e-05
8,463 D3-GNN: Dynamic Distributed Dataflow for Streaming Graph Neural Networks 2024 VLDB 4.5052127e-05
3,087 Scalable and Efficient Full-Graph GNN Training for Large Graphs 2023 SIGMOD 7.5939896e-05