GRAPE: Parallelizing Sequential Graph Computations
Summary: GRAPE parallelizes sequential graph algorithms via a simultaneous fixed-point model, enabling partial/incremental evaluation across the graph. Unlike prior systems, it requires no algorithm rewrites; under monotonicity it terminates with correct results for plugged-in sequential algorithms; demonstrates performance vs state-of-the-art and a social-media marketing use case. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Wenfei Fan (Beihang University; University of Edinburgh)
- 2. Jingbo Xu (Beihang University; University of Edinburgh)
- 3. Yinghui Wu (Washington State University)
- 4. Wenyuan Yu (Beihang University)
- 5. Jiaxin Jiang (Hong Kong Baptist University)
BibTeX Citation
@article{fan_vldb17,
title = {{GRAPE: Parallelizing Sequential Graph Computations}},
author = {Fan, Wenfei and Xu, Jingbo and Wu, Yinghui and Yu, Wenyuan and Jiang, Jiaxin},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {12},
pages = {1889--1902},
doi = {10.14778/3137765.3137772},
url = {https://doi.org/10.14778/3137765.3137772},
year = {2017}
}
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,134 | SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks | 2022 | VLDB | 0.00011893521 |
| 3,867 | Distributed D-core Decomposition over Large Directed Graphs | 2022 | VLDB | 6.9581326e-05 |
| 5,684 | iTurboGraph: Scaling and Automating Incremental Graph Analytics | 2021 | SIGMOD | 6.0391416e-05 |
| 6,120 | LSMGraph: A High-Performance Dynamic Graph Storage System with Multi-Level CSR | 2024 | SIGMOD | 5.880693e-05 |
| 6,723 | Adaptive Asynchronous Parallelization of Graph Algorithms | 2018 | SIGMOD | 5.6951102e-05 |
| 9,032 | TGraph: A Tensor-centric Graph Processing Framework | 2025 | SIGMOD | 5.2338437e-05 |
| 9,309 | Revisiting Graph Analytics Benchmark | 2025 | SIGMOD | 5.1969334e-05 |
| 10,327 | Parallel Colorful h-star Core Maintenance in Dynamic Graphs | 2023 | VLDB | 5.0333462e-05 |
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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.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3 | Pregel: A System for Large-Scale Graph Processing | 2010 | SIGMOD | 0.0012092602 |
| 22 | Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud | 2012 | VLDB | 0.00055962491 |
| 496 | From "Think Like a Vertex" to "Think Like a Graph" | 2014 | VLDB | 0.00017323054 |
| 947 | Parallelizing Sequential Graph Computations | 2017 | SIGMOD | 0.00012914714 |
| 959 | Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs | 2014 | VLDB | 0.00012854625 |
| 4,858 | Association Rules with Graph Patterns | 2015 | VLDB | 6.3793644e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,372 | Graph Analytics Through Fine-Grained Parallelism | 2016 | SIGMOD |
| 2 | 2,774 | GraphScope: A Unified Engine For Big Graph Processing | 2021 | VLDB |
| 3 | 2,372 | Giraph Unchained: Barrierless Asynchronous Parallel Execution in Pregel-like Graph Processing Systems | 2015 | VLDB |
| 4 | 3,653 | Realtime Top-k Personalized PageRank over Large Graphs on GPUs | 2020 | VLDB |
| 5 | 9,746 | Graphite: A NUMA-aware HPC System for Graph Analytics Based on a new MPI * X Parallelism Model | 2020 | VLDB |
| 6 | 8,202 | Grep: A Graph Learning Based Database Partitioning System | 2023 | SIGMOD |
| 7 | 11,338 | Efficient Graph Data Access for Out-of-Memory GPU Streaming Graph Processing | 2025 | VLDB |
| 8 | 1,504 | Asynchronous Large-Scale Graph Processing Made Easy | 2013 | CIDR |
| 9 | 6,723 | Adaptive Asynchronous Parallelization of Graph Algorithms | 2018 | SIGMOD |
| 10 | 947 | Parallelizing Sequential Graph Computations | 2017 | SIGMOD |