GTS: A Fast and Scalable Graph Processing Method based on Streaming Topology to GPUs
Summary: GTS enables fast GPU graph processing on a single machine by streaming topology from SSDs to thousands of GPU cores, avoiding inter-machine partitioning. Designed for RMAT32-scale graphs (~64B edges), it outperforms GraphX, Giraph, PowerGraph, TOTEM in experiments. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Min-Soo Kim
- 2. Kyuhyeon An
- 3. Himchan Park
- 4. Hyunseok Seo
- 5. Jinwook Kim
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,281 | Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching | 2022 | VLDB | 7.2812392e-05 |
| 3,674 | A Distributed Multi-GPU System for Fast Graph Processing | 2018 | VLDB | 6.8502146e-05 |
| 4,525 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD | 6.1087614e-05 |
| 5,811 | CGgraph: An Ultra-fast Graph Processing System on Modern Commodity CPU-GPU Co-processor | 2024 | VLDB | 5.3168243e-05 |
| 6,658 | TrillionG: A Trillion-scale Synthetic Graph Generator using a Recursive Vector Model | 2017 | SIGMOD | 4.9684622e-05 |
| 6,747 | DistME: A Fast and Elastic Distributed Matrix Computation Engine using GPUs | 2019 | SIGMOD | 4.9369478e-05 |
| 10,044 | ACGraph: An Efficient Asynchronous Out-of-Core Graph Processing Framework | 2026 | SIGMOD | 4.1905499e-05 |
| 10,523 | cuMatch: A GPU-based Memory-Efficient Worst-case Optimal Join Processing Method for Subgraph Queries with Complex Patterns | 2025 | SIGMOD | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 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 | 0.0019040811 |
| 39 | Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud | 2012 | VLDB | 0.00075263552 |
| 70 | Hive - A Warehousing Solution Over a Map-Reduce Framework | 2009 | VLDB | 0.00059744625 |
| 2,761 | Giraph Unchained: Barrierless Asynchronous Parallel Execution in Pregel-like Graph Processing Systems | 2015 | VLDB | 8.1616217e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,684 | Fast Iterative Graph Computation with Block Updates | 2013 | VLDB | 0.00010912102 |
| 10,276 | gMatch: Fine-Grained and Hardware-Efficient Subgraph Matching on GPUs | 2026 | VLDB | 4.1905499e-05 |
| 10,867 | Towards Sufficient GPU-accelerated Dynamic Graph Management: Survey and Experiment | 2025 | VLDB | 4.1905499e-05 |
| 1,876 | Large-Scale Distributed Graph Computing Systems: An Experimental Evaluation | 2015 | VLDB | 0.00010242818 |
| 4,578 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB | 6.0651154e-05 |
| 10,079 | Fast Optimal Group Steiner Tree Search using GPUs | 2026 | SIGMOD | 4.1905499e-05 |
| 5,811 | CGgraph: An Ultra-fast Graph Processing System on Modern Commodity CPU-GPU Co-processor | 2024 | VLDB | 5.3168243e-05 |
| 5,014 | TurboGraph++: A Scalable and Fast Graph Analytics System | 2018 | SIGMOD | 5.7519428e-05 |
| 10,713 | Efficient Graph Data Access for Out-of-Memory GPU Streaming Graph Processing | 2025 | VLDB | 4.1905499e-05 |
| 4,525 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD | 6.1087614e-05 |