Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining
Summary: Non-parametric, self-tunable data representation and a novel tiling scheme optimize SpMV on GPUs for power-law graphs. Auto-tuning with a runtime performance model enables adaptive parameters and scalable multi-GPU graph mining (PageRank, HITS, RWR). (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,767 | Accelerating Triangle Counting on GPU | 2021 | SIGMOD | 7.1923965e-05 |
| 4,101 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD | 6.9638989e-05 |
| 4,178 | Realtime Top-k Personalized PageRank over Large Graphs on GPUs | 2020 | VLDB | 6.914103e-05 |
| 4,289 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB | 6.8514818e-05 |
| 8,188 | GraphINC: Graph Pattern Mining at Network Speed | 2023 | SIGMOD | 5.5378389e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,584 | Scalable Graph Convolutional Network Training on Distributed-Memory Systems | 2023 | VLDB | 5.3099516e-05 |
| 10,867 | Towards Sufficient GPU-accelerated Dynamic Graph Management: Survey and Experiment | 2025 | VLDB | 5.1725247e-05 |
| 10,276 | gMatch: Fine-Grained and Hardware-Efficient Subgraph Matching on GPUs | 2026 | VLDB | 5.1725247e-05 |
| 2,827 | GPU-Accelerated Subgraph Enumeration on Partitioned Graphs | 2020 | SIGMOD | 8.1346366e-05 |
| 10,713 | Efficient Graph Data Access for Out-of-Memory GPU Streaming Graph Processing | 2025 | VLDB | 5.1725247e-05 |
| 3,767 | Accelerating Triangle Counting on GPU | 2021 | SIGMOD | 7.1923965e-05 |
| 4,101 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD | 6.9638989e-05 |
| 4,289 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB | 6.8514818e-05 |
| 1,218 | Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture | 2021 | VLDB | 0.00011709086 |
| 4,178 | Realtime Top-k Personalized PageRank over Large Graphs on GPUs | 2020 | VLDB | 6.914103e-05 |