EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal in GPUs
Summary: EMOGI enables out-of-memory graph traversal on GPUs by streaming directly from host memory at cache-line granularity, bypassing UVM. Coalescing external requests reduces PCIe traffic, enabling near full bandwidth and ~2.6x UVM speedup; scales with PCIe 4.0. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Seung Won Min
- 2. Vikram Sharma Mailthody
- 3. Zaid Qureshi
- 4. Jinjun Xiong
- 5. Eiman Ebrahimi
- 6. Wen-mei Hwu
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,103 | Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture | 2021 | VLDB | 0.00014025101 |
| 5,247 | Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects | 2022 | SIGMOD | 5.6057839e-05 |
| 7,091 | HongTu: Scalable Full-Graph GNN Training on Multiple GPUs | 2023 | SIGMOD | 4.8370645e-05 |
| 7,225 | Self-adaptive Graph Traversal on GPUs | 2021 | SIGMOD | 4.7956162e-05 |
| 8,157 | TOD: GPU-accelerated Outlier Detection via Tensor Operations | 2023 | VLDB | 4.5730908e-05 |
| 10,705 | Efficient Graph Data Access for Out-of-Memory GPU Streaming Graph Processing | 2025 | VLDB | 4.1945683e-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 |
|---|---|---|---|---|
| 331 | The Ubiquity of Large Graphs and Surprising Challenges of Graph Processing | 2018 | VLDB | 0.00027214222 |
| 574 | From "Think Like a Vertex" to "Think Like a Graph" | 2014 | VLDB | 0.00019883211 |
| 1,138 | Traversing Large Graphs on GPUs with Unified Memory | 2020 | VLDB | 0.00013727765 |
| 2,449 | GraphMat: High performance graph analytics made productive | 2015 | VLDB | 8.7915899e-05 |
| 4,522 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD | 6.1146374e-05 |
| 4,577 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB | 6.0709631e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,577 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB | 6.0709631e-05 |
| 10,863 | Towards Sufficient GPU-accelerated Dynamic Graph Management: Survey and Experiment | 2025 | VLDB | 4.1945683e-05 |
| 10,705 | Efficient Graph Data Access for Out-of-Memory GPU Streaming Graph Processing | 2025 | VLDB | 4.1945683e-05 |
| 5,799 | CGgraph: An Ultra-fast Graph Processing System on Modern Commodity CPU-GPU Co-processor | 2024 | VLDB | 5.3219334e-05 |
| 3,641 | GPU-Accelerated Subgraph Enumeration on Partitioned Graphs | 2020 | SIGMOD | 6.8884895e-05 |
| 1,138 | Traversing Large Graphs on GPUs with Unified Memory | 2020 | VLDB | 0.00013727765 |
| 4,968 | Efficient GPU-Accelerated Subgraph Matching | 2023 | SIGMOD | 5.7956205e-05 |
| 1,103 | Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture | 2021 | VLDB | 0.00014025101 |
| 7,225 | Self-adaptive Graph Traversal on GPUs | 2021 | SIGMOD | 4.7956162e-05 |
| 4,522 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD | 6.1146374e-05 |