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 |
|---|---|---|---|---|
| 1,102 | Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture | 2021 | VLDB | 0.00014011556 |
| 5,251 | Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects | 2022 | SIGMOD | 5.6003972e-05 |
| 7,087 | HongTu: Scalable Full-Graph GNN Training on Multiple GPUs | 2023 | SIGMOD | 4.8324242e-05 |
| 7,226 | Self-adaptive Graph Traversal on GPUs | 2021 | SIGMOD | 4.7910164e-05 |
| 8,161 | TOD: GPU-accelerated Outlier Detection via Tensor Operations | 2023 | VLDB | 4.5688249e-05 |
| 10,713 | Efficient Graph Data Access for Out-of-Memory GPU Streaming Graph Processing | 2025 | VLDB | 4.1905499e-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 |
|---|---|---|---|---|
| 327 | The Ubiquity of Large Graphs and Surprising Challenges of Graph Processing | 2018 | VLDB | 0.00027312381 |
| 570 | From "Think Like a Vertex" to "Think Like a Graph" | 2014 | VLDB | 0.00019895021 |
| 1,138 | Traversing Large Graphs on GPUs with Unified Memory | 2020 | VLDB | 0.00013715114 |
| 2,452 | GraphMat: High performance graph analytics made productive | 2015 | VLDB | 8.782919e-05 |
| 4,525 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD | 6.1087614e-05 |
| 4,578 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB | 6.0651154e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,578 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB | 6.0651154e-05 |
| 10,867 | Towards Sufficient GPU-accelerated Dynamic Graph Management: Survey and Experiment | 2025 | VLDB | 4.1905499e-05 |
| 10,713 | Efficient Graph Data Access for Out-of-Memory GPU Streaming Graph Processing | 2025 | VLDB | 4.1905499e-05 |
| 5,811 | CGgraph: An Ultra-fast Graph Processing System on Modern Commodity CPU-GPU Co-processor | 2024 | VLDB | 5.3168243e-05 |
| 3,488 | GPU-Accelerated Subgraph Enumeration on Partitioned Graphs | 2020 | SIGMOD | 7.0460627e-05 |
| 1,138 | Traversing Large Graphs on GPUs with Unified Memory | 2020 | VLDB | 0.00013715114 |
| 4,756 | Efficient GPU-Accelerated Subgraph Matching | 2023 | SIGMOD | 5.9364786e-05 |
| 1,102 | Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture | 2021 | VLDB | 0.00014011556 |
| 7,226 | Self-adaptive Graph Traversal on GPUs | 2021 | SIGMOD | 4.7910164e-05 |
| 4,525 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD | 6.1087614e-05 |