Efficiently Processing Joins and Grouped Aggregations on GPUs
Summary: Revisits GPU join and group-by; GFTR reduces random accesses, up to 2.3x. Optimizes hash- and sort-based group-by (19.4x, 1.7x); adds partition-based group-by for high cardinalities, with cost models and heuristics to guide optimizers. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Bowen Wu (ETH Zurich)
- 2. Dimitrios Koutsoukos (Apple; ETH Zurich)
- 3. Gustavo Alonso (ETH Zurich)
BibTeX Citation
@inproceedings{wu_sigmod25,
title = {{Efficiently Processing Joins and Grouped Aggregations on GPUs}},
author = {Wu, Bowen and Koutsoukos, Dimitrios and Alonso, Gustavo},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3709689},
url = {https://dl.acm.org/doi/10.1145/3709689},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,432 | Powerful GPUs or Fast Interconnects: Analyzing Relational Workloads on Modern GPUs | 2025 | VLDB | 5.6199783e-05 |
| 7,959 | Terabyte-Scale Analytics in the Blink of an Eye | 2026 | VLDB | 5.5181056e-05 |
| 9,333 | Efficiently Joining Large Relations on Multi-GPU Systems | 2025 | VLDB | 5.2887551e-05 |
| 10,118 | Rethinking Analytical Processing in the GPU Era | 2026 | CIDR | 5.093636e-05 |
| 10,375 | GraphMatch: Subgraph Query Processing on Steroids | 2026 | SIGMOD | 5.093636e-05 |
| 10,409 | TQEx: Tensor-based Query Engine Enhanced by Bridging the Gap | 2026 | SIGMOD | 5.093636e-05 |
| 10,580 | GPU Acceleration of SQL Analytics on Compressed Data | 2026 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 23 of 23 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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