Like Water and Oil: With a Proper Emulsifier, Query Compilation and Data Parallelism Will Mix Well
Summary: DogQC: a GPU-aware query compiler blending native-code generation with data-parallel execution. Lane Refill and Push-Down Parallelism mitigate divergence, preserving compiled-code bandwidth and delivering severalfold gains on GPUs. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Henning Funke
- 2. Jens Teubner
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 60 | Efficiently Compiling Efficient Query Plans for Modern Hardware | 2011 | VLDB | 0.00064439773 |
| 5,197 | Data-Parallel Query Processing on Non-Uniform Data | 2020 | VLDB | 5.6347409e-05 |
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