Relaxed Operator Fusion for In-Memory Databases: Making Compilation, Vectorization, and Prefetching Work Together At Last
Summary: Introduces relaxed operator fusion, strategically staging JIT-compiled plans to reconcile SIMD vectorization and software prefetching across operators. Implemented in Peloton, it accelerates cache-resident-challenging OLAP workloads up to 2.2× and outperforms HyPer and Actian Vector. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Prashanth Menon (Carnegie Mellon University)
- 2. Todd C. Mowry (Carnegie Mellon University)
- 3. Andrew Pavlo (Carnegie Mellon University)
BibTeX Citation
@article{menon_vldb18,
title = {{Relaxed Operator Fusion for In-Memory Databases: Making Compilation, Vectorization, and Prefetching Work Together At Last}},
author = {Menon, Prashanth and Mowry, Todd C. and Pavlo, Andrew},
journal = {PVLDB},
series = {{VLDB} '18},
volume = {11},
number = {1},
pages = {1--13},
doi = {10.14778/3151113.3151114},
url = {https://doi.org/10.14778/3151113.3151114},
year = {2018}
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