Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS
Summary: Semantic-aware, fine-grained caching guides CPU-GPU data placement by workload semantics, data correlations, and query frequency. Heterogeneous executor coordinates CPU-GPU execution in Mordred; on Star Schema Benchmark, it beats traditional caching by up to 3x and GPU DBMSs by an order of magnitude. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Bobbi W. Yogatama (University of Wisconsin)
- 2. Weiwei Gong (Oracle)
- 3. Xiangyao Yu (University of Wisconsin)
BibTeX Citation
@article{yogatama_vldb22,
title = {{Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS}},
author = {Yogatama, Bobbi W. and Gong, Weiwei and Yu, Xiangyao},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {11},
pages = {2491--2503},
doi = {10.14778/3551793.3551809},
url = {https://doi.org/10.14778/3551793.3551809},
year = {2022}
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