GPU Database Systems Characterization and Optimization
Summary: Cross-stack characterization of four GPU database systems exposes microarchitectural bottlenecks and resource underutilization via roofline analysis. Implementation tuning and MIG-aware resource allocation reduce latency 1.9× and improve concurrent throughput up to 6.5×. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiashen Cao (Georgia Institute of Technology)
- 2. Rathijit Sen (Microsoft)
- 3. Matteo Interlandi (Microsoft)
- 4. Joy Arulraj (Georgia Institute of Technology)
- 5. Hyesoon Kim (Georgia Institute of Technology)
BibTeX Citation
@article{cao_vldb24,
title = {{GPU Database Systems Characterization and Optimization}},
author = {Cao, Jiashen and Sen, Rathijit and Interlandi, Matteo and Arulraj, Joy and Kim, Hyesoon},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {3},
pages = {441--454},
doi = {10.14778/3632093.3632107},
url = {https://doi.org/10.14778/3632093.3632107},
year = {2024}
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