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Themis: A GPU-accelerated Relational Query Execution Engine

Summary: Themis is a GPU relational engine addressing intra- and inter-warp imbalance from skewed, varying-cardinality pipelines. It redistributes tuples within and across warps using adaptive workload estimates, achieving up to 379× gains on skewed TPC-H. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
hc27442970ea8d016
Venue
VLDB
Year
2025
Pagerank
5.2142646e-05
Overall Rank
9,061 | 39.27%
DOI
10.14778/3705829.3705856
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{hong_vldb25,
        title = {{Themis: A GPU-accelerated Relational Query Execution Engine}},
        author = {Hong, Kijae and Kim, Kyoungmin and Lee, Young-Koo and Moon, Yang-Sae and Bhowmick, Sourav S and Han, Wook-Shin},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {2},
        pages = {426--438},
        doi = {10.14778/3705829.3705856},
        url = {https://doi.org/10.14778/3705829.3705856},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
215 Morsel-Driven Parallelism: A NUMA-Aware Query Evaluation Framework for the Many-Core Age 2014 SIGMOD 0.00024554257
610 Relational Joins on Graphics Processors 2008 SIGMOD 0.00015540189
1,228 A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics 2020 SIGMOD 0.00011425748
1,475 Voodoo - A Vector Algebra for Portable Database Performance on Modern Hardware 2016 VLDB 0.00010525713
1,530 Pipelined Query Processing in Coprocessor Environments 2018 SIGMOD 0.00010318943
1,609 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 0.0001007196
1,748 HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines 2019 VLDB 9.7176232e-05
2,478 GPU-Accelerated Subgraph Enumeration on Partitioned Graphs 2020 SIGMOD 8.3890338e-05
2,808 GPL: A GPU-based Pipelined Query Processing Engine 2016 SIGMOD 7.962315e-05
3,657 Realtime Top-k Personalized PageRank over Large Graphs on GPUs 2020 VLDB 7.1105244e-05
3,968 Data-Parallel Query Processing on Non-Uniform Data 2020 VLDB 6.8770248e-05
4,164 GPU Database Systems Characterization and Optimization 2024 VLDB 6.7560016e-05
4,650 Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs 2021 VLDB 6.471543e-05
8,872 SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms 2023 VLDB 5.2459616e-05
8,873 Workload-driven, Lazy Discovery of Data Dependencies for Query Optimization 2022 CIDR 5.2459234e-05
9,871 Cost-efficiency and Performance Robustness in Serverless Data Exchange 2022 SIGMOD 5.1053749e-05
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