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Efficiently Processing Joins and Grouped Aggregations on GPUs

Summary: Revisits GPU join and group-by; GFTR reduces random accesses, up to 2.3x. Optimizes hash- and sort-based group-by (19.4x, 1.7x); adds partition-based group-by for high cardinalities, with cost models and heuristics to guide optimizers. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7098
Venue
SIGMOD
Year
2025
Pagerank
5.5900315e-05
Overall Rank
7,591 | 47.92%
DOI
10.1145/3709689

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{wu_sigmod25,
        title = {{Efficiently Processing Joins and Grouped Aggregations on GPUs}},
        author = {Wu, Bowen and Koutsoukos, Dimitrios and Alonso, Gustavo},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3709689},
        url = {https://dl.acm.org/doi/10.1145/3709689},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 23 of 23 cited papers.

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

Rank Cited Paper Year Venue Pagerank
74 Cache Conscious Algorithms for Relational Query Processing 1994 VLDB 0.00037330605
631 Relational Joins on Graphics Processors 2008 SIGMOD 0.00015591241
823 The Yin and Yang of Processing Data Warehousing Queries on GPU Devices 2013 VLDB 0.00013792901
1,466 A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics 2020 SIGMOD 0.0001068941
1,574 Pipelined Query Processing in Coprocessor Environments 2018 SIGMOD 0.00010321274
1,666 HippogriffDB: Balancing I/O and GPU Bandwidth in Big Data Analytics 2016 VLDB 0.00010068964
1,757 Velox: Meta's Unified Execution Engine 2022 VLDB 9.8166984e-05
1,977 HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines 2019 VLDB 9.3641101e-05
2,140 Revisiting Co-Processing for Hash Joins on the Coupled CPU-GPU Architecture 2013 VLDB 9.0991487e-05
2,566 Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects 2020 SIGMOD 8.4116562e-05
2,823 Query Processing on Tensor Computation Runtimes 2022 VLDB 8.0893814e-05
2,848 GPL: A GPU-based Pipelined Query Processing Engine 2016 SIGMOD 8.0538815e-05
2,962 To Partition, or Not to Partition, That is the Join Question in a Real System 2021 SIGMOD 7.9170451e-05
3,134 Efficient Join Algorithms For Large Database Tables in a Multi-GPU Environment 2021 VLDB 7.7231028e-05
3,227 MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures 2021 SIGMOD 7.6217889e-05
4,089 TCUDB: Accelerating Database with Tensor Processors 2022 SIGMOD 6.9096857e-05
4,243 Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS 2022 VLDB 6.8073248e-05
4,535 Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects 2022 SIGMOD 6.6419266e-05
4,603 The Art of Balance: A RateupDB Experience of Building a CPU/GPU Hybrid Database Product 2021 VLDB 6.6105578e-05
5,422 GPU Database Systems Characterization and Optimization 2024 VLDB 6.2245373e-05
5,587 Distributed GPU Joins on Fast RDMA-capable Networks 2023 SIGMOD 6.1596139e-05
5,778 GOLAP: A GPU-in-Data-Path Architecture for High-Speed OLAP 2024 SIGMOD 6.0918646e-05
8,487 A Case for Graphics-driven Query Processing 2023 VLDB 5.4153858e-05
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