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: 7036
Venue: SIGMOD
Year: 2025
Pagerank: 4.6603427e-05
Overall Rank: 7,751 | 46.08%
DOI: 10.1145/3709689

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
7,568	Powerful GPUs or Fast Interconnects: Analyzing Relational Workloads on Modern GPUs	2025	VLDB	4.7084322e-05
7,916	Terabyte-Scale Analytics in the Blink of an Eye	2026	VLDB	4.6173899e-05
9,838	Efficiently Joining Large Relations on Multi-GPU Systems	2025	VLDB	4.2740344e-05
9,970	Rethinking Analytical Processing in the GPU Era	2026	CIDR	4.1945683e-05
10,084	GraphMatch: Subgraph Query Processing on Steroids	2026	SIGMOD	4.1945683e-05
10,121	TQEx: Tensor-based Query Engine Enhanced by Bridging the Gap	2026	SIGMOD	4.1945683e-05
10,281	GPU Acceleration of SQL Analytics on Compressed Data	2026	VLDB	4.1945683e-05

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
81	Cache Conscious Algorithms for Relational Query Processing	1994	VLDB	0.00055548574
775	Relational Joins on Graphics Processors	2008	SIGMOD	0.00016823862
1,273	The Yin and Yang of Processing Data Warehousing Queries on GPU Devices	2013	VLDB	0.00012912938
2,040	A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics	2020	SIGMOD	9.7057698e-05
2,067	HippogriffDB: Balancing I/O and GPU Bandwidth in Big Data Analytics	2016	VLDB	9.6392739e-05
2,287	Pipelined Query Processing in Coprocessor Environments	2018	SIGMOD	9.0972606e-05
2,519	Revisiting Co-Processing for Hash Joins on the Coupled CPU-GPU Architecture	2013	VLDB	8.6078505e-05
2,528	Velox: Meta’s Unified Execution Engine	2022	VLDB	8.59454e-05
2,651	HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines	2019	VLDB	8.3694317e-05
3,254	Query Processing on Tensor Computation Runtimes	2022	VLDB	7.3161051e-05
3,327	Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects	2020	SIGMOD	7.2205738e-05
3,465	GPL: A GPU-based Pipelined Query Processing Engine	2016	SIGMOD	7.0695873e-05
3,721	To Partition, or Not to Partition, That is the Join Question in a Real System	2021	SIGMOD	6.8179379e-05
3,898	Efficient Join Algorithms For Large Database Tables in a Multi-GPU Environment	2021	VLDB	6.6551268e-05
4,002	MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures	2021	SIGMOD	6.545665e-05
5,019	Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS	2022	VLDB	5.7559197e-05
5,088	TCUDB: Accelerating Database with Tensor Processors	2022	SIGMOD	5.7072189e-05
5,125	The Art of Balance: A RateupDBTM Experience of Building a CPU/GPU Hybrid Database Product	2021	VLDB	5.679423e-05
5,247	Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects	2022	SIGMOD	5.6057839e-05
6,066	GPU Database Systems Characterization and Optimization	2024	VLDB	5.2290447e-05
6,223	Distributed GPU Joins on Fast RDMA-capable Networks	2023	SIGMOD	5.1496398e-05
6,496	GOLAP: A GPU-in-Data-Path Architecture for High-Speed OLAP	2024	SIGMOD	5.0413077e-05
8,616	A Case for Graphics-driven Query Processing	2023	VLDB	4.4846474e-05

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8,680	A Practical Approach to Groupjoin and Nested Aggregates	2021	VLDB	4.4694927e-05
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2,519	Revisiting Co-Processing for Hash Joins on the Coupled CPU-GPU Architecture	2013	VLDB	8.6078505e-05
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