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Scaling GPU-Accelerated Databases beyond GPU Memory Size

Summary: Hybrid CPU–GPU query processing scales beyond GPU memory: CPU-side filtering minimizes PCIe transfers, while GPUs execute joins and other compute-intensive operators. Handles 1TB TPC-H (SF1000) on one 80GB A100, outperforming CPU-only systems in speed and cost. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
ha338bd3b5ad00f7e
Venue
VLDB
Year
2025
Pagerank
5.3642256e-05
Overall Rank
8,274 | 44.38%
DOI
10.14778/3749646.3749710

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{li_vldb25,
        title = {{Scaling GPU-Accelerated Databases beyond GPU Memory Size}},
        author = {Li, Yinan and Ding, Bailu and Wei, Ziyun and Maas, Lukas M. and Al-Ghosien, Momin and Blanas, Spyros and Bruno, Nicolas and Curino, Carlo and Interlandi, Matteo and Peeper, Craig and Rajan, Kaushik and Chaudhuri, Surajit and Gehrke, Johannes},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {11},
        pages = {4518--4531},
        doi = {10.14778/3749646.3749710},
        url = {https://doi.org/10.14778/3749646.3749710},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 40 of 40 cited papers.

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

Rank Cited Paper Year Venue Pagerank
12 C-Store: A Column-oriented DBMS 2005 VLDB 0.00068998927
61 Integrating Compression and Execution in Column-Oriented Database Systems 2006 SIGMOD 0.000392237
219 SIMD-Scan: Ultra Fast in-Memory Table Scan using on-Chip Vector Processing Units 2009 VLDB 0.00024363532
249 A Performance Evaluation of Four Parallel Join Algorithms in a Shared-Nothing Multiprocessor Environment 1989 SIGMOD 0.00023175253
287 Implementing Database Operations Using SIMD Instructions 2002 SIGMOD 0.00021970198
352 On the Power of Magic 1987 PODS 0.00020223279
616 Relational Joins on Graphics Processors 2008 SIGMOD 0.00015561564
627 Rethinking SIMD Vectorization for In-Memory Databases 2015 SIGMOD 0.00015460957
771 The Yin and Yang of Processing Data Warehousing Queries on GPU Devices 2013 VLDB 0.00014085862
856 Hardware-Oblivious Parallelism for In-Memory Column-Stores 2013 VLDB 0.00013428547
873 BitWeaving: Fast Scans for Main Memory Data Processing 2013 SIGMOD 0.00013338838
1,268 A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics 2020 SIGMOD 0.0001126007
1,459 Row-wise Parallel Predicate Evaluation 2008 VLDB 0.00010585108
1,473 Voodoo - A Vector Algebra for Portable Database Performance on Modern Hardware 2016 VLDB 0.00010557973
1,533 Pipelined Query Processing in Coprocessor Environments 2018 SIGMOD 0.00010332035
1,723 ByteSlice: Pushing the Envelop of Main Memory Data Processing with a New Storage Layout 2015 SIGMOD 9.7931223e-05
1,747 HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines 2019 VLDB 9.7335416e-05
2,185 Database Compression on Graphics Processors 2010 VLDB 8.8948351e-05
2,460 Query Processing on Tensor Computation Runtimes 2022 VLDB 8.4348335e-05
2,487 A Memory Bandwidth-Efficient Hybrid Radix Sort on GPUs 2017 SIGMOD 8.3979719e-05
2,886 Efficient Join Algorithms For Large Database Tables in a Multi-GPU Environment 2021 VLDB 7.9081605e-05
3,053 MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures 2021 SIGMOD 7.7019663e-05
3,181 The FastLanes Compression Layout: Decoding >100 Billion Integers per Second with Scalar Code 2023 VLDB 7.5625307e-05
3,491 In-Cache Query Co-Processing on Coupled CPU-GPU Architectures 2015 VLDB 7.2619913e-05
3,592 Looking Ahead Makes Query Plans Robust: Making the Initial Case with In-Memory Star Schema Data Warehouse Workloads 2017 VLDB 7.1835842e-05
3,655 Tile-based Lightweight Integer Compression in GPU 2022 SIGMOD 7.1260841e-05
3,888 Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS 2022 VLDB 6.945725e-05
4,369 Predicate Transfer: Efficient Pre-Filtering on Multi-Join Queries 2024 CIDR 6.6315141e-05
4,391 Bitvector-aware Query Optimization for Decision Support Queries 2020 SIGMOD 6.6214093e-05
4,480 GPU Database Systems Characterization and Optimization 2024 VLDB 6.5807917e-05
4,645 Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs 2021 VLDB 6.4881339e-05
4,786 Applying Hash Filters to Improving the Execution of Bushy Trees 1993 VLDB 6.4143659e-05
5,371 Distributed GPU Joins on Fast RDMA-capable Networks 2023 SIGMOD 6.1584802e-05
5,394 Towards a Hybrid Design for Fast Query Processing in DB2 with BLU Acceleration Using Graphical Processing Units: A Technology Demonstration 2016 SIGMOD 6.1497789e-05
6,392 Selection Pushdown in Column Stores using Bit Manipulation Instructions 2023 SIGMOD 5.800848e-05
6,561 MotherDuck: DuckDB in the cloud and in the client 2024 CIDR 5.7481696e-05
7,245 Pruning in Snowflake: Working Smarter, Not Harder 2025 SIGMOD 5.5761132e-05
8,236 Scaling your Hybrid CPU-GPU DBMS to Multiple GPUs 2024 VLDB 5.3710413e-05
8,535 New Query Optimization Techniques in the Spark Engine of Azure Synapse 2022 VLDB 5.320973e-05
10,020 Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem 2022 VLDB 5.0943606e-05
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