Scaling your Hybrid CPU-GPU DBMS to Multiple GPUs

Summary: Lancelot combines CPU execution with multiple GPUs to overcome GPU-memory limits. Its cache-aware replication jointly optimizes caching, replication, and shuffle costs, while distributed hybrid execution delivers up to 2×–12× speedups over GPU DBMSs. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: hada67417352dad4e
Venue: VLDB
Year: 2024
Pagerank: 5.3710413e-05
Overall Rank: 8,236 | 44.63%
DOI: 10.14778/3704965.3704977

Incoming Non-self Citations Over Time

Authors

1. Bobbi Yogatama (University of Wisconsin)
2. Weiwei Gong (Oracle)
3. Xiangyao Yu (University of Wisconsin)

BibTeX Citation

@article{yogatama_vldb24,
        title = {{Scaling your Hybrid CPU-GPU DBMS to Multiple GPUs}},
        author = {Yogatama, Bobbi and Gong, Weiwei and Yu, Xiangyao},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {13},
        pages = {4709--4722},
        doi = {10.14778/3704965.3704977},
        url = {https://doi.org/10.14778/3704965.3704977},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
5,991	Terabyte-Scale Analytics in the Blink of an Eye	2026	VLDB	5.9247663e-05
8,274	Scaling GPU-Accelerated Databases beyond GPU Memory Size	2025	VLDB	5.3642256e-05
9,047	Rethinking Analytical Processing in the GPU Era	2026	CIDR	5.2308307e-05
9,863	GPU Acceleration of SQL Analytics on Compressed Data	2026	VLDB	5.1176637e-05
10,785	MGI: A Communication Framework for Data Processing in Massive GPU Infrastructures	2026	VLDB	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 29 of 29 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
71	DuckDB: an Embeddable Analytical Database	2019	SIGMOD	0.00037720227
106	Quickly Generating Billion-Record Synthetic Databases	1994	SIGMOD	0.00033526937
616	Relational Joins on Graphics Processors	2008	SIGMOD	0.00015561564
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
1,268	A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics	2020	SIGMOD	0.0001126007
1,533	Pipelined Query Processing in Coprocessor Environments	2018	SIGMOD	0.00010332035
1,541	HippogriffDB: Balancing I/O and GPU Bandwidth in Big Data Analytics	2016	VLDB	0.00010313459
1,747	HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines	2019	VLDB	9.7335416e-05
2,122	Revisiting Co-Processing for Hash Joins on the Coupled CPU-GPU Architecture	2013	VLDB	9.0084047e-05
2,284	Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects	2020	SIGMOD	8.6954168e-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
2,600	Robust Query Processing in Co-Processor-accelerated Databases	2016	SIGMOD	8.2363864e-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
3,200	Why it is time for a HyPE: A Hybrid Query Processing Engine for Efficient GPU Coprocessing in DBMS	2013	VLDB	7.5437496e-05
3,626	Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects	2022	SIGMOD	7.1524537e-05
3,655	Tile-based Lightweight Integer Compression in GPU	2022	SIGMOD	7.1260841e-05
3,773	Hardware-conscious Query Processing in GPU-accelerated Analytical Engines	2019	CIDR	7.0294475e-05
3,888	Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS	2022	VLDB	6.945725e-05
3,961	Data-Parallel Query Processing on Non-Uniform Data	2020	VLDB	6.8948667e-05
4,199	Adaptive Work Placement for Query Processing on Heterogeneous Computing Resources	2017	VLDB	6.7410637e-05
4,480	GPU Database Systems Characterization and Optimization	2024	VLDB	6.5807917e-05
4,539	OmniDB: Towards Portable and Efficient Query Processing on Parallel CPU/GPU Architectures	2013	VLDB	6.5532239e-05
4,645	Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs	2021	VLDB	6.4881339e-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
6,489	HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics	2023	CIDR	5.7676507e-05

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#	Overall Rank	Paper	Year	Venue
1	2,886	Efficient Join Algorithms For Large Database Tables in a Multi-GPU Environment	2021	VLDB
2	1,541	HippogriffDB: Balancing I/O and GPU Bandwidth in Big Data Analytics	2016	VLDB
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4	3,200	Why it is time for a HyPE: A Hybrid Query Processing Engine for Efficient GPU Coprocessing in DBMS	2013	VLDB
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8	4,480	GPU Database Systems Characterization and Optimization	2024	VLDB
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