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GPU Database Systems Characterization and Optimization
Summary: Cross-stack microarchitectural and roofline analysis of four GPU DBs (incl. Crystal, TQP) revealing resource underutilization and query-processing bottlenecks. Introduce system and MIG-aware resource-allocation optimizations achieving 1.9× lower single-query latency and up to 6.5× concurrent throughput.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 13670
- Venue
- VLDB
- Year
- 2024
- Pagerank
- 5.2290447e-05
- Overall Rank
- 6,066 | 57.81%
- DOI
-
10.14778/3632093.3632107
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 14 of 14 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 6,453 |
Vortex: Overcoming Memory Capacity Limitations in GPU-Accelerated Large-Scale Data Analytics |
2025 |
VLDB |
5.0571108e-05 |
| 7,568 |
Powerful GPUs or Fast Interconnects: Analyzing Relational Workloads on Modern GPUs |
2025 |
VLDB |
4.7084322e-05 |
| 7,751 |
Efficiently Processing Joins and Grouped Aggregations on GPUs |
2025 |
SIGMOD |
4.6603427e-05 |
| 7,916 |
Terabyte-Scale Analytics in the Blink of an Eye |
2026 |
VLDB |
4.6173899e-05 |
| 8,118 |
Maximus: A Modular Accelerated Query Engine for Data Analytics on Heterogeneous Systems |
2025 |
SIGMOD |
4.5814829e-05 |
| 8,846 |
Scaling your Hybrid CPU-GPU DBMS to Multiple GPUs |
2024 |
VLDB |
4.4372012e-05 |
| 9,204 |
Themis: A GPU-accelerated Relational Query Execution Engine |
2025 |
VLDB |
4.3737475e-05 |
| 10,084 |
GraphMatch: Subgraph Query Processing on Steroids |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,111 |
Scalable Graph Indexing using GPUs for Approximate Nearest Neighbor Search |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,121 |
TQEx: Tensor-based Query Engine Enhanced by Bridging the Gap |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,253 |
Scalable GPU Acceleration of Scalar Functions in Analytical Databases: Compilation, Benchmarking, and Optimization |
2026 |
VLDB |
4.1945683e-05 |
| 10,281 |
GPU Acceleration of SQL Analytics on Compressed Data |
2026 |
VLDB |
4.1945683e-05 |
| 10,749 |
Scaling GPU-Accelerated Databases beyond GPU Memory Size |
2025 |
VLDB |
4.1945683e-05 |
| 10,863 |
Towards Sufficient GPU-accelerated Dynamic Graph Management: Survey and Experiment |
2025 |
VLDB |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 24 of 24 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 60 |
Efficiently Compiling Efficient Query Plans for Modern Hardware |
2011 |
VLDB |
0.00064439773 |
| 66 |
Spark SQL: Relational Data Processing in Spark |
2015 |
SIGMOD |
0.00061639801 |
| 124 |
DBMSs On A Modern Processor: Where Does Time Go? |
1999 |
VLDB |
0.00045103515 |
| 1,273 |
The Yin and Yang of Processing Data Warehousing Queries on GPU Devices |
2013 |
VLDB |
0.00012912938 |
| 1,287 |
Hardware-Oblivious Parallelism for In-Memory Column-Stores |
2013 |
VLDB |
0.00012820443 |
| 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 |
| 2,651 |
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 |
| 4,002 |
MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures |
2021 |
SIGMOD |
6.545665e-05 |
| 4,498 |
GaccO - A GPU-accelerated OLTP DBMS |
2022 |
SIGMOD |
6.138538e-05 |
| 5,019 |
Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS |
2022 |
VLDB |
5.7559197e-05 |
| 5,040 |
Tile-based Lightweight Integer Compression in GPU |
2022 |
SIGMOD |
5.7425187e-05 |
| 5,197 |
Data-Parallel Query Processing on Non-Uniform Data |
2020 |
VLDB |
5.6347409e-05 |
| 5,247 |
Triton Join: Efficiently Scaling to a Large Join State on GPUs with Fast Interconnects |
2022 |
SIGMOD |
5.6057839e-05 |
| 6,327 |
The Tensor Data Platform: Towards an AI-centric Database System |
2023 |
CIDR |
5.1083405e-05 |
| 6,369 |
Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs |
2021 |
VLDB |
5.0936663e-05 |
| 6,951 |
A GPU-friendly Geometric Data Model and Algebra for Spatial Queries |
2020 |
SIGMOD |
4.8892276e-05 |
| 7,155 |
Evaluating Multi-GPU Sorting with Modern Interconnects |
2022 |
SIGMOD |
4.8149812e-05 |
| 8,096 |
Micro-architectural Analysis of OLAP: Limitations and Opportunities |
2020 |
VLDB |
4.5860565e-05 |
| 9,695 |
Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem |
2022 |
VLDB |
4.3025567e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 7,209 |
GPU-accelerated data management under the test of time |
2020 |
CIDR |
4.7996023e-05 |
| 1,686 |
Fast Computation of Database Operations using Graphics Processors |
2004 |
SIGMOD |
0.00010917794 |
| 7,916 |
Terabyte-Scale Analytics in the Blink of an Eye |
2026 |
VLDB |
4.6173899e-05 |
| 7,377 |
GPUQP: Query Co-Processing Using Graphics Processors |
2007 |
SIGMOD |
4.7484565e-05 |
| 8,616 |
A Case for Graphics-driven Query Processing |
2023 |
VLDB |
4.4846474e-05 |
| 7,751 |
Efficiently Processing Joins and Grouped Aggregations on GPUs |
2025 |
SIGMOD |
4.6603427e-05 |
| 10,749 |
Scaling GPU-Accelerated Databases beyond GPU Memory Size |
2025 |
VLDB |
4.1945683e-05 |
| 3,305 |
Robust Query Processing in Co-Processor-accelerated Databases |
2016 |
SIGMOD |
7.2460965e-05 |
| 2,330 |
Concurrent Analytical Query Processing with GPUs |
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VLDB |
9.0192228e-05 |
| 2,040 |
A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics |
2020 |
SIGMOD |
9.7057698e-05 |