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Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs

Summary: Shows that JIT GPU query engines are bottlenecked less by memory stalls than by control-flow divergence and resource contention. Pyper introduces cost-based Shuffle and Segment operators to restore parallelism, outperforming existing GPU engines on TPC-H/SSB. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12571
Venue
VLDB
Year
2021
Pagerank
6.0805143e-05
Overall Rank
5,807 | 60.16%
DOI
10.14778/3425879.3425890

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{paul_vldb21,
        title = {{Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs}},
        author = {Paul, Johns and He, Bingsheng and Lu, Shengliang and Lau, Chiew Tong},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {2},
        pages = {202--214},
        doi = {10.14778/3425879.3425890},
        url = {https://doi.org/10.14778/3425879.3425890},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 11 of 11 citing papers.

Rank Citing Paper Year Venue Pagerank
2,823 Query Processing on Tensor Computation Runtimes 2022 VLDB 8.0893814e-05
3,227 MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures 2021 SIGMOD 7.6217889e-05
3,890 GaccO - A GPU-accelerated OLTP DBMS 2022 SIGMOD 7.0435206e-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
8,808 Scaling your Hybrid CPU-GPU DBMS to Multiple GPUs 2024 VLDB 5.3661351e-05
9,280 Themis: A GPU-accelerated Relational Query Execution Engine 2025 VLDB 5.2933689e-05
9,475 BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach 2023 SIGMOD 5.2634238e-05
10,787 cuMatch: A GPU-based Memory-Efficient Worst-case Optimal Join Processing Method for Subgraph Queries with Complex Patterns 2025 SIGMOD 5.093636e-05
10,985 Scaling GPU-Accelerated Databases beyond GPU Memory Size 2025 VLDB 5.093636e-05
11,231 Accelerating Merkle Patricia Trie with GPU 2024 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

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

Rank Cited Paper Year Venue Pagerank
23 Efficiently Compiling Efficient Query Plans for Modern Hardware 2011 VLDB 0.00054886415
823 The Yin and Yang of Processing Data Warehousing Queries on GPU Devices 2013 VLDB 0.00013792901
912 Hardware-Oblivious Parallelism for In-Memory Column-Stores 2013 VLDB 0.00013269804
1,379 Relaxed Operator Fusion for In-Memory Databases: Making Compilation, Vectorization, and Prefetching Work Together At Last 2018 VLDB 0.00010970894
1,466 A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics 2020 SIGMOD 0.0001068941
1,469 Voodoo - A Vector Algebra for Portable Database Performance on Modern Hardware 2016 VLDB 0.00010678751
1,503 Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation 2015 SIGMOD 0.000105564
1,574 Pipelined Query Processing in Coprocessor Environments 2018 SIGMOD 0.00010321274
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
2,848 GPL: A GPU-based Pipelined Query Processing Engine 2016 SIGMOD 8.0538815e-05
3,471 In-Cache Query Co-Processing on Coupled CPU-GPU Architectures 2015 VLDB 7.3885861e-05
3,791 Hardware-conscious Query Processing in GPU-accelerated Analytical Engines 2019 CIDR 7.1235328e-05
4,585 Data-Parallel Query Processing on Non-Uniform Data 2020 VLDB 6.6175897e-05
7,113 GPUQP: Query Co-Processing Using Graphics Processors 2007 SIGMOD 5.6985502e-05
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