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

Summary: JIT-based GPU query processing suffers from divergent execution and contention; Pyper adds Shuffle and Segment to curb divergence. Cost-based insertion locates Shuffle/Segment to boost GPU utilization, yielding gains on TPC-H/SSB vs top GPUs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12384
Venue
VLDB
Year
2021
Pagerank
5.0887599e-05
Overall Rank
6,367 | 55.75%
DOI
10.14778/3425879.3425890

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 11 of 11 citing papers.

Rank Citing Paper Year Venue Pagerank
3,260 Query Processing on Tensor Computation Runtimes 2022 VLDB 7.3091312e-05
4,000 MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures 2021 SIGMOD 6.5419402e-05
4,500 GaccO - A GPU-accelerated OLTP DBMS 2022 SIGMOD 6.1326735e-05
5,129 The Art of Balance: A RateupDBTM Experience of Building a CPU/GPU Hybrid Database Product 2021 VLDB 5.6724875e-05
6,068 GPU Database Systems Characterization and Optimization 2024 VLDB 5.2240241e-05
8,846 Scaling your Hybrid CPU-GPU DBMS to Multiple GPUs 2024 VLDB 4.432948e-05
9,206 Themis: A GPU-accelerated Relational Query Execution Engine 2025 VLDB 4.3695556e-05
9,331 BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach 2023 SIGMOD 4.351469e-05
10,523 cuMatch: A GPU-based Memory-Efficient Worst-case Optimal Join Processing Method for Subgraph Queries with Complex Patterns 2025 SIGMOD 4.1905499e-05
10,755 Scaling GPU-Accelerated Databases beyond GPU Memory Size 2025 VLDB 4.1905499e-05
11,023 Accelerating Merkle Patricia Trie with GPU 2024 VLDB 4.1905499e-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
59 Efficiently Compiling Efficient Query Plans for Modern Hardware 2011 VLDB 0.0006445664
1,271 The Yin and Yang of Processing Data Warehousing Queries on GPU Devices 2013 VLDB 0.00012900735
1,285 Hardware-Oblivious Parallelism for In-Memory Column-Stores 2013 VLDB 0.00012809552
1,865 Relaxed Operator Fusion for In-Memory Databases: Making Compilation, Vectorization, and Prefetching Work Together At Last 2018 VLDB 0.00010271333
2,019 Voodoo - A Vector Algebra for Portable Database Performance on Modern Hardware 2016 VLDB 9.7814175e-05
2,044 A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics 2020 SIGMOD 9.6963999e-05
2,167 Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation 2015 SIGMOD 9.3879598e-05
2,292 Pipelined Query Processing in Coprocessor Environments 2018 SIGMOD 9.0884645e-05
2,523 Revisiting Co-Processing for Hash Joins on the Coupled CPU-GPU Architecture 2013 VLDB 8.599693e-05
2,659 HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines 2019 VLDB 8.3615158e-05
3,328 Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects 2020 SIGMOD 7.2136181e-05
3,471 GPL: A GPU-based Pipelined Query Processing Engine 2016 SIGMOD 7.0628019e-05
4,089 In-Cache Query Co-Processing on Coupled CPU-GPU Architectures 2015 VLDB 6.4559891e-05
4,359 Hardware-conscious Query Processing in GPU-accelerated Analytical Engines 2019 CIDR 6.2493951e-05
5,199 Data-Parallel Query Processing on Non-Uniform Data 2020 VLDB 5.6294232e-05
7,375 GPUQP: Query Co-Processing Using Graphics Processors 2007 SIGMOD 4.7439007e-05
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