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Pipelined Query Processing in Coprocessor Environments

Summary: Introduces a compiler strategy that fuses several operations into a single GPU kernel to exploit GPU parallelism for query processing. This fusion dramatically cuts memory traffic and kernel time, with up to 7.5x fewer memory accesses and 9.5x faster kernels than operator-at-a-time. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h1852d0d4a0abd6e4
Venue
SIGMOD
Year
2018
Pagerank
0.00010332035
Overall Rank
1,533 | 89.70%
DOI
10.1145/3183713.3183734

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{funke_sigmod18,
        title = {{Pipelined Query Processing in Coprocessor Environments}},
        author = {Funke, Henning and Breß, Sebastian and Noll, Stefan and Markl, Volker and Teubner, Jens},
        series = {{SIGMOD} '18},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3183713.3183734},
        url = {https://dl.acm.org/doi/10.1145/3183713.3183734},
        year = {2018}
}

Incoming Citations (Sorted by Pagerank)

Showing 40 of 40 citing papers.

Rank Citing Paper Year Venue Pagerank
1,268 A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics 2020 SIGMOD 0.0001126007
1,747 HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines 2019 VLDB 9.7335416e-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
3,101 On Optimizing Operator Fusion Plans for Large-Scale Machine Learning in SystemML 2018 VLDB 7.649219e-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
3,861 GaccO - A GPU-accelerated OLTP DBMS 2022 SIGMOD 6.9656048e-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
3,972 TCUDB: Accelerating Database with Tensor Processors 2022 SIGMOD 6.8881464e-05
4,137 The Art of Balance: A RateupDB Experience of Building a CPU/GPU Hybrid Database Product 2021 VLDB 6.7861661e-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
5,371 Distributed GPU Joins on Fast RDMA-capable Networks 2023 SIGMOD 6.1584802e-05
5,541 Vortex: Overcoming Memory Capacity Limitations in GPU-Accelerated Large-Scale Data Analytics 2025 VLDB 6.0902254e-05
5,615 BOSS - An Architecture for Database Kernel Composition 2024 VLDB 6.0652416e-05
6,151 Efficiently Processing Joins and Grouped Aggregations on GPUs 2025 SIGMOD 5.8697699e-05
6,489 HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics 2023 CIDR 5.7676507e-05
6,516 GPU-accelerated data management under the test of time 2020 CIDR 5.7588588e-05
6,658 A Morsel-Driven Query Execution Engine for Heterogeneous Multi-Cores 2019 VLDB 5.7182492e-05
6,667 Powerful GPUs or Fast Interconnects: Analyzing Relational Workloads on Modern GPUs 2025 VLDB 5.7152948e-05
6,924 HongTu: Scalable Full-Graph GNN Training on Multiple GPUs 2023 SIGMOD 5.6426299e-05
8,236 Scaling your Hybrid CPU-GPU DBMS to Multiple GPUs 2024 VLDB 5.3710413e-05
8,274 Scaling GPU-Accelerated Databases beyond GPU Memory Size 2025 VLDB 5.3642256e-05
8,493 SPRINTER: A Fast n-ary Join Query Processing Method for Complex OLAP Queries 2020 SIGMOD 5.3310013e-05
8,521 FuseME: Distributed Matrix Computation Engine based on Cuboid-based Fused Operator and Plan Generation 2022 SIGMOD 5.3238144e-05
8,595 A Case for Graphics-driven Query Processing 2023 VLDB 5.3062403e-05
9,392 Themis: A GPU-accelerated Relational Query Execution Engine 2025 VLDB 5.1861628e-05
9,429 Efficiently Joining Large Relations on Multi-GPU Systems 2025 VLDB 5.1786456e-05
9,656 BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach 2023 SIGMOD 5.1453267e-05
10,473 L3: A GPU-Native Co-Designed Data Format for Learned Lossless Lightweight Compression 2026 SIGMOD 4.9793485e-05
10,601 TQEx: Tensor-based Query Engine Enhanced by Bridging the Gap 2026 SIGMOD 4.9793485e-05
10,723 Scalable GPU Acceleration of Scalar Functions in Analytical Databases: Compilation, Benchmarking, and Optimization 2026 VLDB 4.9793485e-05
10,905 ZipFlow: a Compiler-based Framework to Unleash Compressed Data Movement for Modern GPUs 2026 VLDB 4.9793485e-05
10,937 RayDB: Building Databases with Ray Tracing Cores 2026 VLDB 4.9793485e-05
11,203 cuMatch: A GPU-based Memory-Efficient Worst-case Optimal Join Processing Method for Subgraph Queries with Complex Patterns 2025 SIGMOD 4.9793485e-05
11,344 Towards Designing Future-Proof Data Processing Systems 2025 VLDB 4.9793485e-05
11,567 Accelerating Merkle Patricia Trie with GPU 2024 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

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