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GPL: A GPU-based Pipelined Query Processing Engine
Summary: GPL introduces a GPU-based, pipelined query engine for in-memory OLAP. By exploiting concurrent kernel execution and inter-kernel data channels, it enables true pipelining; a cost model tunes tile size to optimize plans, delivering up to 48% speedups on TPC-H versus kernel-based approaches.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 5251
- Venue
- SIGMOD
- Year
- 2016
- Pagerank
- 7.0695873e-05
- Overall Rank
- 3,465 | 75.90%
- DOI
-
10.1145/2882903.2915224
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 19 of 19 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 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 |
| 4,363 |
Hardware-conscious Query Processing in GPU-accelerated Analytical Engines |
2019 |
CIDR |
6.2552614e-05 |
| 4,770 |
The Case For Heterogeneous HTAP |
2017 |
CIDR |
5.9338845e-05 |
| 5,088 |
TCUDB: Accelerating Database with Tensor Processors |
2022 |
SIGMOD |
5.7072189e-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 |
| 6,066 |
GPU Database Systems Characterization and Optimization |
2024 |
VLDB |
5.2290447e-05 |
| 6,282 |
Cheetah: Accelerating Database Queries with Switch Pruning |
2020 |
SIGMOD |
5.128797e-05 |
| 6,369 |
Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs |
2021 |
VLDB |
5.0936663e-05 |
| 7,209 |
GPU-accelerated data management under the test of time |
2020 |
CIDR |
4.7996023e-05 |
| 7,328 |
BOSS - An Architecture for Database Kernel Composition |
2024 |
VLDB |
4.7610909e-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 |
| 8,432 |
SPRINTER: A Fast n-ary Join Query Processing Method for Complex OLAP Queries |
2020 |
SIGMOD |
4.5153924e-05 |
| 9,204 |
Themis: A GPU-accelerated Relational Query Execution Engine |
2025 |
VLDB |
4.3737475e-05 |
| 9,944 |
Out-of-order Execution of Database Queries |
2020 |
VLDB |
4.2446672e-05 |
| 10,121 |
TQEx: Tensor-based Query Engine Enhanced by Bridging the Gap |
2026 |
SIGMOD |
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 |
| 1 |
Access Path Selection in a Relational Database Management System |
1979 |
SIGMOD |
0.0040449103 |
| 35 |
MonetDB/X100: Hyper-Pipelining Query Execution |
2005 |
CIDR |
0.00076197749 |
| 52 |
Database Architecture Optimized for the new Bottleneck: Memory Access |
1999 |
VLDB |
0.00066474881 |
| 81 |
Cache Conscious Algorithms for Relational Query Processing |
1994 |
VLDB |
0.00055548574 |
| 124 |
DBMSs On A Modern Processor: Where Does Time Go? |
1999 |
VLDB |
0.00045103515 |
| 137 |
H-Store: A High-Performance, Distributed Main Memory Transaction Processing System |
2008 |
VLDB |
0.00042342967 |
| 338 |
Data-Oriented Transaction Execution |
2010 |
VLDB |
0.00026973858 |
| 418 |
Morsel-Driven Parallelism: A NUMA-Aware Query Evaluation Framework for the Many-Core Age |
2014 |
SIGMOD |
0.00023729211 |
| 515 |
QPipe: A Simultaneously Pipelined Relational Query Engine |
2005 |
SIGMOD |
0.00021214633 |
| 775 |
Relational Joins on Graphics Processors |
2008 |
SIGMOD |
0.00016823862 |
| 958 |
Rethinking SIMD Vectorization for In-Memory Databases |
2015 |
SIGMOD |
0.00015045316 |
| 1,228 |
Toward a Progress Indicator for Database Queries |
2004 |
SIGMOD |
0.00013164884 |
| 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 |
| 1,299 |
The DataPath System: A Data-Centric Analytic Processing Engine for Large Data Warehouses |
2010 |
SIGMOD |
0.00012751522 |
| 2,165 |
Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation |
2015 |
SIGMOD |
9.389622e-05 |
| 2,330 |
Concurrent Analytical Query Processing with GPUs |
2014 |
VLDB |
9.0192228e-05 |
| 2,519 |
Revisiting Co-Processing for Hash Joins on the Coupled CPU-GPU Architecture |
2013 |
VLDB |
8.6078505e-05 |
| 2,751 |
Mega-KV: A Case for GPUs to Maximize the Throughput of In-Memory Key-Value Stores |
2015 |
VLDB |
8.1760621e-05 |
| 2,973 |
Parallel In-Situ Data Processing with Speculative Loading |
2014 |
SIGMOD |
7.7902322e-05 |
| 3,993 |
Improving Main Memory Hash Joins on Intel Xeon Phi Processors: An Experimental Approach |
2015 |
VLDB |
6.5534805e-05 |
| 4,085 |
In-Cache Query Co-Processing on Coupled CPU-GPU Architectures |
2015 |
VLDB |
6.4620277e-05 |
| 4,610 |
Deployment of Query Plans on Multicores |
2015 |
VLDB |
6.0516573e-05 |
| 4,678 |
OmniDB: Towards Portable and Efficient Query Processing on Parallel CPU/GPU Architectures |
2013 |
VLDB |
6.0046271e-05 |
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Hardware-conscious Query Processing in GPU-accelerated Analytical Engines |
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Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs |
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