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Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS
Summary: Semantic-aware, fine-grained caching guides CPU-GPU data placement by workload semantics, data correlations, and query frequency. Heterogeneous executor coordinates CPU-GPU execution in Mordred; on Star Schema Benchmark, it beats traditional caching by up to 3x and GPU DBMSs by an order of magnitude.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 12740
- Venue
- VLDB
- Year
- 2022
- Pagerank
- 5.7559197e-05
- Overall Rank
- 5,019 | 65.09%
- DOI
-
10.14778/3551793.3551809
Incoming Non-self Citations Over Time
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GOLAP: A GPU-in-Data-Path Architecture for High-Speed OLAP |
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BOSS - An Architecture for Database Kernel Composition |
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4.7610909e-05 |
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Workload Placement on Heterogeneous CPU-GPU Systems |
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Flux: Unifying Heterogeneous Infrastructure for Alibaba AnalyticDB |
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| 11,020 |
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Outgoing Citations (Sorted by Pagerank)
Showing 24 of 24 cited papers.
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| 35 |
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2005 |
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| 145 |
Quickly Generating Billion-Record Synthetic Databases |
1994 |
SIGMOD |
0.0004138408 |
| 239 |
GPUTeraSort: High Performance Graphics Co-processor Sorting for Large Database Management |
2006 |
SIGMOD |
0.00031617428 |
| 775 |
Relational Joins on Graphics Processors |
2008 |
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0.00016823862 |
| 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 |
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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 |
| 2,330 |
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 |
| 2,651 |
HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines |
2019 |
VLDB |
8.3694317e-05 |
| 3,151 |
A Memory Bandwidth-Efficient Hybrid Radix Sort on GPUs |
2017 |
SIGMOD |
7.4720668e-05 |
| 3,305 |
Robust Query Processing in Co-Processor-accelerated Databases |
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7.2460965e-05 |
| 3,327 |
Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects |
2020 |
SIGMOD |
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| 3,696 |
Why it is time for a HyPE: A Hybrid Query Processing Engine for Efficient GPU Coprocessing in DBMS |
2013 |
VLDB |
6.834483e-05 |
| 3,898 |
Efficient Join Algorithms For Large Database Tables in a Multi-GPU Environment |
2021 |
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6.6551268e-05 |
| 4,002 |
MG-Join: A Scalable Join for Massively Parallel Multi-GPU Architectures |
2021 |
SIGMOD |
6.545665e-05 |
| 4,085 |
In-Cache Query Co-Processing on Coupled CPU-GPU Architectures |
2015 |
VLDB |
6.4620277e-05 |
| 4,363 |
Hardware-conscious Query Processing in GPU-accelerated Analytical Engines |
2019 |
CIDR |
6.2552614e-05 |
| 4,678 |
OmniDB: Towards Portable and Efficient Query Processing on Parallel CPU/GPU Architectures |
2013 |
VLDB |
6.0046271e-05 |
| 4,999 |
Adaptive Work Placement for Query Processing on Heterogeneous Computing Resources |
2017 |
VLDB |
5.7752801e-05 |
| 5,578 |
Ocelot/HyPE: Optimized Data Processing on Heterogeneous Hardware |
2014 |
VLDB |
5.4252837e-05 |
| 5,814 |
Towards a Hybrid Design for Fast Query Processing in DB2 with BLU Acceleration Using Graphical Processing Units: A Technology Demonstration |
2016 |
SIGMOD |
5.3167137e-05 |
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