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The Design and Implementation of CoGaDB: A Column-oriented GPU-accelerated DBMS

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Abstract

Nowadays, the performance of processors is primarily bound by a fixed energy budget, the power wall. This forces hardware vendors to optimize processors for specific tasks, which leads to an increasingly heterogeneous hardware landscape. Although efficient algorithms for modern processors such as GPUs are heavily investigated, we also need to prepare the database optimizer to handle computations on heterogeneous processors. GPUs are an interesting base for case studies, because they already offer many difficulties we will face tomorrow.

In this paper, we present CoGaDB, a main-memory DBMS with built-in GPU acceleration, which is optimized for OLAP workloads. CoGaDB uses the self-tuning optimizer framework HyPE to build a hardware-oblivious optimizer, which learns cost models for database operators and efficiently distributes a workload on available processors. Furthermore, CoGaDB implements efficient algorithms on CPU and GPU and efficiently supports star joins. We show in this paper, how these novel techniques interact with each other in a single system. Our evaluation shows that CoGaDB quickly adapts to the underlying hardware by increasing the accuracy of its cost models at runtime.

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Notes

  1. http://wwwiti.cs.uni-magdeburg.de/iti_db/research/gpu/cogadb/

  2. Many main-memory OLTP systems use a row-oriented data layout.

  3. We are aware of Accelerated Processing Units (APUs) from AMD, which integrate a CPU and a GPU on a single chip. However, APUs increase only the raw processing power of the machine, not memory bandwidth.

  4. https://www.threadingbuildingblocks.org.

  5. http://thrust.github.io.

  6. Hyper-threading was enabled during our experiments.

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Acknowledgement

We thank Jens Teubner from TU Dortmund University and Theo Härder from University of Kaiserslautern for their helpful feedback.

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Authors and Affiliations

  1. TU Dortmund University, 44227, Dortmund, Germany

    Sebastian Breß

  2. University of Magdeburg, 39106, Magdeburg, Germany

    Sebastian Breß

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  1. Sebastian Breß
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Correspondence to Sebastian Breß.

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Breß, S. The Design and Implementation of CoGaDB: A Column-oriented GPU-accelerated DBMS. Datenbank Spektrum 14, 199–209 (2014). https://doi.org/10.1007/s13222-014-0164-z

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