Why it is time for a HyPE: A Hybrid Query Processing Engine for Efficient GPU Coprocessing in DBMS

Sebastian Bress
University of Magdeburg
The VLDB PhD workshop, 2013


   title={Why it is time for a HyPE: A Hybrid Query Processing Engine for Efficient GPU Coprocessing in DBMS},

   author={Bre{ss}, Sebastian},

   journal={Proceedings of the VLDB Endowment},





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GPU acceleration is a promising approach to speed up query processing of database systems by using low cost graphic processors as coprocessors. Two major trends have emerged in this area: (1) The development of frameworks for scheduling tasks in heterogeneous CPU/GPU platforms, which is mainly in the context of coprocessing for applications and does not consider specifics of database-query processing and optimization. (2) The acceleration of database operations using efficient GPU algorithms, which typically cannot be applied easily on other database systems, because of their analytical{algorithm-specific cost models. One major challenge is how to combine traditional database query processing with GPU coprocessing techniques and efficient database operation scheduling in a GPU-aware query optimizer. In this thesis, we develop a hybrid query processing engine, which extends the traditional physical optimization process to generate hybrid query plans and to perform a cost-based optimization in a way that the advantages of CPUs and GPUs are combined. Furthermore, we aim at a portable solution between different GPU-accelerated database management systems to maximize applicability. Preliminary results indicate great potential.
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