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GPUQP: query co-processing using graphics processors

Rui Fang, Bingsheng He, Mian Lu, Ke Yang, Naga K. Govindaraju, Qiong Luo, Pedro V. Sander
The Hong Kong University of Science and Technology
In SIGMOD ’07: Proceedings of the 2007 ACM SIGMOD international conference on Management of data (2007), pp. 1061-1063

@conference{fang2007gpuqp,

   title={GPUQP: query co-processing using graphics processors},

   author={Fang, R. and He, B. and Lu, M. and Yang, K. and Govindaraju, N.K. and Luo, Q. and Sander, P.V.},

   booktitle={Proceedings of the 2007 ACM SIGMOD international conference on Management of data},

   pages={1061–1063},

   year={2007},

   organization={ACM}

}

We present GPUQP, a relational query engine that employs both CPUs and GPUs (Graphics Processing Units) for in-memory query co-processing. GPUs are commodity processors traditionally designed for graphics applications. Recent research has shown that they can accelerate some database operations orders of magnitude over CPUs. So far, there has been little work on how GPUs can be programmed for heavy-duty database constructs, such as tree indexes and joins, and how well a full-fledged GPU query co-processor performs in comparison with their CPU counterparts. In this work, we explore the design decisions in using GPUs for query co-processing using both a graphics API and a general purpose programming model. We then demonstrate the processing flows as well as the performance results of our methods.
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