Abstract
Due to their high computational power and internal memory bandwidth, graphic processing units (GPUs) have been extensively studied by the database systems research community. A heterogeneous query processing system that employs CPUs and GPUs at the same time has to solve many challenges, including how to distribute the workload on processors with different capabilities; how to overcome the data transfer bottleneck; and how to support implementations for multiple processors efficiently. In this survey we devise a classification scheme to categorize techniques developed to address these challenges. Based on this scheme, we categorize query processing systems on heterogeneous CPU/GPU systems and identify open research problems.
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