Efficient GPU-based skyline computation

Abstract

The skyline operator for multi-criteria search returns the most interesting points of a data set with respect to any monotone preference function. Existing work has almost exclusively focused on efficiently computing skylines on one or more CPUs, ignoring the high parallelism possible in GPUs. In this paper we investigate the challenges for efficient skyline algorithms that exploit the computational power of the GPU. We present a novel strategy for managing data transfer and memory for skylines using CPU and GPU. Our new sorting based data-parallel skyline algorithm is introduced and its properties are discussed. We demonstrate in a thorough experimental evaluation that this algorithm is faster than state-of-the-art sequential sorting based skyline algorithms and that it shows superior scalability.