SkyCell: A Space-Pruning Based Parallel Skyline Algorithm

TL;DR

SkyCell is a novel parallel skyline algorithm that uses grid-based cell domination checks and GPU acceleration to significantly outperform existing methods on large datasets.

Contribution

The paper introduces a grid-based structure for skyline computation that enables efficient parallel processing and drastically improves performance over prior algorithms.

Findings

SkyCell outperforms state-of-the-art algorithms by up to 100 times.

The grid-based approach reduces the number of domination checks needed.

GPU parallelization significantly accelerates skyline computation.

Abstract

Skyline computation is an essential database operation that has many applications in multi-criteria decision making scenarios such as recommender systems. Existing algorithms have focused on checking point domination, which lack efficiency over large datasets. We propose a grid-based structure that enables grid cell domination checks. We show that only a small constant number of cells need to be checked which is independent from the number of data points. Our structure also enables parallel processing. We thus obtain a highly efficient parallel skyline algorithm named SkyCell, taking advantage of the parallelization power of graphics processing units. Experimental results confirm the effectiveness and efficiency of SkyCell -- it outperforms state-of-the-art algorithms consistently and by up to over two orders of magnitude in the computation time.