Efficient implementation of continuous skyline computation on a multi-core processor

The skyline operator has been proposed as a method for extracting highly-utility samples from a large database. A set of the extracted samples is called `skyline'. The theme of the MEMOCODE 2015 Design Contest is to accelerate continuous skyline computation, skyline computing for a streaming dataset, on any platform. In this paper, we present our method that achieved the best performance in the contest. We describe our data structure, algorithms, and optimization methods for the contest reference code in the multi-core processor. We have accelerated our solution in the two aspects of efficient algorithms and code optimizations. The task of the contest is to compute the skyline at each time-step for 800,000 entries with a seven-dimensional vector value and the activation time and the deactivation time. We use one commodity computer and the average runtime of our solution is 407 milliseconds.