VSkyline: vectorization for efficient skyline computation

Sung-Ryoung Cho, Jongwuk Lee, Seung-won Hwang, Hwansoo Han, Sang-Won Lee

Abstract: A dominance test, which decides the dominance relationship between tuples, is a core operation in skyline computation. Optimizing dominance tests can thus improve the performance of all existing skyline algorithms. Towards this goal, this paper proposes a vectorization of dominance tests in SIMD architectures. Specifically, our vectorization can perform the dominance test of multiple consecutive dimensions in parallel, thereby achieving a speedup of SIMD parallelism degree in theory. However, achieving such performance gain is non-trivial due to complex control dependencies within the dominance test. To address this problem, we devise an efficient vectorization, called VSkyline, which performs the dominance test with SIMD instructions by determining incomparability in a block of four dimensional values. Experimental results using a performance monitor show that VSkyline considerably reduces the numbers of both executed instructions and branch mispredictions.