English

A Hybrid Vectorized Merge Sort on ARM NEON

Distributed, Parallel, and Cluster Computing 2024-09-09 v1 Data Structures and Algorithms

Abstract

Sorting algorithms are the most extensively researched topics in computer science and serve for numerous practical applications. Although various sorts have been proposed for efficiency, different architectures offer distinct flavors to the implementation of parallel sorting. In this paper, we propose a hybrid vectorized merge sort on ARM NEON, named NEON Merge Sort for short (NEON-MS). In detail, according to the granted register functions, we first identify the optimal register number to avoid the register-to-memory access, due to the write-back of intermediate outcomes. More importantly, following the generic merge sort framework that primarily uses sorting network for column sort and merging networks for three types of vectorized merge, we further improve their structures for high efficiency in an unified asymmetry way: 1) it makes the optimal sorting networks with few comparators become possible; 2) hybrid implementation of both serial and vectorized merges incurs the pipeline with merge instructions highly interleaved. Experiments on a single FT2000+ core show that NEON-MS is 3.8 and 2.1 times faster than std::sort and boost::block\_sort, respectively, on average. Additionally, as compared to the parallel version of the latter, NEON-MS gains an average speedup of 1.25.

Keywords

Cite

@article{arxiv.2409.03970,
  title  = {A Hybrid Vectorized Merge Sort on ARM NEON},
  author = {Jincheng Zhou and Jin Zhang and Xiang Zhang and Tiaojie Xiao and Di Ma and Chunye Gong},
  journal= {arXiv preprint arXiv:2409.03970},
  year   = {2024}
}

Comments

Accepted by ICA3PP

R2 v1 2026-06-28T18:36:01.536Z