Parallel Wavelet Tree Construction

TL;DR

This paper introduces parallel algorithms for wavelet tree construction that significantly reduce depth and improve speed over previous methods, demonstrating strong scalability and practical performance on multi-core systems.

Contribution

The paper presents the first parallel algorithms for wavelet tree construction with polylogarithmic depth, outperforming existing approaches in speed and scalability.

Findings

Achieved up to 27x speedup over sequential algorithms.

Outperformed previous parallel algorithms by 1.3--5.6x on a 40-core machine.

Algorithms scale well with input size, thread count, and alphabet size.

Abstract

We present parallel algorithms for wavelet tree construction with polylogarithmic depth, improving upon the linear depth of the recent parallel algorithms by Fuentes-Sepulveda et al. We experimentally show on a 40-core machine with two-way hyper-threading that we outperform the existing parallel algorithms by 1.3--5.6x and achieve up to 27x speedup over the sequential algorithm on a variety of real-world and artificial inputs. Our algorithms show good scalability with increasing thread count, input size and alphabet size. We also discuss extensions to variants of the standard wavelet tree.