Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs

Munro, J Ian and Wild, Sebastian ORCID: 0000-0002-6061-9177 (2018) Nearly-Optimal Mergesorts: Fast, Practical Sorting Methods That Optimally Adapt to Existing Runs. .

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Official URL: http://dx.doi.org/10.4230/lipics.esa.2018.63

Abstract

We present two stable mergesort variants, "peeksort" and "powersort", that exploit existing runs and find nearly-optimal merging orders with practically negligible overhead. Previous methods either require substantial effort for determining the merging order (Takaoka 2009; Barbay & Navarro 2013) or do not have a constant-factor optimal worst-case guarantee (Peters 2001; Auger, Nicaud & Pivoteau 2015; Buss & Knop 2018). We demonstrate that our methods are competitive in terms of running time with state-of-the-art implementations of stable sorting methods.

Item Type:	Conference or Workshop Item (Unspecified)
Uncontrolled Keywords:	cs.DS, cs.DS
Depositing User:	Symplectic Admin
Date Deposited:	21 Oct 2019 15:09
Last Modified:	19 Jan 2023 00:21
DOI:	10.4230/LIPIcs.ESA.2018.63
Open Access URL:	http://drops.dagstuhl.de/opus/volltexte/2018/9526/...
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3058941