Evidence map›Paper›PMID 38679714›Full record

ArticleAlgorithms for molecular biology : AMB2024

Fast, parallel, and cache-friendly suffix array construction.

Jamshed Khan, Tobias Rubel, Erin Molloy, Laxman Dhulipala, Rob Patro

Abstract read
In one paragraph

Article in Algorithms for molecular biology : AMB, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jamshed KhanDepartment of Computer Science, University of Maryland, College Park, MD, 20742, USA. jamshed@cs.umd.edu.
Tobias RubelDepartment of Computer Science, University of Maryland, College Park, MD, 20742, USA.
Erin MolloyDepartment of Computer Science, University of Maryland, College Park, MD, 20742, USA.
Laxman DhulipalaDepartment of Computer Science, University of Maryland, College Park, MD, 20742, USA.
Rob PatroDepartment of Computer Science, University of Maryland, College Park, MD, 20742, USA. rob@cs.umd.edu.

Funding

A Modular Framework for Accurate, Interpretable, and Reproducible Analysis of Long Read RNA-Seq DataR01HG009937 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Michael Isaiah Love, Robert Patro · 2018 to 2026
$2.8M
NHGRI NIH HHS R01 HG009937NIH HHS R01HG009937
6 · The paper itself

Abstract

purposeString indexes such as the suffix array (SA) and the closely related longest common prefix (LCP) array are fundamental objects in bioinformatics and have a wide variety of applications. Despite their importance in practice, few scalable parallel algorithms for constructing these are known, and the existing algorithms can be highly non-trivial to implement and parallelize.

methodsIn this paper we present CAPS-SA, a simple and scalable parallel algorithm for constructing these string indexes inspired by samplesort and utilizing an LCP-informed mergesort. Due to its design, CAPS-SA has excellent memory-locality and thus incurs fewer cache misses and achieves strong performance on modern multicore systems with deep cache hierarchies.

resultsWe show that despite its simple design, CAPS-SA outperforms existing state-of-the-art parallel SA and LCP-array construction algorithms on modern hardware. Finally, motivated by applications in modern aligners where the query strings have bounded lengths, we introduce the notion of a bounded-context SA and show that CAPS-SA can easily be extended to exploit this structure to obtain further speedups. We make our code publicly available at https://github.com/jamshed/CaPS-SA .

Indexed as

Data structuresIndexingLongest common prefixParallel algorithmsSuffix array

Identifiers

PMID38679714
PMCPMC11056320

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.