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Author: Roman Snytsar

Affiliation: Microsoft Research, One Microsoft Way, Redmond WA 98052, U.S.A.

ISBN: 978-989-758-353-7

Keyword(s): Parallel Processing, Vectorization, Bioinformatics, FM-Index.

Abstract: Many modern sequence alignment tools implement fast string matching using the space efficient data structure called a FM-index. The succinct nature of this data structure presents unique challenges for the algorithm designers. In this paper, we explore the opportunities for parallelization of the exact and inexact matches, and present an efficient solution for the Occ portion of the algorithm that utilizes the instruction-level parallelism of the modern CPUs. Our implementation computes all eight Occ values required for the inexact match algorithm step in a single pass. We showcase the algorithm performance in a multi-core genome aligner and discuss effects of the memory prefetch.

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Paper citation in several formats:
Snytsar, R. (2019). Vectorized Character Counting for Faster Pattern Matching.In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, ISBN 978-989-758-353-7, pages 149-154. DOI: 10.5220/0007258201490154

@conference{bioinformatics19,
author={Roman Snytsar.},
title={Vectorized Character Counting for Faster Pattern Matching},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS,},
year={2019},
pages={149-154},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007258201490154},
isbn={978-989-758-353-7},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS,
TI - Vectorized Character Counting for Faster Pattern Matching
SN - 978-989-758-353-7
AU - Snytsar, R.
PY - 2019
SP - 149
EP - 154
DO - 10.5220/0007258201490154

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