SeqMatcher: efficient genome sequence matching with AVX-512 extensions

Abstract The recent emergence of long-read sequencing technologies has enabled substantial improvements in accuracy and reduced computational costs. Nonetheless, pairwise sequence alignment remains a time-consuming step in common bioinformatics pipelines, becoming a bottleneck in de novo whole-genome assembly. Speeding up this step requires heuristics and the development of memory-frugal and efficient implementations. A promising candidate for all of the above is Myers’ algorithm. However, the state-of-the-art implementations face scalability challenges when dealing with longer reads and large datasets. To address these challenges, we propose SeqMatcher , a fast and memory-frugal genomics sequence aligner. By leveraging the long registers of AVX-512, SeqMatcher reduces the data movement and memory footprint. In a comprehensive performance evaluation, SeqMatcher achieves speedups of up to 12.32x for the unbanded version and 26.70x for the banded version compared to the non-vectorized implementation, along with energy footprint reductions of up to 2.59x. It also outperforms state-of-the-art implementations by factors of up to 29.21x, 17.56x, 13.47x, 9.12x, and 8.81x compared to Edlib , WFA2-lib , SeqAn , BSAlign , and QuickEd , while improving energy consumption with reductions of up to 6.78x.

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Publication Details

Journal
The Journal of Supercomputing
Published
2024-12-31
DOI
https://doi.org/10.1007/s11227-024-06789-0
Citations
2
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.47

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article

SeqMatcher: efficient genome sequence matching with AVX-512 extensions

Ricardo Quislant, Elena Espinosa, Óscar Plata, Rafael Larrosa Jiménez
2 citations
The Journal of Supercomputing
Genomics and Phylogenetic Studies
0.47
article

SeqMatcher: efficient genome sequence matching with AVX-512 extensions

Ricardo Quislant, Elena Espinosa, Óscar Plata, Rafael Larrosa Jiménez
article en
2 citations

Abstract

Abstract The recent emergence of long-read sequencing technologies has enabled substantial improvements in accuracy and reduced computational costs. Nonetheless, pairwise sequence alignment remains a time-consuming step in common bioinformatics pipelines, becoming a bottleneck in de novo whole-genome assembly. Speeding up this step requires heuristics and the development of memory-frugal and efficient implementations. A promising candidate for all of the above is Myers’ algorithm. However, the state-of-the-art implementations face scalability challenges when dealing with longer reads and large datasets. To address these challenges, we propose SeqMatcher , a fast and memory-frugal genomics sequence aligner. By leveraging the long registers of AVX-512, SeqMatcher reduces the data movement and memory footprint. In a comprehensive performance evaluation, SeqMatcher achieves speedups of up to 12.32x for the unbanded version and 26.70x for the banded version compared to the non-vectorized implementation, along with energy footprint reductions of up to 2.59x. It also outperforms state-of-the-art implementations by factors of up to 29.21x, 17.56x, 13.47x, 9.12x, and 8.81x compared to Edlib , WFA2-lib , SeqAn , BSAlign , and QuickEd , while improving energy consumption with reductions of up to 6.78x.

The Journal of SupercomputingVol. 81(1)
Universidad de Málaga (ES)
Universidad de Málaga, Smithsonian Conservation Biology Institute
Affordable and clean energy
Openalex Percentile: Top 33%
Genomics and Phylogenetic Studies
0.47
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