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oai:riuma.uma.es:10630/362022026-02-03T10:57:27Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Espinosa, Elena author Quislant-del-Barrio, Ricardo author Larrosa-Jiménez, Rafael author Plata-González, Óscar Guillermo author 2024-12 The recent emergence of long-read sequencing technologies has enabled substan- tial improvements in accuracy and reduced computational costs. Nonetheless, pair- wise sequence alignment remains a time-consuming step in common bioinformat- ics 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 deal- ing 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 speed- ups 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 reduc- tions 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 reduc- tions of up to 6.78x Espinosa, E., Quislant, R., Larrosa, R. et al. SeqMatcher: efficient genome sequence matching with AVX-512 extensions. J Supercomput 81, 355 (2025). https://doi.org/10.1007/s11227-024-06789-0 https://hdl.handle.net/10630/36202 10.1007/s11227-024-06789-0 Algoritmos computacionales Arquitectura de ordenadores SeqMatcher: efficient genome sequence matching with AVX-512 extensions