2026-06-06T04:35:50Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/357132026-02-03T11:23:26Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Gálvez-Rojas, Sergio
author
Federico, Agostini
author
Caselli, Javier
author
Hernández, Pilar
author
Dorado, Gabriel
2024-12-17T11:23:34Z
2024-12-17T11:23:34Z
2021-02-02
Gálvez S, Agostini F, Caselli J, Hernandez P and Dorado G (2021) BLVector: Fast BLAST-Like Algorithm for Manycore CPU With Vectorization. Front. Genet. 12:618659. doi: 10.3389/fgene.2021.618659
https://hdl.handle.net/10630/35713
10.3389/fgene.2021.618659
New High-Performance Computing architectures have been recently developed for commercial central processing unit (CPU). Yet, that has not improved the execution time of widely used bioinformatics applications, like BLAST+. This is due to a lack of optimization between the bases of the existing algorithms and the internals of the hardware that allows taking full advantage of the available CPU cores. To optimize the new architectures, algorithms must be revised and redesigned; usually rewritten from scratch. BLVector adapts the high-level concepts of BLAST+ to the x86 architectures with AVX-512, to harness their capabilities. A deep comprehensive study has been carried out to optimize the approach, with a significant reduction in time execution. BLVector reduces the execution time of BLAST+ when aligning up to mid-size protein sequences (∼750 amino acids). The gain in real scenario cases is 3.2-fold. When applied to longer proteins, BLVector consumes more time than BLAST+, but retrieves a much larger set of results. BLVector and BLAST+ are fine-tuned heuristics. Therefore, the relevant results returned by both are the same, although they behave differently specially when performing alignments with low scores. Hence, they can be considered complementary bioinformatics tools.
eng
Atribución 4.0 Internacional
Hardware
Arquitectura de ordenadores
BLVector: Fast BLAST-Like Algorithm for Manycore CPU With Vectorization
journal article
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URL
https://riuma.uma.es/bitstreams/f9dccdc5-56b7-408d-8d29-5d21c1260222/download
File
MD5
5ed006e1fd4c72fa51433b72bbc2f754
4273373
application/pdf
fgene-12-618659.pdf