The well-known Smith-Waterman (SW) algorithm is the most commonly used method for local sequence alignments. However, SW is very computationally demanding for large protein databases. There are several implementations that take advantage of parallel capacities on many-cores, FPGAs or GPUs, in order to increase the alignment throughtput. In this paper, we have explored SW acceleration on Intel KNL processor. The novelty of this architecture requires the revision of previous programming and optimization techniques on many-core architectures. To the best of authors knowledge, this is the first KNL architecture assessment for SW algorithm. Our evaluation, using the renowned Environmental NR database as benchmark, has shown that multi-threading and SIMD exploitation showed competitive performance (351 GCUPS) in comparison with other implementations.
CITATION STYLE
Rucci, E., Garcia, C., Botella, G., De Giusti, A., Naiouf, M., & Prieto-Matias, M. (2017). First experiences accelerating Smith-Waterman on intel’s knights landing processor. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10393 LNCS, pp. 569–579). Springer Verlag. https://doi.org/10.1007/978-3-319-65482-9_42
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