Abstract
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.
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Notes
- 1.
Environmental NR: ftp://ftp.ncbi.nih.gov/blast/db/FASTA/env_nr.gz.
- 2.
Swiss-Prot: http://web.expasy.org/docs/swiss-prot_guideline.html.
- 3.
SSE4.1 and AVX2 versions using QP technique were excluded from the analysis to improve figure readability since we found that SP scheme always achieved the best performance, as in previous work [13].
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Acknowledgments
This work has been partially supported by Spanish government through research contract TIN2015-65277-R and CAPAP-H6 network (TIN2016-81840-REDT).
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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: Ibrahim, S., Choo, KK., Yan, Z., Pedrycz, W. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2017. Lecture Notes in Computer Science(), vol 10393. Springer, Cham. https://doi.org/10.1007/978-3-319-65482-9_42
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