DNA sequences alignment in multi-GPUs: acceleration and energy payoff

We present a performance per watt analysis of CUDAlign 4.0, a parallel strategy to obtain the optimal pairwise alignment of huge DNA sequences in multi-GPU platforms using the exact Smith-Waterman method. Our study includes acceleration factors, performance, scalability, power efficiency and energy...

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Bibliographic Details
Published in:	BMC bioinformatics Vol. 19; no. Suppl 14; p. 421
Main Authors:	Pérez-Serrano, Jesús, Sandes, Edans, Magalhaes Alves de Melo, Alba Cristina, Ujaldón, Manuel
Format:	Journal Article
Language:	English
Published:	England BioMed Central 20-11-2018 BMC
Subjects:	Acceleration Algorithms Alignment Amino acids Animals Base Sequence Bioinformatics Computer Graphics Cost control CUDA Deoxyribonucleic acid DNA DNA sequences alignment Electric Power Supplies Electronic devices Energy Energy conservation Energy consumption Energy costs Energy usage Gene sequencing Genomes GPGPU HPC Humans Monkeys & apes Nucleotide sequence Pan troglodytes - genetics Power Power efficiency Proteins Researchers Sequence Alignment Supercomputers Time Factors CUDA HPC Power efficiency GPGPU DNA sequences alignment
Online Access:	Get full text
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