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Smith-Waterman Acceleration in Multi-GPUs: A Performance per Watt Analysis

Jesus Perez Serrano, Edans Flavius De Oliveira Sandes, Alba Cristina Magalhaes Alves de Melo, Manuel Ujaldon
Computer Architecture Department, University of Malaga, Spain
5th Intl. Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO’17), 2017

@article{perez2017smith,

   title={Smith-Waterman Acceleration in Multi-GPUs: A Performance per Watt Analysis},

   author={P{‘e}rez-Serrano, Jes{‘u}s and Sandes, Edans and Melo, Alba and Ujald{‘o}n, Manuel},

   year={2017},

   publisher={Springer}

}

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We present a performance per watt analysis of CUDAlign 4.0, a parallel strategy to obtain the optimal alignment of huge DNA se- quences in multi-GPU platforms using the exact Smith-Waterman method. Speed-up factors and energy consumption are monitored on different stages of the algorithm with the goal of identifying advantageous sce- narios to maximize acceleration and minimize power consumption. Ex- perimental results using CUDA on a set of GeForce GTX 980 GPUs illustrate their capabilities as high-performance and low-power devices, with a energy cost to be more attractive when increasing the number of GPUs. Overall, our results demonstrate a good correlation between the performance attained and the extra energy required, even in scenarios where multi-GPUs do not show great scalability.
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