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

Jesús Pérez Serrano, Edans Flavius De Oliveira Sandes, Alba Cristina Magalhaes Alves de Melo, Manuel Ujaldón
2017 Lecture Notes in Computer Science  
We present a performance per watt analysis of CUDAlign 4.0, a parallel strategy to obtain the optimal alignment of huge DNA sequences 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 scenarios to maximize acceleration and minimize power consumption. Experimental results using CUDA on a set of GeForce GTX 980 GPUs illustrate their capabilities as
more » ... erformance 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.
doi:10.1007/978-3-319-56154-7_46 fatcat:q4mfjtje4nehpc67yvmn7w47jy