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DNA Sequences Alignment in Multi-GPUs: Energy Payoff on Speculative Executions
dc.contributor.author | Pérez-Serrano, Jesús | |
dc.contributor.author | Sandes, Edans | |
dc.contributor.author | Melo, Alba | |
dc.contributor.author | Ujaldon-Martínez, Manuel | |
dc.date.accessioned | 2017-05-30T12:41:30Z | |
dc.date.available | 2017-05-30T12:41:30Z | |
dc.date.created | 2017 | |
dc.date.issued | 2017-05-30 | |
dc.identifier.uri | http://hdl.handle.net/10630/13777 | |
dc.description.abstract | 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. | es_ES |
dc.description.sponsorship | Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech | es_ES |
dc.language.iso | eng | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.subject | Ácido desoxirribonucleico | es_ES |
dc.subject.other | GPGPU | es_ES |
dc.subject.other | CUDA | es_ES |
dc.subject.other | DNA Sequence Alignment | es_ES |
dc.title | DNA Sequences Alignment in Multi-GPUs: Energy Payoff on Speculative Executions | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.centro | E.T.S.I. Informática | es_ES |
dc.relation.eventtitle | Graphics Technology Conference (GTC) 2017 | es_ES |
dc.relation.eventplace | San José (California), Estados Unidos | es_ES |
dc.relation.eventdate | Mayo de 2017 | es_ES |
dc.cclicense | by-nc-nd | es_ES |