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003 AR-LpUFIB
005 20250311170453.0
008 230201s2018 xx o 000 0 eng d
024 8 _aDIF-M7779
_b7996
_zDIF007108
040 _aAR-LpUFIB
_bspa
_cAR-LpUFIB
100 1 _aRucci, Enzo
245 1 0 _aSWIFOLD :
_bSmith-Waterman implementation on FPGA with OpenCL for long DNA sequences
300 _a1 archivo (764,0 kB)
500 _aFormato de archivo PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca)
520 _aBackground The Smith-Waterman (SW) algorithm is the best choice for searching similar regions between two DNA or protein sequences. However, it may become impracticable in some contexts due to its high computational demands. Consequently, the computer science community has focused on the use of modern parallel architectures such as Graphics Processing Units (GPUs), Xeon Phi accelerators and Field Programmable Gate Arrays (FGPAs) to speed up large-scale workloads. Results This paper presents and evaluates SWIFOLD: a Smith-Waterman parallel Implementation on FPGA with OpenCL for Long DNA sequences. First, we evaluate its performance and resource usage for different kernel configurations. Next, we carry out a performance comparison between our tool and other state-of-the-art implementations considering three different datasets. SWIFOLD offers the best average performance for small and medium test sets, achieving a performance that is independent of input size and sequence similarity. In addition, SWIFOLD provides competitive performance rates in comparison with GPU-based implementations on the latest GPU generation for the large dataset. Conclusions The results suggest that SWIFOLD can be a serious contender for accelerating the SW alignment of DNA sequences of unrestricted size in an affordable way reaching on average 125 GCUPS and almost a peak of 270 GCUPS.
534 _aBMC Systems Biology, 12(S5), pp. 44-131.
650 4 _aCOMPUTACIÓN DE ALTO RENDIMIENTO - HPC
653 _aADN
653 _aSmith-Waterman
700 1 _aGarcía, Carlos Diego
700 1 _aBotella, Guillermo
700 1 _aDe Giusti, Armando Eduardo
700 1 _aNaiouf, Ricardo Marcelo
700 1 _aPrieto-Matias, Manuel
856 4 0 _uhttps://doi.org/10.1186/s12918-018-0614-6
942 _cCP
999 _c56883
_d56883