Performance-Based Analogising of Needleman Wunsch Algorithm to Align DNA Sequences Using GPU and FPGA

This paper presents a performance-based approach to the Needleman-Wunsch algorithm of global sequence alignment. Sequence comparison lies at the heart of the bioinformatics, which describes the way of arrangement of DNA, RNA or protein sequences, to identify the regions of similarity among them. We compare the execution time of sequential CPU-based implementation with parallel GPU-based implementation using CUDA-C and hardware-based implementation using FPGA. Both the approaches were far more improved over the sequential CPU-based implementation.