Performance evaluation of SW algorithm on NVIDIA geforce GTX TITAN X graphic processing unit (GPU)

Abstract

Nowadays, the requirement for high performance and sensitive alignment tools have increased after the advantage of the Deoxyribonucleic Acid (DNA) and molecular biology has been figured out through Bioinformatics study. Therefore, this paper reports the performance evaluation of parallel Smith-Waterman Algorithm implementation on the new NVIDIA GeForce GTX Titan X Graphic Processing Unit (GPU) compared to the Central Processing Unit (CPU) running on Intel® CoreTM i5-4440S CPU 2.80GHz. Both of the design were developed using C-programming language and targeted to the respective platform. The code for GPU was developed and compiled using NVIDIA Compute Unified Device Architecture (CUDA). It clearly recorded that, the performance of GPU based computational is better compared to the CPU based. These results indicate that the GPU based DNA sequence alignment has a better speed in accelerating the computational process of DNA sequence alignment.