A hybrid CPU-GPU implementation to accelerate multiple pairwise protein sequence alignment

Bioinformatics is an interdisciplinary field that applies techniques from computer science, statistics and engineering to guide in the study of large biological data. Protein structure and sequence analysis is very important in bioinformatics mainly in understanding cellular processes which helps in simplifying the development of drugs for metabolic pathways. Protein sequence alignment is a technique that is concerned with identifying the similarities among different protein structures in order to discover the relationships among them. These kinds of techniques are computationally extensive which hinders their applicability. In this paper, we propose a parallel approach to speed up the computational time of two sequence alignment algorithms using a hybrid implementation that combines the power of multicore CPUs and that of contemporary GPUs. Our study shows that the hybrid approach solves the problem much faster than its sequential counterpart.