GPU Accelerated Approaches for Efficient Simulation of Functional Bioinformatics Systems

Abstract

Heavy reliance on bioinformatics systems, a field that involves extensive interactions
between proteins, gene regulation systems, and metabolism, has led to the creation of high
performance computational systems. Classical CPU based simulations tend to be scalable and
efficient particularly in cases of large datasets or to conduct sequences of analysis. It examines the
application of the use of accelerated computing in a graphics card (GPU) to simulate functional
bioinformatics systems with spec ial emphasis on parallel algorithms and optimised computational
pipelines. We find that with the help of GPU based simulations, calculation time can be greatly
decreased without loss in its accuracy and allow us to analyze complex biological processes in r eal
time. Best practices on how to use GPU architectures in bioinformatics research are also brought out
in the study.