Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2017 Sep 1;18(5):870-885.
doi: 10.1093/bib/bbw058.

Graphics processing units in bioinformatics, computational biology and systems biology

Marco S Nobile, Paolo Cazzaniga, Andrea Tangherloni, Daniela Besozzi
Review

Graphics processing units in bioinformatics, computational biology and systems biology

Marco S Nobile et al. Brief Bioinform. .

Abstract

Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools.

Keywords: CUDA; bioinformatics; computational biology; graphics processing units; high-performance computing; systems biology.

PubMed Disclaimer

Figures

Figure 1
Figure 1
With the advances in the manufacturing processes, the architectural features of both CPUs (red dots) and GPUs (green squares) continuously improve. This figure shows the trends for both architectures by comparing the following characteristics: (A) the performances in terms of GFLOPS when performing double precision floating point operations; (B) the power consumption; (C) the GPWR; (D) the number of cores per unit; (E) the core working frequencies. The GPUs considered in this figure are reported in Supplementary File 3, while the CPUs are the Intel Core i7 processors released in the same years (namely, from the Westmere up to the Haswell microarchitectures). A colour version of this figure is available at BIB online: https://academic.oup.com/bib.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Rapaport DC. The Art of Molecular Dynamics Simulation. Cambridge: Cambridge University Press, 2004.
    1. Haile JM. Molecular Dynamics Simulation: Elementary Methods. New York: Wiley, 1997.
    1. He M, Petoukhov S.. Mathematics of Bioinformatics: Theory, Methods and Applications. Hoboken, NJ: John Wiley & Sons, 2011.
    1. Alberghina L, Westerhoff HV.. Systems Biology: Definitions and Perspectives, Vol. 13 of Topics in Current Genetics. Berlin, Germany: Springer-Verlag, 2005.
    1. Karr JR, Sanghvi JC, Macklin DN, et al.A whole-cell computational model predicts phenotype from genotype. Cell 2012;150(2):389–401. - PMC - PubMed
-