A Review on GPU Accelerated Bioinformatics Tool

Subrata Sinha, Abinash Hazarika, Gopal C Hazarika


Traditional computational methods and software tools developed in the research fields of Bioinformatics, Computational Biology and Systems Biology have a common property which is that they are 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 worldwide, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. The latest generation of graphics processing units (GPUs) has democratized the use of HPC also as they push desktop computers to cluster level performance. In this review work, we present a collection of GPU enhanced bioinformatics tools developed recently in the past two to three decades to perform computational analysis in various life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures.


Bioinformatics GPU (Graphical Processing Unit) HPC (High Performance Computing) CPU (Central Processing Unit) CUDA computational biology systems biology

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Sinha 2020


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