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

机译:混合CPU-GPU实现可加速多个成对蛋白质序列比对

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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.
机译:生物信息学是一个跨学科领域,应用计算机科学,统计学和工程学中的技术来指导大型生物数据的研究。蛋白质结构和序列分析在生物信息学中非常重要,主要在于了解细胞过程,这有助于简化用于代谢途径的药物的开发。蛋白质序列比对是一种与鉴定不同蛋白质结构之间的相似性以发现它们之间的关系有关的技术。这些类型的技术在计算上是广泛的,这妨碍了它们的适用性。在本文中,我们提出了一种并行方法,该方法使用混合实现来加快两种序列比对算法的计算时间,该实现结合了多核CPU和现代GPU的功能。我们的研究表明,混合方法比顺序方法解决问题的速度快得多。

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