Intel MIC在生物信息学中的应用趋势

Xinyi Wang, Cangshuai Wu, Zhen Huang
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引用次数: 0

摘要

随着新一代测序技术的快速发展,不断增加的生物序列数据对数据处理提出了巨大的挑战。因此,迫切需要强大的计算能力来加快数据分析过程。在最先进的并行加速器中,Intel Xeon Phi协处理器是一款基于Intel多集成核心(MIC)架构的可启动主机处理器,提供大规模并行性和矢量化,以支持最苛刻的高性能计算(HPC)应用。底层x86架构支持常见的并行编程标准库,这些标准库提供了将现有代码移植到异构计算环境的熟悉性和灵活性。此外,它还提供了三种使用模型,包括本机模型、卸载模型和对称模型,以解决基于mic的新异构体系结构上的不同应用问题。目前,Intel Xeon Phi正在成为一个通用的并行计算平台,用于降低生物信息学中最苛刻过程的计算成本。为了帮助研究人员更好地利用MIC,本文综述了基于MIC的生物信息学应用,为生物信息学研究人员在各自领域应用MIC提供了综合指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trends of Intel MIC Application In Bioinformatics
With the rapid development of next-generation sequencing (NGS) technology, the ever-increasing biological sequence data poses a tremendous challenge to data processing. Therefore, there is an urgent need for intensive computing power to speed up the data analysis process. Among the state-of-the-art parallel accelerators, Intel Xeon Phi coprocessor is a bootable host processor based on Intel Many Integrated Core (MIC) architecture that provides massive parallelism and vectorization to support the most demanding high-performance computing (HPC) applications. The underlying x86 architecture supports common parallel programming standard libraries that provide familiarity and flexibility to transplant existing code to heterogeneous computing environments. In addition, it delivers three usage model including native, offload and symmetric models to solve different application problems on the MIC-based neo-heterogeneous architectures. Currently, Intel Xeon Phi is becoming a common parallel computing platform for decreasing the computational cost of the most demanding processes in bioinformatics. To help researchers make better use of MIC, we reviewed the MIC-based bioinformatics applications, providing a comprehensive guideline for bioinformatics researchers to apply MIC in their own fields.
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