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用于分子动力学模拟的百亿亿次级高性能计算方法。新冠疫情研究:一个应用案例。

Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case.

作者信息

Wieczór Miłosz, Genna Vito, Aranda Juan, Badia Rosa M, Gelpí Josep Lluís, Gapsys Vytautas, de Groot Bert L, Lindahl Erik, Municoy Martí, Hospital Adam, Orozco Modesto

机构信息

Institute for Research in Biomedicine (IRB Barcelona). The Barcelona Institute of Science and Technology Barcelona Spain.

Department of Physical Chemistry Gdansk University of Technology Gdańsk Poland.

出版信息

Wiley Interdiscip Rev Comput Mol Sci. 2022 May 30:e1622. doi: 10.1002/wcms.1622.

Abstract

Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics. This article is categorized under:Data Science > Computer Algorithms and ProgrammingData Science > Databases and Expert SystemsMolecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods.

摘要

百亿亿次计算长久以来一直是个梦想,如今已接近成为现实,这将影响分子模拟的执行方式,以及由此获得的信息的数量和质量。我们回顾了生物分子模拟领域如何期待这些新架构,重点介绍了高性能计算卓越中心BioExcel中心各团队的近期工作。我们以高性能计算模拟社区为抗击新冠疫情所做的工作为例,展示了这些模拟策略的强大力量。本文分类如下:数据科学>计算机算法与编程;数据科学>数据库与专家系统;分子与统计力学>分子动力学与蒙特卡罗方法。

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