G8 Initiative: Collaborative Research: ECS: Enabling Climate Simulation at Extreme Scale

该NSF奖授予伊利诺伊大学厄巴纳-香槟分校和田纳西大学诺克斯维尔分校，资助美国研究人员参与一个由G8研究理事会倡议通过面向全球规模问题的亿级计算应用软件跨学科计划进行多边研究的项目。这是美国国家科学基金会、加拿大国家科学与工程研究委员会(NSERC)、法国国家科学与工程研究委员会(ANR)、德国科学促进会(DFG)、日本科学促进会(JSPS)、俄罗斯基础研究基金会(RFBR)和英国研究委员会(RC-UK)之间的试点合作。这个跨六个国家的跨学科项目专注于三个研究主题，这些研究主题旨在解决物理数值建模方面的限制，这些研究项目是在竞争基础上选出的，由至少三个合作伙伴国家的研究人员组成。化学和生物学使用NCAR共同体地球系统模型版本1(CESM1)和其他国家使用的类似代码。这些研究主题包括处理弹性、节点级优化和系统级可伸缩性的新方法。这项研究将使可伸缩性更强的模型组合的开发成为可能。这将有助于更好地评估气候敏感性和气候反馈过程，更好地量化模型的不确定性，并更好地了解自然变化的影响。该项目将提供基本知识，以扩大艾级气候代码，从而减少当前气候演变的不确定性；它将促进计算机科学家和气候科学家之间的互动；将促进气候模拟和艾级计算领域的国际合作；并将培养了解气候模拟和高性能计算应用领域的新一代研究人员

This NSF award to the University of Illinois at Urbana-Champaign and the University of Tennessee at Knoxville funds U.S. researchers participating in a project competitively selected by the G8 Research Councils Initiative on Multilateral Research through the Interdisciplinary Program on Application Software towards Exascale Computing for Global Scale Issues. This is a pilot collaboration among the U.S. National Science Foundation, the Canadian National Sciences and Engineering Research Council (NSERC), the French Agence Nationale de la Recherche (ANR), the German Deutsche Forschungsgemeinschaft (DFG), the Japan Society for the Promotion of Science (JSPS), the Russian Foundation for Basic Research (RFBR),and the United Kingdom Research Councils (RC-UK), supporting collaborative research projects selected on a competitive basis that are comprised of researchers from at least three of the partner countries.This interdisciplinary project across six countries focuses on three research topics that address limitations in numerical modeling of physics, chemistry and biology with the NCAR Community Earth System Model Version 1 (CESM1) and similar codes used by other countries. These research topics include new approaches to handle resilience, node level optimization and system level scalability. This research will enable the development of more scalable model ensembles. These will allow better evaluation of climate sensitivity and climate feedback processes, a better quantification of model uncertainty and a better understanding of the effects of natural variability.The project will provide essential knowledge toward scaling climate codes for exascale and thus reducing current uncertainties on climate evolution; it will foster interactions between computer scientists and climate scientists; will foster international collaborations in the area of climate simulations and exascale computing; and will educate a new generation of researchers that understand both the application domain of climate simulation and high-performance computing