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首页> 外文期刊>Geoscientific Model Development Discussions >A new end-to-end workflow for the Community Earth System Model (version 2.0) for the Coupled Model Intercomparison Project Phase 6 (CMIP6)
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A new end-to-end workflow for the Community Earth System Model (version 2.0) for the Coupled Model Intercomparison Project Phase 6 (CMIP6)

机译:用于耦合型号的社区地球系统模型(版本2.0)的新的端到端工作流程为耦合型号互通项目6(CMIP6)

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The complexity of each Coupled Model Intercomparison Project grows with every new generation. The Phase?5 effort saw a dramatic increase in the number of experiments that were performed and the number of variables that were requested compared to its previous generation, Phase?3. The large increase in data volume stressed the resources of several centers including at the National Center for Atmospheric Research. During Phase?5, we missed several deadlines and we struggled to get the data out to the community for analysis. In preparation for the current generation, Phase?6, we examined the weaknesses in our workflow and addressed the performance issues with new software tools. Through this investment, we were able to publish approximately 565TB of compressed data to the community, with another 30TB yet to be published. When compared to the volumes we produced in the previous generation, 165TB of uncompressed data, we were able to provide 6 times the amount of data and we accomplish this within one-third of the time. This provided us with an approximate 18 times faster speedup. While this paper discusses the improvements we have made to our own workflow for the Coupled Model Intercomparison Project Phase?6 (CMIP6), we hope to encourage other centers to evaluate and invest in their own workflows in order to be successful in these types of modeling campaigns.
机译:每个耦合模型的复杂性与每一代新一代都会增长。阶段Δ5努力在执行的实验数量和与之前的一代相比的相比所要求的变量的数量中看到了显着增加。数据量大增加强调了几个中心的资源,包括国家大气研究中心。在阶段?5期间,我们错过了几个截止日期,我们努力将数据达到社区进行分析。为准备当前一代,阶段?6,我们检查了工作流程中的弱点,并通过新的软件工具解决了性能问题。通过这项投资,我们能够向社区发布大约565TB的压缩数据,另外30TB尚未发布。与我们在上一代中生产的卷相比,165TB的未压缩数据时,我们能够提供数据量的6倍,我们在三分之一的时间内完成这一点。这为我们提供了近似的18倍的加速。虽然本文讨论了我们对耦合模型交流项目阶段的改进,但我们希望鼓励其他中心来评估和投资自己的工作流程,以便在这些类型的建模中取得成功竞选活动。

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