Ongoing solution reproducibility of earth system models as they progress toward exascale computing

Salil Mahajan, Katherine J. Evans, Joseph H. Kennedy, Min Xu, Mathew R. Norman, Marcia L. Branstetter

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

We present a methodology for solution reproducibility for the Energy Exascale Earth System Model during its ongoing software infrastructure development to prepare for exascale computers. The nonlinear chaotic nature of climate system simulations precludes traditional model verification approaches since machine precision differences—resulting from code refactoring, changes in software environment, and so on—grow exponentially to a different weather state. Here, we leverage the nature of climate as a statistical description of the atmosphere in order to establish model reproducibility. We evaluate the degree to which two-sample equality of distribution tests can confidently detect the change in climate from minor tuning parameter changes on model output variables in order to establish the level of difference that indicates a new climate. To apply this (baselined test), we target a section of the model’s development cycle wherein no intentional science changes have been applied to its source code. We compare an ensemble of short simulations that were conducted using a verified model configuration against a new ensemble with the same configuration but with the latest software infrastructure (Common Infrastructure for Modeling the Earth, CIME5.0), compiler versions, and software libraries. We also compare these against ensemble simulations conducted using the original version of the software infrastructure (CIME4.0) of the earlier model configuration, but with the latest compilers and software libraries, to test the impact of new compilers and libraries in isolation from additional software infrastructure. The two-sample equality of distribution tests indicates that these ensembles indeed represent the same climate.

Original languageEnglish
Pages (from-to)784-790
Number of pages7
JournalInternational Journal of High Performance Computing Applications
Volume33
Issue number5
DOIs
StatePublished - Sep 1 2019

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported as part of the E3SM project, by the U.S. DOE, Office of Science, Office of Biological and Environmental Research. This manuscript has been authored by UT-Battelle, LLC and used resources of the National Center for Computational Sciences at Oak Ridge National Laboratory, both of which are supported by the Office of Science of the U.S. DOE under contract no DE-AC05-00OR22725.

FundersFunder number
Office of Biological and Environmental Research
U.S. DOE
U.S. Department of EnergyDE-AC05-00OR22725
Office of Science
Oak Ridge National Laboratory

    Keywords

    • Earth system models
    • climate reproducibility
    • exascale computing
    • short ensembles

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