Ongoing Solution Reproducibility of Earth System Models as They Progress Toward Exascale Computing

TitleOngoing Solution Reproducibility of Earth System Models as They Progress Toward Exascale Computing
Publication TypeJournal Article
Year of Publication2019
JournalThe International Journal of High Performance Computing Applications
Pages109434201983734
Date Published03/2019
Abstract / Summary

We present a methodology for solution reproducibility for the Energy Exascale Earth System Model (E3SM) during its ongoing software infrastructure development to prepare for exascale computers. The non-linear chaotic nature of climate system simulations precludes traditional model verification approaches since machine precision differences - resulting from code refactoring, changes in a software environment, etc. - 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 (baseline 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.

URLhttp://dx.doi.org/10.1177/1094342019837341
DOI10.1177/1094342019837341
Journal: The International Journal of High Performance Computing Applications
Year of Publication: 2019
Pages: 109434201983734
Date Published: 03/2019

We present a methodology for solution reproducibility for the Energy Exascale Earth System Model (E3SM) during its ongoing software infrastructure development to prepare for exascale computers. The non-linear chaotic nature of climate system simulations precludes traditional model verification approaches since machine precision differences - resulting from code refactoring, changes in a software environment, etc. - 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 (baseline 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.

DOI: 10.1177/1094342019837341
Citation:
Mahajan, S, K Evans, J Kennedy, M Xu, M Norman, and M Branstetter.  2019.  "Ongoing Solution Reproducibility of Earth System Models as They Progress Toward Exascale Computing."  The International Journal of High Performance Computing Applications 109434201983734.  https://doi.org/10.1177/1094342019837341.